Volume-4 , Issue-1 , Feb 2016, ISSN 2320-7639 (Online) Go Back

• Open Access   Article

  Precision Improvement in Information Storage and Retrieval System by Document Length Normalization

  D. Sharma, H Nagar

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.4 , Issue.1 , pp.1-5, Feb-2016

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  Abstract
  Huge amount of information are available over the internet in electronic document format but retrieving the correct document according to users information need is very critical task. The relevancy of the document can vary according to the length of document. Automatic information storage and retrieval system have to deal with documents of varying length in text collection. In this paper we are presenting a document term weighting scheme based on length of document. Our method increases the rank of relevant document in the retrieved ordered document set. From the result we have seen that our method increase the document rank from 0.83 precision to 0.16 precision.

  Key-Words / Index Term
  Document length, Normalization, Rank, Storage system, Precision, Information Storage and Retrieval System, Normalization

  References
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  [24] A. Todirascu, L. Romary, D. Bekhouche, “Vulcain — An Ontology- Based Information Extraction System,” Lecture Notes in Computer Science, Vol. 2553, pp.64-75, 2002.
  [25] M. Vargas-Vera, E. Motta, J. Domingu, S. Shum, M. Lanzoni, “Knowledge extraction by using an ontology-based annotation tool”, In Proceedings of the workshop on knowledge markup and semantic annotation, NY, pp.1-13, 2001.
  [26] B. Popov, A. Kiryakov, D. Ognyanoff, D. Monov, A. Kirilov, “KIM – a semantic platform for information extraction and retrieval”, Natural Language Engineering, Vol.10, Issue3, pp. 375-392,2004.
  [27] B. Adrian, J. Hees, L. Elst, A. Dengel, “iDocument: Using Ontologies for Extracting and Annotating Information from Unstructured Text”, Lecture Notes in Computer Science, Vol.5803, pp.249-256, 2009.
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  Citation
  D. Sharma, H Nagar, "Precision Improvement in Information Storage and Retrieval System by Document Length Normalization," International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.1, pp.1-5, 2016

• Open Access   Article

  Analysis of Full and Half Adder Using Different Logic Style

  Anil Pratap

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.4 , Issue.1 , pp.6-9, Feb-2016

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  Abstract
  In recent year, power dissipation is one of the biggest challenges in VLSI design. Adder circuits are the main sources of power dissipation in signal processing units. By reducing the number of transistors in the circuits and the design structures are may occupied small area and low power design. In this paper a Full Adder Circuit is designed by using CMOS, Transmission gates and pass Transistor logic and the power and delay are analysed. Power consumption and speed are two important but conflicting design aspects; hence a better way to evaluate circuit performance is power delay product (PDP). The designs are implemented and power, delay results are obtained by using TANNER EDA Tool. The results show that the transistor counts, delay and the power required are significantly concentrated in the design.

  Key-Words / Index Term
  Full Adder, CMOS, Transmission Gate (TG), Pass Transistor, Power Dissipation, Delay, PDP

  References
  [1]. Sung-Mo Kang, Yusuf Leblebici; “CMOS digital integrated circuits: analysis and design”; Tata Mcgraw-Hill, Third Edition, pp.1-847, 2003
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  [7]. Nishan Singh, Mandeep Kaur, Amardeep singh, Puneet Jain, “An Efficient Full Adder Design using Different Logic Styles”; International Journal of Computer Applications, Vol.98, No.21, 2014.
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  Citation
  Anil Pratap, "Analysis of Full and Half Adder Using Different Logic Style," International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.1, pp.6-9, 2016

• Open Access   Article

  Analyzing the perfoamce of Big Data in Education System

  N. Bhargaw, H. Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.4 , Issue.1 , pp.10-14, Feb-2016

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  Abstract
  Big data have emerged very fast in the last couple of years and it came up with a number of solutions to different problems varies from effective decision making, real time decision making, and effective implementation of E-Governance etc. Information and Communication technology is the major responsible for this boom in the data. It has also given birth to number of challenges like Effective data architectures, Effective analysis algorithm, Frameworks to handle this big data. As the size of data is increasing repeatedly, it gives a challenge of scaling the frameworks which could be able to handle such data. On the basis of aforesaid problems and challenges this paper has proposed a scalable architecture for the analysis of Big Data in higher Education System.

  Key-Words / Index Term
  Big Data, ICT, Scalability, Frameworks, Architectures, Education system

  References
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  Citation
  N. Bhargaw, H. Sharma, "Analyzing the perfoamce of Big Data in Education System," International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.1, pp.10-14, 2016

• Open Access   Article

  Survey of Quality Models for Evaluating Quality in OSS (Open Source Software)

  Hemant Malviya, Sita Solanki

  Survey Paper | Isroset-Journal (IJSRCSE)

  Vol.4 , Issue.1 , pp.15-20, Feb-2016

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  Abstract
  Open source software (OSS) projects are available in various application domains in a large number. It is difficult to choose any product/project. Quality is a big concern while choosing a software among many of the same type. To measure the quality there are many quality models around us since long. More specifically, from 2003 ,there has been many quality models available in OSS. But how good these quality models are ,remains the question of concern. This research is intended to provide an insight in existing quality models and provide the strength & weakness of these models, thus to provide the OSS community a best suitable quality model. In this paper, the researchers have reviewed the available literature on some conventional quality models and some selective OSS quality models, and carried out a comparative study on these models. In first generation models, open source maturity model embraces the maximum quality characteristics. We concluded that Qual-OSS quality model in second generation is close to international standard organization (ISO) 25010 quality standard. The second generation models offer more tools to support the quality evaluation by considering the community characteristic of OSS.

  Key-Words / Index Term
  OSS, OSMM, ISO, Qual-OSS, Qualipso, OpenBRR, QSOS, QualOSS, CMM,OSSD

  References
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  Citation
  Hemant Malviya, Sita Solanki, "Survey of Quality Models for Evaluating Quality in OSS (Open Source Software)," International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.1, pp.15-20, 2016

• Open Access   Article

  Classification of Data Mining Techniques for Weather Prediction

  Jaswant Meena, Ashish Mandloi

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.4 , Issue.1 , pp.21-24, Feb-2016

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  Abstract
  Weather forecasting is critically important application in meteorology and has been one of the most scientifically and technologically challenging problem through out the globe since past and still only approximations are being made to accurate prediction of weather eventslike cloudburst,hailingetc. Machine learning algorithms are implemented in data mining process to extract hidden patterns and useful information from huge weather databases, essential to get prepare for the worst of the ambience. This paper propounds the comparative analysis of various data mining techniques applied by different researchers in different domains. This survey also reviews the available literatures of algorithms applied by different researchers to exploit various data mining techniques for detecting and predicting weather events. For weather prediction Decision Tree, Artificial Neural Network and SVM techniques gives better results with high prediction accuracy than other data mining techniques for multidimensional weather data sets.

  Key-Words / Index Term
  Data mining; Decision Tree; Hailstorm; Machine Learning; Multilayer Perceptron; Support Vector Machine

  References
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  [8] K. Pabreja,“Clustering technique to interpret Numerical Weather Prediction output products for forecast of Cloudburst”, International Journal of Computer Science and Information Technologies, Vol.3, Issue.1, pp.2996 – 2999, 2012.
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  Citation
  Jaswant Meena, Ashish Mandloi , "Classification of Data Mining Techniques for Weather Prediction," International Journal of Scientific Research in Computer Science and Engineering, Vol.4, Issue.1, pp.21-24, 2016