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检索条件"任意字段=2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023"

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2023 3rd international conference on Electrical Engineering and Control science, IC2ECS 2023

2023 3rd International Conference on Electrical Engineering ...

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3rd international conference on Electrical Engineering and Control science, IC2ECS 2023

ISBN: (纸本)9798350382426

The proceedings contain 322 papers. The topics discussed include: electromagnetic design of 10kV high voltage induction motor based on Ansoft Maxwell;efficiency promotion strategy for three-level ANPC-DAB-based DC-DC converter with wide-range multi-objective optimization method;nonlinear data classification of power Internet of Things considering transient and steady state;analysis of early warning indicators for high voltage power cable tunnel fire based on experimental data;real-time evaluation model construction of GIS conductor thermal state based on PSO-BP neural network;research and application of CPS-based automatic circulation system for the entire silk production process;and transmission line relay protection fault-tolerant information sharing and joint analysis method.

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Enhancing the Channel Quality in Cognitive network by Traffic Reduction Method 3

Enhancing the Channel Quality in Cognitive network by Traffi...

引用

3rd ieee international conference on Intelligent Technologies, CONIT 2023

作者： Singh, Sanjay Pilania, Urmila Kumar, Manoj Awasthi, Satya Prakash Nelson, Leema Manav Rachna University Dept. of Computer Science & Technology Faridabad India Poornima University Faculty of Computer Engineering Jaipur India Chitkara University Institute of Engineering & Technology Chitkara University Department of Computer Science & Engineering Punjab India

ISBN: (纸本)9798350338607

Cognitive radio (CR) has some specific unique characteristics like flexibility, interoperability and adaptability. Optimal technological candidate is particularly contributed which reduces the challenges towards spectrum scarceness sin multimedia communications. Moreover, this communication over CR networks produces few severe issues like delay-sensitive, bandwidth-hungry, and loss-tolerant service and particularly ensuring quality of service (QoS). Improved Dynamic Optimization Algorithm (IDOA) is proposed for spectrum sensing in cognitive radio networks (CRN) where for the Secondary User (SU), data traffic is considered. From the comparison of several works in the literature, it is assumed that SU have no packets to transmit always;but actually data sent per second is considered instead of channel capacity as the possible throughput with which the problem of sensing-throughput tradeoff is reformulated. The parameters such as probability of availability, Signal to Interference Noise Ratio (SINR), Processing time and transmission time are considered to analyze the efficiency of the IDOA approach proposed which is compared with two state of methods namely Medium Access Control (MAC) and Dijikstra Algorithm (DA). © 2023 ieee.

关键词： Cognitive radio

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Enhancing Remote Oversight of Plants with a Compact IIoT System 3

Enhancing Remote Oversight of Plants with a Compact IIoT Sys...

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3rd ieee international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Singh, Shweta Ganorkar, Akshaya M Anujhna, B. Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350343274

It is impossible to overestimate the importance of remotely monitoring industrial facilities in the context of the Industrial Internet of Things. The goal of this line of research is to improve remote monitoring by using real-time data analytics, predictive maintenance, and energy optimization with a tiny Industrial Internet of Things (IIoT) system. The three most important algorithms are an energy optimization method using a proportional-integral-derivative (PID) controller, a predictive maintenance strategy based on machine learning models, and a real-time data streaming and analysis tool. The proposed method is said to be able to use these algorithms in real time, which enables it to schedule preventive maintenance, identify anomalies, and use energy effectively. Effective, sustainable, and data-driven plant management support should be expected to result in minimal downtime, lower operating costs, and ecologically conscious operations. © 2023 ieee.

关键词： Proportional control systems

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A 3D Multi-Modal Network for MRI Fast Reconstruction 3

A 3D Multi-Modal Network for MRI Fast Reconstruction

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3rd international conference on Electronic Information Engineering and computer, EIECT 2023

作者： Zhou, Xiuyun Du, Hongwei University of Science and Technology of China Department of Electronic Engineering and Information Science Hefei China

ISBN: (纸本)9798350357707

Magnetic resonance imaging (MRI) has the advantages of non-ionizing radiation, multi-directional scanning, multi-orientation scanning and high resolution. However, its acquisition time is long, which can easily lead to patient discomfort and motion artifacts. Traditional technologies include compressed sensing and parallel imaging to accelerate imaging, and in more recent years, deep learning has also been employed for MRI fast reconstruction. On the other hand, imaging the same site with different parameters (modalities) is frequently necessary for more accurate and comprehensive radiological assessment. However, multi-modal methods, as opposed to earlier single-modal reconstruction techniques, can make use of correlation data between various modality images to produce better reconstruction outcomes. Based on this, we propose a 3D multi-modal MRI fast reconstruction network. The experimental results show that, compared with other methods, the 3DMMNet network achieves better experimental results in PSNR, SSIM, and NMSE metrics, showing the efficacy and superiority of the network. © 2023 ieee.

关键词： Magnetic resonance imaging

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Small object detection algorithm for aerial photography based on improved YOLOv5 3

Small object detection algorithm for aerial photography base...

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3rd international conference on Electronic Information Engineering and computer Communication, EIECC 2023

作者： Wang, Li Yu, Yuecheng Xu, Pucheng Zou, Rundong Hua, Wei Yuan, You School of Computer Science Jiangsu University of Science and Technology Zhenjiang Jiangsu China

ISBN: (纸本)9798350359961

Aiming at the problems such as high missed detection rate and inaccurate positioning caused by complex background, large number and dense distribution of small targets in UAV aerial photography target detection tasks, this paper proposed an improved YOLOv5 based aerial small target detection model. Firstly, the reparameterized structure RepVGG is introduced into the backbone network, and the multi-branch structure is used to enhance the feature extraction capability of the model. Secondly, a hybrid domain Attention mechanism (ECA DSAM Model, EDM), Efficient Channel Attention mechanism (ECA) and Dilated Spatial attention Model (Dilated Spatial Attention Model) are designed. EDM). Experiments on UAV aerial photography data set VisDrone show that m AP0.5 of the original YOLOv5 model has improved by 2.7%, and the improved method has better performance in the detection of small targets in aerial photography. © 2023 ieee.

关键词： Attention mechanism Small target detection UAV aerial photography YOLOv5

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Dual Aggregation Convolution for Image Super-Resolution 3

Dual Aggregation Convolution for Image Super-Resolution

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3rd international conference on Cloud Computing, Big data application and Software Engineering, CBASE 2024

作者： Wang, Zhongxun Xie, Zheng School of Physics and Electronic Information Yantai University Shandong China Yantai University Shandong Data Open Innovation Application Laboratory of Smart grid Advanced Technology Shandong China

ISBN: (纸本)9798331506582

In recent years, numerous image super-resolution (SR) methods have been introduced, achieving significant advancements. However, many existing methods employ complex, task-specific operations that, while effective, introduce substantial computational overhead when directly stacked, thereby hampering their practical utility. In response, we introduce DACNet, an efficient SR model that innovatively integrates spatial and channel information through a collaborative framework. Specifically, we alternately apply the Aggregation Spatial Convolution Module (ASCM) and the Aggregation Channel Convolution Module (ACCM) to dynamically extract and integrate multi-level features. Furthermore, we employ a Convolution Compensation Module (CCM) to mitigate local pixel forgetting. Our comprehensive experiments demonstrate that DACNet not only achieves superior performance but also maintains minimal computational demands, making it highly effective in resource-constrained environments. © 2024 ieee.

关键词： Convolution

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An Analysis Of Anomaly Detection Techniques for IoT Devices: A Review 3

An Analysis Of Anomaly Detection Techniques for IoT Devices:...

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3rd international conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Bindra, Shivam Malik, Aruna Dr Br Ambedkar National Institute of Technology Department of Computer Science and Engineering Punjab Jalandhar India

ISBN: (纸本)9798350300710

There is an increasing demand for effective intrusion detection systems to protect the privacy and security of IoT devices and the data they collect and transmit. IoT devices are susceptible to a broad spectrum of security risks, such as unauthorised access, assaults, and breaches, which can put in danger the network's integrity, confidentiality, and availability. This study investigates the various methodologies used in IoT device anomaly detection. The paper discusses possible solutions, such as using lightweight algorithms, distributed intrusion detection systems, and adaptive security mechanisms. Some of the frameworks reviewed in this paper are BFA-PDBSCAN, B-Stacking, Two stream neural network and Hybrid (Anomaly-based +Specification-based) detection. Effective anomaly detection in IoT devices requires a multi-layered security approach that incorporates various intrusion detection techniques and best practises in order to protect the confidentiality and anonymity of IoT devices or the collected and transmitted data. © 2023 ieee.

关键词： Intrusion detection

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Simple Industrial Cutting Machine Safety System Based on computer Vision 3

Simple Industrial Cutting Machine Safety System Based on Com...

引用

3rd ieee international conference on Electronic Communications, Internet of Things and Big data, ICEIB 2023

作者： Chiang, Chien-Lin Peng, Ming-Yuan Lin, I-Long Chou, Yu-Wei Fong, Ji-Men Chiang, Yi-Yuan Department of Computer Science and Engineering Tatung University Taipei Taiwan Graduate Institute of National Development and Mainland China Studies Chinese Culture University Taipei Taiwan Department of Computer Science and Information Engineering Vanung University Taoyuan Taiwan

ISBN: (纸本)9798350333862

Safety devices are often not fitted to many simple panel-cutting machines due to cost. Designing and installing low-cost safety devices on the simple panel-cutting machine improves the safety of operators. We propose a computer vision-based safety system with a camera to capture images of the operator and machine from above. Each captured image is analyzed by a neural network. If the operator's hands are too close to the cutting tool, the safety system sends a warning signal and stops the machine. The neural network used in the vision system is a ten-layer convolutional neural network. In addition to the input and output layers, there are five convolutional layers in the middle, followed by three fully connected layers. The input image undergoes five convolution operations to obtain feature maps of different granularity. With three fully connected layers, a combination of features is used to determine the positions of the operator's hands as a guideline for stopping the machine. To improve the generalization of the model, we collect thousands of training data. The experimental results show that the model has a low bias, low variance, and high accuracy characteristics. The accuracy of the verification data is over 98%. © 2023 ieee.

关键词： Convolutional neural networks

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Diagnosing Spinal Abnormalities Using Machine Learning: A data-Driven Approach 3

Diagnosing Spinal Abnormalities Using Machine Learning: A Da...

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3rd ieee international conference on Artificial Intelligence, ICAI 2023

作者： Ul Islam Nasir, Zia Khan, Khalil Asghar, Momna Islamabad Pakistan Pak-Austria Institute of Applied Science & Technology Department of Computer Software Engineering & Computer Science Haripur Pakistan University of Azad Jammu & Kashmir Department of Electrical Engineering A.K Muzaffarabad Pakistan

ISBN: (纸本)9798350322125

Low back pain is a predominant condition which can affects people from different diaspora. The goal of this work is to use machine learning approach to forecast spinal abnormalities. Extratreesclassifier is utilized as a data preprocessing stage to choose the dataset's most prominent features. On a dataset of 310 samples, spinal anomalies are diagnosed using machine learning algorithms like the Support Vector Machine (SVM) and the multilayer perceptron (MLP). The purpose of this study is to determine the most crucial factors that produce backbone abnormalities and to predict them using supervised machine learning techniques. The classification of normal and abnormal spinal patients is investigated in terms of various aspects, including testing and training accuracy, precision, and recall. The observed accuracies for SVM and MLP with 80% training data are 92% and 90%, respectively. The result shows that these models can achieve high accuracy in predicting spinal abnormalities, with the SVM model performing the better. The result suggest that this approach has the potential to significantly improve the efficiency and accuracy of spinal abnormality diagnosis, leading to better patient outcomes. © 2023 ieee.

关键词： Support vector machines

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2023 ieee 3rd international conference on Power, Electronics and computer applications, ICPECA 2023

2023 IEEE 3rd International Conference on Power, Electronics...

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3rd ieee international conference on Power, Electronics and computer applications, ICPECA 2023

ISBN: (纸本)9781665472784

The proceedings contain 344 papers. The topics discussed include: image defogging based on joint contrast enhancement and multi-scale fusion;face tracking by fusing convolutional neural networks and particle filtering;construction of LC filter integrated circuit and analysis of control system function;privacy preserved federated learning for skin cancer diagnosis;research on the control under the participation of heat storage device and fast cut back control strategies in isolated grid;large-scale energy storage battery technology participates in the application of AGC frequency modulation in thermal power plants;intelligent monitoring and analysis system for boiler combustion based on big data;research on the platform of metrological inspection calibration;inverter fault diagnosis algorithm based on midpoint voltage deviation polarity and topology reconstruction;next point-of-interest recommendation for cold-start users with spatial-temporal meta-learning;the influence of axial flux leakage from motor coils on the magnetic bearing and shielding measures;a common-mode voltage suppression oriented modulation method for modular multilevel converters;chance-constrained energy management strategy for micro-grids intra-day operation;and an improved support vector machine attack detection algorithm for industry controls system.

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