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7th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2024

作者： Min, Sipei Yu, Canping Li, Liping Li, Yingsong Zlatanov, Nikola Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China Innopolis University Faculty of Computer and Engineering Sciences Russia

ISBN: (纸本)9798350384437

This paper aims to investigate the ability of reconfigurable intelligent surfaces (RIS) damaged in multi-user environments to eliminate interference. Our research found that even if the RIS is damaged, interference can still be eliminated in the absence of a direct path and when the number of RIS is sufficient. In order to solve interference cancellation, we adopted the alternating projection algorithm, which ensures local convergence and good convergence speed. © 2024 IEEE.

关键词： Interference suppression

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Distance Recognition Using QR Code Marker 6

Distance Recognition Using QR Code Marker

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6th IEEE International Conference on Artificial Intelligence in engineering and Technology, IICAIET 2024

作者： Lee, Ian Jian Yi Yoong, Hou Pin Teo, Kenneth Tze Kin Chai, Chang Yii Universiti Malaysia Sabah Biomechatronic Research Laboratory Faculty of Engineering Sabah Kota Kinabalu Malaysia Universiti Malaysia Sabah Modelling Simulation & Computing Laboratory Faculty of Engineering Kota Kinabalu Malaysia Universiti Malaysia Sabah High Voltage Power Energy Research Faculty of Engineering Sabah Kota Kinabalu Malaysia

ISBN: (纸本)9798350389692

Existing distance measuring technologies such as ultrasonic distance sensor and laser range finders are commercially viable but have considerable drawbacks together with significant advantages. There is no balanced distancing solution when factoring together cost, size, maximum range and minimum clearance. This study proposes an incremental distancing solution which could minimize the individual drawbacks of the current absolute distancing solutions while maintaining most of their advantages. The solution consists of a device with a camera and processor that is capable of capturing two distance markers in a single frame and decode the encoded information in the distance markers. This solution will provide measurement precision more than each individual marker can provide itself based on the resolution of the camera and also the length between the two markers in frame. QR codes will be used as the distance marker due to their widespread use, error correction and royalty-free standard. The distance markers will have to be placed at a fixed distance interval onto a measuring surface. Millimeter precision is possible based on the calculations performed and verified with experimental results. © 2024 IEEE.

关键词： Cameras

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Optimizing PV Array Performance: Comparative Study of Shading Mitigation Techniques and Row-Constrained Swapping 4

Optimizing PV Array Performance: Comparative Study of Shadin...

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4th IEEE Industrial Electronics and Applications Conference, IEACon 2023

作者： Ting, Lawrence Sii Ying Then, Yi Lung Basri, Hazrul Mohamed Azhar, Abadi Chanik Swinburne University of Technology Sarawak Campus Faculty of Engineering Computing & Science Sarawak Kuching93350 Malaysia Universiti Malaysia Sarawak Faculty of Engineering Sarawak Kota Samarahan94300 Malaysia

ISBN: (纸本)9798350347517

Partial shading presents a recurring problem for PV modules, leading to uneven exposure and reduced power generation. Various setups have been proposed to mitigate shading effects by creating alternative paths for current flow. This comprehensive review examines different photovoltaic (PV) configurations like total-cross-tied (TCT), Sudoku puzzle pattern, and Futoshiki puzzle pattern, assessing their advantages and limitations. To overcome existing limitations, a new configuration pattern called Row-Constrained Swapping (RCS) is proposed. The performance of the RCS pattern is evaluated in five partial shading scenarios through MATLAB Simulink simulations, and the resulting power output characteristics are analyzed. The findings demonstrate the superiority of the proposed RCS configuration, surpassing other PV setups and establishing it as an optimal choice for large-scale PV applications. By optimizing PV array performance, this study contributes to maximizing power generation and addressing the negative impacts of partial shading. The RCS configuration decreases the number of shaded panels required for relocation by 30%, resulting in a corresponding increase in power generation. © 2023 IEEE.

关键词： MATLAB

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Computer vision and Generative AI for yield prediction in Digital Agriculture 2

Computer vision and Generative AI for yield prediction in Di...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Majumder, Sayan Khandelwal, Yash Sornalakshmi, K. SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Data Science and Business Systems Kattankulathur Chennai603203 India

ISBN: (纸本)9798350365269

For the cause of evolution of agriculture to its next generation, the introduction of A.I. and data-driven approach is going to be an important part of the agricultural industry that as per our vision would offer numerous economic, environmental and social benefits. Controlled Environment Agriculture (CEA) is providing more benefits since the weather and other environmental conditions is controlled and predictable. In CEA, the benefits include enhanced productivity in yield, reduced environmental footprints and better resource management. Our solution uses the adoption of Generative AI to visually forecast the potential yield of a crop using stable diffusion and conditional prompts additionally implementing several Generative Adversarial Networks (GAN) architectures for data generation, augmentation and super-resolution. Our proposed system also adopts generative AI for real time monitoring of plants. studying their respective conditions and their autonomous cultivation and harvesting patterns. The dataset used contained over 8479 examples for different fruits alongside annotations. This data was used to train the detection models as well categorically feed the GANs for data generation. Data generated by DCGAN has a structural similarity of 0.5-0.7 whereas data generated by pix2pix network returns us a structural similarity of 0.7-0.9. © 2024 IEEE.

关键词： Cultivation

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Analysis and Classification of Fake News Using Sequential Pattern Mining

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Big Data Mining and Analytics 2024年第3期7卷 942-963页

作者： M.Zohaib Nawaz M.Saqib Nawaz Philippe Fournier-Viger Yulin He College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060 Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518107China Department of Computer Science Faculty of Computing and Information TechnologyUnivesity of SargodhaSargodha 40100Pakistan

Disinformation,often known as fake news,is a major issue that has received a lot of attention *** researchers have proposed effective means of detecting and addressing *** machine and deep learning based methodologies for classification/detection of fake news are content-based,network(propagation)based,or multimodal methods that combine both textual and visual *** introduce here a framework,called FNACSPM,based on sequential pattern mining(SPM),for fake news analysis and *** this framework,six publicly available datasets,containing a diverse range of fake and real news,and their combination,are first transformed into a proper ***,algorithms for SPM are applied to the transformed datasets to extract frequent patterns(and rules)of words,phrases,or linguistic *** obtained patterns capture distinctive characteristics associated with fake or real news content,providing valuable insights into the underlying structures and commonalities of ***,the discovered frequent patterns are used as features for fake news *** framework is evaluated with eight classifiers,and their performance is assessed with various *** experiments were performed and obtained results show that FNACSPM outperformed other state-of-the-art approaches for fake news classification,and that it expedites the classification task with high accuracy.

关键词： disinformation fake news sequential pattern mining(SPM) frequent patterns classification

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Ergonomic Design of the Hand Saw Handle 9th

Ergonomic Design of the Hand Saw Handle

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Proceedings of the 9th International Ergonomics Conference, ERGONOMICS 2022

作者： Milcic, Diana Vucina, Adisa Bosnjak, Marija Faculty of Graphic Art University of Zagreb Getaldiceva 2 Zagreb Croatia Faculty of Mechanical Engineering Computing and Electrical Engineering University of Mostar Matice Hrvatske bb Mostar Bosnia and Herzegovina

ISBN: (纸本)9783031339851

In order to design the handle of a hand tool as ergonomically acceptable, it is necessary to know all aspects of the human hand and define ergonomic design guidelines. Defining requirements and technical specifications ensures the quality of ergonomic design. Following the results of current research in tool handle design, the possibility of better interaction between the tool and the user is created. The handle of the hand tool was created based on defined ergonomic guidelines in order to reduce disorders of the musculoskeletal system and increase functionality, comfort and safety. The research was conducted on the example of a hand saw handle. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Musculoskeletal system

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QSroute : A QoS Aware Routing Scheme for Software Defined Networking 8

QSroute : A QoS Aware Routing Scheme for Software Defined Ne...

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8th IEEE International Conference on Software engineering and Computer Systems, ICSECS 2023

作者： Kamarudin, Imran Edzereiq Ameedeen, Mohamed Ariff Umar Ong, Muhamad Idaham Zabidi, Azlee Universiti Malaysia Pahang AL-Sultan Abdullah Faculty of Computing Department of Computer Systems and Networking Pekan Malaysia Department of Software Engineering Faculty of Computing Universiti Malaysia Pahang AL-Sultan Abdullah Pekan Malaysia

ISBN: (纸本)9798350310931

The increasing demand for bandwidth-intensive network applications, such as video streaming, multimedia, and Internet of Things (IoT) applications, necessitates improved resource management to protect the network without compromising Quality of Service (QoS). Meeting these challenges requires a centralized view of all available network resources. Software Defined Networking (SDN), an emerging technology, provides a centralized view and control of network resources. This feature enables administrators to programmatically define and manage network behavior, including routing, making it more flexible and adaptable. This study proposes a QoS-aware routing scheme for SDN that considers available bandwidth, packet delay, and packet loss to determine the optimal routing path. Optimal paths are selected based on meeting predefined threshold criteria. The study concludes by discussing potential directions for future research in this field. © 2023 IEEE.

关键词： Quality of service

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Revolutionizing indoor air quality monitoring through IoT innovations: a comprehensive systematic review and bibliometric analysis

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Environmental Science and Pollution Research 2024年第32期31卷 44463-44488页

作者： Tan, Huiyi Othman, Mohd Hafiz Dzarfan Kek, Hong Yee Chong, Wen Tong Nyakuma, Bemgba Bevan Wahab, Roswanira Abdul Teck, Gabriel Ling Hoh Wong, Keng Yinn Faculty of Chemical and Energy Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Faculty of Mechanical Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Department of Mechanical Engineering Faculty of Engineering Universiti Malaya Kuala Lumpur50603 Malaysia Department of Chemical Sciences Faculty of Science and Computing Pen Resource University P. M. B Gombe State Gombe0198 Nigeria Department of Chemistry Faculty of Sciences Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Universiti Teknologi Malaysia Skudai Johor81310 Malaysia

Indoor air quality (IAQ) in the built environment is significantly influenced by particulate matter, volatile organic compounds, and air temperature. Recently, the Internet of Things (IoT) has been integrated to improve IAQ and safeguard human health, comfort, and productivity. This review seeks to highlight the potential of IoT integration for monitoring IAQ. Additionally, the paper details progress by researchers in developing IoT/mobile applications for IAQ monitoring, and their transformative impact in smart building, healthcare, predictive maintenance, and real-time data analysis systems. It also outlines the persistent challenges (e.g., data privacy, security, and user acceptability), hampering effective IoT implementation for IAQ monitoring. Lastly, the global developments and research landscape on IoT for IAQ monitoring were examined through bibliometric analysis (BA) of 106 publications indexed in Web of Science from 2015 to 2022. BA revealed the most significant contributing countries are India and Portugal, while the top productive institutions and researchers are Instituto Politecnico da Guarda (10.37% of TP) and Marques Goncalo (15.09% of TP), respectively. Keyword analysis revealed four major research themes: IoT, pollution, monitoring, and health. Overall, this paper provides significant insights for identifying prospective collaborators, benchmark publications, strategic funding, and institutions for future IoT-IAQ researchers. Graphical Abstract: (Figure presented.). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： COVID-19

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Intelligent Modeling of Temperature Profile for Sustainable Food Waste Composting 6

Intelligent Modeling of Temperature Profile for Sustainable ...

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6th International Conference on Applied Computational Intelligence in Information Systems, ACIIS 2023

作者： Lai, Jia Chi Lung Then, Yi Hwang, Siaw San Swinburne University of Technology Sarawak Campus Faculty of Engineering Computing & Science Sarawak Kuching93350 Malaysia Universiti Malaysia Sarawak Faculty of Engineering Kota Samarahan Sarawak 94300 Malaysia

ISBN: (纸本)9798350317428

The composting process exhibits dynamic changes in environmental variables due to underlying biological and physiochemical mechanisms, adding complexity to its modeling. This work focuses on developing a mathematical model for food waste composting in forced continuous aeration conditions. The model incorporates substrate degradation with microbial kinetics, heat balance, and mass balance to address the complexity. In this study, we compare the performance of nth order kinetics against first-order kinetics in predicting temperature variations during food waste composting. Additionally, a comparison is made between nth order kinetics and Monod kinetics for forecasting temperature variations in manure waste composting. The six-stage with fifth order ODE solver (ode45) in MATLAB is employed to numerically solve the differential equations and generate temperature profiles. The developed model successfully predicts peak temperature and the time taken to reach it, enabling better temperature control during the thermophilic phase. This control is vital for avoiding excessive temperatures that can inhibit microbial activities. Comparison of experimental and simulation data, using RRMSE and MAE validation, demonstrates good agreement in the performance of the nth order model when utilizing experimental heat of reaction and proposed kinetics. To further enhance the predictive model for composting processes, it is suggested to expand the nth order model to incorporate other factors such as oxygen concentration, pH, and moisture content. This expansion can contribute to improved prediction accuracy and performance. By employing intelligent and resilient digital innovations, this research strives to advance sustainable living practices in the domain of food waste composting. © 2023 IEEE.

关键词： Temperature control

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Synergistically Learning Class-specific Tokens for Multi-class Whole Slide Image Classification

Synergistically Learning Class-specific Tokens for Multi-cla...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Sun, Pengzhong Wang, Wei Li, Xiangyu Dong, Suyu Li, Shuo Wang, Kuanquan Luo, Gongning Harbin Institute of Technology Faculty of Computing Harbin China Harbin Institute of Technology Faculty of Computing Shenzhen China Northeast Forestry University College of Computer and Control Engineering Harbin China Case Western Reserve University Case School of Engineering Cleveland United States

ISBN: (纸本)9798350337488

The application of transformer architecture in analyzing whole slide images (WSIs) has become increasingly popular due to its remarkable ability to learn complex associations. Nevertheless, a significant drawback emerges in the multiclass analysis of WSIs. The majority of the transformer-based methods available currently rely primarily on a single, class-agnostic token. This approach might not ideally capture the subtleties of class-discriminative information. To address this challenge, we present an innovative approach tailored for multi-class WSI analysis that harnesses the power of class-specific tokens. Central to our method is a novel attention mechanism designed to foster a synergistic learning relationship between patch and class tokens, enhancing the granularity of information captured and ensuring a more comprehensive representation of the WSI. Complementing this, we introduce a dynamic class-centric training strategy designed to optimize token representation learning, ensuring each token is informatively aligned with its corresponding class. Through extensive experimentation on three challenging multi-class WSI analysis datasets, our method consistently demonstrates superior performance, underscoring its potential as a robust solution for multi-class WSI analysis tasks. © 2023 IEEE.

关键词： Multi-class whole slide image analysis Multiple instance learning Transformer

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