- Все статьи 611
Статьи журнала - International Journal of Information Engineering and Electronic Business
Все статьи: 611
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-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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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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User story based information visualization type recommendation system
Статья научная
To help users to determine the most appropriate visualization type is a useful feature of business visualization tools. Existing systems often give preliminary suggestions based on data sources but usually cannot make practical final decision. User stories are generalizations of user requirements. To recommend visualization type based on user stories can make better use of human experience to achieve automated decision making. One approach discussed in the paper is using machine learning techniques to model existing visualization types with corresponding user stories, and then use this model to predict recommended visualization type for new user story. This paper designs and implements a recommendation system prototype ReViz to verify the feasibility of this approach. As a typical web application, Modeling, Input Processing and Predicting components of ReViz are programmed using Python with Flask framework and Anaconda package set, and user interface is implemented using HTML, JavaScript and CSS with Bootstrap front-end library. The evaluation results show that ReViz can give recommended visualization type based on user story keywords. As a data-based intelligent software development technology achievement, visualization type recommendation system can also be integrated into larger business information management systems.
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Using publications linked open data to define organizational policies
Статья научная
Researchers around the world are publishing their scientific research results in different forms such as books, journal articles, reference works and project reports. Publishers of these scientific documents usually describe them by using metadata for organizational purposes. This metadata provides a rich information about scientific documents that can be used for analysis purposes such as measuring the impact of researchers and research centers. It can also be used to find scientific documents published in domain of some ones interest, which ultimately can be used to raise the state of the art to the next level. Scientific publications metadata can also be used to analyze the quality and directions of common and highly cited individuals and organizations, and based on this analysis other individuals and organizations can define directions for their future work and research. However, the main limitation of this metadata is that it is available in different formats that might not facilitate the analysis of scientific documents. Therefore, in this paper we clarify that how our SPedia knowledge base (a semantic based knowledge base of scientific publications metadata which we extracted by using SpringerLink as information source) facilitates the analysis of scientific data for policy making. We discuss different kind of questions that can be answered through SPedia knowledge base and we show that how results of these questions can be used to analyze the performance of individuals as well as organizations. We also show that how results of such analysis can help in making organizational policies regarding future research directions.
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Validation lamina for maintaining confidentiality within the Hadoop
Статья научная
In the white paper we strive to cogitate vulnerabilities of one of the most popular big data technology tool Hadoop. The elephant technology is not a bundled one rather by product of the last five decades of technological evolution. The astronomical data today looks like a potential gold mine, but like a gold mine, we only have a little of gold and more of everything else. We can say Big Data is a trending technology but not a fancy one. It is needed for survival for system to exist & persist. Critical Analysis of historic data thus becomes very crucial to play in market with the competitors. Such a state of global organizations where data is going more and more important, illegal attempts are obvious and needed to be checked. Hadoop provides data local processing computation style in which we try to go towards data rather than moving data towards us. Thus, confidentiality of data should be monitored by authorities while sharing it within organization or with third parties so that it does not get leaked out by mistake by naïve employees having access to it. We are proposing a technique of introducing Validation Lamina in Hadoop system that will review electronic signatures from an access control list of concerned authorities while sending & receiving confidential data in organization. If Validation gets failed, concerned authorities would be urgently intimated by the system and the request shall be automatically put on halt till required action is not taken for privacy governance by the authorities.
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Value-Risk Analysis of Crowdsourcing in Pakistan’s Perspective
Статья научная
The benefits of crowdsourcing are enabled by open environments where multiple external stakeholders contribute to a firm's outcomes. In recent years, crowdsourcing has emerged as a distributed model of problem-solving and market development. Here, model assignments are assigned to networked individuals to complete so that the manufacturing expense of a business can be minimized considerably. The main objective of this research is to develop a methodology which will capture the value generation process in the presence of uncertainties (Risk factors) in crowdsourcing context. This study is designed to make an important contribution to the field of practice and knowledge. Value-Risk Analysis of crowd souring is one of the under studies Worldwide, especially in Pakistan. Provided the need, we have discussed the crowdsourcing as business process and presented an understanding of the risks associated with crowdsourcing use and possible strategies that can be used to maximize the value and minimize the identified risks. For the better understanding of crowdsourcing practices in Pakistan, three case studies were conducted based on three well reputed organizations of Pakistan and results gathered to help understand its practices, some of the risks associated with it and how they manage those risks.
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Variable Structure Control on Active Suspension of 4 DOF Vehicle Model
Статья научная
In this paper, the theory of a variable structure model following control (VSMFC) is employed to the design of the controller for an active suspensions of 4-degree-of-freedom (4-DOF) automobile model. The sliding mode equation is derived by applying VSMFC theory and the parameters of the switching function are obtained by using the method of pole assignment; a hierarchical algorithm with control variables started in sequence is applied to solve the active force; a method of exponential approach law is used to improve the dynamic performance of the controller. The efficacy of the controller is verified by simulation carried out with the help of Matlab/ Simulink. The results show that the active suspension controller based on VSMFC theory is superior in both robustness and performance.
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Vulnerabilities Assessment of Emerging Web-based Services in Developing Countries
Статья научная
To cope up with the pace of digitalization all over the world, like developed countries, developing countries are also offering services to its citizens through various online portals, web applications and web sites. Unfortunately, due to the lack of consideration on vulnerability issues during the development phase, many of those web based services are suffering from serious security threats. For these developing countries, vulnerability statistics are required to have insight about the current security status of the provided web services. That statistical data can assist the stakeholders to take appropriate actions against cyberattacks. In this work, we conduct a survey to observe the responses of web based services against four most commonly found web attacks called Man in the Middle, SQL Injection, Cross Site Scripting and Denial of Service. We carry out the survey for 30 websites (applications) of Bangladesh as the country has been focusing on digitalization of government services for the last few years and has already been offering various online services to its citizens. Among the 30 websites of several categories, result shows that approximately 77% sites are vulnerable to Man in the Middle attack whereas 3% are vulnerable to SQL Injection and Cross Site Scripting.
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Vulnerabilities Assessment of Financial and Government Websites: A Developing Country Perspective
Статья научная
The growing number of web applications in a developing country like Bangladesh has led to an increase in cybercrime activities. This study focuses on measuring the vulnerabilities present in financial and government websites of Bangladesh to address the rising security concerns. We reviewed related works on web application vulnerability scanners, comparative studies on web application security parameters, surveys on web application penetration testing methodologies and tools, and security analyses of government and financial websites in Bangladesh. Existing studies in the context of developing countries have provided limited insight into web application vulnerabilities and their solutions. These studies have focused on specific vulnerabilities, lacked comprehensive evaluations of security parameters, and offered a limited comparative analysis of vulnerability scanners. Our study aims to address these gaps by conducting an in-depth analysis using the OWASP ZAP tool to scan and analyze risk alerts, including risk levels such as high, medium, low, and informational. Our investigation unveiled eight key vulnerabilities, including Hash Disclosure, SQL injection (SQLi), Cross-Site Request Forgery (CSRF), missing Content Security Policy (CSP) headers, Cross-Domain JavaScript File Inclusion, absence of X-Content-Type-Options headers, Cache-related concerns, and potential Cross-Site Scripting (XSS), which can lead to revealing hidden information, enabling malicious code, and failing to protect against specific types of attacks. In essence, this study does not only reveal major security weaknesses but also provides guidance on how to mitigate them, thereby playing a vital role in promoting enhanced cybersecurity practices within the nation.
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