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Improving Energy Harvesting System from Ambient RF Sources in Social Systems with Overcrowding

International Journal of Crowd Science 2025年第1期9卷 13-28页

作者： Agieb, Ramy Amer, Ayman Mansour, Ibrahim Solyman, Ahmed Yahya, Khalid Samir, Ahmed Department of Electrical Engineering Faculty of Engineering MTI University Cairo11511 Egypt Faculty of Engineering Zarqa University Zarqa13110 Jordan School of Computing Engineering and Built Environment Glasgow Caledonian University GlasgowG4 0BA United Kingdom College of Engineering University of Business and Technology Jeddah22233 Saudi Arabia Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Istanbul Gelisim University Istanbul34310 Turkey

This paper presents a novel approach to enhance energy harvesting systems from ambient Radio Frequency (RF) sources in overcrowded environments. In environments like shopping malls, coffee shops, and airports, where wireless devices are prevalent, the electromagnetic energy emitted by these devices can be harvested and converted into electrical energy to power small devices, specifically those associated with the Social Internet of Things (SIoT). However, due to the high density of devices in such environments, the RF signals can be weak, resulting in low energy harvesting efficiency. This study focuses on developing technologies for wireless power transfer through a radio frequency ambient energy harvesting scheme, specifically designing to improve energy harvesting systems in crowded social environments. Recognizing the growing importance of energy harvesting for low-power devices in intelligent environments, our proposed method utilizes the ambient environment to capture energy in the downlink radio frequency range of the GSM-900 band. The system architecture comprises four main stages: a supercapacitor, a Villard voltage doubler circuit with seven stages, a lumped element matching network, and a microstrip patch antenna. The voltage doubler circuit is designed and simulated using the Agilent Advanced Design System (ADS) 2014 environment, and simulations and tests are conducted across different input power levels. Throughout the study, several key factors are identified as crucial to the system’s efficiency, including the frequency band, input power level, voltage doubler circuit design, impedance matching, diode selection, number of rectification stages, and load resistance. The proposed method demonstrates significant potential in enhancing the energy harvesting efficiency from ambient RF sources in crowded social environments. By providing a sustainable power source for SIoT devices in such settings, our approach contributes to the advancement of energy harves

关键词： Slot antennas

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Review and prospect of four-point bending fatigue test of asphalt mixture

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Journal of Road engineering 2024年第4期4卷 446-467页

作者： Yongjun Meng Dichao Liu Hongliu Rong Xiaolong Yang School of Civil Engineering and Architecture Guangxi UniversityNanning 530004China Key Laboratory of Disaster Prevention and Engineering Safety of Ministry of Education Nanning 530004China Special Geological Highway Safety Engineering Technology Research Center of Guangxi Nanning 530004China National High-Performance Computing Center Nanning Branch Nanning 530004China

Fatigue cracking is one of the principal failure modes of asphalt pavement. The chief factors affecting the fatiguefailure of asphalt pavement are load, environment, pavement structure and the fatigue resistance of asphaltmixture itself. Among them, the most important part is the research on the fatigue resistance of asphalt mixture,which has been studied deeply at home and abroad. This paper summarized some important research results andfatigue characterization parameters of the four-point bending fatigue test method in recent years, and suggestedthe future research direction of the four-point bending test. In the analysis and comparison of loading modes offour-point bending test, further research on various analysis methods is required. Researchers can appropriatelyrefine the test method to account for nonlinear viscoelastic energy dissipation, as well as plastic and permanentdeformation per cycle. The fatigue evaluation index of asphalt mixture can be comprehensively evaluated by fourindicators, and can be combined with new fatigue characterization parameters in the future. It is suggested todevelop a complete set of four-point bending fatigue test methods under various stress states consistent with theservice state of asphalt pavement. This method can be used to eliminate the influences of environment, testcondition and specimen size on the fatigue test results of asphalt mixture to improve the effectiveness andcompleteness of asphalt mixture fatigue performance characterization.

关键词： Asphalt mixture Four-pointbending Fatigue characteristics Influencing factors

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Business Process Innovation Through Enterprise Resource Planning Implementation

Business Process Innovation Through Enterprise Resource Plan...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Frias, Noli Celis, Nelson Balmes, Irene De la Salle University - Manila Information Technology Department Metro Manila Philippines School of Architecture Computing and Engineering National University - Philippines SM Lipa City Philippines

ISBN: (纸本)9798350369106

Enterprise systems are among the information technology (IT) solutions aimed at transforming the organization's business processes. This IT investment has been considered a major cost among organizations hoping to streamline business processes and maintain competitive advantage. Implementing IT solutions such as enterprise resource planning (ERP) system has become an inevitable action to have an efficient business process. Specifically, this study seeks to put forward the question, 'How does ERP implementation influence business process innovation?'. Using the lens of dynamic capability, a qualitative case study in the pharmaceutical industry was conducted tracing the stages and experiences of the ERP implementation. The findings confirmed that there is a revolutionary transformation of the business process brought about by the ERP system implementation. Moreover, this study identified factors enabling and transforming the business process. The case site illustrates an example of a business process innovation that can be used as a reference for companies adopting an ERP system as an IT solution. © 2024 IEEE.

关键词： business process innovation enterprise resource planning ERP systems information systems

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Coastal and Rural Digital Exclusion: The Case for Voice AI

Coastal and Rural Digital Exclusion: The Case for Voice AI

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Baxter, Rory Hagen, Oksana Aly, Amir Jones, Ray B. Willis, Katharine School of Nursing and Midwifery University of Plymouth Plymouth United Kingdom School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom School of Art Design and Architecture University of Plymouth Plymouth United Kingdom

The adoption of digital platforms for health and social resources disadvantages vulnerable populations, including older adults and those living in remote or deprived areas. This could be remediated using voice-based conversational AI (Voice AI) systems delivered via landline phone, bypassing the requirement for digital device access or digital skills. British rural and coastal regions often have poorer digital infrastructure and pockets of deprivation, and consequently higher levels of digital exclusion. This study explores digital exclusion in Southwest England and the suitability of Voice AI systems for supporting digital inclusion. Seventeen participants aged 50 years or over were interviewed by telephone and took part in one of two face to face focus groups to identify how digital exclusion impacts access to health and wellbeing resources. The results indicated that digital access was severely impacted by unreliable infrastructure and exacerbated by limited digital skills. Phone-based Voice AI systems could then provide viable solutions to support access to digital health and social resources for digitally marginalised coastal and rural communities. © 2025 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Electronic health record

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Acoustic Emission Characteristics of Different Porcine Bones Under Loading

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International Journal of Acoustics and Vibrations 2023年第1期28卷 44-49页

作者： He, Weikai Yan, Dongliang Liu, Muxuan Gao, Xiang Zhang, Ying Xu, Dongyu School of Aeronautics Shandong Jiaotong University Shandong Jinan250357 China Shandong Provincial Key Laboratory of Network Based Intelligent Computing University of Jinan Shandong Jinan250022 China School of Civil Engineering and Architecture Linyi University Shandong Linyi276000 China

In order to obtain the acoustic emission (AE) characteristics of fresh porcine bones of different parts under loadings, the fresh porcine femur, scapula and vertebra were investigated by using a compression testing machine and the AE instrument, respectively. The results show that the compression curve of the porcine bones has an obvious dependence on the shape of the porcine bones, and cracks can be observed with an increase of loading. Some obvious inflection points can also be found on the compression curve. The AE parameters of porcine bones under loading agrees well with the variation of the inflection points. The porcine femur exhibits the most obvious variation of AE parameters with an increase of loading and has the largest frequency band of 20-140 kHz and a dominant frequency value of 65 kHz. However, the AE energy of the scapula vertebra is weak under loading effects, and the vertebra has the smallest dominant frequency value of 25 kHz. © 2023 International Institute of Acoustics and Vibrations. All rights reserved.

关键词： Compression testing

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Sustainable Cloud Resource Deployment: Integrating Real-Time Energy Data and Edge Continuum for Optimized Cloud Operations

Sustainable Cloud Resource Deployment: Integrating Real-Time...

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IEEE International Conference on Utility and Cloud computing (UCC)

作者： Naveen Kumar Kamalakannan Khalander Shariff Rafiulla Shariff Umaima Haider School of Architecture Computing and Engineering University of East London London UK

ISBN: (数字)9798350367201

ISBN: (纸本)9798350367218

The environmental impact of cloud computing has driven a demand for transparent, sustainable resource deployment in data centers. However, current sustainability efforts by cloud providers often lack real-time insights into the energy composition of cloud regions, limiting users’ control over deployment decisions based on renewable energy sources. This study introduces a system integrating real-time energy data and an edge continuity feature, enabling users to prioritize ecologically favorable regions for deploying cloud resources. The system supports the selection of Amazon Web Services (AWS) regions by fuel source and allows cross-region replication of resources, improving both resilience and performance. Results indicate a significant reduction in carbon footprint for deployments while enhancing system availability. The findings emphasize the importance of automated energy monitoring to support sustainable cloud infrastructure management.

关键词： Cloud computing Renewable energy sources Costs Web services Organizations Real-time systems Energy efficiency Fuels Sustainable development Carbon footprint

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Efficient Tree-based Parallel Algorithms for N-Body Simulations Using C++ Standard Parallelism

Efficient Tree-based Parallel Algorithms for N-Body Simulati...

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2024 Workshops of the International Conference for High Performance computing, Networking, Storage and Analysis, SC Workshops 2024

作者： Cassell, Thomas Lane Deakin, Tom Alpay, Aksel Heuveline, Vincent Gadeschi, Gonzalo Brito University of Bristol School of Computer Science BristolBS8 1UB United Kingdom Heidelberg University Engineering Mathematics and Computing Lab Interdisciplinary Center for Scientific Computing Heidelberg Germany NVIDIA GPU Architecture Munich Germany

ISBN: (纸本)9798350355543

The Barnes-Hut approximation for N-body simulations reduces the time complexity of the naive all-pairs approach from O(N2) to O(N log N) by hierarchically aggregating nearby particles into single entities using a tree data structure. This inherently irregular algorithm poses substantial challenges for performance portable implementations on multi-core CPUs and GPUs. We introduce two portable fully-parallel Barnes-Hut implementation strategies that trade-off different levels of GPU support for performance: an unbalanced concurrent octree, and a balanced bounding volume hierarchy sorted by a Hilbert spacefilling curve. We implement these algorithms in portable ISO C++ using parallel algorithms and concurrency primitives like atomics. The results demonstrate competitive performance on a range of CPUs and GPUs. Additionally, they highlight the effectiveness of the par execution policy for highly concurrent irregular algorithms, outperforming par_unseq on CPUs and GPUs with Independent Thread Scheduling. © 2024 IEEE.

关键词： n/a

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Boosting cationic and anionic redox activity of Li-rich layered oxide cathodes via Li/Ni disordered regulation

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Journal of Energy Chemistry 2025年第1期100卷 533-543页

作者： Zewen Liu Zhen Wu Hao Wang Xudong Zhang Yuanzhen Chen Yongning Liu Shengwu Guo Shenghua Chen Yanli Nan Yan Liu State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina School of Materials Science and Engineering Xi’an University of Architecture and TechnologyXi’an 710055ShaanxiChina Hefei Advanced Computing Center Operation Management Corp Ltd Hefei 230088AnhuiChina Network Information Center Xi’an Jiaotong UniversityXi’an 710049ShaanxiChina

Lithium-rich layered oxides (LLOs) are increasingly recognized as promising cathode materials for nextgeneration high-energy-density lithium-ion batteries (LIBs).However,they suffer from voltage decay and low initial Coulombic efficiency (ICE) due to severe structural degradation caused by irreversible O ***,we introduce a three-in-one strategy of increasing Ni and Mn content,along with Li/Ni disordering and TM–O covalency regulation to boost cationic and anionic redox activity simultaneously and thus enhance the electrochemical activity of *** target material,Li_(1.2)Ni_(0.168)Mn_(0.558)Co_(0.074)O_(2)(L1),exhibits an improved ICE of 87.2%and specific capacity of 293.2 mA h g^(-1)and minimal voltage decay of less than 0.53 m V cycle-1over 300 cycles at 1C,compared to Li_(1.2)Ni_(0.13)Mn_(0.54)Co_(0.13)O_(2)(Ls)(274.4 mA h g^(-1)for initial capacity,73.8%for ICE and voltage decay of 0.84 mV/cycle over 300 cycles at 1C).Theoretical calculations reveal that the density of states (DOS) area near the Fermi energy level for L1 is larger than that of Ls,indicating higher anionic and cationic redox reactivity than ***,L1 exhibits increased O-vacancy formation energy due to higher Li/Ni disordering of 4.76%(quantified by X-ray diffraction Rietveld refinement) and enhanced TM–O covalency,making lattice O release more difficult and thus improving electrochemical *** increased Li/Ni disordering also leads to more Ni^(2+)presence in the Li layer,which acts as a pillar during Li+de-embedding,improving structural *** research not only presents a viable approach to designing low-Co LLOs with enhanced capacity and ICE but also contributes significantly to the fundamental understanding of structural regulation in high-performance LIB cathodes.

关键词： Low-Co Li-rich layered oxides Li/Ni disordering TM-O covalency Cationic and anionic redox activity

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Leveraging Artificial Intelligence to Secure Wireless Network: Exploring Threats, Existing Approaches, and Proposed Mitigation Strategies

Leveraging Artificial Intelligence to Secure Wireless Networ...

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International Conference on Innovation and Intelligence for Informatics, computing, and Technologies (3ICT)

作者： Alice Lee Nan Xin Athirah Mohd Ramly Mehran Behjati Mhd Saeed Sharif Department of Computing and Information Systems Sunway University Selangor Malaysia School of Architecture Computing and Engineering UEL London United Kingdom Intelligent Technologies Research Group School of Architecture Computing and Engineering UEL London United Kingdom

ISBN: (数字)9798331533137

ISBN: (纸本)9798331533144

The exponential growth of network has introduced new Internet-of-Things (IoT) use cases that has enabling us convenience and comfort. The surge of IoT devices due to the capabilities brought by fifth generation (5G) have given rise to security threats and attacks, particularly malware attacks IoT botnets have been an alarming issue, where smart devices can be manipulated by malicious actors to commence subsequent attacks such as Denial of Service (DoS). Traditional and complex security techniques may not be a viable solution towards these resource-constrained devices with limited processing power. Machine Learning techniques (ML) are the rising trend, and it is often used in Intrusion Detection Systems and Network Anomaly Detection. This paper emphasizes on analyzing and comparing various ML models on the IoT-23 dataset. It aims to predict anomalies and conclude the model with optimal performance and least computational time cost that can be used for network anomaly detection systems with real-time data in future works. The ML models used in this paper are Decision Trees (DT), K-nearest neighbours (KNN), Random Forest (RF), Naïve Bayes (NB) and Histogram Gradient Boosting (HGB). DT displayed the best performance with an accuracy score of 73% and F1 score of 0.49 with a time cost of 28.22 seconds.

关键词： Support vector machines Costs Accuracy 5G mobile communication Computational modeling Hardware Internet of Things Security Anomaly detection Tuning

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Artificial Intelligence Models in Power Generation for Energy Consumption Prediction

Artificial Intelligence Models in Power Generation for Energ...

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International Conference on Emerging Trends in Networks and Computer Communications (ETNCC)

作者： Lit Yang Tan Charis Shwu Chen Kwan Samuel-Soma M. Ajibade Athirah Mohd Ramly Department of Computing and Information Systems School of Engineering and Technology Sunway University Selangor Malaysia Department of Computing School of Architecture Computing and Engineering University of East London London UK

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

The incorporation of artificial intelligence (AI) into power-related applications signifies a new and unexplored domain in machine learning for predicting power generation. This novel method utilizes prediction models, often used in different fields, to predict energy-related patterns, providing a unique and specialized viewpoint. The synergy of academicians, AI experts, and industry professionals in the energy sector has resulted in the creation of customized AI models to optimize operational efficiency. By customizing various AI models to suit the distinct attributes of energy scenarios and datasets, these models are positioned to transform energy management methods. This study examines the utilization of AI models to enhance energy efficiency in power generation in Malaysia. The project seeks to predict future power consumption in various sectors, analyze growth rates, and identify sectors with investment potential by developing a Linear Regression model. In addition, a thorough power plan is developed using the estimated energy usage. A comparative analysis is performed to determine the most appropriate model for this particular scenario, which will improve decision-making in the energy sector. The results of this study present promising opportunities for further investigation. By broadening the study's focus to encompass a broader array of AI models and their assessment of performance, it is possible to gain useful insights for predicting power generation. Furthermore, the integration of real-time data streams and the inclusion of feedback loops in the AI models could improve their ability to adapt and increase their accuracy as time progresses.

关键词： Adaptation models Energy consumption Analytical models Linear regression Artificial neural networks Predictive models Data models Artificial intelligence Power generation Streams

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