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An Edge AI System Based on FPGA Platform for Railway Fault Detection 13

An Edge AI System Based on FPGA Platform for Railway Fault D...

引用

13th IEEE Global conference on Consumer Electronic, GCCE 2024

作者： Li, Jiale Fu, Yulin Yan, Dongwei Ma, Sean Longyu Sham, Chiu-Wing The University of Auckland School of Computer Science Auckland New Zealand

ISBN: (纸本)9798350355079

As the demands for railway transportation safety increase, traditional methods of rail track inspection no longer meet the needs of modern railway systems. To address the issues of automation and efficiency in rail fault detection, this study introduces a railway inspection system based on Field Programmable Gate Array (FPGA). this edge AI system collects track images via cameras and uses Convolutional Neural networks (CNN) to perform real-time detection of track defects and automatically reports fault information. the innovation of this system lies in its high level of automation and detection efficiency. the neural network approach employed by this system achieves a detection accuracy of 88.9%, significantly enhancing the reliability and efficiency of detection. Experimental results demonstrate that this FPGA-based system is 1.39× and 4.67× better in energy efficiency than peer implementation on the GPU and CPU platform, respectively. © 2024 IEEE.

关键词： Convolutional neural networks

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A Semi-supervised Fake News Detection using Sentiment Encoding and LSTM with Self-Attention 13

A Semi-supervised Fake News Detection using Sentiment Encodi...

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13th International conference on computer and Knowledge Engineering, ICCKE 2023

作者： Shaeri, Pouya Katanforoush, Ali Shahid Beheshti University Department of Computer and Data Sciences Tehran Iran

ISBN: (纸本)9798350330151

Micro-blogs and cyber-space social networks are the main communication mediums to receive and share news nowadays. As a side effect, however, the networks can disseminate fake news that harms individuals and the society. Several methods have been developed to detect fake news, but the majority require large sets of manually labeled data to attain the application-level accuracy. Due to the strict privacy policies, the required data are often inaccessible or limited to some specific topics. On the other side, quite diverse and abundant unlabeled data on social media suggests that with a few labeled data, the problem of detecting fake news could be tackled via semi-supervised learning. Here, we propose a semi-supervised self-learning method in which a sentiment analysis is acquired by some state-of-the-art pretrained models. Our learning model is trained in a semi-supervised fashion and incorporates LSTM with self-attention layers. We benchmark our model on a dataset with 20,000 news content along with their feedback, which shows better performance in precision, recall, and measures compared to competitive methods in fake news detection. © 2023 IEEE.

关键词： Sentiment analysis

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Security Risk Analysis in computer networks for Small and Medium-Sized Enterprises 13th

Security Risk Analysis in Computer Networks for Small and Me...

引用

13th computer Science Online conference

作者： Horak, Tibor Strelec, Peter Kovac, Szabolcs Sido, Jan Skypala, Richard Ruzarovsky, Roman Slovak Univ Technol Bratislava Fac Mat Sci & Technol Trnava Inst Appl Informat Automat & Mechatron Trnava Slovakia Slovak Univ Technol Bratislava Fac Mat Sci & Technol Trnava Inst Mfg Technol Trnava Slovakia

ISBN: (纸本)9783031702990;9783031703003

Small- and medium-sized organizations, such as public administrations and other institutions, are facing increasing demands for efficient information processing and storage, as well as for securing sensitive data. threats such as cyber-attacks, phishing, ransomware, and other forms of data tampering pose a real risk to organizations and can lead to loss of confidentiality and reputation, financial loss, and other consequences. Cybercrime is a growing problem today. It is not easy to protect an ordinary business from such dangers. Security is a key consideration in infrastructure design because it protects the confidentiality, integrity, and availability of sensitive information and services. Well-configured network security includes separating individual network segments, ensuring the security of network services, monitoring, data flow analysis, and access trust management. therefore, the objective of this publication is to present an analysis of security risks in computing infrastructures to minimize the likelihood of security incidents and ensure the continuous availability, integrity, and confidentiality of data and services.

关键词： computer network network technologies server network security firewall

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5G Indoor Distributed Antenna System Wiring Planning Fast Algorithm 13

5G Indoor Distributed Antenna System Wiring Planning Fast Al...

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13th International conference on Information Science and Technology, ICIST 2023

作者： Zeng, Shaoda Wang, Yuping Liu, Hai-Lin Wen, Jiechang Zhang, Qingfu School of Mathematics and Statistics Guangdong University of Technology Guangzhou China School of Computer Science and Technology Xidian University Xi'an China Department of Computer Science City University of Hong Kong Hong Kong

ISBN: (纸本)9798350313925

With the increasing demand for indoor 5G communications, distributed antenna system (DAS) has received more attention as an important way to deploy indoor signals. As an important part of DAS design, the wiring planning largely affects the deployment cost and the output power of each antenna. Regrettably, the wiring planning problem has been somewhat neglected in past studies. this paper establishes a two-stage solution model for this problem as a way to fastly solve the DAS wiring planning problem. In addition, in order to accelerate the solution process for the wiring planning problem, an algorithm that utilizes a local search strategy and a diagonal turning points path retracing strategy is proposed. In two real scenarios, computer simulation experiments show that the proposed algorithm is better than the comparison algorithm in solving the problem and reduces the solving time greatly. © 2023 IEEE.

关键词： Antennas

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Shaping the Future of Mobile Edge Computing with Innovative Architectures and Designs for Web3.0 over 5G/6G networks 13

Shaping the Future of Mobile Edge Computing with Innovative ...

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13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Malviya, Ashwini Lora, Chandra Prakash Kannagi, A. Atlas SkillTech University Department of UGDX Maharashtra Mumbai India Vivekananda Global University Department of Chemistry Jaipur India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350305463

Web3.0 apps, with their emphasis on decentralization, real-time processing, and low latency, hold the key to MEC's bright future. this calls for an all-encompassing, future-oriented strategy in MEC architecture and design. the suggested technique is a multi-stage strategy for molding the future of MEC via cutting-edge architectures and designs for Web3.0 over 5G/6G networks. In the first stage, you'll examine the needs and goals of Web3.0 in detail. Real-time, lowlatency interactions are essential, as is familiarity with the dynamics of distributed apps and blockchain technology. In the second stage, we examine the current MEC setup, from edge server dispersion to data center density to network topology. the technique takes use of the low latency, high throughput, and huge device connection offered by 5G and impending 6G networks to guarantee preparedness for the future. the suggested technique is based on novel building layouts as its foundation. Latency, throughput, resource usage, scalability, and security compliance are only few of the metrics that may be evaluated to guarantee that the design is effective. the difficulties of actual deployment are also discussed;they include issues like where to put edge servers and how to scale resources according to demand. To ensure that the process remains in step with developing technologies and user preferences, it is recommended that improvements be made in a series of iterations. © 2024 IEEE.

关键词： Blockchain

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Visualization and Interpretation of Mel-Frequency Cepstral Coefficients for UAV Drone Audio Data 13

Visualization and Interpretation of Mel-Frequency Cepstral C...

引用

13th International conference on Data Science, Technology and Applications, DATA 2024

作者： Wang, Mia Y. Chu, Zhiwei Entzminger, Conner Ding, Yi Zhang, Qian Department of Computer Science College of Charleston CharlestonSC United States Departmemt of Computer and Information System Purdue University West LafayetteIN United States Department of Biology College of Charleston CharlestonSC United States Department of Business Administration Anhui Polytechnic University China Department of Engineering College of Charleston CharlestonSC United States

ISBN: (纸本)9789897587078

Unmanned Aerial Vehicles (UAVs) have become a focal point in various fields, prompting the need for effective detection and classification methodologies. this paper presents a thorough investigation into UAV audio signatures using Mel-Frequency Cepstral Coefficients (MFCCs). We meticulously explore the influence of varying MFCC quantities on classification accuracy across diverse UAV categories. Our analysis demonstrates that employing 30 MFCCs produces promising outcomes, characterized by reduced variance and heightened discriminatory capability compared to alternative configurations. Moreover, we introduce a novel image-based dataset derived from our existing audio dataset, encompassing waveform, spectrogram, Mel filter bank, and MFCC plots for 26 UAV categories, each comprising 100 audio files. this dataset facilitates comprehensive analysis and the development of multimodal UAV detection systems. Our research highlights the significance of leveraging diverse datasets and identifies future paths for UAV detection and classification research. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Spectrographs

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DeMedia: Decentralization of Social Media 13

DeMedia: Decentralization of Social Media

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13th IEEE International conference on Communication Systems and Network Technologies, CSNT 2024

作者： Perera, B.S.S. Dhananjani, G.G.S. Bandara, A.M.C.A. Abeykoon, A.W.Y.I.K. Abeywardena, Kavinga Yapa Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350305463

Social media networks have become an essential part of the modern world, with billions of people using them as an integral part of their daily lives. Despite their popularity, these networks are centralized, allowing the companies that own them to monitor and track their users' activities. this has given rise to serious concerns regarding the privacy and security of user data, which are often sold to third parties for profit. Given the massive value of user data in today's and tomorrow's world, many people are concerned about this issue. While decentralized, community-driven applications have emerged as a potential solution to this problem, none have yet been able to compete with centralized social network platforms. Due to those facts, this research aimed to propose a decentralized social network architecture that would incorporate the basic functionalities of a social media platform while ensuring the privacy and security of users' data, which would be stored locally on their devices. A thorough study of the existing centralized and decentralized social media platforms was conducted to identify the path for this research. the proposed protocol offers a decentralized and secure social media platform architecture that provides true ownership of user data along with decentralized data integrity and caching. © 2024 IEEE.

关键词： Network architecture

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Parallel Computations in the Problem of Identification of Interval Discrete Models based on Swarm Intelligence of a Bee Colony 13

Parallel Computations in the Problem of Identification of In...

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13th International conference on Advanced computer Information Technologies, ACIT 2023

作者： Dyvak, Mykola Kindzerskyi, Oleksandr Dostalek, Libor Stetsko, Mykola Nowak, Joachim West Ukrainian National University Department of Computer Science Ternopil Ukraine Czech Technical University in Prague Computer Networks Research Group Department of Computer Systems Prague Czech Republic West Ukrainian National University Department of Financial Management and Insurance Ternopil Ukraine Catholic University in Ruzomberok Faculty of Theology Ruzomberok Slovakia

the article discusses the problem of parametric identification of interval discrete models of complex objects. A new scheme of parallel computations for solving the problem of parametric identification based on the behavioral model of an artificial bee colony is proposed and justified. the effectiveness of the proposed parallel computing scheme is considered using the example of parametric identification of a mathematical model of the anaerobic microbiological fermentation process in biogas plants. A nonlinear second-order discrete model describes the dynamics of residual organic waste mass in the biogas reactor during fermentation. According to the results of the experiments, a 2-fold acceleration of the algorithm's computational time was achieved. © 2023 IEEE.

关键词： Swarm intelligence

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13th EAI International conference on Mobile networks and Management, MONAMI 2023

13th EAI International Conference on Mobile Networks and Man...

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13th EAI International conference on Mobile networks and Management, MONAMI 2023

ISBN: (纸本)9783031554704

the proceedings contain 21 papers. the special focus in this conference is on Mobile networks and Management. the topics include: Client Selection Method for Federated Learning in Multi-robot Collaborative Systems;cross-Chain Model of Notary Group Based on Verifiable Random Functions;enhancing Cloud Data Integrity Verification Scheme with User Legitimacy Check;Decoupled 2S-AGCN Human Behavior Recognition Based on New Partition Strategy;Human Behavior Recognition Algorithm Based on HD-C3D Model;inverse Pyramid Pooling Attention for Ultrasonic Image Signal Recognition;an Improved 4D Convolutional Neural Network for Light Field Reconstruction;Fusing PSA to Improve YOLOv5s Detection algorithm for Electric Power Operation Wearable devices;image Deblurring Using Fusion Transformer-Based Generative Adversarial networks;Improved AODNet for Fast Image Dehazing;image Classification Algorithm for Graphite Ore Carbon Grade Based on Multi-scale Feature Fusion;graphite Ore Grade Classification Algorithm Based on Multi-scale Fused Image Features;Improved WGAN for Image Generation Methods;research on Multi-scale Pedestrian Attribute Recognition Based on Dual Self-attention Mechanism;improving Pedestrian Attribute Recognition with Dense Feature Pyramid and Mixed Pooling;Double DQN Reinforcement Learning-Based Computational Offloading and Resource Allocation for MEC;Content Prediction for Proactive Tile-Based VR Video Streaming in Mobile Edge Caching System;research on Latent Semantic Relationship Search Engine Based on Knowledge Graph;promoting Animation Synthesis through Dual-Channel Fusion.

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Active Learning on Neural networks through Interactive Generation of Digit Patterns and Visual Representation 13

Active Learning on Neural Networks through Interactive Gener...

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13th IEEE Integrated STEM Education conference, ISEC 2023

作者： Jeong, Dong H. Cho, Jin-Hee Chen, Feng Josang, Audun Ji, Soo-Yeon University of the District of Columbia Department of Computer Science and Information Technology WashingtonDC United States Virginia Tech. Department of Computer Science Falls Church United States University of Texas at Dallas Department of Computer Science Richardson United States University of Oslo Department of Informatics Oslo Norway Bowie State University Department of Computer Science Bowie United States

ISBN: (纸本)9798350300017

Artificial neural networks (ANNs) have been broadly utilized to analyze various data and solve different domain problems. However, neural networks (NNs) have been considered a black box operation for years because their underlying computation and meaning are hidden. Due to this nature, users often face difficulties in interpreting the underlying mechanism of the NNs and the benefits of using them. In this paper, to improve users' karning and understanding of NNs, an interactive learning system is designed to create digit patterns and recognize the m in real time. To help users clearly understand the visual differences of digit patterns (i.e., 0∼9) and their results with an NN, integrating visualization is considered to present all digit patterns in a two-dimensional display space with supporting multiple user interactions. An evaluation with multiple datasets is conducted to determine its usability for active learning In addition, informal user testing is managed during a summer workshop by asking the workshop participants to use the system. © 2023 IEEE.

关键词： Neural networks

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