Статьи журнала - International Journal of Information Technology and Computer Science
Все статьи: 1195
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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Experimental Analysis of Browser based Novel Anti-Phishing System Tool at Educational Level
Статья научная
In the phishing attack, the user sends their confidential information on mimic websites and face the financial problem, so the user should be informed immediately about the visiting website. According to the Third Quarter Phishing Activity Trends Report, there are 55,282 new phishing websites have been detected in the month of July 2014. To solve the phishing problem, a browser based add-on system may be one of the best solution to aware the user about the website type. In this paper, a novel browser based add-on system is proposed and compared its performance with the existing anti-phishing tools. The proposed anti-phishing tool 'ePhish' is compared with the existing browser based anti-phishing toolbars. All the anti-phishing tools have been installed in computer systems at an autonomous college to check their performance. The obtained result shows that if the task is divided into a group of systems, it can give better results. For different phishing features, the add-on system tool show around 97 percentage successful results at different case conditions. The current study would be very helpful to countermeasure the phishing attach and the proposed system is able to protect the user by phishing attacks. Since the system tool is capable of handling and managing the phishing website details, so it would be helpful to identify the category of the websites.
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Expert Finding System using Latent Effort Ranking in Academic Social Networks
Статья научная
The dynamic nature of social network and the influence it has on the provision of immediate solutions to a simple task made their usage prominent and dependable. Whether it is a task of getting a solution to a trivial problem or buying a gadget online or any other task that involves collaborative effort, interacting with people across the globe, the immediate elucidation that comes into anyone’s mind is the social network. Question Answer systems, Feedback systems, Recommender systems, Reviewer Systems are some of the frequently needed applications that are used by people for taking a decision on performing a day to day task. Experts are needed to maintain such systems which will be helpful for the overall development of the web communities. Finding an expert who can do justice for a question involving multiple domain knowledge is a difficult task. This paper deal with an expert finding approach that involves extraction of expertise that is hidden in the profile documents and publications of a researcher who is a member of academic social network. Keywords extracted from an expert’s profile are correlated against index terms of the domain of expertise and the experts are ranked in the respective domains. This approach emphasizes on text mining to retrieve prominent keywords from publications of a researcher to identify his expertise and visualizes the result after statistical analysis.
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Extend Web Service Security Negotiation Framework in Privacy
Статья научная
Nowadays web service privacy gets high attention especially in the fields of finance and medical. Privacy preserves access rights to personally identifiable information. Different models have been proposed for enforcing privacy in web service environment. Getting a privacy level for protecting data transferred between consumer and provider in a web service environment is still a problem. Negotiation helps participants to get a privacy level. This paper extends web service security negotiation framework in a multilateral web service environment for negotiating privacy. A repaired genetic negotiation framework used to conduct the privacy negotiation. In privacy negotiation, the negotiation communication structure uses a broker for negotiation; where each participant sends its attributes to the broker. Negotiation using this communication structure decreases the number of messages transferred so less execution time. The genetic-based Negotiation is compared to traditional time-based negotiation. Through experimental results, genetic based negotiation outperforms traditional time-based negotiation.
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Статья научная
We describe the programming language FOBS-X (Extensible FOBS). FOBS-X is interpreted, and is intended as a universal scripting language. One of the more interesting features of FOBS-X is its ability to be extended, allowing it to be adopted to new scripting environments. FOBS-x is structured as a core language that is parsed by the interpreter, and an extended language that is translated to the core by macro expansion. The syntax of the language can easily be modified by writing new macros. The library for FOBS-X is reconfigurable, allowing the semantics of the language to be modified, and adapted to facilitate the interaction with interfaces to new scripting environments. This paper focuses on the tools used for the semantic extension of the language. A tool called FEDELE has been developed, allowing the user to add library modules to the FOBS-X library. In this way the semantics of the language can be enhanced, and the language can be adapted.
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Extension of K-Modes Algorithm for Generating Clusters Automatically
Статья научная
K-Modes is an eminent algorithm for clustering data set with categorical attributes. This algorithm is famous for its simplicity and speed. The K-Modes is an extension of the K-Means algorithm for categorical data. Since K-Modes is used for categorical data so 'Simple Matching Dissimilarity' measure is used instead of Euclidean distance and the 'Modes' of clusters are used instead of 'Means'. However, one major limitation of this algorithm is dependency on prior input of number of clusters K, and sometimes it becomes practically impossible to correctly estimate the optimum number of clusters in advance. In this paper we have proposed an algorithm which will overcome this limitation while maintaining the simplicity of K-Modes algorithm.
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Extraction of Root Words using Morphological Analyzer for Devanagari Script
Статья научная
In India, more than 300 million people use Devanagari script for documentation. In Devanagari script, Marathi and Hindi are mainly used as primary language of Maharashtra state and national language of India respectively. As compared with English script, Devanagari script is reach of morphemes. Thus the lemmatization of Devanagari script is quite complex than that of English script. There is lack of resources for Devanagari script such as WordNet, ontology representation, parsing the keywords and their part of speech. Thus the overall task of information retrieval becomes complex and time consuming. Devanagari script document always carries suffixes which may cause problem in accurate information retrieval. We propose a method of extracting root words from Devanagari script document which can be used for information retrieval, text summarization, text categorization, ontology building etc. An attempt is made to design the Morphological Analyzer for Devanagari script. We have designed CORPUS containing more than 3000 possible stop words and suffixes for Marathi language. Morphological Analyzer can acts as a preliminary stage for developing any information retrieval application in Devanagari script. We have conducted the experiments on randomly selected Marathi documents and we found the accuracy of designed morphological analyzer is up to 96%.
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FBSEM: A Novel Feature-Based Stacked Ensemble Method for Sentiment Analysis
Статья научная
Sentiment analysis is the process of determining the attitude or the emotional state of a text automatically. Many algorithms are proposed for this task including ensemble methods, which have the potential to decrease error rates of the individual base learners considerably. In many machine learning tasks and especially in sentiment analysis, extracting informative features is as important as developing sophisticated classifiers. In this study, a stacked ensemble method is proposed for sentiment analysis, which systematically combines six feature extraction methods and three classifiers. The proposed method obtains cross-validation accuracies of 89.6%, 90.7% and 67.2% on large movie, Turkish movie and SemEval-2017 datasets, respectively, outperforming the other classifiers. The accuracy improvements are shown to be statistically significant at the 99% confidence level by performing a Z-test.
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FPGA Based High Accuracy Synchronous Acquisition Design for Binocular Vision System
Статья научная
This paper proposes a coarse-to-fine two-level synchronous data acquisition and transmission system for binocular stereo vision, which satisfies strict synchronous requirement of stereo vision. Specifically, this synchronization system design contains: coarse level synchronous based on hardware circuit design and the fine level synchronous based on hardware description language (HDL) design. The former includes the synchronization design of clock and external trigger. The latter utilizes a multi-level synchronous control strategy from field-level to pixel-level, which consists of field-synchronous acquisition of the two-channel video inputs, two-channel Ping-pong buffers switch control module, and pixel-synchronous bit-splicing and PCI transmission module. The experiments of synchronous acquisition and display demonstrate the high reliability and great performance of this synchronous system.
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