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共 4259 条记录，以下是151-160 订阅

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A Study on Platform of intelligent Metering Builds on Cloud computing 7th

A Study on Platform of Intelligent Metering Builds on Cloud ...

引用

7th international conference on computing, Control and Industrial Engineering, CCIE 2023

作者： Li, Xinyi Sun, Hang Wen, Shijie Chen, Chen Zhang, Hongzhong Deng, Longhai Guizhou Power Grid Co. Ltd. Guiyang Power Supply Bureau Guizhou Guiyang55001 China

ISBN: (纸本)9789819927296

To meet the needs of intelligent metering platform in the future, the current status of metering automation system and problems have been described and a new system solutions based on cloud computing is presents in this paper. the feasibility and necessity of cloud computing applications in the intelligent metering platform are analyzed. A distributed cloud computing method is proposed in the light of massive electric data and a massive electric data cloud computing platform based on Hadoop is built. In this platform, virtualization technology is used to get the unified organization for various types of heterogeneous hardware and software, while he HDFS and HBase technologies are used to get the efficient distributed storage and management for massive and MapReduce technology is used to get distributed paralleled processing for user service and resource scheduling. Now, the new intelligent metering platform has practical applications, third-party test results show that most of the functions the system meet the requirement in the future smart metering platform. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Digital storage

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Unraveling the Black Box: Interpreting CNNs for Leaf Disease Detection through Model Analysis and Feature Importance 17

Unraveling the Black Box: Interpreting CNNs for Leaf Disease...

引用

17th international conference on INnovations in intelligent SysTems and Applications, INISTA 2023

作者： Ghazouani, Haythem Barhoumi, Walid Jeon, Gwanggil Zagrouba, Ezzeddine Tunisia Université de Carthage Ecole Nationale d'Ingénieurs de Carthage Tunisia Shandong University of Technology School of Electrical and Electronic Engineering Zibo China Incheon National University Department of Embedded Systems Engineering Incheon Korea Republic of

ISBN: (纸本)9798350338904

Convolutional Neural Networks (CNNs) have been highly successful in computer vision tasks, including leaf disease detection. However, their lack of interpretability limits our understanding of their decision-making process and undermines trust in their predictions. In this study, we aim to unravel the black box of CNNs for leaf disease detection through a comprehensive model analysis and feature importance study. We review various techniques in explainable artificial intelligence and propose a methodology that combines model analysis and feature importance methods. We analyze the model's internal representations and activations in order to understand how different layers process information. Additionally, we employ feature importance methods, like SHapley Additive exPlanations (SHAP), to quantify the influence of individual features on predictions. By assigning importance scores to each pixel or feature, we identify the most discriminative regions or characteristics used by the CNN for disease detection. these insights provide a deeper understanding of learned representations, the decision-making process, and the key visual cues used by CNNs. Our findings enhance interpretability, foster trust in automated leaf disease detection systems, and facilitate the development of more explainable and reliable models in precision agriculture. © 2023 IEEE.

关键词： Decision making

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A Text Block Refinement Framework For Text Classification and Object Recognition From Academic Articles 17

A Text Block Refinement Framework For Text Classification an...

引用

17th international conference on INnovations in intelligent SysTems and Applications, INISTA 2023

作者： Jinghong, Li Koichi, Ota Wen, Gu Shinobu, Hasegawa Japan Advanced Institute of Science and Technology Japan

ISBN: (纸本)9798350338904

With the widespread use of the internet, it has become increasingly crucial to extract specific information from vast amounts of academic articles efficiently. Data mining techniques are generally employed to solve this issue. However, data mining for academic articles is challenging since it requires automatically extracting specific patterns in complex and unstructured layout documents. Current data mining methods for academic articles employ rule-based (RB) or machine learning (ML) approaches. However, using rule-based methods incurs a high coding cost for complex typesetting articles. On the other hand, simply using machine learning methods requires annotation work for complex content types within the paper, which can be costly. Furthermore, only using machine learning can lead to cases where patterns easily recognized by rule-based methods are mistakenly extracted. To overcome these issues, from the perspective of analyzing the standard layout and typesetting used in the specified publication, we emphasize implementing specific methods for specific characteristics in academic articles. We have developed a novel Text Block Refinement Framework (TBRF), a machine learning and rule-based scheme hybrid. We used the well-known ACL proceeding articles as experimental data for the validation experiment. the experiment shows that our approach achieved over 95% classification accuracy and 90% detection accuracy for tables and figures. © 2023 IEEE.

关键词： Data mining

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A Review on Detection and Prevention of the DDoS Attacks in the Blockchain 4

A Review on Detection and Prevention of the DDoS Attacks in ...

引用

4th IEEE international conference on computing, Communication, and intelligent Systems, ICCCIS 2023

作者： Vaghela, Hansa Khirasaria, Vivek Parul University Faculty of Engineering and Technology Vadodara India Sharda University Faculty of Engineering and Technology Uzbekistan

ISBN: (纸本)9798350306118

Now a day's, blockchain technology is an emerging technology. the Blockchain is a distributed network technology that uses a decentralized approach to information storage. When transactions are performed using blockchain technology, security concerns are a top priority. It required more storage and used more energy. Security is affected by endpoint vulnerability. Attackers exploit this weakness to damage the system and carry out attacks. A DDoS attack is the most harmful attack on the blockchain peer-To-peer network. It affects the unavailability of every internet-based network. Node crashes, software failure, network congestion, and a bloated ledger are the aspects of blockchain DDoS attacks that are most affected. In this paper we find out solutions to prevent this attack from occurring by increase system security, and defend against security attacks. © 2023 IEEE.

关键词： Smart contract

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Enhancing Security in distributed computing through Quantum Neural Network-Enabled Blockchain 7th

Enhancing Security in Distributed Computing Through Quantum ...

引用

7th international conference on intelligent computing and Optimization, ICO 2023

作者： Xiuliang, Qiu Rajawat, Anand Singh Goyal, S.B. Solanki, Ram Kumar Chengyi University College Jimei University Xiamen361021 China Faculty of Information Technology City University Petaling Jaya46100 Malaysia School of Computers Science & Engineering Sandip University Nashik422213 India

ISBN: (纸本)9783031733239

It is more crucial than ever to maintain proper security in the constantly changing world of distributed computing due to the complexity and variety of cyber threats that are on the rise. In this study, we describe a novel approach that combines blockchain technology with quantum neural networks to increase the security of distributed systems. Quantum Neural Networks (QNNs) are based on the principles of quantum physics and are more robust and secure than classical systems. We take advantage of both the higher processing capability of quantum computing and the decentralized, unchangeable nature of blockchain by integrating QNN into a blockchain architecture. Our suggested methodology not only expedites transaction verifications but also greatly lowers exposure to common security issues like double spending and the Sybil attack. Initial tests reveal a considerable decline in fraudulent activity as well as an improvement in system speed and reduced latency. this study shows that a QNN-capable blockchain has the potential to herald in a new era of dependable, efficient, and secure distributed computing. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Quantum computers

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A Self-learning Hyper-Heuristic Algorithm for Energy-Efficient distributed Flexible Job Shop Scheduling 20th

A Self-learning Hyper-Heuristic Algorithm for Energy-Efficie...

引用

20th international conference on intelligent computing (ICIC)

作者： Zhao, Fuqing Geng, Zewu Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China

ISBN: (纸本)9789819755776;9789819755783

the distributed flexible job shop scheduling problem (DFJSP) has been studied intensively over the past decades, and the energy-efficient distributed flexible job shop scheduling problem (EDFJSP) has emerged as a hot and challenging research topic. A self-learning hyper-heuristic algorithm (SLHH) is proposed in this paper to solve EDFJSP. First, an EDFJSP model is established, and a coding scheme is designed based on the characteristics of the problem. Second, a Qlearning-based high-level strategy and an improved epsilon - greedy policy are designed to guide six knowledge-based low-level heuristics (LLHs) to explore the solution space and move acceptance to ensure the diversity of solutions. third, an energy-saving strategy is proposed which can effectively reduce the energy consumption of the solution. the performance of SLHH is tested against three state-of-the-art algorithms in 20 benchmark instances. the experiment results demonstrate the effectiveness of SLHH in addressing the multifaceted challenges of EDFJSP.

关键词： Hyper-heuristics Q-learning distributed scheduling Flexible shop scheduling Energy-efficient

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Cross-Domain Deterministic Communication System for Differentiated Concurrent Services Based on intelligent Compression 4

Cross-Domain Deterministic Communication System for Differen...

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4th international conference on Computer Science, Electronic Information Engineering and intelligent Control technology, CEI 2024

作者： Gao, Chengtao Wu, Runze Guo, Haobo College of Electrical and Electronic Engineering North China Electric Power University Beijing China

ISBN: (纸本)9798350378542

Under the background of the 'dual carbon' goal and related policies and the construction of new power systems, the large-scale deployment of sensing terminals and the explosive growth of the perception amount of data in the distribution system, the low transmission efficiency of the traditional distribution network has been unable to meet the needs of 'comprehensive perception and efficient collaboration'. How to achieve rapid transmission and real-time analysis of massive sensing data has become one of the main challenges of the new distribution network. Adding lossless compression to edge computing provides a way to transmit lightweight data at cloud edge. Considering the QoS requirements of differentiated concurrent services, this paper proposes an intelligent compressed cross-domain deterministic communication system for differentiated concurrent services. First, a cross-domain deterministic communication system model for differentiated concurrent services is constructed. the problem is optimized according to service QoS requirements and model constraints, and the service compression ratio is minimized under the condition that the service requirements are met. then deep reinforcement learning method is used to solve the problem, and finally the proposed system effectively improves the certainty of massive distributed PV through simulation. © 2024 IEEE.

关键词： DC distribution systems

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Blockchain technology for Addressing Privacy and Security Issues in Cloud computing

Blockchain Technology for Addressing Privacy and Security Is...

引用

17th international conference on Cyber Warfare and Security (ICCWS)

作者： Tehrani, Pardis Moslemzadeh Kotsis, Gabriele Pranata, Andasmara Rizky Univ Malaya Fac Law Kuala Lumpur Malaysia Johannes Kepler Univ Linz Head Telecooperat Dept Linz Austria

ISBN: (纸本)9781914587276

Blockchain technology is a recent and important financial technology that has completely transformed business transactions. the adoption of cloud computing in all IT environments due to its efficiency and availability has increased dramatically. Despite attempts to address privacy and security issues, confusion remains in the cloud environment. It is said that blockchains are a promising solution for many distributed applications and have the potential to overcome issues pertaining to the centralized system. the decentralized nature of blockchains provides a new forms of distributed software architectures where users can reach agreement consensually on the shared system without relying on a central integration point. Nonetheless, there are some challenges which need to be evaluated. Accordingly, this study explores how blockchains can curb cloud computing issues from both legal and technical aspects. this article presents the use of blockchain in current cloud storage applications and discusses how blockchain technology can be used to resolve security and privacy challenges. the use of blockchains as a solution for each issue will be proposed by explaining how they can overcome the shortcomings of cloud computing.

关键词： Blockchain Cloud computing Privacy Security Contractual Terms

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U-Shaped Network Based on Deformable Convolutional Encoder for Semantic Segmentation of Winter Wheat 9

U-Shaped Network Based on Deformable Convolutional Encoder f...

引用

9th international conference on intelligent computing and Signal Processing, ICSP 2024

作者： Hu, Qiao Wang, Nan Zhang, Haining Beijing Institute of Technology Beijing China Neijiang Normal Uninversity Sichuan China

ISBN: (纸本)9798350376548

the distribution of winter wheat in mountainous regions is fragmented and exhibits irregular shapes. Conventional networks tend to lose the fragmented distribution of winter wheat and struggle to accurately predict the distribution edges. To address this issue, this study improves the encoder part of the UNet network by replacing ordinary convolutions with deformable convolutions to achieve flexible extraction of local features. this improvement is beneficial for extracting features from fragmented and irregularly distributed winter wheat. To leverage the advantages of multi-spectral imagery, a bi-temporal remote sensing dataset of winter wheat was created. the bi-temporal data provides more spectral information for the model. In order to model the correlation between the extracted feature channels and the importance of each channel for the segmentation task, a channel attention module called SEblock was added at the bottom of the network. Finally, comparative experiments demonstrate that DUNet effectively locates winter wheat under complex terrain conditions. © 2024 IEEE.

关键词： Semantic Segmentation

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Research on distributed Control technology of Ship Pod Propeller Turning Small Angle 18th

Research on Distributed Control Technology of Ship Pod Prope...

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18th international conference on Bio-Inspired computing: theories and Applications (BIC-TA)

作者： Xu, Ningjun Shi, Zhangsong Lyu, Xu Naval Univ Engn Coll Weap Engn Wuhan 430033 Peoples R China Jiangsu Automat Res Inst Lianyungang 222062 Peoples R China Tsinghua Univ Dept Precis Instrument Beijing 100084 Peoples R China

ISBN: (纸本)9789819722747;9789819722754

At present, most of the control systems of the full swing ship adopt the classical PI control or open loop transfer method, which has low control accuracy and slow response speed. In this paper, the idea of intelligent distributed control is introduced into the control of the propulsion device of the full swing ship pod, and the physical model and mathematical model of the hydraulic propulsion system of the pod are established. the PID control strategy based on fuzzy reasoning is designed for the full rotary propulsion device, which can accurately and reliably control the rotation Angle of the pod. Finally, the modeling and simulation of the full rotary hydraulic propulsion system of the pod are carried out under small Angle conditions. the results show that the rotation Angle error is small, and the proposed method has application value.

关键词： fuzzy reasoning distributed PID ship control

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