Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1165
The Major Physical Layer Constraints of Fiber Optical fiber Packet Switch Architectures
Статья научная
Many optical packet switch (OPS) architectures are proposed and demonstrated. In the design of these architectures, most of the attention is paid on the network layer parameters like high through put (low packet loss probability) and low latency, etc. and to achieve these goals. The structure of the architectures becomes very complex. In real scenarios, these architectures may not work efficiently because of physical layer constraints. Hence, cross layer optimization needs to be considered. This paper addresses the major physical layer constraints, and it has been found that the optical packet switch architecture can work efficiently within the bounded regimes which can be called as an operation window.
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Статья научная
With the growing size of software’s and increasing needs of people we need a complex software system to provide a solution to the many problems among the humans. For that, we need to develop the software system with high quality and limited amount of time. Due to this reason, the software development process is moved to the component based software development (CBSD). The preliminary life cycle models of software development is not compatible with component based software development. For that we need a novel life cycle model to develop the software system using components with high quality. Some of the life cycle models are developed by some researchers, but when we are considering the quality of the software system those models are not assured the highest quality. Because of this we have developed one novel life cycle model based on v-model using KCW framework which assures the quality of the architecture of a software system itself.
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The Obstacles in Big Data Process
Статья научная
The increasing amount of data and a need to analyze the given data in a timely manner for multiple purposes has created a serious barrier in the big data analysis process. This article describes the challenges that big data creates at each step of the big data analysis process. These problems include typical analytical problems as well as the most uncommon challenges that are futuristic for the big data only. The article breaks down problems for each step of the big data analysis process and discusses these problems separately at each stage. It also offers some simplistic ways to solve these problems.
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Статья научная
In this paper the probabilistic method is presented for solving the minimum vertex cover problem using systems of non-linear equations that are formed on the basis of a neighborhood relationship of a particular vertex of a given graph. The minimum vertex cover problem is one of the classic mathematical optimization problems that have been shown to be NP-hard. It has a lot of real-world applications in different fields of science and technology. This study finds solutions to this problem by means of the two basic procedures. In the first procedure three probabilistic pairs of variables according to the maximum vertex degree are formed and processed accordingly. The second procedure checks a given graph for the presence of the leaf vertices. Special software package to check the validity of these procedures was written. The experiment results show that our method has significantly better time complexity and much smaller frequency of the approximation errors in comparison with one of the most currently efficient algorithms.
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The Proposal of Scaling the Roles in Scrum of Scrums for Distributed Large Projects
Статья научная
Scrum of scrums is an approach used to scale the traditional Scrum methodology to fit for the development of complex and large projects. However, scaling the roles of scrum members brought new challenges especially in distributed and large software projects. This paper describes in details the roles of each scrum member in scrum of scrum to propose a solution to use a dedicated product owner for a team and inclusion of sub-backlog. The main goal of the proposed solution is to optimize the role of product owner for distributed large projects. The proposed changes will increase cohesiveness among scrum teams and it will also eliminate duplication of work. Survey is used as a research design to evaluate the proposed solution. The results are found encouraging supporting the proposed solution. It is anticipated that the proposed solution will help the software companies to scale Scrum methodology effectively for large and complex software projects.
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The SEIQR–V model: on a more accurate analytical characterization of malicious threat defense
Статья научная
Epidemic models have been used in recent times to model the dynamics of malicious codes in wireless sensor network (WSN). This is due to its open nature which provides an easy target for malware attacks aimed at disrupting the activities of the network or at worse, causing total failure of the network. The Susceptible-Exposed-Infectious-Quarantined-Recovered–Susceptible with a Vaccination compartment (SEIQR-V) model by Mishra and Tyagi is one of such models that characterize worm dynamics in WSN. However, a critical analysis of this model and WSN epidemic literature shows that it is absent essential factors such as communication range and distribution density. Therefore, we modify the SEIQR-V model to include these factors and to generate better reproduction ratios for the introduction of an infectious sensor into a susceptible sensor population. The symbolic solutions of the equilibriums were derived for two topological expressions culled from WSN literature. A suitable numerical method was used to solve, simulate and validate the modified model. Simulation results show the effect of our modifications.
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Статья научная
The computational intelligence such as artificial neural network (ANN) and fuzzy inference system (FIS) is a strong tool for prediction and simulation in engineering applications. In this paper, radial basis function (RBF) network and adaptive neuro-fuzzy inference system (ANFIS) are used for prediction of IC50 (the 50% inhibitory concentration) values evaluated by the MTT assay in human cancer cell lines. For developing of the proposed models, the input parameters are the concentration of the drug and the types of cell lines and the output is IC50 values in the A549, H157, H460 and H1975 cell lines. The predicted IC50 values using the proposed RBF and ANFIS models are compared with the experimental data. The obtained results show that both RBF and ANFIS models have achieved good agreement with the experimental data. Therefore, the proposed RBF and ANFIS models are useful, reliable, fast and cheap tools to predict the IC50 values determined by the MTT assay in human cancer cell lines.
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The Use of PLC Technology in Broadband Services Offered to Households
Статья научная
The volume and quality of broadband services in any country is being understood not only as a major parameter related to the economic growth of that country, but also as a major parameter how much that country is ready for economic growth in the near future. With this understanding the main reasons why expansion of broadband services in Slovakia is an urgent issue are briefly outlined in this paper.
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The Web Navigability Structure of E- Banking in India
Статья научная
The recent exponential growth of Internet has made the online banking very popular .It has become integral part of life for many people. But still the majority of people have probably not even tried it yet possibly because the websites of the banks are too complicated to understand and navigate. It has therefore become important to evaluate the quality of the banking websites. Most of the studies in the literature on banking websites have focused on evaluating the quality of services of these websites. In this paper we have investigated the structural properties of the websites with emphasis on navigability study of these business sites. Also evaluated the correlation between the navigability, popularity and importance of the Web sites.
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The effects of mobile phone use on human behaviors: a study of developing country like Bangladesh
Статья научная
The mobile phone is an essential part for human life all over the world. From developed to developing, developing to under developed countries are affected by the mobile phone usages, each and every corner of this universe. In every single minute we are using mobile phone for our various purposes. Even when there is no purpose we are also just using mobile phone. This scenario is almost same all over the world. The mobile phone has been affected the human behavior and changed the nature of behavior in developing countries. This paper has divided into three parts first part gathered information; second part analyses collected information and third part draw conclusions. In this paper, the result of the mobile phone used and effect on human behaviors in developing country like Bangladesh has been presented. This paper will also analyze this issue by exploring the exiting literature related to the mobile phone usages on human behavior and effect of the mobile phone on society in developing countries. Finally, this paper was presented some efficient solutions to minimize the problems in developing countries.
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The impact of feature selection techniques on the performance of predicting Parkinson’s disease
Статья научная
Parkinson’s Disease (PD) is one of the leading causes of death around the world. However, there is no cure for this disease yet; only treatments after early diagnosis may help to relieve the symptoms. This study aims to analyze the impact of feature selection techniques on the performance of diagnosing PD by incorporating different data mining techniques. To accomplish this task, identifying the best feature selection approach was the primary focus. In this paper, the authors had applied five feature selection techniques namely: Gain Ratio, Kruskal-Wallis Test, Random Forest Variable Importance, RELIEF and Symmetrical Uncertainty along with four classification algorithms (K-Nearest Neighbor, Logistic Regression, Random forest, and Support Vector machine) on the PD dataset collected from the UCI Machine Learning repository. The result of this study was obtained by taking the four different subsets (Top 5, 10, 15, and 20 features) from each feature selection approach and applying the classifiers. The obtained result showed that in terms of accuracy, Random Forest Variable Importance, Gain Ratio, and Kruskal-Wallis Test techniques generated the highest 89% score. On the other hand, in terms of sensitivity, Gain Ratio and Kruskal-Walis Test approaches produced the highest 97% score. The findings of this research clearly indicated the impact of feature selection techniques on predicting PD and our applied methods outperformed the state-of-the-art performance.
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The impact of web contents color contrast on human psychology in the lens of HCI
Статья научная
Web contents include text, image, and any visual element that represents in web applications. Users conduct web applications throughout visual contents; therefore, the contents should visible clearly and follow a strict contrast ratio to differentiate from the other contents of the application. The color contrast assists to visualize contents combining the contrast ratio between background and foreground. Whether the web contents not visible clearly or overpass to split its color contrast from the background shall be worthless, and in addition, the human brain and psychology have an impact of colors which lead physiologically effects such as feelings and senses. Numerous web applications existing on the web and some applications failed to follow the design principles of Human-Computer Interaction (HCI). In HCI, visualization is the most widespread research area and, in the context of visual interaction, the HCI facilitates and guides application design that to be user-centric. This research reveals the HCI for color effects on the human eye, brain, phycology, and contrast ratio. Also extended the existing standard minimum contrast ratio for the design of web contents in light and dark background and foreground following HCI principles. The extended ratio experimented on a web application contents to differentiate the accuracy between the existing and the extended ratio.
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Time and Accuracy Analysis of Skew Detection Methods for Document Images
Статья научная
Detecting skew angle in a document image has been an area of research interest for a long time. This paper presents an experimental analysis of various existing skew detection techniques involving methods such as Radon transform, Hough transform, Principal Component Analysis (PCA), PCA with Wavelet transform and Moments with Wavelet transform. Detailed analysis of existing skew detection method against the parameters time complexity, space complexity, robustness, accuracy, flexibility, etc. has been carried out for seven different categories of digital documents. The categories of these documents spans from those containing handwritten text in different languages, to the ones with both text and pictures. Radon transform is observed to be the fastest method when the image size is small and works with virtually all types of documents. It is an accurate method as well as works faster, even with the document containing pictures. PCA method is also faster than Hough transform for machine printed documents but used less for real time skew distortion due to its limitations. If the document image size is large, then Moments with Wavelet transform has better time complexity than other methods, but do not work well with documents containing images. Hough transform is the most accurate method, though it is computationally expensive.
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Time effective workflow scheduling using genetic algorithm in cloud computing
Статья научная
Cloud computing is service based technology on internet which facilitates users to access plenty of resources on demand from anywhere and anytime in a metered manner i.e. pay per usage without paying much heed to the maintenance and implementation details of application. As cloud technology is evolving day by day it is being confronted by numerous challenges, such as time and cost under deadline constraints. Research work done so far mainly focused on reducing cost as well as execution time. In order to minimize cost and execution time previously existing workflow scheduling model known as predict earliest finish time is used. In this research work we have proposed a new PEFT genetic algorithm approach to further reduce the execution time on this model. A strategy is developed to let GA focus on to optimize chromosomes objective to get best suitable mutated children. After obtaining a feasible solution, the genetic algorithm focuses on optimizing the execution time. Experimental results show that our algorithm can find better solution within lesser time.
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Time-Delay Neural Network for Smart MIMO Channel Estimation in Downlink 4G-LTE-Advance System
Статья научная
Long-Term Evolution (LTE) is the next generation of current mobile telecommunication networks. LTE has a new flat radio-network architecture and significant increase in spectrum efficiency. In this paper, main focus on throughput performance analysis of robust MIMO channel estimators for Downlink Long Term Evolution-Advance (DL LTE-A)-4G system using three Artificial Neural Networks: Feed-forward neural network (FFNN), Cascade-forward neural network (CFNN) and Time-Delay neural network (TDNN) are adopted to train the constructed neural networks’ models separately using Back-Propagation Algorithm. The methods use the information received by the received reference symbols to estimate the total frequency response of the channel in two important phases. In the first phase, the proposed ANN based method learns to adapt to the channel variations, and in the second phase, it estimates the MIMO channel matrix and try to improve throughput of LTE. The performance of the estimation methods is evaluated by simulations in Vienna LTE-A DL Link Level Simulator. Performance of the proposed channel estimator, Time-Delay neural network (TDNN) is compared with traditional Least Square (LS) algorithm and ANN based other estimators for Closed Loop Spatial Multiplexing (CLSM) - Single User Multi-input Multi-output (MIMO-2×2 and 4×4) in terms of throughput. Simulation result shows TDNN gives better performance than other ANN based estimations methods and LS.
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Toward Grasping the Dynamic Concept of Big Data
Статья научная
The idea of Big Data represents a growing challenge for companies such as Google, Yahoo, Bing, Amazon, eBay, YouTube, LinkedIn, Facebook, Instagram, and Twitter. However, the challenge goes beyond private companies, government agencies, and many other organizations. It is actually an alarm clock that is ringing everywhere: newspapers, magazines, books, research papers, online, offline, it is all over the world and people are worried about it. Its economic impact and consequences are of unproportioned dimensions. This research outlines the fundamental literature required to understand the concept of Big Data. Additionally, the present work provides a conclusion and recommendations for further research on Big Data. This study is part of an ongoing research that addresses the link between Economic Growth and Big Data.
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Towards Automated Web Accessibility Evaluation: A Comparative Study
Статья научная
With each passing day, the Web is becoming increasingly important in our lives. Hence, the need of making it more accessible to everyone, especially for the disabled and elderly spurred a great interest in automated tools, the total registered number of which has been continuously increasing and reached from forty-five software bids in 2014 to ninety-three in 2017. The purpose of this empirical research is to assess and compare eight popular and free online automated Web accessibility evaluation tools (AWAETs) such as AChecker, Cynthia Says, EIII Checker, MAUVE, SortSite, TAW, Tenon and WAVE with regard to the WCAG 2.0 conformance. As a result, significant differences were observed in terms of tool’s coverage (a maximum of 32.4%), completeness (ranges between 10% and 59%), correctness (an average of 70.7%), specificity (reaches 32%), inter-reliability (lies between 1.56% and 18.32%) and intra-reliability (the acceptable score), validity, efficiency and capacity. These eight criteria can help to determine a new role played by modern AWAETs as dependent methods in Web accessibility evaluation. Moreover, consequences of relying on AWAETs alone are quantified and concluded that applying such approaches is a great mistake since subjective and less frequent objective success criteria (SC) failed to be automated. However, using a good combination of AWAETs is highly recommended as overall results in all the mentioned quality criteria are maximized and tools could definitely validate and complete each other. Ultimately, integrating automated methods with the others is ideal and preferably at an early stage of the website development life cycle. The study also provides potential accessibility barriers that make websites inaccessible, challenges AWAETs are currently facing, nineteen pros and fourteen cons and fifteen improvement recommendations for the existing and next generation of AWAETs. Fundamentally, achieving the objectives of this study was possible due to the elaboration and implementation of a new five-phased methodology named as “5PhM-for-AWAEMs” for successful selection, evaluation and/or comparison of AWAEMs. In addition to providing detailed descriptions of the estimation process, this methodology represents eleven key criteria for effective selection of suitable AWAEMs and necessary numbers of web pages and expert evaluators for acceptable, normal or ideal assessment.
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Статья научная
Solid Waste Management is an especially important task related to human health and the environment. Due to ineffective scheduled date & time, poor communication between waste collecting institutions and local house owners, people are compelled to throw waste on streets which is not good. Even if there is a routine, people tend to miss the schedule. Our aim is to develop an application for mobile phones, which consists of two parties- the user and waste management officials, where the second one acts as reminders. Officials will send a notification to the user, signaling that they are at a certain checkpoint near the user and the user can now throw waste properly and not on the streets. An incremental model was used throughout our project; basic requirements are fulfilled first and then iterated to create the final product. The proposed application includes two portals for whether you are user or waste management personnel. This application helps to improve the coordination between clients and collectors and determines whether the waste in an area has been collected or not. The survey conducted in this study involved consulting the Environment and Agricultural Department of Kathmandu Metropolitan City, which highlighted the significance of a notifying application. This application addresses the issue of uncoordinated waste disposal by providing users with information about collection schedules, leading to better waste management practices and reduced unsystematic garbage disposal.
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Towards Improving the Quality of Mobile App Reviews
Статья научная
Mobile app reviews are gaining importance as a crowd source to improve the quality of mobile apps. Mobile app review systems are providing a platform for users to share their experiences and to support in decision making for a certain app. Developers, on the other side, are utilizing the review system to get real-life user experience as a source of improving their apps. This paper has analyzed existing review system and proposed few recommendations for the current review system to improve the quality of app reviews. The proposed review system can help for collection and analysis of user reviews to make it more meaningful with less intensive data mining techniques. The proposed system can help the end users to get an overview of mobile apps. The recommendations in this paper are derived from the existing literature related to app reviews and will help to improve the current review systems for better app reviews from users as well as developers perspective.
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Статья научная
The Agent Petri Nets (APN) formalism provides a set of adapted and specific tools, relations and functions for modeling multi-agent systems (MAS). However, there is a lack of tools for verifying the APN models. In order to fill some of these gaps, we propose in this paper, a meta-modeling approach based on the Model Driven Architecture (MDA). The Eclipse Modeling Framework (EMF) permits to define a generic APN Meta-model in Ecore informal format. Its abstraction level is very high, it offers as a basis for developing system models dedicated to various specific domains. In addition, the Object Constraint Language (OCL) aims to increase the structural verification level of the model and the Graphical Modeling Framework (GMF), for its part, is concerned with generating a graphical editor associated with the APN meta-model. Thus, we combine the rigor of APN formalism with the power of the MDA-based meta-modeling tools for verifying APN models.
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