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Deep Learning and SVM-Based Approach for Indian Licence Plate Character Recognition

computers, Materials & Continua 2023年第1期74卷 881-895页

作者： Nitin Sharma Mohd Anul Haq Pawan Kumar Dahiya B.R.Marwah Reema Lalit Nitin Mittal Ismail Keshta Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Electronics&Communication Engineering DCRUST Murthal131039India Department of Transportation Engineering IITKanpur208016Uttar PradeshIndia Department of Computer Science Applications PIETSmalkha132102India Skill Faculty of Science and Technology Shri Vishwakarma Skill UniversityPalwal121102India Computer Science and Information Systems Department College of Applied SciencesAlMaarefa UniversityRiyadhSaudi Arabia

Every developing country relies on transportation,and there has been an exponential expansion in the development of various sorts of vehicles with various configurations,which is a major component strengthening the automobile *** is a developing country with increasing road traffic,which has resulted in challenges such as increased road accidents and traffic oversight *** the lack of a parametric technique for accurate vehicle recognition,which is a major worry in terms of reliability,high traffic density also leads to mayhem at checkpoints and toll plazas.A system that combines an intelligent domain approach with more sustainability indices is a better way to handle traffic density and transparency *** Automatic Licence Plate Recognition(ALPR)system is one of the components of the intelligent transportation system for traffic *** study is based on a comprehensive and detailed literature evaluation in the field of *** major goal of this study is to create an automatic pattern recognition system with various combinations and higher accuracy in order to increase the reliability and accuracy of identifying digits and alphabets on a car *** research is founded on the idea that image processing opens up a diverse environment with allied fields when employing distinct soft techniques for *** properties of characters are employed to recognise the Indian licence plate in this *** licence plate recognition,more than 200 images were analysed with various parameters and soft computing techniques were *** comparison to neural networks,a hybrid technique using a Convolution Neural Network(CNN)and a Support Vector Machine(SVM)classifier has a 98.45%efficiency.

关键词： Intelligent transportation system automatic license plate recognition system neural network random forest convolutional neural network support vector machine

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Possibility of Profit Gain in Futures Cryptocurrency Trading Plans Using a Patterned Dataset Model under Moon Conditions 10

Possibility of Profit Gain in Futures Cryptocurrency Trading...

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10th IEEE information Technology International Seminar, ITIS 2024

作者： Parlika, Rizky Isnanto, R. Rizal Rahmat, Basuki Universitas Diponegoro Doctoral Programe of Information Systems Semarang Indonesia University of Pembangunan Nasional "Veteran"Jawa Timur Faculty of Computer Science Department of Information System Surabaya Indonesia

ISBN: (纸本)9798331521295

Among the various components of cryptocurrency trading are futures (2-way trading based on short or long contracts) and spot schemes (which operate in the same direction as buying and selling crypto assets). The futures scheme transaction was selected for this study's test since it frequently results in trades with comparatively larger swings than spot scheme deals. If these variations are not correctly anticipated, they may result in losses. Real-time position reading for cryptocurrency trading is made possible by the Patterned Dataset Model. Based on observations of the pattern of influence that Bitcoin price changes have on a variety of other cryptocurrency asset values in a trading market, this model was developed. Three types of data are generated by this model, and they are mined nonstop every few seconds. The entire conditions (a mix of moon and crash conditions), price increase conditions (moon), and price fall conditions (crash) make up the patterned dataset. In this study, the topic of discussion is patterned datasets in rising price (moon) environments. It is possible to demonstrate the possibility of reasonably consistent gains from short contract purchase positions using the Patterned Dataset in Moon Conditions. © 2024 IEEE.

关键词： Marketplaces

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Enhancing handwritten text feature extraction through key point detection and graph representation

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Soft Computing 2024年第21期28卷 12977-12990页

作者： Rahman, Atta Ur Alahmadi, Tahani Jaser Alsenani, Yousef S. Ali, Sania Faculty of Computer Science and Engineering Ghulam Ishaq Khan Institute of Engineering Sciences and Technologies P.O. Box 23460 Topi Pakistan P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Computer Science University of Science and Technology Bannu P.O. Box 28100 Khyber Pakhtunkhwa Bannu Pakistan

Handwriting typically consists of a wide range of writing forms with substantial differences in the placements and size of those writing shapes. The arrangement, organization, and spatial association of individual letters, words, and phrases on a written page are all examples of handwritten text structure. This study proposed a novel approach in which a handwritten text structure is primarily transformed into a Cartesian XY-coordinate system while maintaining its shape characteristics. The points on the contour of handwritten text with local maximum bending values are considered hypothetical breakdown points called Key Points (KPs). From the skeletal representation of handwriting, this approach first identifies KPs and their coordinate positions. After that, KPs are transformed into a graph-based representation with vertices and edges. With the use of geometric graphs, this representation attempts to capture the spatial and temporal organization of handwriting. Previous techniques focused on statistical methods, which offer fixed-size descriptions;however, graph-based representations are flexible in size and reveal the relationship between text structure. Graph representations enable the incorporation of contextual information by integrating extra features which improve text accuracy and understanding. The proposed approach is tested for writer identification and verification tasks on four benchmark datasets (CERUG-EN, CVL, Firemaker, and IAM) and one custom-built dataset. The findings demonstrated that the proposed approach obtained state-of-the-art accuracies across all the mentioned datasets. Particularly, it achieved the highest accuracy of 99.75% for identification and 99.81% for verification on the Firemaker dataset. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Feature extraction

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Comprehensive Rubrics for Evaluating computer-Related Capstones 2

Comprehensive Rubrics for Evaluating Computer-Related Capsto...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Atoum, Ibrahim Innab, Nisreen Alghayadh, Faisal Alahmari, Mona Alrowili, Reem Alshehri, Afnan College Of Applied Sciences AlMaarefa University Computer Science And Information Systems Department Riyadh Saudi Arabia Arab East Colleges For Graduate Studies Arab East Colleges Computer Science Department Riyadh Saudi Arabia

ISBN: (纸本)9798350394962

The capstone projects for computing primary students require the embodiment of the skills and ideas learned by developing specific solutions to some existing challenges. This project must follow an organized and elaborate life cycle to reach the required solution. This task ends with the production of applicable software and a document showing the production stages of this work, which will be presented orally. During this scientific paper, we will evaluate all the forms and models of assessment used and their relevance to the student's level at the undergraduate level. (Abstract) © 2024 IEEE.

关键词： Life cycle

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Modified Aquila Optimizer Feature Selection Approach and Support Vector Machine Classifier for Intrusion Detection System

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Multimedia Tools and Applications 2024年第21期83卷 59887-59913页

作者： Abualigah, Laith Ahmed, Saba Hussein Almomani, Mohammad H. Zitar, Raed Abu Alsoud, Anas Ratib Abuhaija, Belal Hanandeh, Essam Said Jia, Heming Elminaam, Diaa Salama Abd Elaziz, Mohamed Abd Computer Science Department Al Al-Bayt University Mafraq25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman19328 Jordan MEU Research Unit Middle East University Amman11831 Jordan Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya27500 Malaysia Department of Mathematics Facility of Science The Hashemite University P.O box 330127 Zarqa13133 Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi Abu Dhabi United Arab Emirates Department of Computer Science Wenzhou-Kean University Wenzhou China Department of Computer Information System Zarqa University P.O. Box 13132 Zarqa Jordan School of Information Engineering Sanming University Sanming365004 China Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Benha12311 Egypt Computer Science Department Faculty of Computer Science Misr International University Cairo12585 Egypt Faculty of Computer Science & Engineering Galala University Suze435611 Egypt Ajman University Ajman346 United Arab Emirates Department of Mathematics Faculty of Science Zagazig University Zagazig44519 Egypt

With the ever-expanding ubiquity of the Internet, wireless networks have permeated every facet of modern life, escalating concerns surrounding network security for users. Consequently, the demand for a robust Intrusion Detection System (IDS) has surged. The IDS serves as a critical bastion within the security framework, a significance further magnified in wireless networks where intrusions may stem from the deluge of sensor data. This influx of data, however, inevitably taxes the efficiency and computational speed of IDS. To address these limitations, numerous strategies for enhancing IDS performance have been posited by researchers. This paper introduces a novel feature selection method grounded in Support Vector Machine (SVM) and harnessing the innovative modified Aquila Optimizer (mAO) for Intrusion Detection systems in Wireless Sensor Networks. To evaluate the efficacy of our approach, we employed the KDD'99 dataset for testing and benchmarking against established methods. Multiple performance metrics, including accuracy, detection rate, false alarm rate, feature count, and execution time, were utilized for assessment. Our comparative analysis reveals the superiority of the proposed method, with standout results in terms of feature reduction, detection accuracy, and false alarm mitigation, yielding significant improvements of 11%, 98.76%, and 0.02%, respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2023.

关键词： Network security

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Towards Eco-Sustainability and Green Analytics Model to Measure the Performance of Big Data systems 9

Towards Eco-Sustainability and Green Analytics Model to Meas...

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9th International Conference on information Management, ICIM 2023

作者： Jusoh, Yusmadi Yah Abdullah, Rusli Nor, Rozi Nor Haizan Yahaya, Jamaiah Hj. Muhammad, Shireen Arunachalam, Aishwharya Raani Universiti Putra Malaysia Faculty of Computer Science and Information Technology Dept. of Software Engineering and Information Systems Serdang Malaysia Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi Malaysia Faculty of Communication Selangor Malaysia

ISBN: (纸本)9798350336382

Many BDS is doomed to failure because of the missing knowledge on measuring the performance of BDS. The failure to identify the performance measurement and correct will make the problems worsen. This will complicate the efforts of fixing such problems and more importantly, will affect the quality of knowledge, insights, and results expected by the users in the future. In achieving durable performance, the organization needsto understand the factors that contribute to the performance of the eco-sustainability and green analytics metrics for BDS. Although the existence of its importance and awareness was largely neglected. Therefore, the eco-sustainability and green analytic measurement of the BDS is examined in this research. Measuring the BDS performance has the benefit of identifying problems and launching corrective actions before these problems happen and become worsen. The research will investigate the eco-sustainability and green analytic measures which will be proposed and used to capture performance for each process of BDS. Then, based on such measures and metrics, as well as existing performance concepts, frameworks, and models, a measurement model for BDS will be created. The model will be validated through expert evaluations and confirmatory studies with users and practitioners of BDS users. The research has a greater significance in leveraging existing performance concepts in BDS settings and the research proposes users' participation in the sustainability and continuous performance evaluation of theirBDS. © 2023 IEEE.

关键词： Big data

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Deep learning on medical image analysis

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CAAI Transactions on Intelligence Technology 2025年第1期10卷 1-35页

作者： Jiaji Wang Shuihua Wang Yudong Zhang School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Biological Sciences Xi'an Jiaotong-Liverpool UniversitySuzhouJiangsuChina Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia School of Computer Science and Engineering Southeast UniversityNanjingJiangsuChina

Medical image analysis plays an irreplaceable role in diagnosing,treating,and monitoring various *** neural networks(CNNs)have become popular as they can extract intricate features and patterns from extensive *** paper covers the structure of CNN and its advances and explores the different types of transfer learning strategies as well as classic pre-trained *** paper also discusses how transfer learning has been applied to different areas within medical image *** comprehensive overview aims to assist researchers,clinicians,and policymakers by providing detailed insights,helping them make informed decisions about future research and policy initiatives to improve medical image analysis and patient outcomes.

关键词： CNN deep learning medical image transfer learning

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A Cost-Effective Approach for NDN-Based Internet of Medical Things Deployment

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computers, Materials & Continua 2022年第1期70卷 233-249页

作者： Syed Sajid Ullah Saddam Hussain Abdu Gumaei Mohsin SAlhilal Bader Fahad Alkhamees Mueen Uddin Mabrook Al-Rakhami Department of Information Technology Hazara University MansehraKPK21120Pakistan Research Chair of Pervasive and Mobile Computing Department of Information SystemsKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science Faculty of Applied SciencesTaiz UniversityTaiz6803Yemen Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Digital Science Faculty of ScienceUniversiti Brunei DarussalamJln Tungku linkGadongBruneiBE1410Darussalam

Nowadays,healthcare has become an important area for the Internet of Things(IoT)to automate healthcare facilities to share and use patient data anytime and anywhere with Internet *** present,the host-based Internet paradigm is used for sharing and accessing healthcare-related ***,due to the location-dependent nature,it suffers from latency,mobility,and *** this purpose,Named Data Networking(NDN)has been recommended as the future Internet paradigm to cover the shortcomings of the traditional host-based Internet ***,the novel breed lacks a secure framework for *** article constructs an NDN-Based Internet of Medical Things(NDN-IoMT)framework using a lightweight certificateless(CLC)*** adopt the Hyperelliptic Curve Cryptosystem(HCC)to reduce cost,which provides strong security using a smaller key size compared to Elliptic Curve Cryptosystem(ECC).Furthermore,we validate the safety of the proposed scheme through *** cost-efficiency,we compare the designed scheme with relevant certificateless signature *** final result shows that our proposed scheme uses minimal network ***,we deploy the given framework on NDN-IoMT.

关键词： Internet of Medical Things healthcare Named Data Networking

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No More Binge Learning - Using Gamification Elements to Support Distributed Practice in Engineering Education

No More Binge Learning - Using Gamification Elements to Supp...

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IEEE Education Engineering (EDUCON)

作者： Isabel John Anne Hess Tobias Fertig Faculty of Computer Science and Business Information Systems Technical University of Applied Sciences Würzburg-Schweinfurt

ISBN: (数字)9798331539498

ISBN: (纸本)9798331539504

An effective technique to support sustainable learning is distributed practice, a method shown to enhance long-term knowledge retention. As part of our research agenda, we aim to investigate suitable design strategies for eLearning courses that support distributed practice through intrinsic motivation. Our most recent strategy followed the idea of linking the acquisition of badges gained by completing a set of quizzes with a small extrinsic reward, a small bonus in the exam grade. We built a course with quizzes and timed badges with staged deadlines for the badges to ensure students do the quizzes during the semester and not shortly before the exam. An initial evaluation of this course design yielded encouraging results. The assessment showed that students learned a great deal from the quizzes and were highly motivated by the quizzes and by receiving the badges. Qualitative feedback highlighted increased motivation, increased engagement, and lower levels of perceived stress among students, who attributed these changes to the platform's ability to make learning more enjoyable and less monotonous. This paper argues that the strategic use of gamification in engineering education can significantly support distributed practice by creating an interactive, motivating, and supportive learning environment.

关键词： Electronic learning Refining Buildings Hybrid learning Engineering education Stress Portfolios Software engineering

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Security model to identify block withholding attack in blockchain

Security model to identify block withholding attack in block...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Keshta, Ismail Reegu, Faheem Ahmad Ahmad, Adeel Saxena, Archana Chandan, Radha Raman Mahalakshmi, V. Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia Department of Computer Applications Invertis University UP Bareilly India Department of Computer Science and Engineering Shambhunath Institute of Engineering and Technology College Jhalwa Prayagraj India Department of Computer Science College of Computer Science and Information Technology Jazan University Jazan Saudi Arabia

ISBN: (纸本)9781032669663

Block interception attack, also known as block withholding attack, is an attack method in the blockchain. The attacker penetrates the target mining pool for passive mining to destroy the target mining pool. This paper briefly introduces the mining mechanism and the working principle of block interception attack, summarizes several models of block interception attack, studies the attack methods and benefits of the existing block interception attack models, and analyses their attack effects. A block interception attack model is constructed to increase the rate of return while increasing the rate of return. The completed model is verified through simulated mining experiments. The typical and made models are compared and analyzed based on the rate of return. Finally, the applicable environments of different attack models are given based on the experimental results. © 2024 The Author(s).

关键词： Blockchain

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