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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Khandari, Harsimrat Sahoo, Girija Shankar Raja Praveen, K.N. Shree, Ritu Umamaheswari, B. Yashwant, V. Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350319125

With the constantly growing volume of facts being produced, conventional data evaluation structures are regularly insufficient in terms of presenting an correct overview of the most modern-day data. The utilization of system mastering provides the potential to create an improved real-time records evaluation device this is more able to making experience of and knowledge the records. The development of an progressed actual-time statistics evaluation device utilizing system studying can hugely enhance statistics analysis techniques by means of integrating relevant data and structured analyses of the identical. this will include strategies inclusive of natural language processing and clustering algorithms to perceive trends, sentiment evaluation to understand customer feedback, and predictive analytics to better perceive areas for improvement. Moreover, the realtime statistics analysis system can be further enhanced by means of incorporating AI to make extra correct predictions, as well as reinforcement studying to evolve present models as new statistics is integrated. this would allow the system to learn more efficaciously and modify its algorithms to continually enhance its overall performance. Universal, by using machine studying to develop an advanced actual-time statistics evaluation system, extra correct and comprehensive insights can be generated from information, and groups can use this facts to better tell their choice making. moreover, temporal records evaluation can be advanced with faster response times as a result of the device being able to process records © 2023 IEEE.

关键词： Statistics

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A nano-scale design of a multiply-accumulate unit for digital signal processing based on quantum computing

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Optical and Quantum Electronics 2024年第1期56卷 1-25页

作者： Ahmadpour, Seyed-Sajad Navimipour, Nima Jafari Yalcin, Senay Bakhshayeshi Avval, Danial Ain, Noor Ul Department of Computer Engineering Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou 64002 Taiwan Department of Computer Engineering Nisantasi University Istanbul Turkey Department of Information Systems Engineering Sakarya University Sakarya Turkey Department of Business Administration Kadir Has University Istanbul Turkey

Digital signal processing (DSP) is used in computer processing to conduct different signal-processing tasks. The DSPs are used in the series numbers representing a continuous variable in a domain such as time, area, or frequency. The multiply-accumulate (MAC) unit is crucial in various DSP applications, including convolution, discrete cosine transform (DCT), Fourier Transform, etc. Thus, all DSPs contain a critical MAC unit in signal processing. The MAC unit conducts multiplication and accumulation operations for continuous and complicated DSP application processes. On the other hand, in the MAC structure, the stability of the circuit and the occupied area pose some significant challenges. However, high-performance quantum technology can easily overcome all the previous shortcomings. Hence, this paper suggests an efficient MAC for DSP applications using a Vedic multiplier, half adder, and accumulator based on quantum technology. All the proposed structures have used a single-layer layout without rotated cells. The suggested architecture is designed and validated based on the QCADesigner 2.0.3 tool. The findings revealed that all the developed circuits have a simple architecture with fewer quantum cells, optimal area, and low latency. © 2023, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Multiply-accumulate (MAC) Nano-design Quantum dot cellular automata (QCA) Signal processing

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Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing

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computer Systems science & engineering 2022年第5期41卷 479-492页

作者： A.S.Anakath R.Kannadasan Niju P.Joseph P.Boominathan G.R.Sreekanth School of Computing E.G.S.Pillay Engineering CollegeNagapattinam611002TamilnaduIndia Department of Software Systems School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of Computer Science CHRIST(Deemed to be University)Bengaluru560029India Department of Information Security School of Computer Science and Engineering(SCOPE)Vellore Institute of Technology UniversityVellore632014TamilnaduIndia Department of Computer Science and Engineering Kongu Engineering CollegeErode638060TamilnaduIndia

Cloud computing is a high network infrastructure where users,owners,third users,authorized users,and customers can access and store their information *** use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing *** cloud is nowadays highly affected by internal threats of the *** applications such as banking,hospital,and business are more likely affected by real user *** intruder is presented as a user and set as a member of the *** becoming an insider in the network,they will try to attack or steal sensitive data during information sharing or *** major issue in today's technological development is identifying the insider threat in the cloud *** data are lost,compromising cloud users is *** and security are not ensured,and then,the usage of the cloud is not *** solutions are available for the external security of the cloud ***,insider or internal threats need to be *** this research work,we focus on a solution for identifying an insider attack using the artificial intelligence *** insider attack is possible by using nodes of weak users’*** will log in using a weak user id,connect to a network,and pretend to be a trusted ***,they can easily attack and hack information as an insider,and identifying them is very *** types of attacks need intelligent solutions.A machine learning approach is widely used for security *** date,the existing lags can classify the attackers *** information hijacking process is very absurd,which motivates young researchers to provide a solution for internal *** our proposed work,we track the attackers using a user interaction behavior pattern and deep learning *** usage of mouse movements and clicks and keystrokes of the real user is stored in a *** deep belief neural

关键词： Cloud computing security insider attack network security privacy user interaction behavior deep belief neural network

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Text Extraction with Optimal Bi-LSTM

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computers, Materials & Continua 2023年第9期76卷 3549-3567页

作者： Bahera H.Nayef Siti Norul Huda Sheikh Abdullah Rossilawati Sulaiman Ashwaq Mukred Saeed Computer Techniques Engineering Department Ibn Khaldun University CollegeBaghdad10011Iraq Faculty of Information Science and Technology Universiti Kebangsaan MalaysiaBangiSelangor43600Malaysia School of Electrical Engineering and Artificial Intelligence Xiamen University MalaysiaSepang43900Malaysia

Text extraction from images using the traditional techniques of image collecting,and pattern recognition using machine learning consume time due to the amount of extracted features from the *** Neural Networks introduce effective solutions to extract text features from images using a few techniques and the ability to train large datasets of images with significant *** study proposes using Dual Maxpooling and concatenating convolution Neural Networks(CNN)layers with the activation functions Relu and the Optimized Leaky Relu(OLRelu).The proposed method works by dividing the word image into slices that contain *** pass them to deep learning layers to extract feature maps and reform the predicted *** Short Memory(BiLSTM)layers extractmore compelling features and link the time sequence fromforward and backward directions during the training *** Connectionist Temporal Classification(CTC)function calcifies the training and validation loss *** addition to decoding the extracted feature to reform characters again and linking them according to their time *** proposed model performance is evaluated using training and validation loss errors on the Mjsynth and Integrated Argument Mining Tasks(IAM)*** result of IAM was 2.09%for the average loss errors with the proposed dualMaxpooling and *** the Mjsynth dataset,the best validation loss rate shrunk to 2.2%by applying concatenating CNN layers,and Relu.

关键词： Deep neural network text features dual max-pooling concatenating convolution neural networks bidirectional long short memory text connector characteristics

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Competency Comparison of Deep Neural Networks for Identifying Gender in Color Fundus Photographs 26

Competency Comparison of Deep Neural Networks for Identifyin...

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26th International Conference on computer and information technology, ICCIT 2023

作者： Arif Khan, Md. Ahanaf Hasnain Ali, Md. Saha, Nirjor Shakib Shoumik, Md. Sadman Biswas, Sangeeta University of Rajshahi Department of Computer Science & Engineering Rajshahi6205 Bangladesh Brno University of Technology Faculty of Information Technology Brno61200 Czech Republic

ISBN: (纸本)9798350359015

Retina specialists and researchers have been using color fundus photographs for almost 100 years for diagnosing retinal diseases, systemic disorders and recognizing humans. In 2018, researchers for the first time showed that gender identification can also be done by color fundus photographs using a deep neural network (DNN). Subsequent studies further confirmed the capability of DNNs in fundus photograph-based gender identification. However, the findings of these studies cannot be directly comparable with each other, since different datasets were used in different studies. In this paper, we conduct a competency comparison of six DNNs in gender identification by using a single dataset of color fundus photographs. © 2023 IEEE.

关键词： Deep Neural Networks Fundus Images Gender Retina

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PROBEXPERT: An Enhanced Q&A Platform for Reducing Time Spent on Learning and Finding Answers 7

PROBEXPERT: An Enhanced Q&A Platform for Reducing Time Spent...

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7th IEEE International conference for Convergence in technology, I2CT 2022

作者： Thennakoon, Kamal Ekanayake, Dasun Marapana, Thanura Ranasinghe, Ashen Wijendra, Dinuka R. Gamage, Anjalie Sri Lanka Institute of Information Technology Department of Computer Science & Software Engineering Malabe Sri Lanka

ISBN: (纸本)9781665421683

The World Wide Web contains a wide range of material from a variety of fields. However, when concerns towards the computer science domain, information users find on the internet may not be up-to-date due to the rapid pace of change and having to spend less time on the internet for researching and debugging tasks is an added luxury. Having an expertise level while providing answers through a platform is convenient for users, yet when a user signs into a platform, the user must start from the beginning, regardless of the level of competence in the field. Moreover, not having a proper way to evaluate the existing programming knowledge is another obstacle. To address mentioned complications, researchers of this paper have introduced a new e-learning platform- 'ProbExpert'. The platform has been constructed with machine learning and deep learning approaches such as NLP, keyword extraction, semantic information analysis, cosine similarity, and information summarization. With aforesaid technologies, ProbExpert provides systems in automated answering, optimized answer generation, structured question-based quiz evaluation together with a fully automated portfolio generation with a novel user ranking algorithm based on the bell curve. © 2022 IEEE.

关键词： Automation

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Development of an Educational Game Visual Novel Introduction to Traditional Dance Based on Android: Case Study of Typical Dance of Lombok Island 6

Development of an Educational Game Visual Novel Introduction...

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6th International Conference on computer and Informatics engineering, IC2IE 2023

作者： Susilowati, Dyah Chani Saputri, Dian Syafitri Rahim, Abdul Sujaka, Tomi Tri Wardhana, Helna Husnita, Sausan Rosanensi, Melati Augustin, Kartarina Bumigora University Department of Information Technology Education Mataram Indonesia Bumigora University Department of Software Engineering Mataram Indonesia Bumigora University Department of Computer Science Mataram Indonesia

ISBN: (纸本)9798350345162

This research aims to produce a practical Visual Novel Game learning media. This research is development research with the Multimedia Development Life Cycle (MDLC) method, including 4 stages, namely concept, design, material collection, manufacture, testing, and distribution. The subjects in this study were elementary school students, dance teachers, and songwriters with a purposive sampling technique. The data collection instrument was a questionnaire sheet. The analysis technique uses quantitative descriptive statistics and percentages. The results of testing the functionality of the application from black box testing show the results of the Visual Novel Game learning media are appropriate. The last test on the black box using the User Acceptance Test (UAT) shows the user satisfaction with Visual Novel Game learning media with very good results. The application feasibility results show very good with a percentage of 87.76% and the usability of the application shows very good with a percentage of 90.03%. The visual novel educational game adds insight into the typical dances of Lombok Island with a score of 92%, helps students understand the meaning of the Beriuk Tinjal dance with a score of 92%, and makes learning easy and fun with a score of 92%. © 2023 IEEE.

关键词： android educational game traditional dance visual novel

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A Novel Cryptocurrency Prediction Method Using Optimum CNN

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computers, Materials & Continua 2022年第4期71卷 1051-1063页

作者： Syed H.Hasan Syeda Huyam Hasan Mohammed Salih Ahmed Syed Hamid Hasan Iowa State University AmesUSA University of Texas at Arlington USA Department of Computer Engineering College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

In recent years,cryptocurrency has become gradually more significant in economic regions *** cryptocurrencies,records are stored using a cryptographic *** main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social *** is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media ***,this work focuses on extracting Tweets and gathering data from different sources to classify them into positive,negative,and neutral categories,and further examining the correlations between cryptocurrency movements and Tweet *** paper proposes an optimized method using a deep learning algorithm and convolution neural network for cryptocurrency prediction;this method is used to predict the prices of four cryptocurrencies,namely,Litecoin,Monero,Bitcoin,and *** results of analyses demonstrate that the proposed method forecasts prices with a high accuracy of about 98.75%.The method is validated by comparison with existing methods using visualization tools.

关键词： Cryptocurrency litecoin monero bitcoin ethereum twitter optimal CNN price prediction sentiment analysis

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Uncovering the Hidden Insights of the Government AI Readiness Index: Application of Fuzzy LMAW and Schweizer-Sklar Weighted Framework

Decision Making: Applications in Management and Engineering

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Decision Making: Applications in Management and engineering 2024年第2期7卷 443-468页

作者： Nasution, Mahyuddin K. M. Elveny, Marischa Pamucar, Dragan Popovic, Milena Gušavac, Bisera Andric Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan20155 Indonesia Data Science & Artificial Intelligence Fasilkom-TI Universitas Sumatera Utara Medan20155 Indonesia University of Belgrade Faculty of Organizational Science Department of Operations Research and Statistics Jove Ilica 154 Belgrade Serbia Department of Mechanics and Mathematics Western Caspian University Baku Azerbaijan School of Engineering and Technology Sunway University Selangor Malaysia

There is considerable promising in artificial intelligence (AI) and algorithms, with governments worldwide increasingly investing in this transformative technology. The potential benefits include improved performance, cost reduction, efficient management, and crime prediction and prevention, among others. The AI era holds the promise of revolutionizing various aspects of society. However, as countries prepare to leverage the power of artificial intelligence, questions arise about the validity of rankings published on the readiness of the governments for the application of AI. In this article, the weighting criteria that are analysed in the Oxford Insights AI Readiness Index are scrutinized, aiming to provide a more accurate assessment. Instead of conventional averaging, arithmetic and geometric non-linear functions are employed to analyse and assess the rank of the countries. Through clustering analysis, countries are categorized into three distinct groups based on observed criteria, offering a nuanced perspective on government AI readiness. This clustering approach not only facilitates a more effective categorization of countries based on their AI preparedness, but also accentuates the variations and similarities within each cluster, which enables deeper insights into regional trends and pinpoint targeted strategies for enhancement within each cluster. © 2024 Regional Association for Security and crisis management. All rights reserved.

关键词： Cost reduction

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E-tutor: Comprehensive Student Productivity Management System for Education 4

E-tutor: Comprehensive Student Productivity Management Syste...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Silva, Kumuditha Induwara, Rashmin Wimukthi, Malshan Poornika, Sathsarani Samaratunge Arachchillage, Udara Srimath S. Jayalath, Thilini Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

With the advancement of technology, e-learning has emerged as predominant in the education sector. As students, parents, and educators acknowledged, adopting e-learning can offer several benefits over traditional learning techniques. Since more individuals are becoming acclimated to online learning platforms, these online platforms can provide a simple, instructive, and efficient mode of delivery. This novel approach could be improved with the aid of Artificial Intelligence (AI) to comprehend consumers more thoroughly and provide valuable and better-suited services. Most sectors in education, including universities, swiftly adapted to new educational methodologies because of their flexibility and productivity. Nevertheless, there are some downsides that young demography experiences, such as less instructiveness, distraction due to the absence of teachers, and poor IT literacy. Consequently, these drawbacks would recede the capability of students to assimilate content during the lecture. Therefore, the main objective of this research is to implement an E-learning platform with AI learning analytics to enhance students' performance regularly while reducing the significant drawbacks of the E-learning platforms. This research consists of students' focus detection, essay-based answer evaluation, note summarization, mind map generation, and personalized guidance facilities. © 2022 IEEE.

关键词： Object detection

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