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communication, computer sciences and engineering (IC3SE), International Conference on

作者： Kumaran U Thammisetty Swetha G. S. N. Santhosh Reddy Harini Ala Senthil Murugan Nagarajan B. Umah Department of Computer Science & Engineering Amrita School of Computing Bengaluru India Department of Computer Science & Engineering (Data Science) Madanapalle Institute of Technology & Science Madanapalle Andhra Pradesh India Department of Electronics and Communication Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka India Department of Mathematics Faculty of Science Technology and Medicine University of Luxembourg Luxembourg Department of Computer Science & Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

The dynamic nature of cyber threats necessitates the development of novel approaches to strengthen database system security. The novel method for fortifying defenses against SQL injection attacks—a pervasive and ongoing danger in the field of cybersecurity—is presented in this study. The suggested methodology creates a strong and adaptable defense mechanism by seamlessly integrating cutting-edge honeypot technology with current SQL injection mitigation techniques. Our approach, which we have named HoneySQLGuard, uses carefully con- structed honeypot tables inside the database system. These tables serve as sly bait, drawing potential attackers’ attention away from genuine data and toward themselves. By utilizing the most recent developments in technology, Honey SQL Guard surpasses the limitations of conventional signature-based detection techniques and is able to adjust to changing attack strategies via anomaly and machine learning. The honeypot tables are cleverly incorporated within the database architecture, making them invisible to an outside observer when compared to real tables. The technology immediately recognizes and isolates unusual behavior suggestive of SQL injection attempts by closely monitoring and analyzing query patterns. Furthermore, HoneySQLGuard has real-time reporting and alerting functions that guarantee an early reaction to any possible intrusions. Extensive testing is conducted to validate the effectiveness of the proposed solution, which shows it can dramatically lower the success rate of SQL injection attacks while keeping false-positive rates low. This study advances the subject by providing a thorough and flexible method for fortifying databases against SQL injection attacks, in line with the industry's increasing demand for robust cybersecurity defenses.

关键词： Protocols Prevention and mitigation Machine learning SQL injection Observers Database systems Real-time systems

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Adaptive neural output constrained control for an unmanned surface vessel with coupled input constraint

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Ocean engineering 2025年 335卷

作者： Ouyang, Yuncheng Bai, Yang Kong, Linghuan Wang, Xuerao School of Artificial Intelligence the Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Anhui University Hefei China Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao China

In this paper, we focus on the tracking control problem of an uncertain unmanned surface vessel (USV) system with coupled input constraint and output constraint. Considering the issue of coupled input constraint, a transformation matrix is proposed to decouple the constrained inputs. Concerning output constraint occurring in a limited time interval (OCOLT) of the USV system, a novel shifting function with a new barrier function is introduced to transform the constrained system into an unconstrained one. Furthermore, neural network technology is employed to tackle the problems of system uncertainty. Through the Lyapunov stability theory, the stability analysis of the USV system is given to demonstrate the feasibility of the proposed control method. Finally, effectiveness of the proposed control method is verified by simulations. © 2025 Elsevier Ltd

关键词： Adaptive control systems

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Performance Evaluation Customer Access Network Using Difference Modulation Technique 1st

Performance Evaluation Customer Access Network Using Differe...

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1st International Symposium on systems Modelling and Simulation, SMS 2024

作者： Mugunthan, Sivaguru Abdul Rahman, Juwairiyyah Abu Hassan, Hasliza Muslim, Norliana Ab Rahman, Mohammad Syuhaimi Department of Engineering Faculty of Engineering and Life Sciences Universiti Selangor Selangor Bestari Jaya45600 Malaysia Department of Computer and Communication Technology Universiti Tunku Abdul Rahman Perak Kampar31900 Malaysia Department of Electrical Electronic and System Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (纸本)9789819646128

Modeling Fiber To The Home (FTTH) networks involves several technical aspects and design considerations to enable effective and high-quality service delivery. This research seeks to boost the received signal quality for end-users inside a FTTH network. In order to create suitable and high-quality FTTH networks, this study will simulate FTTH networks utilizing network feasibility criteria, with an emphasis on BER and Q-factor. The signal distribution inside access networks is improved using Wavelength Division Multiplexing (WDM) and 10G-Passive Optical Network (PON) technology is used since it can deliver a fourfold improvement in downstream data transfer rates per user. Simulation result using Optisystem 21 software, by setting transmitter wavelengths of 1490 nm and 1550 nm with a loss of 0 dB for a maximum of 2 users for total access based on the Q-factor calculation, which must be more than 6, while the BER must be less than 1 × e−9. system performance parameters that demonstrate Q-factor and Bit Error Rate (BER) give good quality and good performance is also shown by eye pattern in optical simulation. For 1490 nm, the highest Q-factor for 2 users is 35.8226, with a minimum BER of 2.4360 × 10−281. For 1550 nm, the highest Q-factor is 15.3668 (in phase) and 14.8087 (in quadrature), with minimal BER values of 1.3674 × e−53 (in phase) and 6.4291 × e−50 (in quadrature). Good performance is also shown by eye pattern in optical simulation that displays amplitude signals. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Q factor measurement

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Review On the Techniques Used for Detection of Fabric Defects Using AI

Review On the Techniques Used for Detection of Fabric Defect...

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Advances in Electronics, communication, Computing and Intelligent Information systems (ICAECIS), International Conference on

作者： Isheeta Batra S A Hari Prasad K S Arvind Department of Computer Science and Engineering Faculty of Engineering & Technology JAIN (Deemed-to-be UNIVERSITY) Karnataka India Department of Electronics and Communication Engineering Faculty of Engineering & Technology JAIN (Deemed-to-be UNIVERSITY) Karnataka India

The garment industry is the second-most polluting industry after oil. These mass-produced clothes if rejected are dumped and have an enormous impact on the environment. Therefore, to save the cost post production it is important to identify any sorts of defects pre-production when clothes are in a textile form, so that in case the fabric lacks somewhere in quality it can always be replaced, saving all the time and cost. This detection is possible using techniques like segmentation, or on the basis of texture or by using deep learning algorithms each having its own advantages and disadvantages to efficiently identify the defects in textile fabric. This paper is a comprehensive study of these three techniques and comparison made on basis of brief analysis which say that the deep learning technique is the best of the three for detection of defects keeping in contrast the type of research and developing technologies.

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Medical Image Synthesis Workbench Supporting Multiple Modalities with Feature-Level Transforms 1

Medical Image Synthesis Workbench Supporting Multiple Modali...

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1st IEEE International Conference on Innovations in High Speed communication and Signal Processing, IHCSP 2023

作者： Sharma, Nitin Carlos Cotrina-Aliaga, Juan Philip Bhimavarapu, John Kumar Illa, Pavan Jyotiyana, Priya IMS Engineering College Uttar Pradesh India Universidad Privada San Juan Bautista Faculty of Human Medicine Chincha Peru Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Department of Information Technology Hyderabad India Jaipur Engineering College and Research Centre Computer Science and Engineering Jaipur India

ISBN: (纸本)9798350345957

Multi-modal In recent years, medical image synthesis has arisen as a holistic analytic strategy that typically employs many transformation methods. When it comes to medicine, multi-modal image synthesis refers to the technique of combining images from several imaging modalities to enhance image quality while maintaining detail. Image processing, computer apparition, pattern acknowledgment, machine knowledge, and artificial intellect are just few of the many cutting-edge fields that fall under the umbrella of medical image synthesis. The synthesis of many medicinal imaging modalities has been used extensively in the clinic to help doctors better understand the lesion. This paper presents the firefly algorithm, a multi-learning model workbench that minimises squared errors and maximises synthesis quality via weighted entropy. MATLAB simulations are used to compare the proposed workbench against state-of-the-art methods in terms of peak signal-to-noise ratio, Mean square error, correlation, and precision. The proposed workbench performs well across the board and requires less computing power. © 2023 IEEE.

关键词： Image enhancement

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Reinforcement Learning Based Technique for Interference Management in UAV Aided HetNets 10

Reinforcement Learning Based Technique for Interference Mana...

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10th International Japan-Africa Conference on Electronics, communications, and Computations, JAC-ECC 2022

作者： Hamden, Nehal Nasser, Ahmed Selim, Mohamed Y. Elsabrouty, Maha Egyptian Customs Authority Ministry of Finance Egypt Suez Canal University Faculty of Engineering Department of Electronics and Communication Egypt Iowa State University Electrical and Computer Engineering Department Ames United States Egypt Japan University of Science and Technology Department of Electronics and Communication Egypt

ISBN: (纸本)9781665464635

In this paper, we consider the sum rate maximization problem in a downlink unmanned aerial vehicles (UAV) assisted heterogeneous networks (HetNets) to mitigate existing interference. We propose to manage the interference by jointly optimizing the position of the UAV as well as power allocation. The proposed optimization problem is non-convex due to the non-linearity in the objective function and the constraints. We propose a near-optimal solution that breaks down the problem into two consecutive problems. First, we proposed a reinforcement learning-based technique to solve the UAV positioning problem. Then, a particle swarm optimization (PSO) based technique is applied to the power allocation problem. Simulation results demonstrate the efficiency of the proposed algorithm. © 2022 IEEE.

关键词： Heterogeneous networks

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CUDA Parallelization of Teacher-Learner Optimization Algorithm 1

CUDA Parallelization of Teacher-Learner Optimization Algorit...

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1st International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2022

作者： Abbasi, Mahdi Alghanim, Mohammed Sabri, Mohammad Khosravi, Mohammad R. Bu Ali Sina University Engineering Faculty Department of Computer Engineering Hamedan Iran Zarqa University Faculty of Information Technology Jordan Zarqa University Department of Management Information System Jordan Weifang University of Science and Technology Weifang Shandong China

ISBN: (纸本)9798350332742

Evolutionary algorithms are effective methods for solving optimization problems that do not require any special assumptions to find optimal solutions. Optimization based on teaching and learning has been parallelized using CUDA parallelization technology. The results show that the proposed parallel version of the algorithm is fast and efficient in teaching and learning phases. © 2022 IEEE.

关键词： Evolutionary algorithms

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ROF systems performance efficiency based on continuous phase frequency shift keying phase modulation scheme

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Journal of Optical communications 2024年第0期45卷 s417-s429页

作者： Eid, Mahmoud M. A. Sorathiya, Vishal Lavadiya, Sunil Abd El-Aziz, Ismail A. Asaduzzaman, Sayed Rehana, Hasin Ali Mohammed Ibrahim, Abd El-Naser Rashed, Ahmed Nabih Zaki Department of Electrical Engineering College of Engineering Taif University Taif Saudi Arabia Department of Information and Communication Technology Marwadi University Rajkot India Benha Faculty of Engineering Benha University Benha Egypt Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh Higher Institute of Electronic Engineering Belbeis Ministry of Higher Education 10th of Raman Belbeis Egypt Electronics and Electrical Communications Engineering Department Faculty of Electronic Engineering Menoufia University Menouf32951 Egypt

Radio over fiber (ROF) technique has been presented with hybrid ordinary modulation technology to achieve improvement in optical communication network performance. Fiber Bragg grating (FBG) is employed in single mode (SM) optical channel in order to enhance the transmission environment with dispersion compensation. The continuous phase frequency shift keying phase modulation (CPFSKPM) technique is included in this study. Both previous and proposed models have been inspected and investigated. Min. bit error rate (BER), max. Q factor, signal/noise ratio (SNR), received power (RP), and noise figure (NF) are the most essential parameters able to explain the behavior performance of optical communication network model. © 2021 Walter de Gruyter GmbH, Berlin/Boston.

关键词： Fiber Bragg gratings

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Combination of CRITIC and PROMETHEE II Methods as An Early Detection of Potential Dropout Students

Combination of CRITIC and PROMETHEE II Methods as An Early D...

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International Conference on Information and communications Technology (ICOIACT)

作者： Mochammad Yusa Funny Farady Coastera Deni Rahmadani Julia Purnama Sari Kusrini Kusrini Anggit Dwi Hartanto Department of Informatics Faculty of Engineering University of Bengkulu Bengkulu Indonesia Department of Information System Faculty of Engineering University of Bengkulu Bengkulu Indonesia Magister of Informatics Engineering Faculty of Computer Science Universitas AMIKOM Yogyakarta Yogyakarta Indonesia Department of Information System Faculty of Computer Science Universitas AMIKOM Yogyakarta Yogyakarta Indonesia

Dropout (DO) has negative implications for individuals and educational institutions. The field of education data mining (EDM) offers valuable contributions to prevent dropout cases and improve student retention. This study focuses on implementing EDM to identify students at risk of dropping out by integrating academic activity criteria with real-time data sources. Previous studies have encountered limitations in classification and clustering techniques, with classification relying on labeled training data (supervised learning) and clustering constrained by attribute or criteria weight (unsupervised learning). This study aims to address these limitations by combining the PROMETHEE II ranking approach and the CRITIC weighting method, producing a list of students with dropout potential. The results can aid stakeholders in implementing preventive measures. The study involves several steps: 1) Collecting data through integration with academic portals; 2) Filtering and selecting criteria for student academic activities; 3) Transforming and normalizing the data; 4) Applying automatic weighting using CRITIC; 5) Calculating criteria rankings using the PROMETHEE II technique; and 6) Validating the ranking outcomes.

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A Big Data, Bigger Impact: A Comprehensive Review of Machine Learning Advancements

A Big Data, Bigger Impact: A Comprehensive Review of Machine...

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International Conference on Electrical engineering and computer science (ICECOS)

作者： Didar Dlshad Hamad Ameen Shahab Wahhab Kareem Sarhad Baez Hasan Computer Science Department Soran University Faculty of Science Soran Kurdistan Iraq Department of Information System Engineering Erbil Polytechnic University Erbil Kurdistan Iraq

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

The exponential growth of data driven by the internet has necessitated effective extraction of insights, with big data and machine learning standing as pivotal tools. This paper aims to provide insights into the evolving landscape of machine learning and big data analytics through a comprehensive literature review. It seeks to underscore the key advancements and intersections between these domains and their transformative applications across industries. Specifically, the study will delve into the foundational theories that underpin machine learning algorithms, data collection and preprocessing techniques involved in big data analysis, and the prominent challenges associated with extracting insights from large and complex datasets. It will further explore major studies that exemplify the integration of machine learning methodologies and big data technologies for addressing real-world problems. The study will also examine visualization methods that facilitate comprehending insights gleaned from big data. Finally, it will discuss future research directions and highlight best practices for leveraging machine learning and big data analytics in decision-making processes.

关键词： Industries computer science Electrical engineering Machine learning algorithms Reviews Bibliographies Decision making Machine learning Transforms Big Data

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