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A 3D Streamline Selection Algorithm Based on Comprehensive Similarity 3

A 3D Streamline Selection Algorithm Based on Comprehensive S...

引用

3rd international conference on Artificial Intelligence and Computer Engineering, ICAICE 2022

作者： Hu, Xiaomei Weng, Jiahong Chai, Jianfei Zhang, Mingnan Li, Yilin Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China Information Technology Office School of Mechatronic Engineering and Automation Shanghai University Shanghai200444 China

ISBN: (纸本)9781510663473

In order to avoid the occlusion problems and missing important features of streamlines in the flow field, this paper proposes a 3D streamline selection algorithm based on comprehensive similarity. The method starts with a hierarchical clustering of streamline sets and then extracts streamlines with high similarity based on their comprehensive similarity. The comprehensive similarity of streamlines requires the calculation of the distance and contour similarity of the streamlines. In this paper, the Hausdorff distance is improved by proposing a partially matched Hausdorff distance to reduce the influence of streamline length on the similarity calculation. Then the contour similarity is calculated according to the ICP algorithm and the entropy weighting method is used to calculate the weights to obtain the combined similarity. The final comparison with the result of another algorithm shows that the flow field structure is clearer, more complete and more evenly distributed when the streamlines are selected using this algorithm. © 2023 SPIE.

关键词： Flow fields

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Task Assignment Algorithm for Unmanned systems Based on Step Clustering Ant Colony 1

引用

3rd international conference on Autonomous Unmanned systems, ICAUS 2023

作者： Jiang, Jian Men, Xinghuo Zhang, Defeng Jiang, Wenkai Liu, Haiying State Key Laboratory of Complex Electromagnetic Environment Effects On Electronics and Information System LuoYang471003 China College of Astronautics Nanjing University of Aeronautics and Astronautics Nanjing210016 China

ISBN: (数字)9789819710874

ISBN: (纸本)9789819710867

The task assignment of unmanned systems is widely used and has been studied extensively. However, when there are a large number of target points in the task area, it is often a difficult problem to carry out reasonable task allocation. In view of the above situation, this paper proposes a task assignment based on step clustering ant colony algorithm. Firstly, by analyzing a large number of task scenarios in the case of target points, the task scenarios are transformed into NP-hard problems, and the mathematical model is established. Secondly, the k-means algorithm is used to cluster the target to be distributed, and the "elbow method" is used to determine the optimal clustering K value, the task area is divided into "target block", and the problem dimension is reduced. After that, ant colony algorithm is used to solve the TSP problem for the target points in the "target block", and the task assignment for a large number of targets is finally completed Finally, simulation experiment is conducted to verify the effectiveness of the algorithm. The results show that the ant colony algorithm based on step clustering can effectively assign tasks with a large number of target points in the task area. © Beijing HIWING Scientific and Technological information Institute 2024.

关键词： K-means clustering

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Blockchain-based ciphertext access control for data sharing using key encapsulation mechanism 3

Blockchain-based ciphertext access control for data sharing ...

引用

3rd international conference on Blockchain Technology and information Security, ICBCTIS 2023

作者： Feng, Yashi Zhao, Jinyi Chen, Taowei Yu, Yimin School of Information Yunnan University of Finance and Economics Kunming China

ISBN: (纸本)9798350340402

The article presents a plan for distribnting access control and data sharing through CP-ABE. This plan allows for provable security and privacy protection without requiring authorization agencies. The main key of the CP-ABE algorithm is managed in a distributed manner based on blockchain through proxy key encapsulation technology, and a blockchain dual-chain model is adopted to improve system performance and security. At the same time, the block structure and data format specifications are designed to achieve on-chain supervision with traceable management and operational behavior of the PKEM-CPABE algorithm. Experimental simulation analysis shows that the proposed algorithm achieves an efficient and secure sharing mechanism while protecting data privacy. © 2023 IEEE.

关键词： Authorization

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High Performance and Energy Efficient Floating-Point Multiplier on FPGA 3

High Performance and Energy Efficient Floating-Point Multipl...

引用

3rd IEEE international conference on Computer systems, ICCS 2023

作者： Zhang, Hao Zheng, Xueyi Ko, Seok-Bum Ocean University of China Information Science and Engineering Qingdao China University of Saskatchewan Electrical and Computer Engineering Saskatoon Canada

ISBN: (纸本)9798350313666

In this paper, a high performance and energy efficient double-precision floating-point multiplier is designed and implemented on FPGA devices. A novel mapping solution of the mantissa multiplier is proposed which makes full use of the DSP blocks and requires less pipeline stages. In addition, a dual-mode floating-point multiplier is also proposed in this paper which is designed by splitting the components of the proposed double-precision multiplier. Two parallel single-precision operations are supported. For comparison purpose, the proposed architecture is implemented on Xilinx Virtex-5 (xc5vlx155ff1760-3) device, where the proposed double-precision multiplier can run 3.4% faster than previous work with less latency and can run 32.3% faster than the IP core multiplier with same latency. The proposed dual-mode multiplier can run 20.9% faster than previous fastest dual-mode design. In terms of energy consumption, the proposed double-precision multiplier consumes 43.3% less energy per operation compared to the double-precision IP core. The proposed dual-mode multiplier can achieve 24.5% less energy per operation compared to the double-precision IP core. The implementation results of the proposed architectures on latest Xilinx Virtex-7 and Altera Arria-10 devices are provided. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Real-Time Anomaly Detection in 5G Networks Through Edge Computing 3

Real-Time Anomaly Detection in 5G Networks Through Edge Comp...

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3rd IEEE international conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Shaik, Riaz Raju, Dara Behera, Prakash Chandra Changala, Ravindra Mary, S. Suma Christal Balakumar, A. Kl University Department of Cse Andhra Pradesh Vaddeswaram India Vignana Bharathi Institute and Technology Dept. of Computer Science & Engineering Aushapur Ghatkesar India St. Claret College Department of Science Bangalore India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of Ece samayapuram Trichy India

ISBN: (纸本)9798350361186

Strong anomaly detection techniques are becoming more and more necessary as 5G networks develop in order to maintain network performance, security, and dependability. This study leverages the capabilities of Mobile Edge Computing (MEC) to present a novel method for anomaly detection in 5G networks. By processing data closer to the network edge, the integration of MEC offers an efficient and decentralized architecture that lowers latency and improves real-time detection capabilities. The distributed module takes advantage of its close proximity to network devices by using sophisticated algorithms for anomaly detection, which are implemented at the mobile edge. The system can quickly detect abnormalities from typical network activity by utilizing capabilities including Flow Collection, Anomaly Symptom Detection, and Network Anomaly Detection. The distributed module provides anomalous information to the centralized decision-making module for thorough examination. It takes into account variables like resource use and network traffic and integrates this data with metrics gathered from monitoring modules. Because of its adaptive characteristics, the system may expand anomaly detection components, enhance detection functions, and modify virtualized resources in response to shifting network circumstances. The evaluation findings reveal that the suggested anomaly detection method performs well in 5G networks, with decreased false positives, increased responsiveness, and better flexibility to changing network conditions. Using MEC not only makes anomaly detection more effective, but it also fits in with the 5G design, which makes it a viable option for protecting the upcoming generation of communication networks. It obtains 95% accuracy in classification. The suggested approach has proven to be resilient in handling security issues by producing outcomes that are either comparable to or better than those attained by other techniques that have been previously presented in the s

关键词： 5G mobile communication systems

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Software and Hardware Platform Technology of Embedded Device Based on Heterogeneous SoC Chip in substation 3

Software and Hardware Platform Technology of Embedded Device...

引用

3rd IEEE international conference on information Technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Zhiqiang, Yao Hui, Ren Xin, Xu Xin, Chen Yanping, Wu Jiajia, Zhu Chen, Fan Electric Power Research Institute Limited Company Nanjing Department of China Nanjing China State Grid Jiangsu Electric Power Co.LTD Information & Telecommunication Branch Nanjing China

ISBN: (纸本)9781665490788

In order to meet the demand of high-precision harmonic sampling in electronics power grid, and further improve the performance of secondary equipment such as substation measurement and control, PMU and broadband measurement, the application scenarios and performance requirements of high-performance hardware platform are analyzed, and the technical status of domestic chips in mass production is investigated. The hardware platform scheme of heterogeneous SoC chips is adopted, and the dual-system software architecture based on Linux and RTOS system is adopted, We have designed a large-capacity real-time data parallel processing and layered drive technology scheme, fully developed the computing potential of heterogeneous multi-core chips, improved the performance of hardware platform based on domestic chips, and completed the development and testing of the hardware platform of broadband measurement device prototype. Finally, the feasibility of the hardware platform technology scheme based on heterogeneous SoC chips is verified through the comparison of various performance tests. © 2023 IEEE.

关键词： System-on-chip

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Enhancing Networked Embedded systems Using Deep Learning Techniques 3

Enhancing Networked Embedded Systems Using Deep Learning Tec...

引用

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

作者： Asha, K. Kumar, Ritesh Fiza, Samreen Department of Life Sciences Karnataka India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India

ISBN: (纸本)9798350343274

Improving performance and flexibility is crucial in the field of networked embedded systems. Using deep learning methods, this research presents a fresh strategy for doing this. Our suggested approach involves creating a custom deep learning architecture tailored to the specific needs of distributed embedded systems. This strategy makes use of Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory Networks (LSTMs) to evaluate real-time data streams, expedite decision-making, and intelligently adapt to ever-changing environments. In addition, using reinforcement learning helps systems behave and use energy more efficiently, creating a more flexible and smart setting. To reduce latency and reliance on centralized servers, edge computing plays a crucial role by allowing for real-time data processing on embedded devices. The suggested technique was evaluated alongside more conventional methods in a side-by-side comparison. Imaginary numbers were utilized for demonstration purposes. The findings illustrate the higher performance of the suggested technique across several parameters. When compared to baseline deep learning methods like Convolutional Neural Networks, Recurrent Neural Networks, Long Short-Term Memory Networks, Generative Adversarial Networks, Federated Learning, Transfer Learning, and Time Series Analysis with Deep Learning, the proposed method shows marked improvements in accuracy, latency, energy efficiency, robustness, security, scalability, and resource utilization. Finally, the suggested methodology emerges as a game-changing strategy for enhancing the capabilities of networked embedded systems, since it is supported by deep learning methods, reinforcement learning, and edge computing. Its ushers in a new era of networked embedded systems with its flexibility to process sequential data, analyze picture and video material, and maximize energy efficiency. The results of the comparison study validate the superior

关键词： Energy efficiency

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Security Attacks and Key Challenges in Blockchain Technology: A survey 3

Security Attacks and Key Challenges in Blockchain Technology...

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3rd international conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2022

作者： Krishnaraj Rao, N.S. Raghunadan, K.R. Dodmane, Radhakrishna Bhavya, K. Islam, Sardar M N Shetty, Surendra NMAM Institute of Technology Nitte Information Science and Engineering Karkala574110 India ISILC Victoria University MelbourneVIC8001 Australia Master of Computer Applications NMAM Institute of Technology Nitte Karkala574110 India

ISBN: (纸本)9781665456647

A blockchain is a decentralized, distributed, and open ledger that is used to record transactions across several computer clusters. Without a change in subsequent blocks, the record cannot be changed. Blockchain is a well-known phrase in the IT industry. There are several issues with Blockchain technology that need to be taken into account, despite the fact that it has many applications in the fields of information technology, banking, and other industries. In this paper, we discussed the major challenges and issues associated with Blockchain technology © 2022 IEEE.

关键词： Smart contract

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Where to Turn: Road Fork Detection in Sparse 3D Point Cloud 3rd

Where to Turn: Road Fork Detection in Sparse 3D Point Clou...

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3rd international conference on Autonomous Unmanned systems, ICAUS 2023

作者： Hu, Di Zhang, Kai Zhong, Yipan Xu, Jiachen Yuan, Xia Zhao, Chunxia School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Research Institute of Intelligence Southwest Research Institute of Information Control Chengdu611700 China

ISBN: (纸本)9789819711024

Intersection detection plays a crucial role in localizing and planning the path of autonomous vehicles in urban environments. This paper presents a novel approach, PVWO, for adaptive intersection detection in autonomous vehicles equipped with 3D LiDAR. Firstly, the algorithm removes ground and obstacles effectively, and eliminates noise points. Secondly, a polyarticular viewpoints beam model is applied to detect the type and location of intersections. Thirdly, a linear feature extraction approach in a rolling window is proposed to detect road width and optimize key parameters, enhancing model robustness across different scenes. Compared to parallel intersection detection algorithms, our method exhibits excellent performance under diverse road conditions. Experiments in sparse point clouds show an average precision exceeding 89% and an average processing time of approximately 88 ms/frame. These results demonstrate that our method can accurately detect intersections in real-time, across various road structures. © Beijing HIWING Scientific and Technological information Institute 2024.

关键词： Extraction

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A Comparative Analysis Between Quantum Machine Learning and Machine Learning on EEG Dataset 3

A Comparative Analysis Between Quantum Machine Learning and ...

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3rd IEEE international conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024

作者： Angrisani, Leopoldo De Benedetto, Egidio Di Bernardo, Alessandro Prevete, Roberto Tedesco, Annarita University of Naples Federico Ii Department of Information Technology and Electrical Engineering Naples Italy University of Naples Federico Ii Department of Public Health Naples Italy

ISBN: (纸本)9798350378009

In recent years, quantum technology has been developing in several fields, including quantum computing. Quantum Computing (QC) is a type of computing that uses quantum bits (qubits) instead of classical bits to perform calculations. Unlike classical computers, which use binary logic (0s and 1s), quantum computers exploit quantum phenomena (such as superposition and entanglement), which are expected to bring advantages over traditional Machine Learning (ML). However, QC is still an emerging field, and further research is needed to fully understand its potential in ML. In this regard, for example, it is still unclear how QC compares with traditional ML in terms of stability and generalization. Starting from this consideration, this work intends to experimentally compare quantum and traditional ML. In particular, the classical Support Vector Machine (SVM), which belongs to the traditional ML approach, and a Quantum Support Vector Machine (QSVM), as Quantum Machine Learning (QML) approach (which combines quantum computing and machine learning through quantum properties), are applied to a specific case study related to electroencephalographic (EEG) data. The comparison was conducted on similar development environments to ensure comparable results from a measurement standpoint. The results highlight that there are some critical points involving the generalization ability of QML algorithms, possibly related to an appropriate and specific hyperparameter search. © 2024 IEEE.

关键词： Quantum computers

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