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检索条件"任意字段=5th International Conference on Informational Processing in Sensor Networks"

共 8138 条记录，以下是921-930 订阅

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Cyber Security in Fog Computing Using Blockchain: A Mini Literature Review 5

Cyber Security in Fog Computing Using Blockchain: A Mini Lit...

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5th international conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Alhumam, Norah Arif Alyemni, Noura Saud Rahman, M. M. Hafizur King Faisal Univ Dept Comp Networks & Commun CCSIT Al Hufuf 31982 Al Hassa Saudi Arabia

ISBN: (纸本)9781665456456

Due to its many uses and ability to save and restore data, whether for businesses or individuals, cloud computing has become one of the mainstays in the technology world over the past few years. However, the limitations on speeds and sizes as well as the evolving of the Internet of things made it challenging to rely on the cloud due to the extremely slow data processing. therefore, to store and interpret the massive amount of data rapidly, programmers switched towards a new technology which is fog computing. this mini survey paper will outline fog computing as an integral part of cloud and edge computing for improving security and data protection. A systematic literature review of selected research papers that include findings and algorithms used to enhance security-related problems such as availability, latency, and intrusion detection will be discussed. this mini review paper finds out a state-of-the-art on the cybersecurity issues in fog computing using blockchain.

关键词： Fog Computing Cloud Computing Edge Computing Security Blockchain

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Replica Node Detection in Distributed Wireless sensor networks 5

Replica Node Detection in Distributed Wireless Sensor Networ...

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5th international conference on Trends in Electronics and Informatics, ICOEI 2021

作者： Sujihelen, L. Satyanarayana, M. Senthilsingh, C. Sathyabama Institute of Science and Technology Dept. of Cse Chennai India Shadan College of Engineering and Technology Peerancheru Dept. of Ece Hyderabad India Shadan Women's College of Engineering and Technology Dept. of Ece Hyderabad India

ISBN: (纸本)9781665415712

Security is the important problem in wireless sensor networks. the nodes are deployed in environment without any security measures. One of the important attacks in wireless sensor networks is node replication attack. the node replication attack will behave as an original node and hack the information. the proposed work is for detecting replica node in distributed networks. the drawback of the existing has less detection accuracy when replica node is less. the proposed work improves the detection accuracy when the replica node is less. the proposed work is detected in an efficient with less energy consumption and without any delay. © 2021 IEEE.

关键词： Energy utilization

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Unleashing Agricultural Precision: A Deep Learning Paradigm for Papaya (Carica Papaya L.) Variety Discrimination and Yield Optimization 5th

Unleashing Agricultural Precision: A Deep Learning Paradigm ...

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5th international conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

作者： Ratha, Ashoka Kumar Barpanda, Nalini Kanta Sethy, Prabira Kumar Behera, Santi Kumari Department of Electronics Sambalpur University Odisha Burla768019 India Department of Computer Science and Engineering VSSUT Burla768018 India

ISBN: (纸本)9789819788606

the categorization of papaya fruit varieties is important within the agricultural industry. there is a need for a system that can accurately evaluate the different varieties of papaya fruits to save labor expenses associated with discarding specific types of papaya fruits throughout the packaging and distribution process. the present work introduces a novel approach for the categorization of papaya fruit varieties with the aim of enhancing efficiency and accuracy. the proposed method comprises a series of interconnected steps. Once the data on papaya fruits are collected, they undergo preprocessing techniques, such as color uniformization, image scaling, augmentation, and image labelling. Subsequently, the AlexNet architecture was employed, incorporating 08 layers, comprising 05 conv layers and 03 fully connected layers. Simultaneously, the process of transfer learning and fine-tuning of the convolutional neural network was executed. During the concluding phase, a SoftMax classifier was employed to perform the ultimate classification. Detailed simulations were conducted using self-generated datasets. the proposed model demonstrated the highest classification accuracy of 98.0%. Furthermore, our developed model exhibits computational efficiency with an average processing time of 8 ms to generate the ultimate classification outcome. the obtained results enhance the comprehensibility and reliability of convolutional neural network (CNN) models, thereby offering valuable insights for the prospective utilization of deep learning techniques in agricultural fields. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Sub-network Multi-objective Evolutionary Algorithm for Filter Pruning 5

Sub-network Multi-objective Evolutionary Algorithm for Filte...

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5th international conference on Information Communication and Signal processing, ICICSP 2022

作者： Li, Xuhua Sun, Weize Huang, Lei Chen, Shaowu Shenzhen University Dept. of Electronics and Information Engineering Shenzhen China

ISBN: (纸本)9781665485890

Filter pruning is a common method to achieve model compression and acceleration in deep neural networks (DNNs). Some research regarded filter pruning as a combinatorial optimization problem and thus used evolutionary algorithms (EA) to prune filters of DNNs. However, it is difficult to find a satisfactory compromise solution in a reasonable time due to the complexity of solution space searching. To solve this problem, we first formulate a multi-objective optimization problem based on a sub-network of the full model and propose a Sub-network Multi-objective Evolutionary Algorithm (SMOEA) for filter pruning. By progressively pruning the convolutional layers in groups, SMOEA can obtain a lightweight pruned result with better performance. Experiments on VGG-14 model for CIFAR-10 verify the effectiveness of the proposed SMOEA. Specifically, the accuracy of the pruned model with 16.56% parameters decreases by 0.28% only, which is better than the widely used popular filter pruning criteria. © 2022 IEEE.

关键词： Deep neural networks

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Optimization Coverage Method of Wireless sensor networks for Dynamic Areas 5

Optimization Coverage Method of Wireless Sensor Networks for...

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5th international conference on Artificial Intelligence and Pattern Recognition, AIPR 2022

作者： Huang, Qingdong Wang, Mei Chen, Chen School of Communication and Information Engineering Xi'an University of Posts and Telecommunications China

ISBN: (纸本)9781450396899

the coverage problem of wireless sensor networks (WSNs) for dynamic areas is studied. It is explicitly observed that most of the existing studies focus on static areas. However the areas of interest for many WSNs applications are dynamic, which makes it a challenge to cover the area in real time. therefore, a virtual force-based dynamic coverage optimization method is proposed for the coverage of dynamic areas with arbitrary polygons. the easily accessed received signal strength indication (RSSI) is used to construct the virtual force model based on the rules of leader-following, boundary attraction and collision avoidance. In the virtual force model, the attractive force of the area guides the network nodes to follow and cover the dynamic area, the attractive force of boundary attracts the nodes to cover the area uniformly, and the repulsive force avoids node collisions and reduces network redundancy. In addition, the whale swarm algorithm is introduced to speed up the nodes' search for the optimal positions. It enables the sensor network to perform coverage maintenance, motion following and coverage optimization while ensuring connectivity, and achieves good dynamic area coverage. Simulation results show that the method has higher coverage ratio, stability and effectiveness compared with other methods in the same category. © 2022 ACM.

关键词： sensor nodes

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A Review on Image processing Tecniques for In-Pipe Robots 5th

A Review on Image Processing Tecniques for In-Pipe Robots

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5th international conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2024

作者： Suryawanshi, Shubhangi Chavan, Amol Bhosale, Digvijay G. Mahakal, Shivam Jakate, Govind Kanojiya, Abhay Department of Artificial Intelligence and Data Science Dr. D. Y. Patil Institute of Technology Maharashtra Pune411 018 India Department of Mechatronics Engineering Rajarambapu Institute of Technology Shivaji University RajaramnagarKolhapur Maharashtra 415 414 India Department of Mechanical Engineering Dr. D. Y. Patil Institute of Technology Maharashtra Pune411 018 India Department of Automation and Robotics Dr. D. Y Patil Institute of Technology Maharashtra Pune411 018 India

ISBN: (纸本)9789819788644

Pipelines are vital infrastructure for the transportation of water, sewage, oil, and gas because they offer a better safety option and fit into the minimum environmental hazardous than other modes. But pipelines are aging and getting damaged all the time, which can lead to significant loss of resources and contamination of the environment. Regular maintenance and inspections are necessary for pipelines to operate efficiently and prevent overspending. this paper reviews the core techniques used in each of the four missions—localization, mapping, navigation, and inspection—that these robots have completed. Additionally, because image processing has become a widely used and crucial strategy for completing all of the aforementioned missions, we made the decision to review the thorough classification of techniques for image processing in a separate section. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Navigation

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SPML 2022 - Proceedings of 2022 5th international conference on Signal processing and Machine Learning

SPML 2022 - Proceedings of 2022 5th International Conference...

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5th international conference on Signal processing and Machine Learning, SPML 2022

ISBN: (纸本)9781450396912

the proceedings contain 43 papers. the topics discussed include: performance comparison of seven pretrained models on a text classification task;decorrelation proportionate normalized least mean M-estimate algorithm with variable step-size;cluster analysis for cancer omics data using neural network with data augmentation;sentiment analysis for e-commerce reviews based on deep learning hybrid model;aspect-sited hybrid graph neural networks for sentiment classification;handling concept drift in financial time series data: recurrent Xavier on-line sequential extreme learning machine;an investigation of feature difference between child and adult voices using line spectral pairs;wideband beamspace robust capon beamformer;application of adaptive sub-band filters on active noise control;a unifying framework for blind source separation algorithms based on generalized eigen-value decomposition;research on visual recognition technology of damaged navigation mark based on improved Efficientnet;and human activity recognition based on convolutional neural network via smart-phone sensors.

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Malicious Node Detection in Wireless sensor networks: Comparative Study

Malicious Node Detection in Wireless Sensor Networks: Compar...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Lara Darwish Mohammad Nassr Fadi Ghosna Habib M. Fardoun Daria K. Voronkova Mohammad Anbar Dept. of Telecommunication Technology Engineering University of Tartous Tartous Syria Research Center Canadian University Dubai Dubai United Arab Emirates Bauman Moscow State Technical University Moscow Russia

Wireless sensor networks have become so widespread where they have become an important part of our daily lives. Wireless sensor networks have characteristics that distinguish them from other communication systems. However, these networks suffer from security gaps and threats such as presence of malicious nodes. the main objective of this work is detecting the presence of such nodes in sensor networks. Detecting malicious nodes helps in reducing power consumption, delay, and packet drop rate. this in turn reflects positively on the performance of these networks. throughput, power consumption, and delay have been studied for the purpose of detecting the presence of the malicious node in a sensor network. Empirical study has been performed in this work using NS-2 simulator.

关键词： Wireless sensor networks Power engineering Power demand Network security throughput Delays Reliability

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Proceedings of the 2022 5th international conference on Advanced Systems and Emergent Technologies, IC_ASET 2022

Proceedings of the 2022 5th International Conference on Adva...

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5th international conference on Advanced Systems and Emergent Technologies, IC_ASET 2022

ISBN: (纸本)9781665427357

the proceedings contain 92 papers. the topics discussed include: analog approximation of functions using generalized polynomials;secure images transmission using a three-dimensional s-box-based encryption algorithm;development of a wind turbine digital-twin for failure prognosis: first results;an efficient design of 1:2 demultiplexer based on QCA technology;automatic software engineering position resume screening using natural language processing, word matching, character positioning, and regex;modeling of three-tank hybrid system using mixed logical dynamical formalism;optimal configurations of a photovoltaic-diesel electrical production system with electrochemical and inertial storage for an isolated agricultural site electrification;optimal configurations of a photovoltaic-diesel electrical production system with electrochemical and inertial storage for an isolated agricultural site electrification;sun sensor design for full field of view coverage;and sliding mode observer for fractional order nonlinear dynamical systems.

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Smart Home Voice and Gesture Control Integration using Bluetooth and Gesture sensor

Smart Home Voice and Gesture Control Integration using Bluet...

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Image processing and Capsule networks (ICIPCN), international conference on

作者： Anwaraly Yasmine Begum G Chandu Chowdary R M Umesh Shaik Afroz S. Sai Madhur Electronics and Communication Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati India Electronics and Instrumentation Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Tirupati India

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

Smart technologies have revolutionized home automation, enhancing the way people interact with the environment. this study introduces an innovative home automation system that combines voice and gesture recognition technologies for seamless control of household appliances. the proposed system integrates various hardware components, including a gesture sensor, Bluetooth module, Arduino, LCD display, and a 4-channel relay module to manage devices such as fans, lights, plugs, and AC/TV units. Voice commands and hand gestures are processed via Arduino, activating or deactivating appliances through relay modules. the Bluetooth module allows remote operation via smartphones, enhancing convenience and accessibility. the LCD display provides real-time feedback and status updates, improving user experience with clear and concise information. this smart and user-friendly system offers an efficient solution for managing home environments, leveraging advanced recognition technologies and intelligent hardware integration.

关键词： Home appliances Fans Bluetooth Image recognition Automation Speech recognition Liquid crystal displays

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