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9th International Conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Keerthika, J. AnandaKumar, H. Priya, V. Yuvalatha, S. Gayathri, N. Sri Eshwar College of Engineering Department of Computer Science and Engineering Coimbatore India Dr NGP Institute of Technology Department of Artificial Intelligence and Data Science Coimbatore India Bannari Amman Institute of Technology Department of Computer Science and Business System Sathyamangalam India

ISBN: (纸本)9798350397376

A Cognitive radio is the mobile communication technologies which help to utilize the efficient need of radio spectrum origin. The performance of CRN is significantly impacted by the spectrum sensing function. The problem of bandwidth has risen as a more specific one with breakthroughs in remote communications. By forgiving unlicensed users to usage the available spectrum in primary networks is the solution to the CR technology. An innovative method for enhancing the electromagnetic spectrum's use efficiency, cognitive radio is a encouraging technology. Spectrum sensing has high spectral resolution capabilities and aids in the detection of the spectrum holes. The various methodologies are used to enhance the spectrum sensing essence. These techniques are distinguished by a sensing threshold, which is crucial to the performance of the sensing. The most important element in selecting the best threshold to optimize spectrum sensing performance is the dynamic threshold in the proposed system's spectrum detection algorithm. The energy earned from the licensed user over a precise time of observation, then the dynamic threshold is commutated between two levels. The estimation of the noise ambiguity factor forms the basis for threshold evaluations. These criteria are used to hike the likelihood of detection and contraction the possibility of false alarms. © 2023 IEEE.

关键词： Cognitive radio

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Dual-State-Driven Evolutionary Optimization for Expensive Optimization Problems with Continuous and Categorical Variables 5

Dual-State-Driven Evolutionary Optimization for Expensive Op...

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5th International Conference on Data-Driven Optimization of Complex systems, DOCS 2023

作者： Xie, Lindong Li, Genghui Lin, Kangnian Wang, Zhenkun School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350393521

The surrogate-assisted evolutionary algorithm (SAEA) is one of the most efficient approaches for addressing expensive continuous or combinatorial optimization problems. However, it encounters significant challenges in expensive mixed-variable optimization problems (EMVOPs). To overcome this limitation, a dual-state-driven evolutionary optimization (called DSDEO), integrating a surrogate-assisted mixed-variable evolutionary optimization stage (MVEOS) and a surrogate-assisted continuous-variable evolutionary optimization stage (CVEOS), is proposed in this paper. Specifically, MVEOS employs global and local search to enhance the exploration and exploitation of the mixed-variable space. Global and local searches are alternately executed if one search fails to yield a better solution. CVEOS utilizes a continuous-improvement strategy to refine the continuous variables of the best solution obtained so far. Experimental results demonstrate the advantages of DSDEO compared to some state-of-the-art SAEAs on many benchmark problems. © 2023 IEEE.

关键词： Evolutionary algorithms

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Classification of Skin Lesions using PyQt5 and Deep Learning Methods 5

Classification of Skin Lesions using PyQt5 and Deep Learning...

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5th IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2024

作者： Koishiyeva, Dina Bissembayev, Alibek Iliev, Teodor Kang, Jeong Won Mukasheva, Assel Almaty University of Power Engineering and Telecommunications Dept. of Information Technology Almaty Kazakhstan Kazakh-British Technical University School of Information Technology and Engineering Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria Korea National University of Transportation Department of Transportation System Engineering Uiwang-Si Korea Republic of

ISBN: (纸本)9798350352863

This study presents the OncoScan system designed to assist dermatologists in classifying skin diseases using an improved DenseNet121 model. The system was tested on the large HAM10000 dataset of over 10,000 images of skin lesions in seven categories. The DenseNet121 model, characterized by dense connectivity and transient layers, was compared with the InceptionV3 and EfficientNetB7 models. The results demonstrated the superiority of the DenseNet121 model, with an accuracy of 86.04% and an AUC of 96.32%. The OncoScan interface, developed using PyQt5, supports multilingual functionality including English, Russian, and Kazakh, and offers image processing tools. The system's ability to handle image processing and classification with ease makes it a valuable asset for dermatologic diagnostics. © 2024 IEEE.

关键词： denseNet121 pyqt5 skin disease transient layers

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SSP: A Large-Scale Semi-Real Dataset for Semantic Segmentation of Spacecraft Payloads 8

SSP: A Large-Scale Semi-Real Dataset for Semantic Segmentati...

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8th International Conference on Image, Vision and Computing, ICIVC 2023

作者： Guo, Yanning Feng, Zhen Song, Bin Li, Xinglong School of Astronautics Harbin Institute of Technology Harbin China Hong Kong Polytechnic University The Department of Mechanical Engineering Kowloon Hong Kong Shanghai Aerospace System Engineering Shanghai China

ISBN: (纸本)9798350335231

Semantic segmentation technology is widely used in autonomous driving, environment perception, and other fields. With the development of deep learning technology, semantic segmentation will also be applied to spacecraft-related research (i.e., spacecraft-payload segmentation). However, the lack of spacecraft-related datasets seriously hinders the development of deep learning technology in research fields, such as spacecraft control and payload segmentation. To address this issue, we release a novel semi-real dataset for the segmentation of spacecraft payload. Specifically, the images in our released dataset are generated by merging images of spacecraft models taken by a real camera and space images released by the National Aeronautics and Space Administration (NASA). Furthermore, we propose a network SPSNet with an anti-pyramid-structured decoder for the segmentation of spacecraft payload. Experimental results show that our proposed network achieves superior performance compared with the well-known networks on our released dataset. © 2023 IEEE.

关键词： Spacecraft

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Electrode Design and Process Analysis for Precision Internal Gear in Electrochemical Machining 14

Electrode Design and Process Analysis for Precision Internal...

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14th International Conference on Mechanical and Aerospace engineering, ICMAE 2023

作者： Hung, Jung-Chou Tsui, Hai-Ping Wang, A-Cheng Liu, Jheng-Hong National Central University Department of Mechanical Engineering Taoyuan Taiwan Chien Hsin University of Science and Technology Department of Mechanical Engineering Taoyuan Taiwan Aeronautical System Research Division National Chung-Shan Institute of Science and Technology Taichung Taiwan

ISBN: (纸本)9798350340327

This research is to analyze the electrochemical machining characteristics of precision internal gears in order to explore the influence of electrode shape and insulation layer design on machining. Electrochemical machining is used to make internal gears, and the cathode pattern can be accurately reversed and molded on the anode workpiece. There is no contact during the process, and there is no doubt about the wear of the cathode, and there is no problem of residual stress. During the process, the design of the processing cathode and the setting of processing parameters, the shape and quality of the workpiece to be processed through electrochemical processing under the given different processing parameters through the simulation of the analysis software, and the most appropriate processing data are set. According to the comparison of experimental results, it is observed that the verticality, tooth shape and integrity have been significantly improved, and the final pitch circle diameter of the tooth shape is 15.5 mm, which can reach the error range of ±0.1 mm, which proves that this design method is feasible. © 2023 IEEE.

关键词： Multiphysics

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Resource Allocation in Reconfigurable Intelligent Surfaces with Imperfect Phase Compensation 16

Resource Allocation in Reconfigurable Intelligent Surfaces w...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Srivastava, Swaraj Ramamoorthi, Yoghitha Kumar, Abhinav Murakami, Tomoki Ogawa, Tomoki Takatori, Yasushi Indian Institute of Technology Hyderabad Department of Electrical Engineering Telangana India Ntt Access Network Service System Laboratories Nippon Telegraph and Telephone Corporation Yokosuka Japan

ISBN: (纸本)9798350383119

Reconfigurable Intelligent Surfaces (RISs) are acknowledged as key technologies for the upcoming sixth generation (6G) of mobile communication networks. The performance of the RIS systems heavily relies on the accuracy of phase compensation, which is often imperfect in practical scenarios. In this poster, we analyze the performance of RIS systems by allocating the fraction of total elements within the RIS used for a particular user, taking into account this imperfect phase compensation (IPC). We then derive a lower bound on the element allocation factor required for a user to achieve higher data rates when compared to benchmark scenario (without RIS). Additionally, we establish an upper bound on the IPC to assess in advance whether this system can provide higher spectral efficiency in comparison to the benchmark system. Furthermore, we demonstrate a trade-off between the IPC and the fraction of elements of RIS utilized by a user to obtain a specific data rate. © 2024 IEEE.

关键词： Imperfect Phase Compensation (IPC) Reconfigurable Intelligent Surfaces (RIS) Resource allocation Spectral efficiency

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Supervisor Control of Power system for Stability Problems and Improvements Using Computer Control technology

Supervisor Control of Power System for Stability Problems an...

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2023 International Conference on Emerging Power Technologies, ICEPT 2023

作者： Yaqoob, M. Sardar, M. Usman Shahid, M. Usama Shahid, Tanzeela Mutloob, Tayyaba Ahmad Shah, S. Imran Huzaif, Muhammad Khwaja Fareed University of Engg.& It Dept. of Electrical & Biomedical Engineering Rahim Yar Khan Pakistan Lahore College for Women University Department of Electrical Engineering Lahore Pakistan Uspcase Nust Department of Electrical Power Engineering Islamabad Pakistan Ned University of Engineering & Technology Department of Computer & Information System Engineering Karachi Pakistan

ISBN: (纸本)9798350301014

Currently, there is a growing interest in the topic of power quality across the entire electric power system. The power system is a complex network of modules with a broad distribution area, designed to meet the demand for electric power. The power system is susceptible to a range of disturbances arising from either dynamic consumer load behavior or faults. The power system necessitates a precise and advanced stability and protection mechanism. Ensuring the safe and reliable operation of the power system is a significant challenge, with voltage stability and fault protection being key areas of concern. The present research study proposes a technique to augment the stability of a grid-connected system that comprises of several generating sources through the utilization of FACTS devices, specifically static synchronous compensator (STATCOM). The technology has been designed to enable the monitoring of supervisory control of devices, while the distribution system offers decision-making tools to enhance system performance. A fault was generated between the time interval of 1-1.04 sec duration, and the simulation waveform was subsequently observed. The present study entails a simulation-based comparison between a power system without a STATCOM devise and one equipped with the STATCOM. The analysis results of the transient voltage stability of HV AC transmission lines utilizing STATCOM. © 2023 IEEE.

关键词： Static synchronous compensators

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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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Research on Wastewater Quality Prediction Method Based on DBSCAN Algorithm and Conv1D-LSTM Model 11th

Research on Wastewater Quality Prediction Method Based on DB...

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11th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2023

作者： Lu, Mingquan Zhao, Xingyuan Yu, Wentong Department of Electronic Engineering Tsinghua University Beijing100084 China Shenzhen Aerospace Smart City System Technology Co. Ltd. Shenzhen518057 China

ISBN: (纸本)9789819721153

Wastewater treatment and its quality prediction have always been pivotal for environmental protection and public health. Accurate forecasting of wastewater quality parameters is essential for optimizing treatment processes and ensuring water safety. In light of this, our study proposes a hybrid model integrating Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Convolutional Neural Network-Long Short-Term Memory (Conv1D-LSTM) for wastewater quality prediction. DBSCAN enables anomaly detection in the influent data, reducing noise impact. The Conv1D-LSTM model automatically extracts features and captures time series dependencies. Experiments demonstrate superior performance of the proposed model over LSTM alone in both single-step and multi-step forecasting of ammonia nitrogen levels, with lower RMSE, MAE and RMSLE. The integration of DBSCAN and Conv1D-LSTM can effectively leverage their respective strengths for enhanced wastewater quality prediction. Further research will focus on multi-variable prediction and incorporating data smoothing techniques. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Anomaly detection

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A bibliometric analysis of research on remote sensing-based monitoring of soil organic matter conducted between 2003 and 2023

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Artificial Intelligence in Agriculture 2025年第1期15卷 26-38页

作者： Xionghai Chen Fei Yuan Syed Tahir Ata-Ul-Karim Xiaojun Liu Yongchao Tian Yan Zhu Weixing Cao Qiang Cao National Engineering and Technology Center for Information Agriculture MOE Engineering and Research Center for Smart AgricultureMARA Key Laboratory for Crop System Analysis and Decision MakingJiangsu Key Laboratory for Information AgricultureCollaborative Innovation Centre for Modern Crop Production Co-sponsored by Province and MinistryNanjing Agricultural UniversityNanjing 210095China Department of Geography Minnesota State UniversityMankatoMN 56001USA Department of Agroecology Climate and WaterAarhus UniversityTjele 8830Denmark

Soil organic matter(SOM)is a key metric for assessing soil quality and crop yield *** plays a vital role in maintaining the ecological balance environment and promoting sustainable farming *** review examines the evolving trends in remote sensing(RS)-based SOM monitoring by analyzing 739 scholarly publications from the Web of Science database from 2003 to 2023 using a bibliometric *** study reveals that research on RS-based SOM monitoring has entered a rapid growth phase since 2018,with China and the United States as the main contributors and an extensive international cooperation *** model construction,high frequency covariates such as soil pH,precipitation,temperature,and topography significantly improved the prediction *** preprocessing methods such as Standard Normal Variables(SNV),Principal Component Analysis(PCA),and Multiple Scattering Correction(MSC)enhanced data *** statistical models are gradually being replaced by nonlinear machine learning and deep learning methods(CNN,XGBoost,andStacking),which are particularly good at handling complex high-dimensional *** spectral libraries(OzSoil and AfSIS)excel in local accuracy,while global spectral libraries(ISRIC and LUCAS)are more suitable for cross-region modeling,and the migration learning technique effectively improves the model generalization ability in low data *** models(CNN-LSTM and GAN)have significant advantages in capturing the spatial and temporal dynamics of SOMs,and uncertainty quantification methods(Bayesian inference,Monte Carlo simulation)enhance the reliability of the models in multi-source data and data-scarce *** research should focus on further optimization of multi-source data fusion and uncertainty quantification to promote the development and applicability of RS-based SOM monitoring techniques for precision soil management and sustainable agriculture.

关键词： Data fusion Modeling methods Transfer learning Spatial mapping Spectral libraries

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