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检索条件"任意字段=6th IEEE International Conference on Distributed Computing in Sensor Systems"

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Research on Natural Language Generation System of BERT Model Computer Big Data Technology

Research on Natural Language Generation System of BERT Model...

引用

ieee international conference on Power, Intelligent computing and systems (ICPICS)

作者： Jianqin Zhang Nanjing Engineering Branch Jiangsu Union Technical Institute Nanjing China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

this paper focuses on the application and research of pre-trained model BERT in natural language generation system to meet the needs of natural language processing tasks in the era of big data. With the emergence of massive data, it is of great significance to use big data technology to understand and generate natural language efficiently. this study aims to build and optimize a natural language generation system based on BERT model, which can fully tap and utilize large-scale unannotated text data and capture complex context dependencies through deep two-way Transformer architecture to achieve accurate and smooth natural language generation. First, this paper discusses the core mechanism of BERT model and its superiority in natural language understanding, and analyzes its ability to effectively learn massive text resources in big data environment. then, we design a BERT model extension scheme that ADAPTS to big data environment. By combining distributed computing framework and targeted model optimization strategy, the training efficiency and generalization performance of the model can be improved when processing massive data. In the experimental part, we conduct a detailed evaluation of the constructed natural language generation system using large-scale real-world data sets, compare multiple benchmark models, and demonstrate significant effects on specific tasks such as news summary generation and conversation response generation. Experiments show that the natural language generation system based on BERT model effectively utilizes the advantages of big data while maintaining high language quality, and improves the relevance and accuracy of generated content.

关键词： Training Adaptation models Accuracy Computational modeling Natural language generation distributed databases Big Data Transformers Data models Optimization

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Modeling and Control of Discrete Event systems under Joint sensor-Actuator Cyber Attacks 6

Modeling and Control of Discrete Event Systems under Joint S...

引用

6th international conference on Automation, Control and Robotics Engineering (CACRE)

作者： Zheng, Shengbao Shu, Shaolong Lin, Feng Tongji Univ Sch Elect & Informat Engn Shanghai Peoples R China Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA

ISBN: (纸本)9781665435765

In this paper, we investigate joint sensor-actuator cyber attacks in discrete event systems. We assume that attackers can attack some sensors and actuators at the same time by altering observations and control commands. Because of the nondeterminism in observation and control caused by cyber attacks, the behavior of the supervised systems becomes non-deterministic and deviates from the target. We define two bounds on languages, an upper-bound and a lower-bound, to describe the nondeterministic behavior. We then use the upper-bound language to investigate the safety supervisory control problem under cyber attacks. After introducing CA-controllability and CA-observability, we successfully solve the supervisory control problem under cyber attacks.

关键词： Discrete event systems supervisory control cyber attacks network security resilient control

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A method of using standard flat objects to calibrate the spatial position of the sensor 6

A method of using standard flat objects to calibrate the spa...

引用

6th ieee international conference on Intelligent computing and Signal Processing, ICSP 2021

作者： Lin, Sheng Cheng, Yunyong Dou, Hao Fan, Xinxin Ye, Wenguang Northwestern Polytechnical University School of Mechanical Engineering Xi'an Shaanxi China

ISBN: (纸本)9780738143705

Determining the relationship between coordinate systems during measurement is one of the key works to ensure the accuracy of the measurement system. According to the traditional calibration method of standard spherical surface, because of the problem of measuring angle of surface features such as spherical surface, and the interference of specular reflection is easy to occur, the measurement of spherical surface by structural light often cannot fully describe the calibration feature or produce errors. In this paper, a unified calibration method based on the standard plane is proposed. Because plane features are easier to obtain and easier to control the appearance of specular reflection interference, and the calibration of plane geometry features used in this paper can completely avoid the distortion caused by the pending calibration measurement system. therefore, the method can fully meet the measurement accuracy requirements of the measurement system. © 2021 ieee.

关键词： Calibration

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A Blockchain-Enabled Approach to Cross-Border Compliance and Trust

A Blockchain-Enabled Approach to Cross-Border Compliance and...

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ieee international conference on Trust, Privacy and Security in Intelligent systems and Applications (TPS-ISA)

作者： Vikram Kulothungan Capitol Technology University North Bergen U.S.A

ISBN: (数字)9798350386745

ISBN: (纸本)9798350386752

As artificial intelligence (AI) systems become increasingly integral to critical infrastructure and global operations, the need for a unified, trustworthy governance framework is more urgent that ever. this paper proposes a novel approach to AI governance, utilizing blockchain and distributed ledger technologies (DLT) to establish a decentralized, globally recognized framework that ensures security, privacy, and trustworthiness of AI systems across borders. the paper presents specific implementation scenarios within the financial sector, outlines a phased deployment timeline over the next decade, and addresses potential challenges with solutions grounded in current research. By synthesizing advancements in blockchain, AI ethics, and cybersecurity, this paper offers a comprehensive roadmap for a decentralized AI governance framework capable of adapting to the complex and evolving landscape of global AI regulation.

关键词： Ethics Privacy Technological innovation distributed ledger Solids Regulation Safety Stakeholders Artificial intelligence Standards

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Standardized Blockchain Structure using TLV-Encoding for Large-scale Interoperability

Standardized Blockchain Structure using TLV-Encoding for Lar...

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Blockchain computing and Applications (BCCA), international conference on

作者： Sadaf Bukhari Kashif Sharif Liehuang Zhu School of Computer Science & Technology Beijing Institute of Technology Beijing China School of Cyber Security Beijing Institute of Technology Beijing China

ISBN: (数字)9798350351538

ISBN: (纸本)9798350351545

Blockchain systems have seen extensive research and adoption. However, its standardization remains challenging, hindering seamless interoperability and value transfer across diverse blockchain ecosystems. In addition, merging or conversion of heterogeneous chains in large-scale systems is impossible due to extensive variations in the fields and structures of the blocks. To address this challenge, this paper proposes a solution based on a unified and standardized representation of different BC ledgers. the proposed approach employs Type-Length-Value (TLV) encoding to facilitate a unified block structure. this mechanism allows the translation or conversion of existing blocks, merging heterogeneous chains, and creating hybrid chains with diverse block and transaction structures. Hence, facilitating large-scale interoperability among existing and new blockchain systems. Prototype implementation shows that the proposed mechanism is self-sustaining and has negligible processing and storage impact on distributed ledgers.

关键词： Translation distributed ledger Merging Ecosystems Prototypes Standardization Encoding Blockchains Large-scale systems Interoperability

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Intelligent Log Analysis Technology for distributed Energy Production Management System

Intelligent Log Analysis Technology for Distributed Energy P...

引用

China international Electrical and Energy conference (CIEEC)

作者： Kaiming Qie Yuanyuan Wang Fuliang Lin Ruizheng Zhao Han Yang Science and Technology on Information Systems Engineering Laboratory Beijing Institute of Control and Electronic Technology Beijing China School of Automation Chongqing University Chongqing China

Aiming at the demand of distributed energy production management system for intelligent operation and maintenance, considering the problems in current log analysis method, we propose an intelligent log analysis technology for distributed energy production management system. this technology applies distributed log framework to achieve the collection, storage, analysis and display of various equipment and service logs in the energy production management system. On the one hand, we use log anomaly detection technology to realize the anomaly detection of single node and the generating of log anomaly alarm, On the other hand, we use rule reasoning technology to realize the analysis and tracing of log anomaly alarm. In addition, we combine with practical application, optimize the traditional rule matching algorithm, which improves the fault tolerance of the matching network, and gets better accuracy and efficiency of the algorithm.

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An Intrusion Detection System on Fog Architecture 18

An Intrusion Detection System on Fog Architecture

引用

18th ieee international conference on Mobile Ad hoc and Smart systems (ieee MASS)

作者： Sahi, Mansi Soni, Mahip Auluck, Nitin Indian Inst Technol Dept Comp Sci & Engn Ropar India

ISBN: (纸本)9781665449359

Due to advancements in technology, electrical appliances are now inter-connected. the goal of Internet -of-things (IoT) is to access every appliance or device through the Internet. this is done in order to operate these gadgets from remote locations. the goal is to improve our day-to-day life. However, this technology raises serious privacy and security issues. As IoT devices are resource-constrained, it is impractical to secure them using traditional approaches. Hence, a light-weight Intrusion detection system (IDS) is required. In this work, we implement a machine learning based Network Intrusion Detection (NID) system in a multi-node fog environment using a Raspberry Pi cluster on a local area network. the proposed Pi-IDS system has been evaluated on ADFA-LD datasets. these datasets comprise of new generation system calls for various attacks on different applications. the proposed fog architecture offers significant advantages in terms of latency, energy consumption and cost over traditional cloud or dedicated personal computer systems. the experiments show that we are able to achieve a Recall of 89%in ADFA-LD with the XGBoost model. the proposed system was able to predict intrusion with an inference time 130 ms in comparison to Cloud with 735 ms, with an estimated running cost of 201 INR/month in comparison to the Cloud cost of 2051 INR/month.

关键词： Raspberry Pi ADFA-LD Cluster Machine Learning distributed Edge computing Fog computing Intrusion Detection System

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An Odor Interference Discrimination and Elimination Method Based on Broad Learning System

An Odor Interference Discrimination and Elimination Method B...

引用

6th international conference on Intelligent computing and Signal Processing (ICSP)

作者： Zhiyun He Yan Liu Jiafeng He School of Information Engineering Guangdong University of Technology Guangzhou China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

sensor array in electronic nose has the disadvantage of being highly susceptibility to certain interference, which seriously affects the detection of target gases. As a result, the electronic nose cannot be used when interference exists. therefore, it is urgent to solve the interference problem. In this paper, we propose an odor interference discrimination and interference elimination method based on broad learning system, which train a prediction matrix and an elimination matrix by broad learning system. the method gets rid of the dependence on interference samples in the discrimination training process, and has the advantages of faster training and better elimination. the eliminated response data is more closely matched to the target gas response data without interference than other methods.

关键词： Learning systems Training Gases Accuracy Interference elimination Interference Signal processing Electronic noses Complexity theory sensor arrays

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Enhancing Energy Efficiency and Security in Wireless sensor Networks: A Survey and Proposed Methodology Integrating Prediction Algorithms and Deep Neural Networks

Enhancing Energy Efficiency and Security in Wireless Sensor ...

引用

Cybernetics, Cognition and Machine Learning Applications (ICCCMLA), ieee international conference on

作者： Shaik Shafiuddin Konda Hari Krishna Department of Computer Science and Engineering School of Computing Mohan Babu University Tirupati Andhra Pradesh India

ISBN: (数字)9798331505790

ISBN: (纸本)9798331505806

this research study provides a complete assessment of energy- and trust-aware techniques in IoT-WSNs, emphasizing the significant problems and limits of current methodologies. Traditional methodologies frequently face challenges such as excessive processing overhead, difficulty reaching real-time optimal solutions, and increased delay, especially in large-scale or resource-constrained contexts. To solve these issues, the paper suggests a new approach that combines powerful prediction algorithms, deep neural networks, and strong security frameworks. the process entails initializing exact inputs and simulation settings, modeling advanced prediction algorithms, developing deep neural networks, and constructing resilient sensor nodes, all while implementing extensive security measures. the suggested approach seeks to considerably improve energy efficiency, network lifetime, and security by focusing on mobile sink movement prediction and network operation optimization. this study not only covers existing methodologies, but also shows the promise of the proposed methodology through extensive analysis and preliminary results, demonstrating its ability to overcome the limits of present WSN deployments.

关键词： Surveys Wireless sensor networks Artificial neural networks Predictive models Prediction algorithms Real-time systems Energy efficiency Stability analysis Security Optimization

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Application of Simulated LIDAR Methodology in Autonomous Aerial Platforms

Application of Simulated LIDAR Methodology in Autonomous Aer...

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Mobile computing and Sustainable Informatics (ICMCSI), international conference on

作者： E. Ajitha E. Hephzibai S. Ilakkiya Department of Computer Science and Engineering St. Joseph's Institute of Technology Tamil Nadu India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

the real-time obstacle identification and precise distance calculation is necessary for drone deliveries but the traditional LIDAR sensors are expensive and their weight poses significant challenges. the high financial investment required to procure and integrate LIDAR into drones also adds significant weight to drones, which impacts their performance. this project offers a low-cost substitute for LIDAR sensors in drone applications that require pre-pixel depth estimation. A great deal of testing confirms the effectiveness of depth estimation. the object's distance is yield by a disparity map. this demonstrates how depth information can be accurately determined with the help of stereo vision by using block-matching and semi-global block-matching algorithms. According to our research, integrating pseudo-LIDAR systems offers a viable and affordable alternative to LIDAR sensors for drone applications.

关键词： Laser radar Depth measurement sensor systems and applications Real-time systems Stereo vision Informatics Mobile computing Drones Testing Investment

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