Human Interaction, Emerging Technologies and Future Systems V

Trust and autonomous systems, especially weapon systems, could be the most difficult technological challenge facing defense industries, militaries, politicians, and the public because the algorithms have to be trusted. Furthermore, the operator, the military, defense industry, politicians and the public need to trust the system to also follow ethical and legal rules. This paper briefly describes the trust considerations, concerns and constraints regarding autonomous weapons systems and concludes with a brief description of the current development programs and projects by the various US military services.

The proposed approach can filter, study, analyze, and interpret written communications from social media platforms for early detection of Cognitive Impairment (CI) to connect individuals with CI with assistive services in their location. It has three novel functionalities. First, it presents a Big Data-centric Data Mining methodology that uses a host of Natural Language Processing and Information Retrieval approaches to filter and analyze tweets to detect if the tweets were made by a user with some form of CI – for instance, Dementia. Second, it consists of a string-matching functionality that uses the Levenshtein distance algorithm and Fuzzy matching to score tweets indicating the degree of CI. Finally, the framework consists of a text mining approach for detecting the geolocation of the Twitter user so that, if the user is cognitively impaired, caregivers in that area could be alerted and connected to them to facilitate early-stage care, services, therapies, or treatment.

The mutual awareness and availability across team members is essential for effective and efficient cooperation. Yet, interruptions in general and interruptions unrelated to the current domain and task in particular can lead to disturbing disruption. The literature on boundary management has great insight to offer with respect to organising and maintaining a balance between different life domains. In this paper we introduce a formal model of the semantic structure of life domains, grounded in the concept of integration and segmentation found in boundary theory. This formal model is based on simple set theory and relations. It is system unrelated but serves as a starting point for creating further implementation specific models in UML or other notations during the development process.

Human-technology combination is normally conceptualized on a bi-polar dimension from no technical autonomy to full technical autonomy, and consequently from full human control to no human control. This paper presents an alternative scale for describing levels of human-technology teaming. It assumes complementarity of humans and technology. Humans and technology are considered to remain qualitatively different in spite of new technical capabilities. When combined smartly, they are able to mutually compensate for weaknesses and to mutually reinforce strengths. On the proposed scale, both full human control as well as full technical autonomy are on the lowest level, as there is no teaming at all. Higher levels represent an increasing intensity of teaming ranging from (i) technology informs the human, via (ii) human and technology influence each other to (iii) true human-technology collaboration that allows for shared control. These levels are described and substantiated in the paper.

In this study, we found effective facial expressions with the minimal elements required to identify someone's emotion. One circle for each eye and one for the mouth makes triangular facial expressions. In all the preceding studies, facial expressions have only used visual details that had been shown in three dimensions, with the mouth being stretched wide, the face tilted, and the eyes slanted. As well as previously discovered in affective studies, the correlations between visual input and outcomes have correlated. We discovered that people exhibit ten expressions of feeling, which are (I) happy, (II) angry, (III) sad, (IV) disgust, (V) fear, (VI) surprised, (VII) angry*, (VIII) fear*, (IX) neutral pleasant (positive), and (X) neutral unpleasant (negative). Mathematical transformations transmitted the feelings. Cultural variations are also noted in face expressions described in the article.

This exploratory study examines the white-collar worker perception of the three most common game elements in learning Level, Points and Badges applied in online training. Through surveys and interviews, the study reveals that the perception of the gamified course design was engaging. The game elements Levels and Badges were considered positive, while Points was viewed as indifferent. The study also detects that respondents in both the surveys and interviews had not noticed parts of the gamification design, making them negative towards the gamified course due to lack of coherence in the design. The authors of the paper suggest that further studies should address multimodal feedback, juiciness, and gamification to disclose which type of feedback is paramount in various gamified situations.

Chemistry teaching requires active methodologies that involve students in carrying out activities that generate critical thinking. The Escape Rooms is a micro gamification strategy where the student escapes from the traditional classroom. In this room the student must find keys, do puzzles, investigate, solve riddles and obtain combinations or objects. The goal of this study focuses on proposing Escape Rooms to strengthen high school chemistry teaching. The proposal contains activities designed by the teacher, which will be solved by students in a certain time using technological resources. To implement this work, a baseline was drawn up through an interview with three teachers from Chemistry area; as well as a 178 student’s survey. As a result of the exploratory research, the need for teachers and students to implement playful methodologies is evidenced, this would allow inferring that Escape Rooms is a novel and attractive strategy for teaching chemistry.

This study aims to find out how the Indonesian Ministry of Health disseminates information about COVID-19 in Indonesia using the Twitter account @KemenkesRI. This research uses descriptive qualitative research. Data analysis using NVivo 12 Plus software, data retrieval via the Ministry of Health’s Twitter account via NCapture from NVivo 12 Plus with Web Chrome. The data is processed with the cross tab feature to automatically calculate the required main statistical tests with meaningful comparisons and analysis of indirect variables. The Crosstab Query feature is to enter code (manual, generated, etc.), text data, and numeric data in variables and pattern data. At this stage, an automatic calculation is found between all data related to the dissemination of COVID-19 information. Furthermore, using the Word Cloud feature, words that often appear in data searches or display terms are discussed. and the last one is looking for a cluster related to the @KemenkesRI account. This research reveals the Indonesian Ministry of Health’s tweet regarding COVID-19 on their Twitter account. The findings also include updating of COVID-19 data, health protocols, vaccinations and adaptation of public policies. In these four indicators, there are 363 tweets about vaccination indicators, the second is an indicator about the Covid-19 case data update of 265 tweets, the third is a health protocol indicator with 72 tweets, and the last is an indicator about public policy with 63 tweets.

The COVID-19 pandemic transformed education from face-to-face to virtual. This accelerated the creation of new learning environments based on the everyday use of mobile devices, presenting new challenges for education. Emerging technologies today drive mobile learning or m-learning. This research focuses on the development of a mobile application that seeks to strengthen the mathematical abilities of whole number empowerment in high school students in a blended mode. The application includes four missions that make up an interactive game, in which the player has three lives and accumulates points. Mate-potencia Olympics faces two players, who must meet the challenges of each mission, the winners go to a second round, until they have the winner. Students learn the process of calculating square powers, identifying each of its elements, allowing dynamic, ubiquitous and flexible learning.

Throughout our lives, we are very dependent on the ability to see the “world”. Everyday our eyes capture images that enable us to describe our ideas, our tastes and influence our identity. How we dress up is determined by our personal taste, mainly fed through our own eyesight. Once esthetics are supported by our vision, blind people is limited while performing tasks such as purchasing, selecting and matching outfits. These are considered easy tasks for visually enabled people and difficult tasks for people that cannot see. Therefore, within this scope it has been developed and distributed a survey to all the departments of the Association of the Blind and Amblyopes of Portugal (ACAPO). The survey has two main objectives: to recognize the importance of identifying and combing garments and to assess the needs in the development of clothing identification and combination systems that support blind people.

Online learning is a cost-effective way of promoting social inclusion and enhancing the work-life economy. International employees and higher education students can find that they have limited opportunities to access comprehensive supplemental training opportunities, related to employment, in Finland. Tailored services based on UX design can be beneficial for their supplemental studies. This paper explores key elements identified on the basis of UX design, and how these elements can be utilized to develop effective online learning designs. An innovative case design was implemented in a Finnish firm (with 270 service users) between 2015 and 2019. The key design elements identified relate to types of accessibility, namely pedagogical, lingual, technological and economical. The study explains noticeable improvements in the overall process due to UX design utilization, such as flexibility, cost-effectiveness, user-empathetic solutions and an interactive learning experience. The practical implications of this service include enhancing required competencies and strengthening sustainable work culture.

Cognitive Behavioral Therapy (CBT) is a variety of psychoeducational procedures that allow a variety of disturbances including attention deficit disorder, impulsivity, and hyperactivity to be intervened - ADHD to children essentially in school, improving their abilities and integrating into society with better fitness. Cognitive behavioral therapy is based on continuously observing, analyzing, evaluating and evolving; Meanwhile, ADHD is difficult to detect in children under the age of 6 because the symptoms are similar to the behavior of this age, which makes this combination playful, motivating, constant and modifiable in a school group, i.e. a group of children with an average of three years who have no or no disorder through learning through technology such as a robot, toy, computer or any other instrument with artificial intelligence. This iteration has as pillars the game, quantitative observation, discipline, motivation, simulation and creation of solutions, allowing variables, symptoms or causes to be collected automatically from each and the entire school group, instantly analyzed by the robot or tool with artificial intelligence using algorithms or implemented models that systematize what is quantitatively observed to a diagnosis or clinical picture of each and every one of them at that time while continuing the progressive evaluation of each child during iteration with the school group strengthening their qualities, developing their creativity by reducing their anomaly individually. This iteration of child-home-school - artificial intelligence; in the early years of education facilitates the inclusion of each child who suffers from attention deficit disorder, impulsivity, and hyperactivity.

This study looks for the relationship between social media and the sentiment in COVID-19 vaccine policy in Indonesia spread on Twitter. This study used social media data from Twitter with hashtags related to vaccination program issues. This study used Nvivo 12 to collect data and analyze data with word cloud analysis, matrix analysis, and crosstab analysis. The results showed that the government used Twitter to convey information about the COVID-19 vaccine by 100% pros. The pro-cons opinion mapping on the news is 37.5% for the pro opinion and 62.5% for the cons opinion. The general public opinion showed 21.32% for pro opinions and 77.68% for contra opinions. This study’s limitations were only hashtags and pros and cons.

Cyber-attacks have become a problem at a global level. Awareness of cyber threats has grown in recent years, driven by companies’ growing dependence on data and information systems and a series of major incidents. Maritime transport is the most represented branch of transport in the world and is highly exposed to cyber-attacks due to sophisticated equipment and high usage of information and communication technology. The aim of this research is to examine awareness of Croatian seafarers about cyber threats using a questionnaire. The results of the research show that there is a high level of awareness of cyber threats. However, without a serious full integration of technical and human factors and educated, trained and aware staff, there is no reliable security system, or a system that can withstand security challenges.

During the global anti-epidemiological measures imposed to combat the COVID-19, in July 2020 protests broke out in Bulgaria, caused by a number of corruption scandals in the country. The demand was the resignations of the chief prosecutor of the Republic of Bulgaria and the ruling government and sumonning of early elections for national Parliament. The object of the study is the public unrest against corruption in Bulgaria. The subject is the relationship between digital and real environment through computerization. The research method is analysis. Some of the conclusions are that the protests in Bulgaria ran from the virtual to the real environment and back through social networks and social media and had significant societal impacts.

This paper aims to determine the function and relationship between social media and the dissemination of disaster mitigation information by the National Disaster Relief Agency. The method used in this research is Q-DAS (Qualitative Data Analysis Software) Nvivo 12 plus. Stages of data analysis with Nvivo 12 plus captured data, data import, data coding, data classification, and data display. This study’s findings reveal that the National Disaster Relief Agency has made various efforts related to disaster mitigation by conveying the substance of information through the hashtags #bersatulawancovid19 and #infobencanaabnpb, which dominate the trend with a percentage of 47% and 22%.

The purpose of this study is to compare information on COVID-19 mitigation in Indonesia through the Twitter accounts @dinkesJKT and @pikobar_jabar and analyze them using a qualitative descriptive approach. Meanwhile, this research method used the NVivo 12 Plus application to collect data, including word frequency and chemical crosstab. This study’s findings or novelty were the four message variables or mitigation information. They were health protocol call information, COVID-19 vaccination, COVID-19 data, and the PSBB (large-scale social restrictions) policy. Furthermore, the difference or comparison regarding the two Twitter accounts’ contents was the quantity of information provision. The @dinkesJKT account in one year tweeted 1078 posts, and the @pikobar_jabar account had 2,624 Tweets. From this data, Jakarta Province has used Twitter more heavily to provide information on COVID-19 mitigation. The difference in mitigation information from the two Twitter accounts was the dominance of different messages in quantity.

This paper examines social media’s role as a social protest movement and the scattered narrative related to the Presidential Decrees, which opens up opportunities for alcohol investment in Indonesia and understands the narrative content spread on social media. The data was obtained from Twitter with hashtags #tolakinvestasimiras, #rezimperusakmoral, #batalkanperpresmiras. This study used Q-DAS (Qualitative Data Analysis Software) Nvivo 12 Plus. This study’s results reveal that the protest movement carried out through hashtags related to refusal to invest in alcohol is based on disadvantages and increased levels of consumption. It is based on religious rules considering that the majority of Indonesian people are Muslim. Still besides, health, crime rates, and applicable laws also make the basis for refusing alcohol investment. As an alternative to the most influential social movements, social media shows how The social protest movement through this hashtag shows results with removing alcohol investment attachments.

Due to the anonymity of Internet, it has created fertile ground for exacerbating online sellers’ opportunistic behavior. Social academic community’s interest in studying opportunistic behavior is still developing. This study aims to develop a model that depicts a set of mitigating factors (e.g., information consistency and relevancy) on sellers’ opportunistic behavior. A survey was used to collect data from online consumers. The results indicate that fears of seller opportunism mediated the relationship between information consistency and perceived risk. Also, information relevancy moderates the effects of information consistency on fears of seller opportunism. The theoretical and practical implications of this study are discussed.

The COVID-19 pandemic has heightened the need for a better understanding of how service robots (SR) can aid practitioners as well as society. Individuals must not only embrace the robotic environment but also learn how to collaborate with humanoid service robots for collective value creation. Starting with the eminence of humanoid SR in the context of the COVID-19 pandemic, we majorly focus on anthropomorphism and social exclusion. These two key concepts present both opportunities and challenges, being the most eminent areas of research in the quest for understanding society-robot relationships.

The application of ICT development does not occur in administering governance administratively and in political administration in general election techniques. This study aims to elaborate on using information technology in implementing the 2020 Election for governors, regents, mayors in Indonesia, which was held in 270 regions. This research method used a qualitative descriptive method. This study's findings are that the use of SIREKAP has benefits in maintaining the principles of transparency and integrity of election administrators. Using ICT in general elections plays a role in improving the integrity of election administrators and increasing public trust in the election results. The Indonesian General Election Commission (KPU) made innovations through the SIREKAP (Recapitulation Information System) application, a form of transparency in the implementation of vote counting and recapitulation of vote count results which are carried out in stages starting from the TPS level to the Regency/City/Provincial KPU.

This study aims to determine the effect of social media, in this case, Twitter, on social resilience effectiveness during a pandemic and explore the distribution of COVID-19 assistance funds and analyze the effectiveness of implementing government assistance to the community. A qualitative descriptive research method was used with NVivo 12 Plus software. The results showed that Twitter was a transparent medium for organizing social assistance from the Ministry of Social Affairs. From the four indicators, the indicators for the monitoring program were still lacking. There is still a need for improvement in program monitoring while the other indicators are excellent. The effectiveness of social assistance during the pandemic through Twitter is adequate.

The purpose of this research is to look at the Indonesian government’s strategy for economic recovery in the tourism sector due to the severe impact of COVID-19. This study analyzes the Ministry of Tourism’s Twitter account in promoting tourism after the COVID-19 pandemic. The method used in this study was Q-DAS (Qualitative Data Analysis). The software was Nvivo 12 plus. Stages of data analysis with Nvivo 12 plus captured data, data import, data coding, data classification, and data display. The results indicated the role of the Ministry of Tourism’s Twitter account in promoting massive promotion. The Ministry of Tourism has actively promoted tourism in 2021 with various hashtags and community sentiments that are pretty positive in responding to tourism recovery due to the decline in tourism.

The heuristic evaluation is a cost-effective method that identifies usability problems with interfaces and interactive systems. In order to perform it, a set of heuristics must be selected, which can be of two types: generic or domain specific heuristics. Currently, with the dissemination of mobile devices and their applications in people's daily lives, several mobile applications that interact with external equipment have emerged, with particularities in terms of their use. The inexistence of domain-specific heuristics for this field, led us to propose our own set following the methodology proposed by Quiñones et al. to develop usability and UX heuristics for specific domains. This paper presents the application of such methodology to propose a set of heuristics suitable to evaluate mobile applications that interact with external equipment. For this, we have taken into account 3 mobile applications, and integrated 4 experiments, to improve and validate the results.

For neuromorphic processes specified by the behavior of a local neural population (for example, processes induced by a “brain-machine” interface platform of the Neuralink type), we study the solvability of the problem of the existence of a differential realization of these processes in the class of bilinear nonstationary ordinary differential equations of the second order (with delay) in a separable Hilbert space. This formulation belongs to the type of inverse problems for an additive combination of nonstationary linear and bilinear operators of evolutionary equations in an infinite-dimensional Hilbert space. The metalanguage of the theory being developed is the constructions of tensor products of Hilbert spaces, orthocomplemented lattice structures, the functional means of the nonlinear Rayleigh-Ritz operator, and the principle of maximum entropy. It is shown that the property of sublinearity of this operator permits one to obtain conditions for the existence of such differential realizations; concurrently, metric conditions of the continuity of the projectivization of this operator are substantiated with the calculation of the fundamental group of its compact image. This work was financially supported by the Russian Foundation for Basic Research (project no. 19-01-00301).

Many significant changes and shifts in daily human life have occurred in the digital era because of technology, with claims that the newest technology makes life more comfortable and more efficient, increasing quality of life. In particular, the introduction of artificial intelligence (AI) devices that depend on automatic speech recognition (ASR), such as Siri from Apple, Alexa from Amazon, Google Assistant from Google, and others, have led to a digital voice community that is formed by the interaction with those AI devices. Using a critical cognitive approach to the ethics and privacy of that community, this paper integrates various interdisciplinary fields to provide a foundational analysis for a model of cognitive hack in the AI digital voice community. In addition, the paper discusses the strategies of manipulation and deception of a targeted audience.

This paper contributes to the field of Human-Centered Design by introducing a new method for participatory visual analysis of manual assembly processes in factories to identify user requirements for digital assistance systems. The process-oriented, visual method integrates the process, need for information, automation level as well as the worker experiences within the process. With the help of the method, user requirements can be derived, and assistance potential can be identified.

Currently, the burden on the ears is increasing with the increase in the viewing rate of videos due to the new coronavirus. Therefore, the purpose of this study is to reduce the discomfort of video advertisements. For this purpose, we proposed a method to reduce the discomfort by smoothing the volume change, and conducted evaluation experiments on its effectiveness. In the evaluation experiment, 65 kinds of created sounds were presented to 10 subjects, and they were asked to answer their impressions of “discomfort” of the three parts of the presented sounds (music, junction, and advertisement) on a rating scale. As a result of the evaluation experiment, it was found that the use of the proposed type of cheek in the junction part reduced the overall unpleasantness compared to the case where it was not used.

This article presents a literary focusing on accessibility in architectural projects for historic buildings. It is an exploratory study, in which some concepts were raised regarding the area of conservation and restoration to introduce the context in which the patrimonial assets are inserted. With these definitions, the historical trajectory of the exclusion of people with disabilities or mobility difficulties by society and the development of cities was outlined. From this, the work showed the emergence and development of concepts and standards of accessibility and universal design. Then, to present two cases of architectural interventions in the city of Florianópolis (SC - Brazil), in order to bring dialogues between the new and the old and the acquisition of more access to individuals in the contemporary city.

In March 2020 the world health organization declared covid-19 as a global pandemic. As a result, many states have adopted social measures to prevent the transmission of the virus (quarantine and self-isolation, closure of schools and businesses, social distancing, etc.). In the short term, this resulted in a reduction in the transmission of the virus but also a negative impact on human society (on lifestyle, social relationships, psycho-physical well-being). In the long term, this social restriction can lead to change in how people can be active and a new global health pandemic: physical inactivity and sedentary lifestyles. The fact the government’s rules include daily exercise outside shows how important they believe it is for people. Because physical activity and a sedentary lifestyle have consequences on the increase in the risk of cardiovascular disease, diabetes, obesity (for the whole population) and pathological ageing or with disabilities (for the elderly population which constitutes a large part of the total population), it is important to start thinking about the roles and duties of public spaces and how we can change them for the next phase of the pandemic and a more sustainable future. It is therefore a matter of placing the user at the centre in terms of its variability, whose interaction with the built environment is physical, cognitive-sensory and social.

The fashion world is trying various changes due to the development of technology, the non-face-to-face environment caused by Covid-19, and the lifestyle change of the digital generation. It is a world where luxury brands promote and sell their products in a metaverse environment. Fashion influencers also use YouTube to give advice on styling and short content, and lead lifestyle changes. As a result, the values and sensibility of digital-based fashion are also changing. Therefore, this thesis researched related contents through Fashion YouTube. Fashion YouTube, which has the top 5 domestic subscribers and videos as of May 2021, was selected. I crawled their youtube data reviews with python. As a result of the analysis of the collected data with text-mining, past fashion discovered fashion and trends, but modern fashion further emphasized the philosophy and values of life based on their own lifestyles. Rather than changing fashion based on trends, fashion is a means of expressing individual values, emphasizing emotional details and expressing fashion changes.

This paper focuses on the design and evaluation of an educational solution centered on environments that do not have internet access. Two different prototypes were evaluated, one focused on creating the class content aimed at teachers, and the other focused on displaying and using the class content aimed at students. For this, twenty teachers and ten students were reached from African and Asian countries where the network conditions are not proper for remote educational environments. Preliminary results state that the participants were favorable to these solutions.

In this study we aim to observe if intentions are conveyed by a relevant conversational context in a chatbot interface and if it influences decision-making. We created two conditions using the alternate counter-offer version of the ultimatum game in 2 negotiation settings: face-to-face and through a chatbot. There are two inter-locutors: the proposer and the respondent. The proposer must share 10 units with the respondent. If the respondent accepts the units are shared while everyone loses if the respondent refuses. 92 participants took part in this study: 62 in the chat-bot condition and 30 in the face-to-face condition. Participants faced three player profiles: stochastic, selfish, and rational. Results show that participants decrease the value of the offer more easily in the chatbot condition with the selfish profile. We conclude that the intentions are correctly conveyed by the profiles even in a chatbot-like negotiation despite the absence of non-verbal behaviors.

Adaptive automation is pivotal for the calibration of trust between automation and its users. This paper presents an exploratory analysis into the use of facial expressions to trust in automation. This was done by analysing facial expressions of distrust and classifying into facial AUs composites, and comparing these to the 6 basic emotions. Results suggests the existence of two prototypical expressions of distrust that can be distinguished from the basic emotions based on AUs combinations. This shows promise into using facial AUs as a means for detecting distrust.

Digital learning and virtual backgrounds have been there for years but started to gain evident popularity after the Covid-19 pandemic. Now video conferencing tools such as Zoom, Google Meet and Microsoft Teams have become the new normal in almost every individual’s life. This study emphasizes how students experience the use of backgrounds in a digital learning context. In an online survey conducted among students enrolled in higher education institutions in Norway, we look at the effects of real (non-virtual) backgrounds versus virtual backgrounds. Findings show that virtual background is not strongly preferred by students in a learning context, few students change background in digital lectures and some attention is paid to the use of backgrounds by lectures and fellow students. To some extent, the use of backgrounds is perceived as distracting, and changing backgrounds is linked, among other things, to doing so for fun. Grounded in our findings, we conclude with some practical recommendations concerning the use of backgrounds in digital a learning context and call for further research.

This work presents a new approach to evaluate operators skills regarding their activities. This approach is based on an activity model composed of three primary activities. For each primary activities, an indicator has been proposed. The method has been applied in the case of a picking task. Results are compared with expert analysis and seem consistent. The approach shows there is no clear link between performance and skills.

Video games for education still remain unpopular educational resources and tools for learning. One of the reasons is that teachers do not understand the efficiency of video games for learning. In this perspective, the game assessment reports such as scores, points, and statistics have to provide meaningful information not only to players but as well to teachers and lecturers who have to assess and evaluate the learning outcomes. Considering the user-centered design approach, the present research aims to investigate how to select appropriate assessment metrics to make the game analytics and feedback reports for the adaptive video games for education more relevant for teachers and learners. The game metrics, collected before, during, and after the game experiences have to ensure relevant data for all end user’s groups – teachers/lecturers, students/learners, system designers, and others. This research will be adapted for the design of the APOGEE platform for adaptive serious video games.

The aim of this study is to investigate the opinions of architecture students about the usage of online platforms as alternative socialization environments during the Covid-19 outbreak. Accordingly, a questionnaire was directed to students of architecture from different levels in the host university to see and compare their opinions and preferences about the contribution of online platforms to their socialization needs. Results indicate that digital platforms in online studio contribute to socialization between students, but still need to be improved.

The present study demonstrates the ongoing development of a service robot application in a campus library through the application of Design Science Research (DSR) combined with user-centered design (UCD). In particular, we involved librarians and co-created an application solution addressing two use cases: giving directions to a desired subject area/book and providing recommendations for an event/book. Additionally, we involved potential end users to evaluate the robot artifact through an onsite usability test (N = 14) already within the design cycle. This process resulted in a successful application of the robot artifact for the identified use cases and shows feasibility of combining DSR with UCD.

The paper investigates a fashion sector which is unexplored and ignored: Adaptive Fashion. The aim of this design is to answer to this new group of consumers creating functional and trendy garments for them. Firstly, the paper analyzes what the Adaptive Fashion was and its transformation through the years. The Adaptive Clothing companies haven’t thought about a functional, creative design that follows the fashion trends and the innovations. After it shows that an accurate research was done on the physical structure of disabled people and their different requests: it studied their anthropometry and thought about a correct design process for the creation of a knitwear collection for wheelchair women. It is inspired by Milan, which won the Access City Awards 2016 prize. The collection is made of Wool and Cotton because these fibers were identified as the best natural ones for this project after a lot of scientific investigations.

In a business building, different stakeholders communicate with each other frequently. It is important to understand their communication needs to be able to develop smart building solutions to support the communication. Our study focused on an entrepreneurial business campus that hosts start-up companies, investor companies and service providers. As data collection methods, we used interviews complemented with one-week diaries. In total, we interviewed representatives of ten different stakeholder roles. Especially important contacts as well as communication needs related to providing services were studied. As a result, we present how these professionals currently communicate with each other and what communication needs they have. These findings can be used when defining communication requirements in the development of smart solutions for business campus buildings.

Electrotactile displays reproduce tactile properties of an object such as texture and shape to provide feedback in human-machine interactions. Electrotactile perception threshold (EPT) is a critical psychophysical parameter in designing a safe display as prolonged usage causes skin irritation. This study's main objective was to reduce EPT with background thermal stimulation (BTS) and analyze the qualitative and quantitative aspects of EPT with and without BTS. A psychophysical experiment was conducted to measure EPT with and without BTS (+7 °C)) over a wide range of stimulus frequencies of EPT from 20 Hz to 640 Hz. Findings from these experiments showed a reduction in the EPT (∆EPT), which was 13% to 17% (with an average of 15%). Reduced EPT may provide safer and comfortable electrotactile displays for prolonged usage.

Adaptive automation is paramount in alleviating the undesired effects of high levels of automation. This paper examines various visual physiological measures whilst participants were engaged in conflict detection tasks in an air traffic control environment of varying traffic densities. Results showed that global means of fixation count and duration do not perfectly convey the underlying cognitive processes of operators and that successive comparisons on aircraft targets could serve as potential predictors of conflict detection performance end states. The agnostic nature of successive comparisons to varying traffic densities is also vital in a realistic air traffic control environment where traffic is fluctuating constantly. Additionally, physiological measures derived from such behavioural cues could potentially serve as fail-safe triggers in conventional physiological-based adaptive automation triggers in safety-critical domains.

This article presents research practices for a biometric data collection protocol involving virtual reality equipment, based on principles that guide human-centered design (HCD) and experience design (UX), with the aim of exploring the potential for applying design methodologies and their tools for research practices in data collection in the context of Virtual Reality and others. With the know-how in research and design of the team of the Creativity Laboratory of the Scientific and Technological Park of PUCRS (Tecnopuc Crialab), a research protocol and a participant’s journey map were conceived based in the principles of HCD and UX. These were improved based on feedback from tests carried out with researchers and subjects, in an iterative process throughout the research. Based on theoretical contributions and the practical experience described, practices are presented that can be considered in research with virtual reality equipment, and in any type of experiment involving people.

External human-machine interfaces (eHMIs) could enhance the interaction between automated vehicles and surrounding traffic participants if implicit signals are insufficient. Traffic safety requires an appropriate level of trust considering potential eHMI failures. Thus, the current study investigated effects of eHMI system failures on elderly participants’ system assessment. During a video-based study, participants assessed an augmented eHMI in three experimental blocks of trials. The first block exclusively displayed valid eHMI signals that acted consistently to the vehicle’s movements. The additional blocks also comprised invalid eHMI signals that mismatched the vehicle’s movements. Results revealed higher ratings of trust and perceived safety for a valid system acting consistently to vehicle’s movements compared to an initial assessment without system experience. After experiencing eHMI failures, participants’ system assessment declined. Results underline that eHMI signals are required to be in line with vehicles’ movements to support traffic safety and smooth communication with other traffic participants.

With the growth in air traffic volume, automation tools are being developed to increase the capabilities of Air Traffic Control Officers (ATCOs). In this paper, a novel approach to unearth Air Traffic Control (ATC) strategies from raw simulator data is described by utilizing executed radar commands obtained via mouse click data. Five sets of air traffic simulation exercise data were used to identify potential conflicts and unearth likely strategies undertaken using a proposed strategy identification model. The preliminary results demonstrate the success of the model in its ability to identify four distinct strategies adopted by the controllers to safely navigate air traffic conflicts that occurred during the simulation and the conflict type in which they occurred. Strategies identified were also verified by an expert panel to be effective in solving the targeted conflict type. The proposed model can be used to objectively identify ATC strategies for use in automation development.

The advent of augmented reality technology has been a boon for automotive segment, particularly the vehicle diagnostics. Augmented reality enables the overlay of critical diagnostic digital data on the field of view of the real-world vehicle parts thus providing valuable information with the context of diagnosis and repair thus greatly reducing the digital-analog divide. Another key advantage in augmenting critical information like DTC codes, RT measurements over the actual vehicle parts helps in reducing the cognitive load for the technician in remembering the details from service manuals and can help in lowering the human error factor as well. This is one of the reasons why many of the tier 1 vehicle OEMs are eagerly embracing this technology. However, the platform on which most of the tools are designed are predominantly smartphone and tablet based since the smartphone hardware and software provide a cost effective as well as comprehensive ecosystem for rendering the augmented content. This, in reality, poses challenges from an environmental and ergonomic standpoint for the technician who needs to use these tools in conditions which is dynamic and may not always be linear. The paper details study ongoing across multiple geographies including US, Europe and India involving contextual observations as well as moderated in person interviews conducted with the technicians with an aim to capture the environmental conditions and ergonomic factors pertaining to the technicians’ work zone and how it influences the user experience of designing augmented reality tools for vehicle diagnostics. For the purpose of this study, application of readily available and cost-effective AR platforms is being considered and high-end mixed reality headsets like Microsoft’s Hololens are excluded.

This paper presents the first results of the development of a holistic care platform. A user-centered approach is taken to align the platform as closely as possible to the needs of potential users and to create real added value with the platform in contrast to existing solutions. In the context of this study, the term user is understood to mean both people with assistance needs and their relatives or caregivers, but also potential providers who offer their products or services via the platform. Within the framework of the user-centered approach, potential competitors were first analyzed. Besides, a qualitative analysis was conducted to identify unmet needs and implementation ideas of the users that could be covered by a care platform.

Teleoperation offers a way to harness the collaborative benefits of machine precision and efficiency combined with human flexibility and cognitive abilities. One of the main technical challenges in teleoperation is signal latency; despite the large body of literature investigating this topic, there is relatively little exploration of why signal latency impacts human performance. Those few studies on human performance in teleoperations have focused on objective measurements in short duration scenarios, often performed by newbie participants in laboratory contexts and with well-defined targets and completion goals. This is in stark contrast with the characteristics of real-world teleoperation scenarios, where highly trained operators will perform longer tasks, concurrently, in noisy environments, with combinations of performance shaping factors such as fatigue, distraction, time pressure, stress, etc. In this paper, we propose a study to evaluate the effects of signal latency on human performance in simulated scenarios that more closely mirror real-world operations.

In web usability studies, a ‘contextual fidelity’ model identifies four factors that significantly affects testing accuracy: web aesthetics; testing environment and circumstances; participants’ personality traits and user states; and the nature of test task. In most works, these factors are considered independent; however, this has never been properly tested. To partly cover this gap, we experimentally test the one-directional effects of web aesthetics and task nature upon user states. Of dysfunctional user states described in literature, we have chosen monotony and anxiety, both equally damaging for user experience but differing by cognitive strategy. By combining high/low-quality web aesthetics and tasks directed to monotony/anxiety, we show that these two factors condition each other in users’ action. To detect monotony and anxiety, we measured cognitive efficiency and emotional stress. 48 student assessors divided into 4 groups were involved in the experiment. Our results shown that, counter-intuitively, the impact of website aesthetics on user states differs in cognitive performance and not in emotional stress. In the case of anxiety, high quality of design provokes hyper-lability of attention, does not contribute to its concentration, and reduces productivity. In the case of monotony, the aesthetic layout dramatically reduces the rate of fatigue and increases productivity. Our results prove that web aesthetics has a non-negligible impact upon more rational decision-making of users, which was overlooked in previous studies.

Factors such as the lack of standardization of processes and unproductive times in manufacturing companies cause deficiencies in production processes, this in turn causes delays in the delivery of finished products. Given the problem, the use of Lean-QRM is proposed as a solution model to reduce the delivery times of orders in SMEs, both methodologies complement each other and are aimed at improving efficiency in companies with production-to-order systems. For this reason, the research carried out seeks to implement a model focusing on increasing efficiency in the production area of the company under study in order to improve the performance of on-time deliveries (OTD). The results suggest a minimum increase of 1.5% in the delivery of orders on time.

In a production system in the plastics industry, the implementation of the Lean Manufacturing tool is carried out with a view to reducing machine downtime, because there is a relatively low availability rate, which is generated by breakdowns constant and prolonged time in its restoration. With the application of the Total Productive Maintenance technique focused on the criticality analysis of modes, effects and failures. It seeks to reduce the six major losses of equipment, through the timely identification of the main causes of unforeseen breakdowns, which affects the availability of machines and their productivity and increases production costs. The Solution model will be implemented in three of these: First, the preparation stage. Then, the implementation stage that consists of the development of two methodology that is Total Productive Maintenance and 5S. Finally, the monitoring stage that allows the indicators to be compared with the improved line.

With the innovation of supply chain, customization services in jewelry industry are thriving. Various online platforms enable users to cooperate with designers to create personalized jewelry works. Considering that normal users are not professional in 3D modeling, the actual design is conducted by others to a large extent. As a result, there is still a wide gap between users and the creative process. To solve this problem, the GemForest system is introduced in the paper, offering a more efficient and inclusive way for users to generate digital models ready for 3D printing. Combining Snowflake algorithm with Fourier transform, the system is able to automatically produce diverse geometric patterns for jewelry manufacture. Through case study, design process and usability test, we provide reference for designers dedicated to the relevant field and discuss future research directions.

Intelligent technologies have already revolutionized the economy, and they will continue to do so via autonomous, AI-based systems and artefacts. Artefacts can handle much more intellectually complicated tasks than was possible before. However, the technological transformation will set new demands for technology design and designers. Designing electromechanical technologies has been based on natural science, but intelligent technologies will extensively use knowledge of human research and information processing to create new artefacts. Intelligent information processing has so far been possible only for biological systems and especially for human minds. Therefore, their functions and behaviors will become essential both for the development of new technologies and for the technologies themselves. In this paper, we concentrate on the foundations of investigating how language and thought interact in design thinking. To illustrate the importance of interaction, we present three examples of phenomena in which design thinking and design language meet: explication, understanding, and linguistic (conceptual) change. Understanding how language and thinking are linked within these phenomena may improve the design processes and, e.g., how to train designers’ domain-specific skills.

Engineers are not usually confronted with empirical research methods during their education. Classical product developers thus lack knowledge and the intuition of what to consider when using methods in user studies. The problem is that user studies therefore miss potential development goals for optimized user-centered product design. To resolve these difficulties, a process approach and an in-depth guide have been developed. They provide knowledge, focused on psychology and social sciences about user studies along the ideally typical history of an empirical study in a structured, compact and comprehensible form. This enables product developers to more effectively and efficiently capture the needs of customers. At the same time, the effort required to implement user studies is reduced, errors are avoided and quality is increased. In the future, the process approach and the guide will be verified and validated.

This study empirically examines the theoretical framework model for the relationship between COVID-19, stress, anxiety, and university students’ online exam cheating in the USA during the COVID-19 pandemic. The researcher collected primary data of 251 male and female university students in the USA via Survey Monkey and tested the six hypotheses using the structural modeling equation technique. The results validate the significant and positive relationship between COVID-19 quarantine and stress and COVID-19 quarantine and anxiety. The study results show that COVID-19 quarantine causes anxiety and stress among university students, influencing students’ behavior to cheat more on online exams. Besides, this study develops a conceptual framework for the relationship between COVID-19, anxiety, stress, and online exam cheating and refines six hypotheses from previously generated propositions. Finally, faculty members and administrators can use the study results as guidelines when thinking and deciding on exams, assignments, and how to monitor online exams.

With the rapid development of urbanization, the issue of the construction of an elderly-friendly city has been raised. Due to the deterioration of the mobility and perception abilities of the elderly, it is more difficult to adapt to the urban traffic travel environment, and there is a greater demand for intelligent travel auxiliary products. This paper analyzes the travel characteristics and pain points of the elderly through user experience maps and typical scene analysis, and explores the feasibility of combining AR technology application with aging travel based on sensory compensation theory. This paper takes the two daily travel needs of elderly people, including walking and public transportation, as the starting point, and proposes the design concept of wearable travel assist glasses. It adds new possibilities for the aging of smart cities in the future.

Biomechanical simulations can be used to evaluate the human stress during use of existing power tools. However, when the design is disruptively changed, it is challenging to predict the future nature of the user's use, posture, and load. Although simulation environments already exist for body posture prediction, they are not suitable for unbounded motion or postures. In this paper, a multi-level research approach is described. This approach allows the development of application-specific body posture models based on co-simulation in combination with a subject-based study as well as the evaluation of human stress. This enables manufacturers of power tools to make disruptive design changes and evaluate them concerning musculoskeletal stress at an early stage in product development.

This research endeavors to justify why tribalism__a sense of belonging to an individual’s tribe, superiority among other tribes, blindly loyal to a tribe, and demeaning outgroups__is a different cultural value different from Hofstede’s initial first four dimensions of 1984 in 76 countries. The author used the bivariate analysis and data from Corruption Perception Index, Tribalism Index, and Hofstede’s Cultural Dimensions’ Study 2001. The results show that tribalism is different from Hofstede’s initial cultural values of uncertainty avoidance, PD, masculinity, and collectivism. The results confirm the author’s argument why tribalism should be added to Hofstede’s Cultural Dimensions Theory. This study validates the concept of tribalism as a testable dimension by testing the relationship between tribalism and corruption using linear regression analysis. Researchers can use tribalism as a new cultural value that differentiates societies from one another.

Urban Airport is a transportation infrastructure for electrically powered Vertical Take-Off and Landing (eVTOLs) aircrafts, or so-called flying cars. It is one of the emerging solutions for improving urban environments in terms of sustainability and traffic. This paper explores how adapting a human-centred design approach enhances passengers’ journey through the future Urban Airport. In order to deliver a user-friendly experience, accessibility, comfort and efficiency are vital. Understanding users’ journey throughout the Urban Airport will help us comprehend how the infrastructure should be designed for targeted user groups with different characteristics and expectations. This paper presents three user personas and associated storyboards to provide insights into the spectrum of goals, needs and frustrations of the Urban Airport potential users.

Effective interpersonal communication is important to maintain relationships and build trust, empathy, and confidence. In this digital age, communication has become mediated, which filters out many of the social cues that are essential to facilitate interpersonal communication. This paper investigates the extent to which social cues influence social presence in mediated, bidirectional, multiparty interaction. Literature related to six social cues – paralinguistic cues, linguistic cues, body language, eye movements, facial expressions, and proxemic cues – was reviewed. These cues were ranked based on how relevant they are in creating a sense of social presence in mediated social communication (MSC). The most relevant cue was eye movements, followed by facial expression and linguistic cues, and lastly, body language and proxemic cues. Paralinguistic cues could not be ranked due to sparse literature in the context of MSC. Further research is required to better understand how social cues can be incorporated into MSC systems.

Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death in the U.S., particularly impacting elderly populations (Learn about COPD. American Lung Association.). In this study, we integrate advanced machine learning methods with health patterns, environmental exposures, and patient outcomes, identifying the value of human-centered decision making tools. With the aim of reducing the negative effects of COPD at a zipcode level, this research investigates how risk variables such as age, sex, underlying conditions, and environmental exposures impact 30-day hospitalization, readmission, and emergency visit rates in New York, Pennsylvania, and Florida – urban areas that experience high annual rates of hospitalization. Our aim is to help patients preemptively prevent exacerbations of COPD by providing clinicians with visual tools to anticipate environmental changes so that they can offer more timely care to vulnerable populations. This study found that weather and pollution have strong impacts on COPD-related hospitalizations and ER visits and a moderate effect on 30-day readmissions.

The existing physical education is limited by the characteristics of text media and spatial dimensions. Many technical teaching contents are taught only through language description and basic action demonstration, making it difficult for students to understand the main points and theoretical basis of action. The application of digital media language in physical education teaching, the application perspective of interdisciplinary subjects, the application analysis of animation in sports technology enriches the construction of the digital teaching material system of sports technology, promotes the construction and development of sports disciplines. The animation interpretation of basketball technology vividly presents the components of basketball technology, promotes the development and perfection of basketball theory, and the construction of the digital model is conducive to students’ in-depth understanding of teaching knowledge. Digital technology will give traditional teaching a more comprehensive perspective and interpretation so that in the digital age to find a better way to integrate with digital technology, improve teaching content, and promote the development of disciplines.

The concept of truck platooning comes from the virtual linking of two or more trucks driving on the road in convoy, with a short distance between them. These vehicles keep the distance using SAE level 2 or 3 automated driving technology supported by a Cooperative Adaptive Cruise Control system. The first truck is considered the leader and the following truck(s) react(s) and adapt(s) their speed and position on the lane without human action.The TRAIN project addresses these issues through a Human-Centred approach to identify requirements for the development of truck platooning technology and assesses risks towards a safe deployment in the real world. Following the collection of qualitative data from experienced truck drivers, tests in a driving simulator will allow for identifying risks related to the drivers’ activity in truck platooning.Finally, design and operational guidelines highlighting the importance of human-system integration in the system development will be issued.

In second language learning, listening and comprehension are essential processes in knowledge extraction and information processing. Cultural differences will encounter many ambiguous situations, which will make the learners feel nervous and uneasy. At this time, the level of tolerance of ambiguity will affect the results of language understanding. Therefore, studying the tolerance of ambiguity in listening comprehension improves second language comprehension and a better understanding of culture under different social backgrounds. Our research focuses on tolerance of ambiguity on second language users’ speech understanding and foreign language anxiety when using English in different situations. In this study, we interviewed 6 students with bilingual training experience, and used the tolerance of ambiguity scale to test 60 students with bilingual training experience, and came to the following conclusion: different tolerance of ambiguity in different scenarios affect the second Language learners have different influences; second language users with a high tolerance for ambiguity have better speech comprehension performance and less foreign language anxiety than second language users with a low tolerance for ambiguity; contrast situation and tolerance for ambiguity, Scenarios such as comparing the classroom environment, in the daily environment of high tolerance for ambiguity and a low tolerance for ambiguity second language users have better speech comprehension performance, and produce less foreign language anxiety. This research aims to find ways to improve the tolerance of ambiguity in different situations to improve the language comprehension performance of second language learners and reduce their foreign language anxiety.

The COVID-19 pandemic has led us to new social behavior. To contain the virus, governments have imposed social distancing and confinement. The fear of contamination and the inability to go out to buy essential and non-essential goods intensified the perceived threats associated with offline channels, as well as the perceived benefits and relative attractiveness of digital ones. This dynamic has shifted the market towards online platforms. This paper intended to identify new behavior patterns in online shopping as we face an unprecedented scenario. We conducted exploratory interviews with 18 people and constructed an online questionnaire that had 327 respondents. Our findings reinforce the relationship between a flawless consumer journey (from pre- to post-sales) and a positive shopping experience.

Digital transformation currently affects all parts of society. We believe it is important to investigate what impact a company’s digital transformation has on its HRM and its activities. Thus, we apply a mixed-methods approach to observe this technology-induced shift. We analyze the annual reports of German DAX companies from the last ten years using a text mining method and a qualitative content analysis. After discussing the results in interviews with HR managers, we present our main findings: As suggested by our literature review, we cannot establish a uniform correlation between digitization and HR activities as the technology usage varies greatly between HR activities. Strong external influences affect the developments at personnel, organizational and market levels. Further research—also in international settings—is necessary.

Conditionally automated cars share the driving task with the driver. When the control switches from one to another, accidents can occur, especially when the car emits a takeover request (TOR) to warn the driver that they must take the control back immediately. The driver’s physiological state prior to the TOR may impact takeover performance and as such was extensively studied experimentally. However, little was done about using Machine Learning (ML) to cluster natural states of the driver. In this study, four unsupervised ML algorithms were trained and optimized using a dataset collected in a driving simulator. Their performances for generating clusters of physiological states prior to takeover were compared. Some algorithms provide interesting insights regarding the number of clusters, but most of the results were not statistically significant. As such, we advise researchers to focus on supervised ML using ground truth labels after experimental manipulation of drivers’ states.

This paper presents the Additive Manufacturing (AM) evaluation methods and methodologies. A comparative analysis is conducted in order to categorize the methods according to different criteria. The comparison describes various approaches, along with their objectives and requirements. The emphasis is put on the aspects of automation and machine learning in the context of AM suitability evaluation. The aim of the article is to offer a high-level reference point for researchers who verify the potential of AM in the context of their studies or business activities. The comparison should facilitate the choice of an optimal, applicable method for identifying AM potential in a specific scenario. Additionally, the analysis offers an insight into the trends of the AM potential analysis methods, evaluating the role of AI and other aspects of Industry 4.0 in the field.

The scientific contribution of this paper is a multilayered Human-Human Interaction driven framework that aims to connect the needs of different sectors of the society to provide a long-term, viable, robust, and implementable solution for addressing multiple societal, economic, and humanitarian issues related to the increasing population of the world. ‘Connecting dots’ here involves issues of three major constituents of the society: the loneliness in the rapidly increasing elderly population, the increasing housing needs of low-income families, and caregiver shortage. The proposed framework would facilitate mutually beneficial, sustainable, equitable, and long-term solutions, based on several factors, to address these global societal challenges. The development of this framework involved integrating the latest advancements from Human-Human Interaction, Big Data, Information Retrieval, and Natural Language Processing. The results presented and discussed uphold the significance, relevance, and potential of this framework for addressing these above-mentioned societal issues associated with the increasing global population.

Drone technologies are now increasingly paving their way into commercial application with a promise of facilitating traditional operations. With the foreseeable increase in use of drones across multiple sectors and with rising concerns associated with drone flights, there is a need to perform stakeholder analyses for commercial drone usage. Based on the data collected from 15 expert interviews, literature search and a workshop, this paper presents a framework of actors who impact on or are impacted by the use of drones. It illustrates how the identified stakeholder groups could potentially benefit from drones, mainly economic, societal and environmental advantages, and on the other describes the challenges and concerns from the view-point of each stakeholder group. The findings reveled that safety is regarded as a high concern, however does not appear to be a principle concern for industry users and the overflown communities. The performed analysis points out that among the categorized stakeholders, overflown communities are perceived to have the highest opposition towards drone use. We conclude with discussing solutions on how to mitigate their concerns so as to facilitate increased social acceptance of drone usage.

The scientific contribution of this paper is a Big Data-centric study, conducted using Google Trends, that involved analysis of the global, country-level, and state-level search trends related to indoor localization by mining relevant Google Search data from 2015–2020. There are three novel findings of this study. First, the current global search interest in indoor localization is higher than the average, median, and mode values of search interests (since 2015), and it is projected to keep increasing in the near future. Second, Singapore predominantly leads all other countries in terms of user interests in indoor localization. It is followed by Canada and United States, which are followed by the other countries. Third, the state-level analysis for the United States shows that Massachusetts leads all other states in terms of user interests in indoor localization. It is followed by New Jersey and Michigan, which are followed by the other states.

Currently SMEs present many challenges such as competition with local markets, inefficiency in productivity, quality and services, representing a financial imbalance. In Peru, one of the main problems for SMEs is the lack of planned production and a poor distribution of work. These problems faced by all SMEs generate that entrepreneurs seek different ways to overcome the problems mentioned above applying different solutions to generate opportunities, providing greater productivity and establishing sustainability in companies. This article presents a case study in a small upholstery company that presents production efficiency problems where a production management model based on Lean Manufacturing and SLP will be implemented to achieve that capacity improves, productivity increases eliminating waste while minimizing waste. costs and activities within production in order to increase the flow of material rotation, managing to meet customer orders on time, both in the manufacturing and service industries.

The Inter Planetary File System is a decentralized storage network based on peer-to-peer communication and strives to become an alternative to centralized standards such as HTTP. However, there is a pressing need in analyzing the performance of the former compared to the latter. Therefore, this paper deploys a testbed scenario to compare physical resources’ usage and transmission delay between IPFS, IPFS Cluster and threaded and non-threaded HTTP. Results show that although HTTP currently delivers higher throughput, its centralized approach can overwhelm servers and IPFS can leverage its decentralized architecture mostly for large-scale scenarios. Moreover, results also empirically show that IPFS’ content addressing resolution poses a serious challenge and should be addressed by its developers.

The article deals with the problem of responsibility or accountability of artificial intelligence built into the vehicle. Researchers introduce the problem of algorithmization of the society and some thought of the prominent persons on the artificial intelligence implementation into day-by-day life. From this background the article focuses on the problems of cooperative autonomous vehicles, their grouping and the behavior of the group in dynamically changed environment. The engineering, sociological and psychological view are compared. Following conclusions are based on the Strawsonian account distinguish between strong and weak AI and argue the power of these AI groups, pointing out reasonable responsibility gap. The article is closed by conclusion on responsibility or accountability of AI in autonomous vehicles at current state of art.

This paper deals with the combined implementation of the optimal redistribution of warehouse stations through layout analysis, as well as the use of lean techniques in warehouse operations of an air cargo company. The study highlights the effort to improve operations within the warehouse through the use of existing lean tools that allow eliminating waste (activities, materials, among others) that do not generate operational value, as well as improving and expanding the warehouse's storage capacity using the plant distribution tools and block stacking in order to maximize the allowed load and maintain the proper order that allows the continuous flow of operations within the air cargo warehouse.

The paper presents the development of an innovative solution based on a smart controller for solar thermal systems. The controller can intelligently optimize all sources and consumers of heating energy in order to maximize the savings. It has an easy to use user interface that allows advanced configuration. The solution consists of solar controllers, other IoT devices and a platform that provides remote control, extended user interface, and a number of different services.

In this research, we will focus on analyzing the influence of the rains on mining companies in the district of San Marcos in the department of Ancash, Peru. To do in this investigation, a stability analysis of slopes with limit equilibrium methods, being the Janbú the one selected for said study. On the other hand, it calculated the probability of failure of the slopes using methods probabilistic such as Monte Carlo. Such studies mentioned were applied with the help of the Slide software.

Cyberspace open-source intelligence is a subset of open-source intelligence that mainly pay attention to the information that reflects tactics, technology, procedures, behaviors, events, and other elements which are valuable for cyberspace defenders to gain an advantage in finding out what is happening, why is it happening and how to deal with troubles concerning cyberspace environments. As the scale and complexity of cyberspace continue to rise, nobody could process that increasing amount of data in time. To extract important information from fragments of observing results, it is necessary to strengthen human-machine cooperation in the intelligence domain for better accuracy, insight, and efficiency. From the viewpoint of space dimension, time dimension, and layer model of intelligence-organization, the desired relationship between human and machine and their respective duties are investigated by model-based methodology research, while corresponding suggestions are purposed for better analysis accuracy, insight, and efficiency in the future.

The paper presents the modeling of an educational WebQuest as a component of didactic information technology with special attention to the criteria and levels of success in its applications. A WebQuest is a problem-oriented task that requires the use of information resources available online. The relevance of using a WebQuest in the educational process is connected with the implementation of the competence-based approach, the main requirement of which is effective knowledge and skills management. The authors have developed primary mathematical models of a WebQuest based on set theory. Sample applications of these modern models in education are provided.

The coronavirus pandemic and the measures to curb it persuaded humanity of the crucial importance of the telecommunications industry for the functioning of society. The need to strengthen the existing telecommunication networks and facilities and to build new ones becomes inevitable. In 2020 two of the leading telecoms in Bulgaria managed to launch 5G networks despite postponed frequency tenders. This research is a case study of the process of building 5G telecommunications networks in Bulgaria, against the background of the unfolding global COVID-19 pandemic. The author claims that COVID-19 related restrictions do not cause a significant delay in the entry of innovations on the telecommunication market in Bulgaria. Alongside with the EU Strategies and Plans, it can be perceived as an accelerator for the development of 5G networks and services.

Currently, small- and medium-sized musical product businesses in Peru are in standstill due to low market demand. Under these conditions, venturing into a foreign market can be an option, where according to the reports of the Integrated Foreign Trade Information System (SIICEX), they received great acceptance in 36 countries amounting 497,391 US dollars, but the problem of higher productivity arises for a continuous export. Therefore, a lean manufacturing production management model needs to be developed under the design thinking approach to solve this issue. The proposed validation obtained a significant representation not only by promoting the product line but also in complying with high production standards of the different foreign countries. This study forms a research base to establish a production management model that benefits most SMEs in the 21st century.

In Perú, 90% of companies that employ 50 workers or less have an average life span of only 10 months in the market. This statistic is closely linked to informality and low productivity issues in such companies. Moreover, in March 2020, manufacturing production plummeted to 32.2% owing to low productivity levels exhibited by some companies. Therefore, to improve this situation, a production management method is required to enhance production management at metalworking MSMEs. This research work is based on the design and application of a production method based on lean manufacturing tools and agile methodologies to improve production process performance and meet market demands. Results revealed that manufacturing times reduced to 14.5 min, productivity increased by 30%, and the level of unfulfilled orders reduced by 30%.

Through this study, we present a framework to easily develop Social Media posts to enhance Educational experiences. The framework is validated with a study case including students from different engineering majors, seniorities and courses, who were invited to follow optionally an Instagram account where diverse content related to their specific syllabus was published throughout the sixteen weeks that the courses lasted, and was available only for 24 h. Results were cross-compared with a few Kahoot! quizzes with no negative impact on their grades, in order to validate if the posts designed with the framework helped those students who watched them.

This paper proposes a Lean Green model for increasing profitability in small and medium-sized businesses operating within the plastics sector. This model will use the 5S methodology, KanBan for inventory control and TPM to standardize new corrective and preventive maintenance processes. As an added contribution, a Circular Economy process will be included to reuse products, thus reducing consumption and generating less solid waste. In this way, companies will not only prevent damaging the environment but will also guarantee their compliance with regulatory standards. As a result, an 11% reduction was observed in the acquisition of supplies and spare parts for machine maintenance along with a 4% reduction in the number of machine breakdowns.

Currently, the way of working was affected by the pandemic we are experiencing and mining is not exempt from this. For this reason, preventive action plans had to be implemented to restart operations in all areas involved in the mining sector. In the execution of these operations it is necessary to review the operating protocols and see if they are effective for the continuity of the mine as well as the stability at the time of exploitation. Mining is carried out under different methods depending on various geomechanical, geotechnical and design factors, where balance is sought. The different mining methods include cutting and descending fill with long underground drills. For this reason, the current geomechanical design should be reviewed in order to identify the stress values that indicate better stability and that have as a consequence the reduction of events caused by rock fall.

Training of deep neural networks is difficult due to vanishing gradients. Therefore, a pre-training procedure based on restricted Boltzmann machines is suggested to resolve this problem. However, new developments in deep learning aim to resolve the problem with vanishing gradients by using rectifier linear units (ReLU). This study compares the performance of a RBM pre-trained auto-encoder with sigmoid activations to the performance of auto-encoder with ReLU activation. The results showed that the ReLU auto-encoder achieved better reconstruction and saved training time, since it doesn't require pre-training .

The aim of the paper is to point out to a new educational program, which was created as one of the outputs of the TAČR ÉTA project (project number TL01000192) at the Czech Technical University in Prague, Masaryk Institute of Advanced Studies within the research grant of the Czech Republic [1]. The educational program develops the digital competencies of teachers, is focused on working with new technologies and the application of digital technologies in the educational process.

Usually the purpose of a conveyor is not only to transfer the load to its destination but also to make a buffer that allows storing some number of products before the accepting side is available. Compromise between the throughput and storage density gets harder when the load varies during operation. The conveyour’s efficiency could improve if it can predict the load. Here we present a novel method for finding load distribution patterns in conveyor systems using neural network in order to predict the load and to automatically adapt the conveyor behavior. We used simulated input load and output loads for the conveyour to train a neural network. The experimental results showed that the network is able to predict the input and output loads with high accuracy.

Textile SMEs differ from others by their ability to generate garment designs according to current trends, this is the main competitive advantage of an SME in the field, however, design management refers to management problems from within every company. It seeks to establish a model that can improve the times, costs and satisfaction of workers who collaborate within the design management of textile SMEs, using a BPM management model under the Design Thinking approach, changing the focus of the Design Thinking tool to seek solutions within business problems through the BPM structure and its life cycle A case study was carried out for the validation of the model in a textile SME in Peru, the main results obtained were the improvement of times and costs in management design by 9% and 7%, respectively.

In recent years, the number of workers in Japan’s construction industry has been decreasing, and the working environment at construction sites and other facilities is being improved. For example, the use of professional headsets equipped with bone conduction microphones, which enable clear voice communication even under noise, is expanding. Therefore, we aim to improve the performance of speaker identification using bone conduction microphones. In this study, we propose a speaker identification method using the difference of spectrum between bone conduction and throat speech. In the proposed method, Mel log power spectrum of bone conduction and throat speech is calculated. Then, the difference of spectrums is calculated and SVM is used to identify the speaker. The proposed method using the difference of spectrum between bone conduction and throat speech achieves the highest identification rate, which confirms the effectiveness of the difference of spectrum between bone conduction and throat speech.

Food industries face complicated inventory management problems, since the products are perishable, that is, after a certain time the product will no longer be edible. Therefore, the importance of this project is to optimize the inventory control of olive products in SMEs in the agro-industrial sector. Additionally, the goal of the research is to minimize inventory costs and the time it takes for products to reach their respective customers. For this, the indicators of inventory rotation, perfect deliveries, inventory accuracy and satisfied customers were established so that an increase in each of them was achieved and standardization was achieved efficiently. For this reason, the PDCA (plan-do-verify-act) methodology will be implemented, also known as the Deming cycle in the agro-industrial company in order to standardize the processes of reception, location, preparation and dispatch in the product warehouse finished.

The increased pace of adopting virtual reality (VR) technology in the digital age as a new way of communication, enabled the decision-making concept to evolve in environments influenced by improved technologies and operational processes. Human Factors pertinent to team members sharing a real and a virtual environment (VE) have been examined by capturing the interaction capabilities to gain and maintain individual situation awareness (SA) impacting the team SA level. This baseline has been explored with a Joint Cognitive System foundation and integrated in a modified cyclical model with different modes to measure the level of immersion required for achieving higher levels of SA. In addition, a modified Observe, Orient, Decide and Act (OODA) model is introduced to address how information is collected, processed, and conveyed through the interchange of individual and shared mental models of one user immersed in the real world and one user immersed in virtual reality.

Older adults are often affected by a decline of mental and physical abilities, which results in frailty, anxiety and reclusiveness. They often live alone; family and friends cannot visit them on a regular basis and thus they suffer from social exclusion and loneliness. TACTILE tackles this problem by fostering an active lifestyle and the wellbeing of the elderlies. TACTILE’s novelty is the use of Mixed Reality that makes the remote partner virtually present. Continuous user feedback collected in three workshops guarantees that the user interaction and experience will meet the end users’ needs. In this paper we describe the TACTILE system and its components, the strong end-user involvement, and the results from the second user workshop, where the second prototype was tested. The system will be validated in final field trials in two test countries – Austria and the Netherlands – with the elderly people and secondary end-users (family members and caregivers).

We want to motivate and inspire children to learn languages with the help of augmented reality. In this individual case study, we evaluate the potential of our Augmented Reality learning assistant “ARTranslate”. We conduct a individual case study by letting children do everyday shopping with the help of our augmented reality learning app. We evaluate these repeatedly with queries in the following days. The respective retention rates range from 26% to 92%. We were able to show that children autonomously learn foreign language terms with the help of our augmented reality learning initiator. To start the initial motivation when learning a new language, ARTranslate has delivered strong indications of high effectiveness.

This paper explores an application of immersive Virtual Reality (iVR) as a medium to combine Android Graphical User Interface (GUI) development and CAD-based virtual prototypes to improve user experience testing. We also present tentative experimental findings, that a virtualized GUI need not be realistically placed or sized to be evaluated in an iVR environment .

Simulator sickness is still an unresolved issue in the VR field. Especially in driving or flight simulators, a perceptual discrepancy often leads to nausea and dizziness. This study tested the assumption that a mild stimulus to the sense of balance prevents or reduces this discrepancy using a VRGo, which acts as a control in contrast to conventional tilt input devices. A trend towards reduction in both time to nausea and severity of symptoms of simulator sickness were found supporting this hypothesis.

Operators monitoring closed-circuit television systems face many error-prone situations given the cognitive challenges they experience. The Scantracker is a prototype tool developed to support surveillance, relying on live oculometric data to trigger notifications that mitigate camera negligence, attention tunneling and vigilance decrement. To be robust and flexible, this tool must however collect valid gaze measures at a sufficient sampling rate and allow the display of surveillance-supportive visual notifications. This paper documents the integration of the Scantracker with the Microsoft HoloLens 2 augmented reality (AR) system embarked with eye tracking and reports a validity study performed in a high-fidelity surveillance simulation. The AR solution led to superior gaze validity than previous mobile or fixed oculometer integration. Implications of the solution integration are discussed and compared with the other implementations.

Immersive virtual reality (iVR) is becoming increasingly popular in the field of learning. However, due to the large number of scientific publications, it is questionable whether a substantial increase in knowledge in the use of this technology faces a manageable number of challenges. The question of the theoretical-conceptual embedding in the state of the art of psychological learning research (4E Cognition) must also be examined in order to enable the optimization of future iVR learning applications.

This study analyzes studies that have a methodological basis in the development of computer applications for the area of tourism supported by augmented reality technology. Augmented reality has proven to have great potential in learning due to its high level of visibility and interaction. The problem is the lack of research on development methodologies, supplementation of information for users with augmented reality, other alternatives in steps that allow the integration of image information in the tourism sector. The objective is to propose or adopt a methodology for the development of computer applications with augmented reality in the tourism sector. The methodology used in this proposal is oriented in analytical and exploratory research for a review of research work on the subject and theoretical proposal. After conducting the bibliographic analysis, the result was a Mixed methodology prototype for the development of computer applications and a general algorithm of methodology. It was concluded that, in the proposed methodology, the amount required in functionalities, data management processes, and codes of an application influence the development of computer applications; Augmented reality has great potential in many areas, tourism is a good application option for its features and benefits.

The pandemic, produced by covid-19, gave rise to a new normal, in which education is part of that change. In certain cases, the quality of education was affected, either by factors such as deficient online teaching material, teaching issues, attention, and adaptation problems on the part of students in their online courses. To help improve performance in online education, some educational institutions have chosen to use the virtual world of Second Life to implement it in their classes, offering features that benefit learning from home, making it more didactic and enjoyable for students. The objective of this article is to find and analyze the critical success factors for the implementation of Second Life in virtual classrooms, through the construction of fuzzy cognitive maps. The use of forms aimed at students is proposed, from which the results will be evaluated and the factors that influence a quality education will be determined, building a fuzzy cognitive map for their understanding.

The advent of Industry 4.0 has boosted the usage of innovative technologies to promote the digital transformation of manufacturing realities, especially exploiting the possibilities offered by cyber physical systems and virtual environments (VEs). Digital Twins (DTs) have been widely adopted to virtually reproduce the physical world for training activities and simulations, and today they can also leverage on the integration of Machine Learning (ML), which is considered a relevant technology for industry 4.0. This paper investigates the usage of a combination of DT and ML technologies in the context of a real production environment, specifically on the creation of a DT enhanced with YOLO (You only look once), a state-of-the-art, real-time object detection algorithm. The ML system has been trained with synthetic data automatically generated and labelled and its performance enables its usage in the VE for real-time users training.

Augmented reality is a concept for extending reality with additional information, which is basically not limited to visual representation, but is mostly an essential component. Here, we developed an augmented reality (AR)-based human-machine interface to run an industry robot. A Microsoft HoloLens with spatial mapping was used in an AR environment to operate a full-size virtual industry robot with bare hands, using the natural operation behaviors without additional handheld devices. Communication between HoloLens and the real industry robot was achieved by using the Mitsubishi-owned R3-protocol. The precise and timely transmission of instructions from the HoloLens to the industry robot via the Mitsubishi-owned R3-protocol provides a suitable template for future AR-based research and development in the field of engineering.

This paper describes an implementation of an augmented reality user interface for a model factory. The focus here is that the user interfaces are exactly where the user expects them to be, be it directly on the devices or that they follow the user.

The objective of the paper is to analyse how digital technologies are used in jewellery design in an era in which products and environments are becoming increasingly intangible to leave space to digital worlds, thanks to augmented and virtual reality. The paper gives an outline of jewellery within the contemporary scenario, analysing the direction traced by digital technologies within the jewellery system as well as the impact of virtual environments. To this end the contribution describes the results of an applied research case study developed during a five-day design workshop at Politecnico di Milano. The aim of the experience was to explore the contribution of digital and virtual tools in shaping and conferring value to jewellery items. In conclusion, the paper analyses the outcome of the case study in terms of concepts of preciousness and wearability, being defined based on personalization, interaction, and fruition.

This numerical study, made inside a virtual office, considers a Building Thermal Response software to evaluate the surrounding surfaces, a CFD software to evaluate airflow around the occupants and the indoor air quality and a Human Thermal Response to calculate the occupants’ temperature distribution and the thermal comfort level. This study considers a Heated, Ventilation and Air Conditioning system constituted by an inlet and exhaust systems. The inlet system, based on confluent jets, is built with horizontal ducts, located on the sides of the room, equipped with nozzles to promote vertical jets. The exhaust system is founded on a vertical duct, placed in the ceiling central area. The virtual office is occupied by four persons seated around a table. The Air Diffusion Index (ADI) and Air Diffusion Turbulence Index (ADTI) are calculated for winter typical conditions. The results show that ADI and ADTI improve with increasing inlet air velocity.

This numerical work developed and analyzed a HVAC system, based on horizontal confluents jets system, in summer typical day conditions placed in a virtual office chamber. Presents and applies a numerical model, developed by the authors in the last years, that considers the coupling of the CFD and HTR. In the input data are used the Computer Aided Design geometry, the location of the occupants and the external environmental variables, while the occupants’ geometry is generated by empirical equations, based in height and weight. Above the head level, six air ducts, connected to the ceiling area, compose the exhaust system. The inlet system was based on four vertical ducts with 0.15 m diameter, located on the corner of the office chamber, are equipped with consecutive holes who promotes horizontal jets near the wall. The thermal comfort, the indoor air quality, the Draught Risk, the effectiveness for heat removal, the effectiveness for contaminant removal and the ADI are evaluated.

A coronavirus called COVID-19 appeared in Wuhan, China in December 2019. By early 2020 it caused a worldwide pandemic of a respiratory illness. This virus crisis affected the economy in the world in 2020 and will affect it in 2021, a lot of companies lost $ billions, especially the airlines, and because of that a lot of people lost their jobs; it also caused deaths of many people and till now it causes deaths of thousands of people in the world every day, a lot of people have died and till now a lot of people are dying every day because of a late detection of the virus in their bodies. The coronavirus can spread from an infected person’s mouth or nose in small liquid particles, having different sizes, ranging from larger ‘respiratory droplets’ to smaller ‘aerosols’, when they cough, sneeze, speak, sing or breathe heavily, which means that it can be spread through breathing from an infected person to another person. There are different types (shapes) of COVID-19. This article aims to introduce a new approach that allows us to detect a coronavirus immediately using the artificial intelligence techniques and 3D modeling. The basic idea is to use 3D modeling technology to prepare the geometric data for different shapes of COVID-19 and AI technique, which can detect a coronavirus immediately through breathing by comparing the respiratory droplets or smaller aerosols with the shapes of COVID-19 specified by the 3D model .

The choice of the most suitable activation functions for artificial neural networks significantly affects training time and task performance. Breast cancer detection is currently based on the use of neural networks and their selection is an element that affects performance. In the present work, reference information on activation functions in neural networks was analyzed. Exploratory research, comprehensive reading, stepwise approach, and deduction were applied as a method. It resulted in phases of comparative evaluation inactivation functions, a quantitative and qualitative comparison of activation functions, and a prototype of neural network algorithm with activation function to detect cancer; It was concluded that the final results put as the best option to use ReLU for early detection of cancer.

Analysis of critical success factors allows software development organizations to focus on the factors to be successful. Selecting and implementing an algorithm for bosom cancer recognition could be hard. In this paper, a framework for modeling and analysis of success factors for the selection of Machine Learning methods used for the recognition of bosom cancer is presented. The objective is to analyze critical success factors in Machine Learning techniques selection for bosom cancer recognition built on Fuzzy Mental Maps. A group of common ML algorithms is presented in conjunction with the success factors. An analysis through measures calculation is presented in a case study. It was concluded that relevant factors for the selection of ML algorithms in the recognition of bosom cancer are: Selection of an ML algorithm according to the results, the study of ML algorithms tested in bosom cancer, obtaining and analyzing algorithm results.

In this article the application of a geostatistical method based on Gaussian simulation is studied to reduce the uncertainty of atypical data related to the hydrogeological data of a quarry, for which the data of the hydrogeological model of the impact study was considered as a basis environment of a quarry. This research proposes the application of Gaussian Simulation to identify the data that generate uncertainties in the elaboration of the hydrogeological model; such as the identification of underground aquifer levels. This technique first develops the verification of the hydrogeological data, then identifies the outliers, which will allow a better application of the Gaussian Simulation technique with the Gaussian algorithm to obtain a more reliable hydrogeological model. Finally, it is geostatistically demonstrated that the application of the Gaussian simulation reduced the uncertainty of the hydrogeological model by 20%.

In today’s time, software quality assurance is the most essential and costly set of activities during software development in the information technology (IT) industries. Finding defects in system modules has always been one of the most relevant problems in software engineering, leading to increased costs and reduced confidence in the product, resulting in dissatisfaction with customer requirements. Therefore, to provide and deliver an efficient software product with as few defects as possible on time and of good quality, it is necessary to use machine learning techniques and models, such as supervised learning to accurately classify and predict defects in each of the software development life cycle (SDLC) phases before delivering a software product to the customer. The main objective is to evaluate the performance of different machine learning models in software defect prediction applied to 4 NASA datasets, such as CM1, JM1, KC1, and PC1, then de-terminate and select the best performing model using the MCDM: VIKOR multi-criteria decision-making method.

In this research we propose to apply the qualitative evaluation technique by points to the factors that influence the price of gold. In addition, we will simulate the context of 2015, a year in which the price of gold reached historical lows, and at the same time, a period in which the analyzed company was going through a period of crisis when seeing that its valuation was affected by the devaluation of its reserves and growth of debts with suppliers. The research was carried out for the forecast of the price of gold, the general budget of the company, the budget in the mine operations area and the budget of the plant operations area, but for reasons of space in the development of the paper we will only show the development with the price of gold and the area of operations in the process plant.

The packaging is part of the final product and its ergonomic design becomes a purchase motivator. They fulfill different functions, such as: protector, conservator and provides logistical security of the product, among others. The use of technological tools as a transforming element in digitization, printing and prototyping accelerates the process and significant savings are achieved in the use of materials. In the prototyping stage, it is designed according to the product and different methodologies are used, such as participatory design and design thinking, before its construction. The objective of this research is to present the experience of higher education students in the design of prototypes using disruptive tools focused on the construction of packaging. 18 graphic design students participated, who managed to generate 3 prototypes, which were tested by direct observation in the Gesell chamber with 5 children with disabilities, 8 early childhood teachers and 8 parents separated into groups due to similarity. Digital modeling and the use of ecological substrates (earth pact) with their own colors and diverse textures, friendly to the environment, generated an appeal to the end user prior to production. The use of lasers in the die cutting process creates an attractive color effect (dark beige) by burning the paper. In the future, the aim is to work with other substrates (papers and cardboard) that allow measuring durability and malleability (if it can be easily bent without being damaged).

Although children suffering from attention deficit hyperactivity disorder tend to be nervous, not concentrated in specific jobs, anxiety that is transmitted to all those who are confined to the family, reviewed studies evidence that there are a large number of families that are affected by post-traumatic stress that obviously affects the whole home, the proposal is to create a playful environment capable of presenting scenarios that allow children to discharge their energy and focus on the educational environment, health and family well-being. The environment aims to be a counseling system that allows to identify the mood of the infant and proceeds through an intelligent system to deliver specific tasks aimed at improving the quality of life and reducing the level of anxiety, as well as helping concentration through the intervention of the family as a group or support group, we will focus on children from 4 to 6 years where children already enter virtual classes in most cases.

The goal of this paper is to predict electrical energy consumption using nonlinear autoregressive (NAR) models. The practical section contains historical data on Iraq’s annual electricity consumption rate from 1980 to 2013. The most significant findings are that neural networks perform better at predictive analytics due to the hidden layers. To make predictions, linear regression models only use input and output nodes. The hidden layer is also used by the neural network to improve prediction accuracy. This is because it ‘learns’ in the same way that humans do. It is recommended that further research be undertaken in the following areas Intelligent forecasting methods are being used as an alternative to traditional forecasting methods.

When hearing aids are used in a noisy environment, it is susceptible to noise because built-in microphones alone are used to capture voice. The ultimate goal is to develop a system that efficiently suppresses noise entering a hearing aid by combining multiple microphones located at different positions from the hearing aid. As a preliminary step in building this system, in addition to hearing aid built-in microphones, we placed several microphones between the subject and the conversation partner, recorded under various conditions. And, main microphones and external microphones were evaluated for noise impact and speech intelligibility on a five-point scale. As a result, the evaluation items were scored approximately up to two levels higher, and the external microphone reduced the effect of noise and improved listening comprehension. Therefore, the use of external microphones may solve the problem of hearing aids that have challenges in using them in noisy environments.

The purpose of the work is to identify the stressed state of a person and compare the results obtained by measuring the galvanic skin response and the pupillography method. Within the framework of the work, a pupillographic module for registering changes in pupil size, a hardware-software complex “Activatiometer-6” is used. Before the experiment, we created a situation that was a source of stress. With the help of an optoelectronic system, a video recording of the movement of the pupil was made. In this case, before and after diagnostics were carried out on the device “Activation-6”. The difference between measurements on the device “Activatiometer-6” before and after exposure to stimuli is an indicator of the stress state. In combination with other methods (eye-tracking, vibro-image), it is possible to carry out remote diagnostics of the stress state.

As the elderly age, their hearing deteriorates and it becomes difficult to hear the sounds of daily life. Especially, “TV sound” is hard to hear for one in two elderly people. The cause is that the voice is drowned out by the BGM. In this research, we focus on the volume balance between voice and BGM in TV sound, and propose a volume balance adjustment method using sound source separation technology as a method to adjust these appropriately. In addition, the effectiveness of the proposed method will be evaluated through subjective evaluation. In order to improve your hearing of TV sounds, you need to emphasize them. Therefore, in this research, we propose a method to emphasize the sound by separating the TV sound into voice and BGM by the sound source separation technology, suppressing the gain of BGM, and then reintegrating it. In this study, Spleeter is used. Spleeter is a sound source separation software that uses supervised deep learning. It is mainly used to separate songs into parts, and the input music data can be divided into parts (Example: Vocal/Accompaniment). In the experiment, we used a mixture of voice and BGM as the sound of the TV. (We have prepared two types of voice, “Natural voice” and “Whispering voice”.) This simulated data is separated by Spleeter, and the gain of the BGM after separation is suppressed and mixed again. Eight male subjects in their twenties will be asked to hear the sound before and after processing to evaluate whether the ease of hearing the voice can be improved. As a result, it was found that increasing the ratio of voice improves the ease of hearing the voice. However, it was also found that the distortion generated in the process of sound source separation also affects the sound quality. Therefore, it can be said that it is necessary to improve the accuracy of sound source separation in order to further enhance the effect. In this study, we proposed a method to adjust the volume balance between voice and BGM to an appropriate level using sound source separation technology. In the future, we would like to consider ways to further improve hearing by improving the accuracy of sound source separation.

The main goal of this work is to present a wearable device to assist the visually impaired. This device brings help in navigation and reading tasks, keeping a low-cost, and without an internet connection. The main technologies integrated are Object Detection, Optical Character Recognition (OCR), Text to speech (TTS), and Speech Recognition. It uses a Raspberry pi 3B and complementary accessories in order to accomplish this task. To customize object detection, a SSD MobileNet V2 FPNLite 320 × 320 was re-trained, with images from a public dataset mixed with own images.

In comparison with human body modeling, breast modeling requires more details. As we delve into relevant literature, we found that the mainstream approaches to human body modeling are curve modeling and hybrid modeling. Given the existed approaches to human body modeling, there are three ways to model the shape of breast, which are surface modeling, graphic modeling and finite element modeling. Though the main methods remain to be the surface modeling and graphic modeling, the finite element modeling, which is an emerging technology, has a promising future. Our paper expounds the application of parametric modeling, 2D image generation method and inverse modeling in virtual modeling. In the end, we conclude that inverse modeling is an effective and accurate method at present.

The research objective is to look at secondary education services during the COVID-19 pandemic to determine education services’ effectiveness. The method in this research is Q-DAS (Qualitative Data Analysis Software) NVivo 12 plus. The research data use the Twitter social media activity of the Ministry of Education and Culture of Indonesia. Stages of data analysis with NVivo 12 plus data were taken, data import, data coding, data classification, and data display. The research results show that educational services during the COVID-19 pandemic in Indonesia are ineffective compared to conventional (face-to-face) learning. Online knowledge is only practical for giving assignments. The success of online learning during COVID-19 depends on all school parties’ discipline by making schemes to compile good management in regulating the online learning system. Creating a systematic and straightforward schedule facilitates parent and school communication to monitor students effectively.

Twenty-three male soldiers were exposed to continuous (7 kHz sine wave), non-continuous (irregular 7 kHz sine wave) and no-sound conditions during performance of cognitive tasks on a tablet computer. Tasks were sustained attention to response (SART) task and Baddeley’s 3 min reasoning task. Task performance, workload assessment (NASA-TLX) and emotional responses (pleasantness and arousal) were assessed after each sound-task condition. We expected that disturbing and task irrelevant background sound would interference concentration and cognitive function and therefore have detrimental effect on performance, workload assessment and emotional responses. We found no effects on cognitive performance. However, in connection with subjective assessments, (1) workload was significantly higher during non-continuous sound conditions as compared to continuous and no-sound conditions and (2) no-sound conditions were experienced more pleasant and less arousing than the sound conditions. The results are of interest when considering working in noisy environments, as well as cognitive resilience to interference.

While the role played by air pollution and meteorological conditions on SARS-Cov-2 transmission is still subject of a scientific controversy, we have extended our analysis on this association by studying the impact of particulate on the beginning of the second wave in Emilia-Romagna (Italy), in the period October-November 2020. Again, we found many clues in favour of this hypothesis, with new results that shed a particular light on the time varying effect of the particulate on the virus spread. Specifically, we found a strong magnitude of correlation between the PM10 particulate and CoViD-19 infections, peaking at 6–7th day lags for contagions, while this magnitude drops to a medium level value with 9–11th day lags. This is of special interest, if we consider that the specialized literature suggests a median CoViD-19 incubation period of almost 6 days before that infected people display symptoms.

The paper compares three assessment methods for the measurement of the trunk range of motion (ROM) in flexion-extension movements of subjects suspected of lumbar vertebrae instability (LVI). For five male adults affected by low-back pain and with morpho-dynamic prescription for suspected LVI, ROM was computed: from the analysis of morpho-dynamic radiographs, according to the definition proposed by i) Kapandji and ii) Yang et al.; from the analysis of the flexion-extension movement captured with an optoelectronic acquisition system iii) as the maximum angular stroke in transductors’ displacement, according to a specifically designed custom protocol. Data obtained from optoelectronic acquisitions result comparable with literature values, suggesting the suitability of optoelectronic systems as non-invasive measurement tool for the trunk ROM assessing, to support the physician in the LVI diagnosis.

The purpose of this article was to identify the influence of technology and quality management on the work of nurses working in hemodialysis. The methodology used was field research with a qualitative approach, through the study of multiple cases. Seven nurses participated in the research. The survey was conducted in March of this year. The subject's speech was used for analysis. It was concluded with this research that both technology and quality management positively influence the work of nurses working in hemodialysis. The technology reduces the handwritten workload, optimizing the time to be devoted to patient care. The quality management influence is positive because the standardization of procedures, facilitate the work process of the nurse indicating assertive decisions, search for continuous improvement, reliability and stability in relation to the techniques developed, equipment and resources used by nurses in assistance.

On the current information in the medical area related to cancer analysis, the selection of an optimal Machine Learning algorithm, based on a multicriteria method, for a system that supports clinical decisions is sought. As a methodology, exploratory research and the deductive method were applied to analyze the information from existing articles and ML algorithms' behavior applied in the area of medicine. This research and based on a use case of training and testing of the GLM, SVM, and ANN algorithms for selecting an algorithm. Addition-ally, for clinical decisions, and architecture prototype for medical data collection is presented resulted. Based on AHP and TOPSIS methods Support Vector Machine (SVM) is the best alternative.

Recent years have been characterized by global changes related to epidemic and emergency situations in a number of countries and regions. This requires rapid and adequate changes in the healthcare system. The development of modern technologies contributes to the timely response in supporting people's health in accordance with the imposed restrictive and remote ways of communication. This gives a reason to look at eHealth in a new promising way for modern healthcare. In this regard, the application of Information-Communication Technologies (ICT) and specialized computer software applications in Telemedicine for the needs of healthcare are of paramount importance. This report aims to present modern ways to help people and facilitate their work through the application of advanced technologies.

The superior soft-tissue contrast and sensitivity for pathologies have made magnetic resonance imaging (MRI) a primary modality in medical imaging. At present, the high initial and running costs, and demanding requirements for siting and operating personnel limit its availability to large hospitals and imaging clinics. Improved accessibility of MRI technology can lead into new healthcare services. To study this, we set up the Accessible Magnetic Resonance Imaging (AMRI) research platform, including a multidisciplinary research team and a very low field MRI device for evaluation of new service solutions. We explored the expected value of accessibility in point-of-care contexts, achieving validation and improved focus for initial need-descriptions for the solution. Our design research points towards the potential of a more accessible MRI in improving healthcare provision, and that ever-prevalent medical imaging healthcare services could cause systemic changes to the healthcare processes, technologies, and operating environments.

Keeping social distance is important to contain the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and reduce the risk of getting infected. Some wireless communication technologies such as Ultra-wideband (UWB), Bluetooth, Wifi can help to accomplish that. This work focuses on UWB technology due to its impressive accuracy in location and tracking applications. More specifically, this paper shows the impact of an UWB-based social distancing monitoring system on people’s behavior. The experiment consisted of detecting and registering the events of breaking the social distance policy established at 1.5 m for more than 20 s between 15 people during four days. The main result showed that even if the place has the proper signaling for social distancing, the adherence percentage of the social distancing policy was only 13%. On the other hand, with a real-time audible alert generated by a device of the monitoring system, the adherence percentage increased to 33%.

A worker in an eight-hour workday is exposed to muscle aches or numbness in the legs and fatigue. Matrices were made for the identification and evaluation of physical risks to the population of artisans of marzipan figures in the parish of Calderon in Quito Ecuador, ergonomic evaluation methods were also applied such as: The RULA, Check list OCRA and the NIOSH equation. Five stages that make up the production process were identified: Preparation of the dough, kneading, shaping and finishing, varnishing, and drying, of all these stages the drying process is the most time consuming, the shaping and finishing stage is the one that more work and details requires, the kneading is in which a standing posture is maintained by the craftsman and with repetitive movements. It is necessary to implement a production system with well-defined phases, it is necessary to redesign the jobs that present a high level of ergonomic and physical risk, once the improvements proposed in the project have been applied, it is essential to maintain constant training with the artisans.

Approximately 42 Americans die every day as a result of prescription opioids. Although controlled, opioids remain one of the primary pain management strategies after surgery. This research focused on comparing the efficacy of Virtual Reality (VR) and video interventions against standard care in mitigating preoperative anxiety and postoperative pain among 12 older adults (mean age = 61.5 ± 9.4 years, 8F, 4M) undergoing Total Knee Arthroplasty. On analyzing the survey response, both VR and video groups reported a reduction in pain and anxiety compared to no change among the control group. Further, both VR and video groups showed a significant increase (p-value = 0.01) in time-domain metrics of Heart Rate Variability (HRV), suggesting a decrease in anxiety. However, only the VR group showed a significant reduction (p-value < 0.01) in the frequency-domain metric of HRV and electrodermal activity, reflecting an increased parasympathetic activity. No significant differences were observed in postoperative opioid requirement.

Japan’s aging population is one of the highest in the world, and the need for nursing care is expected to increase more and more. Back pain accounts for more than 60% of all work-related illnesses, and by industry, the insurance and sanitation industry accounts for about 24% of the total. As the correlation between back pain and the physical load of moving and transfer care has been reported in the health insurance industry, measures to prevent back pain among caregivers are an urgent issue. In this research, we will develop a posture determination system for wheelchair caregivers. The system consists of an Arduino Uno and a 9-axis sensor module, and acquires data from acceleration sensors and angular rate sensors. The system is attached to the subject’s body and evaluates the burden during the work operation based on the values of the accelerometer and angular rate sensor. In the experiment with different postures, the frequency of the sensor value exceeding the threshold value under the condition of forward leaning posture is 0.62, which means that the forward leaning posture is a slightly more burdensome posture. On the other hand, in the experiment with different inclinations, the frequency with which the sensor value exceeded the threshold value in the condition with an inclination was 0.78, indicating that the condition is quite burdensome. Furthermore, in the walking experiment with different walking speeds, the frequency with which the sensor value exceeds the threshold under the condition of fast walking speed is 0.40, indicating that the walking speed does not affect the physical burden during the work.

Our ability to bite and swallow declines with advancing age, and the risk of aspiration increases. In this study, as premises for the development of an aspiration prevention system, we will detect mastication by chin movement from moving images. At the same time, we will count the number of times that a person masticates simply, and think about validity of this method. In order to detect mastication, we focused on the time variation of the distance between the point at the tip of the nose and the chin. First of all, we start to detect face organ points. From them, the distance between the two points is calculated for each frame. When it exceeds the threshold, it is regarded as the mastication. At this time, we apply a moving average in order to increase the robustness of outliers. As a result of the experiment, the detection frequency of “mastication as usual” were close to the actual frequency. Similarly, it can be said that we could detect “mastication slower than usual” almost exactly. However, violent noises occurred frequently in “mastication faster than usual”. They are thought to be the aftereffects of the blurring of the image caused by the intense movement of subjects in the stage of detecting the face organ points. Besides, unclear chin movement made the detection difficult.

Motor imagery training is commonly used for sport and neurorehabilitation, improving human motor performance. In our previous works we have shown that motor imagery can be an effective way to reach higher performance in some sensorimotor tasks, technically related to esports. In this work reaction time of 10 participants was measured in the mouse aim task before and after motor imagery training session, while EEG was recorded. Statistically significant decrease in reaction time between before and after motor imagery training was obtained, while stable contralateral central ERD patterns during motor imagery were presented. A high correlation between baseline reactions’ time of participants and their levels of progress was observed. We believe that motor imagery training associated with sensorimotor rhythms desynchronization in EEG has great potential for esports training programs.

Over the years, manufacturing companies have become an influential factor in the country's economy, 95% of them being small and medium-sized companies. However, many are not competitive due to low labor productivity that affects their production levels and the fulfillment of their demand; Furthermore, they lack the knowledge or resources to solve these problems. This research was carried out in view of the need to take advantage of human resources in a manufacturing SME, for which a micro-level production management model was proposed aimed at improving the production area by evaluating the anthropometric posture-base measurement of the operator, redesigning the production area and conducting a time study to improve the company's labor productivity. Through the simulation in the Arena software, an increase in labor productivity was achieved by 25%.

The article presents a method of mathematical computer analysis of the state of the main regulatory system of the body - the autonomic nervous system in patients with thyroid diseases. A formula has been proposed that allows one to calculate the severity of impairments in the regulatory system and the degree of stress (depletion) of adaptive mechanisms - a single vegetative index (SVI). Using the method of computer modeling, the boundary values of this indicator were determined and the effectiveness of its use was tested on a group of patients (26 people) diagnosed with thyroid diseases. The results obtained confirmed the effectiveness of using the method, both for assessing the current state of the body, and for determining the safety of the functional reserves of the body and predicting the course of the disease.

The mobile device ownership rate of the elderly is rising, but there are few suitable specific design principles. In addition, assessing an elderly-centered design's usability and social benefits is challenging, but the existing human-computer interaction does not fully support it. By making it easier to obtain digitalized life through mobile devices, the elderly can gain more benefits. This project aims to fully understand the needs of the elderly by investigating the current aging trend in China's society and the living conditions of the elderly and designing and developing a digital interface based on cognitive psychology theories that promote it to different communities and hospitals. This study produces two application concepts for the elderly on various platforms, including mobile phones, tablets, and wearable devices. In a social sense, such products can increase attention to the elderly, measure the mental health of the elderly.

The increasing number of total hip arthroplasty and the demographic change lead to a rise in the number of revision surgeries. Implementation of musculoskeletal models in surgical planning could improve quality of life after revision surgery, due to the consideration of the individual patient’s biomechanical conditions. In multibody simulation, a distinction is made in the degree of individualization between the anthropometric and patient-specific scaling of musculoskeletal models. In this study, the differences in moment arm length, hip joint reaction force, muscle activation and forces between these two musculoskeletal models were analyzed. Due to high influences of individualized anatomical parameters on simulation results, it is recommended to consider patient-specific biomechanics for future total hip arthroplasty planning.

This article presents a numerical work on the occupants’ comfort conditions of a building where passive and active solutions have been implemented. The comfort conditions are evaluated using a software based on the human thermo-physiology, used to simulate the human thermal and thermoregulatory and clothing thermal response. The building has constructive characteristics that allow it to use solar radiation as a passive solution. As an active solution, it is proposed to operate the Heating, Ventilation and Air Conditioning system through the control of the occupants’ thermal comfort level. The whole building thermal response in transient conditions is obtained by a research software. The indoor thermal comfort and the indoor air quality were obtained for all occupied spaces. The implemented control system uses the Predicted Mean Vote index as a control variable. The obtained results show that the adopted solutions allow to improve the thermal comfort level of the occupants.

Robotic systems have been effectively used in healthcare while a new role for them has emerged during the COVID-19 pandemic. Robots were used as part of prevention, screening and diagnosis of the disease, but also to assist with the treatment of patients. The purpose of the paper is to provide an overview of the relevant applications for robots and highlight their potential.

The 3-Dimensional (3D) printing in footwear has become a significate development direction. Researchers have found that providing a suitable insole can combat pain and help to avoid fall-related injuries. Therefore, many research projects focusing on insole designs and functionality were conducted. In contrast, a midsole design for footwear has not been adequately developed in functional footwear. A lot of footwear research projects looked at insole or midsole modification but did not include a changeable drop-in sole inside the midsole. Different softness and construction of 3D-printed midsole were developed to simulate the foot comfort and biomechanics measurement. The changeable 3D-printed midsoles can increase comfort and flexibility for customization in functional footwear. The current study demonstrates functionality and flexibility simultaneously for footwear design in terms of comfort control. Footwear consisting of different 3D-printed midsole structures that improve comfort can decrease injury frequency. Consequently, the midsole providing a comfortable, soft, and movable dual-density footbed is critical to wearers.

In order for industrial companies to continue to succeed in dynamic, globalized markets, they must be able to train their employees in an agile manner and at short notice in line with the exogenous conditions that arise. For this purpose, it is indispensable to operate a proactive competence management system for employees that recognizes qualification needs timely in order to be able to address them promptly through qualification measures. However, there are hardly any approaches to be found in the literature that include systematic proactive competence management. In order to help close this gap, this publication presents a process model that systematically develops bottom-up, future-oriented target competence profiles based on the tasks of the employees. This process model provides industrial companies with a tool that they can use to determine the competencies required by their own employees in the future and compare them with the prevailing actual competencies.

Open innovation is becoming the frontline strategy to develop new products and services in most R&D based firms. This paper focuses on the strategies of the companies which protect their R&D capabilities and their effect on the open innovation process in new product development. The theoretical framework of this research was extracted from open innovation, product development and management science literature. Data from 20 countries have been collected from 60 open innovation and intensive R&D dependent firms. Statistical techniques were used to analyse the data. The data analysis showed five protectionist motives involved in open innovation-based product development between companies. The results provided the validation of the theoretical framework and explored these motives based on managers' feedback. The study implies strong linkages between open innovation, product development and protectionist motives of companies.

To inform, guide and optimize the design of cyber-physical systems (CPS), this study examined whether and how delayed visual feedback affects human fine-motor skills. Two experiments are presented, in which participants performed a complex motor task with their hands. During the task, visual feedback was provided on a display with varying delay lengths. Further, to investigate effects of adaptation and transfer, some participants were first exposed to a fixed delay before performing the task with varying delay lengths. Results show that independent of earlier delay exposure feedback delays had detrimental effects on performance, particularly when performance information was lacking and delay length variable. Hand kinematic indicate the use of a strategy geared to a slowing of the movement process. Implications and future research ideas like the application of augmented feedback on movement kinematic and the examination of different settings to promote adaptation effects are discussed.

This article presents a numerical study where the thermal responses of a tree and a fireman are compared, both inserted in a forest fire environment. The three-dimensional pine tree model is constituted by 1039 cylindrical elements to represent its trunk, branches and leaves. The human body model is divided into 35 elements. Each element is subdivided into several layers, constituted by fat, muscle, core and skin, and can be shielded from the outside environment by several clothing layers. The tree and fireman thermal response numerical models are based on energy and mass balance integral equations. In the last one the thermoregulatory system is also considered. Both systems consider the phenomena of conduction, convection, transpiration and radiation. The tree and the fireman are placed nearby the fire front, which represents the forest fire. The surface temperature of both bodies is analyzed on a steady-state and transient regime.

Currently, companies engaged in maintenance and repair work are being affected due to the gradual increase in delays in their services. Consequently, an important economic impact has been generated in the sector, which is reflected in a 21% increase in its operating costs. After reviewing the literature, little information was found about the sector, due to which, the motivation is to carry out the study of a service SME in Lima, Peru. The proposed solution model comprises four phases: in the first phase, change management is developed, in the second phase, a study of the work is carried out, in the third phase, inventory management is applied, and in the last phase, they are standardized. The procedures previously developed. Based on this, it is possible to reduce costs by up to 12%, as well as reducing the number of delays by 15%.

Psychosocial risks in the workplace result from the nature and organization of work, interpersonal relationships in the workplace and the balance of work and family life. We decided to conduct the research project to identify and assess the psychosocial risks in the sector of postal services in the Czech Republic. In cooperation with trade unions a special questionnaire with 25 items was prepared and administered to employees of the postal services in the Czech Republic from February to November 2020. To date, a preliminary analysis of 648 questionnaires was made. These results show some signs of the psychosocial work-related risks (verbal violence from clients, dissatisfaction with financial evaluation, shift work and poor quality and quantity of sleep) but also some positive findings (interesting work, use of skills, sufficient managerial appreciation, good health protection).

This paper points out that we have devoted too much time and efforts in the artificial world, and we have forgotten the natural world. But the Real World comes to change frequently, extensively, and unpredictably. Therefore, to cope with this Real World, we need to perceive it correctly and make adequate decisions. We need to work together with machines on the same team. To achieve this goal, we need to introduce nonverbal approach and movement plays an important role. It is a nonverbal communication tool and enable us to be intelligent in the original sense.

The maintenance service sector shows continuous growth since the incorporation of machines for the development of operations. However, in Peru, the type of service they provide does not meet certain essential aspects to satisfy the demand, due to the excess time in the attention of the services and arrival at the wrong time for the attention. That is why the main objective of the project is to reduce the lead time to comply with the annual schedule, since there is a loss of 33.44% of the billing of the maintenance service for the year 2019. For this reason, a model is designed of maintenance service management that includes the assignment of the route by the Vehicle Routing Problem through the Euclidean distance and the standardization of processes through the study of times. Finally, it has been possible to reduce lead time and comply with the maintenance schedule.

The Department of Construction Economics, University of Pretoria, offers three-year BSc programmes in Quantity Surveying (QS) and Real Estate (RE) and use an Admission Points Score (APS) of 30, based on school performance as the main entry threshold. The validity of the current threshold requirements is being reconsidered to improve first-year students' marks and the throughput rate of enrolled students. A 2020 study found that undergraduate performance (average first-year marks, likelihood to qualify in three years and to qualify with distinction) amongst QS students from 2010 to 2015 strongly correlated with higher APS and better school marks in Mathematics and Natural Science. This new study considered the performance of RE students against their APS as the independent variable. For both RE and QS students a higher APS correlated with better first-year performance, but for average first-year marks and for students who managed to graduate, the gradients of the regression lines were steeper for RE students than for QS students. The findings will assist informed decisions about amending future entry threshold levels and add to our understanding of the relationships between school-level performance and undergraduate performance.

Lean manufacturing and Constraint Theory (TOC) are tools that specialize in continuous improvement. The proposal focuses on obtaining the best result by executing the 5 phases of the Thinking process, an introductory tool to TOC, which, hand in hand with Lean Manufacturing tools, will be responsible for eliminating activities that do not add value to the process and optimize the process. In this way, the improvement proposal is applied to the cement industry in Pisco, Ica. This industry poses a growing demand, being directly affected by low productivity compared to other cement companies. The following research develops from the need to improve productivity, as well as to increase the production capacity and competitiveness of companies in the construction segment. In such matter, these methods will reduce high inventory costs, unmet demand costs, low level of service and logistical cost overruns, among other problems that the company is dealing.

This study mainly analyzes the increase in food and beverage (F&B) costs and its economic impact on business. Likewise, the related indicators that would cause this main indicator to increase were studied. The study was conducted and validated using a procurement simulation process of a specialized restaurant company belonging to a restaurant group. The results showed that the model proposed in the study reduces by 1.73% the main indicator of F&B cost; in addition, the related indicators are presented. Therefore, it can be confirmed that poor management, poor control of resources, such as supplies, and the absence of procurement strategies generate an excessive supply of resources to the restaurant or cause the loss of some supplies.

In recent years, production environments have gone from predictable to dynamic, therefore factors such as delivery time and a high percentage of customer satisfaction have become fundamental criteria for this new environment. Production planning and control (PPC) systems must be aligned with the new objectives of the manufacturers, however, the most popular PPC don’t satisfy their needs. This is how this article proposes a PPC model based on the Demand-Driven MRP system supported by the stages of the PDCA cycle so that it can perform optimally in dynamic environments such as make-to-order manufacturing models. As a result of the simulation in the case study, 100% compliance with deliveries on time was obtained and a reduction in lead time by 50.33%. Therefore, it is concluded that the proposed model is applicable and beneficial in this context.

In response to China’s innovation-driven development strategy. The course development team is developing a course on innovation and entrepreneurship education. The course guides students to break through their professional limitations and develop creative thinking from multiple perspectives and at a deeper level. The team breaks away from the previous “teaching and learning” pattern and combines virtual simulation technology to develop an online teaching platform. The team develops virtual simulation modules and designs immersive interactive teaching classes and scenes based on the existing creative thinking courses. Explore the application of virtual simulation technology in online teaching, building a new innovative co-construction pattern, co-management, and sharing of universities, scientific research institutes, and enterprises. Create a virtual simulation service support system with independent intellectual property rights, high market utilization, a wide range of applications, and realize the open sharing of educational resources.

Staff turnover is a consistent threat for companies, as the cost overrun generated by each rotated employee may be between 80% and 130% of an average salary. In Peru, small and medium-sized companies in the service sector have the highest turnover rate (19%). Therefore, it is necessary to strengthen the management of human talent within such types of enterprises and establish relevant mechanisms to curb or reduce the significant predictors of staff turnover. Thus, this paper proposes a system composed of three processes: Workload Distribution, Professional Growth and Development, Compensation and Rewards. For the conceptual validation, experts agree that the probability of success of the expected results of the system is greater than 75%. It can be concluded from this that the proposed system would reduce the probability of employees of SMEs in the service industry leaving the workplace.

The article highlights the academic and applied aspects of youth policy development in higher education institutions. The authors analyze the experience of the Faculty of Social and Psychological Education of Pavlo Tychyna Uman State Pedagogical University according to the educational and methodological support of educational subjects “Social Youth Policy”, “Social Policy”, “Youth Work”.

Modern trends in the development of Ukrainian society have brought to the forefront of public life the problem of citizenship - both as a quality of society and as a quality of an individual. The development of democracy is inextricably linked to increasing the level of citizenship of society in general, and young people in particular. The problems of young people are always in the center of attention of teachers, public figures and politicians. The purpose of the study is to theoretically substantiate the features of youth work in a higher education institution (from the practical experience of the youth center “START”). Research methods: theoretical (systematic, normative-legal analysis of sources, content-analysis of documentation on youth work); empirical (quantitative - questionnaires, surveys; qualitative - conversation, structured interview to determine the level and needs of student youth).

This study is aimed to evaluate the comprehensibility of 40 safety prohibition signs in accordance with China’s current national standards and their relevance to three ergonomic principles (familiarity, physical representation, and conceptual compatibility) of sign design, thereby discovering signs of poor comprehensibility. Twenty elderly people aged 60 and above were included in this study for the sign comprehensibility test and ergonomics principles evaluation test. The results revealed that there were 13 signs with a correct comprehensibility rate of 0, and no signs had a comprehensibility rate of greater than 67% specified in ISO 3864–3 (2006). A lot of signs with poor comprehensibility need to be redesigned, which should abide by ergonomics principles, thereby improving people’s comprehension. This study can provide a sound theoretical basis for researchers and designers when improving these signs to design comprehensible signs for safety enhancement.

Based on a systematic literature review, this study aims to survey applications regarding how the concept of “downstream” is used. Taking as a starting point the research question: “Based on scientific literature, in which areas is downstream used?”, it will leave us to obtain a more accurate image of the areas which make use of “downstream” and in what context. Considering the documents found, a descriptive analysis was attained, allowing a ‘big picture’, and then a set of documents were selected for critical analysis. To complement the analysis, bibliometric maps where developed for the co-authorship and co-citation networks, allowing the identification of clusters for authors’ countries considering documents’ weights and density by item and keywords. Based on the score of the keywords by average of occurrence by publication year, it is possible to visualize their use over the years. The results show a current trend in the use of “satellite data” and “imagery” and “downstream applications”.

Project in the process of scientific research to identify the typology of productive chains and business vocations of the ecosystems of economic development in the populations of the Baja California Peninsula and with it the relevance and integration of the engineering careers of the Tecnológico Nacional de Mexico Campus Tijuana [1] in the region. With the purpose of strengthening sectoral ties, social and regional development. The research will be carried out in the cities of Tijuana, Ensenada and Mexicali through the methodological proposal for the construction of variables of an Observatory for sectoral systemic analysis. The research focuses on two areas of interest; the relevance of the study program of the TecNM [2] engineering careers in the region. First, identify the professional competencies of the Engineers who intervene in the supply chain within companies and manage local supply as a competitive strategy in the regional economic development ecosystem. The second approach is the factors that intervene in entrepreneurship such as MSMEs in the strategic service [3] sector as a key strategy for promoting local supply as professional development of engineers graduated from TecNM in the Baja California Peninsula. The results of the research will define the bases to develop an Observatory for the integration of engineering in the ecosystem of economic development of the Baja California Peninsula, generating inputs from the research indicators called Dictionaries of Professional Competences [4] of the careers of engineering, as well as the conditions to develop a sector linkage and continuing education program that aligns with the needs of the institutional development plan and the state development plan that links the Tijuana Technological Institute, offering professional updating activities with internship activities of social service, professional residencies and postgraduate research projects for theses [5].

The development of this scientific research project with a descriptive scope with documentary analysis to support the theoretical framework to determine if there is a relationship between the variables that have an impact on the degree of visibility and evolution of the Sustainable Development Goals (SDG) of the UN 2030 [1]. Goals and the implementation of the Circular Economy in SMEs in Baja California, as well as the Social Economy and Social Innovation undertakings and practices. Through the systemic methodological application as a reference index and sector feedback, from the Tecnologico Nacional de Mexico Campus Tijuana [2] to society through a Web Page. That it can provide information on the detection and evaluation of the evolution of the SDGs to identify opportunities, programs and actions to develop; evaluate the critical factors that promote social innovation and sectoral articulation for the benefit of society and the different levels of education; strengthening the skills of future generations.The results will provide necessary information that may be useful for awareness-raising and technical assistance actions at the local level for the development of capacities of SMEs and competence laboratories in Technological Higher Education, Higher Secondary Education and Basic Education. Likewise, to society in general by means of linking and social service through the linking of different sectors such as the Government, Academia, Companies, Associations and sectoral specialists.

This applied research initiative is aimed at developing actions to strengthen sectoral competitiveness, the experience generated in the productive vocations of each region of Mexico [1], the frame of reference of investigations developed in the Technological Institutes at the national level. The objective is to develop the model for the design and development of the Dictionary of Sector Competencies (DCS) [2]. The application of a sectoral integration methodology will facilitate the identification of needs from a comprehensive approach and of relevance according to the competencies required in each productive sector, whether public or private.; DCS arises from the sector of technological higher education, considering the relevance of the Tecnologico Nacional de Mexico [3] Campus Tijuana [4] towards innovation. According to the 2017 report of the Organization for Economic Cooperation and Development (OECD) [5] on skills in Mexico. The research in this article proposes the design of competency standards according to the different levels established by ISCED-UNESCO, in the specific case the competences of level 6, 7 and 8 [6], as well as the national model and the effective methodology to move to the next stage of development of the sectors, The goal is to design and propose methodological alternatives to develop competency standards that cover business requirements for job performance and aspects of professional development, considering management skills strengthened with applied research, based on the study plans of the Tecnologico Nacional de Mexico. Tijuana campus.

Nowadays, huge amounts of data are generated every second, and a quantity of that data can be defined as sensitive. Blockchain technology has private, secure, transparent and decentralized exchange of data as ‘native’. It is adaptable and can be used in a wide range of Internet-based interactive systems in academic and industrial settings. The essential part of programmable distributed ledgers such as Ethereum, Polkadot, Cardano and other Web 3.0 technologies are smart contracts. Smart contracts are programs executed on the global blockchain, the code is public as well as all of the data managed within the transactions, thus creating a system that is reliable and cannot be cheated if designed properly. In this paper, in order to make the educational system more transparent and versatile we will describe an educational learning platform designed as a distributed system.

The paper presents mathematical models of students’ independent work, which is the dominant component of the educational process, both in its volume and in its didactic significance. These models are based on probability theory and set theory. As part of the research of the independent work of students in the conditions of the information and educational environment at university, a pedagogical experiment was conducted at Kuban State Technological University and Krasnodar Cooperative Institute (branch) of the Russian University of Cooperation, both located in the city of Krasnodar, Russia. The undergraduate students involved in the research entered university in the period from 2014 to 2016. As a result of the analysis of empirical data, a matrix reflecting the relationship between the success of students’ classroom work and independent work has been obtained. The authors have developed information and probability models that reflect the relationship between classroom and independent work of students.

Road damage on highways and freeways lead to numerous construction sites and maintenance activities every year, causing congestion, increased environmental pollution and costs. In addition, road damage exposes road users to an increased risk of accidents. The EU project ESRIUM aims to help reducing both the number of road works and the associated problems by using new digital services for intelligent road infrastructure use and predictive maintenance. The aim of this study is the presentation of four use cases and the elaboration of non-technological requirements of the offered digital services, which should lead to a deep understanding of the requirements of all stakeholders in the early phase of the project.

This article presents a numerical study on the thermal response of a trunk tree, in a forest fire environment, provided with an incorporated water control system. This numerical control system activates the water system when the temperature rises above 60 ℃. The numerical model of the trunk tree is based on energy balance integral and differential equations. The virtual trunk tree geometry was developed used adaptive mesh generation. The numerical simulation was made for a fire front propagation at a constant fire spread rate of 0.01 m/s. The temperature distribution in the pine tree trunk, obtained for a flame temperature of 500 ℃, will make it possible to identify the areas of the trunk tree that will reach temperatures that will trigger the control system. The results show that the water system will mostly be activated when the fire is on the upstream side of the tree trunk.