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User eXperience (UX) Evaluation in Virtual Reality (VR) 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Garcia, Matias Cano, Sandra Moreira, Fernando Pontificia Univ Catolica Valparaiso Sch Comp Engn Valparaiso Chile Univ Portucalense REMIT IJP Porto Portugal Univ Aveiro IEETA Aveiro Portugal

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

The potential of Virtual Reality (VR) devices lies in their ability to put the user in an interactive 3D environment as seen in simulations, prototyping and gaming. In order to create a more valuable experience in these environments, it is important to not only evaluate users' behavior, but also understand their preferences and emotions in this context. However the challenge of applying User eXperience (UX) evaluation in VR comes from the fact that behavioral methods may require the use of additional hardware to capture objective data unlike attitudinal methods which depend on what the user expresses during and after the experiment. This review lists the UX evaluation methods, comparing their applicability in VR devices, considering aspects such as complexity, data analysis and additional requirements. We also discuss the feasibility and benefit of combining these two types of evaluation methods in the same case of study.

关键词： UX evaluation Virtual Reality Human-Computer Interaction

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Fuzzy Logic-Based Energy Management System for an AC Microgrid 4th

Fuzzy Logic-Based Energy Management System for an AC Microgr...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Rahmouni, Ayoub Yousfi, Driss Bachiri, Mohammed Bakhouya, Mohamed Rochd, Abdelilah Univ Mohammed Premier Oujda Natl Sch Appl Sci ESETI Lab Oujda Morocco Int Univ Rabat Coll Engn & Architecture LERMA Lab El Jadida 11100 Morocco Green Energy Pk GEP Benguerir Morocco

ISBN: (纸本)9783031686740;9783031686757

Microgrids, as decentralized production systems, are attracting increasing interest due to their greater efficiency and reliability, helping to redefine the way we approach the transition to cleaner energy. At the same time, sustainable energy resources such as solar, wind, hydro, etc. are positioning themselves as indispensable pillars in this evolution towards a more sustainable energy future. This study focuses on sizing and energy management for an AC microgrid. The system integrates a photovoltaic (PV) source, energy storage sources (ESS) and the distribution grid as a backup source. The main objective is to propose an approach to energy management using fuzzy logic to ensure stable energy distribution between renewable sources and loads, guaranteeing an efficient, sustainable and reliable power supply. A dimensional analysis was carried out using Homer Pro software for the region of Oujda, Morocco, followed by a temporal simulation in the Matlab/Simulink environment. This simulation confirmed the ability of themicrogrid to operate safely, while guaranteeing the efficiency of the energy management system employed. Parameters such as photovoltaic energy availability, load demand, and battery state of charge are taken into account to optimize the power supply. This research makes a significant contribution by demonstrating the viability of an AC microgrid and developing an energy management system that will be implemented in a future scaled-down laboratory prototype.

关键词： MG-FARM Microgrid Smart city Fuzzy logic Energy management system Prototype Homer Pro Matlab/Simulink Photovoltaic

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Exploring Critical Success Factors in the Adoption of Industry 4.0 by Using DEMATEL Technique 7th

Exploring Critical Success Factors in the Adoption of Indust...

引用

7th International Conference on Logistics Operations Management (GOL)

作者： Jamouli, Younes Tetouani, Samir Soulhi, Aziz ESITH Higher Sch Text & Clothing Ind Casablanca Morocco ENSMR Natl Higher Sch Mines Rabat Morocco

ISBN: (纸本)9783031686337;9783031686344

Globalization has created a highly competitive and diverse market, an uncertain and risky business environment, and changing customer expectations. An effective manufacturing strategy reduces complexity and provides organizations with a well-organized manufacturing structure. However, existing research on "Industry 4.0 adoption" appears scattered, lacking systematic understanding and finding no causal relationship between critical success factors (CSFs) in the adoption of Industry 4.0 (I4.0) and their importance. Therefore, this study discusses the essential factors of success for implementing (I4.0) in SMEs operating in clothing sector in Morocco, which have differing specific application characteristics from the conditions in other countries, utilizing the decision-making trial and evaluation laboratory (DEMATEL) approach. This method is considered an effective method for identifying the cause-effect relationship of complex problems. It evaluates interdependent relationships among CSFs from the perspective of academic and industry experts. Identifying cause and effect factors leads to increasing the market's competitiveness and prioritizing them. Results show that Organization and environment are the main dimensions to successfully implement I4.0.

关键词： Critical success factors (CSF) Industry 4.0 DEMATEL

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Impact of Internet of Things in Smart Agriculture 8th

Impact of Internet of Things in Smart Agriculture

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Siva, Vijay Ponnusamy, Vijayakumar SRM Inst Sci & Technol Dept Elect & Commun Engn Chengalpattu Tamil Nadu India

ISBN: (纸本)9789819713226;9789819713233

IoT in agriculture bought remarkable improvement in food production. It not only improves production. It enhances the quality of agricultural products and decreases the cost of labor. The architecture of IoT is analyzed. The current status of IoT in agriculture is discussed. Five key technologies were discussed: sensor perception technology, information processing, information transmission, radio-frequency identification, Geographic Information System technology, and Global Navigation Satellite System. The role of IoT in various agricultural operations, such as harvesting, fertilizer spray, and weed detection, is discussed in detail. The part of multiple sensors in agriculture is analyzed. The limitations of IoT and prospects are analyzed.

关键词： Internet of Things Agriculture Fertilizer spray Weed detection Harvesting

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Theory of Programming Adoption

Theory of Programming Adoption

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Computing Conference

作者： Ampofo, Isaac Atta, Sr. Ampofo, Isaac Atta Junior, Jr. Ampofo, Beatrice Badzongoly, Eugene Louis Batie Boateng, Francis Ohene Asiedu, William Univ Liverpool Brownlow Hill Liverpool L69 7ZX Merseyside England Univ Educ Winneba Ghana Ghana Commun Technol Univ Accra Ghana Aketen Appaih Menka Univ Skills Training & Entrep 1277 IPT Rd Kumasi Ghana

ISBN: (纸本)9783031622717;9783031622694;9783031622687

Experience in teaching up to university level in computer programming has proven to be a challenge due to the fact that many students did not have a proper exposure to programming during high school. There are teaching and learning theories that describes how teachers teach and students receive, process, and retain knowledge during learning. In literature, there is no theory that have been developed for programming adoption. Thus, the study developed theory of programming adoption. In testing the theory of programming adoption, descriptive and explanatory design was used to help test the model whether it fit the theory or not. The study covered programming students where these students were contacted through Google Forms to answer a questionnaire. Quota sampling technique was used because the study wanted to get as many programming students across the world. A total of 237 programming students took part in the survey. SPSS, AMOS and PROCESS macro were used to analyze the study and test the theory. The Theory of Programming Adoption shows that tutorials, project work and accessibility of resources on the internet have a strong significant effect on students' perception with 139.59%, 27.52% and 98.79% respectively. The highest mediating effect was a mediating effect of students' perception in the relationship between project work and programming adoption with a positive coefficient value of.6472, representing 64.72%. As such, the adoption of computer programming will be higher. The researchers recommend that the TPAshould be used to enhance the theoretical knowledge of future studies.

关键词： Programming Adoption Project work Tutorials Internet resource accessibility

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A Comprehensive Literature Review on Slope Entropy Algorithm: Bridging Past Insights with Future Directions

A Comprehensive Literature Review on Slope Entropy Algorithm...

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Computing Conference

作者： Segui Moreno, Juan Molina Pico, Antonio Univ Politecn Valencia Alcoi Campus Alcoy 03801 Spain

ISBN: (纸本)9783031622717;9783031622694;9783031622687

In recent years, the Slope Entropy (SlopEn) algorithm has been recognized as a critical tool for Time Series Analysis and Time Series Classification, particularly within biomedical signal processing. This paper presents a thorough literature review on the developments, applications, and advancements of the Slope Entropy algorithm, drawing extensively from the seminal work of Dr. David Cuesta Frau in 2019. By meticulously examining the existing literature, we discuss the algorithm's potential for unveiling intricate dynamics inherent in time series data and its capability for enhancing signal quality recognition. We also explore the algorithm's adaptability across various domains beyond biomedical applications, including finance and environmental monitoring. Furthermore, we identify potential areas of improvement, such as computational efficiency and real-time processing capabilities, which could pave the way for novel applications and methodologies. This review culminates in providing a clear roadmap for researchers aiming to employ the Slope Entropy algorithm in novel settings, contributing to its continuous evolution and broader acceptance in the scientific community.

关键词： Slope entropy Time series analysis Time series classification

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Artificial Intelligence in Renewable Energy: Bibliometric Review of Current Trends and Collaborations 1

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19th International Conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Kut, Pawel Pietrucha-Urbanik, Katarzyna Zelenakova, Martina Abd-Elhamid, Hany F. Rzeszow Univ Technol Fac Civil Environm Engn & Architecture Al Powstancow Warszawy 6 PL-35959 Rzeszow Poland Tech Univ Kosice Fac Civil Engn Vysokoskolska 4 Kosice 04200 Slovakia Zagazig Univ Fac Engn Zagazig 44519 Egypt

ISBN: (数字)9783031618574

ISBN: (纸本)9783031618567;9783031618574

The article presents a bibliometric analysis of publications on the use of artificial intelligence (AI) in the area of renewable energy sources (RES). The study is based on data downloaded from the Web of Science database, using the keywords "artificial intelligence" and "renewable energy". The aim of the analysis is to identify the main trends, research areas, as well as leading institutions and authors in this interdisciplinary field. The CiteSpace tool was used to process and visualize the data. The analysis covers publications from the last two decades, enabling understanding of the evolution and development directions of the combination of AI and renewable energy. Particular attention was paid to interactions between various branches of science, which allows for the identification of potential new research areas and interdisciplinary cooperation. The results of the analysis show how AI contributes to the development of renewable energy efficiency, management and integration, also highlighting challenges and opportunities for future research in this field.

关键词： CiteSpace Bibliometric Artificial Intelligence Renewable Energy

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Using Machine Learning to Predict Additional Taxi-Out Time as a Airport Key Performance Indicator in the Eurocontrol Zone 10th

Using Machine Learning to Predict Additional Taxi-Out Time a...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Simic, Edvin Begovic, Muhamed Sabic, Muharem Muharemovic, Ermin Univ Sarajevo Fac Traff & Commun Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

The need to expand the air transport system capacity has increased rapidly in the last few years. European airports are located in urban areas and have limited opportunities for expansion. In addition, there is high pressure on air traffic and is associated with reducing the negative impact on the environment. Therefore, it is important to optimize and transform the system from what already exists into a more efficient and greener one. This paper will evaluate how to use machine learning methods to predict a key performance indicator for airside operation, taxi-out time. Statistical correlation methods will be used to establish the dependence between attributes and the output variable. This will help decision makers with airport optimization measures and ease the decision-making process at the macroscale level.

关键词： Pearson correlation airport capacity prediction taxi-out time

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Automatic People Detection Based on RGB and Thermal Imagery for Military Applications 6th

Automatic People Detection Based on RGB and Thermal Imagery ...

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6th Iberian Robotics Conference (Robot)

作者： Matos, Joao Pedro Machado, Artur Ribeiro, Ricardo Moutinho, Alexandra Univ Lisbon Inst Super Tecn Lisbon Portugal Exerc Portugues Lisbon Portugal Univ Lisbon Inst Super Tecn ISR Lisbon Portugal Univ Lisbon Inst Super Tecn IDMEC Lisbon Portugal

ISBN: (纸本)9783031591662;9783031591679

Automatic detection of people in military applications offers numerous benefits that enhance situational awareness, operational efficiency, and overall security. RGB images offer high resolution and color information, making them suitable for detailed visualization, but they are limited by lighting conditions and can struggle to detect people in low-light or nighttime scenarios. Additionally, camouflage and adverse weather can hinder their effectiveness. On the other hand, thermal images detect heat signatures, enabling people detection in darkness and adverse conditions, but they may lack detail, and their cost is higher. Both technologies have their merits, and a combined approach can provide a more comprehensive solution for people detection in various military and security applications. This research contributes to the field of perception systems for military applications, by harnessing the potential of artificial intelligence (AI) and deep learning technologies. This paper presents a comparison of performance of three people detectors based on the YOLOv8 architecture, a computer vision model, namely using 1) RGB images, 2) thermal images, and 3) RGB and thermal images combined. A quantitative analysis of performance of the three models allows to compare their performance in realistic and challenging scenarios. Additionally, a qualitative assessment is conducted to identify specific limitations and advantages associated with each approach, providing valuable insights for further improvement and optimization of these detection systems.

关键词： Perception Deep learning YOLOv8 People detection RGB imagery Thermal imagery Military application Intelligence Surveillance and Reconnaissance

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Beyond Information System User Behavior Models: The Power of User Groups in Preventing Insider Attacks

Beyond Information System User Behavior Models: The Power of...

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Intelligent systems Conference

作者： Nikiforova, Oksana Zabiniako, Vitaly Riga Tech Univ Riga Latvia ABC Software Ltd Riga Latvia

ISBN: (纸本)9783031663284;9783031663291

Traditional information security methods, such as access control and firewalls, cannot always provide effective protection against internal threats. Analysis of user behavior allows us to identify anomalous actions that may indicate an attempt to gain unauthorized access to information or commit other illegal actions. The most common sign about suspicious user behavior is changing system usage patterns, atypical data queries, an attempt to access unallowed resources, sudden change in workload, etc. Various methods can be used to analyze user behavior, such as collection and analysis of data about user actions in the system and application of machine learning methods to identify anomalous patterns. All these methods analyze the behavior of individual users relative to their usual behavior. Such an analysis may be inaccurate if it is determined that the user regularly makes unauthorized use of information systems. This paper proposes grouping users according to their behavior patterns and analyze the behavior of each individual user against the behavior that is expected for the group. Then, by excluding user behavior data from the group's expected behavior pattern, the behavior pattern of the individual user can be analyzed against the behavior of the remained users in the group. The novelty consists in obtaining more precise behavioral analyzes by introducing the concept of subgroups (groups consisting of the users remaining after the extraction of the respective user, which is analyzed against expected behavior model of its group).

关键词： Insider threats Machine learning User behavior modelling e-StepControl

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