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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821-830 订阅

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Deep Neural networks for Transmission Impairment Mitigation in Long-Reach 5G Access networks 5

Deep Neural Networks for Transmission Impairment Mitigation ...

引用

5th international conference on Signal processing and Information Security, ICSPIS 2022

作者： Maniak, Tomasz Iqbal, Rahat Vujicic, Zoran Karyotis, Charalampos Passas, Nikos Doctor, Faiyaz Interactive Coventry Coventry United Kingdom University of Dubai College of Engineering and IT Dubai United Arab Emirates Campus Universitario de Santiago Instituto de Telecomunicacoes Aveiro Portugal University of Athens Department of Informatics and Telecommunications Athens Greece University of Essex School of Science and Electronic Engineering Colchester United Kingdom

ISBN: (纸本)9781665492652

the mitigation of transmission impairments in optical communication systems requires implementation of digital signal processing that can easily adapt to changing conditions and work on continuous streams of data. In this paper, the application of continual learning in deep neural networks for transmission impairments in long haul transmission systems is considered. this work investigates the novel use of continual learning to overcome the problem of catastrophic forgetting and remembrance in deep neural networks that can be used for dispersion and nonlinearity mitigation in long-haul transmission systems. We perform comparisons between state-of-the-art methods such as iCaRL, DGR, EWC, XdG and traditional DNNs implementations typically used in optical networks. We demonstrate improvements in training accuracy towards signal recovery, and increased flexibility for DNN equalization applications. the results show that the method can be successfully used for fiber lengths ranging from less than 1km to 250km and over with no need to retrain the network from scratch for each fibre length. the introduction of continual learning enables training DNNs on a continuous stream of data with no loss of prior knowledge. © 2022 IEEE.

关键词： Fiber optic networks

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Investigations on IoT with SWIPT-NOMA Combination in Wireless sensor networks 5

Investigations on IoT with SWIPT-NOMA Combination in Wireles...

引用

5th international conference on Inventive Computation Technologies (ICICT)

作者： Sixtus, Reginald Jude J. Muthu, Tamilarasi Puducheny Technol Univ Dept Elect & Commun Engn Pondicherry India

ISBN: (数字)9781665408370

ISBN: (纸本)9781665408387;9781665408370

the IoT is defined as the interconnection of various devices and sensors that are connected to establish communication between them with internet as communicating medium. Every device or sensor is employed to perform a specific task. the prime advantage of IoT is that it facilitates connecting, con-trolling, and monitoring the network which makes it efficient and reliable. Most of the sensors employed are battery powered and are prone to battery depletion which leads to termination in connectivity. Energy harvesting is seen as a prominent solution which facilitates RF signal to be made use as power source thus ensuring the sensors to be independent of external power source. the emerging communication network not only focuses on being energy efficient but also concentrates on utilizing the available resources to the fullest. the non-orthogonal multiple access (NOMA) ,ensures fairness by fairly splitting the available spectral resources irrespective of domain. this paper, describes the massive contribution of the SWIPT-NOMA combination which makes IOT network efficient in terms of energy and spectrum.

关键词： energy harvesting fairness Radio frequency signal Simultaneous Wireless Information and Power Transfer

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A Comparative Approach on Enhancing Lifetime of Wireless sensor networks 5

A Comparative Approach on Enhancing Lifetime of Wireless Sen...

引用

5th international conference on Contemporary Computing and Informatics, IC3I 2022

作者： Sultana, Shakira Bordoloi, Dibyhash Singh, Charanjeet Srivastava, Arun Pratap N., thiyagarajan N., Chinthamu Loyola Academy Department of Electronics and Communication Technology Telangana Alwal India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Deenbandhu Chhotu Ram University of Science and Technology Electronics and Communication Department Murthal India Lloyd Institute of Engineering and Technology Department of CSE Uttar Pradesh Greater Noida India Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamilnadu Coimbatore India CTO Candidate DallasTX United States

ISBN: (纸本)9798350398267

Wireless sensor networks are crucial elements that are employed to assess the environment, in addition, to utilizing the sensor information for additional computing including climate forecast, human medical-related forecasts, transportation management, and so on. Because of the significant operational expense of the system, the sensor network of the system is anticipated to run independently in the area for an extended length of time in these circumstances. As a consequence of this, the exhaustion of single sensor nodes may have an impact on the network's operations. As a result, in an attempt to extend the network lifespan, an energy-efficient alternative must be proposed. Wireless sensor network technologies have emerged in past decades as an evolving innovation for monitoring & recording ambient physical variables utilizing many sensors. For the organizing of gathered data, centralized sites are required. Multi-hop communication is used to transfer data to the sink nodes communications are needed. To eliminate undesired transmissions, the most well-known WSN approach known as information aggregating is utilized. It must gather information from various sensors & transmit it to the ground station. the procedure of gathering information is repeated many times to maximize information effectiveness. this technology contributes to lower transmitting information power costs. © 2022 IEEE.

关键词： sensor nodes

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UWSN: A Novel Artificial Intelligence (AI) enabled Scheme to Improve Security and Energy Efficiency over Underwater Wireless sensor networks 5

UWSN: A Novel Artificial Intelligence (AI) enabled Scheme to...

引用

5th IEEE international conference on Advances in Electrical, Computing, Communication and Sustainable Technologies, ICAECT 2025

作者： Bharathi, P. Shyamala Reddy, M. Jaya Bharatha Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350356236

Underwater Wireless sensor networks (UWSNs) are critical for monitoring and managing marine environments, supporting applications in environmental science, defense, and resource exploration. this study presents an innovative AIenabled scheme for improving security and energy efficiency in Underwater Wireless sensor networks (UWSNs). By incorporating artificial intelligence, the proposed AI-UWSN protocol dynamically adapts to environmental and network conditions, enhancing key performance metrics like energy consumption, packet delivery ratio (PDR), latency, and network lifetime. the AI-UWSN achieved an average energy consumption of 146J, which is 24% lower than conventional protocols, extending the network lifetime to 1067 hours, compared to 722 hours in existing methods. Additionally, the protocol's intelligent routing increased PDR to 89%, significantly reducing data loss, and maintained an average latency of 108ms, 15% lower than alternative protocols. these improvements result from AI-based routing and clustering strategies, which optimize data aggregation and power usage, extending the network's functionality even in high-density, high-traffic environments. © 2025 IEEE.

关键词： Wireless sensor networks

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Machine Learning on Web: Skin Lesion Classification using CNN 5

Machine Learning on Web: Skin Lesion Classification using CN...

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5th international conference on Inventive Computation Technologies (ICICT)

作者： Kumar, Senthil R. Singh, Amarjeet Srinath, Sparsha Arasu, Vishal thomas, Nimal Kurien New Horizon Coll Engn Comp Sci & Engn Dept Bangalore Karnataka India

ISBN: (数字)9781665408370

ISBN: (纸本)9781665408387;9781665408370

this paper summarizes the different methods that can be employed to perform any type of disease classification using a Web Application. the modus operandi involves the use of Convolutional Neural networks to diagnose and identify the skin lesion with the help of ISIC dataset that accommodates 2747 training images. the model provides an accuracy of 90% while classifying the training dataset as one of the following categories- melanoma, nevus, seborrheic keratosis and benign. the Flask Web Framework is employed to create the user interface and embed the pre trained model into the backend. the skin cancer patient can simply upload the skin image and receive an immediate classification among the abovementioned classes.

关键词： Deep Learning Models Tensorflow Image processing Flask Web Framework Keras Convolutional Neural networks

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Research on Robustness of Network Security Vulnerability Detection Algorithm based on Recurrent Bayesian networks 5

Research on Robustness of Network Security Vulnerability Det...

引用

5th international conference on Inventive Computation Technologies (ICICT)

作者： He, Jian Hue, Yan Luoding Polytech Dept Informat Engn Luoding 527200 Peoples R China Luoding Open Univ Dept Continuing Educ Luoding 527200 Peoples R China

ISBN: (数字)9781665408370

ISBN: (纸本)9781665408387;9781665408370

Aiming at the problems of low detection accuracy and poor robustness of the existing zero-speed detection methods, an effective gait cycle segmentation method is adopted and a Bayesian network model based on inertial sensor measurements and kinematics knowledge is introduced to infer the zero-speed interval;the method can effectively reduce the ambiguity of the zero velocity (ZV) boundary. Support vector machine has the advantages of versatility, simple calculation, high operation efficiency and perfect theory. It is a relatively mature and efficient algorithm in the current network security situation algorithm. And a looped Bayesian network model for probabilistic safety assessment of simple feedback control systems is established.

关键词： Robustness Network Security Vulnerability Detection - Recurrent Bayesian networks

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A Factor Graph-Based Attitude Determination Approach for Microsatellite with Star sensor and Gyros 5th

A Factor Graph-Based Attitude Determination Approach for Mic...

引用

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

作者： Wu, Xiwei Ran, Dechao Cao, Lu Xiao, Bing Northwestern Polytech Univ Sch Automat Xian 710072 Peoples R China Natl Innovat Inst Def Technol Beijing 100071 Peoples R China

ISBN: (纸本)9783030945510;9783030945503

Attitude determination is an important part of microsatellite attitude control system. Its determination accuracy directly affects microsatellite's attitude control performance. Hence, a novel attitude determination approach is presented in this work for microsatellites with star sensor and gyros fixed. the factor graph representing the probabilistic graphical model as a bipartite graph is applied to solve the attitude estimation problem. this allows multi-rate, asynchronous, and possible delayed measurements to be incorporated in a natural way. An incremental smoothing algorithm is then proposed to achieve optimal estimation. Simulation results are finally presented to verify that the proposed approach can significantly improve the attitude determination accuracy.

关键词： Microsatellite Attitude determination Factor graph Smooth optimization Star sensor Gyro

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Tensor Completion-Based Data Imputation Framework for IoT-Based Underwater sensor Network 1

引用

4th international conference on Communication and Intelligent Systems, ICCIS 2022

作者： Gupta, Govind P. Rajak, Prince Department of Information Technology National Institute of Technology Raipur India

ISBN: (数字)9789819923229

ISBN: (纸本)9789819923212

In the IoT-based Underwater sensor Network (IoT-USN), a set of underwater sensor nodes are deployed for monitoring of the marine ecosystems. these deployed nodes perform sensing tasks and periodically send the observations to the base station for additional data analytic and processing. In the IoT data analytics over the marine data, it is observed that many observations collected at the base station are missing due to malfunctions of sensor nodes, packet loss during wireless communication. Data imputation of the missing data entries for efficient data analytics is a very fundamental research issue in the real-time monitoring of the marine ecosystems. thus, to impute the missing data problem, a data imputation framework using tensor completion techniques is proposed in this paper for an IoT-based Underwater sensor Network system. In the proposed framework, three well-known tensor completion algorithms such as Bayesian Gaussian CP decomposition (BGCP), Bayesian Augmented Tensor Factorization (BATF), and HaLRTC are used for data imputation. In the proposed framework, a 3D tensor of shape 19 × 720 × 5 is used for employing the data imputation technique. Result evaluation of the proposed framework is done using real-time marine ecosystem dataset in terms of MAPE and RMSE. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data Analytics

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Research on Intelligent Cost Accounting Solutions for Public Hospitals Based on Neural networks 24

Research on Intelligent Cost Accounting Solutions for Public...

引用

2024 5th international conference on Big Data Economy and Information Management, BDEIM 2024

作者： Jing, Ling Wang, Liying School of Accountancy Guangzhou Xinhua University Guangdong Guangzhou China School of Economics and Trade Guangzhou Xinhua University Guangdong Guangzhou China

ISBN: (纸本)9798400711862

An intelligent cost accounting system based on artificial neural network is proposed to address the problems faced by cost accounting in public hospitals in China, such as the difficulty of high-dimensional data processing and the low accuracy of accounting. On this basis, a cost apportionment and prediction method based on multilayer forward neural network is proposed, and standardised interface and visualisation techniques are used to improve accounting efficiency and system stability. © 2024 Copyright held by the owner/author(s).

关键词： Intelligent cost accounting Neural networks Precision management Public hospitals

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Research on Information Fusion Algorithm for Wireless sensor Isomorphic Network

Research on Information Fusion Algorithm for Wireless Sensor...

引用

sensors and Information Technology (ICSI), international conference on

作者： Dongsheng Li Bing Ma Jiayi Du Xiaotan Liu Fu Chen Taijiang Zhang Army Infantry College Shijiazhuang China School of Information and Communications National Defense University of China Wuhan China Hainan Hospital of Chinese PLA General Hospital Sanya China 31207 Gangzhou China

ISBN: (数字)9798331542887

ISBN: (纸本)9798331542894

Information fusion is an effective way to solve the energy and communication bandwidth limitations of wireless sensor networks. Based on the characteristics of homogeneous wireless sensor networks, algorithm research is conducted to distinguish between routing selection and related information fusion steps. this article mainly studies routing selection. Based on the analysis of the advantages and disadvantages of the classic LEACH algorithm, an improved algorithm is proposed to extend the survival time and reduce energy consumption indicators, laying the foundation for information fusion in wireless sensor homogeneous networks

关键词： Wireless communication Wireless sensor networks Energy consumption Clustering algorithms Bandwidth Routing Energy efficiency Data communication Information technology

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