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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information technology, Applications and Tools, FITAT 2020

作者： Omer, Abdalaziz Altayeb Ibrahim Chang, Kuo-Chi Deng, Hui-Qiong Chu, Kai-Chun Amesimenu, Governor David Kwabena Zhou, Yu-Wen Chang, Fu-Hsiang School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Provincial University Engineering Research Genter of Smart Grid Simulation Analysis and Integrated Control Fuzhou350108 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China Department of Tourism Shih-Hsin University Taipei Taiwan College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9789813364196

The use of prepaid electricity meters appeared in many countries a few years ago and has been widely recognized by consumers and managed to find solutions to too many problems faced by distribution companies. But for traditional systems, users must purchase electricity and manually charge the meter. For example, if he is in the office and needs to charge the house electricity meter, then he must go home to do this, which is considered a waste of time and energy. However, the advanced low-cost smart prepaid electricity meter is a solution to the problem mentioned earlier. By sending GSM text messages to the Arduino as a microcontroller through the GSM module, consumers can use their mobile phones to charge the electricity meter anywhere. This is the main reason for the microcontroller. The control process is also connected to an electricity meter and also to a relay module to provide power for consumers or consumers when the balance is equal to zero. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global system for mobile communications

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Artificial Intelligence-based scheduling with Multi-Objective Power Optimization in Smart Homes Utilizing Particle Swarm Optimizer

Artificial Intelligence-based scheduling with Multi-Objectiv...

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Technological engineering and its Applications in Sustainable Development (ICTEASD), International Conference for

作者： S. Jagan G. Murugan K. Rajasathiya Arti Badhoutiya Hemalatha S Kabulov Ilyos Laith H. Alzubaidi Tabitha Indupalli CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Computer Science and Business System E.G.S. Pillay Engineering College Nagapattinam Tamil Nadu India Department of Computer Science and Engineering P.S.R.R College of Engineering Sivakasi Department of Electrical Engineering GLA University Mathura EEE Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University Tashkent Uzbekistan The Islamic University Najaf Iraq GRIET Hyderabad Telangana India

ISBN: (数字)9798350336474

ISBN: (纸本)9798350336481

This research proposes a novel approach that integrates distinct Artificial Intelligence (AI) methodologies to address the issue of energy demand planning in Smart Homes (SH). The novel technique is designed to address a multi-objective scheduling issue, aiming to strike a balance between energy consumption and user convenience. The AI-based Power Scheduling issue in a Smart Home (AI-PSSH) involves efficiently scheduling intelligent home equipment within specified constraints and flexible pricing schemes. Various methods have been suggested to tackle the problem of AI-PSSH effectively, including both optimal and non-optimal strategies. This study presents a novel formulation for the Intelligent Home Batteries (IHB) in the context of AI-PSSH, which mitigates the impact of constraints in achieving the optimum or near-optimum outcomes. IHB may optimize the scheduling of intelligent home devices by saving excess power when it is not needed and using saved power when it is more suited to achieve the goals of PSSH. PSSH is a multi-objective optimization problem aimed at concurrently achieving all goals. Incorporating AI into smart homes has facilitated the development of sophisticated energy management techniques in scheduling and power optimization. The approach utilizes Particle Swarm Optimization (PSO) to improve the effectiveness of scheduling algorithms. Integrating PSO into the scheduling process enhances flexibility and enables smart decision-making based on real-time adjustments. The simulation results assess the proposed multi-objective AI-PSSH utilizing the IHB (MO-AI-PSSH) strategy by considering five possibilities of energy use and flexible pricing strategies. The efficiency of the suggested MO-AI-PSSH technique is compared to that of existing cutting-edge algorithms using the suggested databases utilizing the provided datasets. The MO-AI-PSSH technique, as suggested, demonstrates superior performance compared to the other algorithms in almost all instances.

关键词： Energy consumption Scheduling algorithms Simulation Smart homes Pricing Real-time systems Artificial intelligence

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Study of 2D SubMarine Tracking with Complete Worked Out Example Based on Kalman Filter 16th

Study of 2D SubMarine Tracking with Complete Worked Out Exam...

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作者： Chang, Kuo-Chi Gakiza, Joram Chu, Kai-Chun Wang, Hsiao-Chuan Hsu, Tsui-Lien Amesimenu, Governor David Kwabena Chang, Fu-Hsiang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China Department of Business Management Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan Department of Tourism Shih-Hsin University Taipei Taiwan College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9789813364196

In many applications such as maritime surveillance and autonomous derivation, specific target tracking has become extremely important, and the characteristics of the research target will come from various distributed sources in different spaces and their noise measurements. We provide a new idea based on mobile submarine prediction data and ion pair measurement in this study, using Kalman filter based on accurate two-dimensional to approximate the results. However, we proposed to minimize the error covariance to calculate the total uncertainty measurement using the gain matrix K of Kalman filter. The actual measurement ix(k) of Kalman filter will be incorporated into each previously estimated sampling time. According to the correction equation to further improves the estimated value. The research results can be ground, the method can quickly converge to the true value, and its accuracy is better than the current passive omnidirectional sonar buoy submarine. This is an important result of the research. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Kalman filters

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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An efficient approach for driver’s drowsiness detection system using deep learning and transfer learning

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AIP Conference Proceedings 2024年第1期3075卷

作者： Gupta Arindam D. Rajeswari Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur - 603203 Chengalpattu Tamilnadu India

The key goal of this project is to create an eye-tracking drowsiness detection system because it is thought that doing so will allow for the early diagnosis of driving fatigue symptoms and the prevention of auto accidents. When this happens when drowsiness is identified, a warning signal is given to the driver. This study introduces a component in the Advanced Driver Assistance system (ADAS) that handles automatically detecting driver tiredness using visual data and artificial intelligence. This approach seeks to improve transportation safety by reducing the number of accidents brought on by fatigued drivers. We propose an algorithm for the detection, observation, and analysis of the the driver’s face and gaze for the evaluation of PERCLOS, a drowsiness indication associated with slowly closing eyes with scientific support. The preprocessing techniques that we have used are CNN+Inception V3,RNN,LSTM and VGG13.

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Eye tracking and assistance using deep learning for paralyzed people with cloud integration for data processing

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AIP Conference Proceedings 2024年第1期2742卷

作者： Bhavik Kumar Imron Khan Nishit Balakrishnan Subramanian Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore Tamil Nadu India Department of Computer Science and Business System Sri Krishna College of Engineering and Technology Coimbatore Tamil Nadu India

The daily life of paralysed people can be very challenging resulting in a need to develop new technologies and innovation. Paralysis is a condition when people are unable to make voluntary muscle movements. A nervous system problem causes paralysis. Injured nerves send muscle signals. Those symptoms cause the muscles to move. If you are disabled, or have a disability, you are unable to move certain parts of your body. The objective is to make a system that speaks for the paralyzed people and to accomplish certain things by themselves. A smart camera will be fixed to capture the eye movement of the Patient who is Paralyzed. By detecting the movement of the eye, the system executes the defined commands and speaks up for the paralysed by sending notifications, calling the caretaker for emergency.

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Towards High-resolution 3D Anomaly Detection via Group-Level Feature Contrastive Learning

arXiv

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arXiv 2024年

作者： Zhu, Hongze Xie, Guoyang Hou, Chengbin Dai, Tao Gao, Can Wang, Jinbao Shen, Linlin National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong Department of Intelligent Manufacturing CATL Ningde China Fuzhou Fuyao Institute for Advanced Study Fuyao University of Science and Technology Fuzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Guangdong Provincial Key Laboratory of Intelligent Information Processing Shenzhen China Shenzhen University Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

High-resolution point clouds (HRPCD) anomaly detection (AD) plays a critical role in precision machining and high-end equipment manufacturing. Despite considerable 3D-AD methods that have been proposed recently, they still cannot meet the requirements of the HRPCD-AD task. There are several challenges: i) It is difficult to directly capture HRPCD information due to large amounts of points at the sample level;ii) The advanced transformer-based methods usually obtain anisotropic features, leading to degradation of the representation;iii) The proportion of abnormal areas is very small, which makes it difficult to characterize. To address these challenges, we propose a novel group-level feature-based network, called Group3AD, which has a significantly efficient representation ability. First, we design an Intercluster Uniformity Network (IUN) to present the mapping of different groups in the feature space as several clusters, and obtain a more uniform distribution between clusters representing different parts of the point clouds in the feature space. Then, an Intracluster Alignment Network (IAN) is designed to encourage groups within the cluster to be distributed tightly in the feature space. In addition, we propose an Adaptive Group-Center Selection (AGCS) based on geometric information to improve the pixel density of potential anomalous regions during inference. The experimental results verify the effectiveness of our proposed Group3AD, which surpasses Reg3D-AD by the margin of 5% in terms of object-level AUROC on Real3DAD. We provide the code and supplementary information on our website: https://***/M-3LAB/Group3AD. Copyright © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Artificial intelligence-based vociferation chatbot for emergency health assistant

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AIP Conference Proceedings 2024年第1期2742卷

作者： S. Balakrishnan P. Sri Jayanth S. Parvathynathan R. Sivashankar Department of Computer Science and Business System Sri Krishna College of Engineering and Technology Coimbatore Tamil Nadu India Department of Computer Science and Engineering Sri Krishna College of Engineering and Technology Coimbatore Tamil Nadu India

It has brought up to clarity that Artificial Intelligence has become very vast in every tech place. The human interface as telecommunication becomes effortless with AI technology. The AI pays the hands for the growth of many challenging ideas like automation, and brain-computer interfaces. As machine learning becomes the subset of artificial intelligence the training part is made unchallenging for computer application. We made this a great tool for our project with the links of Application Programming Interface along with vociferation technology in a personalized chatbot. We made this to bring out a supportive application for medical areas. To make the emergency to be tranquil. We ensure that our programs embedded in the chatbot will be effective for the user with vociferation technology. Which is itself brings the originality of our software interface. We also feel that every new outcome as a product of the enriching technologies process improves the betterment of every individual user and ensures that life becomes easily accessible. The upcoming technology proves that it is better than existing ones in one or the other way comparatively. They don’t let mankind have the workloads as they allow the users to be controlled in a precise manner all the time. The real-time interface with the technology and the user becomes more user-friendly with the fast-growing designing era. This makes plenty of unchallenging works possible. The technology that is growing up to date ensures the activity of humanity is becoming manifest in this trendsetting society. The curiosity of the upcoming process or the gadgets raises high among the users and also the technologies to keep satisfying all the user’s needs in everyday application.

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Research on the Welding system of Soft Pack Power Battery Tabs Based on Laser Sensor 6th

Research on the Welding System of Soft Pack Power Battery Ta...

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6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Huang, Jing Lin, Zhe Wang, Zezhou Qi, Yanfeng Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Province Industrial Integrated Automation Industry Technology Development Base Fuzhou China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

The soft pack power battery’s lug is prone to welding through and missing welding during the welding process due to its low flatness. A welding track detection system for the soft-pack power battery tabs is designed to solve the soft-pack power battery tabs’ welding difficulties. The system uses a laser sensor to perform non-contact detection on the welding surface of the tab. The system uses a laser sensor to perform non-contact detection on the welding surface of the lug. Then filter the collected data, and perform a non-uniform B-spline curve-fitting on the processed data to generate a welding track curve. Finally, welding the tabs according to the welding track curve can improve the tabs’ welding quality. The experimental results show that the average deviation between the fitted curve and the measured data points is 0.0817 mm, which has a good fitting effect and high calculation accuracy. It can be used on other occasions where this function is needed. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Curve fitting

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Fintech adoption and sustainable deployment of natural resources: Evidence from mineral management in Brazil

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Resources Policy 2024年 99卷

作者： Raihan, Asif Atasoy, Filiz Guneysu Coskun, Mehmet Burhanettin Tanchangya, Tipon Rahman, Junaid Ridwan, Mohammad Sarker, Tapan Elkassabgi, Ahmed Atasoy, Murat Yer, Huseyin Institute of Climate Change National University of Malaysia Selangor Bangi43600 Malaysia Information and Data Sciences The University of the Ozarks ClarksvilleAR72830 United States Department of Political Science and Public Administration School of Economics and Administrative Science Osmaniye Korkut Ata University Osmaniye Turkey Department of Finance University of Chittagong Chittagong4331 Bangladesh Department of Economics Noakhali Science and Technology University Noakhali 3814 Bangladesh School of Business University of Southern Queensland QLD4300 Australia College of Business Arkansas Tech University AR United States Department of Environmental Science Wilson Science Center The University of the Ozarks AR United States Center of Clean Energy Engineering University of Connecticut StorrsCT United States

This research aims to investigate the influence of FinTech implementation on responsible mineral resources management in Brazilian economy. For the study purposes it has utilized data set from 1990 to 2022 and for data analysis the autoregressive distributed lag (ARDL) approach has been used. The results show cointegration correlation between FinTech adoption, investment in eco-friendly mining, government funding for FinTech in the mining industry, environmental compliance, technological readiness, and sustainable mineral extraction. The result shows that a 1% increase in FinTech adoption and technology infrastructure readiness would improve sustainable mineral management by 0.01% and 0.03% respectively. However, a 1% increase in the government funding for FinTech in the mining industry, environmental compliance, and investments in sustainable mining technology adversely affect sustainable mineral management by 0.2%, 0.1%, and 0.1% over the long term. The finding provides insight about how variables may affect sustainable mining policies in the future. FinTech adoption and technology flexibility are expected to have a favorable impact on natural resources. This research offers important insights for using natural resources responsibly in the shift to Industry 4.0 by utilizing FinTech and technological readiness in Brazil. © 2024

关键词： Decentralized finance

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