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

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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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Improving Energy Efficiency through Green Cloud Computing in IoT networks 5

Improving Energy Efficiency through Green Cloud Computing in...

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5th IEEE international conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Shekhar, Aishwarya Aleem, Abdul Scse Galgotias University Greater Noida India

ISBN: (纸本)9798350383522

Improving the energy efficiency by using green cloud computing cover through an IoT network which involves optimizing the resource utilization and implementing all the smart technologies. By integrating the sensors and the actuators, the IoT network can dynamically adjust the power consumption based on demand, which leads to a more sustainable and efficient type of cloud infrastructure. Additionally, using the machine learning algorithms can forecast workload patterns, allowing for energy management. these new research contribute to a greener cloud environment, reducing both the operational costs and environmental impact. the integration of Renewable Energy in Cloud Computing explore ways to integrate renewable energy sources into cloud data centers, ensuring a more sustainable, recyclable and eco-friendly cloud infrastructure. Dynamic Resource Allocation in Cloud Computing with IoT investigate how IoT devices can assist in real-time resource allocation, optimizing energy usage and enhancing overall efficiency in cloud environments. Carbon Footprint Reduction through Cloud-Based IoT Solutions discusses strategies to reduce the footprint of carbon coming from IoT devices and cloud services, promoting environmentally conscious practices in the digital realm. the present study aims to investigate the potential synergies between cloud computing and smart grid technologies in order to establish a more integrated and energy-efficient environment. By processing the data closer to the source and limiting the need for lengthy data transfers, edge computing can help reduce the energy usage of cloud services. this is explored in Edge Computing for Green Clouds. Blockchain for Sustainable Cloud Computing examines how block chain technology might improve cloud services' accountability and transparency while encouraging environmentally friendly behavior. Low-Power IoT Devices for Cloud Connectivity explores the creation and application of low-power IoT devices that promote a gree

关键词： Green Cloud Computing Green IoT Green Servers IoT networks

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Tone Analysis of Regional Articles in English-Language Newspapers Based on Recurrent Neural Network Bi-LSTM 5

Tone Analysis of Regional Articles in English-Language Newsp...

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5th IEEE international conference on Advanced Information and Communication Technologies, AICT 2023

作者： Vysotska, Victoria Voloshyn, Serhii Markiv, Oksana Brodyak, Oksana Sokulska, Nataliia Panasyuk, Valentyna Lviv Polytechnic National University Lviv Ukraine Osnabriick University Osnabrück Germany Information Systems and Networks Lviv Polytechnic National University Lviv Ukraine Lviv Polytechnic National University Information Systems and Networks Department Lviv Ukraine Lviv Polytechnic National University Mathematics Department Lviv Ukraine Hetman Petro Sahaidachnyi National Army Academy Department of Engineering Mechancs Weapons and Equipment of Military Engineering Forces Lviv Ukraine West Ukrainian National University Accounting and Taxation Department Ternopil Ukraine

ISBN: (纸本)9798350372571

this publication dwells upon the study of the human language processing techniques use, namely sentimental analysis to identify attitudes in English-language newspapers articles. General information about the development of human language has been presented. A brief description of analogues and the use of machine learning to carry out sentimental analysis of the text have been described. the section of analysis processes gives information about the sequence of program processes and the tools used. the statistics of neural network tasks with different functions of activators has been presented. the publication provides a control example of a demo version of the product, shows the main scenario of use. the classifier is needed to classify the vector that corresponds to the entered text. Each application in the program corresponds to one classifier, which is presented as a neural network model. the neural network has the following parameters: an embedding layer (with an input dimension of 541830, which corresponds to the size of the dictionary, an output vector with a dimension of 100, the length of the input data - 40) and a Bi-LSTM layer (intended to use a recursive Bi-LSTM neural network with the number of units 128). there is also the output fully connected 2-dimension and activator function - softmax, the Adam feedback function and the categorical cross entropy loss function and the accuracy metric. the maximum and minimum values for precision and loss have been found for the functions softmax (0.9117;0.2138), relu (0.5002;0.6134) and sigmoid (0.9681;0.078) according to the training sample. the maximum accuracy values for the softmax, relu and sigmoid functions have been also found according to the test selection (0.8232;0.4993;0.8236). It is highlighted that the accuracy of the softmax, sigmoid function increases on the training sample, whereas the accuracy of the sigmoid function is the greatest, and the loss is the least. the accuracy of the softmax, sigmoid fu

关键词： Sentiment analysis

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thermal Zero Drift Compensation of Pressure sensor Based on Data Mining and BP Neural Network 5th

Thermal Zero Drift Compensation of Pressure Sensor Based on ...

引用

5th EAI international conference on Advanced Hybrid Information processing (ADHIP)

作者： Li, Ya-ping Zhao, Dan Beijing Polytech Coll Mechatron Engn Beijing 100176 Peoples R China

ISBN: (纸本)9783030945510;9783030945503

Due to the poor compensation accuracy, the traditional compensation algorithm for thermal zero shift of pressure sensor results in large error of pressure measurement. therefore, this paper proposes a pressure sensor thermal zero drift compensation algorithm based on data mining and BP neural network. Combined with the data mining process, the characteristics of the thermal zero drift of the pressure sensor are analyzed, and the hysteresis and nonlinear characteristic curve of the pressure sensor is obtained to prepare for the compensation of the thermal zero drift. then BP neural network is introduced to determine the parameter update mode, which is effectively combined with artificial fish swarm algorithm, and the compensation of pressure sensor thermal zero shift is realized by implementing the thermal zero shift compensation algorithm of pressure sensor. the experimental results show that the pressure measurement error range of the algorithm in this paper is 0.30 N-1.45 N. Compared with the three existing algorithms, the pressure measurement error of the algorithm in this paper is smaller, which indirectly shows that the algorithm in this paper has a higher thermal zero drift compensation accuracy, which fully shows that the algorithm in this paper compensates better performance.

关键词： Data mining BP neural network Pressure sensor drift compensation Artificial fish swarm algorithm

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Industrial Building Vibration Detection Using Wireless sensor Network

Industrial Building Vibration Detection Using Wireless Senso...

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Recent Trends in Computer Science and Technology (ICRTCST), international conference on

作者： Sushanta Mahanty Rakesh Kumar Akash Sharma Madhu Kumari Prity Kumari Puja Kumari DECE RVSCET Jamshedpur Jharkhand India DEEE RVSCET Jamshedpur Jharkhand India

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

this paper focuses on the structural health monitoring (SHM) of worldwide modern industrial architecture. the vibration monitoring is one of the challenging issues among the other parameters of the structural deformation. the real-time monitoring incorporated with advanced safety features is proposed in this paper. Microelectro mechanical system (MEMS) based sensors and controllers are utilized for the dynamic data collection and analysis. Internet of things (IoT) and wireless sensor networks (WSN) are accountable for interfaces with the end users.

关键词： Vibrations Micromechanical devices Wireless sensor networks Data visualization Real-time systems sensor systems Maintenance

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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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Leveraging AI in Prevention and Protection of Women Against Cybercrime in India: A Paradigm Shift of Criminal Law in the Making 5th

Leveraging AI in Prevention and Protection of Women Against ...

引用

5th international Ethical Hacking conference, eHaCON 2024

作者： Dey, Alice Dey, Sadhan Kumar IEM’s International Institute of Juridical Sciences University of Engineering and Management Kolkata Kolkata700160 India Department of ESM RCC Institute of Information Technology Kolkata700015 India

ISBN: (纸本)9789819784561

Innovative strategies are required for the efficient prevention and defense of legal rights considering the serious problems that the growth of cybercrime has presented to established legal systems in recent years. the paper additionally explores how India's criminal law is evolving due to technological developments in artificial intelligence (AI), with an emphasis on preventing cybercrime and strengthening the laws that protect women's rights. India is among the digital economies that growing at the fastest pace, that necessitates to fortify its legal defenses against cyberattacks promptly. the expansive presence of technology inclusive of its uses and misuses poses a set of different challenges both for international and National legal frameworks to combat them. In this respect, technologies powered by AI provide promising substitutes by giving legal domain the state-of-the-art tools for threat detection, evidence processing, and pro-active crime prevention. With the use of AI-enabled technologies, enormous volumes of data from various sources—such as social media, online forums, and digital communication channels—would be analyzed to look for trends that can point to cybercrimes directed at women according to NCRB Report. thus, to tackle cyber dangers and defend the rights of women in India, this abstract idea calls for the creation of progressive legislation that integrates AI technologies, data privacy measures, and gender-sensitive policies. In conclusion, a paradigm shifts in the battle against cybercrime and the defense of women's legal rights in India is represented by the incorporation of AI into the legal sphere. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

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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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One-Bit Source Number Detection via Neural Network 5

One-Bit Source Number Detection via Neural Network

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

作者： Chen, Mingyang Xiao, Yu-Hang Li, Qiang Feng, Lifang Rihan, Mohamed Guo, Nannan College of Electronics and Information Engineering Shenzhen University Shenzhen China Menoufia University Faculty of Electronic Engineering Menoufia Menouf Egypt Beijing Institute of Control and Electronic Technology Beijing China

ISBN: (纸本)9781665485890

Accurate source number detection with one-bit quantized data is of considerable interest in array signal processing, as one-bit quantization offers low cost and low complexity in practical systems. Conventional model-driven methods, e.g., Akaikes information criterion and minimum description length, suffer from severe performance degradation when one-bit quantization is implemented with only the sign information of signal available. In this paper, the well-known Arcsine Law is explored to recover a normalized covariance matrix, and then a model-aided neural network is established to estimate the source number. Specially, two eigenvalues-based networks, an eigenvalues-based regression neural network (ERNN) and an eigenvalues-based classification neural network (ECNN), are trained, while considering part of the eigenvalues of normalized covariance matrix as input data and source number as the corresponding output label of the neural network, respectively, for source number detection. Experimental results show that the proposed method outperforms the state-of-the-art approaches in terms of accuracy. © 2022 IEEE.

关键词： 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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