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Explaining the Applicability of the Stimuli-Organism-Response (SOR) Framework in UX Processes for Static and Dynamic Contexts 2

Explaining the Applicability of the Stimuli-Organism-Respons...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Mkpojiogu, Emmanuel O.C. Okeke-Uzodike, Obianuju E. Abdullahi, Monday Jubrin Universiti Utara Malaysia Uum Sintok06010 Malaysia Veritas University Department of Software Engineering Abuja Nigeria Durban University of Technology Department of Applied Management Pietermaritzburg South Africa Airforce Institute of Technology Department of Computer Science Kaduna State Kaduna Nigeria

ISBN: (纸本)9798350360523

The implementation of the Stimuli-Organism-Response (SOR) framework introduced by Mehrabian and Russell in 1974 is described in this paper. The framework as an environmental psychology framework specifies that the organism of a person who interacts with a specified external object is influenced by specified external environmental factors. These factors make the individual to respond in some particular way by either accepting or avoiding the objects. With respect to user experience (UX), the external interactive objects are any interactive artifact which a user interacts with in certain specified context. The external environmental factors are design factors or quality attributes that impact or activate (arouse) the user's organism. The organism is the user's being that is influenced by external stimulating factors. The influenced organism responds by either approaching the object (interactive application) in delight;satisfaction and pleasure or avoiding the interactive product in disgust, frustration, and pain. Notwithstanding the benefit of this framework, the application is rarely employed in the context of UX. This study seeks to flag off awareness on how applicable the framework is to UX research. © 2024 IEEE.

关键词： User interfaces

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A survey and recent advances in black widow optimization: variants and applications

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Neural Computing and Applications 2024年 1-21页

作者： Shehab, Mohammad Shambour, Mohd Khaled Yousef Abu Hashem, Muhannad A. Al Hamad, Husam Ahmad Shannaq, Fatima Mizher, Manar Jaradat, Ghaith Sh. Daoud, Mohammad Abualigah, Laith College of Computer Sciences and Informatics Amman Arab University Amman11953 Jordan The Custodian of the Two Holy Mosques Institute for Hajj and Umrah Research Umm Al-Qura University Makkah Saudi Arabia Department of Geomatics Architecture and Planning Faculty King Abdulaziz University Jeddah Saudi Arabia College of Engineering Al Ain University Abu Dhabi United Arab Emirates Research Center University of Tabuk Tabuk71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq25113 Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Applied science research center Applied science private university Amman11931 Jordan College of Engineering Yuan Ze University Taoyuan32003 Taiwan

Artificial Intelligence techniques, such as optimization algorithms, have become essential for success in many fields. Therefore, most researchers, especially in computer and engineering sciences, focused their efforts and abilities on adapting the optimization algorithms for solving various problems. This review introduces one of the recent nature-inspired optimization algorithms, called black widow optimization (BWO). This review highlights the main procedures of BWO, its strengths and weaknesses, the growth of BWO, the variants of BWO (i.e., binary, modification, and hybridization), and the efficiency of BWO in different fields and applications (i.e., feature selection, medical, image processing, engineering, IoT, power and energy, and networks). As a result, the review seeks to assist researchers who are interested in using the BWO to address their challenges. For instance, it could help manage large pilgrim crowds, enabling smoother ritual performances and overcoming potential difficulties they encounter. Also, it suggests new possible ways of enhancing the efficiency of the basic BWO. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Optimization

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OLBR: Optimization of Location-Based Routing Protocols in Vehicular Ad Hoc Networks

OLBR: Optimization of Location-Based Routing Protocols in Ve...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Srikar Reddy, M. Vivek Ullas, Karthik Khadar Jilani, N. Abdul Venkatesh, K. Janet Kumari, J. Jesy Saleem Raja, A. Amrita School of Computing Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350309140

The proposed work employs ns-3, SUMO, and NetAnim to create geographical routing in vehicular ad hoc networks (VANETs). The research attempts to assess the performance of three well-known protocols AODV, DSDV, and OLSR in VANET settings. Utilizing SUMO's realistic mobility models and NS3's simulation capabilities, the project simulates node communication, protocol behaviour, and vehicle movement. The main purpose is to know how well various routing techniques work in dynamic vehicular situations. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Enhanced Metaheuristics with Trust Aware Route Selection for Wireless Sensor Networks

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computer Systems science & engineering 2023年第8期46卷 1431-1445页

作者： A.Francis Saviour Devaraj T.Satyanarayana Murthy Fayadh Alenezi E.Laxmi Lydia Mohamad Adzhar Md Zawawi Mohamad Khairi Ishak Department of IT The University of Technology and Applied Sciences-IbriPO Box:466IbriPostal Code:516Sultanate of Oman Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains MalaysiaNibong Tebal14300PenangMalaysia

Recently,a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks(WSN).In routing,the trust system includes or avoids nodes related to the estimated trust values in the routing *** article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol(EMTA-SRSP)for *** presented EMTA-SRSP technique majorly involves the optimal selection of routes in *** accomplish this,the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data *** the clustering process,the nodes with maximum residual energy will be considered cluster heads(CHs).In addition,the OAOA technique gets executed to choose optimal routes based on objective functions with multiple parameters such as energy,distance,and trust *** experimental validation of the EMTA-SRSP technique is tested,and the results exhibited a better performance of the EMTA-SRSP technique over other approaches.

关键词： Security wireless sensor networks trust factor routing protocol privacy

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Fused Transformers: Fused Information of Arabic long Article for Summarization 6

Fused Transformers: Fused Information of Arabic long Article...

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6th International Conference on AI in Computational Linguistics, ACLing 2024

作者： Ezzat, Zeyad Khalfallah, Ayman Khoriba, Ghadad Center for Informatics Science Information Technology and Computer Science School Nile University Giza Egypt Computer and Systems Department Faculty of Engineering Alexandria University Alexandria Egypt Applied Innovation Centre Egypt Faculty of Computers and Artificial Intelligence Helwan University Cairo Egypt

This paper introduces a novel approach for extending the applicability of pre-trained models to accommodate longer texts. Addressing the inherent limitation of quadratic performance in attention models within transformers, we propose the concept of fused transformers. By integrating new adaptor techniques, we enhance the encoding of lengthy text segments by breaking them into shorter spans. Subsequently, these segments are fused to increase the model's effectiveness in processing extended texts. This fusion mechanism serves to fortify the model's capacity for fine-tuning. Furthermore, we implement a length-based curriculum for expedited training Our experiments yielded 16 Rouge-2 points, representing a doubling of the score achieved by the vanilla fine-tuning method on the newly introduced "Mukhtasar" dataset for summarization. This highlights the effectiveness of managing complex relations among text segments and confirms that our method can outperform conventional training approaches. © 2024 Elsevier B.V.. All rights reserved.

关键词： Distribution transformers

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Smart Traffic Management in Green VANETs: Ant-Inspired Routing Strategies with Local Search Optimization

Smart Traffic Management in Green VANETs: Ant-Inspired Routi...

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2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024

作者： Thangam, S. Jahnavi, M. Chandana, K. Dheeraj, K. Janet Kumari, J Jesy Saleem Raja, A. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Bengaluru India University of Technology and Applied Sciences-Shinas College of Computing and Information Sciences It Department Oman

ISBN: (纸本)9798350309140

Green Vehicular Ad-hoc Networks (VANETs) are gaining significance in smart mobility because of growing concerns about the environment. The research introduces a novel method for managing traffic in such networks by combining ant-inspired routing methods with local search optimization approaches. The solution, which draws inspiration from the efficient path-finding abilities of ants, facilitates decentralized communication and sharing of traffic data among cars. It allows rapid adaptation to changing traffic circumstances and environmental elements. Local search optimization enhances routing decisions by considering the near vicinity of each vehicle. Extensive simulations demonstrate notable enhancements in traffic efficiency, decreased congestion, and improved energy conservation as compared to conventional routing methods. The suggested solutions also enhance the development of environmentally friendly and enduring transportation networks. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Body Fat Prediction using Various Regression Techniques 2

Body Fat Prediction using Various Regression Techniques

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2nd IEEE International Conference on Advances in Computing, Communication and applied Informatics, ACCAI 2023

作者： Mahesh, Nikhil Pati, Peeta Basa Deepa, K. Yanan, Suresh Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Bengaluru India Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India University of Technology and Applied Sciences-Al Musannah Sultanate of Oman Department of Engineering Oman

ISBN: (纸本)9798350315905

Predicting body fat percentage is essential for addressing the obesity problem. This paper compares the performance of several machine learning models based on Regression, to predict the body fat percentage. Using a dataset of 252 participants with information on age, weight, height, and fat percentage, the models were assessed based on multiple performance criteria, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Squared Error(MSE). The results demonstrates that Random Forest Regressor surpass other models with a lower RMSE of 0.276. These findings suggest that machine learning models can be a valuable tool for precise BFP, the use of machine learning provides a faster and more precise method for predicting body fat percentage. Overall, the study's results suggest that machine learning models can be valuable tool for accurate body fat percentage prediction. © 2023 IEEE.

关键词： Forecasting

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Effect of E-Learning on Public Health and Environment During COVID-19 Lockdown

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Big Data Mining and Analytics 2021年第2期4卷 104-115页

作者： Avani Agarwal Sahil Sharma Vijay Kumar Manjit Kaur Department of Computer Science Thapar Institute of Engineering and TechnologyPatiala 147001India Department of Computer Science and Engineering National Institute of TechnologyHamirpurHimachal Pradesh 177005India Department of Computer Science Engineering School of Engineering and Applied SciencesBennett UniversityGreater Noida 201310India

E-learning is the most promising venture in the entire world. During the COVID-19 lockdown, e-learning is successfully providing potential information to the students and researchers. In developing nations like India, with limited resources, e-learning tools and platforms provide a chance to make education available to middle and low income households. This paper gives insights about three different online services, namely Google Classroom,Zoom, and Microsoft Teams being used by three different educational institutions. We aim to analyze the efficiency and acceptability of e-learning tools among Indian students during the COVID-19 lockdown. The paper also aims to evaluate the impact of e-learning on the environment and public health during COVID-19 lockdown. It is found that e-learning has potential to reduce carbon emissions, which has beneficial impact on the environment. However, the mental health is impacted as e-learning may lead to self-isolation and reduction in academic achievements that may lead to anxiety and mental depression. Due to usage of electronic devices for learning, the eyes and neck muscles may be put in strain, having deleterious effects on physical health.

关键词： e-learning environment health COVID-19

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Resource Allocation in Edge Computing Environment Using Deterministic Policy Gradient Algorithm

Resource Allocation in Edge Computing Environment Using Dete...

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International Conference on Advanced Computing and Communication Systems (ICACCS)

作者： C. P. Shabariram N. Shanthi P. Priya Ponnuswamy V. Subramaniyaswamy V. Sathana Department of Computer Science and Engineering PSG Institute of Technology and Applied Research Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Erode India Department of Computer Science and Engineering School of Computing SASTRA University Thanjavur India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384376

In recent years, the edge computing paradigm enables the movement of processing units and storage nearer to the data available locations. The mechanism completes the computation in a short span of time in minimum bandwidth. Edge ecosystem is a type of distributed computing that is sensitive to topology and geography; the Internet of Things is a prime instance of this. Rather than referring to a single technology, Edge computing refers to an architecture. This paper proposes a resource allocation methodology that will enliven the situation between users and edge servers. By creating continuous control at the edge servers to determine resource allocation, edge computing improves reaction time, provides high security with decreased risk, scalability, lowers transmission costs, and versatility (offload targets, migration bandwidth and computing resources). The Deterministic Policy Gradient, Deep learning and Quality Network concepts are combined in the proposed system. The continuous action space is achieved by a deterministic policy gradient. The experience relay includes a quality network. In the proposed system, the actor-critic network produces a single continuous action instead of resulting probability based actions. The critic-part uses Q-value from a quality network based on current status and activity. The goal of the proposed system is to develop a Deep Deterministic Policy Gradient methodology to allocate servers for mobile users with the help of the Edge computing while taking computation resources, offloading goals and migration bandwidth into consideration. The simulation result indicates that deterministic policy gradients integrated deep learning models improve the system performance compared with Game theory.

关键词： Deep learning System performance Simulation Scalability Bandwidth Topology Servers Resource management Security Edge computing

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Optimization Algorithms for Sidelobes SSL Reduction: A Comparative Study

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Journal of computer and Communications 2024年第7期12卷 120-132页

作者： Mohsen Denden Aymen Alhamdan Department of Computer Science Higher Institute of Applied Sciences of Sousse Sousse University Sousse Tunisia Department of Electrical Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah Saudi Arabia

The development of new technologies in smart cities is often hailed as it becomes a necessity to solve many problems like energy consumption and transportation. Wireless networks are part of these technologies but implementation of several antennas, using different frequency bandwidths for many applications might introduce a negative effect on human health security. In wireless networks, most antennas generate sidelobes SSL. SSL causes interference and can be an additional resource for RF power that can affect human being health. This paper aims to study algorithms that can reduce SSL. The study concerns typical uniform linear antenna arrays. Different optimum side lobe level reduction algorithms are presented. Genetic algorithm GA, Chebyshev, and Particle Swarm Optimization algorithm are used in the optimization process. A comparative study between the indicated algorithms in terms of stability, precision, and running time is shown. Results show that using these algorithms in optimizing antenna parameters can reduce SSL. A comparison of these algorithms is carried out and results show the difference between them in terms of running time and SSL reduction Level.

关键词： SSL Radio Wave Interference SAR Linear Antenna Arrays Genetic Algorithm Chebyshev Particle Swarm Optimization

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