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International Journal of Information Engineering and Electronic Business @ijieeb
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 658
The Philosophy of Smart Learning Using the Approach Thomas Kuhn Paradigm Shift
Статья научная
The impact of technology must be addressed by the educational methods themselves and their perspectives in the new paradigm of citizenship in this intelligent environment. Learning environments have changed dramatically in the last 50 years, in large part due to information and communications technologies. The study uses a qualitative descriptive. Thomas S. Kuhn, fully Thomas Samuel Kuhn, (born 18 July 1922 in Cincinnati, Ohio, USA-17 June 1996 in Cambridge, Massachusetts), best known for The Structure of the Scientific. Kuhn explains that in every scientific discipline, there are some identified and natural phenomena that are then investigated experimentally and explained theoretically. Pre-paradigm as the basis of normal science, the formation of smart learning is started when primitive cave. Normal science for learning is a traditional teaching method, teaching takes place within the four walls of a classroom. Anomalies are surprising discoveries that cannot be defined through a paradigm, together with discoveries of troubles that cannot be solved through a paradigm. The lock down following the COVID-19 pandemic has made us extrude in a single day from mastering withinside the bodily international to mastering withinside the virtual one. Model crises are the third phase of the Kuhn cycle. Triggering the Model Crisis movement Blended learning can be the brand new normal – “Blended learning”. The smart learning cognizance and traits has emerged as a brand-new fashion withinside the international academic field. different smart technologies, consisting of cloud computing, learning analytics, huge information, Internet of things (IoT) and wearable generation.
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The Role of Knowledge Management in Enhancing Organizational Performance
Статья научная
Knowledge management is recognized as an important weapon for sustaining competitive advantage and improving performance. The evaluation of knowledge management (KM) performance has become increasingly important since it provides the reference for directing the organizations to enhance their performance and competitiveness. This paper provides an understanding of factors that involved in implementing knowledge management concept to enhance organizational performance. Also, it provides an assessment tool that helps organizations to assess their knowledge management capabilities and identify the possible existing gaps in their knowledge management systems and suggest the possible ways to enhance organizational performance. The results show that all elements of knowledge management capabilities have a positive significant relationship with all measures of the performance at 1% level of significant; it means that there is a great correlation between knowledge management capabilities and organizational performance
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The Series of Leaflets as Media for Education, Promotion and Monitoring of Exclusive Breastfeeding
Статья научная
Mother's knowledge about the importance of exclusive breastfeeding is a problem that determines the success of exclusive breastfeeding. Information support is needed to increase the mother's knowledge. This research create an acceptable media for increasing breastfeeding mother's knowledge of exclusive breastfeeding. This research uses the action research method. There are 5 stages including diagnosis, making an action plan, acting, evaluating and learning. The informants of this research are the baby mothers, maternal and child health services cadres and the breastfeeding counseling team at the Pleret health centre. Data collection instruments and techniques using questionnaires and interviews. Credibility test with technical triangulation, which was analyzed using theories from Milles and Huberman. The creation of a series of leaflet media about exclusive breastfeeding guidelines consisting of six series. Leaflets are made attractive in terms of design. This series of leaflet media effective as an educational and promotional media about exclusive breastfeeding.
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The Split Domination in Product Graphs
Статья научная
The paper concentrates on the theory of domination in graphs. The split domination in graphs was introduced by Kulli and Janakirm. In this paper; we have investigated some properties of the split domination number of some product graphs and obtained several interesting results.
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The Usability of Agent-Based Simulation in Decision Support System of E-Commerce Architecture
Статья научная
Electronic commerce (e-commerce) has the potential to improve the competitiveness of the enterprises. A decision support system, used in e-commerce, is a term used to describe any software engine that enhances the user’s ability to make decisions. The paper presents a new approach for decision support system modeling. This approach is applied by a modification and extension of existing decision support system architecture by multi-agent technology and agent-based simulation models. Multi-agent technology is one of the fastest growing fields of information and communication technology – new agent-based services, products, and applications are being developed almost every day. Agent-based simulation model is applied to coordinate, control, and simulate the architecture of decision support system, used in e-commerce. The proposed architecture improves the existing decision support systems and gains competitive advantage.
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The proposed L-ScrumBan methodology to improve the efficiency of agile software development
Статья научная
Agile software development methodologies gaining the attention in the field of software engineering. There are several methods of agile such as Scrum, Lean, and Kanban. Scrum methodology divides the product into series of sprints. Lean is agile toolkit which has seven principles that facilitate: eliminating the wastes, delivering fast, and improving value for the final customer. Kanban is a visual method that can help in managing the production. To take the advantages of the following methodologies: Lean, Scrum, and Kanban we can integrate them together thus, the result will be a new methodology that can contribute in enhancing and improving the efficiency of the software development process, which is the aim of this thesis. An integrated methodology that integrating Scrum, Kanban, and Lean methodologies to yield a comprehensive agile methodology called L-ScrumBan has been proposed. The validation of the proposed methodology has been done through a survey by using a questionnaire; the survey results confirmed the efficiency of the proposed methodology.
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Статья научная
Keyword extraction approaches based on directed graph representation of text mostly use word positions in the sentences. A preceding word points to a succeeding word or vice versa in a window of N consecutive words in the text. The accuracy of this approach is dependent on the number of active voice and passive voice sentences in the given text. Edge direction can only be applied by considering the entire text as a single unit leaving no importance for the sentences in the document. Otherwise words at the initial or ending positions in each sentence will get less connections/recommendations. In this paper we propose a directed graph representation technique (Thematic text graph) in which weighted edges are drawn between the words based on the theme of the document. Keyword weights are identified from the Thematic text graph using an existing centrality measure and the resulting weights are used for computing the importance of sentences in the document. Experiments conducted on the benchmark data sets SemEval-2010 and DUC 2002 data sets shown that the proposed keyword weighting model is effective and facilitates an improvement in the quality of system generated extractive summaries.
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Theoretical Validation of Inheritance Metrics for Object-Oriented Design against Briand's Property
Статья научная
Many inheritance metrics can be found in the literature, but most of those are validated theoretically by using Weyuker's property. Theoretical validation of inheritance metrics using Briand's property is rare in the literature. This paper considers the metrics proposed by Rajnish and Sandip and presents a theoretical validation of the inheritance metrics using the Briand's size and length properties of an inheritance hierarchy. This paper also gives the projection and viewpoint of the inheritance metrics.
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Theory of Fuzzy Sets: An Overview
Статья научная
In this article, we would like to revisit and comment on the definition of complementation of fuzzy sets and also on some of the theories and formulas associated with this. Furthermore, the existing probability-possibility consistency principles are also revisited and related results are viewed from the standpoint of the Randomness-Fuzziness consistency principles. It is found that the existing definition of complementation as well as the probability – possibility consistency principles is not well defined. Consequently the results obtained from these would be inappropriate from our standpoints. Hence we would like to suggest some new definitions for some of the terms often used in the theory of fuzzy sets whenever possible.
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Time Series Forecasting Enhanced by Integrating GRU and N-BEATS
Статья научная
Accurate stock price prediction is crucial for financial markets, where investors and analysts forecast future prices to support informed decision-making. In this study, various methods for integrating two advanced time series prediction models, Gated Recurrent Unit (GRU) and Neural Basis Expansion Analysis Time Series Forecasting (N-BEATS), are explored to enhance stock price prediction accuracy. GRU is recognized for its ability to capture temporal dependencies in sequential data, while N-BEATS is known for handling complex trends and seasonality components. Several integration techniques, including feature fusion, residual learning, Ensemble learning and hybrid modeling, are proposed to leverage the strengths of both models and improve forecasting performance. These methods are evaluated on datasets of ten stocks from the S&P 500, with some exhibiting strong seasonal or cyclic patterns and others lacking such characteristics. Results demonstrate that the integrated models consistently outperform individual models. Feature selection, including the integration of technical indicators, is employed during data processing to further improve prediction accuracy.
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Time-Frequency Wavelet Based Coherence Analysis of EEG in EC and EO during Resting State
Статья научная
The electrophysiological brain activities are nonlinear in nature as measured by Electroencephalography (EEG). There are coherent activities in brain not only seen during explicit tasks but also during rest. This article aims to employ most robust nonlinear dynamics Time - Frequency representation (TFR) techniques such as wavelet phase coherence to investigate brain activity in different frequency bands at temporal and spatial scale dynamics in form of topographic maps in resting state networks. The TFR has the advantages to study the combined effect of time and frequency domains simultaneously. The wavelet coherence computed in this way exhibit high precision to detect the phase coherence in different frequency intervals to analyze highly complex non-autonomous and non-stationary EEG signals. The spatiotemporal dynamics of resting state networks are investigated by computing coherence. We have investigated the Wavelet based Phase coherence of oscillations of eye closed and eye open signals during resting states. The wavelet coherence is computed for selected 19 electrodes according to 10-20 system from 129 channel EEG signals. The significance was obtained using Wilcoxon Signed Rank test and pairwise wavelet coherence was computed for each possible combination. The Wavelet Phase Coherence using Wavelet Transform gives significantly high results (P<0.05) in EC and EO signals during resting states in frequency interval 0.5-50 Hz overall as well as in the band intervals such as delta (05-4 Hz), theta (4-7 Hz), alpha (7-13 Hz), beta (13-22 Hz) and gamma (22-50 Hz). By computing the spatial wavelet phase coherence, we observed significant pathways including sagittal factor (anterior-posterior interhemispheric) and lateral factor (perpendicular to anterior-posterior axis). The lateral factor differences have less affect than the sagittal factor. Each band was involved in different activities in some way, however alpha band showed distinct anterior-posterior activity when the eye-closed coherence was higher than the eye open coherence.
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Top-k Closed Sequential Graph Pattern Mining
Статья научная
Graphs have become increasingly important in modeling structures with broad applications like Chemical informatics, Bioinformatics, Web page retrieval and World Wide Web. Frequent graph pattern mining plays an important role in many data mining tasks to find interesting patterns from graph databases. Among different graph patterns, frequent substructures are the very basic patterns that can be discovered in a collection of graphs. We extended the problem of mining frequent subgraph patterns to the problem of mining sequential patterns in a graph database. In this paper, we introduce the concept of Sequential Graph-Pattern Mining and proposed two novel algorithms SFG(Sequential Frequent Graph Pattern Mining) and TCSFG(Top-k Closed Sequential Frequent Graph Pattern Mining). SFG generates all the frequent sequences from the graph database, whereas TCSFG generates top-k frequent closed sequences. We have applied these algorithms on synthetic graph database and generated top-k frequent graph sequences.
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Статья научная
With the advent of W3C standards such as DID, VCs, and DPKI beyond 2020, the industry has reached a new level where a technological infrastructure overhaul is possible. By employing blockchain and other Decentralized Ledger Technologies, it is believed that we can eliminate the requirement for paper-based verification. Researchers are aware of the technological components we possess at present and are trying to bring forth their sets of POCs. Additionally, governments ranging from developing to developed countries are taking industrial initiatives that incorporate these technologies. This research also evaluates the latest events and cases to find the need for paperless verification. Previous development conducted in the domains of Information Systems and Public forensics has presented us with various issues at both infrastructural and user levels. It also introduced us to the presence of lots of gaps present that can be improved with a more improvised form of decentralized paperless solution. Researchers have pointed out that the modern day identity check and forensic solutions will face difficulties with blockchain compatibility, since most of those previous components will require built-in integration with a decentralized environment. As the latest researches suggest the key to this integration is now possible with the proper application of the W3C standards. In this paper, we propose an architecture that interlinks the latest decentralized W3C standards with a permissioned blockchain for implementing paperless verification and identity check.
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Towards data exchange between health information system and insurance claims management system
Статья научная
The advancement of technology observed today has led to the development of many Health Information Systems (HIS) which are cost-effective, reliable, scalable and flexible. Moreover, integrated Health Information System (iHIS) plays a crucial role in the dissemination of information, which helps in decision-making. The care2x HIS in Tanzania does not have a module for exchanging data between Care2x HIS and the National Health Insurance Fund (NHIF) claims management system. The absence of this module in Care2x has resulted into long waiting time for a patient, inaccuracy of the data submitted in claim forms, the consumption of time when processing claims, delay in processing payment and the high costs incurred in printing claims forms. In this paper, we used both qualitative and quantitative methods to gather the requirements for the development of the module. Interviews, questionnaire and document review were employed in data collection. The requirements were gathered with the help of 12 practitioners and one Information Technology (IT) specialist from NHIF headquarters. The results showed that the integration of the data exchange module is very potential in solving the present challenges. The data exchange module between Care2x HIS and NHIF Claims management System will increase the accuracy of claims submitted and reduce the cost for printing claims forms and time spent in filling and processing claims.
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Статья научная
To contribute in filling up the semantic gap in data warehouses and OLAP data cubes, and enable semantic exploration and reasoning on them, this paper highlights the need for semantically augmenting Geo/BI data with convenient semantic relations, and provides OWL-based ontologies (ODW and OOLAP) which are capable of replicating data warehouses (respectively OLAP data cubes) in the form semantic data with respect of Geo/BI data structures, and which enable the possibility of augmenting these semantic BI data with semantic relations. Moreover, the paper demonstrates how ODW and OOLAP ontologies can be combined to current Geo/BI data structures to deliver either pure semantic Geo/BI data or mixed semantically interrelated Geo/BI data to business professionals.
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Two Level Hybrid SECO Environment for Secure Cloud Environment
Статья научная
As cloud computing becomes prevalent, sensitive information are being increasingly centralized into the cloud. Number of users used cloud to store their data. In general terms means encrypted form hackers can easily hack or modify the data because there is no security while uploading the data to cloud server. Due to this problem cloud server can easily deployed. As security is one of the major concerns in cloud environment for preventing data deployment during upload. The best solution for the protection of data privacy is done by encryption the sensitive data before being outsourced to cloud server, which makes effective data utilization a very challenging task. There are a number of security and privacy concerns associated with cloud computing but these issues fall into two broad categories: security and privacy concerns faced by cloud providers and security and privacy concerns faced by their customers. Different set of algorithms have been implemented on cloud environment for enhancing the security but still there are some major concerns like malicious attacks. In previous work on AES based encryption and a SECO based environment were introduced.. In SECO based environment root package generated key by using diffie-hellman algorithm and domain package generated key by using private key of root package. In AES algorithm and SECO based environment individually provided some sort of level encryption. In this both algorithms work on single level encryption approach which may be easily broken by malicious users. So, in proposed work both techniques that is AES and SECO based environment will be combined to provide two level security and also will double the encrypted environment which may not be easily broken by malicious users. Result will be more efficient and secure than the previous work.
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Статья научная
An Enterprise Resource Planning (ERP) system is a software application that serves as a centralized platform to streamline and automate organizational functions and share real-time data, facilitating efficient communication and collaboration. It provides an all-inclusive approach to managing and optimizing business processes, boosting efficiency, fostering cooperation, and giving an overall picture of how the organization is operating. However, the traditional centralized databases in ERP systems pose security concerns. Blockchain Technology can be an appealing alternative as it comes with immutable and decentralized data as well as enhanced security. This study focuses on two methods of securing data management in ERP systems: Organizing the distributed information using The Ralph Kimball data model and optimizing an individual block using Database Sharding. This study does an extensive examination to determine the effectiveness of both suggested strategies, comprising a detailed evaluation that highlights the benefits and limitations of both techniques. This paper intends to patch the security holes in ERP systems to safeguard sensitive data and mitigate risks.
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URLGuard: A Holistic Hybrid Machine Learning Approach for Phishing Detection
Статья научная
The fast growth of Internet technology has significantly changed online users’ experiences, while security concerns are becoming increasingly overpowering. Among these concerns, phishing stands out as a prominent criminal activity that uses social engineering and technology to steal a victim’s identification data and account information. According to the Anti-Phishing Working Group (APWG), the number of phishing detections increased by 46 in the first quarter of 2018 compared to the fourth quarter of 2017. So to overcome these situations below paper introduces a phishing detection system using a hybrid machine learning approach based on URL attributes. It addresses the growing threat of phishing attacks that exploit email manipulation and fake websites to deceive users and steal sensitive data. The study employs a phishing URL dataset with over 11,000 websites, extracted from a reputable repository. After pre-processing, a hybrid machine learning model, which includes Decision Tree, Random Forest, and XGB is employed to safeguard against phishing URLs. The proposed approach undergoes evaluation with key metrics such as precision, accuracy, recall, F1-score, and specificity. Results demonstrate that the proposed method surpasses other models, achieving superior accuracy and efficiency in detecting phishing attacks.
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USSD System for Monitoring and Management of Employee Leave in Higher Educational Institution
Статья научная
Unstructured supplementary service data also referred to as feature code or quick code has become a monumental part of services and products offered by Telecommunication Operators, and its application to various areas of telecommunication and real-world scenarios. It is a protocol of communication utilized by global system for mobile communications cell phones to communicate with mobile telecommunication network operators and applicable to various areas of trend in modern information technology sectors such as Wireless Application Protocol browsing, mobile-money services, prepaid call back services, menu-based information services, location-based content services, paid content portal, voting surveys, and product promotion. This system was designed by integrating the designed unstructured supplementary service data channel for employee leave management system into the standard global system for mobile communications architecture. The architecture consists of three parts; the front end, the middle end, and the back end. The system is implemented using PHP for the overall programming, MySQL for the database, and Windows 7 operating system as a development environment with Adobe dream weaver CS3 IDE. Apache TOMCAT webserver was used to host the system locally. Two interfaces were developed; one side with the mobile operators, which requires setting up of SS7 stack and the unstructured supplementary service data application over the stack. On the other side, HTTP-basedAPIs were used for the unstructured supplementary service data application. Several types of leaves exist and their usage depends on educational institution policies. An employee may apply for study leave like maternity leave, sick leave, and annual leave. Paper-based work is time consuming, USSD based activities are very simple and effective. This research work was conducted to solve the leave management in an academic institution using the USSD. Using the developed system, 1326 USSD sessions were recorded, 1238 sessions were successful, 59 were incomplete, and 29 failed. Cumulative findings from the 41 respondents reveal that the system is faster, more convenient, and user-friendly than the manual method of applying and managing employee leave, which indicates 94% of the success of the system. Thus, it can be concluded that the system was able to manage the leave management very well and very effectively.
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Unified Domain Adaptation with Discriminative Features and Similarity Preservation
Статья научная
In visual domain adaptation, the goal is to train effective classifiers for the target domain by leveraging information from the source domain. In unsupervised domain adaptation, the source domain provides labeled data while the target domain lacks labels. However, it is crucial to recognize that the source and target domains have different underlying distributions despite sharing the same label space. Directly applying source domain information to the target domain often leads to poor performance due to the distribution gap between the two domains. Unsupervised do- main adaptation aims to bridge this gap and improve performance. We introduce a comprehensive UDADFSP (Unified Domain Adaptation with Discriminative Features and Similarity Preservation) de- signed explicitly for unsupervised domain adaptation to tackle these challenges. Our framework focuses on incorporating discriminative and invariant features. We employ clustering with entropy regularization on the unlabeled target domain to refine the neighbor relationships. This step significantly enhances the alignment between the target and source domains, facilitating a more effective adaptation. Furthermore, we seamlessly incorporate discriminative features while preserving similarity in the source and target domains. We carefully balance the discrimination and similarity aspects by considering linear and non-linear data representations. Extensive testing demonstrates that learning discriminative and similarity features in the same feature space yields significant improvements over several state-of-the-art domain adaptation techniques. In a comparative evaluation, our approach surpasses several existing methods across four diverse cross-domain visual tasks and the Amazon re- view sentiment analysis task.
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