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2024 International Conference on Advances in Computing Research on Science engineering and Technology, ACROSET 2024

作者： Mankar, Nikhilesh Pramod Mahure, Tushar Joshi, Anushka A. Pande, Sagar Dhanraj Khamparia, Aditya Nathe, Ankita Shrikrushna Turjman, Fadi Al Pune India Independent Researcher Amravati India Babasaheb Bhimrao Ambedkar University Department of Computer Science Amethi India Kavikulguru Institute of Technology and Science Department of Information Technology Nagpur India Ai and Robotics Institute Near East University Artificial Intelligence Software Information Systems Engineering Departments Nicosia Cyprus University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Turkey

ISBN: (纸本)9798350388800

The usage of online entertainment has increased dramatically after some time with the enhancement of the Internet and has turned into the most compelling systems administration stage in this century. Notwithstanding, the upgrade of a social network regularly makes adverse consequences on society that add to two or three terrible peculiarities, for example, online maltreatment, badgering cyberbullying, cybercrime, and internet savaging. Cyberbullying habitually prompts genuine mental and actual misery, especially for ladies and kids, and even occasionally make them to use self-destruction methods. Multiple number of episodes have as of late happened worldwide because of online badgering, like sharing private talks, bits of hearsay, and sexual comments. In this way, the distinguishing proof of harassing messages or messages via online entertainment has gained a significant measure for development for consideration with in scientists. The ground or motive for this exploration is to create a full-fledged way or a method to differentiate online harmful and tormenting drafts by combining various methods and techniques in the domain of natural language processing and AI © 2024 IEEE.

关键词： Adversarial machine learning

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Customers' sentiment on food delivery services: An Arabic text mining approach

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International Journal of Information Management Data Insights 2024年第2期4卷

作者： Mustafa, Dheya Khabour, Safaa M. Shatnawi, Ahmed S. Department of Computer Engineering Faculty of Engineering The Hashemite University Zarqa 13133 Jordan Department of Information Systems Faculty of Information Technology and Computer Sciences Yarmouk University Irbid 21163 Jordan Department of Software Engineering Jordan University of Science & Technology Irbid 21110 Jordan

The Covid-19 pandemic has accelerated the shift in organizations' strategies toward innovative online services. Customer reviews on platforms for online ordering and delivery are a vital source of information about how well a business is performing. Businesses that provide food delivery services (FDS) seek to leverage consumer input to locate areas where customer satisfaction could be raised. Sentiment analysis (SA) has been the subject of an enormous amount of English-language research. Despite Arabic's increasing popularity as a writing language on the Internet, not much study has been conducted on sentiment analysis of Arabic up to this point, with a limited number of publicly available resources for Arabic SA such as datasets and lexicons. The present study collects FDS-related reviews in Arabic to conduct extensive emotion mining, taking advantage of Natural Language Processing, feature selection, and Machine Learning techniques to elicit personal judgments, identify polarity, and recognize customers’ feelings in the FDS domain. To demonstrate that the proposed approach is suitable for analyzing human perceptions of FDS, we designed and carried out excessive experiments that assess the utility of each phase. Our highest categorization accuracy was 90 % using Mutual Information with the SVM classifier. The study's findings provide various managerial insights for improving their plans and service delivery, as well as revealing the main reasons for consumer complaints. It also demonstrates how future academics might harness the power of online business reviews in Arabic using a variety of text-mining approaches. © 2024 The Author(s)

关键词： Arabic dialects Arabic sentiments resources Consumer sentiment Features selection Food delivery services Machine learning

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RSA-1024 Cryptography on Artix-7 FPGA: Medical Imaging Application 16

RSA-1024 Cryptography on Artix-7 FPGA: Medical Imaging Appli...

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16th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2024

作者： Ghayoula, Ridha Amara, Wided Smida, Amor Fattahi, Jaouhar Waly, Mohamed I. Bahroun, Sahbi Gmati, Issam El University of Moncton Faculty of Engineering New Brunswick Canada Enit University of Tunis El Manar SysCom Laboratory Tunis Tunisia Majmaah University College of Applied Medical Sciences Majmaah Saudi Arabia Laval University Department of Computer Science && Software Engineering Quebec Canada Institut Superieur d'Informatique University of Tunis El Manar Tunis Tunisia Umm Al Qura University College of Engineering Umm Al Qura Saudi Arabia

ISBN: (纸本)9798350371154

In the domain of medical imaging, ensuring the security of confidential patient data stands as a paramount concern. The imperative for robust encryption to safeguard medical images against unauthorized access has driven the widespread adoption of the RSA algorithm, celebrated for its efficacy in data security assurance. This study specifically centers on the deployment of RSA-1024 cryptography on an Artix-7 FPGA, targeting applications in medical imaging. Acknowledging the demand for heightened security and accelerated processing, we have engineered RSA crypto-accelerators as hardware implementations of the RSA algorithm. We present a comprehensive methodology for implementing the 1024-bit RSA encryption/decryption algorithm, leveraging the square and multiply technique for modular exponentiation. Our algorithms are meticulously instantiated through VHDL code, tailored for execution on the Artix-7 xc7a35tcsg324-1 FPGA manufactured by Xilinx. Rigorous testing using the Vivado 2022.2 tool validates the functionality and dependability of our design. This research underscores the pivotal role of advanced cryptographic methodologies in safeguarding medical images and underscores the strides made in FPGA-based security solutions. © 2024 IEEE.

关键词： Field programmable gate arrays (FPGA)

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An Enhanced Authentication Protocol Suitable for Constrained RFID Systems

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IEEE Access 2024年 12卷 61610-61628页

作者： Hosseinzadeh, Mehdi Servati, Mohammad Reza Rahmani, Amir Masoud Safkhani, Masoumeh Lansky, Jan Janoscova, Renata Ahmed, Omed Hassan Tanveer, Jawad Lee, Sang-Woong Duy Tan University Institute of Research and Development Da Nang550000 Viet Nam Duy Tan University School of Medicine and Pharmacy Da Nang550000 Viet Nam Shahid Rajaee Teacher Training University Department of Computer Engineering Tehran16788-15811 Iran National Yunlin University of Science and Technology Future Technology Research Center Douliou Yunlin64002 Taiwan School of Computer Science Tehran19395-5746 Iran University of Finance and Administration Faculty of Economic Studies Department of Computer Science and Mathematics Prague101 00 Czech Republic University of Human Development Department of Information Technology Sulaymaniyah0778-6 Iraq Sejong University Department of Computer Science and Engineering Seoul05006 Korea Republic of Gachon University Pattern Recognition and Machine Learning Laboratory Department of Ai Software Seongnam-si13557 Korea Republic of

RFID technology offers an affordable and user-friendly solution for contactless identification of objects and individuals. However, the widespread adoption of RFID systems raises concerns regarding security and privacy. Vulnerabilities such as message tampering, interception, and eavesdropping pose significant risks to the integrity of the system. This study examines the effectiveness of two recently proposed ultra-lightweight RFID authentication protocols, URASP and KUAJB, in addressing these security challenges. Surprisingly, our findings reveal that both URASP and KUAJB protocols are susceptible to secret disclosure attacks, despite their claims of providing robust security. Consequently, the development of a truly ultra-lightweight protocol that ensures adequate security becomes a formidable task. As a potential solution, the enhancement of the URASP protocol through the integration of a simple cryptographic primitive is suggested to bolster its security measures. © 2013 IEEE.

关键词： Hash functions

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Improved LOPCOW-SAW Method for Optimal Supplier Selection in Supply Chain Management

Improved LOPCOW-SAW Method for Optimal Supplier Selection in...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Sumanto Sumarna Hafis Nurdin Taufik Asra Irwan Agus Sobari Herman Kuswanto Indra Chaidir Ibnu Akil Felix Wuryo Handono Informatics Faculty of Engineering and Informatics Universitas Bina Sarana Informatika Jakarta Indonesia Information System Faculty of Engineering and Informatics Universitas Nusa Mandiri Jakarta Indonesia Software Engineering Faculty of Engineering and Informatics Universitas Bina Sarana Informatika Jakarta Indonesia Information System Faculty of Engineering and Informatics Universitas Nusa Mandiri Universitas Bina Sarana Informatika Computer Engineering Faculty of Engineering and Informatics Universitas Nusa Mandiri Universitas Bina Sarana Informatika

ISBN: (数字)9798331528799

ISBN: (纸本)9798331528805

Supplier selection is a critical component of Supply Chain Management (SCM), as suppliers provide raw materials or services essential for supporting a company's operations. Traditional supplier selection methods often rely on subjective assessments to determine the weighting of criteria, which can lead to biases and suboptimal decision making. To address this issue, this study combines the Logarithmic Percentage Change of Weight (LOPCOW) method with the Simple Additive Weighting (SAW) method to enhance objectivity in the supplier selection process. The LOPCOW method is used to assign criterion weights objectively based on logarithmic percentage changes, which helps minimize subjectivity, These weights are then applied using the SAW method to evaluate and rank suppliers. The results of the study show that this combined approach is more reliable for selecting suppliers objectively and accurately. The study suggests integrating other Multi-Criteria Decision-Making (MCDM) methods to further strengthen the results while recommending the inclusion of real-time data analytics to improve the model's adaptability to dynamic market conditions. The LOPCOW-SAW approach can be applied across various industries for more effective and efficient SCM supplier selection.

关键词： Industries Analytical models Adaptation models Supply chain management Data analysis Real-time systems Data models Robustness MCDM Weighted sum model

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DasAtom: A Divide-and-Shuttle Atom Approach to Quantum Circuit Transformation

arXiv

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arXiv 2024年

作者： Huang, Yunqi Gao, Dingchao Ying, Shenggang Li, Sanjiang Faculty of Engineering and Information Technology University of Technology SydneyNSW2007 Australia Key Laboratory of System Software Chinese Academy of Sciences State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China

Neutral atom (NA) quantum systems are emerging as a leading platform for quantum computation, offering superior or competitive qubit count and gate fidelity compared to superconducting circuits and ion traps. However, the unique features of NA devices, such as long-range interactions, long qubit coherence time, and the ability to physically move qubits, present distinct challenges for quantum circuit compilation. In this paper, we introduce DasAtom, a novel divide-and-shuttle atom approach designed to optimise quantum circuit transformation for NA devices by leveraging these capabilities. DasAtom partitions circuits into subcircuits, each associated with a qubit mapping that allows all gates within the subcircuit to be directly executed. The algorithm then shuttles atoms to transition seamlessly from one mapping to the next, enhancing both execution efficiency and overall fidelity. For a 30-qubit Quantum Fourier Transform (QFT), DasAtom achieves a 415.8x improvement in fidelity over the move-based algorithm Enola and a 10.6x improvement over the SWAP-based algorithm Tetris. Notably, this improvement is expected to increase exponentially with the number of qubits, positioning DasAtom as a highly promising solution for scaling quantum computation on NA platforms. © 2024, CC BY.

关键词： Qubits

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The relationship between TSH levels, maternal characteristics and racial group of the aneuploidy screening

The relationship between TSH levels, maternal characteristic...

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2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022

作者： Soylemez, Ummu Gulsum Celebiler, Hande Kaymakcalan Harkonen, Juho Bakir-Gungor, Burcu Mus Alparslan University Faculty of Engineering and Architecture Department of Software Engineering Mus Turkey School of Medicine Istanbul Bilim University Department of Pediatrics Istanbul Turkey Sociology European University Institute Florence Italy School of Engineering Abdullah Gul University Department of Computer Engineering Kayseri Turkey

ISBN: (数字)9781665488945

ISBN: (纸本)9781665488945

First-trimester maternal screening is a widely used test for detecting fetal aneuploidies and neural tube defects for over two decades. Human chorionic gonadotropin hormone (beta-hCG) and pregnancy-associated plasma protein A (PAPP-A) are two serum biomarkers that are analyzed in this screening. The thyroid hormone is a critical hormone for normal pregnancy and fetal development. During the first half of pregnancy, placental and fetal development depends on the thyroid hormone levels in the mother. Therefore, thyroid abnormalities in the mother can result in unfavorable pregnancy outcomes such as intrauterine growth restriction, miscarriage, hypertensive disorders, premature birth, and an increase in the risk of low IQ in the newborn. In this study, we analyzed the first-trimester screening data collected from 410 pregnant women who were seen at Yale University Hospital Prenatal Unit;and checked for possible correlations of TSH levels with maternal characteristics, racial group PAPP-A MoM levels. © 2022 IEEE.

关键词： Obstetrics

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DDoS Detection Using Active and Idle Features of Revised CICFlowMeter and Statistical Approaches 4

DDoS Detection Using Active and Idle Features of Revised CIC...

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4th International Conference on Advanced Science and engineering, ICOASE 2022

作者： Ali, Basheer Husham Sulaiman, Nasri Al-Haddad, S.A.R. Atan, Rodziah Hassan, Siti Lailatul Mohd Department of Electrical and Electronic Engineering Serdang Malaysia Faculty of Engineering Department of Electrical and Electronic Engineering Serdang Malaysia Department of Computer and Communication Systems Engineering Serdang Malaysia Software Eng. and Information Systems Dept Serdang Malaysia School of Electrical Engineering Universiti Teknologi Mara Shah Alam Malaysia

ISBN: (纸本)9781665472227

Distributed Denial of services (DDoS) attack is one of the most dangerous attacks that targeted servers. The main consequence of this attack is to prevent users from getting their legitimate services by bringing down targeted victim. CICFlowMeter tool generates bi-directional flows from packets. Each flow generates 83 of different features. The research focuses on 8 features which are active min (f1), active mean (f2), active max (f3), active std (f4), idle min (f5), idle mean (f6), idle max (f7), and idle std (f8). CICFlowMeter tool has several problems that affected on the detection accuracy of DDoS attacks. The idle and active based feature of Shannon entropy and sequential probability ratio test (SE-SPRT) approach was implemented in this research. The problems of original CICFlowMeter were presented, and the differences between original and revised version of CICFlowMeter tool were explored. The DARPA database and confusion matrix were used to evaluate the detection technique and present the comparison between two versions of CICFlowMeter. The detection method detected neptune and smurf attacks and had higher accuracy, f1-score, sensitivity, specificity, and precision when revised version of CICFlowMeter used to generate flows. However, the detection method failed to detect neptune attack and had higher miss-rate, lower accuracy, lower f1-score, and lower specificity, and lower precision when original version used in generating flows. © 2022 IEEE.

关键词： Denial-of-service attack

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Joint Channel and Multi-User Detection Empowered with Machine Learning

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computers, Materials & Continua 2022年第1期70卷 109-121页

作者： Mohammad Sh.Daoud Areej Fatima Waseem Ahmad Khan Muhammad Adnan Khan Sagheer Abbas Baha Ihnaini Munir Ahmad Muhammad Sheraz Javeid Shabib Aftab College of Engineering Al Ain UniversityAbu Dhabi112612UAE Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of Software EngineeringGachon UniversitySeongnam13557South Korea Department of Computer Science College of Science and TechnologyWenzhou Kean University325060USA Department of Computer Science Hameeda Rasheed Institute of Science and TechnologyMultan66000Pakistan

The numbers of multimedia applications and their users increase with each passing *** multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network *** this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two *** first stage estimates the channel parameters,and the second performsmulti-user *** proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural *** study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO *** FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.

关键词： Channel and multi-user detection minimum mean square error multiple-input and multiple-output minimum mean channel error bit error rate

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Hybrid Multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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computer Systems Science & engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha Racharla ELaxmi Lydia Mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AIML Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid Multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HMAODL-CTC)algorithm *** proposed HMAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HMAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HMAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HMAO algorithm is ***,the presented HMAODL-CTC model uses an extreme learning machine(ELM)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HMAODL-CTC *** comparison studies reported the improved performance of the presented HMAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

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