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computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Hai-Feng Zhu Yao-Hui Liu Kun Guo Si-Jie Zhang Ge Chen Department of Computer Science and Technology XiangNan University ChenZhou China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Xiangnan University ChenZhou China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

Intracerebral hemorrhage is a disease with high fatality rate, and the expansion of hematoma caused by hemorrhage is one of the factors leading to poor prognosis. Fast and accurate segmentation of the contours of cerebral hematoma will help doctors to make diagnosis to a large extent. In order to solve the problem of insufficient precision of U-net segmentation, pixel image segmentation based on U-net and clustering is proposed. The CT images are divided into multiple channels by preprocessing, and on this basis, the cluster is processed twice, and then they enter the improved U-net network respectively. Finally, multiple results are fused to obtain the final segmentation result.

关键词： Image segmentation Accuracy Computed tomography Clustering algorithms Feature extraction Classification algorithms Kernel Hemorrhaging Unsupervised learning Diseases

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On transitioning from PID to ADRC in thermal power plants

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Control Theory and Technology 2021年第1期19卷 3-18页

作者： Zhenlong Wu Zhiqiang Gao Donghai Li YangQuan Chen Yanhong Liu School of Electrical Engineering Zhengzhou UniversityZhengzhou 450001HenanChina Department of Electrical and Computer Engineering Cleveland State UniversityClevelandOH 44115USA State Key Lab of Power Systems Department of Energy and Power EngineeringTsinghua UniversityBeijing 100084China Mechatronics Embedded Systems and Automation(MESA)LabDepartment of Mechanical EngineeringSchool of EngineeringUniversity of CaliforniaMercedCA 95343USA

This paper focuscs on the recent progress in the adoption of active disturbance rejection control(ADRC)in thermal pro-cesses as a viable alternative to proportional-_integral-derivative(PID),especially in coa-fired power *** profound interpretation of this paradigm shift,with backward compatibility,is discussed in detail.A few fundamental issues associated with ADRC's applications in thermal processes are discussed,such as implementation,tuning,and the structural *** and case studies are presented,encompassing coal-fired power plants,gas turbines and nuclear power plants,as well as highlighting results of field *** discussed are future research opportunities brought by ADRC's entry as the baseline control technology in thermal processes.

关键词： Active disturbance rejection control(ADRC) Proportional-integral-derivative(PID) Thermal processes Coal-fired power plant Field applications

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Data-Driven Analysis of Skin Cancer Classification with Convolutional Neural Networks for E-Health Applications

Data-Driven Analysis of Skin Cancer Classification with Conv...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Ahmed, Imran Ahmad, Misbah Chehri, Abdellah Jeon, Gwanggil Anglia Ruskin University School of Computing and Information Science Cambridge United Kingdom Hartpury University Animal and Agriculture Department Gloucester United Kingdom University of the West of England Centre for Machine Vision Bristol Robotics Laboratory Bristol United Kingdom Department of Mathematics and Computer Science Canada Incheon National University Department of Embedded Systems Engineering Incheon Korea Republic of

ISBN: (纸本)9798350351255

This study explores the effectiveness of Convolutional Neural Networks (CNNs) in automatically classifying skin cancer for e-health applications. The trained model showcases impressive performance by leveraging the HAM10000 dataset, which includes a wide range of skin lesion images from seven different classes. The parameters and architecture of the CNN model are presented in a systematic manner, providing valuable insights into the reasoning behind its design. The model is optimized using the Adam optimizer and annealing techniques to ensure efficient convergence. The model's performance is assessed on validation and test datasets, showcasing an accuracy of 78.55% and 76.49%, respectively, for skin cancer classification. This study highlights the significant potential of CNN as a powerful tool for automating the diagnosis of skin cancer, which is in line with the growing trend of using deep learning for medical image analysis. © 2024 IEEE.

关键词： Electronic health record

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Optimization of Cognitive Radio System Using Self-Learning Salp Swarm Algorithm

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computers, Materials & Continua 2022年第2期70卷 3821-3835页

作者： Nitin Mittal Harbinder Singh Vikas Mittal Shubham Mahajan Amit Kant Pandit Mehedi Masud Mohammed Baz Mohamed Abouhawwash Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India School of VLSI Design and Embedded Systems National Institute of TechnologyKurukshetra136119India School of Electronics&Communication Engineering Shri Mata Vaishno Devi UniversityKatra182320India Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer and Information TechnologyTaif UniversityTaif21994Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

CognitiveRadio(CR)has been developed as an enabling technology that allows the unused or underused spectrum to be used dynamically to increase spectral *** improve the overall performance of the CR systemit is extremely important to adapt or reconfigure the *** Decision Engine is a major module in the CR-based system that not only includes radio monitoring and cognition functions but also responsible for parameter *** meta-heuristic algorithms offer numerous advantages compared to traditional mathematical approaches,the performance of these algorithms is investigated in order to design an efficient CR system that is able to adapt the transmitting parameters to effectively reduce power consumption,bit error rate and adjacent interference of the channel,while maximized secondary user ***-Learning Salp Swarm Algorithm(SLSSA)is a recent meta-heuristic algorithm that is the enhanced version of SSA inspired by the swarming behavior of *** this work,the parametric adaption of CR system is performed by SLSSA and the simulation results show that SLSSA has high accuracy,stability and outperforms other competitive algorithms formaximizing the throughput of secondary *** results obtained with SLSSA are also shown to be extremely satisfactory and need fewer iterations to converge compared to the competitive methods.

关键词： Cognitive radio meta-heuristic algorithm cognitive decision engine salp swarm algorithm

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Multi-Layer Secured Edge-AI Enabled Model for Consumer Health systems

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IEEE Transactions on Consumer Electronics 2025年

作者： Rehman, Amjad Haseeb, Khalid Saba, Tanzila Jeon, Gwanggil Al-Otaibi, Shaha Lab Riyadh12435 Saudi Arabia Incheon National University College of Information Technology Department of Embedded Systems Engineering Incheon22012 Korea Republic of Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Information Systems Riyadh11671 Saudi Arabia

The Internet of Medical Things (IoMT) and edge computing technologies have significantly advanced the healthcare industry by enabling real-time monitoring and data processing at the network edges. Medical devices are combined with consumer electronics to measure the physiological factors of the human body and transfer them to cloud storage for further analysis and processing. However, optimizing routing to account for limited processing power and network constraints of the consumer healthcare system poses a significant research challenge. Moreover, due to the restricted environment, several privacy and security issues arise with integrating heterogeneous technologies over wireless systems. In this work, we proposed a multi-layer secured-edged-enabled AI model for health systems to provide real-time data analysis and transmission decisions at the edges. Firstly, the intelligent algorithm employs dynamic and trusted routing strategies at the edges to control the data flow and minimize the network congestion on consumers’ data. Secondly, in the event of data and integrity breaches, randomized security patterns are investigated to build trust among devices using edge management and raise the degree of data privacy. The randomized security patterns improve the analysis of data security by integrating the concept of rotating encryption keys and their management. Such a paradigm decreases the probabilities of network threats and generates unpredictable patterns for increasing the resilience of IoT systems in the existence of harmful devices. The proposed model is tested using various simulation based experiments, revealing its significant improvement over existing studies for packet drop ratio, data delay, system uptime, data breaches, and security overhead. © 1975-2011 IEEE.

关键词： Electronic health record

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VersaSens: An Extendable Multimodal Platform for Next-Generation Edge-AI Wearables

IEEE Transactions on Circuits and Systems for Artificial Int...

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IEEE Transactions on Circuits and systems for Artificial Intelligence 2024年第1期1卷 83-96页

作者： Taraneh Aminosharieh Najafi José Angel Miranda Calero Jérôme Thevenot Benjamin Duc Stefano Albini Alireza Amirshahi Hossein Taji María José Belda Beneyto Antonio Affanni David Atienza Embedded Systems Laboratory (ESL) Institute of Electrical and Micro Engineering École Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Polytechnic Department of Engineering and Architecture Udine Italy Computer Architecture and Automation Department Universidad Complutense de Madrid Madrid Spain

The transition of healthcare towards digitalization is closely related to the advancement of health-related technologies, including wearable sensors and edge computing. In this paper, we present VersaSens, a versatile and customizable platform concept and its real implementation as a tool to boost research in wearable sensors. The platform embodies the core attributes of the VersaSens concept: versatility, flexibility, and extendability across multiple aspects of hardware, software, and processing components. It features a modular design, consisting of sensor, processor, and co-processor modules, allowing for various configurations. To evaluate the efficiency of the platform, we tested three use cases: cough monitoring, heartbeat classification and epileptic seizure detection. In all cases, the results indicate that the platform effectively executes the applications, achieving low energy consumption. In particular, our findings indicates that the integration of a domain-specific edge-AI co-processor [i.e., HEEP ocrates (Machetti et al., 2024)] equipped with several hardware accelerators further improved the overall execution time and energy consumption of the system. These results demonstrate the potential of VersaSens to effectively support a diverse range of edge-AI applications and configurations, thereby providing a robust foundation for the research and development of novel smart wearable sensor systems.

关键词： Sensors Wearable devices Artificial intelligence Wearable sensors Medical services Intelligent sensors Monitoring

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Quantum Calculus-Based Two-Dimensional Least Mean Square Algorithm

Quantum Calculus-Based Two-Dimensional Least Mean Square Alg...

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Asilomar Conference on Signals, systems & computers

作者： Muhammad Moinuddin Azzedine Zerguine Ubaid M. Al-Saggaf Muhammad Arif Electrical and Computer Engineering Department and the Centre of Excellence in Intelligent Engineering Systems King Abdulaziz University Jeddah Saudi Arabia Electrical Engineering Department and the Interdisciplinary Research Center for Communication Systems and Sensing KFUPM Dhahran Saudi Arabia Institute of Networked and Embedded Systems University of Klagenfurt and the Ubiquitous Sensing Systems Lab University of Klagenfurt-Silicon Austria Labs Klagenfurt Austria

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354065

Recent work of the one-dimensional q-LMS algorithm give insight that the Quantum Calculus based gradient called the q-gradient is capable of improving the convergence behavior in contrast to the standard LMS algorithm. The reason for this is the fact that the q-derivative takes larger steps in minimizing a cost function as it evaluates the secant in contrast to the tangent of the cost function. Motivated by this, we propose a two-dimensional version of the q-LMS algorithm. More precisely, we employ Quantum Calculus based q-gradient in steepest descent optimization of mean-square-error (MSE) cost function in 2D adaptive filtering scenario to obtain two-dimensional q-LMS (2D q-LMS) algorithm. A thorough analytical investigation of the proposed 2D q-LMS algorithm in both mean and mean-square sense is provided. Both the transient and steady-state convergence behaviours are examined. Consequently, excess MSE (EMSE) learning curve and its steady-state expression are evaluated in closed form. Simulation results are presented for the application of noise cancelation in images to show the superiority of the proposed 2D q-LMS algorithm.

关键词： Filtering Two-dimensional displays Simulation Cost function Calculus Steady-state Performance analysis Transient analysis Standards Convergence

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PFV2: Packet fragmentation with variable size and vigorous mapping in time-sensitive networking

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Journal of systems Architecture 2025年 166卷

作者： Yan, Wenyan Fu, Bin Wei, Dongsheng Li, Renfa Lei, Yixue Jia, Yuhang Xie, Guoqi Key Laboratory for Embedded and Network Computing of Hunan Province College of Computer Science and Electronic Engineering Hunan University Hunan Changsha410082 China Center for Convergence of Automobile and Cyberspace Research Institute of Hunan University in Chongqing Chongqing401120 China Future Network Laboratory Tencent Beijing100080 China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems School of Computer and Artificial Intelligence Xiangnan University Hunan Chenzhou423000 China

With the rapid advancement of intelligent automobiles, the ever-growing communication data put forward high bandwidth and low latency requirements. To meet these requirements, automotive Original Equipment Manufacturers (OEMs) widely adopt domain-centralized Electrical/Electronic (E/E) architecture. In this architecture, Time-Sensitive Networking (TSN) is expected to serve as the backbone network because of its high bandwidth and deterministic communication. TSN uses the Gate Control List (GCL) to divide its time length into multiple time slots, and the time intervals of these time slots are non-uniform (equal or unequal). Different flows have varying requirements for time slot sizes. To enhance the acceptance ratio of Time-Triggered (TT) flows through GCL time slot allocation, packet fragmentation (i.e., flow fragmentation) is introduced into TSN in the recent study. The state-of-the-art packet fragmentation solution divides one un-schedulable TT flow into multiple equal-sized packets (i.e., equal-sized time slots). In other words, these fixed-size packets are difficult to be mapped into the time slots with different sizes. This study develops a Packet Fragmentation with Variable-size and Vigorous-mapping (PFV2) technique based on the following three innovations: (1) we implement variable-size packet fragmentation, which iteratively divides the un-schedulable TT flow into smaller packets and then dynamically reschedules these packets;(2) we implement the vigorous mapping solution from packets to time slots by deeply searching for available time slots within the flow's deadline;and (3) we verify PFV2 based on the LS1028A with Cortex-A72 (i.e., the NXP automotive-grade development board). PFV2 improves the acceptance ratio by up to 20.18% and bandwidth utilization by up to 7.024% compared with the state-of-the-art solution. The theoretical and practical co-verification experiments demonstrate that the PFV2 can effectively improve the flow acceptance ratio and outperf

关键词： Bandwidth

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Design and Application of Innovative Cluster Education System Based on Artificial Intelligence Algorithm

Design and Application of Innovative Cluster Education Syste...

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2022 IEEE International Conference on Knowledge engineering and Communication systems, ICKES 2022

作者： Wei, Li Xie, Hui Ramachandra, A.C. School of Computer and Artificial Intelligence Xiangnan University Hunan Chenzhou China Hunan Engineering Research Center of Advanced Embedded Computing and Intelligent Medical Systems Hunan Chenzhou423000 China Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9781665456371

After entering the Internet era, people are increasingly digitized and algorithmized. Technology platforms often use their technical advantages in data processing and algorithms to generate an implicit right of dominance and control, thus forming a unique artificial intelligence algorithm. Operational logic. The unique operational logic of artificial intelligence algorithms is profoundly changing the previous production methods and lifestyles. As a modern transformation model of concentrated industrial development, industrial clusters have created a special entrepreneurial environment, and their advantages in resource concentration can also help young entrepreneurs increase their chances of success. With the vigorous development of my country's information technology and artificial intelligence algorithms, its derivative services, technologies and their impact on the social market have further promoted the demand for market innovation. Based on the impact of artificial intelligence algorithms on the social market, this study defines the mutual promotion of 'professional +' innovation and entrepreneurship education and the development of innovative industry clusters from the background of innovation industry clusters. On the basis of clarifying the positive role of innovation industry cluster system in innovation and entrepreneurship education, this research explores the practice form of innovation and entrepreneurship education system in colleges and universities that is more in line with the needs of innovation industry cluster talent development. © 2022 IEEE.

关键词： Clustering algorithms

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On the Detection of Non-Cooperative RISs: Scan B-Testing via Deep Support Vector Data Description

arXiv

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arXiv 2024年

作者： Stamatelis, George Gavriilidis, Panagiotis Fakhreddine, Aymen Alexandropoulos, George C. Department of Informatics and Telecommunications National and Kapodistrian University of Athens Greece Institute of Networked and Embedded Systems University of Klagenfurt Austria Department of Electrical and Computer Engineering University of Illinois Chicago United States

In this paper, we study the problem of promptly detecting the presence of non-cooperative activity from one or more Reconfigurable Intelligent Surfaces (RISs) with unknown characteristics lying in the vicinity of a Multiple-Input Multiple-Output (MIMO) communication system using Orthogonal Frequency-Division Multiplexing (OFDM) transmissions. We first present a novel wideband channel model incorporating RISs as well as non-reconfigurable stationary surfaces, which captures both the effect of the RIS actuation time on the channel in the frequency domain as well as the difference between changing phase configurations during or among transmissions. Considering that RISs may operate under the coordination of a third-party system, and thus, may negatively impact the communication of the intended MIMO OFDM system, we present a novel RIS activity detection framework that is unaware of the distribution of the phase configuration of any of the non-cooperative RISs. In particular, capitalizing on the knowledge of the data distribution at the multi-antenna receiver, we design a novel online change point detection statistic that combines a deep support vector data description model with the scan B-test. The presented numerical investigations demonstrate the improved detection accuracy as well as decreased computational complexity of the proposed RIS detection approach over existing change point detection schemes. © 2024, CC BY.

关键词： Orthogonal frequency division multiplexing

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