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4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024

作者： Liu, Xiaoxiao McGrath, Sean Flanagan, Colin Lei, Yiming Zeng, Liaoyuan Electronic and Computer Engineering University of Limerick Limerick Ireland School of Mathematics and Information HeBei University HeBei China Mobile Digital Hospital System School of Electronics Peking University Ministry of Education Engineering Research Center Beijing China University of Electronic Science and Technology of China Department of Information and Communication Engineering Chengdu China

ISBN: (纸本)9798350360721

A comprehensive understanding of physiological data is essential for anesthesiologists to monitor and maintain the health of surgical patients. Understanding anesthetic signals is essential to improve over the past ten decades to comprehend a variety of diseases, ensure the safety of patients, and accelerate their recovery. We identified and summarized four themes of artificial intelligence (AI) research in anesthesia: applications of AI in anesthesiology, signals monitored in different anesthesia stages, commonly monitored signs, and data standardization. The effect of various AI technologies on data analysis was studied, and the types, functions, sensors, characteristics, and intelligent analysis of physiological signals monitored during anesthesia are presented in this article. AI influences anesthesia practices in many ways, including preoperative data evaluation, anesthetic depth monitoring, and postoperative event prediction. © 2024 IEEE.

关键词： Machine learning

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Classification Of Cancer Genome Atlas Glioblastoma Multiform (TCGA-GBM) Using Machine Learning Method

Classification Of Cancer Genome Atlas Glioblastoma Multiform...

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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Gharaibeh, Hasan Shrestha, Sujeet Trine University Indiana United States Yarmouk University Department of Computer Science Irbid211633 Jordan Wayne State University Department of Industrial and System Engineering DetroitMI48201 United States

ISBN: (纸本)9781665493765

Glioblastoma multiforme (GBM) is a highly ma-lignant type of brain cancer with a bleak prognosis. This study aimed to apply machine learning methods to classify GBM samples from the Cancer Genome Atlas (TCGA) dataset. Several supervised learning algorithms, including Support Vector Machine, Ad boost, Neural Network, and Decision Tree, were employed in the analysis. Our findings indicate that the Decision Tree algorithm was the most effective for this classification task, achieving an impressive 99% accuracy. Our study provides evidence that machine learning can accurately classify GBM samples in large-scale genomic datasets, enabling a deeper understanding of the genomic characteristics of this cancer. This study emphasizes the potential of machine learning approaches for improved cancer diagnosis and treatment through the analysis of large-scale genomic datasets. © 2023 IEEE.

关键词： Genome

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Early Detection and Classification of Tomato Leaf Blight Disease Using Deep Neural Networks

Early Detection and Classification of Tomato Leaf Blight Dis...

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Data science and Network Security (ICDSNS), International Conference on

作者： Anangsha Halder Subhrendu Guha Neogi Shibdas Dutta Koustov Khamaru Arghya Bhattacharya Shovan Roy Department of Computer Science and Engineering The Neotia University Sarisha India Department of Information Technology DCG Data-Core System India Kolkata India Department of Computer Science and Engineering University of Engineering and Management Kolkata India

ISBN: (数字)9798350373110

ISBN: (纸本)9798350373127

The world population relies on agricultural plants for food, and illnesses reduce yield, but proper plant disease monitoring can help to resolve such issues. computer vision and machine learning methods can detect plant illnesses early, reducing their negative consequences and overcoming the drawbacks of continual human monitoring. After pre-processing of input images, the target region needs to be isolated. The proposed models analyzes images for detection and classification to identify edges, colors, and textures. This research has agricultural applications for early disease identification. This study examined ResNet, MobileNet, DenseNet, InceptionV3 and modified CNN model on the PlantVillage dataset to classify tomato illnesses. The F1 score, accuracy, sensitivity, and specificity can evaluate models. This paper evaluates these models using a diverse collection of tomato leaf pictures, contributing to automated disease detection systems and may be helpful for improving farm management and sustainability.

关键词： Plant diseases Image resolution Image color analysis Plants (biology) Image edge detection Machine learning Sensitivity and specificity Network security Sustainable development Monitoring

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Anaesthesia Monitoring: From Conventional to AI-Enabled Data Acquisition Methods 20

Anaesthesia Monitoring: From Conventional to AI-Enabled Data...

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20th International Conference on Smart Technologies, EUROCON 2023

作者： Liu, Xiaoxiao McGrath, Sean Flanagan, Colin Lei, Yiming Zeng, Liaoyuan University of Limerick Electronic and Computer Engineering Limerick Ireland School of Electronics Peking University Ministry of Education Engineering Research Center on Mobile Digital Hospital System Beijing China University of Electronic Science and Technology of China Department of Information and Communication Engineering Chengdu China

ISBN: (纸本)9781665463973

It is widely recognized that the timely acquisition and presentation of accurate physiological data is a vital aid to the anaesthesiologist in monitoring and maintaining the well-being of a patient undergoing surgery. Collecting, storing, synchronizing, integrating, evaluating, and retrieving pertinent information from patient data remains very difficult due to limited computer power, the need for specialized software, inconsistency between monitoring devices, and inadequate data storage. This paper introduces the general steps of data acquisition in anaesthesia and summarizes some data acquisition systems. It also introduces some applications of the burgeoning field of artificial intelligence (AI) to data acquisition, illustrating how AI techniques may be used to advantage to assist the anaesthesiologist in monitoring and interpreting such data. © 2023 IEEE.

关键词： Data acquisition

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system of systems Architecture and Autonomous Robot Swarms: A Long Awaited Junction

System of Systems Architecture and Autonomous Robot Swarms: ...

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Annual IEEE systems Conference

作者： Thomas Rigaut Omar Hammami U2IS - Computer Science and System Engineering Laboratory ENSTA Paris Polytechnique Institute of Paris Palaiseau France

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

Research on the design of autonomous robot swarms has explored many directions over the past ten years (multi-robot systems, coordination protocols, biomimicry, centralized or distributed architecture) but has struggled to combine these different axes in a holistic design approach. The junction between autonomous robot swarm engineering and systems of systems engineering must be pushed further. The first step is to evaluate the contribution of systems of systems architecture to the design of autonomous robot swarms. We propose two initial tests of the relevance of this approach: do the methods and languages of systems of systems architecture allow us to describe the dynamics of these autonomous robot swarms? Do the concepts of system of systems architecture allow us to establish a taxonomy of autonomous robot swarms? This approach should also allow us to test the current limits of the standards of system of systems architecture: taxonomies too focused on the governance of systems of systems, and coexistence without unification of numerous static architecture methods (Model-Based systems engineering, Architecture Frameworks, Hypergraphs, etc.) and dynamic architecture methods (Dynamical systems, system Dynamics, State Machine Diagrams, Event-B modeling, Agent-Based Modeling, BPMN, Activity Diagrams, etc.)

关键词： Protocols system dynamics Taxonomy Multi-robot systems Modeling Junctions Dynamical systems Standards system of systems Autonomous robots

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Design of 12-Lead Electrocardiogram Smart Clothing Based on Capacitive Sensing Technique

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IEEE Sensors Journal 2024年第10期24卷 16826-16835页

作者： Chang, Wei-Ting Lin, Bor-Shing Tsai, Wei-Lun Chen, Heng-Yin Liu, Chengyu Lin, Bor-Shyh Chi Mei Medical Center The Department of Cardiology Tainan71004 Taiwan National Taipei University Department of Computer Science and Information Engineering New Taipei City237303 Taiwan Institute of Imaging and Biomedical Photonics National Yang Ming Chiao Tung University Tainan71150 Taiwan Industrial Technology Research Institute System Design and Integration Department Hsinchu31057 Taiwan Southeast University School of Instrument Science and Engineering Nanjing210096 China

A 12-lead electrocardiogram (ECG) is one of the most commonly used tools for evaluating cardiovascular diseases (CVDs). In clinical, the conventional Ag/AgCl electrodes with conductive gel are usually used to monitor ECG, but they may encounter gel drying and skin allergic reaction problems for long-term ECG monitoring. In order to improve the above issue, several dry electrodes, made by conductive materials, was proposed in the design of wearable devices, but they still encounter the problems of electrode shifting and stretching, and the risk of skin irritation. Capacitive electrode can access biopotential without contacting skin directly and can completely avoid skin irritation. However, for capacitive electrode, how to maintain a good electrode-skin contacting condition is still a challenge due to electrode fixation problem, in particular in multichannel ECG measurement. In this study, a 12-lead ECG smart clothing based on capacitive sensing technology was proposed to monitor ECG in daily life. To improve the electrode-skin contacting condition, elastic conductive foams were used as the electrode plate to effectively fit the rough body contours. Moreover, a specific wearable belt mechanism was also designed to improve the convenience of use, and it could also provide good friction and proper pressure to reduce the electrode slippage and maintain a good electrode-skin contact condition. The experimental results showed that the proposed smart clothing could stably access the good ECG signal quality under different motion levels, and the specific ECG features corresponding to different CVDs could also be reflected on the measured ECG signal in clinical experiment. © 2001-2012 IEEE.

关键词： Electrocardiograms

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Comprehensive Overview of Multi-agent systems for Controlling Smart Grids

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CSEE Journal of Power and Energy systems 2022年第1期8卷 115-131页

作者： Om Prakash Mahela Mahdi Khosravy Neeraj Gupta Baseem Khan Hassan Haes Alhelou Rajendra Mahla Nilesh Patel Pierluigi Siano Power System Planning Division Rajasthan Rajya Vidyut Prasaran Nigam Ltd.Jaipur-302005India Media Integrated Communication Laboratory Graduate School of EngineeringOsaka UniversityOsakaJapan Computer Science and Engineering Department Oakland UniversityRochesterUSA Department of Electrical and Computer Engineering Hawassa UniversityHawassa 1530Ethiopia Faculty of Mechanical and Electrical Engineering Tishreen UniversityLattakiaSyria Department of Electrical Engineering National Institute of Technology Kurukshetra Department of Management&Innovation Systems University of Salerno84084 SalernoItaly

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience.A multi-agent system(MAS)contains multiple,intelligent,and interconnected collaborating agents for solving a problem beyond the ability of a single agent.A smart grid(SG)combines advanced intelligent systems,control techniques,and sensing methods with an existing utility power *** controlling smart grids,various control systems with different architectures have already been ***-based control of power system operations has been shown to overcome the limitations of time required for analysis,relaying,and protection;transmission switching;communication protocols;and management of plant *** systems provide an alternative for fast and accurate power network *** paper provides a comprehensive overview of MASs used for the control of smart *** paper provides a wide-spectrum view of the status of smart grids,MAS-based control techniques and their implementation for the control of smart *** of MASs in the control of various aspects of smart grids-including the management of energy,marketing energy,pricing,scheduling energy,reliability,network security,fault handling capability,communication between agents,SG-electrical vehicles,SG-building energy systems,and soft grids—have been critically *** than a hundred publications on the topic of MAS-based control of smart grids have been critically examined,classified,and arranged for fast reference.

关键词： Coordinated control multi-agent systems renewable energy sources smart energy infrastructure smart grid

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M-DFCPP: A runtime library for multi-machine dataflow computing

M-DFCPP: A runtime library for multi-machine dataflow comput...

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作者： Luo, Qiuming Liu, Senhong Huang, Jinke Li, Jinrong College of Computer Science and Software Engineering Shenzhen University Shenzhen China SKT Group Guangdong Province Key Laboratory of Popular High-Performance Computers Shenzhen China SKT Group Guangdong Province Engineering Center of China-made High Performance Data Computing System Shenzhen China

This article designs and implements a runtime library for general dataflow programming, DFCPP (Luo Q, Huang J, Li J, Du Z. Proceedings of the 52nd International Conference on Parallel Processing Workshops. ACM;2023:145-152.), and builds upon it to design and implement a multi-machine C++ dataflow library, M-DFCPP. In comparison to existing dataflow programming environments, DFCPP features a user-friendly interface and richer expressive capabilities (Luo Q, Huang J, Li J, Du Z. Proceedings of the 52nd International Conference on Parallel Processing Workshops. ACM;2023:145-152.), enabling the representation of various types of dataflow actor tasks (static, dynamic and conditional task). Besides that, DFCPP addresses the memory management and task scheduling for non-uniform memory access architectures, while other dataflow libraries lack attention to these issues. M-DFCPP extends the capability of current dataflow runtime libraries (DFCPP, taskflow, openstream, etc.) and capable of multi-machine computing, while maintains the API compatible with DFCPP. M-DFCPP adopts the concepts of master and follower (Dean J, Ghemawat S. Commun ACM. 2008;51(1):107-113;Ghemawat S, Gobioff H, Leung ST. ACM SIGOPS Operating systems Review. ACM;2003:29-43.), which form a worksharing framework as many multi-machine system. To shift to the M-DFCPP framework, a filtering layer is inserted to the original DFCPP, transforming it into followers that can cooperate with each other. The master is made of modules for scheduling, data processing, graph partition, state management and so forth. In benchmark tests with workload with directed acyclic graph topology of binary trees and random graphs, DFCPP demonstrated performance improvements of 20% and 8%, respectively, compared to the second fastest library. M-DFCPP consistently exhibits outstanding performance across varying levels of concurrency and task workloads, achieving a maximum speedup of more than 20 over DFCPP, when the task parallelism e

关键词： Libraries

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Revisiting Depth Completion from a Stereo Matching Perspective for Cross-domain Generalization

Revisiting Depth Completion from a Stereo Matching Perspecti...

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Luca Bartolomei Matteo Poggi Andrea Conti Fabio Tosi Stefano Mattoccia Advanced Research Center on Electronic System (ARCES) Department of Computer Science and Engineering (DISI) University of Bologna Italy

ISBN: (数字)9798350362459

ISBN: (纸本)9798350362466

This paper proposes a new framework for depth completion robust against domain-shifting issues. It exploits the generalization capability of modern stereo networks to face depth completion, by processing fictitious stereo pairs obtained through a virtual pattern projection paradigm. Any stereo network or traditional stereo matcher can be seamlessly plugged into our framework, allowing for the deployment of a virtual stereo setup that is future-proof against advancement in the stereo field. Exhaustive experiments on cross-domain generalization support our claims. Hence, we argue that our framework can help depth completion to reach new deployment scenarios.

关键词： Training Three-dimensional displays Task analysis Faces

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Emotion Recognition of Humans using modern technology of AI: A Survey 7

Emotion Recognition of Humans using modern technology of AI:...

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7th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2023

作者： Alheeti, Ahmed Adil Mohammed Salih, Mustafa Muhanad M. Mohammed, Alaa Hamid Hamood, Mostafa A. Khudhair, Nemer Radhwan Shakir, Ahmed Thair Karabuk University Department of Computer Engineering Turkey AL Mansour University College Department of Computer Science and Information System Baghdad Iraq Al-Maarif University College Department of Medical Instruments Techniques Engineering Iraq University of Baghdad College of Engineering Department of Chemical Engineering Baghdad Iraq University of Anbar College of Applied Sciences Department of Biophysics Ramadi Iraq

ISBN: (纸本)9798350383065

This comprehensive investigation and evaluation of the subject matter of emotion recognition is presented, focusing on the broader implications for society at large. The study utilizes a thorough analysis of scholarly literature and practical observations to establish a theoretical framework that facilitates comprehension of the topic under investigation. The findings have considerable implications for future investigations and pragmatic applications. Emotion recognition holds immense importance in diverse domains such as human-computer interaction and healthcare. The analysis of techniques used for emotional recognition includes facial expression assessment, speech patterns analysis, physiological signal interpretation, music perception, and written expression evaluation. The study presents a comprehensive overview of research methodologies commonly used in emotion recognition, discussing datasets, feature extraction techniques, and classification algorithms. The analysis of challenges and limitations pertaining to emotion recognition systems, including privacy concerns, is also discussed. Performance evaluation is analyzed through various methods, including machine assessment and self-report. The significance of continued investigation within the domains encompassing data integration across diverse modalities, the creation of robust classification algorithms, and the exploration of the intricate connection between the brain and affective states is underscored. © 2023 IEEE.

关键词： Emotion Recognition

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