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2024 International Conference on communication, computer sciences and engineering, IC3SE 2024

作者： Kumaran, U. Swetha, Thammisetty Reddy, G. S. N. Santhosh Ala, Harini Nagarajan, Senthil Murugan Umah, B. Amrita School Of Computing Department Of Computer Science & Engineering Amrita Vishwa Vidyapeetham Bengaluru India Andhra Pradesh Madanapalle India Amrita School Of Engineering Amrita Vishwa Vidyapeetham Department Of Electronics And Communication Engineering Karnataka Bengaluru India University Of Luxembourg Department Of Mathematics Faculty Of Science Technology And Medicine L-4365 Luxembourg Amrita School Of Engineering Amrita Vishwa Vidyapeetham Department Of Computer Science & Engineering Karnataka Bengaluru India

ISBN: (纸本)9798350366846

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. © 2024 IEEE.

关键词： Database systems

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Student Perceptions of AI-Enhanced Adaptive Learning Systems: A Pilot Survey 7

Student Perceptions of AI-Enhanced Adaptive Learning Systems...

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7th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2024

作者： Katonane Gyonyoru, Klara Ida Katona, Jozsef Institute of Social Sciences University of Dunaujvaros Department of Organizational Development and Communication Science Dunaujvaros Hungary Institute of Computer Engineering University of Dunaujvaros Department of Software Development and Application Dunaujvaros Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemet Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary

ISBN: (纸本)9798331531119

Artificial Intelligence (AI) significantly enhances adaptive learning by personalizing and tailoring instruction to individual student needs. AI analyzes data in real-time to create personalized learning paths based on students' strengths, weaknesses, and preferences, which keeps students engaged and motivated. A major benefit of AI in adaptive learning is the provision of real-time feedback and assessment, allowing students to correct mistakes promptly and understand concepts more thoroughly. AI-based intelligent tutoring systems are primarily intended to simulate personalized tutoring processes that guide students in complex problem-solving and answering questions. It is convenient in teaching mathematics, sciences, and languages. AI also supports inclusive education, dealing with diversified learning requirements and styles, such as those of learners with disabilities. For the teacher, AI acts as a reflector of student performance so that one can intervene early and make adjustments in the method of instruction by creating effective learning environments. AI technology is a field in constant development and harbors the potential to change the face of adaptive learning, bringing an upswing in educational outcomes. This article will summarize the advantages and features that merit improvement of the AI-embedded adaptive learning systems with student feedback. © 2024 IEEE.

关键词： Contrastive Learning

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Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security

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Intelligent Automation & Soft Computing 2023年第3期35卷 2773-2787页

作者： Amal H.Alharbi S.Karthick K.Venkatachalam Mohamed Abouhawwash Doaa Sami Khafaga Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Electrical Electronics and Communication Engineering GITAM School of TechnologyGITAM Deemed to be UniversityBengaluru CampusKarnataka560065India Department of Computer Science and Engineering CHRIST(Deemed to be University)Bangalore560074India Department of Mathematics Faculty of ScienceMansoura UniversityMansoura 35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

Recent security applications in mobile technologies and computer sys-tems use face recognition for high-end *** numerous security tech-niques,face recognition is considered a high-security *** fuse and carry out face identiﬁcation as an access authority into these ***,face identiﬁcation authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized *** the existing spooﬁng detection algorithm,there was some loss in the recreation of *** research proposes an unobtrusive technique to detect face spooﬁng attacks that apply a single frame of the sequenced set of frames to overcome the above-said *** research offers a novel Edge-Net autoencoder to select convoluted and dominant features of the input diffused ***,this pro-posed method is tested with the Cross-ethnicity Face Anti-spooﬁng(CASIA),Fetal alcohol spectrum disorders(FASD)*** database has three models of attacks:distorted photographs in printed form,photographs with removed eyes portion,and video *** images are taken with three different quality cameras:low,average,and high-quality real and spoofed *** extensive experimental study was performed with CASIA-FASD,3 Diagnostic Machine Aid-Digital(DMAD)dataset that proved higher results when compared to existing algorithms.

关键词： Image processing edge detection edge net auto-encoder face authentication digital security

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Health Recommender System for Maternal Care Implementation Challenges: A Qualitative Analysis of Physicians' Perspective 14

Health Recommender System for Maternal Care Implementation C...

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14th International Conference on Advanced computer science and Information Systems, ICACSIS 2022

作者： Priambodo, Rinto Handayani, Putu Wuri Sensuse, Dana Indra Suryono, Ryan Randy Kautsarina Universitas Mercu Buana Faculty of Computer Science Jakarta Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandar Lampung Indonesia Ministry of Communication and Information Technology Jakarta Indonesia

ISBN: (数字)9781665489362

ISBN: (纸本)9781665489362

The World Health Organization (WHO) strategy for Ending Preventable Maternal Mortality (EPMM) accommodates guidelines and objectives to lower the level of the global Maternal Mortality Ratio (MMR). Regular antenatal care (ANC) visits could increase maternal satisfaction, hence activities in ANC include risk identification, prevention, and management of pregnancy-related diseases, which could lead to maternal death. The health recommender system in healthcare helps patients and health professionals perform early predictions and receive meaningful recommendations based on patients' up-to-date health records. However, implementations of this application in maternal care are still few. Therefore, we conducted a semi-structured interview to five physicians working in maternal care to explore the challenge. The interview data were afterwards analyzed using qualitative content analysis. This qualitative study has identified six major challenges related to technological issues, such as the ability to display critical information, simplicity, compatibility, correctness, consistency, and fulfillment of functionalities required to adhere to maternal care guidelines, as well as challenges related to regulations and policies. This study contributes knowledge about the implementation of health recommender systems for maternal care and provides recommendations to application vendors and health regulators for the implementation of this system in Indonesia. © 2022 IEEE.

关键词： Recommender systems

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Predicting Hand Injury Severity Using Bayesian Networks in Cloud-Based Emergency Medicine 10

Predicting Hand Injury Severity Using Bayesian Networks in C...

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10th International Conference on communication and Signal Processing, ICCSP 2024

作者： Yuvaraj, S. Thinakaran, K. Srinivas, S. Porandla Sivakumar, S. Ishwarya, M.V. Thirumaraiselvan, P. Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Electronics and Communication Engineering Chennai Tamil Nadu Kattankulathur India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Malla Reddy Institute of Engineering and Technology Department of Information Technology Telangana Hyderabad India Department of Computer Science Tamil Nadu Perambalur India Agni College of Technology Artificial Intelligence and Data Science Department Tamil Nadu Thazhambur India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

Predicting the severity of hand injuries in emergency care is the focus of this study, which suggests using cloud-based Bayesian networks. It is crucial to have accurate severity prediction in order to treat emergency hand injuries promptly since they are prevalent. By using the scalability and flexibility of cloud computing, this method constructs a Bayesian severity assessment network with patient data, injury characteristics, and historical medical records. The model's training data comes from a massive database of hand injury cases with different results. Emergency medical professionals may use real-time parameter modifications to strengthen and adapt the Bayesian network. Through the use of the cloud, healthcare providers may simply exchange data and reach consensus. It demonstrates that, compared to other well-established methods of evaluating hand injury severity, the model performs better in making predictions. The suggested method improves severity forecasts and advances cloud-based emergency care. The method for emergency hand injury care uses Bayesian networks in the cloud to improve scalability and accessibility. The findings show that the data-driven and efficient hand injury severity prediction method might transform emergency care by improving patient outcomes. © 2024 IEEE.

关键词： Bayesian networks

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Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

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computers, Materials & Continua 2022年第8期72卷 3113-3129页

作者： Murad A.A.Almekhlafi Fahd N.Al-Wesabi Majdy M.Eltahir Anwer Mustafa Hilal Amin M.El-Kustaban Abdelwahed Motwakel Ishfaq Yaseen Manar Ahmed Hamza Department of Electrical Engineering–Communication Engineering Sana’a UniversityYemen Department of Computer Science King Khalid UniversityMuhayelAseerSaudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Information Systems King Khalid UniversityMuhayelAseerSaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Electronic Department Faculty of EngineeringUniversity of Science and TechnologySana’aYemen

Energy is an essential element for any civilized country’s social and economic development,but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the *** Republic of Yemen has very good potential to use renewable ***,we find few studies on renewable wind energy in *** the lack of a similar analysis for the coastal city,this research newly investigates wind energy’s potential near the Almukalla area by analyzing wind ***,evaluation,model identification,determination of available energy density,computing the capacity factors for several wind turbines and calculation of wind energy were extracted at three heights of 15,30,and *** wind speeds were obtained only for the currently available data of five recent years,2005–*** study involves a preliminary assessment of Almukalla’s wind energy potential to provide a primary base and useful insights for wind engineers and *** research aims to provide useful assessment of the potential of wind energy in Almukalla for developing wind energy and an efficient wind *** Weibull distribution shows a perfect approximation for estimating the intensity of Yemen’s wind *** on both theWeibullmodel and the results of the annual wind speed data analysis for the study site in Mukalla,the capacity factor for many turbines was also calculated,and the best suitable turbine was *** to the International Wind Energy Rating criteria,Almukalla falls under Category 7,which is,rated“Superb”most of the year.

关键词： Almukalla energy potential Rayleigh distribution Weibull distribution wind power density wind speed

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Analysis of integration of IoMT with blockchain: issues, challenges and solutions

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Discover Internet of Things 2024年第1期4卷 21页

作者： Mazhar, Tehseen Shah, Syed Faisal Abbas Inam, Syed Azeem Awotunde, Joseph Bamidele Saeed, Mamoon M. Hamam, Habib Department of Computer Science Virtual University of Pakistan Lahore55150 Pakistan Department of Artificial Intelligence and Mathematical Sciences Sindh Madressatul Islam University Karachi74000 Pakistan Department of Computer Science Faculty of Communication and Information Sciences University of Ilorin Ilorin Nigeria Sana’a Yemen Faculty of Engineering Uni de Moncton MonctonNBE1A3E9 Canada Department of Electrical and Electronic Engineering Science University of Johannesburg Auckland Park Johannesburg2006 South Africa Av. Grandes Ecoles LibrevilleBP 1989 Gabon Bridges for Academic Excellence Spectrum Tunis Tunisia

The incorporation of Artificial Intelligence (AI) into the fields of Neurosurgery and Neurology has transformed the landscape of the healthcare industry. The present study describes seven dimensions of AI that have transformed the way of providing care, diagnosing, and treating patients. It has exhibited unparalleled accuracy in analyzing complex medical imaging data and expediting precise diagnoses of neurological conditions. It has also enabled personalized treatment plans by harnessing patient-specific data and genetic information, promising more effective therapies. For instance, AI-powered surgical robots have brought precision and remote capabilities to neurosurgical procedures, reducing human error. In AI, machine learning models predict disease progression, optimizing resource allocation and patient care, whereas wearable devices with AI provide continuous neurological monitoring, and enable early intervention for chronic conditions. It has also accelerated drug discovery by analyzing vast datasets, potentially leading to breakthrough therapies. Chatbots and virtual assistants powered by AI, enhance patient engagement and adherence to treatment plans. It holds promise in further personalization of care, augmented decision-making, earlier intervention, and the development of groundbreaking treatments. The present study mainly focuses on the incorporation of blockchain technology and provides a reasonable understanding of the associated issues and challenges along with its solutions. It will allow AI and healthcare professionals to advance the field and contribute towards the improvement of an individual's well-being when facing neurological challenges. © The Author(s) 2024.

关键词： Neurosurgery

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Cloud-Based Oxygen Management System with Seamless HTTP Protocol Integration 4

Cloud-Based Oxygen Management System with Seamless HTTP Prot...

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4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Hemalatha, S. Ramasamy, Jayabharathi Selvi, K. Anandan, P. Meenakshi, R. Maniraj, S.P. Tagore Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India S. A. Engineering College Faculty of Management Studies Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Electronics and Communication Engineering Tamil Nadu Chennai India Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350307757

In this study, an efficient system to improve the oxygen supply in hospitals and other healthcare institutions is proposed. It uses Internet of things (IoT) devices and cloud based data transmission and processing system. The controller unit collects the oxygen sensor data for the analysis and uses HTTP protocols to send and receive data with cloud computing in HTTP website server. The cloud is data storage, processes and real-time monitoring, analysis and control system. It has a user interface with viewed administrators and medical professionals. The interface provides real-time data regarding oxygen supply, consumption patterns, and possible concerns. Authorized workers can access and manage the system via the display, allowing for timely adjustments to oxygen supply settings, optimizations to refill schedules, and responses to emergency circumstances. It's adaptable, flexible, and resilient, which are benefits. There will be less need to worry about oxygen shortages and interruptions, and healthcare institutions of all sizes can benefit from this. The cloud's remote access and control capabilities provide continuous functioning and rapid reaction times. It's an effective solution for hospitals and other healthcare facilities that need to control their oxygen supplies. With its cloud-based design, the solution increases productivity, improves patient safety, and simplifies oxygen management. © 2024 IEEE.

关键词： HTTP

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A Dual Broadband Antenna for V2X, LTE, and 5G Vehicular communication Systems 7

A Dual Broadband Antenna for V2X, LTE, and 5G Vehicular Comm...

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7th IEEE International Conference on Electronic Information and communication Technology, ICEICT 2024

作者： Hu, Yiting Feng, Botao Chung, Kwok L. Ding, Xiao Gu, Wenzhe Deng, Li Shenzhen University College of Electronics and Information Engineering Shenzhen518060 China Huizhou University School of Computer Science and Engineering Huizhou China Macau University of Science and Technology Faculty of Humanities and Arts Macau999078 China Beijing University of Posts and Telecommunications College of Information and Communication Engineering Beijing China

In this paper, we present a novel dual broadband antenna tailored for vehicular applications. The antenna design incorporates circular and square patches, metal cylinders, and conductive vias. Our simulated results de... 详细信息

ISBN: (纸本)9798350384437

关键词： Advanced driver assistance systems

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Hyper tension Detection for Diabetic Patients using Machine Learning 14

Hyper tension Detection for Diabetic Patients using Machine ...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Saranya, S. Thilak, K. Deepa Kalaiselvi, K. Kumar, T. Rajesh Kumaresan, K. Department of Electronics and communication Engineering EaswariEngineering College Ramapuram Chennai India Tamil Nadu Kattankulathur603 203 India Department of Computer Science and Engineering Saveetha school of Engineering Saveetha University Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Faculty of Computer Science and Engineering KSR College of Engineering India

Hypertension is the primary wellspring of passing and cardiovascular contaminations all over the planet addressing around 15 spending consistently. Hypertension revives the development of all-cause mortality, stroke, coronary course disease, and diabetes mellitus. The improvement of diabetes among hypertensive patients is generally on different occasions more progressive than in normotensive individuals. The two hypertensions similarly as diabetes are ordinary diseases which occur at a high repeat and deal standard causes. In like manner, there arises prerequisite for development of sensible models which can perform precise assumption for hyper-strain among diabetic patients. Along these lines, diabetes is the principal wellspring of visual hindrance, renal dissatisfaction;idiocy and diabetic foot issue whose reality can cause lower-limb removals. The large scale vascular traps of diabetes integrate cardiovascular infection, for instance. Coronary disappointments, strokes and cerebrovascular contamination. The inspiration driving standard extraction is because of adhering to two reasons: 1) To decipher the arrangement performed by the fundamental non-straight black-box model;2) To work on the presentation of rule acceptance methods. Hereafter, we focus in fostering a mutt rule-based model for finding of hypertension among diabetic individuals by joining of a non-rule-based characterization estimation with a standard based computation. The potential gains of the non-rule-based calculation are solidified into the standard based approach. © Grenze Scientific Society, 2023.

关键词： Machine learning

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