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2022 ieee international conference on distributed computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022 - Proceedings

2022 IEEE International Conference on Distributed Computing,...

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6th ieee international conference on distributed computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2022

ISBN: (纸本)9781665487160

the proceedings contain 59 papers. the topics discussed include: a prognostic reasoning model for improving areacanut crop productivity using data analytics approach;identification of toxicity in multimedia messages for controlling cyberbullying on social media by natural language processing;improving soybean disease prediction by performing late-stage re-training using fireworks algorithm;strong baseline with auto-encoder for scale-invariant person re-identification;visualized document similarity framework with the aid of knowledge graph;voice assisted form filling for the differently abled;an optimized RISC-V processor with five stage pipelining using tournament branch predictor for efficient performance;comparison of memristor mathematical models;and design of asynchronous circular FIFO buffer for asynchronous network on chips.

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Lattice-Based Fine-grained Data Access Control and Sharing Scheme in Fog and Cloud computing Environments for the 6G systems 18

Lattice-Based Fine-grained Data Access Control and Sharing S...

引用

18th ieee international conference on Mobility, Sensing and Networking (MSN)

作者： Pei, Bei Zhou, Xianbin Jiang, Rui Minist Publ Secur Res Inst 3 Shanghai 200031 Peoples R China Southeast Univ Sch Cyber Sci & Engn Nanjing 210096 Peoples R China

ISBN: (纸本)9781665464574

the 6G (the sixth generation mobile communication) network is a heterogeneous network, which includes the cloud computing and the fog computing environment. And, the data securities in the 6G systems may face great challenges. On the one hand, fine-grained data access control in fog and cloud computing environments is essential to the 6G network. On the other hand, quantum computing attacks may cause great security threats for the 6G network. In order to solve the above problems, we propose a lattice-based fine-grained data access control and sharing scheme in fog and cloud computing environments (LB-DACSS) for the 6G network. Firstly, our LB-DACSS scheme can achieve secure data sharing and fine-grained access control in fog and cloud computing environments. Secondly, we apply a lattice encryption algorithm to ensure our LB-DACSS scheme can withstand quantum computing attacks. thirdly, our LB-DACSS scheme can achieve secure attribute revocation. Fourthly, we bind a unique secret value related to the user's attribute to construct the user's secret key. Finally, both formal security analysis and performance analysis show that our LB-DACSS scheme is efficient and secure.

关键词： Fine-grained Access Control Fog and Cloud computing Environments Quantum computing attacks Lattice-Based Encryption Ring-Learning with Errors Attribute Revocation

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Temperature sensor Realized by Inkjet Printing on Polyimide Flexible Substrate 4

Temperature Sensor Realized by Inkjet Printing on Polyimide ...

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4th ieee international conference on Design and Test of Integrated Micro and Nano-systems, DTS 2022

作者： Khalaf, Ayatallah M. Issa, Hanady Hussein Mohamed, Shaimaa A. Ramirez, Jose Luis Technology and Maritime Transport Department of Electronics and Communications Arab Academy for Science Cairo11799 Egypt Centre for Nanotechnolog Zewail City of Science and Technology October Gardens 6th of October City Giza12578 Egypt Electrica i Automatica Universitat Rovira i Virgili Departament d'Enginyeria Electronica Tarragona43007 Spain

ISBN: (纸本)9781665497831

In this work, Resistive Temperature sensors were fabricated on Polyimide (PI) substrate using inkjet printing, utilizing a commercial silver nano-particles conductive ink. the Temperature sensors were characterized in a temperature range from room temperature up to 90°C. three-line widths were fabricated to investigate the effect of dimension change. Different printing layers have been studied and verified as well. the sensor showed good linearity and sensitivity of 0.177%/oC in the tested temperature range. © 2022 ieee.

关键词： Polyimides

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A Scalable and Cost-Efficient Antenna Testbed Using FPGA-Server Compound Structures for Prototyping 6G Applications 19

A Scalable and Cost-Efficient Antenna Testbed Using FPGA-Ser...

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19th Annual international conference on distributed computing in Smart systems and the Internet of things, DCOSS-IoT 2023

作者： Neu, Marc Karle, Christian Nuss, Benjamin Groeschel, Patrick Becker, Juergen Itiv Karlsruhe Institute of Technology Karlsruhe Germany Lhft Nuremberg University of Erlangen Nuremberg Germany

ISBN: (纸本)9798350346497

Developing the sixth generation mobile network infrastructure is expected to utilize mm-Wave technology and multiple-input multiple-output (MIMO) arrays to enable high-speed, low-latency communication. Designing suitable MIMO arrays that support multi-GHz bandwidths per channel imposes enormous requirements on all sub-components performing analog-digital conversion, data acquisition, and digital signal processing. Current MIMO testbeds lack the bandwidth and radio-frequency sampling rates of future mobile network applications. therefore, we propose a cost-efficient architecture based on off-the-shelf components that is scalable in the number of antennas per testbed and the attainable bandwidth per channel. We demonstrate the feasibility of our approach by implementing two testbeds and transmitting a broadband orthogonal frequency-division multiplexing signal over concurrent channels. In comparison to current MIMO testbeds, we support 2.46 times higher bandwidths per channel and 9.84 times higher radio-frequency sampling rates, which we demonstrate by performing infield measurements. To conclude, our testbed allows for the proto-typing of broadband MIMO antennas, forming the foundation for cost-efficient evaluation of novel communication protocols in large test fields. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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Local Tetra Pattern-based Bilateral LPP in Robot Navigation Guidance systems: A Robust Approach against Vision sensor Noises 6

Local Tetra Pattern-based Bilateral LPP in Robot Navigation ...

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6th ieee international conference on Condition Assessment Techniques in Electrical systems, CATCON 2022

作者： Ghosh, Saibal Chatterjee, Amitava Munshi, Sugata Jadavpur University Dept. of Electrical Engineering Kolkata India

ISBN: (纸本)9781665473804

Locality preserving projections (LPP), originally being a graph Laplacian-based dimensionality reduction technique, searches for a space to embed the higher-dimensional data, keeping the local neighborhood information of the data preserved. However, with conventional LPP, a major challenge lies in the fact that the projection matrix of LPP solely depends on the spatial distribution of the data. this distribution in the Euclidean space is susceptible to spatial factors like scaling, rotation, translation, etc. Apart from that, similar to most graph-based methods, the graph formulation in LPP is influenced by noise and outliers. In this paper, the concept of bilateral filtering has been utilized in the case of LPP, which incorporates feature weights obtained from the higher-dimensional data along with the Euclidean spatial kernel. It enables LPP to make use of the important intrinsic information from the feature space as well, which ameliorates its vulnerability to spatial distortions reasonably. Moreover, a local tetra pattern (LTrP)-based feature descriptor has been utilized here, which helps in extracting robust features from the vision sensor data corrupted with sensor noises. With extensive experimental studies, the proposed algorithm of LTrP-BLPP has been comprehended to be a robust variant of LPP against vision sensor noises. © 2022 ieee.

关键词： Human robot interaction

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A UAV Swarm Sensing Oriented distributed computing Cooperation Scheme 6

A UAV Swarm Sensing Oriented Distributed Computing Cooperati...

引用

6th ieee international conference on Computer and Communication systems, ICCCS 2021

作者： Li, Tianyang Cheng, Zekun Leng, Supeng School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9780738126043

With the advantages of flexibility and miniaturization, Unmanned Aerial Vehicle (UAV) has been widely applied to operate sensing tasks in many complicated environments. Based on the airborne sensors, a UAV can capture multiple videos or snapshots for monitoring and data analysis. However, the scarce computing resource of one single UAV may cause an unacceptable execution delay for image processing, especially when a batch of images are captured in a very short period of time. To solve the challenge, we propose a UAV swarm based distributed computing collaboration structure to integrate the computing resource of UAVs for real-time sensing tasks. Specifically, a UAV is elected as the coordinator to conduct the resource scheduling strategy for the computing cooperation among the remaining UAVs. In order to improve the utilization of computing resource, different layers of the Convolutional Neural Network (CNN) are computed by diverse UAVs. these UAVs can rapidly process the batch of images in a pipeline manner. Moreover, we formulate a non-linear programming model to minimize the batch execution time. A distributed CNN based Resource Scheduling (DCRS) algorithm is proposed to obtain the minimal execution time based on deep reinforcement learning. Simulation results demonstrate that our schemes not only can reduce the execution time but also can improve the computing resource utilization significantly. © 2021 ieee.

关键词： Unmanned aerial vehicles (UAV)

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A Garbage Disposal Management System to Support Swachh Bharath Mission 6

A Garbage Disposal Management System to Support Swachh Bhara...

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6th international conference on Devices, Circuits and systems, ICDCS 2022

作者： Denicke Solomon, H. Abishek, R. Ramachandra, T. Pavithra, P. Ezhilarasi, S. Madras Institute of Technology Anna University Department of Electronics Engineering Chennai India

ISBN: (纸本)9781665480949

In the current scenario, people prefer to live in cleaner locality to have a healthy lifestyle. Both organic and inorganic wastes from home are disposed at common garbage bins maintained by panchayat or municipality or corporation. Overflow of the bins are due to the stray dogs pulling out the food wastes and wastes thrown by people from moving vehicles that causes severe health issues to the people in the neighborhood. Lot of challenges exists, though there is an awareness among Indians to Swachh Bharath Mission. the work proposed in the paper is to facilitate a Garbage Disposal Management System using Arduino, a parallel switching network, two ultrasonic sensors, servo motors, GSM/GPRS module, 4 X 4 matrix keypad, piezo electric buzzer and LED. the proposed Garbage Disposal Management System is ideal for busy and public locations such as college campuses, malls, railway stations and airports. though its design cost is higher than the normal dustbins, it serves for a longer term and easy to handle. © 2022 ieee.

关键词： Costs Switches Dogs Light emitting diodes sensor systems Rail transportation sensors

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FakeSens: A Social Sensing Approach to COVID-19 Misinformation Detection on Social Media 17

FakeSens: A Social Sensing Approach to COVID-19 Misinformati...

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17th Annual ieee international conference on distributed computing in sensor systems (ieee DCOSS)

作者： Kou, Ziyi Shang, Lanyu Zhang, Yang Youn, Christina Wang, Dong Univ Notre Dame Dept Comp Sci & Engn Notre Dame IN 46556 USA

ISBN: (纸本)9781665439299

Social sensing is emerging as an effective and pervasive sensing paradigm to collect timely data and observations from human sensors. this paper focuses on the problem of COVID-19 misinformation detection on social media. Our work is motivated by the lack of COVID-specific knowledge in current misinformation detection solutions, which is critical to assess the truthfulness of social media claims about the emerging COVID19 disease. In this paper, we leverage human intelligence on a crowdsourcing platform to obtain essential knowledge facts for detecting the COVID-19 misinformation on social media. Two critical challenges exist in solving our problem: i) how to efficiently acquire accurate and timely knowledge that is both inclusive and specific to COVID-19? ii) How to effectively coordinate the efforts from both expert and non-expert workers to detect COVID-19 misinformation? To address these challenges, we develop FakeSens, a social sensing based crowd knowledge graph approach that explicitly explores the knowledge facts specific to COVID-19 and models the reliability of different types of crowd workers to capture the misleading COVID-19 claims Evaluation results on a real-world dataset show that FakeSens significantly outperforms state-of-the-art baselines in accurately detecting misleading claims of COVID-19 on social media.

关键词： COVID-19 Knowledge engineering Social networking (online) Human intelligence Performance gain sensor systems Graph neural networks

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Blockchain-Based distributed Caching with replication for Efficient Service Provision in Edge-cloud Environments 23

Blockchain-Based Distributed Caching with replication for Ef...

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6th international conference on Networking, Intelligent systems and Security, NISS 2023

作者： Chanyour, Tarik Kaddari, Abdelhak Lis Lab Science Faculty of Ain-Chock Hassan Ii University Maarif Casablanca Morocco Lmsc Lab Ensa Marrakech Cadi Ayyad University Gueliz Marrakech Morocco

ISBN: (纸本)9798400700194

5G networks promote integrating Multi-access Edge computing (MEC) capabilities in Dense Small Cell (DSC) networks in order to address the strict latency requirement of Smart Mobile Devices (SMDs) services. this article investigates the contribution of a split-cache method integrated within a secure blockchain based MEC system and present a novel method to enhance service provision by distributing the containers' base image chunks among multiple Edge-Cloud Nodes (ECNs). the objective of this study is to minimize the service starting/restarting time by collecting, verifying and compiling the best chunks candidates while resources allocation is considered at each request slot. the formulated problem is a mixed-integer nonlinear program, subject to network bandwidth capacity, base image chunks availability, and services starting deadlines constraint. Finally, the numerical results of the proposed two solutions demonstrate its benefits regarding service provision operations while taking bandwidth,timing and resources into consideration. © 2023 ACM.

关键词： Containers

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Wearable sensor Based Cloud Data Analytics Using Federated Learning Integrated with Classification by Deep Learning Technique 1

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6th international conference on Innovative computing and Communication, ICICC 2023

作者： Munnangi, Ashok Kumar Rajeyyagari, Sivaram Sekaran, Ramesh Jikkiriya, Nashreen Begum Ramachandran, Manikandan Department of Information Technology Velagapudi Ramakrishna Siddhartha Engineering College Andhra Pradesh Vijayawada520007 India Department of Computer Science College of Computing and Information Technology Shaqra University Shaqra Saudi Arabia Karnataka Bangalore562112 India Department of Artificial Intelligence and Machine Learning Malla Reddy University Telangana Hyderabad500100 India School of Computing SASTRA Deemed University Tamil Nadu Thanjavur India

ISBN: (数字)9789819933150

ISBN: (纸本)9789819933143

Wearable sensors and person to person communication stages assume a key part in giving another strategy to gather patient information for productive medical care observing. In any case, persistent patient observing utilizing wearable sensors produces a lot of medical care information. Deep learning (DL) is a potential method for big data analytics since it can be utilized to quickly classify as well as analyse this plethora of data. this research proposes novel method in wearable sensor based cloud data analysis by federated learning as well as classification using DL. Input is collected by cloud architecture based wearable sensor and processed for noise removal as well as normalization. Cloud data is secured based on federated learning and classified using U-Net convolutional auto encoder radial neural networks. Experimental analysis has been carried out in terms of accuracy, precision, recall, F-1 score, RMSE and NSE for different wearable sensor dataset. Proposed method attained accuracy 98%, precision 85%, recall 75%, F-1 score 66%, RMSE 55% and NSE 55%. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Classification (of information)

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