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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Walke, Suchita Nalluri, Mounika Lavanya, R. Rongali, Aruna Sri Vanjari, Hrishikesh Bhanudas Ritu Pillai Collage of Engg and Technology Mumbai University Computer Engineering India Murray State University Masters in Computer Information Systems United States Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Ece India Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology University of the Cumberlands United States BVCOE Lavale Sppu Pune E &tc Engineering Dept Maharashtra India Ambala Haryana Mullana India

ISBN: (纸本)9798350357769

there are numerous distinct strategies and techniques that fall under the huge class of neural network-primarily based deep gaining knowledge of in device getting to know. those strategies revolve around developing and schooling synthetic neural networks, that are computational models that mimic the capabilities and structure of the human brain, to analyze huge datasets and make predictions or decisions based totally on the *** of the key challenges in actual-time information analysis is being capable of method incoming information fast and efficiently, as well as adapt to converting data styles or sudden occasions. traditional device learning algorithms are frequently restricted in their ability to deal with these demanding situations, that is in which deep gaining knowledge of techniques are available *** getting to know techniques contain education neural networks with a couple of layers, every of which strategies one-of-a-kind aspects of the data. This lets in for greater complex and accurate evaluation of the facts, in addition to the potential to handle larger and more numerous datasets. One famous method in deep studying is known as convolutional neural networks (CNNs). Those networks are specifically properly-suitable for studying visual information, including snap shots, by means of breaking down the data into smaller parts and studying them at one of a kind ranges of abstraction. This permits for the identification of patterns and features in the data which could then be used for category or prediction responsibilities. © 2023 IEEE.

关键词： actual-time convolutional neural networks numerous prediction synthetic neural networks

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Traffic Congestion Prevention Using Ant Colony Optimization

Traffic Congestion Prevention Using Ant Colony Optimization

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Renewable Energy & Sustainability (ieCRES), International engineering Conference on

作者： Aiman AbuSamra Abeer Ashour Mai Ghazal Jehad Aldahdooh Raghad Abuarja Computer Engineering Dept. Islamic University of Gaza Gaza Palestine Doctoral Programme in Computer Science University of Helsinki Helsinki Finland Computer Engineering Islamic University of Gaza Gaza Palestine

Managing traffic congestion is crucial for improving mobility, reducing fuel consumption, and mitigating environmental impacts in urban areas. To address this challenge, we present a novel framework named TCP-ACO for detecting traffic congestion that classifies congestion into three distinct types: expected, unexpected, and real-time. The framework utilizes data from various sources, including databases, Ant colony optimization (ACO) systems, and computer vision techniques, to precisely detect and handle traffic congestion. Expected congestion is identified by analyzing historical traffic data and scheduled events, while unexpected congestion is detected by leveraging real-time data from ACO systems. Real-time congestion is detected by employing computer vision techniques, such as analyzing video footage from cameras or drones. The proposed framework has the potential, by recognizing and managing various types of congestion, to improve traffic flow, shorten travel times, and decrease environmental impacts. Additionally, it also offers a precise and effective solution for traffic congestion detection, which is a crucial aspect of smart city traffic management systems. Our analysis shows that the ACO algorithm adapted in TCP-ACO is more effective in finding the shortest path between two cities (result obtained: 4.014) compared to the result obtained from the shortest path technique compounded with computer vision (which yields a score of 6.224 when the path is free). This indicates the effectiveness of the proposed framework in addressing the challenges of traffic congestion, offering a promising solution for smart city traffic management systems to improve mobility and reduce environmental impacts in urban areas.

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Reversible JPEG Data Hiding Based on EMD

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通讯和计算机（中英文版） 2012年第10期9卷 1135-1141页

作者： Wen-Chung Kuo Shao-Hung Kuo Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Yunlin 672 Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Yunlin 640 Taiwan

As the rapid growth of smart phone technology, people have a lot of digital image information such as digital photos or videos. Both data hiding and data compression are very important technologies in image processing field. On the overview, it seems that there is no relationship between data hiding and data compression because data hiding mechanisms focus on information security and data compression mechanisms emphasize the compression ratio. However, the more secret data is embedded, the more capacity the stego image increases. Actually, they are closely related. Until now, there are many literatures to discuss the secret data how to be embedded into the media image and keeps the original capacity as soon as possible. In this paper, a reversible data hiding scheme based on EMD data hiding and JPEG (Joint Picture Experts Group) compression technology will be proposed. According to experimental results, the authors can prove that our proposed scheme maintains high embedding capacity, security and good compression ratio.

关键词：数据隐藏 JPEG EMD 可逆数字图像信息数据嵌入压缩技术数据压缩

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Cross-camera complementary vehicle matching via feature expandsion for video forensics

Cross-camera complementary vehicle matching via feature expa...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Chao-Yung Hsu Chih-Yang Lin Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781467361989

In this paper, we will investigate a more challenging vehicle matching problem. The problem is formulated as invariant image feature matching among opposite viewpoints of cameras, i.e. complementary object matching. For example, a front vehicle object may be given as a query to retrieve a rear vehicle object of the same vehicle. To solve the complementary object matching, invariant image feature is first extracted based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, the ASIFT feature is expanded via a special vehicle database. As a result, cross-camera vehicle matching with the help of complementary part can be greatly improved. Experimental results demonstrate the effectiveness of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Cameras Databases Feature extraction Visualization Digital forensics

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Relevance of ISO/SAE 21434 in Vehicular Architecture Development

Relevance of ISO/SAE 21434 in Vehicular Architecture Develop...

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IEEE International Conference on Systems, Man and Cybernetics

作者： V Kethareswaran Sanjay Moulik Doctoral Researcher in the Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Assam India Assistant Professor in the Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati Assam India

Research in terms of security in vehicular architecture has been a focal point of deliberation in the automotive sector. The Automotive industry development has continuously evolved the scenario of adding more integration to networked vehicles or semi-autonomous vehicles. The end product of such manufacturing practices is a vehicle becoming a networked computer on wheels. In spite of providing numerous advantages, these developments in the automotive industry are also bringing more challenges in terms of security. Hence, the industry has been forced to emphasise the principle of Security by Design. Efforts in this direction have resulted in the formulation of the ISO/SAE 21434 standard. In this work, we focus on summarising the ISO/SAE 21434 standard and analysing its relevance for automotive architecture development. Related works in the standard's approach of Security by Design are summarised. Additionally, we propose an application work of the standard in the context of automotive Architecture development as future work.

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Authenticated secret sharing scheme based on GMEMD

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2016年 9569卷 395-405页

作者： Kuo, Wen-Chung Kuo, Shao-Hung Chang, Hong-Yi Wuu, Lih-Chyau Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Douliu Taiwan Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science and Technology Douliu Taiwan

ISBN: (纸本)9783319319599

In secret image sharing schemes, all legal participants provide legitimate shared images and then they can extract the correct secret message. Recently, Wu et al. proposed a high quality data hiding secret sharing scheme with authentication ability. The major contribution of this scheme maintains good stego image quality while being able to verify secret message integrity. However, to ensure the process can work, the secret image’s pixel values larger than 250 must be changed to 250 for Wu’s scheme. Otherwise, extracting the secret image may fail. In other words, for a secret image, a few errors do not make the big difference but it could be distorted severely for some sensitive secrets. In order to improve this shortcoming, a secret image sharing scheme based on General Multi-Exploiting Modification Direction (GMEMD) data hiding technology will be proposed in this paper. According to simulation results and analysis, we can show that the stego image quality in Wu et al.’s scheme or our proposed scheme is larger than 43dB. We also demonstrate the authentication capability to find unauthorized participants. Furthermore, if all participants are legitimate, then the proposed scheme can extract the secret completely without any distortion. © Springer International Publishing Switzerland 2016.

关键词： Authentication

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Chao-Yung Hsu Li-Wei Kang Hong-Yuan Mark Liao Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program and Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900145

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications.

关键词： Vehicles Visualization Cameras Feature extraction Transforms Robustness Forensics

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Evaluation of knowledge sharing in a collaborative software

Evaluation of knowledge sharing in a collaborative software

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5th International Multi-Conference on engineering and Technological Innovation, IMETI 2012

作者： Juliani, Douglas Juliani, Jordan De Abreu, Aline França De Souza, João Artur Postgraduate Programme in Engineering and Knowledge Management Federal University of Santa Catarina - UFSC Brazil Department of Computer Science Federal Institute of Santa Catarina - IFSC Brazil Department of Library and Information Management State University of Santa Catarina - UDESC Florianopolis Brazil

ISBN: (纸本)9781936338740

The widespread use of collaborative applications as a means of communication, research and collation of information, among others, has significantly accelerated the acquisition, dissemination, and especially the sharing of information and knowledge among individuals. Thus, understanding the factors influencing this process is crucial to the success of a software based on the contribution of people. In this research, among the various factors analyzed, it was found that the usability and the characteristics of individuals are crucial to assess knowledge sharing in a knowledge-based system, in this case, the social software PreipoPublico. We chose to use questionnaire with 23 items as an evaluation tool that, based on two existing, refurbished and was validated by pre-testing and statistical technique. Being 19 closed questions (categorical measures) and 4 open, descriptive. Results showed that users are predisposed to share their knowledge and information about product prices in the software. Still, it was shown that the system has a high degree of usability, despite some difficulties encountered by most respondents coming from the fact it is the first system to access them. The comments collected from the open questions suggest system improvements. Copyright © 2008 by the International Institute of Informatics and Systemics.

关键词： Knowledge based systems

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E-Translator Kawi to Bahasa 2

E-Translator Kawi to Bahasa

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2nd International Joint Conference on Advanced engineering and Technology, IJCAET 2017 and International Symposium on Advanced Mechanical and Power engineering, ISAMPE 2017

作者： Sudana, Oka Putra, Darma Sudarma, M. Hartati, Rukmi S. Pradnya Prastika, Ryan Wirdiani, Ayu Study Program of Doctoral Engineering Science Faculty of Engineering Udayana University Kabupaten Badung-Bali80361 Indonesia Information Technology Departement Faculty of Engineering Udayana University Kabupaten Badung-Bali80361 Indonesia Electrical and Computer EngineeringDepartement Faculty of Engineering Udayana University Jalan Raya Bukit Jimbaran Kabupaten Badung-Bali80361 Indonesia

Kawi Language is a kind of language which has developed in Java during the Hindu-Buddhist era in the ancient Indonesian archipelago. As the time passed, Kawi began to come to extinction. To overcome this, preservation of Kawi language can be done by enhancing the understanding of culture through the use of technology. Technology that can be used for cultural preservation is one of NLP based applications such as Kawi Language to Bahasa Translator Application which is developed in this research. The translator application is an application that translates from one language to another. The result of translation of the translator application is a language that is easy to understand by the people or commonly used language. This translator application is developed to processes Kawi Language text into bahasa based on search method which each word inserted. The stemming method used is Bobby Nazief & Mima Adriani Algorithm using Kawi Language rule. The translated Kawi Language text can be a word, sentence or paragraph with the result of the Text in Bahasa as well as words, sentences or paragraphs. © The Authors, published by EDP sciences, 2018.

关键词： Translation (languages)

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CLUSTERING ANALYSIS OF DEBRIS-FLOW STREAMS

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International Journal of Sediment Research 2004年第1期19卷 37-46页

作者： Yuan-Fan TSAI,Huai-Kuang TSAI,Cheng-Yan KAO Professor of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Assistant Professor of Dept. of Social Studies Education National Taipei Teachers College Taipei 106 Taiwan Post doctoral fellow of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

The Chi-Chi earthquake in 1999 caused disastrous landslides, which triggered numerous debris flows and killed hundreds of people. A critical rainfall intensity line for each debris-flow stream is studied to prevent such a disaster. However, setting rainfall lines from incomplete data is difficult, so this study considered eight critical factors to group streams, such that streams within a cluster have similar rainfall lines. A genetic algorithm is applied to group 377 debris-flow streams selected from the center of an area affected by the Chi-Chi earthquake. These streams are grouped into seven clusters with different characteristics. The results reveal that the proposed method effectively groups debris-flow streams.

关键词： Debris flow Genetic algorithm hierarchical clustering The Chi-Chi earthquake

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