International Journal of Information Technology and Computer Science @ijitcs
Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1211
Entity Extraction from Business Emails
Статья научная
Email still plays an important role in today's business communication thanks to its simplicity, flexibility, low cost, and compatibility of diversified types of information. However processing the large amount of emails received consumes tremendous time and human power for a business. In order to quickly deciphering information and locate business-related information from emails received from a business, a computerized solution is required. In this paper, we have proposed a comprehensive mechanism to extract important information from emails. The proposed solution integrates semantic web technology with natural language processing and information retrieval. It enables automatic extraction of important entities from an email and makes batch processing of business emails efficient. The proposed mechanism has been used in a Transportation company.
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Envisioning Skills for Adopting, Managing, and Implementing Big Data Technology in the 21st Century
Статья научная
The skills for big data technology provide a window of new job opportunities for the information technology (IT) professionals in the emerging data science landscape. Consequently, the objective of this paper is to introduce the research results of suitable skills required to work with big data technology. Such skills include Document Stored Database; Key-value Stored Database; Column-oriented Database; Object-oriented Database; Graph Database; MapReduce; Hadoop Distributed File System (HDFS); YARN Framework; Zookeeper; Oozie; Hive; Pig; HBase; Mahout; Sqoop; Spark; Flume; Drill; Programming Languages; IBM Watson Analytics; Statistical Tools; SQL; Project Management; Program Management; and Portfolio Management. This paper is part of an ongoing research that addresses the link between economic growth and big data.
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Error Detection in a Multi-user Request System Using Enhanced CRC Algorithm
Статья научная
Error and error related issues have been a challenge in the development and reliable usage of computing systems and application. The ability to detect minute error in a system improves the reliability of the system by aiding developers and users to know were challenges are so that they can be fixed during development and even when the system is already in use. In other to achieve that different algorithm have been used including the Cyclic Redundancy Check 16-bit, 32-bit and higher bits. In this paper, error detection schemes are examined and the way they check and detect error in multi-user request and transmitted system. The paper also offers improvement on a Cyclic Redundancy Checks 32-bit detection algorithm for the detection of error that can occur in transmitted data and on stored, backed-up and archived data in the system without consuming large resources as the higher bits.
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Estimating Software Reliability by Monitoring Software Execution through OpCode
Статья научная
Previous studies on estimating software reliability employed statistical functions for next system failure prediction. These models used parameters based on assumptions regarding the nature of software faults and debugging process. However, none of the existing models, attempted on ensuring reliable runtime system operation. To serve the current demand of autonomous, reliable, service-oriented software, we present a novel approach for runtime reliability estimation of executable software. The approach can help control software execution at runtime by monitoring software state-to-state transition at runtime. The approach involves representing executable software as an automata using opcode extracted from executable code. The extracted opcode is then used to learn stochastic finite state machine (SFSM) representation of executable software which is later employed to trace software state-to-state transition at each runtime instance. An evaluation of our approach on Java-based Chart generator application is also discussed to explain how we can ensure reliable software execution and prevent software failures at runtime with the proposed approach.
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Evaluating Design Patterns of Commercial Web Applications using Net Easy Score
Статья научная
Web interface design patterns provide solutions to recurring design problems. Many design patterns use various techniques, which have been proven to be significantly different, to solve the same design problem. Normally, web designers do not know whether users would be satisfied with their chosen choice until near or at the end of the web development process. To obtain user feedback, users are usually asked to interact with a web prototype or the finished web and give their opinion through standardized questionnaires. Net Promoter Score is one of such questionnaires. This scale categorizes users’ responses into promoters and detractors, which makes it easier for companies to understand user satisfaction towards their web. To enable the designers to obtain user feedback early in the design stage, Net Easy Score, a new metric based on Net Promoter Score, was proposed. With Net Easy Score (NES), ease-of-use scores on different design patterns will be divided into a positive and a negative group. The NES is a difference between percentages of positive responses and negative ones. This study examined ease-of-use scores on design patterns for five common tasks in commercial web applications. Results showed that NES and mean ease-of-use score were significantly correlated with an r of 0.965 (p < .000). Also, ranking the average ease-of-use scores and NES revealed the same design patterns identified as the best and the worst ones, which was consistent with the easiest-to-use design patterns voted by participants.
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Evaluating Web Services Functionality and Performance
Статья научная
Traditional distributed database transaction applications within large organizations often involve a large number of resources. In this case, people and DDBMSs distributed over a wide geographic area, may introduce conflict between heterogeneous systems. Web services (WS) provide solution for this problem since WS have an independent platform, independent language, and independent object model. This work presents WS application to access heterogeneous and distributed database via horizontal data fragments that is designed to be reliable, flexible and scalable. It describes the setup of SOAP server and applications based on the SOAP for end user client. In addition, it allows the publishing of WS descriptions to submit user requests (goal) to retrieve the required information. Here we evaluate the functional, behavior and performance of WS among possible different alternatives with real-time and execution parameters. Implementation details and case study experiments are presented along with the corresponding results.
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Статья научная
Most security and privacy issues in software are related to exploiting code vulnerabilities. Many studies have tried to find the correlation between the software characteristics (complexity, coupling, etc.) quantified by corresponding code metrics and its vulnerabilities and to propose automatic prediction models that help developers locate vulnerable components to minimize maintenance costs. The results obtained by these studies cannot be applied directly to web applications because a web application differs in many ways from a non-web application: development, use, etc. and a lot of evaluation of these conclusions has to be made. The purpose of this study is to evaluate and compare the vulnerabilities prediction power of three types of code metrics in web applications. There are a few similar studies that targeted non-web application and to the best of our knowledge, there are no similar studies that targeted web applications. The results obtained show that unlike non-web applications where complexity metrics have better vulnerability prediction power, in web applications the metrics that give better prediction are the coupling metrics with high recall (> 75%) and fewer costs in terms of inspection (<25%).
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Evaluating the Maintainability of a Software System by using Fuzzy Logic Approach
Статья научная
Maintainability is an important quality attribute for almost every quality model. Maintainability of the software is considered as most expensive phase in software development life cycle as it consumes almost major part of the total effort allocated to the software system. Maintainability evaluation is complex due to its imprecise output. This paper proposes a maintainability model by considering its fuzzy aspects. Since fuzzy modeling deals with uncertainty and impreciseness so this paper uses fuzzy methodology and AHP technique to evaluate the maintainability of the model. Object oriented system has taken as case study for maintainability evaluation purpose.
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Evaluating the Scalability of Matrix Factorization and Neighborhood Based Recommender Systems
Статья научная
Recommendation Systems are everywhere, from offline shopping malls to major e-commerce websites, all use recommendation systems to enhance customer experience and grow profit. With a growing customer base, the requirement to store their interest, behavior and respond accordingly requires plenty of scalability. Thus, it is very important for companies to select a scalable recommender system, which can provide the recommendations not just accurately but with low latency as well. This paper focuses on the comparison between the four methods KMeans, KNN, SVD, and SVD++ to find out the better algorithm in terms of scalability. We have analyzed the methods on different parameters i.e., Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Precision, Recall and Running Time (Scalability). Results are elaborated such that selection becomes quite easy depending upon the user requirements.
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Evaluation of H- and G-indices of Scientific Authors using Modified K-Means Clustering Algorithm
Статья научная
In this paper I proposed modified K-means algorithm as the means to assess scientific authors performance by using their h,g-indices values. K-means suffers from poor computational scaling and efficiency as the number of clusters has to be supplied by the user. In this work, I introduce a modification of K-means algorithm that efficiently searches the data to cluster points by compute the sum of squares within each cluster which makes the program to select the most promising subset of classes for clustering. The proposed algorithm was tested on IRIS and ZOO data sets as well as on our local dataset comprising of h- and g-indices, which are the prominent markers for scientific excellence of authors publishing papers in various national and international journals. Results from analyses reveal that the modified k-means algorithm is much faster and outperforms the conventional algorithm in terms of clustering performance, measured by the data discrepancy factor.
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Статья научная
This paper describes and evaluates four different HSMM (hidden semi-Markov model) training methods for HMM-based synthesis of emotional speech. The first method, called emotion-dependent modelling, uses individual models trained for each emotion separately. In the second method, emotion adaptation modelling, at first a model is trained using neutral speech, and thereafter adaptation is performed to each emotion of the database. The third method, emotion-independent approach, is based on an average emotion model which is initially trained using data from all the emotions of the speech database. Consequently, an adaptive model is build for each emotion. In the fourth method, emotion adaptive training, the average emotion model is trained with simultaneously normalization of the output and state duration distributions. To evaluate these training methods, a Modern Greek speech database which consists of four categories of speech, anger, fear, joy and sadness, was used. Finally, an emotion recognition rate subjective test was performed in order to measure and compare the ability of each of the four approaches in synthesizing emotional speech. The evaluation results showed that the emotion adaptive training achieved the highest emotion recognition rates among four evaluated methods, throughout all four emotions of the database.
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Evaluation of Meta-Heuristic Algorithms for Stable Feature Selection
Статья научная
Now a days, developing the science and technology and technology tools, the ability of reviewing and saving the important data has been provided. It is needed to have knowledge for searching the data to reach the necessary useful results. Data mining is searching for big data sources automatically to find patterns and dependencies which are not done by simple statistical analysis. The scope is to study the predictive role and usage domain of data mining in medical science and suggesting a frame for creating, assessing and exploiting the data mining patterns in this field. As it has been found out from previous researches that assessing methods can not be used to specify the data discrepancies, our suggestion is a new approach for assessing the data similarities to find out the relations between the variation in data and stability in selection. Therefore we have chosen meta heuristic methods to be able to choose the best and the stable algorithms among a set of algorithms.
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Evaluation of Reranked Recommended Queries in Web Information Retrieval using NDCG and CV
Статья научная
Tremendous growth of the Web, lack of background knowledge about the Information Retrieval (IR), length of the input query keywords and its ambiguity, Query Recommendation is an important procedure which analyzes the real search intent of the user and recommends set of queries to be used in future to retrieve the relevant and required information. The proposed method recommends the queries by generating frequently accessed queries, rerank the recommended queries and evaluates the recommendation with the help of the ranking measures Normalized Discounted Cumulative Gain (NDCG) and Coefficient of Variance (CV). The proposed strategies are experimentally evaluated using real time American On Line (AOL) search engine query log.
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Evaluation of Software Quality in Test-driven Development: A Perspective of Measurement and Metrics
Статья научная
A software product is expected to be subjected to critical evaluation on its quality attributes in order to ascertain that target quality requirements are met, and that those quality attributes responsible for revealing software quality are not omitted in the software development process. Software metrics are essential to accomplish the task. This paper has carried out an exploratory study of software measurement and software metrics in tandem. The study took into cognizance the interwoven nature of the duo in measuring and revealing software quality. The study formulated a model that expressed the mutual bonding that propels both measurement and metrics to describing software quality in numeric quantities of software attributes. The study identified six software attributes whose values are considered enough quantities to reveal the quality of a software product. The identification enabled the study to create a model equation aimed at giving a numeric value for the complete evaluation of a software system. The result of the implementation of the six software attributes into the model equation showed that two software products employed in the study are of high-quality, having quality values of 0.93 and 0.86 respectively. The attributes produced values that confirmed the maintainability (25 seconds & 20 seconds respectively) and reliability (0.78 & 0.80 respectively) of both software products among other differing features that characterize them.
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Evaluation of TSP for Emergency Routing
Статья научная
The paper considers the symmetric traveling salesman problem and applies it to sixty-four (64) districts of Bangladesh (with geographic coordinates) as a new instance of the problem of finding an optimized route in need of emergency. It approached three different algorithms namely Integer Linear Programming, Nearest-neighbor, and Metric TSP as exact, heuristic, or approximate methods of solving the NP-hard class of problem to model the emergency route planning. These algorithms have been implanted using computer codes, used IBM ILOG CPLEX parallel optimization, visualized using Geographic Information System tools. The performance of these algorithms also has been evaluated in terms of computational complexity, their run-time, and resulted tour distance using exact, approximate, and heuristic methods to find the best fit of route optimization in emergence thus contributing to the field of combinatorial optimization.
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Статья научная
The localization of sensor nodes in a Wireless Sensor Network (WSN) can be examined by the resultant network parameters of covered sensing area and superimposed area. The measurement of covered sensing area is out of the total surface area how much geographical area can be sensed by the placed sensors and superimpose area is out of the total coverage area how much area is sensed or covered by more than one sensor node. A Wireless Sensor Network can be claimed to be productive only if it produces a good degree of coverage area with respect to less superimposing area and with the use of minimum sensor count also a degree of connectivity. To ensure the performance it is important to place the sensor nodes in a Wireless Sensor Network in its appropriate location. The placement of sensor nodes in 3D Wireless Sensor Network deals with complex mathematical modeling and higher sensor count compared to 2D Wireless Sensor Network. In this paper computation of actual covered area and superimposing area are highlighted after designing a network with a particular node placement method for Hilly Surfaces.
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Evaluation of oil viscosity based various empirical correlations for Azerbaijan crude oils
Статья научная
In the oil industry, the evaluation of oil viscosity is one of the important issues. Generally, the viscosity of crude oil depends on pressure and temperature. In this study, the prediction issue of oil viscosity has been viewed applying empirical correlations as Beggs-Robinson, Labedi, modified Kartoatmodjo, Elsharkawy and Alikhan, Al-Khafaji. Original field data reports have been obtained from Guneshli oil field of Azerbaijan sector of Caspian Basin. The correlation models used in the evaluation of viscosity of Azerbaijan oil have been implemented in the Python software environment. The obtained values on empirical correlations have been compared to experimental data obtained from Guneshli oil field. Statistical analysis in terms of percent absolute deviation (% AD) and the percent absolute average deviation (% AAD), mean absolute error (% MAE), correlation coefficient (% ), root mean square error (% RMSE) are used to subject the evaluation of the viscosity correlations. According to statistical analysis, it has been known that the Beggs-Robinson model has shown the lowest value on AAD (10.5614%), MAE (12.4427 %), RMSE (20.0853 %). The Labedi model has presented the worst result on every four criterions. Even though the Elsharkawy-Alikhan model has presented the highest result (99.9272%) on correlation coefficient, in the evaluation of viscosity of Azerbaijan crude oil, the Beggs-Robinson model can be considered more acceptable.
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Evaluation of the Design Metric to Reduce the Number of Defects in Software Development
Статья научная
Software design is one of the most important and key activities in the system development life cycle (SDLC) phase that ensures the quality of software. Different key areas of design are very vital to be taken into consideration while designing software. Software design describes how the software system is decomposed and managed in smaller components. Object-oriented (OO) paradigm has facilitated software industry with more reliable and manageable software and its design. The quality of the software design can be measured through different metrics such as Chidamber and Kemerer (CK) design metrics, Mood Metrics & Lorenz and Kidd metrics. CK metrics is one of the oldest and most reliable metrics among all metrics available to software industry to evaluate OO design. This paper presents an evaluation of CK metrics to propose an improved CK design metrics values to reduce the defects during software design phase in software. This paper will also describe that whether a significant effect of any CK design metrics exists on total number of defects per module or not. This is achieved by conducting survey in two software development companies.
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Evaluation of the Extended CBD Model: A Case Study using IMS Application
Статья научная
A large number of projects failed because of concentrating on developing new software. The Main drawbacks of new software development are more costly, and need maintenance. Reuse is solution of these problems that caused the widespread usage of object oriented (OO) development. Object oriented development is the backbone of component-based development (CBD). CBD facilitates reuse of the existing components (by customizing) with the new ones. Main advantages of reusable components are more reliable, saved time and reduced cost. CBD approach is different from traditional/new software development. Several models have been proposed for traditional software development such as Waterfall, Rapid Application Development (RAD), Evolutionary, Rational Unified Process (RUP) and agile. Whereas the popular CBD models, for customized development, are V, Y, Umbrella and W. Almost all software development companies, both the new software and customized software have to be developed. Therefore majority of the software development companies face problem to select and implement an appropriate process model for the both kinds of developments. To address this problem, the existing RUP and CBD models do work to some extent but the authors intend to propose an extended CBD model that it equally offers its benefits for new and customized developments. The experimental data is taken from a case study to develop IP Multimedia Sub System (IMS)-based examination application using iPhone to evaluate the proposed model. The results provide evidence that the extended CBD model can be equally beneficial for the development of both new and customization components for IMS-based applications.
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Event-Coverage and Weight based Method for Test Suite Prioritization
Статья научная
There are many challenges in testing of Graphical User Interface (GUI) applications due to its event driven nature and infinite input domain. Testing each and every possible combination of input require creating number of test cases to satisfy the adequacy criteria of GUI testing. It is not possible to test each and every test case within specified time frame. Therefore it is important to assign higher priority to test cases which have higher fault revealing capability than other test cases. Various methods are specified in literature for test suite prioritization of GUI based software and some of them are based on interaction coverage and weight of events. Weight based methods are defined namely fault prone weight based method, random weight based method and equal weight based method in which fault prone based method is most effective. In this paper we have proposed Event-Coverage and Weight based Method (EC-WBM) which prioritizes GUI test cases according to their event coverage and weight value. Weight value will be assigned based on unique event coverage and fault revealing capability of events. Event coverage based method is used to evaluate the adequacy of test cases. EC-WBM is evaluated for 2 applications one is Notepad and another is Calculator. Fault seeding method is used to create number of versions of application and these faults are evaluated using APFD (Average percentage of fault detection). APFD for prioritized test cases of Notepad is 98% and APFD for non-prioritized test cases is 62%.
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