International Journal of Information Technology and Computer Science @ijitcs
Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1235

Using Web Services Standards for Dealing with Complexities of Multiple Incompatible Applications
Статья научная
Organizations’ dependence on custom enterprise software and web applications from independent software developers and software companies create a lot of problems such as integration, interoperability, security, and system maintenance. This paper seeks to provide a better approach by using Web services standards in dealing with the complexity of multiple incompatible applications that were written in different programming languages on multiple computers and also making it possible for organizations to add a new layer of abstraction that is open, standards-based, and easy to integrate with any new or existing system. The combination of Service Oriented Architecture and Web services will be used to provide a rapid integration solution that will quickly and easily align Information Technology investments and corporate strategies by focusing on shared data and reusable services rather than proprietary integration products.
Бесплатно

Using an MST based Value for ε in DBSCAN Algorithm for Obtaining Better Result
Статья научная
In this paper, an objective function based on minimal spanning tree (MST) of data points is proposed for clustering and a density-based clustering technique has been used in an attempt to optimize the specified objective function in order to detect the “natural grouping” present in a given data set. A threshold based on MST of data points of each cluster thus found is used to remove noise (if any present in the data) from the final clustering. A comparison of the experimental results obtained by DBSCAN (Density Based Spatial Clustering of Applications with Noise) algorithm and the proposed algorithm has also been incorporated. It is observed that our proposed algorithm performs better than DBSCAN algorithm. Several experiments on synthetic data set in R^2 and R^3 show the utility of the proposed method. The proposed method has also found to provide good results for two real life data sets considered for experimentation. Note thatK-means is one of the most popular methods adopted to solve the clustering problem. This algorithm uses an objective function that is based on minimization of squared error criteria. Note that it may not always provide the “natural grouping” though it is useful in many applications.
Бесплатно

Статья научная
This paper studies the forecasting mechanism of the most widely used machine learning algorithms, namely linear discriminant analysis, logistic regression, k-nearest neighbors, random forests, artificial neural network, naive Bayes, classification and regression trees, support vector machines, adaptive boosting, and stacking ensemble model, in forecasting first-generation college students’ six-year graduation using the first college year’s data. Five standard evaluating metrics are used to evaluate these models. The results show that these machine learning models can significantly predict first-generation college students’ six-year graduation with mean forecasting accuracy rate spanning from 69.58% to 75.17% and median forecasting accuracy rate spanning from 70.37% to 74.52%. Among these machine learning algorithms, stacking ensemble model, logistic regression model, and linear discriminant analysis are the best three ones in terms of mean forecasting accuracy rate. Furthermore, the results from the repeated ten-fold cross-validation process reveal that the variations of the five evaluating metrics exhibit remarkably different patterns across the ten machine learning algorithms.
Бесплатно

Utilizing Conceptual Indexing to Enhance the Effectiveness of Vector Space Model
Статья научная
One of the main purposes of the semantic Web is to improve the retrieval performance of search systems. Unlike keyword based search systems, the semantic search systems aim to discover pages related to the query's concepts rather than merely collecting all pages instantiating its keywords. To that end, the concepts must be defined to be used as a semantic index instead of the traditional lexical one. In fact, The Arabic language is still far from being semantically searchable. Therefore, this paper proposed a model that exploits the Universal Word Net ontology for producing an Arabic Concepts-Space to be used as the index of Semantic Vector Space Model. The Vector Space Model is one of the most common information retrieval models due to its capability of expressing the documents' structure. However, like all keyword-based search systems, its sensitivity to the query's keywords reduces its retrieval effectiveness. The proposed model allows the VSM to represent Arabic documents by their topic, and thus classify them semantically. This, consequently, enhances the retrieval effectiveness of the search system.
Бесплатно

Utilizing Neural Networks for Stocks Prices Prediction in Stocks Markets
Статья научная
The neural networks, AI applications, are effective prediction methods. Therefore, in the current research a prediction system was proposed using these neural networks. It studied the technical share indices, viewing price not only as a function of time, but also as a function depending on several indices among which were the opening and closing, top and bottom trading session prices or trading volume. The above technical indices of a number of Egyptian stock market shares during the period from 2007 to 2017, which can be used for training the proposed system, were collected and used as follows: The data were divided into two sets. The first one contained 67% of the total data and was used for training neural networks and the second contained 33% and was used for testing the proposed system. The training set was segmented into subsets used for training a number of neural networks. The output of such networks was used for training another network hierarchically. The system was, then, tested using the rest of the data.
Бесплатно

Validated CMS: Towards New Generation of Web Content Management Systems on Web 2.0
Статья научная
Web 2.0 makes users the main actors for publishing content and creating applications on the web. The increasing of information overload and consequently the decrease of its quality are the main problems of this domain. Content Management Systems (CMS) provide the ability to publish on the web by offering simple publishing tools for ordinary users with no technical skills. Content available on the web created using the CMS is not well controlled and requires efficient process that evaluates its quality. Therefore, Content Management Systems contribute to the problem related to information and content quality similarly to Web 2.0 tools. The mechanism of validating content has proved a high-level of content’s quality control by involving users in the process according to Web 2.0 philosophy. From these perspectives, we develop Validated Content Management System (VCMS) as a new Web 2.0 tool that supports content validation mechanisms. This article presents the VCMS and its ability to provide an effective quality control for web content. We introduce a new manner of collaborative publishing and we give an overview about features of our system and its core architecture.
Бесплатно

Validation of Novel Approach to Detect Type Mismatch Problem Using Component Based Development
Статья научная
Adaptation software component is a crucial problem in component-based software engineering (CBSE). Components that assembled or reused sometimes cannot perfectly fit one another because of the incompatibility issues between them. The focus today is on finding adaptation technique, to solve the mismatch between component interfaces and to guarantee that the software components are able to interact in the right way. This paper will focus on detecting mismatch, which considers as an important step through adaptation process. We propose a solution to detect mismatch, by suggesting improvement in Symbolic Transition Systems that used in representing component interface, and synchronous vector algorithm to deal with parameters data type mismatch.
Бесплатно

Variant-Order Statistics based Model for Real-Time Plant Species Recognition
Статья научная
There are an urgent need of categorizing plant by its species, to help botanist setting up a plant species database. However, plant recognition model is still very challenging task in computer vision and can be onerous and time consuming because of inefficient representation approaches. This paper, proposes a recognition model for classifying botanical species from leaf images, using combination of variant-order statistics based measures. Hence, the spatial coordinates values of gray pixels defines the qualities of texture, for the proposed model a gray-scale approach is adopted for analyzing the local patterns of leaves images using second and higher order statistical measures. While, first order statistical measures are used to extract color descriptors from leaves images. Evaluation of the proposed model shows the importance of combining variant-order statistics measures for enhancing the plant leaf recognition accuracy. Several experiments on Flavia dataset and swedish dataset are conducted. Experimental results indicates that; the proposed model yields to improve the recognition rate up to 97.1% and 94.7% for both Flavia and Swedish dataset respectively; while taking less execution time.
Бесплатно

Various Approaches of Community Detection in Complex Networks: A Glance
Статья научная
Identifying strongly associated clusters in large complex networks has received an increased amount of interest since the past decade. The problem of community detection in complex networks is an NP complete problem that necessitates the clustering of a network into communities of compactly linked nodes in such a manner that the interconnection between the nodes is found to be denser than the intra-connection between the communities. In this paper, different approaches given by the authors in the field of community detection have been described with each methodology being classified according to algorithm type, along with the comparative analysis of these approaches on the basis of NMI and Modularity for four real world networks.
Бесплатно

Vehicle Theft Alert and Location Identification Using GSM, GPS and Web Technologies
Статья научная
Insecurity is one of the major challenges that the entire world is facing now, each country having their peculiar security issues. The crime rate in every part of the society these days has become a threatening issue such that vehicles are now used for committing criminal activities more than before. The issue of vehicle theft has increased tremendously, mostly at gunpoint or car parks. In view of these, there is a need for adequate records of stolen, identified and recovered vehicles which are not readily available in our society and as such very important. The development of a vehicle theft alert and location identification system becomes more necessary for vehicle owners to ensure theft prevention and a speedy identification towards recovery efforts in situations where a vehicle is missing, stolen or driven by an unauthorized person. The theft alert function makes use of a GSM application developed and installed in a mobile phone device which is embedded in the vehicle to communicate with the vehicle owner's mobile phone. The communication is established via SMS (i.e. between the installed mobile phone device and that of the vehicle owner). The communications established include; (i). Sending an SMS alert from installed mobile phone device to vehicle owner mobile phone when the car ignition is put on. (ii). Sending an SMS from the vehicle owner's mobile phone to start and stop the installed mobile phone device application. The location identification function makes use of a web application developed to; (i). Determine the real time location of a vehicle by means of tracking using GPS. (ii). Broadcast missing or stolen vehicle information to social media and security agency. The implementation of the installed mobile phone device application was done using JAVA because of its capabilities in programming mobile applications while PHP and MySQL was used for the web application functions. Integration testing of the system was carried out using simple percentage calculation for the performance evaluation. Fifty seven (57) vehicle owners were sampled and questionnaires were distributed to them in order to ascertain the acceptability and workability of the developed system. The result obtained shows the effectiveness of the system and hence it can be used to effectively monitor vehicle as it is been driven within or outside its jurisdiction. More so, the system can be used as database of missing, identified or recovered vehicles by various security agencies.
Бесплатно

Verification of Generic Ubiquitous Middleware for Smart Home Using Coloured Petri Nets
Статья научная
Smart home is a relatively new technology, where we applied pervasive computing in all the aspects, so as to make our jobs or things that we normally do in-side the home in a very easier way. Originally, a smart home technology was used to control environmental systems such as lighting and heating; but recently the use of smart technology has been developed so that almost any electrical component within the home can be included in the system. Usually in pervasive computing, a middleware is developed to provide interaction between the user and device. In previous, a middleware is only suitable for specific Smart Home architecture, that can’t be applicable to any other architecture but the Generic Ubiquitous Middleware is suitable for different Smart Home architecture. This paper proposes that any smart home can be built with single architecture and it is verified using a Coloured Petri Nets tool. We have given a verification model of various Smart home Environments.
Бесплатно

Статья научная
The rapid growth of the video game industry and its reliance on digital distribution have created new opportunities for data-driven sales forecasting. Social media platforms serve as influential environments where consumer sentiment, trends, and discussions impact purchasing behaviors. This study examines the potential of using sentiment analysis of social media data to predict video game sales. While traditional sales forecasting models mainly depend on historical sales data and statistical techniques, sentiment analysis offers real-time insights into consumer interest and market demand. This paper reviews existing research on video game sales prediction, the application of sentiment analysis in the gaming industry, and sentiment-based forecasting models in other domains. The findings highlight a significant research gap in applying sentiment analysis to video game sales forecasting, despite its demonstrated efficacy in related fields. The study emphasizes the advantages and challenges of integrating sentiment analysis with traditional forecasting methods and proposes future research directions to enhance predictive accuracy.
Бесплатно

Video Quality Analysis of Distributed Video Coding in Wireless Multimedia Sensor Networks
Статья научная
Multimedia communications in wireless sensor networks is a very challenging task. Video coding with high computational complexity and great contribution to the energy consumption of nodes and video transmission over erroneous wireless channel are the main reasons of these challenges. Distributed Video Coding has high potential for being deployed in these networks due to its unique features like as independent frame coding and low complexity encoding operations. The purpose of this study is to understand and evaluate the distributed video coding performance facing the transmission characteristics in wireless multimedia sensor networks. To this end, the comparative analysis of the coding in respect of main factors of video transmission (i.e., bit rate and error resiliency) in the Wireless Multimedia Sensor Networks (WMSN) has been done. We have used both the objective and subjective criteria for checking the video quality and applied the Gilbert-Elliot channel model for capturing the bit-level error in WMSN. Therefore, unlike previous works, our results are more realistic. In addition, based on this model we have investigated the impact of protection of frames by Reed-Solomon error control scheme. The results show that paying attention to coding parameters and protecting key frames, have a great impact on increasing the quality of the receiving video and will reduce the energy consumption and delays due to low number of requests from the feedback channel.
Бесплатно

Virtual Machine Monitor Indigenous Memory Reclamation Technique
Статья научная
Sandboxing is a mechanism to monitor and control the execution of malicious or untrusted program. Memory overhead incurred by sandbox solutions is one of bottleneck for sandboxing most of applications in a system. Memory reclamation techniques proposed for traditional full virtualization do not suit sandbox environment due to lack of full scale guest operating system in sandbox. In this paper, we propose memory reclamation technique for sandboxed applications. The proposed technique indigenously works in virtual machine monitor layer without installing any driver in VMX non root mode and without new communication channel with host kernel. Proposed Page reclamation algorithm is a simple modified form of Least recently used page reclamation and Working set page reclamation algorithms. For efficiently collecting working set of application, we use a hardware virtualization extension, page Modification logging introduced by Intel. We implemented proposed technique with one of open source sandboxes to show effectiveness of proposed memory reclamation method. Experimental results show that proposed technique successfully reclaim up to 11% memory from sandboxed applications with negligible CPU overheads.
Бесплатно

VisiMark1_0: An Assistance Tool for Evaluating Robustness of Video Watermarking Algorithms
Статья научная
The paper proposes a tool, VisiMark1_0, as assistance for evaluating the robustness of video watermarking algorithms as evaluation of a video watermarking algorithm for robustness with available tools is a tedious task. It is our belief that for researchers of robust video watermarking, a tool needs to be designed that will assist in the evaluation procedure irrespective of the design algorithm. This tool provides a test bed of various attacks. The input to this tool will be a watermarked video whereas the outputs will be attacked videos, evaluated parameters PSNR, MSE, MSAD and DELTA, graphical comparisons of the attacked and watermarked videos with all parameters needed by researchers, and the attacks report. Provision for comparison of any two videos is an additional facility provided in the tool. The attacks implemented in VisiMark1_0 are categorized mainly in three. Firstly, Video attacks: Frame dropping, Frame averaging, Frame swapping, Changing the sequence of the scenes, Changing Frame rate, Fade and dissolve, Contrast stretching, Motion blurring, Chroma sampling, Inter frame averaging are some of the novel offerings in video frame attacks category. Secondly, Geometrical attacks: Apart from the traditional Rotation, Scaling and Cropping attacks for images, VisiMark1_0 contributed towards Sharpening, Shearing, Flipping, Up/down sampling and Dithering attacks for a video and signal processing attacks like Conventional Noising, Denoising and Filtering attacks for images are incorporated for video along with Pixel removal attack as a novel contribution. VisiMark1_0 is an endeavor to design a tool for evaluating a raw video (an .avi file currently) incorporating various attacks having a prospect for numerous video formats in near future.
Бесплатно

Visualization & Prediction of COVID-19 Future Outbreak by Using Machine Learning
Статья научная
Day by day, the accumulative incidence of COVID-19 is rapidly increasing. After the spread of the Corona epidemic and the death of more than a million people around the world countries, scientists and researchers have tended to conduct research and take advantage of modern technologies to learn machine to help the world to get rid of the Coronavirus (COVID-19) epidemic. To track and predict the disease Machine Learning (ML) can be deployed very effectively. ML techniques have been anticipated in areas that need to identify dangerous negative factors and define their priorities. The significance of a proposed system is to find the predict the number of people infected with COVID-19 using ML. Four standard models anticipate COVID-19 prediction, which are Neural Network (NN), Support Vector Machines (SVM), Bayesian Network (BN) and Polynomial Regression (PR). The data utilized to test these models content of number of deaths, newly infected cases, and recoveries in the next 20 days. Five measures parameters were used to evaluate the performance of each model, namely root mean squared error (RMSE), mean squared error (MAE), mean absolute error (MSE), Explained Variance score and r2 score (R2). The significance and value of proposed system auspicious mechanism to anticipate these models for the current scenario of the COVID-19 epidemic. The results showed NN outperformed the other models, while in the available dataset the SVM performs poorly in all the prediction. Reference to our results showed that injuries will increase slightly in the coming days. Also, we find that the results give rise to hope due to the low death rate. For future perspective, case explanation and data amalgamation must be kept up persistently.
Бесплатно

VoIP Technology: Investigation of QoS and Security Issues
Статья научная
Voice over IP (VoIP) is the technology allowing voice traffic transmission as data packets over a private or a public IP network. VoIP allows significant benefits for customers and communication services providers. The main are cost savings, rich media service, phone and service portability and mobility, and the integration with other applications. Nevertheless, the deployment of the VoIP technology encounters many challenges such as architecture complexity, interoperability problems, QoS concerns, and security issues. Due to the inability of the IP networking technology to support the stringent QoS constraints of voice traffic, and the incapability of traditional security mechanisms to adequately protect VoIP systems from recent intelligent attacks, QoS and security issues are considered as the most serious challenges for successful deployment of the VoIP technology. The aim of this paper is to carry out a deep analysis of the security issues and QoS concerns of the VoIP technology. Firstly, we present a brief overview about the VoIP technology. Then, we discuss the QoS problems encountering the deployment of the VoIP technology. The presented discussion mainly address the QoS issues related to the use of the IP networking technology, the QoS concerns related to voice clarity, and the QoS mechanisms proposed to support voice traffic QoS constraints. After that, we investigate the security issues of the VoIP technology. The presented investigation mainly address the vulnerabilities and security attacks of VoIP systems, as well as the countermeasures that should be considered to help the deployment of secured VoIP systems.
Бесплатно

Статья научная
The brain signal or Electroencephalogram (EEG) has been proved as one of the most important bio-signal that deals with a number of problems and disorders related to the human being. Epilepsy is one of the most commonly known disorders found in humans. The application of EEG in epilepsy related research and treatment is now a very common practice. Variety of smart tools and algorithms exist to assist the experts in taking decision related to the treatment to be provided to an epileptic patient. However, web based applications or tools are still needed that can assist those doctors and experts, who are not having such existing smart tools for EEG analysis with them. In the current work, a web based system named WEBspike has been proposed that breaks the geographical boundary in assisting doctors in taking proper and fast decision regarding the treatment of epileptic patient. The proposed system receives the EEG data from various users through internet and processes it for Epileptic Spike (ES) patterns present in it. It sends back a report to the user regarding the appearance of ES pattern present in the submitted EEG data. The average spike recognition rate obtained by the system with the test files, was 99.09% on an average.
Бесплатно

Статья научная
Education is a field that utilizes information technology to support academic and operational activities. One of the technologies widely used in the education sector is web-based applications. Web-based technologies are vulnerable to exploitation by attackers, which highlights the importance of ensuring strong security measures in web-based systems. As an educational organization, Udayana University utilizes a web-based application called OASE. OASE, being a web-based system, requires thorough security verification. Penetration testing is conducted to assess the security of OASE. This testing can be performed using the ISSAF and OSSTMM frameworks. The penetration testing based on the ISSAF framework consists of 9 steps, while the OSSTMM framework consists of 7 steps for assessment. The results of the OASE penetration testing revealed several system vulnerabilities. Throughout the ISSAF phases, only 4 vulnerabilities and 3 information-level vulnerabilities were identified in the final testing results of OASE. Recommendations for addressing these vulnerabilities are provided as follows. Implement a Web Application Firewall (WAF) to reduce the risk of common web attacks in the OASE web application. input and output validation to prevent the injection of malicious scripts addressing the stored XSS vulnerability. Update the server software regularly and directory permission checks to eliminate unnecessary information files and prevent unauthorized access. Configure a content security policy on the web server to ensure mitigation and prevent potential exploitation by attackers.
Бесплатно

Web Crawler Based on Mobile Agent and Java Aglets
Статья научная
With the huge growth of the Internet, many web pages are available online. Search engines use web crawlers to collect these web pages from World Wide Web for the purpose of storage and indexing. Basically Web Crawler is a program, which finds information from the World Wide Web in a systematic and automated manner. This network load farther will be reduced by using mobile agents. The proposed approach uses mobile agents to crawl the pages. A mobile agent is not bound to the system in which it starts execution. It has the unique ability to transfer itself from one system in a network to another system. The main advantages of web crawler based on Mobile Agents are that the analysis part of the crawling process is done locally rather than remote side. This drastically reduces network load and traffic which can improve the performance and efficiency of the whole crawling process.
Бесплатно