C: Software & Data Engineering (217)
GJCST: C
Intuitionistic Partition based Conceptual Granulation Topic-Term Modeling
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 Document Analysis represented in vector space model is often used in information retrieval, topic analysis, and automatic classification. However, it hardly deals with fuzzy information and decision-making problems. To account this, Intuitionistic partition based cosine similarity measure between topic/terms and correlation between document/topic are proposed for evaluation. Conceptual g...
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Authors D. Malathi, S. ValarmathyRead Journal Click Here
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Page No. 65 to 70
Effects of Mining Operations on Local Area Networks in Large Scale Gold Mining Environments in the Western Region of Ghana
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 We investigate the impacts mining operations have on established Wired/Wireless Local Area Networks (WLANs) in mining environments in the Western Region of Ghana. Mining activities have certain immutable negative impacts on the topography of the land with consequent effects on LAN Networks. Notable are undulating landscape with pronounced physical obstructions, LAN infrastructural reloca...
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Authors Emmanuel Effah, Christian Kwaku AmuzuviRead Journal Click Here
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Page No. 47 to 52
Information Retrieval based on Content and Location Ontology for Search Engine (CLOSE)
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 This paper mainly focuses on the personalization of the search engine based on data mining technique, such that user preferences are taken into consideration. Clickthrough data is applied on the user profile to mine the user preferences in order to extract the features to know in which users are really interested. The basic idea behind the concept is to construct the content and location...
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Authors Niranjan Kumar, S G Raghavendra PrasadRead Journal Click Here
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Page No. 19 to 25
An Advanced Clustering Algorithm (ACA) for Clustering Large Data Set to Achieve High Dimensionality
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 Cluster analysis method is one of the main analytical methods in data mining; this method of clustering algorithm will influence the clustering results directly. This paper proposes an Advanced Clustering Algorithm in order to solve this question, requiring a simple data structure to store some information [1] in every iteration, which is to be used in the next iteration. The Advanced Cl...
Evaluation the Quality of Software Design by Call Graph based Metrics
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 The prediction of software defects was introduced to support development and maintenance activities to improve the software quality by finding errors early in the software development. It facilitates maintenance in terms of effort, time and more importantly the cost prediction for software evolution and maintenance activities. In this paper, we evaluate the quality related attributes in ...
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Authors Sanjeev Kumar Punia, Dr. Anuj Kumar, Amit SharmaRead Journal Click Here
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Page No. 59 to 64
Cost based Model for Big Data Processing with Hadoop Architecture
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 With fast pace growth in technology, we are getting more options for making better and optimized systems. For handling huge amount of data, scalable resources are required. In order to move data for computation, measurable amount of time is taken by the systems. Here comes the technology of Hadoop, which works on distributed file system. In this, huge amount of data is stored in distribu...
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Authors Mayank Bhushan, Sumit Kumar YadavRead Journal Click Here
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Page No. 13 to 17
Stochastically Simulating the Effects of Requirements Creep on Software Development Risk Management
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 One of the major chronic problems in software development is the fact that application requirements are almost never stable and fixed. Creeping user requirements have been troublesome since the software industry began. Several empirical studies have reported that volatile requirements are a challenging factor in most information systems development projects. Software process simulation m...
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Authors P.K. Suri, Shilpa RaniRead Journal Click Here
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Page No. 9 to 12
Research of Data Mining Algorithm Based on Cloud Database
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 2 There is an immense amount of data in the cloud database and among these data, much potential and valuable knowledge are implicit. The key point is to discover and pick out the useful knowledge, and to do so automatically. In this paper, the data model of the cloud database is analyzed. Through analyzing and classifying, the common features of the data are extracted to form a feature dat...
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Authors Tianxiang Zhu, Xia Zhang, Dan Zhang, Xin LiuRead Journal Click Here
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Page No. 1 to 7
Supervised Classification of Remote Sensed Data using Support Vector Machine
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 1 Support vector machines have been used as a classification method in various domains including and not restricted to species distribution and land cover detection. Support vector machines offer many key advantages like its capacity to handle huge feature spaces and its flexibility in selecting a similarity function. In this paper the support vector machine classification method is applie...
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Authors Tarun Rao , T.V.RajinikanthRead Journal Click Here
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Page No. 71 to 76
A Framework for Context-Aware Semi Supervised Learning
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 1 Supervised learning techniques require large number of labeled examples to build a classifier which is often difficult and expensive to collect.Unsupervised learning techniques, even though do not require labeled examples often form clusters regardless of the intended purpose or context. The authors proposes a semi supervised learning framework that leverages the large number of unlabele...
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Authors Vijaya Geeta Dharmavaram, Shashi MogallaRead Journal Click Here
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Page No. 61 to 70
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Location Based Path Guiding System for the Visually Impaired People
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 1 Visually impaired or blind people faced tremendous challenges daily in accessing the information while on the move or during communicating with the world around them. They had to depend on their sighted colleagues, friends, relatives, or the people on the road to help them with locating places. Our Location Based Information System is such a location based application that works as an au...
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Authors M. Chowdhury, T. Alam, P.P.Purohit, S.A.FahimRead Journal Click Here
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Page No. 56 to 59
Students Learning Progression through Instrumental Decoding of Mathematical Ideas
Published In: GJCST Part: C: Software & Data Engineering Volume: 14 Issue: 1 The current study aims to focus on mathematical tasks for students’ mathematical literacy and problem solving literacy. Excerpts are presented from dynamic hypothetical learning paths [DHLP]s and students’ learning progression. The excerpts center around activities aimed to develop the students’ geometrical thinking through the developme...
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Authors Stavroula PatsiomitouRead Journal Click Here
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Page No. 1 to 42
Periodic Pattern Mining – Algorithms and Applications
Published In: GJCST Part: C: Software & Data Engineering Volume: 13 Issue: 13 Owing to a large number of applications periodic pattern mining has been extensively studied for over a decade. Periodic pattern is a pattern that repeats itself with a specific period in a give sequence. Periodic patterns can be mined from datasets like biological sequences, continuous and discrete time series data, spatiotemporal data and social networks. Periodic patterns are classifi...
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Authors G.N.V.G. Sirisha, M. Shashi, G.V. Padma RajuRead Journal Click Here
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Page No. 19 to 28
Simulation of Reliability of Software Component
Published In: GJCST Part: C: Software & Data Engineering Volume: 13 Issue: 13 Component-Based Software Engineering (CBSE) is increasingly being accepted worldwide for software development, in most of the industries. Software reliability is defined as the probability that a software system operates with no failure within a specified time on specified operating conditions. Software component reliability and failure intensity are two important parameters that Estimat...
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Authors Dr. P.K. Suri, Er. KarambirRead Journal Click Here
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Page No. 13 to 17