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5th ieee international conference on Flexible and Printable sensors and systems, FLEPS 2023

作者： Lee, Mugeun Kim, Hwajoong Kim, Jinho Jeong, Minji Lee, Jaehong Daegu Gyeongbuk Institute of Science and Technology Department of Robotics and Mechatronics Engineering Daegu Korea Republic of

ISBN: (纸本)9781665457330

Various strain sensors have been developed due to their capability to monitor a piece of basic physiological information. However, a lot of existing strain sensor is based on planar soft sensors, which have a few critical challenges such as structural mismatch and stable fixation on the target organ. Here, we present a 1-dimensional and biocompatible capacitive fiber strain sensor. the fiber strain sensor comprises a conductive fiber electrode based on Au, a representative biocompatible material. the structure of the fiber strain sensor is a double helix. the sensor shows high sensitivity of 9.8 and high stability. © 2023 ieee.

关键词： Biocompatibility

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Energy Efficient Cluster-Based Routing Protocol for WSN Using Nature Inspired Algorithm

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WIRELESS PERSONAL COMMUNICATIONS 2023年第4期130卷 2407-2440页

作者： Mishra, Rashmi Yadav, Rajesh K. K. Delhi Technol Univ Delhi India

WSN consist of tiny sensors that are distributed over the entire network and have the capability of sensing the data, processing it, and conveying it from one node to another. the purpose of the study is to minimize the power utilization per round and elevate the network lifespan. In the present case, nature-inspired mechanisms are used to minimize the power utilization of the network. In the proposed study, the Butterfly Optimization Algorithm (BOA) is used to choose the optimal quantity of cluster heads from the dense nodes (available nodes). the parameters to be considered for the choice of the cluster head are: the remaining power of the node;distance from the other nodes in the network;distance from the base station;node centrality;and node degree. the particle swarm optimization (PSO) is used to form the cluster head by choosing certain parameters, such as distance from the cluster head and the BS. the path is chosen by means of the Ant Colony Optimization (ACO) Mechanism. the route is optimized by the distance, node degree, and the chosen remaining power. the inclusive performance of the projected protocol is measured in terms of stability period, quantity of active nodes, data acknowledged by the base station, and overall power utilization of the network. the results of the put redirect methodology are correlated with the extant mechanisms such as LEACH, DEEC, DDEEC, and EDEEC (Khan et al. in World Appl Sci J, 2013;Arora and Singh in Soft Comput 23:715-734, 2019;Saini and Sharma in 2010 First international conference on parallel, distributed and grid computing (PDGC 2010), 2010;Elbhiri et al. in 2010 5th international symposium on I/V communications and mobile network, 2010) and correlated with the swarm mechanisms such as CRHS, BERA, FUCHAR, ALOC, CPSO, and FLION. this review will help investigators discover the applications in this arena.

关键词： Wireless sensor networks Energy efficiency throughput Delay Nature inspired algorithm

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Static and Dynamic Distribution Network Reconfiguration with the Integration of Renewable Energy Sources 5

Static and Dynamic Distribution Network Reconfiguration with...

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5th ieee international conference on Emerging Trends in Electrical, Electronic and Communications Engineering, ELECOM 2024

作者： Ramsami, Pamela King, Robert T. F. Ah University of Mauritius Department of Electrical and Electronic Engineering Réduit Mauritius

ISBN: (纸本)9798331532475

To satisfy the growing energy demand, renewable distributed generation units are being widely incorporated to the power system. Several optimisation studies have been performed to find the most appropriate size and placement of these sources using a fixed distribution network structure. However, the results produced may work for only one network configuration while producing unsatisfactory results for other probable network structures. therefore, this paper explores the optimisation of the renewable energy sources namely photovoltaic systems and wind turbines along with distribution network reconfiguration. It investigates on both static and dynamic reconfiguration. For the static reconfiguration, three optimisation algorithms namely non-dominated sorting genetic algorithm II, strength pareto evolutionary algorithm 2 and multi-objective evolutionary algorithm based on decomposition were utilised in the ieee-123 Node Test Feeder System. Artificial neural network, group method of data handling and adaptive network based fuzzy inference system models were adopted to predict the load demand one-day ahead for the implementation of dynamic network reconfiguration. the load curve was then partitioned over 24-hour intervals to perform static reconfiguration on an hourly basis. the simulations revealed that the incorporation of renewable distributed generation units along with the change in the network configuration helps to reduce the active power loss. It was found that dynamic reconfiguration reduces the energy loss by almost 60 % while static reconfiguration results in only a slight reduction in the energy loss. © 2024 ieee.

关键词： distributed energy

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A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel methods 5

A Privacy-Preserving Framework for Collaborative Machine Lea...

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5th ieee international conference on Trust, Privacy and Security in Intelligent systems and Applications (TPS-ISA)

作者： Hannemann, Anika Uenal, Ali Burak Swaminathan, Arjhun Buchmann, Erik Akguen, Mete Univ Leipzig Ctr Scalable Data Analyt & Artificial Intelligenc Dept Comp Sci Dresden Germany Univ Tubingen Med Data Privacy & Privacy Preserving Machine Lea Tubingen Germany Univ Tubingen Inst Bioinformat & Med Informat IBMI Tubingen Germany

ISBN: (纸本)9798350323856

It is challenging to implement Kernel methods, if the data sources are distributed and cannot be joined at a trusted third party for privacy reasons. It is even more challenging, if the use case rules out privacy-preserving approaches that introduce noise or entail significant computational overhead. An example for such a use case is machine learning on clinical data. To realize exact and efficient privacy preserving computation of kernel methods, we propose FLAKE, a Framework for Learning with Anonymized KErnels on horizontally distributed data. With our method, the data sources mask their data so that a Gram matrix can be computed without compromising privacy or utility. the Gram matrix allows to calculate many kernel matrices, which can be used to train kernel-based machine learning algorithms such as Support Vector Machines. We prove that our framework prevents an adversary from learning the input data or the number of input features under a semi-honest threat model. the conducted experiments on clinical, genomic, and image data provide confirmation that our approach is applicable across a wide range of settings. Additionally, our method outperforms comparable approaches in both computational efficiency and accuracy. thus, FLAKE is a lightweight, applicable approach suitable for various use cases.

关键词： Privacy Kernel-based Machine Learning distributed Learning

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Full Link Pressure Testing System for Car-Hailing Software System 5

Full Link Pressure Testing System for Car-Hailing Software S...

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5th international conference on Frontiers Technology of Information and Computer, ICFTIC 2023

作者： Du, Wei Jiao, Shupeng Zhang, Wenqi Fang, Tiesuo Didi Infinite Technology Development Co. LTD. Beijing China

ISBN: (纸本)9798350309034

the Car-hailing software system faces the challenge of peak traffic before holidays. To address such challenges, it is crucial to conduct capacity planning for the various service systems that the Car-hailing software system relies on. In this study, we investigate the design architecture of the Car-hailing software system and the operational logic of the Car-hailing business. Based on a simulation of real Car-hailing business scenarios, we propose a comprehensive pressure testing system. this system is designed for the production environment of the system under test, adopting a distributed architecture with high concurrency and availability. It is capable of meeting the capacity planning needs of large-scale Car-hailing software systems. © 2023 ieee.

关键词： distributed architecture high availability high concurrency peak traffic pressure testing system production environment

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Dual-Hop Robust distributed Collaborative Beamforming Over Nominally Rectangular WSNs in Slightly to Moderately Scattered Environments 19

Dual-Hop Robust Distributed Collaborative Beamforming Over N...

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19th ieee international Wireless Communications and Mobile computing (ieee IWCMC)

作者： Ben Smida, Oussama Affes, Sofiene Univ Qubec INRS EMT Montreal PQ H5A 1K6 Canada

ISBN: (纸本)9798350333398

We propose a new distributed collaborative beam-forming (DCB) solution that is robust (i.e., RDCB) against major channel estimation impairments over dual-hop transmissions through a wireless sensor network (WSN) of K nodes with a nominally deterministic geometry, presumably rectangular (or a fortiori square). the source S first sends its signal to the WSN. then, each node forwards its received signal to the destination D after multiplying it by a properly selected beamforming weight. the latter aims to minimize the received noise power while maintaining the desired one equal to unity at the destination D. these weights depend on some channel state information (CSI) parameters. Hence, they have to be estimated locally at each node or fed back to it;resulting in either case in channel parameter estimation or feedback errors that could severely hinder DCB performance. Due to lack of space, we only account here for nodes location placement errors which would always amount to some additional phase error. Accounting for the massive connectivity characterizing new 5G and future 5G+/6G wireless technologies and the Internet of things (IoT), we develop alternative RDCB solutions that properly adapt both to monochromatic [i.e., line-of-sight (LoS)] and bichromatic (i.e., slightly to moderately scattered) propagation scenarios over the first hop while always assuming a LoS link over the second;referred to hereafter as MM-RDCB and BM-RDCB, respectively. We do so by exploiting i) very efficient asymptotic approximations at large numbers K of the WSN nodes and ii) the nominal geometric symmetries of their deterministic (rectangular or square) grid shapes. Furthermore, our new MM-RDCB and BM-RDCB solutions are distributed since their weights can be locally computed at every terminal, thereby dramatically improving both spectral and power efficiencies of the WSN. Simulation results show considerable gains and robustness of the proposed techniques in terms of achieved signal-to-nois

关键词： collaborative beamforming (CB) distributed CB (DCB) robust DCB (RDCB) wireless sensor network (WSN) deterministic WSN positions square and rectangular grids low to moderate angular spread channel mismatch nodes location placement errors synchronization localization direction-of-arrival (DoA)

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Nodes Deployment Techniques for Target Coverage and Connectivity Problems in Underwater Wireless sensor Networks based on JAYA algorithm 5

Nodes Deployment Techniques for Target Coverage and Connecti...

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5th ieee India Council international Subsections conference, INDISCON 2024

作者： Kadoke, Kadoke Marco Goyal, Sonia Kaur, Ranjit Punjabi University Department of Electronics and Communication Engineering Patiala India

ISBN: (纸本)9798350376753

Effective maritime environment monitoring with underwater wireless sensor networks (UWSNs) depends on having optimal network coverage and connectivity through suitable node deployment within a designated detecting region. Many of the node deployment systems that are currently recommended for UWSNs work under the assumption the sensor nodes are stationary and that their placement remains unchanged after deployment. the placed static sensor node moves from its initial positions to new ones due to ocean currents and interactions with underwater current, leaving most of the targets unexplored and disrupting network connectivity. In order to find a solution, we suggest using the JAYA algorithm to deploy nodes in UWSNs at the optimal location for autonomous underwater vehicles (AUVs). Coverage quality, connected cost, and network lifetime are the three factors that make up the innovative fitness function of the proposed method, which is based on the JAYA metaheuristic algorithm and uses a single autonomous underwater vehicle. Additionally, a novel fitness function is developed for both the quantity and position of the sensors by applying an effective detection probability and Euclidean distance in the suggested method. We explain in detail the performance estimation of the proposed algorithm and compare it with the current algorithms concerning connection cost, quality of coverage, convergence rate, and network lifetime. As seen by the simulation results, the suggested methodology improves the network's underwater coverage. © 2024 ieee.

关键词： sensor nodes

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Adaptive Retransmission for Wireless sensor Nodes Under Bursty Error Conditions 5

Adaptive Retransmission for Wireless Sensor Nodes Under Burs...

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5th international conference on Smart sensors and Application, ICSSA 2024

作者： Jonah, Sokipriala Yoo, Seong Ki Sthapit, Saurav Center for Computational Science and Mathematical Modelling Coventry University Coventry United Kingdom Center for Future Transport and Cities Coventry University Coventry United Kingdom

ISBN: (纸本)9798350354294

Wireless sensor nodes, used in disaster management and industrial applications, typically require high reliability and low energy consumption. this reliability is often hindered due to bursty channel errors in practical wireless systems. the existing retransmission scheme used in ieee 802.15.4 fails to capture the characteristics of burst channels as they are designed under the assumption of uniform error channels. thus, they do not significantly improve the reliability under bursty channels while increasing the energy consumption with multiple retransmissions. Our proposed method utilises Reinforcement Learning (RL) to develop an adaptive retransmission strategy. this strategy is informed by analysing the transmission history of the sensor. the RL algorithm learns the optimal policy, which maximises energy efficiency and Packet Delivery Ratio (PDR) in networks with burst channel errors. Our RL retransmission strategy performed better in PDR and energy efficiency than the ieee 802.15.4 and Retransmission Adaptive Intelligence Medium Access Control (RAI-MAC) proposed in the literature. By adaptively modifying the retransmission strategy, we improved the energy efficiency and PDR by 16% and 10%, respectively, under a 10-15% packet error rate. the results highlight the importance of an adaptive retransmission strategy for resource-constrained wireless sensors. © 2024 ieee.

关键词： sensor nodes

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Analysing the Design of a Solar Energy Harvesting Wireless sensor Node for Agricultural Applications 5

Analysing the Design of a Solar Energy Harvesting Wireless S...

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5th international conference on Artificial Intelligence, Big Data, computing and Data Communication systems (ICABCD)

作者： thene, Malebo E. Mathaba, Tebello N. D. Vaal Univ Technol Dept Elect Engn Vanderbijlpark South Africa Univ Johannesburg Postgrad Sch Engn Management Johannesburg South Africa

ISBN: (数字)9781665484220

ISBN: (纸本)9781665484220

the advent of the Internet-of-things (IoT) presents a solution to improving agricultural crop production, to achieve food security and meet the sustainable development goal to eliminate hunger. A literature review indicates that an energy efficient wireless sensor network (WSN) is a good solution for remote crop monitoring. One way of creating an energy efficient WSN is to ensure that the nodes themselves are energy efficient. this paper presents a preliminary analysis of an energy efficient sensor node, a key component in an IoT-based wireless sensor network solution for crop monitoring. A review of recent literature articles is used to analyze the energy usage of each of the components and the energy contribution of a solar harvesting sub-system. Our analysis, in a generic model that can be used to effectively design an energy efficient wireless sensor node.

关键词： Internet-of-things Agriculture energy-efficiency LoRa

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Edge-computing Enabled Si Photonics Multimodal sensor with Integrated Photonic Convolutional Processor 38

Edge-Computing Enabled Si Photonics Multimodal Sensor with I...

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38th ieee international conference on Micro Electro Mechanical systems, MEMS 2025

作者： Xiao, Zian Ren, Zhihao Zhuge, Yangyang Zhang, Zixuan Zhou, Jingkai Xu, Siyu Xu, Cheng Dong, Bowei Lee, Chengkuo Agency for Science Technology and Research Singapore National University of Singapore Department of Electrical & Computer Engineering Singapore Singapore National Centre for Advanced Integrated Photonics S2-B3-01 50 Nanyang Avenue Singapore

ISBN: (纸本)9798331508890

Photonic integrated circuits provide compact and efficient solutions for multimodal spectroscopic sensors. However, the resulting sensory data is highly complex and contains significant redundancy. To circumvent high communication cost for redundancy, the photonic sensor and processor are brought into intimacy and propose a photonic multimodal edge computing system. A microring resonator crossbar is used as photonic processor with 5-bit accuracy. the in-situ processing of sensory data is demonstrated in this system, achieving a classification accuracy of 94.27% across 45 different classes. the multimodal edge computing system demonstrates the feasibility of integrating photonic processors and photonic sensors to enhance the photonic data processing capability. © 2025 ieee.

关键词： In situ processing

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