Vol 11 Issue 4 October 2023-December 2023

Abstract: Cryptocurrencies are one of the main application domains of blockchain technology and have proliferated in the past years with investors seeking alternative ways to established currencies for speculation or value storage. However, not all investors have the same motivation, nor invest large amounts of money. On the contrary, word of mouth and peer to peer influence play an important role in cryptocurrency adoption. This work is exploratory research on the factors that influence cryptocurrency adoption, with focus on the way investors perceive the cryptocurrency market. A qualitative approach is followed with semi-structured interviews on United Kingdom cryptocurrency investors. The key findings from the study can be summarized in two key dimensions. The first dimension is that a significant factor that influences cryptocurrency adoption is the perceived return on investment, while the second dimension is that peer and friend influence is a quite strong factor as well. The study contributes to the existing body of knowledge and promotes the agenda for future research in the domain.

Keywords: Cryptocurrency adoption, Blockchain technology, Technology Acceptance Model.

Title: Influencing Factors for Blockchain and Cryptocurrency Adoption from a Perception Perspective

Author: Eve Hereward, Georgios Rigopoulos

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 80-87

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Website: www.researchpublish.com

Published Date: 28-December-2023

Abstract: The accurate detection and classification of schizophrenia are vital for early intervention and treatment. The realm of medical image analysis encounters a hurdle due to the scarcity of publicly accessible data, often compelling researchers to grapple with small and imbalanced datasets. To address this issue, transfer learning techniques come to the rescue by allowing the utilization of general features from smaller target datasets. This research investigates the application of the EfficientNets for the classification of Schizophrenia rs-fmri images obtained from schizconnect. The dataset is split into three sets with 60% for training, 20% for testing and the remaining 20% for evaluation The results indicate promising classification performance for different EfficientNet convnet variants, with high precision, recall, F1-score, and accuracy. The B3 architecture, in particular, demonstrates exceptional performance, achieving 99.7% accuracy. The findings of this research provide valuable insights into the classification of schizophrenia using neuroimaging data and state-of-the-art neural network models.

Keywords: EfficientNet, Schizophrenia, ConvNets. Transfer Learning.

Title: A Deep Learning Approach to Classifying Schizophrenia Based on EfficientNet Convolutional Neural Network Models

Author: Michael Ayeni, Prof. S.O Adewale, Dr. Ibam

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 72-79

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Website: www.researchpublish.com

Published Date: 15-December-2023

Abstract: This study explores the transformative influence of integrating Health Technology and Artificial Intelligence (AI) within the TOWS matrix framework in healthcare organizations. The research addresses three key questions to investigate the measurable improvements, decision-making processes, and actionable insights resulting from the AI-enhanced TOWS matrix. Firstly, it assesses whether there are discernible enhancements in strategic outcomes to inform managers of the gains available with the integration of AI in their healthcare delivery processes. Secondly, the study delves into the ways in which the integration of AI within the TOWS matrix shapes decision-making processes across various levels within healthcare organizations. Lastly, it examines the capacity of AI-driven TOWS matrix analyses to provide actionable insights, contributing to more informed and strategic decision-making in healthcare settings. The hypothetical nature of the study allows for a forward-looking exploration of the potential impact of advanced technologies on strategic planning in healthcare. The findings aim to inform discussions on leveraging AI and other technology for strategic improvement in patient-centric care.

Keywords: Health Technology, AI, Patient-Centered Care, Strategic Planning.

Title: The Transformative Impact of Health Technology and AI Integration on Patient-Centric Care: A Hypothetical Role of Strategic Planning

Author: Dr. David Augustine Bull

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 55-71

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Website: www.researchpublish.com

Published Date: 13-December-2023

Abstract: With the modern technologies business is evolving and the use of technology become a necessity. But with each technology there is a security and one of the main concerns for companies is awareness. Even if you have the top security controls, user’s awareness most be effective to strengthen the security controls.  Users understanding for the awareness is always different and interesting challenge for any information security analyst. How to know its effectiveness? and how to measure? or even how to provide the right awareness? we will introduce the four WWWW that will lead towards effective, sustainable and sloid awareness. Who are the audience? What is there level of cyber security? What is their role in company business? What is the historical information about cyber security program? These questions are critical and in this technical paper we will discuss its value.

Keywords: Information security, Human factor, Cybersecurity, Analysis.

Title: Strategy for Effective Awareness

Author: Bayan Almulhim, Rami Alghamdi

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 53-54

Research Publish Journals

Website: www.researchpublish.com

Published Date: 21-November-2023

Abstract: ChatGPT has emerged as a noteworthy avenue within the realm of artificial intelligence (AI). In the contemporary digital landscape, the predominant focus of research endeavors revolves around the multifaceted implications of this technology. While numerous scholars, particularly those with expertise in programming and digital security, have acknowledged the existence of a correlation between ChatGPT and cybersecurity as well as social engineering, a comprehensive exploration of this relationship remains conspicuously absent from the academic discourse. The objective of this scholarly work is to elucidate the ramifications of ChatGPT on the domains of cybersecurity and social engineering.To accomplish this aim, a descriptive-analytical approach has been employed to meticulously dissect and assess the influence of ChatGPT. This analysis is conducted from the perspectives of information technology specialists, ChatGPT experts, and cybersecurity professionals operating within the geographical purview encompassing the United Arab Emirates, the Kingdom of Saudi Arabia, the State of Kuwait, and the Arab Republic of Egypt. The research cohort consists of a substantial sample size comprising 93 such professionals, and data collection is facilitated through the utilization of a structured questionnaire. Subsequently, the amassed dataset is subjected to rigorous statistical analysis employing the SPSS statistical software version 22. The findings of this investigation substantiate the presence of a statistically significant impact emanating from ChatGPT on the practices of cybersecurity and the occurrence of social engineering attacks.

Keywords: Artificial intelligence – ChatGPT – Cybersecurity – Social engineering.

Title: The Impact of Using ChatGPT on Cybersecurity & Social Engineering

Author: Dr. Khaled Khalifah Allanqawi, MOHAMMAD HUSSEIN ALSAIDOMAR

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 42-52

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Website: www.researchpublish.com

Published Date: 16-November-2023

Abstract: In today’s technology-driven world, commercialization of information technology (IT) and intellectual property (IP) are driving innovations and economic growth. Many organizations struggle to realize the full value of their IT IP assets, which result in missed opportunities and low returns on investment of their IT IP assets. A comprehensive approach to enhance the value realization of IT IP assets by commercialization is presented in this article. The article begins by examining the significance of establishing a comprehensive IP management strategy that aligns with the organization's broad commercial objectives. IT IP strategies identify and protect valuable IT IP assets, which include patent filing, copyrighting, trademarking, and trade secrets that are needed for organizations to realize the value of its IT IP assets. Furthermore, fostering a spirit of ingenuity and a thorough understanding of intellectual property within the organization is vital for ensuring efficient intellectual property administration.

The article also assesses ongoing IP asset management, encompassing surveillance and enforcement tactics to safeguard IT intellectual property rights. Monitoring the market regularly aids organizations in spotting potential infringements and taking appropriate legal steps to safeguard their intellectual property. Continuous evaluation of the IT IP assets market value and reassessing commercialization strategies allows organizations to adapt to evolving market conditions and maximize long-term value realization.

Keywords: technology-driven world, information technology (IT), economic growth.

Title: Maximizing the Value Realization of IT Intellectual Property Commercialization

Author: Dr. Mufleh M. AlKahtani, Abdulmajeed A. AlAbdulhadi

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 37-41

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Website: www.researchpublish.com

Published Date: 06-November-2023

Abstract: Inefficient classification of agricultural products has resulted to failure or poor market value for many crops. The need for using technology in enhancing crop yield classification cannot be overemphasized. This work used fuzzy logic system in performing crop yield classification and considered yam for the representation. Attributes of yam like size, length, age, date of maturity, and others are considered in this work. Fuzzy rules for the classification are formed. A fuzzy SQL expression using Create, Insert, Select and Classify statements for the implementation are considered. The evaluation shows that classifying crop yield using fuzzy systems adds great value to post harvest yield management and enhances crops marketing and storage value with high efficiency.  

Keywords: Crop Yield, Fuzzy Classification, Fuzzy Logic, SQL, System.

Title: Theoretical framework towards Crop Yield Classification using Fuzzy SQL and Fuzzy Relational Database

Author: Kile, Awuna Samuel, Ukeyima, Dooshima Joyce, Adegoke, O. Folake

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 29-36

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Website: www.researchpublish.com

Published Date: 03-November-2023

Abstract: The wormhole attack is a type of attack on the network layer that affects the routing protocols. In this study, we investigate the use of Gated Recurrent Unit (GRU) with an attention mechanism and Decision Tree, for detecting wormhole attacks in mobile ad hoc networks (MANETs). This study is divided into three main tasks. Firstly, simulating wormhole attacks in a mobile ad hoc networks (MANETs) environment with a finite number of nodes Secondly, describe the network characteristics that contribute to feature selection. Consequently, we perform data generation and data gathering operations that produce a large volume of datasets. Finally, we applied the proposed model to detect wormhole attacks in mobile ad hoc networks (MANETs). The model was evaluated and tested with the simulated datasets consisting of eight selected features and an instance using Accuracy, Precision, Recall, and F1-Score as performance metrics. Experimental results demonstrate that the proposed method outperformed other related methods from the literature in terms of the aforementioned evaluation criteria.

Keywords: Manets, Wormhole, Attention mechanism, DT, Feature Selection.

Title: Attention Based Gated Recurrent Neural Network for Wormhole Attack Detection in MANETs

Author: Balkisu Musa Hari, Ali Ahmad Aminu

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 20-28

Research Publish Journals

Website: www.researchpublish.com

Published Date: 10-October-2023

Abstract: Yemen is currently one of the poorest countries in the world, as indicated by a new report of the United Nations Relief Program, this will be negatively affecting all aspects of life in Yemen, including the aspect of information systems. Evaluating the quality of accounting information systems is very important because of the significant impact on improving the performance of these systems, hence the importance of this study, which evaluates the level of quality of accounting information systems and develops appropriate solutions to solve the problem of low .current study relied on dimensions and criteria taken from The DeLone and McLean Model of Information Systems Success by studying five main factors to measure the quality of information systems ease of use of the system, reliability of the system, flexibility of the system, a realization of user requirements, and user satisfaction with the system. To achieve the objectives of the study, a questionnaire was designed. After analyzing the data the results showed that accounting information systems used in companies in Seiyun city are characterized by ease of use and reliability with a high level of quality, and characterized by flexibility with a middle level, Among the most important recommendations recommended by the study were the following: The necessity of paying attention to quality and raising its level in those systems through the development of specifications, continuous updating, and troubleshooting defects and repairing them. As well as choosing systems through professional consultants’ specialists in information technology.

Keywords: accounting information systems, information System, Quality.

Title: IMPACT OF QUALITY FACTORS ON ACCOUNTING INFORMATION SYSTEMS IN SEIYUN CITY COMPANIES

Author: Ameen Ba yashot, Yazeed Al Moaiad

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 14-19

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Website: www.researchpublish.com

Published Date: 09-October-2023

Abstract: This research paper introduces a novel framework for skin disease classification, combining Wavelet Attention VGG19 and XGBoost algorithms. Wavelet Attention VGG19 leverages the power of deep learning and wavelet attention mechanisms to extract discriminative features from skin lesion images, while XGBoost, a gradient boosting technique, complements the feature extraction capabilities with its ability to handle complex data relationships. The integration of these methodologies aims to improve accuracy and resilience in binary skin disease classification. The two goals of this study are to first improve feature learning and representation from skin lesion images by introducing wavelet attention into the VGG19 architecture, and second to improve classification performance by utilising XGBoost's ensemble and generalisation capabilities.

Keywords: Wavelet Attention, Xgboost, deep learning, convolutional neural network, skin disease classification, VGG19.

Title: Wavelet Attention VGG19 and XGBOOST for Classification of Skin Disease

Author: Samaila Audu, Ali Ahmad Aminu

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 5-13

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Website: www.researchpublish.com

Published Date: 07-October-2023

Abstract: Real-time clock periodic tasks concurrent executor program is being written to execute multiple timed periodic tasks concurrently using modern CPU multithreading and multicores feature at specific RTC periodically. By using RTC as an absolute reference, we can analyze the status of multiple isolated devices on selected time instances to know about overall system status or each individual systems status. Multithreading program able to execute multiple tasks concurrently, making RTC periodic tasks possible. While single threaded sequential program only run multiple tasks in sequence, one at a time. Each task runtime creates delays resulting subsequent periodic tasks no longer synchronous. Nevertheless, this program can run without RTC. It becomes an isolated system, capable of performing its own synchronous operations.

Keywords: multithreaded application, multithreading, real-time clock, concurrency, concurrent execution, thread pool, periodic tasks, RTC periodic tasks, RTC ticking, critical system, sampling rate, synchronous operations, synchronous, data analysis.

Title: Real-time Clock Periodic Tasks Concurrent Executor

Author: Kin Seng, Lee

International Journal of Computer Science and Information Technology Research

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

Vol. 11, Issue 4, October 2023 - December 2023

Page No: 1-4

Research Publish Journals

Website: www.researchpublish.com

Published Date: 03-October-2023