Applied Informatics

Health-related Quality of Life (HRQoL) encompasses physical, psychological, and social well-being and significantly influences healthcare outcomes and policy decisions. Traditional HRQoL measurement tools, such as the SF-36 and EQ-5D questionnaires, face consistent user engagement and interpretation challenges. This paper presents a method to enhance HRQoL interpretability by utilizing clustering algorithms to derive four health indicators: daily mobility, physical activity level, loneliness, and social mobility. These indicators were chosen based on their correlation with physical and psychological QoL domains. By clustering HRQoL data achieved in a longitudinal study with 44 volunteers for six months, we aim to identify patterns and provide insights, addressing the limitations of both traditional and modern QoL inference methods. We also conducted a survey with health and eHealth professionals to evaluate the effectiveness and relevance of these indicators. Our findings indicate that the proposed indicators are highly correlated with HRQoL domains, offering a practical and scalable solution for personalized healthcare. This method does not require continuous human intervention and can evolve with new data, presenting a low-maintenance and cost-effective alternative to rule-based systems.

EnviroLink is a software prototype that utilizes computer vision to analyze head, eye, and lip movements in individuals with reduced mobility. It generates personalized maps to design accessible and adaptive interfaces tailored to each user’s specific needs. Iterative testing with users allowed for interface refinement and ensured that the software met mobility and communication requirements. This project not only provides a valuable tool for people with reduced mobility but also establishes a foundation for future research in assistive technology. By publicly sharing the prototype and results, we aim to foster the development of innovative solutions that promote inclusion and enhance the quality of life for individuals with diverse disabilities.

Promoting products on websites has become relevant in the context of digital marketing. Deciding how a product is exhibited is an important issue, due to psychological factors that impact on attentional-emotional consumers’ responses. The purpose of this study was to compare the emotional and attentional reactions of consumers in relation to three different visual ways to present a product on a website. It was hypothesized that advertising images that contain human faces would be the ones that would work better in terms of attentional-emotional responses. The images were displayed on a Tobii® T-120 eye-tracking device to measure attentional behavior by considering ocular fixations. By using a Face-Reader NOLDUS 7.0 device, the emotional response to the stimuli was assessed. It was found that there are statistically significant differences between the measures of the degree of attention taken in each of the three conditions used. The images with human faces were the most relevant in terms of attention. These images performed better regarding emotional responses. Some limitations are the fact of not having considered variables that can affect the outputs measured, such as the position of stimuli, physical characteristics of participants’ eyes, and their level of expertise while navigating on internet.

CS1 programming courses often exhibit low academic performance. One way to address this issue is by implementing early interventions for students. In higher education, various theories have contributed to the topic of intervention, one of which is Vygotsky’s zone of proximal development. However, there is no consensus in the results, and more studies are needed to evaluate early interventions in CS1 courses. The objective of this research is to examine the effect of an early intervention on students’ academic performance in a CS1 course. The study involved 49 students from a Logic Programming course, with 24 in the experimental group and 25 in the control group. Two stages of the zone of proximal development were used, including group tutoring and the development of a programming reinforcement workshop. Additionally, the Motivated Strategies for Learning Questionnaire (MSLQ) was used to identify the learning and motivation strategies employed by students in a CS1 programming course. The quantitative results of the experimental group show a positive correlation between the percentage of attendance at group tutoring sessions and the student’s final grade. Furthermore, a positive correlation was identified between the percentage of submitted reinforcement exercises and the student’s final grade. In the control group, significant improvements were identified in four subscales of the selected learning and motivation strategies questionnaire, even though no intervention strategy was applied.

The Tobii eye-tracker device reference T-120 was designed to record eye movements in observers whose face is parallel to the monitor. However, by inverting the face position, the sampling rate of captured data may decrease, as well as the recorded eye fixations. The present study wanted to compare the differences in sampling rates and durations of ocular fixations when inverting the face 180⁰, when performing a visual task for 20 s. 96 participants, divided into two groups, observed the same visual stimulus in front of a Tobii T-120 eye-tracker device, half in a normal position, the other half with their faces inverted. The results show that there are differences in the sampling of the captured data and also in the durations of ocular fixations in a salient area of the stimulus, with a significant decrease in those who were in an inverted position. It is concluded that the variation in the position of the eyes affects both the sample of the captured data and the durations of ocular fixations, a fact that has to be estimated when recording eye-movements with remote eye-trackers like the Tobii T-120. The inversion of the face exerts an effect on data sampling concerning oculomotor activity. This decrease of the amount of ocular data is an important issue to take into consideration when conducting research projects in which face positions are atypical in relation to the standards suggested by manufacturers of the Tobii-T-120.

At present, most information is stored on mobile devices such as smartphones, whether for personal or business use. This promotes the availability and access to said data at any time. However, users may be victims of data loss due to physical or logical damage to mobile devices, requiring an advanced procedure for recovery. This work proposes a general recovery process based on the DoJ2 forensic analysis methodology. To achieve this objective, the eMMC memory is extracted from the mobile device by applying the ISP (In-system programming) or chip-off method depending on the level of criticality. The results showed high effectiveness with the ISP method, reaching 100% data recovery when the equipment is blocked.

In the district of Cabanaconde, maize agricultural production faces significant challenges due to the lack of efficient grain processing methods. This study introduces the design and implementation of a corn grain cleaning and sorting machine capable of processing 150 kg/h, aimed at enhancing productivity efficiency and grain quality at Peruanita company. Through a methodology that includes needs analysis, mechanical design, and prototype evaluation, a system combining threshing, cleaning, and sorting technologies was developed. The results showed a significant increase in productivity and a reduction in processing time, with operability that respects grain quality standards. The conclusions underline the importance of integrating technological solutions in agriculture to meet efficiency and sustainability challenges, highlighting the potential of this machine to be replicated in other regions with similar challenges.

The purpose of this study was to identify the state of the aids to navigation in the roadstead of Salinas and Libertad, because these devices constitute a learning resource for students of the Dual Career of Naval Sciences of the Special Academic Unit ESSUNA endorsed by the University of the Armed Forces-ESPE, contribute to execute the practices of seamanship in real environments, assist the maritime transit of oil tankers, as well as guide tourists who use the beaches of San Lorenzo and Chipipe; In order to have safe maritime spaces that comply with national and international regulations; since the absence of these or their deterioration represent a danger for navigators and citizens. It answers the question: What actions are necessary to mitigate the operational risk in landfall maneuvers in Salinas and Libertad; for this purpose, a mixed approach was used with quantitative elements by collecting data through a questionnaire; in addition, qualitative information was collected from primary sources through structured interviews. The study population was 250 people and the design was non-experimental and cross-sectional. With the results, it was determined that it is necessary for the Hydrographic Service of the Ecuadorian Navy to implement and modernize the aids to navigation, create awareness campaigns so that the personnel who carry out activities at sea report the deficiencies found; in conclusion, the non-compliance by tourist vessels of the International Regulations to Prevent Collisions and Collisions added to the limited signaling of the sector increases the risk of accidents.

Virtual reality (VR) has emerged as a transformative tool in several fields, and education is no exception. By creating immersive, interactive environments, VR enables learners to practice language skills in realistic and engaging contexts. This technology simulates real-world situations and provides learners with practical experience and cultural immersion, where students can navigate virtual scenarios, interact with virtual characters, and receive instant feedback. The user experience (UX) of a VR application for language learning among university students is the focus of this study. The study in a VR lab involved 56 students from modern languages, cultural management, and engineering programs with A2-B1 English proficiency levels. The findings underscore the importance of focusing on usability, sustained engagement, and long-term value in VR educational tools. This research provides insights for developing more effective VR-based educational applications.

Nigerian native languages can still be classified as under-resourced concerning the text and speech resources required for technology development. This limitation strikes all human endeavor facets, including healthcare. The study aims to develop multilingual Nigerian speech resources (English, Yorùbá, and Pidgin languages speech) for antenatal orientation. We collected the dataset from LTH in six (6) different Antenatal clinics using an 8 GB Sony digital voice recorder Midget system, along with a language expert. Each clinic had about an hour of orientation before the nurses began to attend to the pregnant women one after the other. The collected dataset was aligned with the World Health Organisation standard on antenatal. The dataset collected was transcribed into English language and later annotated into Yorùbá (Yorùbá Oyo) and Pidgin languages. The speech version was also developed for the three languages. The project uses the English, Yorùbá, and Pidgin language datasets in text and speech. The word count is 2639, 3202, and 2521 for English, Yorùbá, and Pidgin languages, respectively. These were produced (Speech) in 59880, 70380, and 69840 for English, Yorùbá, and Pidgin languages, respectively. The size of the speech dataset was 15.6, 17.9, and 18.3KB for English, Yorùbá, and Pidgin languages, respectively. The dataset was harvested with a higher level of annotation used as a baseline from under-resourced multilingual Nigeria speech for antenatal orientation and out-of-domain speech data.

This research work presents the development of a portable educational mechatronic device that enhances learning in children with attention deficit hyperactivity disorder (ADHD) from the age of three. The device has been designed to facilitate learning through structured interaction focused on games and activities that improve attention and memory, keeping children motivated and engaged with immediate and positive feedback. It stands out for its attractive mechanical design, made from PLA material, and its control via a Raspberry Pi 3, which offers sufficient efficiency for its purpose. It includes a 7-inch touch screen that improves user interaction, making it more intuitive, as well as speakers that emit white noise to improve children’s attention. A mixed methodology between VDI 2206 and MIT was used to achieve the proposed objectives. The results of this research promise to improve attention and memory with an attractive and practical design, a stable structure, an intuitive mechanism, and electronic components suitable for children with mild ADHD.

This article delves into the seamless integration of emotions into AI systems and its potential to enhance human-machine interactions in the context of social research. Furthermore, it strives to contribute to the development of future AIs that excel in responsiveness, empathy, and intuitiveness in their interactions with humans, promising superior user experiences, particularly in sectors like healthcare, education, and entertainment. Ethical considerations, encompassing data privacy, bias mitigation, and transparency, are examined meticulously to ensure that AI is developed and employed responsibly in line with international guidelines. To address these aspects, our study encompassed 25 focus groups and 18 h of ethnographic field notes, involving sociologists, anthropologists, and psychologists who engaged in discussions regarding the intersection of emotions and AI. The outcomes revealed an overall negative and cautious attitude toward these technologies, marked by a multitude of concerns that pose substantial hurdles in integrating AI into social research. An additional noteworthy concern is the perception of AI as peripheral and non-essential in daily life. Participants regarded these technologies as superfluous and questioned their relevance in social research. Mitigating this perception may require effective communication to underscore the value and utility of AI in this context.

Normally, university students are concerned about their academic progress which is reflected with the knowledge and skills acquired in the courses they attend. However, such knowledge and skills depend on the professors’ academic and social capabilities. In this way, students may appreciate having in advance information regarding professors’ methodology, suitability, and kindness, among other qualities, when enrolling in a specific course. This information might be provided by students who already have attended a course with a certain professor. Thus, in this work, we propose an academic social network to enable students to offer references to professors to support other students when enrolling in new courses. Such references include comments and grades for desired criteria that describe the professors’ qualities.

In the following project, the VLSI (Very Large Scale Integration) design of a simple mixed hardware was carried out, capable of extracting sinusoidal stimuli encoded in Pulse Density Modulated (PDM) signals through sigma-delta modulation for exciting Device Under Test (DUT) in mixed-signal integrated circuits. The main feature of this system is its programmability, which allows the user to select, according to their needs, the parameters of the waveform they wish to generate. Additionally, a signal digitizer is developed to extract the response signals of the excited blocks in digital format. Although the focus of the work is on the design of the integrated hardware, a Matlab® algorithm was developed to obtain PDM signals. This software version allows verifying the principle of operation of the developed system. The hardware was designed using 0.12 µm CMOS technology, to be powered with simple and dual  ±1.5V and  ±1.0V sources. Signal digitizer resolutions of 5 bits were achieved with an oversampling of 10.

The multidisciplinary nature of software architects demands a diverse set of skills, ranging from technical expertise to interpersonal abilities. Within this domain, software architects are responsible for designing systems that adhere to quality standards, meet functional requirements, and align with organizational goals. However, educating or training software architects presents a challenge due to the complexity of their roles and responsibilities. To address this challenge, this paper proposes an approach to understanding the learning styles of software architects using Kolb’s Learning Style Inventory (KLSI). It aims to provide a characterization of their teaching and learning preferences, thus facilitating the design and execution of educational strategies tailored to their specific needs. In conducting our research, we utilized LinkedIn as a platform to distribute the KLSI Test, ultimately gathering a sample comprising 18 Senior and Mid-Senior Software Architects. Through trend analysis of their responses, we consistently observed a discernible pattern. This led us to identify the Deciding Learning Style as the primary approach among the sample of software architects regarding their learning preferences. This finding offers initial insights into the predominant learning style within this profession, providing valuable guidance for educational practitioners and institutions aiming to optimize their training programs for software architects.

The increasing digitalization and globalized use of the Internet have increased the exposure of people and institutions to cyber attacks that compromise their sensitive information, involving computer security systems in its mitigation; therefore it is emerging to improve the security of communications. This study presents an experimental prototype to implement free Let’s Encrypt TLS certificates at the DAME Clinic in Quito, improving communications security at the transport layer. A methodology was developed that included the installation and configuration of the Proxmox VE hypervisor, the implementation of virtual services, the installation of TLS certificates and vulnerability analysis. Free TLS certificates from Let’s Encrypt were installed on virtual services (web server, email and video conferencing) deployed on Proxmox VE. The vulnerability analysis, carried out using the QUALYS SSL LABS tool, showed a notable improvement in the security of communications, especially in the videoconferencing service, which obtained a Type A+ rating (TLSv1.2 - TLSv1.3). The proposed methodology facilitated the fulfillment of the research objectives, highlighting the importance of the use of containers in Proxmox VE for the centralized control of services and the improvement of security in the DAME Clinic. Obtaining as results of mitigation and improvement of its services, 35% in Web/WordPress, 65% in Conference/Jitsi and Email.

The integration of Multiple-Input Multiple-Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) offers significant performance improvements by leveraging the strengths of both technologies, resulting in enhanced data throughput, coverage, and energy efficiency. Traditional modulation techniques such as QPSK, 16QAM, and 64QAM, while effective, are limited in their ability to maximize spectral efficiency and data rates, particularly in the high-Signal-to-Noise Ratio (SNR) conditions prevalent in 5G networks. This study extends the evaluation to higher-order schemes including 256QAM, 1024QAM, and 4096QAM to address these limitations. Key performance metrics analyzed include Bit Error Rate (BER), throughput, and spectral efficiency. Using MATLAB simulations, results demonstrate that higher-order modulation schemes provide superior performance in terms of throughput and spectral efficiency at higher SNRs, emphasizing their potential to enhance data rates and reliability in 5G MIMO-OFDM systems. Conversely, lower-order schemes like QPSK exhibit greater robustness in noisy environments, highlighting their continued relevance in specific scenarios where reliability is prioritized over spectral efficiency. Future research should explore the potential of hybrid modulation approaches, which combine the strengths of both low- and high-order schemes to optimize performance across varying network conditions.