Authors - Nelson Herrera Herrera, Estevan Gomez-Torres, Paul Baldeon-Egas, Renato Toasa Abstract - The Context-Aware Mobile Systems (CAMS) framework simplifies the development of context-aware mobile applications using Model-Driven Development (MDD). CAMS incorporates a Domain-Specific Language (DSL) built with Xtext, enabling developers to model contextual information, define business rules, and establish event-driven behaviors. The generation of Android applications is automated via Acceleo, supporting the seamless integration of cloud services such as Azure Maps for geolocation, IoT Hub for sensor data management, and Twilio for contextual notifications. To enhance scalability and deployment efficiency, CAMS leverages Infrastructure-as-Code (IaC) solutions through Pulumi and Terraform, automating cloud resource provisioning. This approach reduces development complexity, minimizes manual configurations, and accelerates deployment cycles. A case study on package tracking showcases CAMS' ability to dynamically adjust application behavior in real time based on contextual data from IoT sensors and geolocation services. Evaluation results demonstrate a 40% reduction in development time compared to traditional methods, alongside improved scalability, supporting up to 10,000 IoT devices simultaneously. CAMS offers an innovative framework for developing intelligent mobile applications across various sectors, including logistics, smart cities, and real-time monitoring. Its modular architecture and automated deployment processes enable rapid prototyping and efficient scaling, making it adaptable to diverse application scenarios. Future enhancements include expanding support for iOS applications, integrating additional IoT capabilities, and incorporating AI-driven decision-making tools to enhance real-time responsiveness. CAMS positions itself as a robust and flexible solution for next-generation mobile applications, bridging the gap between contextual awareness and scalable cloud-based infrastructures.
Authors - Thavaprakash Arulsivakumar, Senthil Veerasamy Abstract - The perspectives and insights of sentiments on destinations are important for tourism stakeholders. Purpose of this research work is to understand tourist behaviour with the help of Electronic Word of Mouth (eWOM) and to bring out the cognitive insights using TripAdvisor for Asian destinations. A well-established Stimulus Organism Response (SOR) theory is used as a thematic foundation in this research and ChatGPT based content analysis is conducted using traveler reviews. Sample size of 151872 TripAdvisor review comments from 90 Asian destinations are analyzed in this research. Logistic regression and Structural equation modelling are used to examine the sample data. Empirical findings highlighted that travelers have unique sentiments on each destination and moderate positive sentiments influence the intention to visit. Macro and micro analysis is used in this research, its findings are re-shaping the demand and supply and is helpful for the decision makers to promote destinations.
Authors - Tihomir Dovramadjiev, Petya Manolova, Rozalina Dimova, Dimo Dimov, Vasil Gatev Abstract - This article investigates the interplay between human factors and criminology in identifying both the techniques and motivations behind cyber threats. By analyzing the psychological, social, and environmental drivers of cybercriminals, as well as the methods they employ, this study proposes a comprehensive framework for detecting and mitigating cyber threats. The integration of criminological theories and human factors research offers a novel approach to understanding and countering the evolving tactics of cyber attackers. In the era of Society 5.0, where human-centric technologies and artificial intelligence (AI) are deeply integrated into daily life, the role of human factors becomes even more critical. Human factors research helps uncover how cognitive biases, emotional states, and social influences shape both the behavior of cybercriminals and the effectiveness of defenders. For instance, AI-driven cybersecurity systems, while powerful, still rely on human oversight and decision-making, making it essential to address human vulnerabilities such as fatigue, stress, and misjudgment. Furthermore, as Society 5.0 emphasizes the fusion of cyber and physical spaces, understanding human behavior is key to designing systems that are resilient to social engineering, phishing, and other human-exploitative techniques. By combining main cybersecurity layers insights with human factors, this study not only addresses the technical aspects of cyber threats but also highlights the importance of human-centered design in cybersecurity of data assets.
Authors - Yuki Shirahama, Kayoko Yamamoto Abstract - In order to help yourself, it is necessary for the general public to keep adequate stockpiles in their homes that will be useful at the disaster outbreak times. Additionally, in order to provide mutual aid from the normal times, it is important for local residents to accumulate and share necessary information in a local community without relying on the government to provide information. Against such a backdrop, the purpose of the present study is to design, develop, operate and evaluate an original disaster information system to support self-help and mutual aid from the normal times to the disaster outbreak times, by integrating a stockpiling improvement support system, a local social network service (SNS) and web-geographic information systems (Web-GIS). Chofu City, Tokyo, was selected as the operation target area for the system. During the operation period of the system, the number of users was 57, and the number of information submitted by users was 25. From the result of the online questionnaire survey for users, it is evident that the system was useful in terms of improving the stockpiling situations in their homes at normal times, and in supporting the accumulation and sharing of disaster information among them from the normal times to the disaster outbreak times.
Authors - Marwan Babiker, Eda Merisalu, Zenija Roja, Henrijs Kalkis Abstract - A Health Information System (HIS) is an electronic database of managerial and clinical information, which allows physicians to utilize quality improvement processes in clinical practice and support multiple services in healthcare organizations. According to research, physician satisfaction varies greatly and is frequently correlated with particular features and the ease of exchanging information. The study aimed to identify the traits of doctors' acceptability of using a hospital information system (HIS) and their degree of satisfaction with it. It is a cross-sectional study that used an online self-administered survey, which was conducted among all 56 physicians working in family medicine centers in the Royal Commission health service program, Saudi Arabia. The questionnaire was used to assess the physician’s satisfaction level about the two structures that will be examined: system quality and satisfaction level. The findings showed that the physicians in the family medicine centers have a high agreement proportion about the use and satisfaction of the use of HIS, which indicates a high quality of the HIS. The outcomes measure system excellence and user satisfaction when assessing the effectiveness of HIS in several domains. The participating physicians expressed satisfaction with the way HIS improved their clinical processes and how reliable it was for patient care. More longitudinal studies are required to understand the indicator of physician satisfaction with the HIS use.
Authors - Rehab Hassan Bader, Issa A. Abed, Bayadir A.Isaa Abstract - Multi-Robot Systems (MRS) have developed as a disruptive technology in robotics, allowing multiple autonomous robots to work together to execute complex tasks. Multi-Robot Task Allocation (MRTA) is an important component of MRS since it involves distributing tasks to robots in a way that maximizes performance, efficiency, and resource use. Effective scheduling is crucial in MRTA because it determines the order and timing of task execution, which has a significant impact on overall system performance. This paper investigates current MRTA and scheduling strategies and algorithms, with an emphasis on the challenges raised by dynamic environments and the requirement for flexibility in task allocation. They discuss numerous approaches, including centralized and decentralized methods, constraint-based models, and reinforcement learning techniques, emphasizing the benefits and drawbacks. The combination of reallocation and rescheduling approaches is also being researched as a means of boosting system responsiveness to unanticipated changes. The findings suggest that future research should focus on developing hybrid models that take advantage of existing approaches to create more resilient and efficient multi-robot systems capable of operating in real-world scenarios.
Authors - Victoria Orozco Arias, Ernesto Rivera Alvarado Abstract - Data protection on websites is a common objective for entities and organizations, so new security strategies are constantly being sought. This research evaluates the effectiveness of using security metadata in HTML structures to protect sensitive data. To achieve this, a website scraping experiment will be conducted on sites that include authentication, to verify on which sites this type of fraud can be performed and to identify the use of security metadata. Our results show that 25% of the websites selected for the experiment could be extracted from the database, and the remaining sites have different settings, such as metadata, robots.txt file, and others, to protect and prevent data extraction. This proves that metadata is the first step of website security.
Authors - Ossman Lopez, Joan Alvarado, Juan Diaz-Gonzalez, Elisa Rendon-Cadavid, Sara Lopez, Mikel Maiza, Juan Felipe Restrepo-Arias, David Velasquez Abstract - This study presents the design and development of a non-invasive sensor for measuring the capacitance of cocoa fruits to detect ripening stages and the onset of fungal disease caused by Moniliophthora roreri. Capacitance is recognized in the state of the art as an effective physiological indicator due to its correlation with moisture content, cell development, and glucose levels in fruit. Based on this premise, the hypothesis was that capacitance measurements are directly related to fruit ripening and fungal infection. The sensor system features an electronic circuit that generates a 10V peak output at a frequency of 1 kHz, integrated with a Sauty Bridge for real-time capacitance measurements without harming the fruit. The device is lightweight, user-friendly, and energy-efficient. The experiments were carried out under controlled conditions using the CNCH13 cocoa variety to standardize the measurements. The preliminary results confirm a strong correlation between capacitance levels, ripening stages in healthy fruits, and the presence of fungal disease. The prototype developed effectively measures capacitance, providing a reliable method for assessing the physiological state of cocoa fruits.
