Asian Journal of Computer and Information Systems
Asian Journal of Computer and Information Systems (AJCIS) ISSN (Online): 2321-5658
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Re-imagining Supply Chain Management through Blockchain Technology for Sustainable Practices
Introduction: Blockchain technology has emerged as a transformative tool with the potential to revolutionize various industries, including supply chain management. By leveraging blockchain technology, organizations can enhance transparency, traceability, and efficiency in their supply chains while also promoting sustainability practices. This research aims to explore the integration of blockchain technology into supply chain management to drive sustainable initiatives and address environmental and social challenges. Methodology : The research design for this comprehensive review adopts a systematic and structured approach to gather, analyze, and synthesize existing literature on the application of blockchain technology in sustainable supply chains. A qualitative research design is employed to provide in-depth insights into the principles, features, and practical implementations of blockchain in the context of sustainable supply chain management. Result: Blockchain technology is a decentralized and distribute ledger system that enables secure and transparent transactions across a network of computers. In the context of supply chain management, blockchain can be utilized to create an immutable record of transactions, product movements, and data exchanges. This transparency helps to build trust among stakeholders and ensures the authenticity and integrity of information shared within the supply chain. Sustainability has become a critical focus for businesses looking to reduce their environmental impact, improve social responsibility, and meet regulatory requirements. By integrating blockchain technology into supply chain management practices, organizations can enhance sustainability efforts in several ways: Blockchain enables end-to-end traceability by recording every transaction and movement of products along the supply chain; this transparency allows companies to track the origin of raw materials, monitor production processes, and verify ethical sourcing practices; blockchain can optimize resource utilization by streamlining inventory management, reducing waste, and improving operational efficiency; smart contracts embedded in blockchain networks can automate processes such as inventory tracking, order fulfillment, and payment settlements; Blockchain enhances supply chain resilience by mitigating risks associated with disruptions, fraud, and counterfeit products, and the decentralized nature of blockchain ensures that data is secure and tamper-proof, reducing vulnerabilities in the supply chain ecosystem. In conclusion, the integration of blockchain technology into supply chain management holds immense potential for enhancing sustainability practices. By leveraging blockchain’s transparency, traceability, and efficiency capabilities, organizations can drive positive environmental and social impact while also improving operational performance within their supply chains.
Blockchain Technology, Supply Chain Management, Sustainable Practices
Copyright (c) 2025 Tamirat Kore, Abebe Rorissa, Getachew Mamo https://creativecommons.org/licenses/by-nc/4.0
A Review of Knowledge-Based Interventions for Mental Health Self-Management
Mental health disorders have affected people's everyday lives globally, showing rapid growth. Effective detection, diagnosis, and treatment of MSDs can occur by utilizing increasingly substantial amounts of available health data from diverse sources. However, there are many challenges in developing effective treatment models for this condition. The challenges are further complicated by the volume, heterogeneity, interoperability, propagation, and complexity of data, especially with the emergence of big data. Knowledge management and knowledge-based systems have significantly impacted healthcare quality and delivery, especially patient self-management. In this work, we review knowledge-based applications for mental health self-management. The research efforts are synthesized, discussing shortcomings and future research directions.
Copyright (c) 2025 Sena Okuboyejo https://creativecommons.org/licenses/by-nc/4.0
An Empirical Comparison of Machine Learning Models for Student’s Mental Health Illness Assessment
Student’s mental health problems have been explored previously in higher education literature in various contexts including empirical work involving quantitative and qualitative methods. Nevertheless, comparatively few research could be found, aiming for computational methods that learn information directly from data without relying on set parameters for a predetermined equation as an analytical method. This study aims to investigate the performance of Machine learning (ML) models used in higher education. ML models considered are Naïve Bayes, Support Vector Machine, K-Nearest Neighbor, Logistic Regression, Stochastic Gradient Descent, Decision Tree, Random Forest, XGBoost (Extreme Gradient Boosting Decision Tree), and NGBoost (Natural) algorithm. Considering the factors of mental health illness among students, we follow three phases of data processing: segmentation, feature extraction, and classification. We evaluate these ML models against classification performance metrics such as accuracy, precision, recall, F1 score, and predicted run time. The empirical analysis includes two contributions: 1. It examines the performance of various ML models on a survey-based educational dataset, inferring a significant classification performance by a tree-based XGBoost algorithm; 2. It explores the feature importance [variables] from the datasets to infer the significant importance of social support, learning environment, and childhood adversities on a student’s mental health illness.
Copyright (c) 2022 Prathamesh Muzumdar, Ganga Prasad Basyal, Piyush Vyas https://creativecommons.org/licenses/by-nc/4.0
Utilisation of Machine Learning Techniques in Testing and Training of Different Medical Datasets
On our planet, chemical waste increases day after day, the emergence of new types of it, as well as the high level of toxic pollution, the difficulty of daily life, the increase in the psychological state of humans, and other factors all have led to the emergence of many diseases that affect humans, including deadly once like COVID-19 disease. Symptoms may appear on a person, and sometimes they may not; some people may know their condition, and others may neglect their health status due to lack of knowledge that may lead to death, or the disease may be chronic for life. In this regard, the author executes machine learning techniques (Support Vector Machine, C5.0 Decision Tree, K-Nearest Neighbours, and Random Forest) due to their influence in medical sciences to identify the best technique that gives the highest level of accuracy in detecting diseases. Thus, this technique will help to recognise symptoms and diagnose them correctly. This article covers a dataset from the UCI machine learning repository, namely the Wisconsin Breast Cancer dataset, Chronic Kidney disease dataset, Immunotherapy dataset, Cryotherapy dataset, Hepatitis dataset and COVID-19 dataset. In the results section, a comparison is made between the execution of each technique to find out which one is the best and which one is the worst in the performance of analysis related to the dataset of each disease.
Copyright (c) 2021 Maad M. Mijwil, Israa Ezzat Salem, Rana A. Abttan https://creativecommons.org/licenses/by-nc/4.0
Three-Layer Access Control Integrated with Policy Enforcement Point
Cloud computing reflects significant risks which is associated with federal agencies and regulations. Any vulnerability that is initiated in the software or platform of the vendors will lead to the leakage of the data, as information may be related to more than one organization. Likewise, next generation solution provide assistance to the legacy system along with the provision of robust, elastic and low cost knowledge based tools of deeper exploration and understanding for processing massive data right to the end users. Moreover, the next generation solution business analytics provides in depth understanding of company clientele and product presentation
Copyright (c) 2025 Nader Shahata https://creativecommons.org/licenses/by-nc/4.0
Task Scheduling Management for Load Balancing Using Task Grouping Based on Cloud Computing
Managing task scheduling management in cloud computing is an essential part for the landscape of complex procedure tasks based on various resources in a proficient and scalable path. The aim of this research is to dynamically optimize the aforesaid issue of task scheduling. The task management improvises the imperfection algorithm by pursue on weighted fair queuing model, which is significantly effective compared to the existing method. A task scheduling model has been created to demonstrate the proposed scheduler management. Study shows the improvement in the adaptation of round robin and shortest job first algorithm performing better than the existing algorithm according to the differentiate execution measurements such as, turnaround time, task size and average waiting time. In addition, context switches play an important role in algorithm by sharing between multiple tasks and running task in the scheduler. Altogether, a significant improvement between existing algorithm and proposed studies follows up accordingly to a specific context switching takes place.
Copyright (c) 2021 Ahmad Helmi Abdul Halim, Asif Iqbal Hajamydeen https://creativecommons.org/licenses/by-nc/4.0
Software Functional Complexity Using a New Set of Criteria
With the rapid technology advances, there is an emerging consensus that the size and complexity of software designs are increasing so rapidly that they proportionally affect the magnitude of administrative and development efforts. An important consideration is how to estimate software complexity. This subject continues to be a research topic in the literature. The software design process researched here uses the Unified Modeling Language (UML) diagrams and the database design for extracting pertinent information. The Entity Relationship (ER) model of Peter Chen (of MIT) is a conceptual method of describing the data in a relational structure. An Entity Relationship Diagram (ERD) and an Entity Relationship Schema (ERS) represents the ER model, containing the entities, attributes, primary and foreign keys, and the relationships between the entities. Extending this ERS modeling construct, this paper uses an additional enhanced schema, called the Object Relationship Schema (ORS), which, together with the existing ERS, creates an enhanced view of the requirements and the design of the database. In addition, functional dependency, security, computational complexity, use cases, component structure and interpretations are considered for estimating functional complexity of modern software systems which is very valuable in higher education for new workforce development.
Copyright (c) 2021 Bhaskar Raj Sinha, Pradip Peter Dey, Mohammad Amin https://creativecommons.org/licenses/by-nc/4.0
Computer Self-Efficacy and Facilitating Conditions as Correlates of Behavioural Intention to Use Electronic Information Resources by Master of Business Administration Students in Federal Universities in Nigeria
The focus of this research work was to investigate computer self-efficacy and facilitating conditions as correlates of behavioural intention to use electronic information resources by MBA students in Nigeria federal universities. Cluster sampling technique was adopted for the study and systematic sampling technique was used to select 60% of the total population of the MBA students across the ten federal universities offering the programme based on probability and proportionate size. Data were collected using questionnaire designed to elicit response from respondents and analysed using Pearson Product Moment Correlation Analysis, Multiple Regression Analysis using Partial Lease Square Method (PLSEM), Mean, Standard Deviation and Percentages. However, out of one thousand two hundred and seventy (1,270) copies of questionnaire administered to the respondents, one thousand and fifteen copies (1,015) were returned which represents 79.9% response rate for the study. Findings revealed that the level computer self-efficacy and facilitating conditions of MBA students towards use of electronic information resources in Nigeria federal universities was high. However, the study concluded that university managements and librarians should ensure rapid adoption and diffusion of ICTs and be proactive by developing relevant ICT policies and strategies toward effective and sustainable electronic information resources development in Nigerian universities, as well as promoting the use of relevant electronic information resources by MBA students to improve their quality of research and global competitiveness.
Computer self-efficacy, facilitating conditions, behavioural intention, electronic information resources, MBA students, Nigeria universities
Copyright (c) 2021 Bamidele Olawale, S. O. Popoola https://creativecommons.org/licenses/by-nc/4.0
Credit Card Fraud Detection in Payment Using Machine Learning Classifiers
The fraud detection in payment is a classification problem that aims to identify fraudulent transactions based individually on the information it contains and on the basis that a fraudster's behaviour patterns differ significantly from that of the actual customer. In this context, the authors propose to implement machine learning classifiers (Naïve Bayes, C4.5 decision trees, and Bagging Ensemble Learner) to predict the outcome of regular transactions and fraudulent transactions. The performance of these classifiers is judged by the following ways: precision, recall rate, and precision-recall curve (PRC) area rate. The dataset includes more than 297K transactions via credit cards in September 2013 and November 2017 that have been collected from Kaggle platform, of which 3293 are frauds. The performance PRC ratio of machine learning classifiers is between 99.9% and 100%, which confirms that these classifiers are very good at identifying binary classes 0 in the dataset. The results of the tests have proved that the best classifier is C4.5 decision trees. This classifier has the best accuracy of 94.12% in prediction of fraudulent transactions.
Copyright (c) 2020 Maad M. Mijwil, Israa Ezzat Salem https://creativecommons.org/licenses/by-nc/4.0
A Hybrid Relational Database Model for Uncertain and Imprecise Information
Recent years, many fuzzy or probabilistic database models have been built for representing and handling imprecise or uncertain information of objects in real-world applications. However, relational database models combining the relevance and strength of both fuzzy set and probability theories have rarely been proposed. This paper introduces a new relational database model, as a hybrid one combining consistently fuzzy set theory and probability theory for modeling and manipulating uncertain and imprecise information, where the uncertainty and imprecision of a relational attribute value are represented by a fuzzy probabilistic triple, the computation and combination of relational attribute values are implemented by using the probabilistic interpretation of binary relations on fuzzy sets, and the elimination of redundant data is dealt with by coalescing e-equivalent tuples. The basic concepts of the classical relational database model are extended in this new model. Then the relational algebraic operations are formally defined accordingly. A set of the properties of the relational algebraic operations is also formulated and proven.
Fuzzy probabilistic triple, ï¥- equivalence, uncertain and imprecise information, relational algebraic operation
Copyright (c) 2020 Hoa Nguyen https://creativecommons.org/licenses/by-nc/4.0
Character Segmentation Of Degraded Odia Script
Optical Character Recognition (OCR) is a field which converts printed text into computer understandable format that is editable in nature. Odia is a regional language used in Odisha, West Bengal & Jharkhand. It is used by over forty million people and still counting. With such large dependency on a language makes it important, to preserve its script, get a digital editable version of odia script. We propose a framework that takes computer printed odia script image as an input & gives a computer readable & user editable format of same, which eventually recognizes the characters printed in input image. The system uses various techniques to improve the image & perform Line segmentation followed by word segmentation & finally character segmentation using horizontal & vertical projection profile.
Analysis of Mobile App Revenue Models Used in the most Popular Games of the Tower Defense Genre on Google Play
This paper analyzes the revenue models of the most popular games of the Tower Defense genre on Google Play. A special look is taken at the quantitative distribution of the app sale model and the free model in terms of quality and download numbers. Additionally, this paper considers the qualitative implementation of the “freeâ€ model in the most popular games. First, the usual revenue models of mobile apps will be discussed and then the Tower Defense genre will be explained. Following that, the quantitative distribution of revenue models and an analysis of the most popular apps’ respective revenue models will be addressed. The analysis also identifies and explains two modifications of established revenue models. The most popular revenue model for mobile apps in the Tower Defense genre are in-app purchases. This distinguishes the genre from many other genres and games. A wide range of Tower Defense games utilizes the revenue models app sale and free. It becomes apparent that revenue models for mobile apps must be analyzed and considered specifically for their respective sector, and that no single promising revenue model for apps exists.
Adaptive Electrocardiogram Steganography Based on 2D Approach with Predetermined Rules
Based on two-dimensional (2D) bit-embedding/-extraction approach, we propose a simple data hiding for electrocardiogram (ECG) signal. The patient’s sensitive (diagnostic) data can be efficiently hidden into 2D ECG host via the proposed decision rules. The performance of the proposed method using various sizes of the host bundles was demonstrated. Simulations have confirmed that the average SNR of the proposed method with a host bundle of size 3 Â´ 3 is superior to that of existing techniques, while our payload is competitive to theirs. In addition, our method with a host bundle of size 2 Â´ Â 2 generated the best SNR values, while that with a host bundle of size 4 Â´ Â 4 provided the largest payload among the compared methods. Moreover, the proposed method provides robustness performance better than existing ECG steganography. Namely, our method provides high hiding capacity and robust against the attacks such as cropping, inversion, scaling, translation, truncation, and Gaussian noise-addition attacks. Since the proposed method is simple, it can be employed in real-time applications such as portable biometric devices.
Ergonomics and Ergonomic Analysis of Driving Education System by Personal Car-2
The subject of IT-supported car training/education system was selected for the research below in the previous article. For the well-known hypothesis, out of the three existing parts, the driver-machine-car subsystem was first selected to handle the theoretical hypothesis; presented later. Thus, the following eight subsystems or parts for human participants are listed: nerve area; sense of sight or visual organ of the eye; hearing aid or hearing organ ear; motion observations; psychological factors, mental and psychomotor properties; individuals' reactions and causes of reactions; types of drivers; the influence of alcohol on road safety. In the practical part of the article, based on the vast amount of data, several analyzes were conducted. The vast amount of data requires multiple publication of the complete content of the thesis, where each new content unit / article must have both parts, both theoretically and practically. To our knowledge, a unique list of 19 types of errors was made, with a detailed description of them. The terms of different types of driving are explained in particular: polygon, city traffic and examinations, as well as the differences between them. In the series of analysis, the terms driving type, teaching unit, candidate and driving hours were taken as the independent variable, while the error types with the predominant frequency characteristic were taken as the dependent variable. Practical parts are supported with IT processing. Appropriate ideas and measures for improvement have been proposed. The articles gratefully acknowledges Prof. B.Sc. Marijan BiÅ¡ÄaniÄ‡ and prof. Ph.D. Dragutin Mikšić for their contribution.
Information Security: Awareness and Training Program in the Middle East Universities
An effective Security Awareness and Training (SAT) program enables organizational members to understand the organization’s security strategies, know their responsibilities, and control risks that are caused by security incidents. Therefore, deploying a SAT program is one of the most important steps for any organization to assure that information assets are appropriately secured. The aim of this paper is into folds: first, to gain an insight and determine the information security awareness and training program levels in Middle Eastern higher education sector through a case study that examined 182 institute websites over eight countries. Second, to provide recommendations based on the findings that aid information security professionals to establish a new or improved existing awareness and training program. Literature showed that no study has been done on the SAT program at the level of the Middle Eastern region. However, there was a need to this investigation and therefore, it was a pioneering study at the region level in the field of information security.
Postgraduate Students’ Acceptance of On-line Databases: A Validation of UTAUT Model in Selected Universities in Nigeria.
Abstract The purpose of this study was to validate the Unified Theory of Acceptance and Use of Technology (UTAUT) model on the acceptance of on-line databases among postgraduate students in Nigeria. the study investigated the four based constructs of UTAUT that is performance expectancy (PE), effort expectancy(EE), social influence (SI) and facilitating conditions (FCs) as the determinants of behavioural intention to use and eventual usage of on-line databases. The study adopted a descriptive survey research design. The population was made up of postgraduate students from Ekiti State University, Ado-Ekiti, and Federal University of Technology, Akure; Nigeria. Data were collected using questionnaire designed to elicit response from respondents and analysed using descriptive statistics method of frequency counts and percentages. However, out of two hundred and twenty five (225) copies of questionnaire administered to the respondents one hundred and eighty six (186) were returned which represents 82.7% response rate for the study. Findings revealed that all four variables i.e. (PE), (EE), (SI) and (FCs) had positive and significant effect on users' behavioural intention to use on-line databases. It was recommended that infrastructure such as computers and high-speed and affordable internet required are provided for easy access in Nigerian universities among other recommendations.
on-line databases and postgraduate students.
Application of the ITIL Method for Management in Practice
The chosen basic and the most important one is the ITIL method. An investigation hypothesis is set, that system and processes are not in sufficient measures in line with theoretical settings from the literature and with some of those are from good practices. It is researched and conducted in the spirit of analytics with the aim of alternative and possible better application of ITIL legality. Collected and analyzed facts and data are compared with the theoretical settings of the ITIL method in management with my own 10 years of experience, knowledge and skills, applicable in good practices. By applying previously cited entries, there is a need to propose ways and conditions of correction of applying the ITIL method, with more successful results. Entire procedures of the ITIL Method are supported by IT. Acknowledgement is dedicated to Domagoj Car, bacc.oec., because of processing his own Expert final work on Graduate studies.
Ergonomics and Ergonomic Analysis of Driving Education System by Personal Car with Supporting ITÂ Â
The subject of the car education / training system, with IT support, was selected for research. The hypothesis was set: to analyze the theory and empiricism of the collected data and to determine the characteristics for the elements of the system and the influences among them. The necessary updating and reworking of the sample operation was made. A multidisciplinary and interdisciplinary science called Ergonomics and Ergonomic Analysis have been selected for this very complex research. First, all the individual parts of the system are presented right down to the theoretical facts, then the individual parts in the subsystem are presented, and finally the whole ergonomic system is presented. In the practical part of the article, many analyzes were performed on the basis of the vast amount of data collected, based on six characteristics. From mathematical statistics and probability theory, major analyzes were performed, including two types of different sample sizes, with cumulative and average values. The enormous scope requires multiple content publishing, where each individual article must have both parts, theoretical and practical. Concrete ideas and measures for implementation have been proposed. Practical parts are supported with IT. The article Â is Â aknowledgement to late B.Sc.Mech.Eng. Marijan BiÅ¡ÄaniÄ‡ and prof. Ph.D. Dragutin Mikšić for their contribution.
Multithread Affinity Scheduling Using a Decision Maker
In a multiprocessor-multithread Operating System (OS), scheduling has two dimensions. The operating system has to decide which thread to run and which Central Processing Unit (CPU) to run it on. Assume the threads are independent and each thread has a priority, the operating system selects a thread with the highest priority and assigns it to the first free CPU. Usually, each CPU has its private cache. To increase the throughput of the system, it is preferred to use affinity scheduling. The affinity scheduling concept is to make an effort to have a thread run on the same CPU it ran on the last time. The existing affinity scheduling is implemented by using a two-level scheduling algorithm. In this paper a new approach is designed to implement independent multithread scheduling on a multiprocessor system. The design approach uses a decision maker to compute a new priority for each ready thread according to the thread pre-priority and affinity. The results show that by using the new priority, the goal of having affinity is satisfied in addition to taking the pre-priority of the thread in consideration. Also, the design approach reduces the scheduling time because it implements affinity scheduling and priority scheduling by employing a one level scheduling algorithm.
Evaluation of the Development Framework Jasonette
In this paper we evaluate the development framework Jasonette which is based on JSON. The evaluation was carried out by means of a prototype of an app informing prospective students about the study program Enterprise Computing at the Mannheim University of Applied Sciences. We defined a set of criteria that we cross checked during and after the implementation of the app.
Decision Fusion based Person Identification System using Fingerprints and Facial Image with Template Matching
In this research, it has been developed a prototype biometric system which integrates facial images and fingerprints. The system overcomes the limitations of face recognition systems as well as fingerprint recognition systems. The integrated prototype system operates in the identification mode with an admissible response time. The identity established by the system is more reliable than the identity established by a face recognition system. In addition, the proposed decision fusion scheme enables performance improvement by integrating multiple features with different confidence measures. Experimental results demonstrate that the system performs Â well. It meet up the response time as well as the accuracy requirements.
A Data Exchange Interoperability Framework for eHealth Applications in Ethiopia
Interoperability between applications is important and creates a bridge between and facilitates data exchange between eHealth applications. In this study, we assess the existing Laboratory Information Systems (LIS) and Electronic Medical Record (EMR) for data exchange interoperability in Ethiopia with the view to proposing and developing a data exchange interoperability framework. We applied a qualitative research method to explore the status of e-Health applications (LIS and EMR) based on functional test done. Using a constructive method, a data exchange interoperability framework on eHealth applications was designed. NVivo-10 software was used for coding the interview and data analysis. The framework is tested by the developers and decision makers. The proposed and designed framework is encouraging for future change.
Adoption and Implementation of Health Information System in Limited Resource Setting: A Survey on User Experience Perspective
Understanding the situation is essential to bring sustainable health information system. It helps to get the detail of the context, methods of communication and tools experienced that will ensure the sustainability of the system. The majority of the research confirms failure is the known end result of information system in developing countries. In principle, information system projects are trying to involve users and collaborate with stakeholders throughout the design process such as requirement gathering, requirement specification, implementation and design, testing, training and so on. Most of information system projects in developing countries will face a difficulty of getting appropriate user requirement and engagement. The consequence of these will degrade the success rate and create fragile information system. Assessment review of Ethiopian Health Information System (EHIS) also noted that the system struggle with poor data management, system resources, dissemination and use of information system. The EHIS review noted that 52% of the components were present but not adequate. However, inadequateness and the fragility of the system mainly arise from lack of appropriate user involvement and requirement. User experience design has been known to create an influence and increase level of participation in the process, but not fully explored in the fragile system and low resource setting scenario. The story of health information in low resource setting is examined. User experience design and participatory design model is proposed as a solution to outline critical issues and mode of communication to increase the success rate of health information system adoption and implementation.
Health System Adoption and Implementation
System Configuration and Error Performance of Spectral Amplitude Coding Labels in Multi-Rate Optical MPLS Network
In this paper, we propose a simple scheme for optical multi-protocol label switching (MPLS) network to support multi-rate data transmissions. Spectral-amplitude coding (SAC) labels of stuffed quadratic congruence (SQC) codes are used for packet switching without multiple access interference (MAI). System performance is analyzed by taking the effects of phase-induced intensity noise (PIIN) and thermal noise into account. We also compare the bit-error rate (BER) of MPLS network with the system where labels of M-sequence codes are employed.
Balanced Incomplete Block Design (BIBD).
Factors Influencing People’s Intention to Adopt E-Banking: An Empirical Study of Consumers in Shandong Province, China
E-Banking is growing at an unprecedented rate and has become a truly worldwide phenomenon, offering convenience, flexibility and interactivity for those that can, and know how to access it. This is clearly evidence in China. However, despite such growth and popularity, some users still have reservations about using Information and communication technology (ICT) in their daily banking activities, perhaps due to deep routed cultural factors that cause consumers to question the efficacy of such changes. Through the application of a technology acceptance framework, and empirical evidence from 52 E-Banking user questionnaires and four key market segment interviews, the research explores the factors that influence consumers’ intention to adopt E-Banking in Shandong Province of China. The findings highlight that perceived usefulness and perceived credibility are significant factors which have a positive influence on consumers’ intention to utilise E-Banking, while perceived ease of use and perceived cost are less significant. Unpacking the reasons for resistance to the use of E-Banking highlighted that “difficult to operateâ€, “unnecessary to use itâ€ and “worry about the securityâ€ are key drivers and therefore challenges for the service providers. Based on the results, recommendations are drawn for banks, involving focusing on the significant factors, avoiding weaknesses and optimising strengths of E-Banking and ultimately developing more accurate market positioning strategies to align and manage consumer expectations and maximise potential acceptance.
Framework for Enhancement Performance of Heterogeneous System via Social Network Analysis
In recent decades, social network analysis arise as a powerful tool for describing social competitive systems. Vertices, or entities represent states or nodes or agents, while edges represent relations between different nodes. A graph theory is a suitable way for simulating complicated systems. This paper presents framework and architecture to improve system performance using social network analysis. System crawling then web blog analysis is a methodology to clustering and exploring community nodes. Graph and semantic network used for simulate agents and edges. The proposed architecture involves two consecutive modules affecting system performance. Clustering is a first module which simulate vertices and it's edges with user supervised for filtering nodes and attribute , while supervised and Â machine learning module stimulate the agents for optimal path and performance under complicated environment circumstances. Data prepared from social networks, relations extracted, and crawling with breadth first search with some small graphs as a base are maintained. The proposed framework affect the performance of learning in university as a sample of community through analyzing and maintaining relations and features enhancement which are achieved via supervised machine learning. The proposed system can be implemented to a various social institutes or organizations, using its webs or blogs with different queries from interviews and emails to enhance its performance.
Personal Computer Usage and Security Threats in the New Juaben Municipality, Ghana
Personal computer (PC) usage in Ghana is on the rise but its security threat lacks behind because most PC owners do not know how to guard themselves and unaware of it danger. This paper studies the current state of PC security threat in the New Juaben Municipality, Eastern Region Ghana. SPSS was used to analyze the questionnaires gathered. The results suggest that (i) good authentic password does not guarantee PC owners safety, (ii) lapse in anti-virus routine update empowers malicious attackers to attack personal computers and (iii) PC’s owners are not free from privacy threat so far as they subscribe to free email accounts.
Multi-Radio Platform for WBAN MAC Protocol
Wireless Body Area Network (WBAN) designed for medical, sports, and entertainment application have drawn the attention of academia and industry alike. A WBAN is a special purpose network, designed to operate autonomously to connect various medical sensors and appliances, located inside and outside of a human body. This network enables physicians to remotely monitor vital signs of patients and provide real time feedback with medical diagnosis and consultations. The WBAN system can offer two significant advantages compared to current electronic patient monitoring system devices. The first is mobility of patient due to use of portable monitoring devices. Second advantage is the location independent monitoring facility. With its appealing dimensions, it brings about a new set of challenges, which we do not consider in such small sensor network. It requires an scalable network in terms of heterogeneous data traffic, low power consumption of sensor nodes, integration of in and around the body networking and coexistence. This work presents a medium access control protocol for WBAN which tries to overcome the challenges specified. We have used Multi-Radio. The evaluation of multi-processor architectures is supported by extrelmely flexible and fully reconfigurable FPGA processing hardware. The use of parallel radio transceivers allows the simultaneous data exchanges with the different neighbors at the same time. As a design case multiprocessor implementations for 1 to 4 parallel Nios II softcore processors with performance measurements are presented. Only WBAN Coordinator (BAN_C) node is mounted with the multi radio multiprocessor.
After IT Outsourcing: An Exploratory Research of an Agency of Taiwan from the Perspectives of IT Personnel’s Ability and IT Budget Allocation _
Building an Information System is essential for achieving the goal of implementing Electronic Government (E-Government). Â Outsourcing has become the strategy for Taiwan government in terms of building the Information Systems. Â Sixty percent of the Information Technology (IT) budget for Taiwan government was spent on maintaining and operating the information systems built by the contracting companies in 2014. Â The ability of IT personnel and IT budget allocation for a government agency may have an impact on the operation of the information system. Â However, there is limited literature about it. Â This exploratory research used in-person observation and In-depth interviews to study an information system inside X agency of Taiwan government. Â This study found that since the IT personnel in this agency did not involve in the development of the system, even though the IT personnel in this agency had sufficient technical skills, the lack of knowledge of technical details of the system weakened their ability to operate and maintain the system. Â This study also found the limited budget made operation cost a priority over system upgrades. Â The insufficiency of technical knowledge of system not only impair the normal operation of system, it also made adequate budgeting for IT department difficult. Â This study provides practical solution and recommendation for future researches.
A Study of Young Taiwanese Consumers’ Attitude toward Internet Transnational Surrogate Buyer Service: Perspectives from Merchandise Attribute, Consumers’ Perceived Result and Characteristics
With the increasing popularity of Internet usage, Internet economy has flourished. The total revenue of Taiwan’s Internet business was 562 billion NT dollars in 2011 and 10% of it was contributed to overseas shopping. Based on Theory of Reasoned Action, this study investigates the relationship between selected variables and consumers’ attitude towards using Internet transnational surrogate buyer services. The selected variables include merchandise attributes (price, brand name and warranty), consumers’ perceived results (benefit and risk), consumers’ characteristics (openness and materialism). The results of this study show that all but two of our hypotheses are supported by our empirical data. Based on the findings of this study, price and warranty do not have significant impact on consumers’ behavior on using Internet Transnational Surrogate Buyer Service. Therefore, this study suggests that Internet transnational buyer service providers need to pay more attention to ‘brand name’ instead of ‘price’ or ‘warranty’ when they develop marketing strategy.
Internet transnational surrogate buyer service