International Journal of Information Technology and Computer Science @ijitcs
Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1211
The Extensive Bit-level Encryption System (EBES)
Статья научная
In the present work, the Extensive Bit-level Encryption System (EBES), a bit-level encryption mechanism has been introduced. It is a symmetric key cryptographic technique that combines advanced randomization of bits and serial bitwise feedback generation modules. After repeated testing with a variety of test inputs, frequency analysis, it would be safe to conclude that the algorithm is free from standard cryptographic attacks. It can effectively encrypt short messages and passwords.
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The Image Recognition of Mobile Robot Based on CIE Lab Space
Статья научная
The image recognition of mobile robot is to extract the effective target information. The essence of image extraction is image segmentation. By extracting and distinguishing planar objects and three-dimensional objects, we propose two new algorithms. The color image is extracted by using CIE Lab Space. Then we propose a comparison method through the collection of two image samples. According to the principle of geometric distortion in the geometric space, we can easily distinguish the planar object in the environment. Therefore, Experimental results show that the combination of these two methods is accurate and fast in the color image recognition.
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The Impact of Financial Statement Integration in Machine Learning for Stock Price Prediction
Статья научная
In the capital market, there are two methods used by investors to make stock price predictions, namely fundamental analysis, and technical analysis. In computer science, it is possible to make prediction, including stock price prediction, use Machine Learning (ML). While there is research result that said both fundamental and technical parameter should give an optimum prediction there is lack of confirmation in Machine Learning to this result. This research conducts experi-ment using Support Vector Regression (SVR) and Support Vector Machine (SVM) as ML method to predict stock price. Further, the result is compared between 3 groups of parameters, technical only (TEC), financial statement only (FIN) and combination of both (COM). Our experimental results show that integrating financial statements has a neutral impact on SVR predictions but a positive impact on SVM predictions and the accuracy value of the model in this research reached 83%.
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The Implementation of Clinical Decision Support System: A Case Study in Saudi Arabia
Статья научная
In recent years, the healthcare sector has shown inclination towards restructuring of healthcare systems to harmonize with technological innovations and adopting decision support system in routine clinical practices. The objective of this paper is to summarize challenges of Clinical Decision Support System (CDSS) and focus on the effectiveness of CDSS to improve clinical practice. This paper also describes the experience of CDSS in healthcare sector in Saudi Arabia and addresses the requirements for implementing successful CDSS with a real example. This study concludes that healthcare sector is in dire need to increase quality of patients' care and improve clinical practices by adopting CDSS.
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The Leading Role of Digital Technologies in the Development of the Smart City Concept in Azerbaijan
Статья научная
The article describes the application of the Smart City concept and the economic opportunities it creates, infrastructure and services, and opportunities to improve governance. The main features of the Smart City concept, development directions and evolution, standards and solutions, and factors and obstacles to its implementation have been analyzed by the author. The experience of different countries in the application of digital technologies is discussed. The article provides the scope and structure of the "smart" market, application stages, and scenarios The international experience in this direction was widely analyzed and examples were shown. The article talks about smart cities, the construction of which has already begun in Azerbaijan. The application of the smart city concept in Azerbaijan has been studied. It is stressed that the spread of digital technologies for the construction of a smart city in Azerbaijan is a prerequisite. The Network Readiness Index (NRI) identifies the indicators that are holding back Azerbaijan in the ranking for 2021.
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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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