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3rd International Conference on Advances in Information and Communication technology, ICTA 2024

作者： Tan, Nguyen Hong Khanh, Phan Hung Long, Cu Kim Van Hai, Pham Tuan, Tran Manh Chuan, Pham Minh Tam, Ngo Duc Son, Le Hoang Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi Viet Nam Faculty of Information Technology Information Communication and Technology University Thai Nguyen Viet Nam Hanoi Viet Nam Hanoi Viet Nam Faculty of Computer Science and Engineering Thuyloi University 175 Tay Son Dong Da Hanoi Viet Nam Faculty of Information Technology UTEHY Hung Yen Viet Nam Artificial Intelligence Research Center VNU Information Technology Institute Vietnam National University Hanoi Viet Nam

ISBN: (纸本)9783031809422

Decision support systems have been widely applied in various sectors in which a vast of models and algorithms have been researched and developed based on knowledge graphs. Recently, Fuzzy Knowledge Graph (FKG) has overcome the challenge of handling uncertain, incomplete input data in decision support systems;yet still its performance could be improved through the integration of multiple data sources. This paper proposes a novel conceptual framework of FKG called FKGF based on multiple data sources. The experimental results based on multiple data sources in the healthcare sector (including ***, kaggle, hospital, etc.) show that the proposed framework gives positive results when combining data from many different sources. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

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Hybrid Particle Swarm and Gray Wolf optimization for Prediction of Appliances in Low-Energy Houses

Hybrid Particle Swarm and Gray Wolf optimization for Predict...

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2022 International Telecommunications Conference, ITC-Egypt 2022

作者： El-Kenawy, El-Sayed M. Eid, Marwa M. Abdelhamid, Abdelaziz A. Ibrahim, Abdelhameed Takieldeen, Ali E. Elkhalik, Said H. Abd Delta University Faculty of Artificial Intelligence Department of Artificial Intelligence Mansoura Egypt Ain Shams University Faculty of Computer and Information Sciences Department of Computer Science Cairo Egypt Mansoura University Faculty of Engineering Computer Engineering Department Mansoura Egypt Delta University for Science and Technology Faculty of Artificial Intelligence Egypt

ISBN: (数字)9781665488082

ISBN: (纸本)9781665488082

In this paper, we propose a new feature optimization prediction framework. This framework consists of two phases. The first phase is the optimization of the feature selection process, in which the dataset is preprocessed by removing non-predictive factors, then the best set of features is selected based on the hybrid modified gray wolf optimizer (GWO) and particle swarm optimization (PSO) algorithms. Whereas the second phase consists of an ensemble model based on the k-nearest neighbors (KNN) regression model, which is trained on the selected features to generate predictions of the appliances in low energy house. The proposed ensemble model consists of three regression models namely, KNN regression, multi-layer perceptron (MLP), and decision trees (DT). Experimental results show that the proposed model achieved the best accuracy and lowest error. In specific, the achieved Root Mean Square Error (RMSE) is (0.00225) and the achieved Mean Absolute Error (MAE) is (0.0002). These results emphasize the effectiveness of the proposed approach when compared with the separate application of regression models. © 2022 IEEE.

关键词： Forecasting

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Transformer-Based Single-Cell Language Model:A Survey

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Big Data Mining and Analytics 2024年第4期7卷 1169-1186页

作者： Wei Lan Guohang He Mingyang Liu Qingfeng Chen Junyue Cao Wei Peng Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronic and InformationGuangxi UniversityNanning 530004China School of Computer and Electronic Information Guangxi UniversityNanning 530004China College of Life Science and Technology Guangxi UniversityNanning 530004China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention *** addition,increasing studies based on transformers have been proposed to model single-cell *** this review,we attempt to systematically summarize the single-cell language models and applications based on ***,we provide a detailed introduction about the structures and principles of ***,we review the single-cell language models and large language models for single-cell data ***,we explore the datasets and applications of single-cell language models in downstream tasks,such as batch correction,cell clustering,cell type annotation,gene regulatory network inference,and perturbation ***,we discuss the challenges of single-cell language models and provide promising research *** hope this review will serve as an up-to-date reference for researchers who are interested in the direction of single-cell language models.

关键词： language model transformers deep learning single-cell data

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A systematic literature review to implement large language model in higher education: issues and solutions

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Discover Education 2025年第1期4卷 1-25页

作者： Guizani, Sghaier Mazhar, Tehseen Shahzad, Tariq Ahmad, Wasim Bibi, Afsha Hamam, Habib College of Engineering Alfaisal University Riyadh 11533 Saudi Arabia School of Computer Science National College of Business Administration and Economics Lahore 54000 Pakistan Department of Computer Science and Information Technology School Education Department Government of Punjab Layyah 31200 Pakistan Department of Computer Engineering COMSATS University Islamabad Sahiwal Campus Sahiwal 57000 Pakistan Department of Computing School of Arts and Creative Technology University of Greater Manchester Manchester BL15AB United Kingdom Department of Computer and Software Technology University of Swat Swat 19200 Pakistan Faculty of Engineering Uni de Moncton Moncton E1A3E9 NB Canada School of Electrical Engineering University of Johannesburg Johannesburg 2006 South Africa International Institute of Technology and Management (IITG) Av. Grandes Ecoles Libreville BP 1989 Gabon Bridges for Academic Excellence - Spectrum Tunis Tunisia

Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role in automating instructional tasks and promoting personalized learning experiences. Despite integration concerns and ethical debates, LLMs showcase the potential of AI to improve educational practices. Our research concludes that LLMs offer transformative opportunities for education. However, their incorporation requires careful ethical considerations, data privacy measures, and a balance between human educators and AI technologies. The findings suggest strategies for integrating LLMs into educational frameworks to enhance learning outcomes while preserving educational integrity. © The Author(s) 2025.

关键词： Artificial intelligence Education Large language models Learning systems Natural language processing systems Neural networks

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Performance Comparison of Deep CNN Models for Detecting Driver’s Distraction

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computers, Materials & Continua 2021年第9期68卷 4109-4124页

作者： Kathiravan Srinivasan Lalit Garg Debajit Datta Abdulellah A.Alaboudi N.Z.Jhanjhi Rishav Agarwal Anmol George Thomas School of Information Technology and Engineering Vellore Institute of TechnologyVellore632014India Faculty of Information and Communication Technology University of MaltaMsida2080MSDMalta School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India College of Computer Science Shaqra UniversityKingdom of Saudi Arabia School of Computer Science and Engineering SCETaylor’s UniversitySubang Jaya47500Malaysia

According to various worldwide statistics,most car accidents occur solely due to human *** person driving a car needs to be alert,especially when travelling through high traffic volumes that permit high-speed transit since a slight distraction can cause a fatal *** though semiautomated checks,such as speed detecting cameras and speed barriers,are deployed,controlling human errors is an arduous *** key causes of driver’s distraction include drunken driving,conversing with co-passengers,fatigue,and operating gadgets while *** these distractions are accurately predicted,the drivers can be alerted through an alarm ***,this research develops a deep convolutional neural network(deep CNN)models for predicting the reason behind the driver’s *** deep CNN models are trained using numerous images of distracted *** performance of deep CNN models,namely the VGG16,ResNet,and Xception network,is assessed based on the evaluation metrics,such as the precision score,the recall/sensitivity score,the F1 score,and the specificity *** ResNet model outperformed all other models as the best detection model for predicting and accurately determining the drivers’activities.

关键词： Deep-CNN ResNet Xception VGG16 data classification

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The Low-Cost IoT Mornitoring the Quality of River: A Case Study of Wang River in Lampang Municipality 27

The Low-Cost IoT Mornitoring the Quality of River: A Case St...

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27th International computer science and engineering Conference, ICSEC 2023

作者： Krueganta, Narong Chieochan, Oran Saokaew, Anukit Yana, Ekkachai Singkaew, Chaowoot Sawangtook, Weerachai Boonchieng, Ekkarat Wongchai, Warakhom Srimakorn, Sakchai School of Industrial Technology Lampang Rajabhat University Faculty of Industrial Technology Lampang52000 Thailand School of Information Technology Lampang Rajabhat University Faculty of Sciences Lampang52100 Thailand School of Environmental Innovation Lampang Rajabhat University Faculty of Science Lampang52100 Thailand School of Computer Engineering Lampang Rajabhat University Faculty of Industrial Technology Lampang52100 Thailand Chiang Mai University Faculty of Sciences Department of Computer Sciences Chiang Mai50200 Thailand School of Industrial Electrical Engineering Lampang Rajabhat University Faculty of Industrial Technology Lampang52000 Thailand School of Software Engineering Lampang Rajabhat University Faculty of Industrial Technology Lampang52000 Thailand

ISBN: (纸本)9798350342109

The research project focuses on prototyping an IoT (Internet of Things) system for measuring and monitoring the quality of the Wang River in Lampang Municipality. The system utilizes EC (Electrical Conductivity), pH, and temperature sensors connected to an ESP32 microcontroller with a custom-developed board. Additionally, the IoT system is supported by a solar cell system to provide power. The software programming is implemented using Arduino C++ on the PlatformIO platform, which is integrated with Visual Studio code. The IoT platform chosen for this project is ThingsBoard, specifically the community version. The research findings indicate that the utilization of IoT technology combined with the sensors has improved the prototype of a low-cost IoT monitoring system for assessing the quality of the Wang River in Lampang Municipality. © 2023 IEEE.

关键词： Rivers

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Development of A Location and Operation Monitoring Device for medical Device Management

Development of A Location and Operation Monitoring Device fo...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Kakutani, Kazuto Ito, Nobuhiro Shima, Kosuke Oyama, Shintaro Otsuka, Takanobu Nagoya Institute of Technology Dept. of Computer Science Aichi Nagoya Japan Nagoya University Innovative Research Center for Preventive Medical Engineering Aichi Nagoya Japan

ISBN: (纸本)9798350324174

Central management has used and maintained many portable medical devices(MDs). However, the central management lends medical staff the MDs only with managing by a ledger;therefore, missing or subletting may be caused. In this paper, we develop and propose a device that can measure MDs' location and power consumption and a visualization system. We implemented 85 developed devices in 4 hospitals and confirmed that the system adequately managed MDs. © 2023 IEEE.

关键词： Indoor positioning systems

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A simple and high -performance immobilization technique of membrane protein from crude cell lysate sample for a membrane-based immunoassay application

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Journal of Immunoassay and Immunochemistry 2023年第1期44卷 76-89页

作者： Khemthongcharoen, Numfon Uawithya, Panapat Yookong, Nutthapon Chanasakulniyom, Mayuree Jeamsaksiri, Wutthinan Sripumkhai, Witsaroot Pattamang, Pattaraluck Juntasaro, Ekachai Kamnerdsook, Ampol Houngkamhang, Nongluck Promptmas, Chamras Department of Biomedical Engineering Faculty of Engineering Mahidol University Nakhon Pathom Thailand NECTEC National Science and Technology Development Agency (NSTDA) Pathumthani Thailand Department of Physiology Faculty of Medicine Siriraj Hospital Mahidol University Bangkok Thailand Department of Clinical Chemistry Faculty of Medical Technology Mahidol University Bangkok Thailand Center for Standardization and Product Validation Faculty of Medical Technology Mahidol University Bangkok Thailand Thai Microelectronics Center (TMEC) NECTEC National Science and Technology Development Agency (NSTDA) Chachoengsao Thailand Mechanical Engineering Simulation and Design Group The Sirindhorn International Thai-German Graduate School of Engineering (TGGS) King Mongkut’s University of Technology North Bangkok (KMUTNB) Bangkok Thailand College of Materials Innovation and Technology King Mongkut’s Institute of Technology Ladkrabang (KMITL) Bangkok Thailand

Membrane proteins are difficult to be extracted and to be coated on the substrate of the immunoassay reaction chamber because of their hydrophobicity. Traditional method to prepare membrane protein sample requires many steps of protein extraction and purification that may lead to protein structure deformation and protein dysfunction. This work proposes a simple technique to prepare and immobilize the membrane protein suspended in an unprocessed crude cell lysate sample. Membrane fractions in crude cell lysate were incorporated with the large unilamellar vesicle (LUV) that was mainly composed of POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) before coating in the polystyrene plate by passive adsorption technique. Immunofluorescence staining and the Enzyme-Linked Immunosorbent Assay (ELISA) examination of a strictly conformation-dependent integral membrane protein, Myelin Oligodendrocyte Glycoprotein (MOG), demonstrate that LUV incorporated cell lysate sample obviously promotes MOG protein immobilization in the microplate well. With LUV incorporation, the dose–response curve of the MOG transfected cell lysate coating plate can be 2–9 times differentiated from that of the untransfected cell lysate coating plate. The LUV incorporated MOG transfected cell lysate can be efficiently coated in the microplate without carbonate/bicarbonate coating buffer assistance. © 2022 Taylor & Francis.

关键词： conformation-dependent immunoassay crude cell lysate coating enzyme-linked immunosorbent assay Membrane protein immobilization unilamellar vesicle preparation

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Enhanced Dye Adsorption and Bacterial Removal of Magnetic Nanoparticle-Functionalized Bacterial Cellulose Acetate Membranes

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Journal of Renewable Materials 2024年第9期12卷 1605-1624页

作者： Heru Suryanto Daimon Syukri Fredy Kurniawan Uun Yanuhar Joseph Selvi Binoj Sahrul Efendi Fajar Nusantara Jibril Maulana Nico Rahman Caesar Komarudin Komarudin Centre of Advanced Material for Renewable Energy(CAMRY) Universitas Negeri MalangMalang65145Indonesia Department of Mechanical and Industrial Engineering Universitas Negeri MalangMalang65145Indonesia Department of Food and Agricultural Product Technology Faculty of Agricultural TechnologyAndalas UniversityPadang25163Indonesia Department of Chemistry Institut Teknologi Sepuluh NopemberSurabaya60111Indonesia Study Program of Aquatic Resources Management Faculty of Fisheries and Marine ScienceBrawijaya UniversityMalang65145Indonesia Institute of Mechanical Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)Saveetha UniversityChennai602105India Faculty of Vocational Universitas Negeri MalangMalang65145Indonesia

Utilizing biomass waste as a potential resource for cellulose production holds promise in mitigating environmental *** current study aims to utilize pineapple biowaste extract in producing bacterial cellulose acetate-based membranes with magnetic nanoparticles(Fe_(3)O_(4)nanoparticles)through the fermentation and esterification process and explore its *** bacterial cellulose fibrillation used a high-pressure homogenization procedure,and membranes were developed incorporating 0.25,0.50,0.75,and 1.0 wt.%of Fe3O4 nanoparticles as magnetic nanoparticle for *** membrane characteristics were measured in terms of Scanning Electron Microscope,X-ray diffraction,Fourier Transform Infrared,Vibrating Sample Magnetometer,antibacterial activity,bacterial adhesion and dye adsorption *** results indicated that the surface morphology of membrane changes where the bacterial cellulose acetate surface looks *** crystallinity index of membrane increased from 54.34%to 68.33%,and the functional groups analysis revealed that multiple peak shifts indicated alterations in membrane functional ***,adding Fe_(3)O_(4)-NPs into membrane exhibits paramagnetic behavior,increases tensile strength to 73%,enhances activity against *** and ***,and is successful in removing bacteria from wastewater of the river to 67.4%and increases adsorption for anionic dyes like Congo Red and Acid Orange.

关键词： Bacterial cellulose dye adsorption Fe_(3)O_(4)nanoparticles membrane pineapple waste

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3-D Electrical Impedance Imaging of Lung Injury

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Progress In Electromagnetics Research B 2023年 103卷 19-36页

作者： Ma, Ming Hao, Zepeng Wang, Qi Li, Xiuyan Duan, Xiaojie Wang, Jianming Feng, Hui School of Life Science TianGong University Tianjin300382 China School of Electronic and Information Engineering TianGong University Tianjin300382 China School of Computer Science and Technology TianGong University Tianjin300382 China Department of Rehabilitation Medicine The Affiliated Jiangning Hospital of Nanjing Medical University China

Pulmonary edema assessment is a key factor in monitoring and guiding the treatment of critically ill patients. To date, the methods available at the bedside to estimate the physiological correlation of pulmonary edema and extravascular pulmonary uid are often unreliable or require invasive measurements. The aim of this article is to develop an imaging method of reliably assessing pulmonary edema by utilizing functional electrical impedance tomography. In this article, the Split- Bregman algorithm is used to solve the Total Variation (TV) minimization problem in EIT image reconstruction. A thorax model is constructed according to CT images of rats. Through simulation and experiment, the proposed method improves the quality of reconstructed image signifficantly compared with existing methods. A pulmonary edema experiment in rats is also carried out. The development of pulmonary edema is analyzed numerically through EIT images. © (2023). All Rights Reserved.

关键词： Rats

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