Vol 12 Issue 2 April 2024-June 2024

Abstract: Real-time data analytics, crucial for immediate data processing and decision-making, is transforming emergency telemedicine by enhancing patient care and operational efficiencies. This review examines the application and impact of real-time analytics in this field, employing a systematic literature review of recent studies from databases like PubMed and IEEE Xplore. Our findings reveal significant improvements, such as a 30% reduction in patient wait times and enhanced treatment accuracy by 25%. Key technologies include IoT devices, cloud computing, and machine learning algorithms. Despite advancements, challenges like data security and system integration persist. Future research should focus on refining these technologies and expanding their applications to overcome current limitations.

Keywords: real-time data analytics, emergency telemedicine, patient care, operational efficiency, healthcare technology.

Title: Review of Real-Time Data Analytics: Transforming Emergency Telemedicine

Author: Jagjot Bhardwaj, Sivanagaraju Gadiparthi

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 62-68

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Published Date: 29-June-2024

Abstract: In this research, we presented an explanation of the definition of cybersecurity, its importance, and its types. We also explained the difference between information security and cybersecurity, as well as the importance of both. we also mentioned how cyber security is important in the education sector and the Role of training and education in enhancing Cybersecurity.

Keywords: cybersecurity, information security, education sector.

Title: Cybersecurity In Education

Author: Jumanah Hasan AlSanad

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 51-61

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Website: www.researchpublish.com

Published Date: 27-June-2024

Abstract: Automated Arabic Essay Scoring (AAES) systems have the potential to revolutionize educational assessment in the Arabic-speaking world, but their accuracy is often hindered by the complexities of Arabic morphology and semantics. This study introduces a novel AAES model, the Arabic Stemming Enhancement (ASE) algorithm, which integrates Arabic WordNet (AWN) to enhance semantic understanding and root extraction accuracy. By leveraging AWN's lexical database, ASE overcomes limitations of traditional stemming approaches, such as misinterpreting polysemous words. Rigorous evaluation on student essays and a WordNet-based dataset demonstrates ASE's superior performance compared to existing algorithms. Notably, ASE achieved a 0.977 Pearson correlation with human-assigned scores and a 15% increase in accuracy, alongside improvements in precision, recall, and F1-score. This research significantly advances Arabic Natural Language Processing (NLP), offering a more accurate, equitable, and scalable automated assessment tool for Arabic language education.

Keywords: Arabic Stemming Enhancement, Automated Essay Scoring, Arabic WordNet, Natural Language Processing, Semantic Analysis, Root Extraction, Educational Assessment, Machine Learning.

Title: A NOVEL ARABIC STEMMING ALGORITHM WITH WORDNET INTEGRATION FOR IMPROVED ESSAY SCORING

Author: Mohamad Alobed, Yazeed Al Moaiad

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 40-50

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Website: www.researchpublish.com

Published Date: 24-June-2024

Abstract: Microsoft Fabric represents a significant leap forward in analytics services, combining data management, analytics, and machine learning into a unified platform. This paper offers a detailed examination of Microsoft Fabric, covering its architecture, prominent features, advantages, and potential applications. Engineered to streamline data processes and foster collaboration among data experts, Microsoft Fabric supports real-time analytics, scalable data storage, advanced machine learning capabilities, and robust security protocols. Future developments for the platform include deeper AI integration, expanded data connectivity, enhanced user experience, fortified security measures, sustainability initiatives, and collaborative tools. By harnessing Microsoft Fabric, organizations can gain comprehensive data insights and drive innovation effectively.

Keywords: Cloud Computing, Microsoft Azure, Data Analytics, Microsoft Fabric, Data Engineering, Data Science.

Title: Microsoft Fabric Review: Exploring Microsoft's New Data Analytics Platform

Author: Praveen Borra

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 34-39

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Website: www.researchpublish.com

Published Date: 06-June-2024

Abstract: Integral to contemporary economies, digital payments have reshaped how individuals and businesses manage financial transactions. As technology continues its relentless progress, the realm of digital payments will undergo further transformations, providing people worldwide with increasingly secure and convenient choices.

Today, customers have the choice of closed wallets, semi-closed wallets, and open wallets, but venturing into this business requires both technical expertise and substantial investment. Success in the realm of digital payments is achievable through a sound business strategy aligned with Payment Card Industry Data Security Standards (PCI DSS).

In the modern business landscape, connecting with multiple Payment Service Providers (PSPs) for seamless payment processes has been challenging. Until now, a comprehensive solution for integrating consumer applications, both SAP and non-SAP, with multiple PSPs and managing real-time payments effectively was lacking.

The SAP digital payments add-on addresses these challenges, offering flexibility by supporting multiple real-time digital payment methods and enabling automatic reconciliation through seamless PSP integrations. It enhances security by eliminating the need to store sensitive credit card data in SAP S/4HANA and non-SAP systems, simplifying PCI compliance. This solution empowers businesses to embrace diverse digital payment methods while ensuring security, flexibility, and efficiency.

This paper is intended to assist enterprises in making an informed choice when selecting digital payment through the SAP Digital Payment add-on. This cloud-based Software-as-a-Service (SAAS) tool facilitates the development of digital payment processing, making it more secure, efficient, and adaptable to diverse customer needs. The company successfully navigated the challenges of modern payment processing and emerged with an enhanced payment system that positions it for continued growth and success in the global marketplace.

Keywords: SAP Digital Payment add-on, SAP S/4 HANA, Payment service Providers.

Title: Credit Card Payments Processing using SAP Digital Payment Add-on for FIAR Process – Case Study

Author: Chandrasekhar Gopisetti

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 29-33

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Website: www.researchpublish.com

Published Date: 31-May-2024

Abstract: Distributed Denial of Service (DDoS) attacks continue to pose a significant threat to network infrastructures, causing disruptions and financial losses for organizations worldwide. Traditional defense mechanisms often fall short in effectively detecting and mitigating these sophisticated attacks. In this study, a novel approach for the detection and protection analysis of DDoS attacks utilizing clustering data mining techniques. By leveraging the inherent patterns and anomalies present in network traffic data, the method aims to enhance the accuracy and efficiency of Distributed Denial of Service (DDoS) attack detection while minimizing false positives. Employ clustering algorithms to group network traffic data into distinct clusters, allowing for the identification of abnormal traffic patterns indicative of DDoS attacks. Furthermore, we analyze the effectiveness of various clustering algorithms, including k-means, DBSCAN, and hierarchical clustering, in accurately detecting and mitigating DDoS attacks. Through extensive experimentation on real-world network datasets, we demonstrate the efficacy of our approach in accurately detecting and mitigating DDoS attacks while minimizing the impact on legitimate network traffic. Our findings underscore the importance of leveraging clustering data mining techniques for enhancing the resilience of network infrastructures against DDoS attacks. [1]

Keywords: DDoS Attacks, Clustering Data Mining, Network Security, Intrusion Detection.

Title: DETECTION AND PROTECTION ANALYSIS OF DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACKS USING CLUSTERING DATA MINING

Author: Ojiruwe Benjamin Uzazo, Yazeed Al Moaiad

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 25-28

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Website: www.researchpublish.com

Published Date: 29-May-2024

Abstract: The ever-evolving landscape of marketing necessitates a robust analytics platform that integrates data from various marketing channels for insightful decision-making. This paper introduces an Integrated Marketing Data Analytics Platform, a comprehensive solution designed to enhance marketing strategies through advanced analytics. The platform amalgamates data from diverse marketing sources, enabling a holistic view of campaigns, customer behavior, and market trends. Key features include cross-channel analytics, predictive modeling, and real-time reporting. This research aims to empower marketing professionals with a versatile tool that maximizes the impact of marketing efforts by providing actionable insights and fostering data-driven decision-making.

Keywords: Integrated Marketing, Data Analytics, Cross-Channel Analytics, Predictive Modeling, Real-time Reporting, Marketing Strategies.

Title: Advanced Data Extraction and Analytics Software on AWS: Revolutionizing Insights with Personalized

Author: Shivanand kumar, Pranav Kumar, Devu Yoganandhiswar Reddy

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 13-24

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Website: www.researchpublish.com

Published Date: 06-May-2024

Abstract: Further improvements are needed in building technology to save time and resources. Nowadays, principal and public buildings are designed as long-span structures. The prestressed concrete system has proven to be more effective for spans exceeding 6 meters instead of the traditional reinforced concrete system, helping to reduce deformations and save materials. There are two types of prestressed concrete systems: pre-tension, where tendons are tensioned before concrete pouring, and post-tension, where tendons are tensioned after pouring. The unbonded system is one type of post tension system. At this research, the ultimate punching shear load was tested on the unbonded post tensioned slab and compared to the theoretical calculated value of the punching shear capacity of reinforced concrete flat slab. Strain behavior of reinforced steel bars and unbonded tendons of the specimen were studied. Also, deformation behavior of specimen during test up to failure was studied.

Keywords: Prestressing strands, Unbonded tendons, Post-tensioned flat slab.

Title: Punching Behavior of Unbonded Post Tensioned flat slab

Author: Omnia S. Ismail, Ayman H. H. Khalil, Mahmoud El-Kateb

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 6-12

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Website: www.researchpublish.com

Published Date: 03-May-2024

Abstract: Instagram as an educational resource allows a wide variety of actions such as uploading photos, videos, audios, live broadcasting, generating texts, sharing information, promoting alternative evaluation processes that allow respecting the principles of continuous evaluation, contributing to collaborative work by promoting interactions and minimizing space and time problems, responding to different learning styles, generating universal learning designs, and promoting creativity, among other aspects. Although the use of Instagram in education is not currently widespread, many proposals can be observed which employ this social network in different ways. This paper presents the use of Instagram as an e-portfolio through a framework consisting of 4 phases. In addition, it concludes by highlighting the many benefits such as making learning more explicit for both teachers and students; helping reflection, self-knowledge, and critical spirit; promoting continuous assessment of learning or contributing to the sense of personal achievement, among others.

Keywords: E-portfolio, social networks, Instagram, education, continuous evaluation, formative evaluation.

Title: Using Instagram in Classroom: Didactic recommendations and guidelines to develop an educational E-portfolio

Author: Javier Mula-Falcón, Javier de la Hoz-Ruiz, Maria del Carmen Flores-Piñero

International Journal of Computer Science and Information Technology Research

ISSN 2348-1196 (print), ISSN 2348-120X (online)

Vol. 12, Issue 2, April 2024 - June 2024

Page No: 1-5

Research Publish Journals

Website: www.researchpublish.com

Published Date: 01-May-2024