Article
Psychology, Multidisciplinary
Pauline Pfeifer, Tim Hilken, Jonas Heller, Saifeddin Alimamy, Roberta Di Palma
Summary: This research demonstrates that augmented reality smart glasses (ARSGs) outperform AR on touchscreen devices in terms of consumer perception, shopping experience, and purchase intention in the context of in-store retail. The findings highlight the importance of implementing ARSGs in-store and provide effective strategies for retailers.
COMPUTERS IN HUMAN BEHAVIOR
(2023)
Article
Business
Candy Lim Chiu, Han -Chiang Ho, Tiancheng Yu, Yijun Liu, Yuwen Mo
Summary: This study examines the predictors of user benefits of augmented reality retail applications in the retail food chain and proposes a model to investigate the mediating effects of user satisfaction and user continuance intention between quality perspectives and user benefits. The findings suggest that both user satisfaction and user continuance intention play positively mediating roles in all proposed relationships.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2021)
Review
Chemistry, Analytical
Matea Zilak, Zeljka Car, Ivana Culjak
Summary: Mobile augmented reality (MAR) has become increasingly popular and effective in various areas of human life. However, not everyone has the same access to this technology. This review paper analyzes handheld AR solutions developed for people with disabilities, identifying accessibility challenges and exploring potential research directions for personalization and customization. The findings can contribute to the creation of accessibility guidelines and the development of accessible AR solutions for both disabled and non-disabled individuals.
Article
Business
Yong-Chin Tan, Sandeep R. Chandukala, Srinivas K. Reddy
Summary: The rise of augmented reality technology offers promising opportunities for marketers to engage customers and transform their brand experience. Research shows that AR is most effective in reducing product-related uncertainty, leading to increased sales and enhanced purchase confidence, especially for less popular and more expensive products in retail settings.
JOURNAL OF MARKETING
(2022)
Article
Computer Science, Information Systems
Krzysztof Zywicki, Pawel Bun
Summary: The research found that while the AR method is effective in identifying materials in a production system, the traditional method is quicker. Therefore, improvements are needed for AR solutions to increase efficiency.
Article
Environmental Studies
Helen Lawton Smith
Summary: The lack of support for disabled entrepreneurs is a significant issue in the UK and many other countries. This study aims to identify ways to overcome the marginalization of disabled entrepreneurs, and promote equality of opportunity and diversity in local economies.
Review
Computer Science, Interdisciplinary Applications
Anthony Scavarelli, Ali Arya, Robert J. Teather
Summary: This survey delves into the utilization of Virtual Reality and Augmented Reality in social learning spaces like classrooms and museums, as well as exploring relevant social interaction concepts within immersive reality-based media frameworks. By examining properties and interactions pertinent to educational use in social learning spaces, and discussing various learning theories through a CSCL lens, a theoretical foundation is built for future virtual reality/augmented reality educational frameworks. The study also presents examples of virtual reality/augmented reality applications in learning, and suggests potential research areas such as focusing on accessibility, the interaction between physical and virtual environments, and updating learning theory foundations.
Article
Computer Science, Information Systems
Ruowei Xiao, Aleksi Vianto, Asif Shaikh, Oguz'oz' Buruk, Juho Hamari, Johanna Virkki
Summary: This article proposes an overarching architecture for seamlessly integrating Radio Frequency Identification (RFID) and virtual reality (VR). Through a comprehensive literature review, the authors identify key design themes and technical affordances of RFID within the VR context. The proposed architecture is demonstrated through three use cases, showcasing the potential and augmentation of RFID in VR applications.
Article
Chemistry, Analytical
Isaias Majil, Mau-Tsuen Yang, Sophia Yang
Summary: This study introduces a new cooking assistance system that utilizes AR and CV technology to allow users to recognize ingredients through gestures and receive recommended recipes. Experimental results show that while YOLOv5 has lower accuracy in ingredient recognition, it can easily locate and classify multiple ingredients, simplifying the scanning process for users.
Article
Computer Science, Information Systems
Oscar Danielsson, Magnus Holm, Anna Syberfeldt
Summary: This study iteratively improved an online tool with practical recommendations for implementing ARSG in production, based on evaluations from focus groups and case studies at three companies. The recommendations were found to be detailed and relevant by industrial representatives and companies, providing good support for considering ARSG integration into production.
Article
Business
S. R. Nikhashemi, Helena H. Knight, Khaldoon Nusair, Cheng Boon Liat
Summary: Smart retailing is a new form of retail brand management that uses technologies like mobile augmented reality applications to enhance customer experience. Research results suggest that the attributes of augmented reality have an impact on continuous use of shopping AR apps and willingness to pay a premium, and increasing AR customization can enhance relationships in the proposed model.
JOURNAL OF RETAILING AND CONSUMER SERVICES
(2021)
Article
Management
Nageswaran Vaidyanathan, Stefan Henningsson
Summary: This study investigates the design of augmented reality (AR) services in retail to enhance customer experiences. It uses a conceptual research approach and design thinking method to develop propositions and principles for effective AR service design.
JOURNAL OF SERVICE MANAGEMENT
(2023)
Review
Engineering, Industrial
Abderahman Rejeb, John G. Keogh, G. Keong Leong, Horst Treiblmaier
Summary: This study explores the potentials and challenges of utilizing augmented reality smart glasses in logistics and supply chain management, highlighting the benefits and obstacles, and setting a path for future research.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Telecommunications
Ali A. El-Moursy, Fadi N. Sibai, Jahanzeb Rehman, Omar M. Gouda, Abdelrahman T. Gaber, Ahmed M. Khedr
Summary: This paper proposes a smart appliance controller that uses Augmented Reality and IoT to control aftermarket home appliances. The system's characteristics are evaluated and the results show that MQTT has a quick response time, being 4 times faster than CoAP.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Chemistry, Analytical
Alice Lo Valvo, Daniele Croce, Domenico Garlisi, Fabrizio Giuliano, Laura Giarre, Ilenia Tinnirello
Summary: In recent years, the advancement in augmented reality systems and computer vision algorithms has enabled mainstream smartphones to accurately estimate their own motion in 3D space. This technology has been utilized to support autonomous mobility for people with visual disabilities, identifying virtual paths and providing context information for navigation.
Article
Psychiatry
Faith Matcham, Daniel Leightley, Sara Siddi, Femke Lamers, Katie M. White, Peter Annas, Giovanni de Girolamo, Sonia Difrancesco, Josep Maria Haro, Melany Horsfall, Alina Ivan, Grace Lavelle, Qingqin Li, Federica Lombardini, David C. Mohr, Vaibhav A. Narayan, Carolin Oetzmann, Brenda W. J. H. Penninx, Stuart Bruce, Raluca Nica, Sara K. Simblett, Til Wykes, Jens Christian Brasen, Inez Myin-Germeys, Aki Rintala, Pauline Conde, Richard J. B. Dobson, Amos A. Folarin, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Nick Cummins, Nikolay Manyakov, Srinivasan Vairavan, Matthew Hotopf
Summary: This study investigated the drop out and data completeness in a naturalistic multimodal longitudinal Remote Measurement Technologies (RMT) study in individuals with a history of recurrent Major Depressive Disorder (MDD). The study found that both active and passive forms of data collection were feasible in this patient group, with high completion rates and comparable levels of data availability.
Article
Automation & Control Systems
Bernat Gaston, Victor Casamayor-Pujol, Sergio Lopez-Soriano, Rafael Pous
Summary: Radio frequency identification (RFID) technology is widely used in the retail industry for accurate inventory management. This article presents a metric for assessing and comparing the performance of autonomous RFID-based robots in retail stores. The metric is based on a theoretical model and can predict the performance of a given robot in a specific store.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Automation & Control Systems
Victor Casamayor-Pujol, Bernat Gaston, Sergio Lopez-Soriano, Abdussalam A. Alajami, Rafael Pous
Summary: This article presents a simple solution using an autonomous ground robot with a radio frequency identification payload to estimate the location of products in a retail store. The model used is designed to be simple and versatile, while achieving accurate location estimations. The research results show that the model performs well in different environments and meets the business requirements of the retail industry.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Psychiatry
Yuezhou Zhang, Amos A. Folarin, Shaoxiong Sun, Nicholas Cummins, Srinivasan Vairavan, Rebecca Bendayan, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Petroula Laiou, Heet Sankesara, Faith Matcham, Katie M. White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Elisabet Vilella, Sara Simblett, Aki Rintala, Stuart Bruce, David C. Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda W. J. H. Penninx, Vaibhav A. Narayan, Peter Annas, Matthew Hotopf, Richard J. B. Dobson
Summary: This study examines the relationships and temporal directions between depressive symptom severity and phone-collected mobility data. Results show a significant negative correlation between depressive symptom severity and phone-measured mobility, with a stronger correlation at the within-individual level. Specific mobility features, such as home stay, location entropy, and residential location count, are significantly correlated with subsequent changes in depressive symptom severity. Changes in depressive symptom severity also significantly affect the subsequent periodicity of mobility.
JMIR MENTAL HEALTH
(2022)
Article
Health Care Sciences & Services
Yuezhou Zhang, Amos A. Folarin, Shaoxiong Sun, Nicholas Cummins, Srinivasan Vairavan, Linglong Qian, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Petroula Laiou, Heet Sankesara, Faith Matcham, Katie M. White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Sara Simblett, Aki Rintala, David C. Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda W. J. H. Penninx, Vaibhav A. Narayan, Peter Annas, Matthew Hotopf, Richard J. B. Dobson
Summary: This study explores the association between daily walking characteristics and severity of depression symptoms, finding a significant link between higher severity and decreased gait cadence during high-performance walking over a long-term period. The models with daily-life gait features performed better in predicting depression scores compared to models with only laboratory gait features. These findings are important for remotely monitoring mental health in real-world settings and developing clinical tools.
JMIR MHEALTH AND UHEALTH
(2022)
Article
Biochemistry & Molecular Biology
Petroula Laiou, Andrea Biondi, Elisa Bruno, Pedro F. Viana, Joel S. Winston, Zulqarnain Rashid, Yatharth Ranjan, Pauline Conde, Callum Stewart, Shaoxiong Sun, Yuezhou Zhang, Amos Folarin, Richard J. B. Dobson, Andreas Schulze-Bonhage, Matthias Duempelmann, Mark P. Richardson
Summary: This study used brain network metrics to characterize the temporal evolution of epileptic functional networks prior to seizures. The findings show that these metrics vary across days and exhibit a circadian periodicity. Additionally, the distribution of strength variance in the days before seizure occurrence is significantly different compared to previous days. These results suggest that brain network metrics could potentially be used to characterize brain network changes before seizures and contribute to the development of seizure warning systems.
Article
Medicine, General & Internal
Sara Siddi, Iago Gine-Vazquez, Raquel Bailon, Faith Matcham, Femke Lamers, Spyridon Kontaxis, Estela Laporta, Esther Garcia, Belen Arranz, Gloria Dalla Costa, Ana Isabel Guerrero, Ana Zabalza, Mathias Due Buron, Giancarlo Comi, Letizia Leocani, Peter Annas, Matthew Hotopf, Brenda W. J. H. Penninx, Melinda Magyari, Per S. Sorensen, Xavier Montalban, Grace Lavelle, Alina Ivan, Carolin Oetzmann, Katie M. White, Sonia Difrancesco, Patrick Locatelli, David C. Mohr, Jordi Aguilo, Vaibhav Narayan, Amos Folarin, Richard J. B. Dobson, Judith Dineley, Daniel Leightley, Nicholas Cummins, Srinivasan Vairavan, Yathart Ranjan, Zulqarnain Rashid, Aki Rintala, Giovanni De Girolamo, Antonio Preti, Sara Simblett, Til Wykes, Inez Myin-Germeys, Josep Maria Haro
Summary: During the COVID-19 lockdowns, there were biopsychosocial changes observed in individuals with Major Depressive Disorders (MDDs) and Multiple Sclerosis (MS). The symptoms of depression remained stable, but there were changes in heart rate, social activity, and physical activity. Remote technology monitoring could help detect these changes and provide early warnings in stressful situations.
JOURNAL OF CLINICAL MEDICINE
(2022)
Article
Psychiatry
Valeria de Angel, Fadekemi Adeleye, Yuezhou Zhang, Nicholas Cummins, Sara Munir, Serena Lewis, Estela Laporta Puyal, Faith Matcham, Shaoxiong Sun, Amos A. Folarin, Yatharth Ranjan, Pauline Conde, Zulqarnain Rashid, Richard Dobson, Matthew Hotopf
Summary: This study assessed engagement with remote measurement technologies (RMTs) in the context of depression treatment. The results showed that higher-intensity treatment and higher baseline anxiety were associated with lower engagement. Different data collection methods also exhibited different patterns of missing data. These findings have important implications for the scalability, accuracy, and long-term use of RMTs in healthcare.
JMIR MENTAL HEALTH
(2023)
Article
Physiology
Spyridon Kontaxis, Estela Laporta, Esther Garcia, Ana Isabel Guerrero, Ana Zabalza, Martinis Matteo, Roselli Lucia, Sara Simblett, Janice Weyer, Matthew Hotopf, Vaibhav A. Narayan, Zulqarnain Rashid, Amos A. Folarin, Richard J. B. Dobson, Mathias Due Buron, Letizia Leocani, Nicholas Cummins, Srinivasan Vairavan, Gloria Dalla Costa, Melinda Magyari, Per Soelberg Sorensen, Carlos Nos, Raquel Bailon, Giancarlo Comi
Summary: This study aimed to evaluate the association between changes in autonomic control induced by walk tests and outcome measures in people with MS. The results showed that people with SPMS had higher heart rate during walk test and larger sympathovagal balance after test performance compared to RRMS. Participants who were able to adjust their heart rate and ventilatory values were associated with better clinical outcomes. Weak associations were found between autonomic parameters and clinical outcomes when the phenotype of MS was not taken into account.
FRONTIERS IN PHYSIOLOGY
(2023)
Article
Health Care Sciences & Services
Yuezhou Zhang, Abhishek Pratap, Amos A. A. Folarin, Shaoxiong Sun, Nicholas Cummins, Faith Matcham, Srinivasan Vairavan, Judith Dineley, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Callum Stewart, Katie M. M. White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Carla Hernandez Rambla, Sara Simblett, Raluca Nica, David C. C. Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda W. J. H. Penninx, Peter Annas, Vaibhav A. A. Narayan, Matthew Hotopf, Richard J. B. Dobson
Summary: Recent growth in digital technologies has allowed for the recruitment and monitoring of large and diverse populations in remote health studies. However, uneven participant engagement and attrition can affect the generalizability of inference drawn from remotely collected health data. This study examined long-term participant retention and engagement patterns in a large observational digital study for depression, finding distinct patterns and factors associated with retention and engagement in the study.
NPJ DIGITAL MEDICINE
(2023)
Article
Clinical Neurology
Nicholas Cummins, Judith Dineley, Pauline Conde, Faith Matcham, Sara Siddi, Femke Lamers, Ewan Carr, Grace Lavelle, Daniel Leightley, Katie M. White, Carolin Oetzmann, Edward L. Campbell, Sara Simblett, Stuart Bruce, Josep Maria Haro, Brenda W. J. H. Penninx, Yatharth Ranjan, Zulqarnain Rashid, Callum Stewart, Amos A. Folarin, Raquel Bailon, Bjoern W. Schuller, Til Wykes, Srinivasan Vairavan, Richard J. B. Dobson, Vaibhav A. Narayan, RADAR-CNS Consortium
Summary: Speech rate, articulation rate, and intensity of speech are associated with depressive symptoms, suggesting that these speech features may serve as biomarkers for major depressive disorder (MDD). This study collected real-world data, providing significant insights into the onset and progress of MDD.
JOURNAL OF AFFECTIVE DISORDERS
(2023)
Article
Health Care Sciences & Services
Shaoxiong Sun, Amos A. Folarin, Yuezhou Zhang, Nicholas Cummins, Rafael Garcia-Dias, Callum Stewart, Yatharth Ranjan, Zulqarnain Rashid, Pauline Conde, Petroula Laiou, Heet Sankesara, Faith Matcham, Daniel Leightley, Katie M. White, Carolin Oetzmann, Alina Ivan, Femke Lamers, Sara Siddi, Sara Simblett, Raluca Nica, Aki Rintala, David C. Mohr, Inez Myin-Germeys, Til Wykes, Josep Maria Haro, Brenda W. J. H. Penninx, Srinivasan Vairavan, Vaibhav A. Narayan, Peter Annas, Matthew Hotopf
Summary: This study aimed to analyze smartphone and wearable data from patients with major depressive disorder (MDD) and address the challenges in analyzing this data. The study found that at least 8 days of data were needed to reliably calculate most features. It also observed that different features had varying degrees of correlation with depression, both cross-sectionally and longitudinally. Furthermore, participants could be stratified into distinct clusters based on their behavioral differences between periods of depression and no depression.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2023)
Article
Computer Science, Information Systems
Golshan Famitafreshi, M. Shahwaiz Afaqui, Joan Melia-Segui
Summary: The crisis of energy supplies has led to the need for sustainability in technology, especially in the IoT paradigm. This paper presents a simulation-based study on the integration of energy harvesting technologies into Wi-Fi networks in an e-Health environment. Optimization algorithms utilizing reinforcement learning methods are introduced to reduce network energy consumption while maintaining the required QoS. The results show significant energy savings and demonstrate the feasibility of using smaller solar cells in IoT devices, enhancing the flexibility of energy harvesting techniques. This research opens up new possibilities for energy harvesting integration in IoT, particularly in contexts with restricted QoS environments.
Article
Computer Science, Information Systems
Abdussalam A. Alajami, Guillem Moreno, Rafael Pous
Summary: This paper discusses the simulation of RFID readers for robots in the context of Industry 4.0, presenting the design of an RFID system plugin based on ROS and Gazebo, as well as the probabilistic model behind the plugin. The paper demonstrates the flexibility of the simulator for use on various robot platforms and compares simulation and experimental results in navigating environments with RFID tags.
Article
Remote Sensing
Abdussalam A. Alajami, Guillem Moreno, Rafael Pous
Summary: This article discusses the issue of autonomous navigation for UAVs in indoor map-less environments while performing an inventory mission. It proposes a solution of using RFID technology with UAVs and introduces a RFID-based stigmergic and obstacle avoidance navigation system (RFID-SOAN) for indoor UAVs. Through experiments, it is proven that the proposed UAV is able to estimate the time needed to read RFID tags accurately and efficiently, and cover only areas with RFID tags, making it more efficient than traditional navigation methods.
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Jesus Carretero, Dagmar Krefting
Summary: Computational methods play a crucial role in bioinformatics and biomedicine, especially in managing large-scale data and simulating complex models. This special issue focuses on security and performance aspects in infrastructure, optimization for popular applications, and the integration of machine learning and data processing platforms to improve the efficiency and accuracy of bioinformatics.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Qiangqiang Jiang, Xu Xin, Libo Yao, Bo Chen
Summary: This paper proposes a multi-objective energy-efficient task scheduling technique (METSM) for edge heterogeneous multiprocessor systems. A mathematical model is established for the task scheduling problem, and a problem-specific algorithm (IMO) is designed for optimizing task scheduling and resource allocation. Experimental results show that the proposed algorithm can achieve optimal Pareto fronts and significantly save time and power consumption.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Weimin Li, Lu Liu, Kevin I. K. Wang, Qun Jin
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Mohammed Riyadh Abdmeziem, Amina Ahmed Nacer, Nawfel Moundji Deroues
Summary: Internet of Things (IoT) devices have become ubiquitous and brought the need for group communications. However, security in group communications is challenging due to the asynchronous nature of IoT devices. This paper introduces an innovative approach using blockchain technology and smart contracts to ensure secure and scalable group communications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Robert Sajina, Nikola Tankovic, Ivo Ipsic
Summary: This paper presents and evaluates a novel approach that utilizes an encoder-only transformer model to enable collaboration between agents learning two distinct NLP tasks. The evaluation results demonstrate that collaboration among agents, even when working towards separate objectives, can result in mutual benefits.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Hebert Cabane, Kleinner Farias
Summary: Event-driven architecture has been widely adopted in the software industry for its benefits in software modularity and performance. However, there is a lack of empirical evidence to support its impact on performance. This study compares the performance of an event-driven application with a monolithic application and finds that the monolithic architecture consumes fewer computational resources and has better response times.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Maruf Monem, Md Tamjid Hossain, Md. Golam Rabiul Alam, Md. Shirajum Munir, Md. Mahbubur Rahman, Salman A. AlQahtani, Samah Almutlaq, Mohammad Mehedi Hassan
Summary: Bitcoin, the largest cryptocurrency, faces challenges in broader adaption due to long verification times and high transaction fees. To tackle these issues, researchers propose a learning framework that uses machine learning to predict the ideal block size in each block generation cycle. This model significantly improves the block size, transaction fees, and transaction approval rate of Bitcoin, addressing the long wait time and broader adaption problem.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Rafael Duque, Crescencio Bravo, Santos Bringas, Daniel Postigo
Summary: This paper introduces the importance of user interfaces for digital twins and presents a technique called ADD for modeling requirements of Human-DT interaction. A study is conducted to assess the feasibility and utility of ADD in designing user interfaces, using the virtualization of a natural space as a case study.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Xiulin Li, Li Pan, Wei Song, Shijun Liu, Xiangxu Meng
Summary: This article proposes a novel multiclass multi-pool analytical model for optimizing the quality of composite service applications deployed in the cloud. By considering embarrassingly parallel services and using differentiated parallel processing mechanisms, the model provides accurate prediction results and significantly reduces job response time.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Seongwan Park, Woojin Jeong, Yunyoung Lee, Bumho Son, Huisu Jang, Jaewook Lee
Summary: In this paper, a novel MEV detection model called ArbiNet is proposed, which offers a low-cost and accurate solution for MEV detection without requiring knowledge of smart contract code or ABIs.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Sacheendra Talluri, Nikolas Herbst, Cristina Abad, Tiziano De Matteis, Alexandru Iosup
Summary: Serverless computing is increasingly used in data-processing applications. This paper presents ExDe, a framework for systematically exploring the design space of scheduling architectures and mechanisms, to help system designers tackle complexity.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Chao Wang, Hui Xia, Shuo Xu, Hao Chi, Rui Zhang, Chunqiang Hu
Summary: This paper introduces a Federated Learning framework called FedBnR to address the issue of potential data heterogeneity in distributed entities. By breaking up the original task into multiple subtasks and reconstructing the representation using feature extractors, the framework improves the learning performance on heterogeneous datasets.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
