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Authentication in the Internet of Vehicles using Blockchain Technology: Review 3

Authentication in the Internet of Vehicles using Blockchain ...

引用

3rd International Conference on Power, Energy, Control and Transmission Systems, ICPECTS 2022

作者： Sarika, Sabavath Prabakeran, S. SRM Institute of Science and Technology Dept. of Computer Science and Engineering TamilNadu India School of Computing Dept. of Networking and Comunications SRM Institute of Science and Technology TamilNadu India

ISBN: (纸本)9781665462754

The Internet of Vehicles (IoV) aims to make transportation autonomous, safe, fast, and efficient while reducing resource waste and harmful environmental impacts. To happen this, IoV interconnects pedestrians, cars, and components of urban infrastructure. It uses numerous sensors, software, in-built hardware, and diverse connections to enable reliable and continuous communication. Therefore, they are prone to attacks that may lead to life-endangering consequences, so it is vital to develop security mechanisms to detect such attacks against IoV. Blockchain technology is one of the emerging technologies that have been used recently in Cybersecurity due to its robustness and integrity-preserving properties. Blockchain technology's immutability, tamper-proof, and security by design make it a promising technology for IoV. This study is a comprehension of existing work of securing IoV using blockchain techniques. © 2022 IEEE.

关键词： Vehicles

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A Graph Convolutional Attention Network with Q-net on Multi-agent Systems 2

A Graph Convolutional Attention Network with Q-net on Multi-...

引用

2nd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2022

作者： Li, Yupei Shen, Tianqi Liu, Zhiyuan Dept. of Computer Science University of Oxford Oxford United Kingdom Department of AeroSpace Information Engineering Beihang University Beijing China Dept. of Computer Science University of Toronto TorontoON Canada

ISBN: (纸本)9781510657717

In recent years, GNNs have becoming one of the hottest topics of deep learning due to their powerful ability in modeling relational data and their wide applications in real world. Besides, reinforcement learning is widely applied in many fields. However, the tradition way to train the reinforcement learning is not that accurate enough. It can be assumed that it is wise to combine GNN and reinforcement learning, making good use of the modeling capability of GNNs, to enhance the reinforcement learning performance. In this paper, the most ordinary GNN is compared within the existing works to see whether it is possible to combine GNN and reinforcement learning. PettingZoo is chosen on behalf of the multi-agent system, and a Graph Convolutional Attention Network with Q-net (GCANQ) is designed and validated, which shows the efficient computational capability of GNN. Experiments show that GNN performs strikingly well on a common multiagent system and in a small scale with some overfit as well. Moreover, the speed of the training of GCANQ is acceptable for the complex calculation needed. © 2022 SPIE. All rights reserved.

关键词： Graph neural networks

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VAR: An Efficient Silent Video to Speech System with Subtitle Generation using Visual Audio Recall

VAR: An Efficient Silent Video to Speech System with Subtitl...

引用

International Conference on Inventive Research in Computing Applications (ICIRCA)

作者： Diya Dhandapani Shanmugam Safiya Fathima Syed Sahana Dinesh S. Chitrakala Dept. of Computer Science and Engineering College of Engineering Guindy Chennai India

In this paper, a method to generate speech from a muted video is proposed. Recent advances in computer vision and deep learning have allowed the development of lip-reading technology that can recognize and interpret lip movements in videos. However, one of the main challenges in visual-to-speech synthesis is distinguishing between homophenes, or sets of words that look identical on a person's lips but contain different sounds. To address this challenge, the proposed model utilizes a speech generation framework that uses an external memory called Visual Audio Recall (VA-Recall) to generate speech from silent video. The VA-Recall system allows the system to effectively synthesize speech from a speaker by recalling the most relevant auditory information that matches the visual input context. The proposed method further generates subtitles for the reconstructed audio. Overall, this process allows for a more natural and contextually appropriate speech synthesis system.

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Data-Driven Approach to Coastal Water Quality Management: Enhancing Sustainable Decision-Making for engineering and Development Initiatives

Data-Driven Approach to Coastal Water Quality Management: En...

引用

Decision Aid sciences and Application (DASA), International Conference on

作者： Ali Sedki Jumana AlTaweel Noor Jasim Zain AlKaabi dept. of Civil and Architectural Engineering Applied Science University Manama Kingdom of Bahrain

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

This paper is part of undergraduate coursework addressing the ecological impacts of urbanization and industrialization, with a focus on water pollution and diminishing water resources in Bahrain coastal areas. The study analyzes water samples from Tubli Bay, Al-Hidd Walkway, and Busaiteen Beach using methodologies such as pH testing, turbidity assessment, conductivity measurement, Total Solids (TS), Total Suspended Solids (TSS), and Total Dissolved Solids (TDS) analysis. Key parameters, including pH, temperature, and turbidity, were assessed against international standards from the World Health Organization and the U.S. Environmental Protection Agency. Results indicated pH levels ranged from 7.15 to 7.44 and turbidity from 20.7 NTU to 22.1 NTU, suggesting suspended particles from sediment runoff and anthropogenic activities. Elevated TDS and conductivity measurements reflect significant salinity in the coastal areas studied. The objectives include monitoring water quality, evaluating compliance with regulatory standards, and assessing pollution impacts on aquatic ecosystems.

关键词： Temperature measurement Environmentally friendly manufacturing techniques Urban areas Sea measurements Turbidity Conductivity measurement Solids Water pollution Water resources Monitoring

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Few-Shot Learning with Feature Pairing and Mean Discrepancy

Few-Shot Learning with Feature Pairing and Mean Discrepancy

引用

Sustainable Computing and Smart Systems (ICSCSS), International Conference on

作者： K K Singh K Hima Bindu dept. of Computer Science and Engineering NIT Andhra Pradesh and RGUKT Nuzvid India dept. of Computer Science and Engineering NIT AP India

Few-Shot Learning (FSL) is a sub-area of machine learning which mainly deals with data where there is a scarcity of training supervised samples. Few shot learning (FSL) more closely resembles the human brain in comparing new concepts to others based on prior experience rather than identifying it exactly. FSL aims to generalize the model across the tasks (in meta learning) opposed to the classical supervised learning which generalizes across the data points. In general the FSL models may suffer from underfitting because of scarcity of supervised samples and at the same time it causes overfitting as it is likely to memorize task specific features of the training set. This work aims to reduce such problems and is presented as a metric based model ”Few Shot Learning with Feature Pairing and Mean Discrepancy” (FL-FPMD). As the title suggests, feature pairing is one among various data augmentations. It is observed that flip augmentation is more suitable in the context of pairing the features within the given task. Memorizing task specific features is reduced by incorporating the discrepancy of mean distributions of the query and the support embedding in the loss function. The training and the evaluation is performed at the miniImageNet dataset and the results indicate that the proposed model outperforms the state-of-the-art models of similar complexity.

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Mapping of Sri Lankan Road Signs by Using Google Street View Images

Mapping of Sri Lankan Road Signs by Using Google Street View...

引用

2022 International Research Conference on Smart Computing and Systems engineering, SCSE 2022

作者： Kiridana, Y.M.W.H.M.R.P.J.R.B. Weerarathna, P.L.M. Wijesingha, W.P.D.Y. Aashiq, M.N.M. Kumara, W.G.C.W. Haleem, M.A.L.A. South Eastern University of Sri Lanka Dept. of Electrical and Telecommunication Engineering Sri Lanka South Eastern University of Sri Lanka Dept. of Computer Science and Engineering Sri Lanka

ISBN: (数字)9781665473750

ISBN: (纸本)9781665473750

The development of autonomous vehicle driving systems and Intelligent Transportation System (ITS) have drawn massive attention since the 1980s. For the development of ITS, road sign detection and identification are considered to be very important due to the vital information provided by road signs. Generally, real-time video-based methods are used as the source of images for the operation of ITS. But they are inefficient and costly due to certain limitations like weather conditions, lighting conditions, and limited range in obtaining quality images. To overcome the limitations of the video-based approach, this research aims to develop techniques for detecting and identifying road signs by using Google Street View (GSV) as the image source, OpenCV for image processing and CNN for road sign identification. EdleNet, LeNet-5, and DenseNet were identified as accurate CNN models. Using images from GSV, generating a database of road signs with the relevant coordinates was possible, which is currently unavailable in Sri Lanka. In addition, this process leads to the generation of a valuable image dataset of Sri Lankan road sign images, and a web interface with mapped road signs. Consequently, this research would yield useful findings that may be applied to future research and provide the means to develop ITS, accident-avoidance systems, and driver assistance systems. © 2022 IEEE.

关键词： Machine learning

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Screening and Ranking resume’s using Stacked Model

Screening and Ranking resume’s using Stacked Model

引用

Advances in Electronics, Communication, Computing and Intelligent Information Systems (ICAECIS), International Conference on

作者： D. Kavitha B Padmavathi V Sushanth P Yashwanth R Yuvaraj Dept. of Computer Science & Engineering Easwari Engineering College TN India

Finding the top candidates for a position is the aim of the resume screening process. The application must make use of machine learning methodologies as well as natural language processing to rate candidates in real time. Natural language processing (NLP) and machine learning methods are used to rate resumes. The output would be the resume of a top candidate, with resumes and job descriptions serving as the input. The output’s results are obtained instantly. String matching, Cosine Similarity, and TF-IDF will all be done with Mon. Existing systems are straightforward and efficient, but they lack precision, efficiency, and processing capacity.

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ML Assisted Web Application Firewall

ML Assisted Web Application Firewall

引用

International Symposium on Digital Forensic and Security (ISDFS)

作者： Pranav Kalariya Manthan Jethva Yasser Alginahi Electrical and Computer Engineering Dept. University of Windsor Windsor Canada Computer Science Dept. Adrian College MI USA

ISBN: (数字)9798350330366

ISBN: (纸本)9798350330373

This study presents the development and implementation of a sophisticated Web Application Firewall (WAF) empowered by machine learning techniques to bolster cybersecurity measures. Traditional WAFs primarily rely on rule-based systems, which may struggle to adapt to the evolving nature of web-based threats. In contrast, our proposed solution leverages machine learning algorithms to dynamically analyze and respond to emerging cyber threats, providing a more proactive and adaptive defense mechanism. The core functionality of the system involves the continuous monitoring of incoming web traffic, extracting relevant features, and utilizing a machine learning model to classify the traffic as either benign or malicious. The model is trained on historical data to recognize patterns and behaviors indicative of various cyber threats, including SQL injection, cross-site scripting, and other common attack vectors. Through this learning process, the system becomes adept.at discerning malicious activities and adapting its defense strategies accordingly. The proposed model helps achieve higher precision in identifying the threat requests from normal requests.

关键词： Adaptation models Machine learning algorithms Firewalls (computing) Machine learning SQL injection Feature extraction Data models

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Analysis of in-place matrix rotation of square matrix for information security applications 4th

Analysis of in-place matrix rotation of square matrix for in...

引用

4th International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2022

作者： Kiran, S. Kumar, A. Ashok Reddy, R. Pradeep Kumar Reddy, D. Sandeep Dept. of Computer Science and Engineering YSR Engineering College of YVU Proddatur516360 India Dept. of Physics YSR Engineering College of YVU Proddatur516360 India ISSE NIT Jamshedpur Jharkhand 831014 India

The concept of matrices was developed to represent complex data into understandable and formattable data. There is a huge number of applications in which matrices are used like classification and data size reduction used to store it. Matrices are widely used in most cryptographic algorithms. Every image can be represented as a matrix where each pixel value is stored as an element of a matrix. The rotation of the matrix defines that a matrix is rotated in the XY-plane to a certain angle concerning the x-axis about the origin. A rotation matrix is a transformation matrix in linear algebra that is used to make a rotation in Euclidean space. The rotation of the matrix includes transformation such that it requires additional memory for a new transformed value. This paper describes the in-place matrix rotation of square matrix using 45° rotation of information. In-place algorithm alters the input without requiring additional memory. A little amount of additional memory could be needed for the implementation of an in-place algorithm. However, the amount of memory required should be consistent and not dependent on the size of the input. With the help of In-place Matrix Rotation (IMR) of the complementary angle, the IMR of 45° is proved. In IMR, the elements change their positions, but the elements remain the same in the matrix. Using IMR is the matrix dimensions are changed with the center fixed to a particular position just by rotating the matrix not transforming the position. © 2023 The Authors. Published by Elsevier B.V.

关键词： Matrix algebra

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JARVIS - Smart AI Support System

JARVIS - Smart AI Support System

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Electrical Power engineering, Communication and Computing Technology(ODICON), Odisha International Conference on

作者： V. Ramya Manaswi Meduri Saketh Mandumula Sai Ravi Tejha Atluri Sai Karthikeya Dharani Chandra Prakash Ahmad Alkhayyat Dept. of Computer Science Engineering Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India Dept. of computer science engineering with specialisation of cybersecurity GITAM university Hyderabad India Dept. of Electronics & Communication Engineering K.G Reddy College of Engineering and Technology Hyderabad Telangana India Dept. of computers Techniques engineering College of technical engineering The Islamic University Najaf Iraq

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

The JARVIS AI Support System represents a remarkable fusion of modern technology, blending a sophisticated GUI design, seamless voice control, and inventive features like the captivating “Air Canvas” facilitated by OpenCV. This AI-driven virtual assistant offers users a natural and intuitive experience, allowing them to effortlessly perform tasks such as browsing the web, interacting with a chatbot, and executing dynamic voice- controlled actions. Moreover, the system showcases advanced capabilities including motion detection and facial recognition with an accuracy of 95% in multiple runs. Leveraging the power of computer vision, the Air Canvas feature empowers users to express creativity through fluid hand gestures, while voice commands effortlessly manage diverse tasks. This innovative project presents an approachable way to interact with technology in the world of AI.

关键词： Emotion recognition Video on demand Speech recognition Chatbots Motion detection Internet of Things Web sites Security Artificial intelligence Graphical user interfaces

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