Human Interaction, Emerging Technologies and Future Applications II

Experience design and engagement is evolving to become the design of presence with the supporting practices and tools of SenseMapping, CC-Align, Experience Vision and Scenario-Based Design Methods.

Intelligent machines can follow ethical rules in their behaviour. However, it is less clear whether intelligent systems can also create new ethical principles. The former position can be called weak ethical AI and the latter strong ethical AI. Hume’s guillotine which claims that one cannot derive values from facts appears to be a fundamental obstacle to strong ethical AI. The analysis of human ethical information processes provides clarity to the possibility of strong ethical AI. Human ethical information processing begins with positive of negative emotions associated to situations. Situations can be seen as consequences of actions and for this reason people can define rules about acceptability of typical actions. Finally, socio-ethical discourse create general ethical rules. Intelligent systems can provide important support in ethical process and thus the difference between weak and strong ethical AI is polar.

We explored the possibility of taking icons from Android Smartphones, for the use in graphical user interfaces (GUI) in bakery sheeter. This idea was generated from the fact that Android Smartphones are sold worldwide and that the icons used in the menu should have a degree of popularity that most people could deal with. With this research question in mind we created a mixed method design for the study (qualitative and quantitative data). Results show that some icons were able to represent basic navigation function in industrial machines.

In a dynamic and ever changing business landscape organizational sustainability is defined and redefined according to the socioeconomic challenges. This paper presents a practical framework that can significantly support organizational efforts on approaching, achieving, sustaining and improving its environmental, social and governance (ESG) strategies, objectives, and targets. The proposed framework, referred to as DESGGO (Democratic ESG Green Ocean) is based on the Company Democracy Model (CDM), covering the ESG governance elements/factors. Furthermore, the paper introduces a synergetic relationship between Corporate Social Responsibility (CSR) and ESG indicating the evolution of an organization to extend from applying outstanding governance practices, which lead to Blue Oceans, into outstanding social and environmental practices which lead to Green Oceans. The paper analyses the main ESG criteria per category and maps them on the DESGGO, six ESG and CSR progression levels moving the organization from Red to Green Oceans by adapting ESG practices.

This paper presents an AcciMap of the Edinburgh Tram Network (ETN) project delivery failure in Edinburgh, Scotland. The AcciMap is used to show how various factors contributed to the ETN delivery failure. The paper starts with the historic background of the ETN project, followed by the AcciMap output of the ETN project failure.

The present study focuses on visual scanning techniques of expert and novice helicopter pilots during an open sea flight simulation in two different workload conditions. Twelve helicopter pilots were involved. Mental workload was assessed through psycho-physiological (EDA and HR) and psychological measures (NASA-TLX). The pilots’ performance was assessed. Eye movements were recorded to analyse the differences in visual scanning techniques. More fixations were made OTW than ITC, but it did not differ between groups and conditions. Fixations were longer OTW than ITC, and they were shorter in high cognitive demand condition than low cognitive demand condition. Higher number of fixations was recorded on the centre line during landing, and on the instruments during cruise phase. The research highlighted that external conditions might change the visual scanning strategy of pilots. The implications for a new visual landing system design, as well as the limitations of the study are ultimately discussed.

Kansei is a Japanese term referred to human feelings activated at emotional level, once in contact or relation with a particular object or context. The Kansei Engineering (KE) method developed by Mitsuo Nagamachi in the 1970s introduced the kansei approach into design community for the first time. In this regard, Kansei Design (KD) is a novel holistic approach to users’ perceptions at cognitive level which seems appropriate to applications in architectural design. Scope of this paper is to investigate about specific approaches and methodologies currently adopted in KE and KD, which are mainly focused on intrinsic characteristics of artefacts, and their possible extension to applications in the fields of Architecture and Built Environment in terms of emotional quality of forms and spaces.

One major challenge in Mergers and Acquisitions is the best possible utilization of the human resources organizations offer. The judgment on employee redundancy is often highly controversial and risky. It can impact the motivation of the remaining employees, the corporate culture, and the reputation of the firm in the market. This paper addresses this challenge by introducing the Democratic Employee-Culture Fit Model (DeECFit) for Post-Merger Corporate Restructuring to avoid downsizing practices and maximize the utilization of the available human resources and intellectual capital. The model describes the relationship between the definition of the cultural values and the concentration of democratic values needed for an employee of either company to effectively join the Merger and operate under a symbiotic model by utilizing their human recourses. The democratic approach of the DeECFit Model provides the opportunity to all employers from both organizations to prove and justify their place in the Merger.

Proposal of interview survey method to extract cultural traits applicable to concept design using disaster prevention a case study.

The article explores the features of the manifestation of the human factor in the development of human-oriented technical and production systems and products, the use of cognitive methods to solve design problems and assess the impact of the design processes of human-oriented technical systems and products on the development of human and social capital. It is proved that the conditions (including the manifestation of the human factor) in which modern advanced manufacturing, technical and production systems are created are determined by the processes of NBIC convergence that have begun and the formation of the new technological paradigm. A method for assessing the growth of human capital based on the information characteristics of the designed systems and products is proposed.

This paper presents a novel two-degree-of-freedom (two-DOF) passive damping system dedicated to the vibration suppression of a dual-axis precision force sensor. The damping system consists of two identical eddy current dampers (ECDs), each of which utilizes a double-layer Halbach-array permanent magnet (PM) structure and a middle-layer copper plate to generate a large damping force. Analytical models are established to predict the damping characteristic of the ECD. The finite element simulations are conducted to verify the effectiveness of the analytical models. The simulation results indicate the large damping coefficient of the developed ECD.

Many businesses enhance on-line user experience using various recommender systems which have a growing innovation and research interest. Recommender systems in music streaming applications proactively suggest new selections to users by attempting to predict user preferences. While current music recommendation systems help users to efficiently discover fascinating music, challenges remain in this research area. This paper presents a critical analysis of current music recommender systems and proposes a new hybrid recommender system with efficient and enhanced prediction capabilities.

This paper evaluates the physiological and psychophysical response of mothers carrying their own baby using three different front baby carriers. Eleven mothers (aged 28–37 years) with their own baby (weight: 9.18 ± 2.1 kg) participated in this study. Maximum right shoulder pressure was measured before walking. The electromyography (EMG) and skin temperature of the shoulder and abdomen area were measured during walking. Immediately after walking, the Borg’s rating scale of perceived exertion was used to collect discomfort ratings at various body parts. The results were similar in all response factors to our previous study, which used a convenient sample of women and dummy doll. However, with further comparison, mothers showed significantly lower EMG activities and all Borg’s scales, but higher temperatures apply in both shoulder and abdomen areas. In conclusion, Type A, B and C carrier performed similar in either mother or women, but in mothers the effect was smaller in most responses.

This paper presents a comparative study amongst the three main frameworks acknowledged for designing trust in AI; specifications, principles and the levels of control necessary to underpin trust in order to address the rising concerns of Highly Automated Systems (HAS). We will also address trust design in four case studies specifically designed to address the rising concerns of these systems in the area of health and wellbeing. Based on the results, levels of control emerge as at the most reliable option to design trust in Highly Automated Systems, as it provides a more structured focus than specifications and principles. However, principles enhance philosophical inquiry to frame the intended outcome and specifications provide a constructive space for product development. In this context, the authors recommend the integration of all the frameworks into a multi-dimensional cross-disciplinary framework to build and extend robustness throughout the entire interactive lifecycle in the development of future applications.

In 2012 the United States passed legislation, penalizing hospitals for readmission of patients discharged within 30 days. However, many unknowns mean that hospitals cannot predict when each patient is appropriate to discharge. Through researching readmissions across the Thomas Jefferson University Hospital enterprise, we found that staff must make judgement calls based on their own clinical perspectives. Rather than expecting doctors to somehow intuit the interaction effects from thousands of variables, we surface trends and present strategies for mitigating readmission risks through machine learning (ML). Commonly, ML models are trained against data aggregated from various sources. This method of sourcing interferes with responding to population-based risk factors and variables that are specific to the hospital of interest. However, creating a custom model presents its own set of hurdles. The work of our team provides hospitals everywhere with an end-to-end pipeline to create a readmissions assessment tool, using their own data.

The article deals with current problems of IT and sets up a new view of semantic memory as a base for artificial intelligence system. The explanation of object defined as a language, not as a data, leads to linked semantic objects and memory sizing paradox.

In order for indoor positioning services to be able to assert themselves across a broad front, simple processes with minimal costs and low user resistance are preferable. This is where our contribution kicks in: We present a method to detect individual positions within buildings by the use of locally induced distortions of the earth’s magnetic field with a smartphone alone, without any additional technology to locate the 2D position. To compensate for the lack of exact 2D coordinates, we fuse the sensor data into a gravitational magnetic vector (GMV) and perform a temporal classification based on a recurrent network. In this work we investigate the applicability of Long-Short-Term-Memory (LSTM) networks to find cross-correlations over a time frame. The trained models are available in a smartphone application. With this application the recognition rates of the locations are analyzed.

In recent years, the existence of open source software (OSS) is indispensable for software development. While developer can benefit from functions of OSS, there is a problem that it is very difficult to locate the cause when problems occur. In this study, we propose a method to calculate anomaly score for each line of log data. In our method, the temporal pattern is learned using Hierarchical Temporal Memory, which is an unsupervised real-time learning algorithm, and the anomaly score is obtained based on the internal state of the model. In the experiment, we compare the learning situation in the following three input formats, word ID, word embedding, and sentence embedding. In the experiments using actual log data, it was found that the method with word ID has the highest f1 score and runtime performance, but the precision needs to be improved in order to suppress useless information.

Early brake pedal operation and corresponding vehicle deceleration are crucial to mitigating rear-end collision risks. In this paper, a mathematical model, hereafter referred to as the deceleration intention inference system (DIIS), was developed to facilitate determining the intent inferences of driver deceleration behaviors. More specifically, a conventional neural network model was integrated into an unscented Kalman filter in an effort to describe the deceleration intentions that can be expected to occur a few seconds later. The numerical examples provided herein show that our proposed model is capable of inferring driver intentions more precisely than the conventional approach.

Satellite-based vessel monitoring systems (VMS) have been widely deployed on fishing vessels for monitoring and surveillance. In this study, we aim to enhance the classification of fishing ship trajectory from the VMS data. We propose a recurrent neural network (RNN)-based approach for discrimination of fishing vessel types from ship trajectories. Our proposed method first eliminates data points that are meaningless by identifying groups of data points describing ship movements using a density-based clustering strategy. We then generate local trajectories and compute a feature vector for each identified group as input for RNN. Finally, we train RNN models to learn high-level representation of ship trajectory for the task of classification. Experiments conducted on real-world VMS records among three fishing ship types: trawl, purse seine, and falling net demonstrate the effective use of RNNs and bidirectional GRU performs the best performance with 89.74% accuracy.

Project accidents, especially accidents and disasters in the industrial sector continue to occur, in most cases with tragic consequences involving the loss of lives [1]. Long-term research shows that there is a vital need for application of systemic cause-consequence analysis techniques that embrace all aspects of the system [2–5]. Such analyses aim to provide safety by finding ways to prevent potential accidents in large-scale projects [6, 7]. This paper analyses the cause of a large explosion that occurred during the construction stage, at the Kleen Energy power plant project in United States, on 7th of February 2010 [1, 8–10]. To this end, a causal analysis of the project explosion has been conducted based on Rasmussen’s [11, 12] AcciMap technique. The AcciMap is a systemic accident analysis technique, which is focused on the performance of the system as a whole [4, 12, 13].

The research objective is to discuss the adoption of the wavelet transformation method (WT) in processing time series, for its efficiency. As well as comparing modern methods represented by wavelet and neural networks with traditional methods represented by Box-Jenkins models, to better diagnose the treatment of any series, whether (linear, semi-linear or non-linear), a way to minimize the error to the nearest zero value, through the use of error accuracy measurements to diagnose the best method among classical and modern methods, some of them are characterized by artificial intelligence (IT) to measuring the accuracy of best forecasting methods in time series. Artificial neural networks (ANN) also used as one of the uses of artificial intelligence (IT) for best results. statistical error criteria have been adopted for comparing and evaluating the efficiency of the methods adopted: (MSE, RMSE, MAPE), Mat lab 8th edition was used. An important conclusion reached, was finding the best technique that minimizes the error to its lowest value with an average error close to zero significantly.

Today it is important to reduce the time spent on exploratory research. To achieve the goal, problems are solved from the field of computer science and cybernetics, which are interdependent. The article proposes new theoretical approaches to the mathematical representation and visualization of moving the working point of the exploratory research process along the planes of the xyz coordinate system. For this, formulas were obtained for the speed of movement of the working point, which reflects the course of the exploratory research. They were obtained using differentiation of the formulas of the dependences of the probabilities on the flow intensity and the time taken to complete the stages of exploratory research on time. To do this, in the theory of the article, a stream of scientific information was appropriately introduced, which changes at each stage. The flow of scientific information can be expressed through useful knowledge for solving the next stage, obtained during the execution of the current one. The results will help to express qualitative indicators of effectiveness and quantitative indicators which are depending on time t.

Networks and informational technologies caused mammoth growth of knowledge volume and sophistication. Serious cognitive and educational problems of scientific big data understanding have arisen. The part and parcel of coming system-informational culture is inter-disciplinary activity based on labor with meanings ensuring knowledge integrity and obviousness. Presented by the utmost mathematical abstractions they are formed by genus in natural science knowledge. Cogno-ontological knowledge base (CogOnt) as core of these scientific presentations consists of them. Achieving personal transcendentality by means of self-reflection secures cognogenesis success. Man’s life-long partnership technology with deep-learned artificial intelligence (DL IA) is contributed to do it. In order to carry out subject’s auto-poiesis (rational self-building) it is impossible to do without continuous assistance of DL IA using CogOnt and applying axiomatic method. Elaboration of CogOnt for DL IA implantation is displayed on example of some universalities study.

The reinforcement learning approach allows learning desired control policy in different environments without explicitly providing system dynamics. A model-free deep Q-learning algorithm is proven to be efficient on a large set of discrete-action tasks. Extension of this method to the continuous control task usually solved with actor-critic methods which approximate a policy function with additional actor network and uses Q function to speed up policy network training. Another approach is to discretize action space which will not give a smooth policy and is not applicable for large action spaces. A direct continuous policy derivation from the Q network leads to optimization of action on each inference and training step which is not efficient but provides optimal and continuous action. Time-efficient Q function input optimization is required in order to apply this method in practice. In this work, we implement efficient action derivation method which allows using Q-learning in real-time continuous control tasks. In addition, we test our algorithm on robotics control tasks from robotics gym environments and compare this method with modern continuous RL methods. The results have shown that in some cases proposed approach learns smooth continuous policy keeping the implementation simplicity of the original discreet action space Q-learning algorithm.

The cooperative operation of soft and hard weapons is very important in air combat. Firstly, aiming at the distributed and intelligent characteristics of soft and hard weapons in air combat, multi-agent technology with autonomy, distribution and collaboration is introduced. Secondly, the cooperative operation agent model of soft and hard weapons is constructed by applying the theory of distributed hierarchy. The combat capability of soft and hard weapons is abstracted and formalized. Finally, adopting the reinforcement learning mechanism, the judgment, fusion and decision-making process of each agent can be guided to achieve the predetermined target. The method of resource allocation and optimization of soft and hard weapons are explored in the paper to provide theoretical support for hard and soft weapons cooperative operations of air combat. A simulation example is illustrated in the end and the simulation result shows that the method is effective.

Image classification is one of the most popular and important problems in computer vision. In self-driving cars image classification is used to classify detected traffic signs. Modern state-of-the-art algorithms based on deep neural networks use softmax function to interpret the output of the network as the probability that the input data belongs to a certain class. This approach works well, however it has several disadvantages. More precisely, it is necessary to know the number of classes in advance, and if one wants to add a new class, then it is necessary to retrain the network. Moreover, a large number of images of each class are required. In the case of road signs, datasets may contain only the most frequent signs while ignoring rarely used ones. Thus, the traffic signs recognition module in autonomous cars will not recognize traffic signs not included into training dataset, which can lead to accidents. In this paper we put forward another approach that does not have disadvantages of networks with softmax. The approach is based on learning image embeddings in which models are trained to bring closer objects of one class and to move away objects of other classes in embeddings space. Therefore, having even a small number of images of rare classes it becomes possible to create a working classification system. In this work, we test the applicability of these algorithms in the traffic signs classification problem, and also compare its accuracy with neural networks with softmax and with networks pre-trained on softmax. We developed publicly available toolbox for training and testing embedding networks with different loss functions, backbone models, training strategies and other configuration parameters and embedding space visualization tools. All our experiments were carried out on the russian road signs dataset. To simplify the process of conducting training experiments, a framework for embedding learning based neural networks making was created. The framework can be found at https://github.com/RocketFlash/EmbeddingNet .

People in Thailand always rely on a calling channel using tele phone. 191 is as an official number to get assistance when a critical or emergency case happens e.g. accident, crime, medical issue and robbery. However, calling channel operated by officer cannot retrieve caller’s location information automatically. The best clue is caller’s cell site or base station where the caller is when they are making a contact. Moreover, many cases that callers do not know exact location where they are or sometimes they have inaccurate position information i.e. wrong street name or wrong address. Then, emergency dispatch team may not be able to arrive at the right location efficiently on time. This work applied Location Based Service framework (LBS) to develop an Android mobile application used for reporting critical and emergency case to the authorized officers. Users can select assistant topic or incident case and request for relevant dispatch team on demand. This application will send geolocation information automatically to the officer how to reach out the reporter via road map navigation system. This application also provides several statistics and reports. This mobile application also helps to prevent false or pranking report because a lot of user’s information will be provided automatically to the authorized officer e.g. IP address, GPS location, and cell phone number. These unique pieces of information will make user realize how serious this report is and avoid making a prank report for fun.

The mangrove forest in Thailand provides food and many living organisms. Mangrove forests also provide important nursery habitat for many species of fishes. Therefore, knowledge on mangroves distribution and change is importance for effective management. Remote sensing and geographic information system has been widely used to characterize and monitor and studies on mangroves change. The main of research is monitoring mangrove forest land cover changes in Samut Songkhram Province from 2008 to 2018. This study used multi-temporal Landsat TM data and ancillary GIS data to quantify mangrove cover changes in the whole of Samut Songkhram. This research used supervised classification technique and NDVI index. Land-use was classed 6 groups which were mangrove forest area, urban area, agricultural area, bare land area, fishery farm area and water area. The result found that overall accuracy by calculating Error matrix during 53 to 83%. The mangrove forest area is increasing between 2008 to 2011 and 2015–2017. In the other hand, mangrove forest areas are decreased between 2011–2015. Information of mangrove forest area change of this study is very useful to local government and urban planners for the betterment of future plans of sustainable development of mangrove forest.

It has been detected through dynamic networks that the interaction processes in a YouTube work system with audible sensory orientation generates Focal Attention Processes in less time and a decrease in the exploratory activity in the object, compared to the processes of Interaction performed without audible guidance. Which affects the perception of the aesthetic - formal elements in a user. The studies show, that the focal attention directed in a linear architecture work system, is not the most appropriate activity to generate detailed analyzes of the aesthetic - formal elements in artistic and design learning environments. Which requires detailed exploratory activities. Therefore, the intention of these studies is promote reflections on the appropriate use of technological tools and objects of the new media based on the effects and processes of interaction generated in a user.

An objective of this research paper is to develop of web application in English subject, and to study the students’ satisfaction in using the created web application. The sample of this research was 87 students who studies in Grade 7 at the Bangpakok Wittayakom School, Thailand from purposive sampling method. The research tools included the web application in English subject, and the students’ satisfaction form on the created media. As a result, the average satisfaction score is 4.53 and standard deviation is 0.57 in a good rate.

This paper describes an early prototype of a distributed multimodal multi-user virtual environment used for the visualization and query of complex data. The system supports different user interfaces for viewing coloured 3D objects of various sizes representing high-dimensional data to allow visual exploration and pattern detection in the data. Users can navigate and query the environment by using multimodal interaction techniques including speech and gesture recognition. The system serves as a testbed to compare the usability of various interaction techniques for visualization and query of complex data.

Data mining design is an approach through which system operational improvements in the search and retrieval of data activity can be augmented. This study explores optimisation processes, including data harvest, analytics and visualisation plus covers a wide range of efforts, including identifying the growing need of ‘making-sense’ of data which requires contextual understanding. In both cyberspace and physical world experiences the exploring of challenges and linkages between the cyber-physical knowledge spaces in data are emerging with excessive amounts of raw data. Possibilities to improve User-interface-design through better visualisation infographics in this study propose a novel mapping approach called ‘Trace’ in the Knowledge Space enabling design opportunities that help articulate unique human-system interaction, which provide potential in re-imagining and re-structuring uses of interaction and user-experience. These experienced through the design, use and context of languages enabling the building of new interactive apparatus, algorithms and dynamics in collective intelligence.

A study, with 44 children examines ideas put forward by children who used a prototype chat application. It appears that the less the child enjoyed the app, the more ideas they proposed. Six of the children had no ideas for improvement, the remaining children contributed 41 unique ideas but only one of these was for a feature that was not commonly seen in fully fledged chat applications. This paper further analyses the outcomes and investigates reason or experience that motivated the children to come up with the ideas.

Daily life problems, can lead to distress, which has a harmful effect on health. Individuals are using machines for longer period. Machines should now have the ability to understand and show empathy which relies on trying to help the other through their emotional situation. In this study, showing empathy is done by reducing the effect of negative stress by using blue light. In the experiment, 17 participants executed a computer-mediated stress-generating test while using an Empatica E4 to extract physiological signals. The test is done without and with additional blue-colored light. The results show that a simple addition of blue colored light has the tendency to reduce mental stress. That can be interpreted as, compared to the normal state, the experiment with no light-induced more stress than the experiment with the blue light in the humans. Which imply that the blue light helped in maintaining a lower level of stress.

Existing research on phubbing focused mainly on the effect of phubbing on individuals’ wellbeing and social relationships. No published work has investigated in detail which apps are commonly used by smartphone users while having a face-to-face conversation with others and which demographic characteristics influences the choice of these apps. An online survey of 385 participants revealed that that Facebook was the most frequently used app by smartphone users while they are having a face-to-face conversation with others and that participants were more likely to use Facebook, Facebook Messenger, and Apple/Android Messages than Whatsapp, Pinterest, LinkedIn, Skype, WeChat, and Tumblr while having a face-to-face conversation with others. Results showed that an increase in age was weakly associated with a decrease in the use of finance apps (internet banking); social networking apps; photo and video apps; music apps; news apps; and lifestyle apps (Tinder) during phubbing. Results also showed that only two significant differences in the scores for males and females across the app categories used during phubbing were found and that there was no significant difference in the scores of urban and regional participants across the app categories. Considering this is the first study of its kind that looked in detail at which apps are commonly used by smartphone users while having a face-to-face conversation with others, a follow up study should next be conducted using qualitative interviews to understand in depth why do people use these apps and not others while having a face-to-face conversation with others.

The aim of this study is to optimize learning environments for collaborative activities through interactive communication by combining members of small groups. It was supposed that supervisors or tutors might be difficult to fix members, matching new students for collaborative learning, especially in a case of utilizing ICT. As one of solutions for those problems, we have developed the support system which provides them the method of combining team members, along with students’ types of traits measured by YGPI (Yatabe-Guilford Personality Inventory). The result of students’ performances in 2015 was shown significantly better than those of 2014. This phenomenon continued in the first semester, however, it has been gradually down in the second semester comparing with those of 2015. Then, we have introduced another method of combinatorial optimization in 2019 by analyzing various students’ data, for example, factor scores of traits, performances in class, report, observations, and so on. From the finding of those investigations, we have divided into successful and unsuccessful teams in order to specify factors which might have an effect on collaborative learning with interactive communication. After brief course of instructions which requires supervisors to focus on factor scores of O (Objectively), Co (Cooperative) and T (thinking introversion), we have asked them to optimize combination of team members for new students in April, 2019, because those factor scores were significant variance among five years in collaborative learning environments. At the present time, we have recognized an effect of the optimization, observing that their performance becomes significantly better than those of previous year. There are remained problems concerning with combinatorial optimization, because of various discrete elements in Education, especially using ICT. Therefore, those studies would be required continuously to gather various data and analyze them in order to improve the method of matching members for interactive communication, which might be useful references for combining members automatically by AI in certain conditions.

Terminology databases constitute an essential tool for academic research and practical translation. Both Europe and China have their special terminology databases for their actual need. The databases echo the integrated thought of Europe and China’s terminology management mechanisms. The IATE in Europe is an inter-active database constructed over many years. China has already created a large set of terminology databases, e.g. TERMONLINE. The present study will comparatively introduce and interview both IATE and TERMONLINE, analyze the background of construction and provide real and practical information for translation. It can be concluded that with the advancement of emerging technologies in the future, more and more terminology databases will be designed and established in Europe and China, thus further keeping the balance between human and knowledge interaction.

The purpose of this work is to discover learning methods in the digital environment that facilitate the training of design students and show the teaching/learning possibilities offered by MOOCs for the education of this discipline. For this research, we analyze and explore how technological innovation can be introduced in the teaching of Design for the acquisition of knowledge in the context of higher education.

We focus in this article on the comparison between machine statistical parsing and human cognitive preference when dealing with the semantic circuit of garden path sentences. Stanford parser and 126 Chinese college students are introduced to discuss the parsing of garden path sentences. Machine has the ability to successfully parse sentences based on statistical information. If the statistical result is coincident with answer, an excellent parsing result comes into being. Otherwise, ambiguous effect and processing breakdown may occur. Human beings have their cognitive preference. When they are required to parse garden path sentences, some are confused by ambiguity just as machine does. However, some people, mostly belonging to high span readers with more linguistic experience, have special ability to disambiguate the sentences after backtracking and reanalyzing. We draw a conclusion that human beings sometimes parse some types of sentences better than machine does.

Driver inattention has been a major contributor to road crashes through the last years. Additionally, professional drivers are more expose to this risk due to the long work journey. The present study aims to explore the data collected by a commercial driver-monitoring system (DMS) in order to identify profiles of professional drivers. The DMS emitted an alert when distraction or drowsiness were detected, generating additional information such as timestamp, GPS and instant speed. The Hierarchical Clustering Approach and the K-means method were used to identify distinct profiles. The results showed a clear distinction among the clusters with respect to the exposition variables (time and distance related) as well as the number of inattention events.

The paper argues that digital literacy includes the ability to search, select and process information in computer and network sources, content creation, and Internet safety skills. Educational approaches, training and learning methods which are parts of educational technologies geared towards shaping digital skills so important in the modern world. The article is based on the survey “Digital Media Literacy in the context of “Knowledge Society”: state and challenges” KII-06-H25/4, team leader V. Milenkova. The main conclusions are that education and technological environment, are crucial in shaping digital skills and more efforts needed to improve the educational methods to create digital competences of learners.

Advances in vehicle technology open up both opportunities and challenges for human-machine interface (HMI) design in intelligent vehicles. Design guidelines for icons in central consoles of vehicles have been discussed in human-computer interaction community, but more study and innovation are needed in icon design. In this paper, we investigated the displayed line thickness and size of icons in the intelligent vehicle’s central control screen, based on international design guidelines and standards. The experiment involved 17 participants performing simulated in-vehicle secondary task. The result from the experiments shows that the usability of icons increases and the driver’s workload decreases as the icons get larger. We also found a set of recommended values for size and line thickness of icons in this context. Future work will focus on providing design guidelines for other aspects of HMI design in intelligent vehicles.

The PersonAge VR project has the two-folded goal of using Virtual Reality (VR) and interactive storytelling to divulge the research and knowledge in the field of ageism and, in the process, to raise awareness about ageism in the population. The system we conceived and developed allows experiencing ageism under three different points of view: the victim, the perpetrator, and the witness. We performed preliminary usability tests (formative usability) with 8 participants from the point of view of the victim. The system was found to be easy to use and the participants provided feedback about the emotions felt when playing the role of an elderly person. The participants felt strong anger and surprise. These feelings could be associated with a situation of discrimination.

This study quantitatively evaluated subjects’ visual perceptions and experiences of an architectural environment in virtual reality. This study was conducted to empirically determine which spatial elements subjects were most interested in in virtual architectural space; to analyze the sequence of objects that captured subjects’ visual attention, how long each object captured their attention for, and the number of objects in each area of interest that captured their attention; to analyze subjects’ emotional responses to virtual architectural spaces. A head-mounted display with an integrated eye-tracking device was used to measure the visual attention that subjects paid to spatial elements of a virtual environment. The result showed which architectural and interior elements subjects paid the most attention to in an area of interest in the virtual architectural space. This study’s findings provide useful information and practical guidelines to architects and designers about which built environment elements attract occupants’ visual attention and what types of physiological responses the elements cause. The conclusions drawn from evaluating visual perception with state-of-the-art VR integrated eye-tracking technology can inform architectural design processes to improve user experiences.

Ensuring proper education for employees represents a key factor in most of the industrial sectors. Several researches have been conducted in order to test the efficiency of new educational methods for improving their flexibility and effectiveness. At the same time, the introduction of emergent technologies, such as Virtual Reality (VR), is offering new solutions for industries for both reducing cost of training programmes and for better tailoring those on the needs of the users. Based on a first cross-industry reflection, the paper analyses how the combination of adaptive learning methods with VR could bring substantial benefits to companies (railway and process industry) in replacing the actual training programmes based on traditional learning approaches. Firstly, the paper offers a short overview on the features of adaptive learning and VR. Secondly, a consideration on the main requirements on railway sector and process industry is conducted in order to link them with constrains appeared during the current training programmes. Finally, possible solutions based on the previous findings are highlighted in order to sketch a possible working framework for creating a Virtual Reality Adaptive Learning Tool. Our research, thereby, shows how long-term strategic educational policies can impact the performance of the industries.

Rapid progress in virtual reality technology empowers immersive and naturalistic driving simulations also for low budget. The technology enables researcher with the means to test different variables in road traffic riskless and reproducible. In real traffic scenarios, differences in driving behavior and safety related-perception can be observed. The object of our study was to develop a low-budget driving simulation environment and to enable a riskless testing of future traffic scenarios.

Current literature demonstrates that the use of both VR technology and gamification can benefit rehabilitation, providing an increase in motivation, a more active user engagement and overall a more fun and joyful experience. This article presents the design of a VR application with the incorporation of gamification elements for a physical rehabilitation equipment. A detailed description of the equipment is made for further understanding of the project. The VR application allows the customization of rehabilitation sessions according to patients’ needs. Furthermore, the application was presented to the medical team of a Portuguese rehabilitation centre (Rovisco Pais) and had great acceptance.

The increase of shipped consumer immersive virtual reality (IVR) up to 6 million units in 2019 shows the increasing popularity of this medium. Invests of 8 billion dollars are anticipated in the next five years for the training sector. With the development the question arise, what effects and advantages can be expected using IVR in human training? This paper reviews three important areas, when it comes to the design of immersive virtual reality trainings: 1. cognitive load, 2. spatial imagination and the contextual interference effect.

The aim of the paper is to highlight the importance of 3D virtual reality and 3D multi-user virtual environments as a support and complement in education. What influence and impact to education represents virtual and augmented reality? Using in teaching is directed towards learning objectives? Let us point out virtual social relationships, social community and 3D virtual simulations.

Pediatric physical therapists (PTs) have long struggled to diagnose and treat congenital muscular torticollis (CMT) at early stages, when such diagnosis and treatment would do the most good. Much of this problem is that very young infants and toddlers have difficulty with poses, are difficult to measure due to their small size, lack of compliancy, and inability to remain stationary. It often takes a team of pediatric PTs to perform these measurements, and usually in a clinical setting. We wish to create a toolset and a methodology that allows for simpler diagnostics, more comprehensive monitoring and treatment, and wider access to such care and treatment by creating TorticollisAR - an Augmented Reality (AR) application that performs critical measurements in a familiar, convenient setting (such as the home). The app uses tracking markers integrated into either bands or clothing to take measurements in real-time and while the subject is in motion.

In this paper, we introduce the design and implementation of a smart foot bracelet for navigation purposes. The foot-band is meant to be worn right above the ankle. FEEDI, as the wearable shall be called, guides pedestrians to their destination by giving them haptic feedback using four vibration motors.That way, the user’s attention is freed from any display and audio feedback, making him perceive more of his surroundings. Furthermore, the wearable could have interesting applications in the medical field. One example is guiding visually impaired individuals or helping people improve their general wellbeing with feedback regarding their physical activities. The band is able to record sensory data from an accelerometer, a gyroscope and a magnetometer. This opens the possibility to use that information for activity monitoring with deep learning methods. All code and further resources are available at https://github.com/Spackelter/FEEDI .

Exoskeletons are wearable robots designed to restore or augment human physical abilities and, indirectly, cognitive functions. These devices can be classified based on the sector of application, the body part they are intended to support or enhance, the degree of assistance, and the source which they gather power from. Regardless of such technical features, exoskeletons are usually equipped with Human-Machine Interfaces (HMIs), allowing users to interact with the system, both physically and cognitively. The current paper critically reviews the state of the art of HMIs, and discusses the future challenges concerning Human Factors issues associated with the experience of utilisation of HMIs for wearable assistive exoskeletons in neuromotor rehabilitation settings. An overview of extant types of rehabilitative exoskeletons’ HMIs is provided, as well as a discussion on novel user experience research questions posed in light of the recent developments in the field.

Sedentary behavior and inactivity are behaviors that are associated with obesity. The aim of this study was to classify 109 adult participants of various BMI in different homogeneous clusters on the basis of time spent at four physical activity levels. The cluster analysis tree shows three distinct clusters. The clusters significantly differed in BMI, hip circumference, and time spent in sedentary and active behaviors. The largest difference between clusters dealt with sedentary time: higher in CL2 (13 normal weight and 33 overweight) than in CL1 (33 normal weight and 20 overweight) and CL3 (9 normal weight and 1 overweight). Overweight is also associated with brief time in light- or moderate-intensity activities. However, some normal-weight adults had the same sedentary pattern as obese individuals. Factors other than physical activity or sedentary time might be more directly involved in body weight excess.

This study aimed to identify the effects of an application of a passive upper-body exoskeleton (EXO) during an overhead, low force, simulated task. Participants were volunteer assembly workers, who performed a simulated work task without and with a commercially available EXO. Their heartrate was recorded at different times during the task, as well as their heartrate recovery time. Frequency of participant-initiated rest breaks was documented. The EXO was also assessed for its perceived usefulness and ease of use by the participants. Findings indicated some potential benefits associated with the adoption of this passive exoskeleton model during an overhead, low-force, simulated work task. Heartrate range and recovery time were reduced in a majority of instances. Participants perceived the EXO to be very easy to use and its usefulness to be average or above average for real-world application.

Postural stability is affected by many physiological and biomechanical aspects as well as cognitive and emotional factors. Postural control may affect a pilot’s ability to successfully deal with specific demands in airspace. The purpose of this study is to investigate the effect of cognitive load on postural stability in the Czech Air Force. Eighteen pilots performed two trials of postural stability and a cognitive test between them. In the control group of fifteen pilots, participants were measured twice for postural stability with no cognitive load between them. Postural stability was quantified using force platform measures during quiet standing, and cognitive load was assessed by selected tests for spatial abilities while obstructing listening with a highly stressful recording of a crying baby. This study investigates the oscillations of body posture before and after the cognitive load with and without visual input. In the group of pilots with the cognitive load, an improvement in performance in postural stability was found. In contrast to the control group, postural stability in the pilots with the cognitive load was significantly affected by the cognitive task in the size of the ellipse area of the center of gravity while the participants had a smaller ellipse area of the center of gravity compared with the default situation. Cognitive load reduced body swaying, both with eyes open and eyes closed. The results indicate that cognitive load has an impact on some aspects of balance control, and cognitive load may arouse attentional resources and have a positive effect on individual postural stability.

The number of people affected by stroke increased during the last decades. However, the number of therapists is not large enough to fulfill the demands for specific training for stroke survivors. Within the project E-BRAiN (Evidence-based Robot-Assistance in Neurorehabilitation) we want to develop software that allows a humanoid robot to give instructions to perform and to observe carefully selected exercises, provide feedback and in addition to motivate patients.

In the context of a technological innovation in one new university hospital center (CHU) in Montreal, Canada, the purpose of this study explores the lived experience of the healthcare professionals in this work environment, how the hospital design and some technology attributes facilitate their work and affect their well-being. It is conducted from august to November 2018 in two care units. The analysis includes a phenomenological interpretation of the lived experiences of these professionals following their narratives, observing their environmental behavior. Related to the hospital’s size, a linear layout of the care unit, some technological elements in the care units facilitate the healthcare professional’s work while others hinder it. The introduction of new technologies and continuous innovation in the hospital work environment must be adapted to the physical context of the hospital in terms of spatial organization and layout of the care unit.

The following paper takes a close look at health care platforms, which are promising to enhance the quality of health care systems for a couple of reasons. In order to get a deeper understanding of the services they provide it is necessary to carry out a systematic analysis from a service innovation point of view. That view is extended by a business model perspective and thus creates a holistic picture on how the platforms operate and what benefit they provide for actors within the health care system.

In addition to usual Information and Communication Technology (ICT) devices, things are becoming “therapeutic” and can be dedicated to the specific needs of aging. However, because there is a diversity of senior impairments, one must diagnose needs, expectations, abilities or skills of seniors in order to provide the best adapted functions and usages. Moreover, these devices must be evaluated to determine their real potential and effectiveness. This paper discusses how to choose the best fit between a health technology and age-related deficits, and how we can assess the results of this fit. In this context we will use a tool and methodology called “Design for Adapted Devices” (i.e. DAD). DAD tries to develop adaptable systems based on the comprehensive diagnosis of human deficits and needs taking into account several dimensions of user diversity like skills and abilities (e.g. motor, cognitive skills, etc.), and measure deficits that “modulate users” performances (e.g. social support, experience, strategies, etc.). DAD gives prospective data to define future smart things and provides information about technology assessment.

Medical simulation presents a viable alternative to traditional methods of medical instruction, such as cadavers and animal models. Simulation can provide safe, consistent, and repeatable learning opportunities. It accomplishes this without risk to patient safety. There is an increasing awareness of the value that simulation brings to learning. The Wide Area Virtual Environment (WAVE) is an 8,000 sq. ft. immersive virtual reality facility intended to support medical team instruction. It is the world’s largest immersive virtual environment. The WAVE represents a novel application of human-computer interaction. It forms the basis for a synergistic amalgamation of live, virtual, and constructive simulation for medical instruction. This paper describes the motivation behind the WAVE. We also describe the WAVE’s primary components, and how they are used during a learning scenario. Our experience with using the WAVE is also described.

Alert Center is a platform aiming at detecting outbreaks caused by food toxin infections and food intoxications in Switzerland. It does this by analyzing tweets and sending alerts to the Federal Food Safety and Veterinary Office (FSVO) when a risk is detected. The platform is composed of four main parts: a real-time extractor that targets tweets based on a list of curated keywords, three classifiers (one for each main spoken language) that isolate tweets related to food toxin, a system that locates tweets on the Swiss territory and a web-based dashboard to visualize the results. Combining localization algorithms of tweets and users allows the system to locate 75.09% of the tweets, 2.31% of which were located in Switerzland. In addition, a list of Swiss Twitter accounts corresponding to 15% of the total estimated number of Swiss accounts has been created.

Emotional work is an activity that influences the organizational culture of the health sector. The physical and mental activities of workers include emotional functions due to the type of service they provide, because it is part of the corporate image; constituting an excessive emphasis on the development of work [1]. For this reason, it is necessary to evaluate the psychosociological conditions and the consequences of emotional work in health services institutions in the city of Bogotá - Colombia. Methods, mixed study with descriptive scope of situations that affect the health of these workers. Population of 291 workers of 20 health units in Bogotá. Use of instrument battery for the evaluation of psychosocial risk factors. Levels of reliability in the questionnaires; intra-work of 0.957 and stress 0.83. Main psychosocial risk found, precariousness and precarious work based on the forms of recruitment and compensation in 72% of workers.

Over the time, the concept of caring has undergone many transformations leading to a broader vision of its meaning. In this sense, taking care of oneself and others also implies taking care of the future. There are many aspects connected to the care design from social design to the more specific product design, such as to the design of daily use objects that have the aim of monitoring, improving, facilitating health-related practices and of psycho-physical well-being. The research refers to children as reference public and main users of care devices, because educating them to a good practice from an early age is surely an important aspect to take care of the future.

Sleep is important for many vital functions. Unfortunately, many people suffer from sleep-related problems, which have negative consequences on sleep quality and therefore on quality of life. Considering the important health benefits of a good night’s sleep, it is crucial to investigate technological solutions that promote and improve sleep hygiene. To that end, the HypnOS framework for “Intelligent Homes” is introduced, aiming to improve the sleep quality of home residents by monitoring their sleep and providing personalized recommendations to overcome sleep-related issues. It describes the design process that was followed, presents its functionality, reports the findings of an expert-based evaluation of the HypnOS mobile app and discusses future plans.

A simple model for diabetes has been considered and represented mathematically in terms of reaction rate equations. The diabetic states determined by the relative intensities of reaction parameters included in the model have been investigated by numerical calculations. This mathematical model could realize the diabetic and non-diabetic states, namely, the change in states according to dietary intake, insulin secretion, and physical activity. Based on these analyses, it has been proposed that, if the parameter set in the model was evaluated for individuals and saved as a clinical database, it could be used for diagnosis, treatment, and risk prediction for diabetes pathogenesis.

This study was developed at a private health care center with problems in its emergency department, which had a process efficiency of 39.6%. As such, implementing a lean healthcare model was proposed using knowledge management and change management as it pillars. As a result, employees were committed to change, which facilitated the transfer of knowledge when implementing the lean tools, reducing waiting time in the process by 67.01% at its highest level, while an efficiency of 63.87% was achieved.

The use of machine learning to support health-related activities is yet to be adequately explored. We present a concept of using user-drawn doodles for communication and reporting of food item and its portion size. This paper aims to devise innovative applications for existing ML-based services. A prototype mobile app is developed and demonstrated. We invite three senior dietitians to evaluate its potential. Analysis is proceeded in used of affinity diagramming. The expert evaluation concluded the proposed system has good potential for promoting food class and macro-nutrient education among children. This research presents an innovative use of existing AI services helping to communicate food intake related information in nutrition education. Our future work will conduct user evaluation, integrate expert and user evaluations to improve app experience and usage, and enhance system functionality.

New diagnostic directions in rehabilitation and expert diagnostics consist in assessing the safety and the possibility of restoring (in whole or in part) the operation of the patient’s systems, using the extra-nosological approach to assessing function at the level of the whole organism. The data on the quantitative assessment of the functional reserves of the body (adaptive potential) in 139 patients with type 2 diabetes was presented. The prospects of using this indicator in predicting the effectiveness of rehabilitation are studied.

Currently, the number of elderly is continuously increasing and by 2020 in Thailand, the population of 60 years is one in six of the total population. Therefore, encouraging the elderly to take care of themselves will help make them live longer and have a good quality of life. Physical therapy is a method of treating the abnormal movement of the body and it must be performed regularly in order for the body to be continuously refreshed. Often, the elderly do not receive proper physical therapy due to travel difficulties and high cost of treatment. Hence, this research studied the possibility of using Kinect technology in the physical therapy program to help the physiotherapist properly. This study was quasi-experimental research using simple random sampling. All participants were interviewed for their demographic information and examined according to the five-arm muscle exercises. The results of the motion detection experiment using the Kinect camera and the experimental physical therapy program using the Kinect device show that Kinect can detect the movement very well and physiotherapy programs with Kinect devices help users perform more accurate physiotherapy compared to doing physical therapy. The data were analyzed by the mean, standard deviation. The results meant that physical therapy Application based on Kinect for Elderly could improve physical fitness and they have a positive effect on balance and thus on the quality of life.

The objective of this research is to isolate strains of probiotic lactic acid bacteria from beef fermented samples. The probiotic lactic acid bacteria has the ability to inhibit microorganisms that cause food poisoning. The use of probiotic lactic acid bacteria as a starter for Naem production will increase food safety. From the experiment, 18 isolates of lactic acid bacteria were isolated and only 4 isolates, A2, A3, A4, A11 and B3, were able to create amino acid decarboxylase which can convert amino acids into biochemical amines. After testing the inhibit pathogenic bacteria ability, it was found that all 18 isolates were able to inhibit the testing gram positive food poisoning bacteria, Bacillus cereus, Staphylococcus aureus and Pseudomonas aeruginosa. 6 isolates which could inhibit Esherichia coli were A1, A3, A6, A8, B1 and B7. 10 isolates that could inhibit Salmonella sp. were A1, A2, A3, A4, A7, A8, A10, A11, B2, and B7. 7 isolates that could inhibit Shigella flexneri were A1, A2, A3, A6, A11, B2, and B7. Heat resistance was tested at 65 ℃ for 1 h. It was found that the number of all isolates were reduced by 2–3 log CFU/ml. The survival tests of the 18 isolates in the digestive system were done. It was found that all 18 isolates were able to withstand acidic conditions from stomach enzymes and bile, with small decrease of bacteria number after 2 h of testing. Therefore, it can concluded that the isolated lactic acid bacteria are suitable to use as starter cultures in Naem production.

Health has always been the focus of human’s attention, however there is not enough research about home medical device interfaces. This paper aims to discover the key principles and perceptual demands that should be taken into consideration when designing a oximeter interface. The concept of ‘human-centered’ is not only for the product design, but also for the interface design. Compared with normal people, patients need more emotional supports from the products they used. In the second part, Kansei engineering is used to discover these emotional needs. Using these Kansei words can guide the next iterative interface of oximeter. In the third part, aesthetic evaluation is proposed in order to choose the best interface among the three optimized interfaces which put forward in part two. Balance, sequence and cohesion are the three calculation indexes. The result of this paper has a great influence on a human oriented interface design.

93 preparations of the right and left lungs of human fetuses of 13–36 weeks of development were examined and measured. We determined the length of the front and back edge of each lung and the length of its base. The three adjacent sequence numbers were interpreted as the lengths of three segments used in the formula to calculate the wurf. The average wurf quantity for each age group in prenatal period of development varies from 1,26 to 1,33 for the right lung and from 1,23 to 1,35 for the left lung. These fluctuations are within a 5% range of 1,31 – the “golden” wurf quantity. In the process of lung growth, the proportions between the length of the front edge, the length of the back edge and the length of the base vary according to the rules of conformal transformations. Changing of one number is consistent with the change of the other two so that at any given time the proportion remains the same and equals 1,31. The rule of the “golden wurf” is subject to all tripartite chains of human body, including the external structure of the heart, its chambers, the teeth of an adult, kidneys, lungs, as confirmed by our research.

The importance of an occupational health and safety management system (OHSMS) in a mining contract allows the establishment of guidelines to prevent and mitigate accidents that may occur in mines and in exploration areas. Such guidelines are integrated to ensure compliance with regulations with respect to the mining activity (DS 024-2016-EM). For developing a model, the literature was initially reviewed (scientific articles and research studies were used as the background), development techniques were established, and an OHSMS was proposed, with prior evaluation from the contractor. Subsequently, this study presents the general requirements, planning, implementation, verification, and the corresponding review by the appropriate authority. Finally, the model is established, supported by tables that will report the current state of the company and the implementation process. This study concludes with the execution of OHSMS in case of mining contracts.

Product variety and short product life cycles are characteristic features of modern assembly systems. When variety gets very high, assembly processes usually become very complex, leading to time losses, human errors, and other negative impacts of system performance. In order to prevent such performance declines different informational assistance systems become part of manual assembly systems, offering additional instructions concerning handling and insertion. Otherwise, such systems can result in additional cognitive load rather than decreasing it. Using mobile physiological measures like heart rate variability (HRV) and eye movements just in time changes of overall cognitive load are detectable. As expected, these data indicate increases of mental workload when task demands are becoming more complex. Practical and theoretical concerns, limitations and chances will be discussed.

This paper reviews the four fundamental frameworks available in normative ethics to underpin the most suitable strategy to facilitate the design of synthetic morality in the context of Highly Automated Systems (HAS). Based on research findings, it will present an updated multidimensional-scalar system of levels of automation specifically adapted to Highly Automated Systems (HAS) in the context of Human-Human-Interaction (HHI). This framework integrates the variables of autonomy, accountability, reparation, actions, contexts, access and inferences to build and facilitate the design of synthetic morality on highly automated unsupervised systems form a consequential perspective. As part of this process, a form of calculation emerges to facilitate the calibration of moral computational reasoning in the context of HAS.

Climate change and global warming are posing a threat to the planet’s biodiversity placing the world’s population at risk. For many years, NGOs, Governmental bodies and entrepreneurs have tried to tackle social and global environmental challenges by the roots through direct action. Nonetheless, those initiatives often fail to achieve short-term, mid-term and long-term impacts, turning out as ineffective solutions to the urgent environmental challenges. The problem lies in the nature of those initiatives as their main objective are solutions for the world’s problems, denying and rather taunting any profitability aspirations. This paper introduces the concept of Green Capitalism which describes how firms can increase profitability by inventing sustainable products/services. It introduces a new way of thinking, based on the Democratic New Product Development (DeNPD) Model in an effort to reduce non-marketable idea wastage and transform it into profitable sustainable innovation with the contribution and participation of the society and individuals.

In the light of a rising number of product variants and increasing dynamics of product modifications in industries such as vehicle and machine construction, the use of complexity management strategies in manual assembly is essential. In this paper different strategies are presented. In the age of digitalization, the strategy of providing cognitive support to assembly workers is highly important, and is therefore described in more detail with the help of morphological boxes. These boxes will support practitioners to develop a company-specific strategy for information management in manual assembly.

Studies that examined the relationship between expressing feelings, such as feeling ‘bored’, ‘excited’, ‘lonely’, loved’, ‘sad’ and ‘happy’ and Twitter users’ network size (i.e. the number of friends and the number of followers) did not take into account the influence of other factors, such as the number of tweets, the number of lists and the number of favourites, because prior research did not provide clues as to why these should be considered. The data mining approach is not biased by prior knowledge. In this study a data mining technique, specifically a decision tree, was applied to look at the interaction between the expression of feelings and all Twitter users’ attributes considered likely to be useful in the discovery of interesting rules. The decision tree technique was applied on a large dataset of tweets containing the phrases, in double quotations marks, “I am bored”, “I am excited”, “I feel lonely”, “I feel loved”, “I feel sad” and “I feel happy”. Only when these phrases were tweeted twice or more at different times that they were retrieved from Twitter using the Digital Methods Initiative Twitter Capture and Analysis Toolset (DMI-TCAT). The decision tree technique generated a number of interesting rules that provided clues about previously unknown relationships between the expression of feelings and a number of Twitter users’ attributes. This study demonstrates that data mining is valuable for shedding light on previously unconsidered factors that can influence the expression of feelings; thereby advancing the research in this area.

Digital Transformation affects our lives in many realms. It is a way to help consumers and users get rid of intermediaries - those people whose jobs are to connect consumers to final products or services - such as salespeople, bank agents, mediators. Now consumers can do things independently using diverse software: for example, they can shop without the help of salespeople on an e-commerce and carry out transactions on an e-banking without a bank agent. The problem is that they are often left to wonder how to use these digital resources properly, getting lost in a tornado of clicks, typing and interfaces. And ironically, they have to establish new intermediary resources to use digital technologies: manuals, trainings, help desk tickets, which are often outside the digital sphere. In this paper, we propose a reflection on how to assist the user, rescuing their independence and confidence while keeping them in the digital realm.

This paper argues that a new digital right, the ‘right to reparation’, is needed to address the accountability gap presented by highly autonomous complex systems (HACS) incapable of fully monitoring their actions in real-time due to the increasing complexity of these advanced systems. The ‘Right to reparation’ follows the articulation of the ‘Right to be forgotten’, the ‘Right of access’ or more recently the ‘Right to Reasonable Inferences’, and aims to ensure that emerging HACS interactions remain accountable as current highly autonomous technologies cannot fully guarantee the effect of their behaviors. Building from an integrative review of previously published surveys specifically designed to address the rising concerns of artificial intelligence in the context of HACS, this paper presents indications by which introducing reparation and accountability strategies increase trust and engagement in the system in the context of unexpected events. Thus, building a case for the introduction of the newly proposed digital right.

Mines are dynamic and hazardous; because of these characteristics along with semi mechanised working procedure, accidents are occurring in Indian underground coal mines mainly due to ill performance of the workforce. It is challenging for the supervisors to achieve optimal work output with an acceptable level of quality and safety. Many studies have reported that work-related factors play a significant role in influencing the level of human performance with safety. This study aims to predict the chance of occurrence of an accident concerning the work-related factors and employee demographics. These objectives were achieved by using modified work compatibility (WC) and binary logistic regression models. We have achieved an inspiring level of accuracy on testing the model with the available data.

This study used EMG coherence to investigate the correlation between muscle fatigue and beta-band energy after the dynamic biceps brachii contraction. HD-sEMG signals were acquired in experiment. 9 healthy subjects participated in the muscle contraction task (from non-fatigue to fatigue), Each participant was asked to perform two trails of experiments and exert their max-muscular strength in each trial. The result shows a significant correlation [p = 0.0058 < 0.01] between fatigue and energy in beta-band.

As traffic safety has become a major health issue in China, it is crucial to characterize driving behavior and provide feasible suggestions to traffic safety works. A semi-structured interview was conducted to understand Chinese drivers’ views of driving behavior and traffic safety works. The results show that the respondents have a clear understanding of safe driving behavior and believe that traffic regulations should be improved. Then, the cause of the accident experienced by respondents was divided into two categories: error and violation. Finally, the respondents provided recommendations for traffic safety work, indicating the importance of equal emphasis on hardware and software. The results of this study give useful information about driving behavior and traffic safety work in China from drivers’ perspectives.

This study aimed to investigate the effect of various levels of dragon fruit peel powder (DFPP) on the physical, chemical and sensory properties of emulsion sausage. DFPP was prepared from drying with a tray dryer at 55 °C for 6 h and ground into powder. DFPP had contents of moisture, protein, fat, ash, crude fiber and carbohydrate as following order respectively: 15.52, 1.79, 0.48, 13.28, 7.88, and 61.05. Water holding capacity, oil holding capacity, and swelling capacity of DFPP were 13.71 g water/g sample, 2.67 g oil/g sample, and 15.94 ml/g, respectively. Emulsion sausages were produced by replacement of pork fat with five different levels of DFPP (0.5, 1.0, 1.5, 2.0, and 2.5%). It was found that moisture, ash and crude fiber contents of sausage increased when the amount of DFPP increased. Sausages made of the addition of 2.0 and 2.5% DFPP had the lowest crude fat content. Adding DFPP resulted in expressible moisture and lower L* (lightness) than the control without DFPP. However, the result of this adding caused higher a* (redness), b* (yellowness), and cooking yield. High DFPP content increased hardness, springiness, gumminess, and chewiness but it decreased cohesiveness. Sausage with 2.0% DFPP had no significant difference of sensory score in appearance, flavor, texture, and overall acceptability. Therefore, the addition of DFPP is useful in improving the qualities, nutritional values, and sensory acceptability of sausage.

Xanthone is the phytochemical which is extracted from the Garcinia mangostana. Xanthone components have yellow color and absorption in the wavelength in 254 and 366 nm and detected by the ultraviolet spectrophotometer. Garcinia mangostana is the plant growth in the east and south of Thailand, peel of the fruit has many xanthone. Extracted of the peel with water: ethanol (1:1) gave xanthone components, and have yellow color when stained on the paper or skin cannot remove it with water. The experiments used the extracted of xanthone components developing on the Silica Nanoparticles (SNP-X). The xanthone covered on the porous of Silica Nanoparticles which have binding affinity on the latent fingerprints (LFPs) detection. The simple preparation and easy controls of the surface properties of SNP-X showed the potential on the UV absorption labeling compounds for enhanced the latent fingerprint detection in forensic science for individual identification.

In Thailand, rice farmers rely on pesticides to control a variety of pests. The study aims to survey of pesticide use in paddy and to assess of EIQ (Environment Impact Quotient) Field Use Rating from the rate of pesticides in paddy, Bang Rachan District, Sing Buri province. The sample consisted of 161 households that were selected by using stratified sampling and proportional sampling. The data were calculated with Calculator for EIQ Field Use Rating to assess of EIQ Field Use Rating (EIQ-FUR). The results showed that 29 types of active ingredients of pesticides, Pho Chon Kai subdistrict, Bang Rachan district had a low EIQ-FUR (37.32). Most of the sample villages (63.6%) had a low EIQ-FUR, while the EIQ-FUR was very low with 27.3% and a moderate level of 9.10%, and founded that the use of pesticides will have the greatest impact on the ecosystem, followed by consumers and famers respectively.

In architecture, the fixed elements that help people to circulate in spaces need to change often. Signs and Information are everywhere. If a new technology with sensors could be introduced into architecture, adding new functions and helping constant changing, this action could probably be a new sustainable measure for our future. Adding to a textile all the needed information can, on the one hand, be observed or, on the other hand, produce sounds and images that improve quality of life.In public buildings, hospitals or social buildings, where interventions need to be fast and active, a new world can embed technology in architecture to meet sustainable open solutions and goals. The internal application on buildings may be the beginning for a real future connection into textile and the ‘Figure of the Architect.’ The benefits will be in a direction of new and more sustainable and green places.

As the military continues its transition from counter-insurgency to one of multi-domain operations (MDO) and the possibility of facing a near-peer threat, the need to achieve overmatch becomes even more important. The Army must be able to attract, retain, and maximize the potential of high quality Soldiers capable of conducting MDO. Optimizing human performance provides an area to achieve overmatch on a large scale through improving Soldier performance in training and on the battlefield. In an effort to gain a more comprehensive understanding of what aspects of human performance correlate to success in military training and on the battlefield, personnel from the Maneuver Center of Excellence (MCoE) and multiple other Department of Defense (DoD) and Army organizations partnered to create a study team and conduct a comprehensive, multi-disciplinary study of indicators of high performance for close combat forces.

The digitalization of humanitarian supply chains allows overcoming one of the greatest difficulties faced by NGOs and governments in managing health equipment in crisis situations: the visibility of stocks and consumption at the end of the chain. This paper presents the design process of the health equipment inventory management system developed to support the humanitarian crisis related to the Syrian refugees in Lebanon. The prototype was tested at the pharmacy of the ICRC Weapon-wounded Trauma and Training Centre in Tripoli, Lebanon, where it was demonstrated to be easy to use and able to facilitate the work related to the management of medicament stocks and orders.

Mining investment represents high risk for any company within or outside this area, and this has repercussions, above all, for the small companies that do not have any investment capital that they can set aside. The methods used to assess investment projects are traditional, with economic estimates such as the Net Present Value (NPV) to determine the project’s profitability. However, these methods do not assess risk factors or qualitative variables, such as socio-environmental factors or the project’s limitations on a supply chain. Given the uniqueness of each mining project variable, a systematic tool simplifying variable identification and ensuring an accurate evaluation of the mining project in its prefeasibility stage is required. This research aims to create and implement the Risk Management Balanced Scorecard approach as a project evaluation tool that will help reduce the evaluation times and implement the project risk variables, which will be analyzed by a number of experts with great experience in the industry. The results will determine the project viability or non-viability for investment.

Corporate responsibility in the protection and safety of workers is daily relevant in the management of occupational risks. To evaluate the intra-labor conditions to determine those precursors of symptomatology that can affect the worker’s physical and mental health, and activities for psychosocial risk management. Methods, mixed type study with a descriptive approach, carried out in 7 service companies, with 263 workers. The sample was 260 workers. The workers signed the informed consent for the collection of information. Application of the instrument battery questionnaires for the evaluation of psychosocial risk factors, which has reliability levels for intra-labor conditions of 0.957 and stress of 0.83 [1]. Organizational management strategies must include periodic evaluation, monitoring and control of psychosocial factors. The due development of plans and programs, as well as the appropriate intervention, improves working conditions and productivity, making this a healthy company.

This study addresses the implementation of a behavior-based safety coaching model to reduce the occurrence of substandard acts in an underground mining company in Peru. The previous database of accidents and incidents provided by the mining company was analyzed to prepare data tables of the degrees of accidents and safety-related incidents. Then, the highest-risk activities are considered with respect to the behavior-based safety model to observe workers. The substandard acts are examined, and an action plan was drafted using the behavior-based coaching model according to the safety management model adopted in the mine. This paper examines the application of a safety management model in an underground mine in Peru by collecting and observing data through the behavior-based safety model, proposal of solutions under the coaching model, and analysis of the final results of substandard behaviors obtained with respect to the initial behaviors.

Accordingly, shared knowledge has enabled the population to focus on this area, the majority of which comprise small-scale informal miners. The government and population must be able to control the informal extraction of minerals and its resulting environmental and social impacts. As such, this study aims to increase the number of formalized small-scale and artisanal miners in accordance with Peruvian regulations. The primary motive is to create a knowledge model based on managing the formalization of small-scale miners. Through this approach, this study contributes to sustainable development in cooperation with the state for informal miners and the neighboring communities. A public management model with a sustainable development approach based on the Six Sigma methodology is proposed to increase the formalization of artisanal miners. Through this methodology, the revision and documentation of the formalization process in the mining sector has improved by 29.3%.

With the arrival of the 5G mobile Internet era, people are accustomed to using the network to look up data and obtain information. In the era of administering the country in accordance with the law, colleges and universities, as the main position of education and the most trusted organization of students, have the obligation and responsibility to provide students with learning opportunities and platforms. Colleges and universities should use convenient modern computer technology and advanced network equipment to extend the traditional counselor hodgepodge to professional cyberspace, provide students with legal consulting services independent of time and space, and gradually develop and research the network legal advisory service system that suitable for school characteristics, opens up a good development path for the improvement of school student work and provides a new model and service platform for school information construction.

A large part of the problems with regard to delivery times and quality of processes at Arnao Industrial Radiators are due to high maintenance times and undefined working methods. Thus, the company seeks to standardize production processes and train its personnel. The company gave an opportunity to resolve these issues to students who together with the company’s personnel sought to implement a set of improvements and reduce the activities that did not add value to the service. In the investigation, in which the causes affecting the areas were analyzed, a lack of organization, poor cleanliness, an inadequate use of tools for inspections, polluted material, reprocesses, and non-conforming material in unassigned areas were identified as factors that put the service at risk and the quality level of the plant in doubt. Therefore, the client requested immediate corrective actions; thus, the main purpose of this project was to reduce delivery time and optimize the quality of the processes.

Small and medium-sized enterprises (SMEs) in the textile sector have decreased their overseas sales in recent years due to noncompliance in their deliveries, waste accumulation caused by reprocessing, defects in merchandize, and lack of appropriate foreign language communication skills; these issues have surfaced due to lack of knowledge and mastery over techniques and tools that optimize processes, reduce waste, and help achieve competitive goals set by SMEs while competing in the foreign markets. To overcome these shortcomings, a production process management model is presented in this study; this model showcases that 5s tools of the lean manufacturing model and process standardization can aid in restructuring current processes and can create an optimal process, facilitating a 20% reduction in the excessive work time on the basis of average foreign market standard and help in meeting the established goals.

The rapid development of 5G mobile networks in the new era is also a new revolution for the education industry. The gradual improvement of online courses provides the key time and opportunity for higher vocational students to improve their legal literacy. In order to allow students to make the most effective legal knowledge storage in the shortest time, in the construction of online courses, we should always adhere to the student-centered, scientifically plan the content and chapter design of online courses, integrate the current legal textbooks, and combine the characteristics and needs of higher vocational students to keep abreast of social life and work needs, constantly update the online courses, reform the education model, and actively cultivate basic legal literacy for students to integrate into social life, effectively improve students’ practical ability to combine practical learning with practical application.

This paper demonstrates how deployment of the Lean Six Sigma (LSS) methodology within the operational management of small- and medium-sized mining companies (mining SMEs) fosters the development of a new assessment method aimed at reducing non-productive times in one or more operations. However, this study only seeks to implement this methodology in the cleaning, hauling, and transportation stages. Even though Lean and Six Sigma methodologies are different tools, they are often combined to reduce waste, non-value-adding activities, and process variability, with the purpose of reaching the desired operational efficiency levels. The LSS methodology traditionally works with a DMA-IC phase structure (Define, Measure, Analyze, Improve, and Control); however, this study uses a variation thereof adapted in the best way to the Operational Assessment method proposed. This variant deploys the first three phases separately while combining the last two to produce a comprehensive improvement and control plan. This papers provides useful and meaningful information to reveal the maximum value obtained from the implementation of the LSS methodology in the development of this new method, as it not only dispenses an exhaustive diagnosis of the operations assessed but also a quantitative estimate of the potential improvement levels that could be reached if correctly implemented at mining SMEs.

One of the many criteria used for the selection of prospective candidates to professional courses all around the world are entrance examinations or aptitude tests. In India, Architecture Education is one of the many preferred professional courses. The national aptitude entrance examinations conducted in India are, the Joint Entrance Examination- Mains (Paper 2) and the National Ability Test for Architecture (NATA). This study, in the above context, focuses upon the analysis of the aptitude and creative aspects of NATA entrance examination, which is used for the selection process of prospective aspirants. Literature study supports the fact that psychometric tests are used for examining various cognitive and scholastic abilities to estimate future success in academic studies in various disciplines. The outcome of the study revealed that there are some more aspects used to evaluate creativity through the works of various psychologists and psychometric tests, which can find favor in the current aptitude tests used for evaluating aptitude required for architecture education.

Subject-matter or course content that is selected to be taught and learnt, including its scope and sequence are significantly one of the major components of any qualified curriculum. The objective of this research is to determine the significance of interconnection attributing to achievements by the undergraduate students of the Mathematics Education curriculum based on the Social Network Analysis. 159 online respondents supplied by the graduates during the academic year 2016–2018 are used in the study with results indicating strongly that Teaching Psychology, Graph Theory and Fundamental of Mathematics are reportedly vital courses upon which their contents if mastered properly would encourage and enable interconnection with others. Additionally, Fundamentals of Mathematics, Linear Algebra, and Graph Theory are found to be powerful courses while the Measurement and Evaluation in Learning Mathematics and Actions research in Mathematics combination can influence effect over the whole courses.

Sustainable growth in the telecommunications sector has led to many small- and medium-sized enterprises (SMEs) becoming involved in projects that are often not time and cost effective owing to the lack of a project management model that meets the needs of this type of company. In this article, a project management model is proposed based on the continuous improvement of processes under the lean and agility approach, and a medium enterprise from the sector is considered as a case study. A 50% reduction in the lead time of projects was observed, reprocessing and overtime were eliminated by 70%, while quality was ensured and the probability of project success increased. Thus, the application of this model solves the problem under study.

To optimize the drilling and blasting process in underground mining using the Holmberg method to create the drilling-and-blasting mesh design. The method it is an experimental applied-type and correlational-level inductive method. The Holmberg method showed good efficiency of 95% because it works with the rock mass and volatility-index parameters of the rock. The total drilling and blasting time with the Holmberg method is 2 h, whereas with the traditional method it will be 8 h because the blasting will not be efficient and there will be an increase in the amount of cutting and/or drilling time. The total cost of the drilling and blasting process in the Holmberg method is 2143.85 soles, while with the traditional method, it is 2820.75 soles, without taking into account the loss and shutdown of production that this would cause.

Through the methods of literature, questionnaires, expert interviews and mathematical statistics, this paper investigates tennis organization service of in the middle-aged and elderly people in Wuhan. The results show that: there is a lack of scientific guidance for tennis organization of middle-aged and elderly people. The municipal government has not given enough support for middle-aged and elderly people to participate in tennis. Middle-aged and elderly people are easy to get sports injury when they take part in tennis. Tennis court facilities are not complete. Some organizations and services need to be improved during tennis.

It has been detected through static and dynamic networks, that the Interoceptive responses, during the interaction processes in a YouTube work system with a weak - visual person, are modified based on the greater or lesser use of Fine Motor Interaction. In addition, there is a constancy in the Focal Attention processes generated by two fundamental factors: Fine motor interaction and Sound interaction. Likewise, studies show that the decrease in the processes of fine motor interaction in a weak - visual person in the YouTube work system decreases Interoceptive responses of stress, and tend to focus on audible symbols during the interaction process. Therefore, the intention of these studies is to promote reflections on the appropriate use in the objects of the new media based on the effects and processes of interaction generated in a weak - visual person.