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• Open Access   Article

  Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics

  C. P. Patidar and Meena Sharma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.1-6, Jul-2013

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  In this paper we implement histogram computations on a Graphics Processing Unit (GPU). Our Histogram computations is implemented using compute unified device architecture (CUDA) which is a minimal extension to C/C++. In this development Histogram computations, computed on GPU’s global memory as well as on shared memory. We also perform Histogram computations on CPU and consider it as a baseline performance. Experimental results demonstrate that shared memory in GPU gives seven times speedup over our baseline CPU.

  Key-Words / Index Term
  GPUs, Histograms, CUDA, Global Memory, Shared Memory

  References
  [1]. J. D. Owens, D. Luebke, N. Govindaraju, M. Harris, J. KrÄuger, A. E. Lefohn, and T. Pur- cell, “A Survey of General-Purpose Computation on Graphics Hardware," Computer Graphics Forum, vol. 26, pp. 80-113, Mar. 2007.
  [2]. NVIDIA Corporation, CUDA: Compute Unified Device Architecture Programming Guide," tech. rep., NVIDIA, 2007.
  [3]. S. Sengupta, M. Harris, Y. Zhang, and J. D. Owens, “Scan Primitives for GPU Computing,"inGH '07: Proceedings of the 22nd ACSIGGRAPH/EUROGRAPHICS Symposium onGraphics Hardware, Switzerland, Eurographics Association, 2007, pp. 97-106.
  [4]. M. Harris, J. Owens, S. Sengupta, Y. Zhang, and A. Davidson. “CUDPP: CUDA Data Parallel Primitives Library".
  [5]. P. Harish and P. Narayanan, “Accelerating Large Graph Algorithms on the GPU Using CUDA" in High Performance Computing HiPC 2007, pp. 197-208.
  [6]. H. Nguyen, GPU Gems 3. Addison-Wesley Professional, 2007.
  [7]. Y. Luo and R. Duraiswami, “Canny Edge Detection on Nvidia CUDA" in Proc. of IEEE Computer Vision and Pattern Recognition, 2008, pp. 1-8.
  [8]. V. Podlozhnyuk, “64-bin histogram”, NVIDIA, Tech. Rep., 2007.
  [9]. K. H. Knuth, “Optimal data-based binning for histograms,” ArXiv Physics e-prints, May 2006.
  [10]. Compute Unified Device Architecture (CUDA) Programming Guide.
  [11]. NVIDIA. CUDA Compute Unified Device Architecture Programming Guide 2.0, July 2008.
  [12]. C. Ling, K. Benkrid, and T. Hamada, “A parameterisable and scalable smith-waterman algorithm implementation on cuda- compatible gpus,” Application Specific Processors, 2009. SASP ’09. IEEE 7th Symposium on, pp. 94–100, jul. 2009
  

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  C. P. Patidar and Meena Sharma, "Histogram Computations on GPUs Kernel using Global and Shared Memory Atomics," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.1-6, 2013

• Open Access   Article

  Data Dependencies Mining In Database by Removing Equivalent Attributes

  Pradeep Sharma and Vijay Kumar Verma

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.7-11, Jul-2013

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  Data Dependency plays a key role in database normalization, which is a systematic process of verifying database design to ensure the nonexistence of undesirable characteristics. Bad design could incur insertion, update, and deletion anomalies that are the major cause of database inconsistency [1, 2]. The discovery of Data Dependency from databases has recently become a significant research problem this paper, we propose a new algorithm, called DM_EC (dependency mining using Equivalent Candidates) for the discovery of all Dependency from a database. DM_EC takes advantage of the rich theory of Functional dependencies [1, 3, 4]. The use of Functional dependencies theory can reduce both the size of the dataset and the number of FDs to be checked by pruning redundant data and skipping the search that follow logically from the Functional dependencies already discovered. We show that our method is sound, that is, the pruning does not lead to loss of information. Experiments on datasets show that DM_EC can prune more candidates than previous methods [5].

  Key-Words / Index Term
  DBMS Normalization, Data Dependencies Mining, Data Mining

  References
  [1] St. Fephane Lopes, Jean-Marc Petit, and Lot_ Lakh Efficient Discovery of Functional Dependencies and Armstrong Relations C. Zaniolo et al. (Eds.): EDBT 2000, LNCS 1777, pp. 350{364, 2000. Springer-Verlag Berlin Heidelberg 2000.
  [2] Jixue Liu, Jiuyong Li, Chengfei Liu, and Yong Feng Chen Discover Dependencies from Data—A Review IEEE Transactions On Knowledge And Data Engineering, Vol. 24, No. 2, February 2012.
  [3] Catharine Wyss, Chris Giannella, and Edward Robertson FastFDs: A Heuristic-Driven, Depth-First Algorithm for Mining Functional Dependencies from Relation Instances Computer Science Department, Indiana University, Bloomington, IN 47405, USA
  [4] Fabien De Marchi CLIM: Closed Inclusion dependency mining in databases This work has been partially Funded by the French National Research Agency DEFIS 2009 Program, project DAG ANR-09-EMER-003-01
  [5] Katalin Tunde Janosi Rancz And Viorica Varga A Method For Mining Functional Dependencies In Relational Database Design Using Fca Studia Univ. Babes_{Bolyai, Informatics, Volume Liii, Number 1, 2008
  [6] Wenfei Fan Dependencies Revisited for Improving Data Quality PODS’08, June 9–12, 2008, Vancouver, BC, Canada.Copyright 2008 ACM
  [7] Pierre Allard⋆, Sebastien Ferr´e, and Olivier Ridoux Discovering Functional Dependencies and IRISA, Universities de Rennes 1, Campus de Beaulieu 35042 Rennes Cedex, France Association Rules by Navigating in a Lattice of OLAP Views
  [8] Y. V. Sreevani1, Prof. T. Venkat Narayana Rao2 Identification and Evaluation of Functional Dependency Analysis using Rough sets for Knowledge Discovery (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 1, No. 5, November 2010
  [9] Fabien De Marchi1, St´ephane Lopes2, and Jean-Marc Petit1 Efficient Algorithms for Mining Inclusion Dependencies C.S. Jensen et al. (Eds.): EDBT 2002, LNCS 2287, pp. 464–476, 2002. Springer-Verlag Berlin Heidelberg
  [10] Vijaya Lakshmi, Dr. E. V. Prasad A Fast and Efficient Method to Find the Conditional Functional Dependencies in Databases International Journal of Engineering Research and Development e-ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com Volume 3, Issue 5 (August 2012).
  [11] Hong Yao • Howard J. Hamilton Mining functional dependencies from data Received: 15 September 2007 Springer Science Business Media,
  [12] Daisy Zhe Wang Michael Franklin Luna Dong Anish Das Sarma Alon Halevy Discovering Functional Dependencies in Pay-As-You- Go Data Integration Systems Electrical Engineering and Computer Sciences University of California at Berkeley
  [13] Jalal Atoum, Dojanah Bader and 1Arafat Awajan Mining Functional Dependency from Relational Databases Using Equivalent Classes and Minimal Cover Journal of Computer Science 4 (6): 421-426, 2008
  [14] Nittaya Kerdprasop And Kittisak KerdprasopData Engineering Research Unit Functional Dependency Discovery via Bayes Net Analysis Recent Researches in Computational Techniques, Non-Linear Systems and Control ISBN: 978-1-61804-011-4
  [15] Mark Levene and Millist W. Vincent Justification for Inclusion DependencyNormal Form IEEE Transactions On Knowledge And Data Engineering, Vol. 12, No. 2, March/April 2000
  

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  Pradeep Sharma and Vijay Kumar Verma, "Data Dependencies Mining In Database by Removing Equivalent Attributes," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.7-11, 2013

• Open Access   Article

  An Intelligent New Age Method of Image Compression and Enhancement with Denoising for Bio-Medical Application

  Gopi.P.C, Sharmila.R, Indhumathi.T and Savitha.S

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.12-16, Jul-2013

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  Image compression is the reduction or elimination of redundancy in data representation in order to achieve reduction in storage and communication costs. In this paper, we are presenting the wavelet using SPIHT algorithm to compress the gray color images. This finds the coefficients of uncompressed image and minimize the number of bits to represent the image. The Huffman encoder is also designed in which the JPEG standardized table values are used for further compression. The compression of an image is followed by enhancement techniques to improve the contrast of an image. An enhancement algorithm is one that yields a better quality image for the purpose of some particular application which can be done by either suppressing the noise or increasing the image contrast Enhancement of image, One of the conventional methods adopted is the Histogram Equalization (HE) technique. The main limitation of this technique causes unpleasant visual artifacts, such as over enhancement, level saturation and raised noise level. Histogram Equalization with Improved Switching Median Filtering technique (WTHEISMF) which eliminates the impulse noise and preserves the edges of an image. This paper presents the parameters comparison and simulation results of HE, WTHE and WTHEISMF with Absolute Mean Brightness Error (AMBE), Measure of Enhancement (EME), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE).

  Key-Words / Index Term
  SPIHT, DWT, Histogram Equalization, contrast enhancement, Impulse noise, Improved Switching Median Filter

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  Citation
  Gopi.P.C, Sharmila.R, Indhumathi.T and Savitha.S, "An Intelligent New Age Method of Image Compression and Enhancement with Denoising for Bio-Medical Application," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.12-16, 2013

• Open Access   Article

  Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment

  Rajesh Verma

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.17-23, Jul-2013

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  Abstract
  Cloud Computing (CC) is emerging as the next generation platform which would facilitate the user s per requirement. It provides a number of benefits which could not otherwise be realized. The p e efficient access to remote and geographically distributed resources. A scheduling algorithm is n o the different resources. There are different types of resource scheduling technologies in CC envi ented at different levels based on different parameters like cost, performance, resource utilization, tances, throughput, bandwidth, resource availability etc. In this research paper various types of r algorithms that provide efficient cloud services have been surveyed and analyzed. Based on the st a classification of the scheduling algorithms on the basis of selected features has been presented.

  Key-Words / Index Term
  Cloud computing;Scheduling algorithms; Resource allocation; Open source; Virtual machine

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  Citation
  Rajesh Verma , "Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.17-23, 2013

• Open Access   Article

  A Wearable Personal Healthcare and Emergency Information Based On Mobile Application

  Sanjay S Bhadoria and Hitesh Gupta

  Technical Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.24-30, Jul-2013

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  Abstract
  Mobile computing makes it possible to achieve system of personal healthcare and emergency alert and tracking which can monitor personal health status in a real-time manner and automatically issue the alert for medical aids in case of emergency by tracking user’s location correctly. With the development of the technologies such as mobile computing, distributed computing and wireless sensor network, it is possible to provide the elderly with healthcare services that can monitor the elderly anytime anywhere. This paper presents a review on mobile based health monitoring systems. It also discusses the desirable properties of a good mobile health care system as well as few existing health care applications are also briefly described.

  Key-Words / Index Term
  Wireless Sensor Networks, GSM, AMON, LAN, MobiHealth

  References
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  Citation
  Sanjay S Bhadoria and Hitesh Gupta , "A Wearable Personal Healthcare and Emergency Information Based On Mobile Application," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.24-30, 2013

• Open Access   Article

  Convergence of IT and Data Mining with other technologies

  Shilpa Mahajan

  Technical Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.31-37, Jul-2013

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  Abstract
  In this age of technology and communication convergence, we cannot help but be impacted by technologies and innovations that center on computers. This paper examines the growing need for a secure environment and a general-purpose analytics engine. The process need for secure environment is Physical or It security and the process used for analysis is called Data Mining. This paper will also give us the review towards the convergence of various technologies such as IT and Physical Security and data mining with biology, computing, mobility, knowledge management, etc. for human values like privacy, recognition, operational intelligence, etc. and also relationship between data mining/IT security.

  Key-Words / Index Term
  IT security, physical security, convergence; mobility data mining; genomics; proteomics; RMS; process management

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  Citation
  Shilpa Mahajan, "Convergence of IT and Data Mining with other technologies," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.31-37, 2013

• Open Access   Article

  Securing the Cloud Environment Using OTP

  Vimmi Pandey

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.38-43, Jul-2013

  Abstract

  Full-Text HTML

  References

  Citation

  Abstract
  In today’s scenario, websites have been converted from just a display of information into an online transaction in the form of goods, services, or money. Along with development, the security of the website is also need to be tightened, not just rely on usernames and passwords but also to the dynamic code of the mobile token which is difficult to be cracked. Dynamic mobile token is an application which is planted in the mobile phone to generate a code that was formed by the method of one time password and can only be used for one login session or transaction. Each mobile token has a value in the "secret" variable that makes it unique or different from the others, to separate one user access transactions or personal page.

  Key-Words / Index Term
  One Time Password, MD5 Algorithm, Website Security, Authentication, Mobile Token

  References
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  [3] Rivest, Ronald L. 1992.The MD5 Message Digest Algorithm.
  [4] Shivlal Mewada, Umesh Kumar Singh and Pradeep Sharma, “ Security Enhancement in Cloud Computing (CC)”, IJSRCSE, Volume-01 , Issue-01, Page No : 31-37 3013
  [5] Rajesh Piplode, Pradeep Sharma and Umesh Kumar Singh , “Study of Threats, Risk and Challenges in Cloud Computing”, IJSRCSE, Volume-01 , Issue-01, Page No : 26- 30, 2013
  [6] Vishal Paranjape and Vimmi Pandey’ “ An Improved Authentication Technique with OTP in Cloud Computing” IJSRCSE, Volume-01 , Issue-03, Page No : 22-26, 2013
  [7] “Privacy and consumer risks in cloud computing”, Dan Svantesson, Roger Clarke, computer law & security review 26 (2010 ) 391e97, @ 2010 Svantesson & Clarke. Published by Elsevier Ltd. doi:10.1016/j.clsr.2010.05.005.
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  Citation
  Vimmi Pandey, "Securing the Cloud Environment Using OTP," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.38-43, 2013

• Open Access   Article

  Analysis of Current Control Techniques on Bridgeless Interleaved Boost DC-DC Converter to Improve Power Quality

  R.Seyezhai, Abhinaya Venkatesan, M.Ishwarya and K.Gayathri

  Research Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.44-49, Jul-2013

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  This paper presents the comparison of various current control techniques employed for a bridgeless interleaved boost converter for improving the power quality. The major control strategies discussed in this paper are: peak current, average current mode and borderline current control. These strategies are implemented in MATLAB/SIMULINK and the performance of the proposed converter is compared under open loop and closed loop operation. From the results, the input current waveform was close to sinusoidal implying high power factor and reduced harmonics for borderline control.

  Key-Words / Index Term
  Bridgeless IBC, THD, Power Factor & , Current Control Techniques

  References
  [1]. Balogh.L and Redl.R, Power-factor correction with interleaved boost converters in continuous-inductor- current mode, Applied Power Electronics Conference and Exposition (APEC), Eighth Annual Conference Proceedings, Print ISBN: 0-7803-0983-9, pp. 168 – 174, 1993.
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  [8]. Kamran Rezaei, “A Control Scheme for an AC-DC Single-Stage Buck-Boost PFC Converter with Improved Output Ripple Reduction”, Dissertation, The School of Graduate and Postdoctoral Studies, University of Western Ontario - Electronic Thesis and Dissertation, 2012.
  [9]. J. P Gegner, C. Q. Lee, Linear Peak Current Mode Control: A Simple Active Power Factor Correction Control Technique for Continuous Conduction Mode, PESC Conf.Proc., 1996, pp. 196-202.
  [10]. J. R. Rajagopalan, P. Nara, F. C. Lee, A generalized Technique for Derivation of Average Current Mode Control Laws for Power Factor Correction without Input Voltage sensing, APEC Conf. Proc., 1997,,pp. 81-87.
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  [12]. Santosh A and Shivashankar Tallada , Simulation Of High-Efficiency AC/DC Converter For Power Factor Correction - International Journal of Engineering Research and Applications(IJERA)ISSN:2248-9622, Vol. 2, Issue4, pp.2043-2050, 2012.
  

  Citation
  R.Seyezhai, Abhinaya Venkatesan, M.Ishwarya and K.Gayathri, "Analysis of Current Control Techniques on Bridgeless Interleaved Boost DC-DC Converter to Improve Power Quality," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.44-49, 2013

• Open Access   Article

  A Report on Latest Software Testing Techniques and Tools

  Chandraprakash Patidar

  Review Paper | Isroset-Journal (IJSRCSE)

  Vol.1 , Issue.4 , pp.50-52, Jul-2013

  Abstract

  Full-Text HTML

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  Citation

  Abstract
  Software testing is a process in which software is tested against the requirements of users. Software testing is itself a separate discipline in itself. Software testing is very important because software must be error free before it goes to the user. There is various software techniques available classified on the basis of nature. As technology grows software testing tools are also emerged to perform software testing smoothly. In a competitive market age variety of software tools available, a software tester can use a tool according to their requirements. Generally in software testing the most commonly used terms are validation and verification. Some people consider both terms as same but both term has different meaning and closely related to each other. Software testing is a process of verifying and validating software.

  Key-Words / Index Term
  Software Testing, Testing Tools, Validation, Verification

  References
  [1] Kaur, M 2011. Comparative study of automated testing tools. Int.J. Comp. Appl. 24(1): 1-7.
  [2] Luo, G and Ural, H. 1995. Approach to constructing software unit testing tools. Soft. Engg. J. 10(6):
  245-252.
  [3] Mesbah, A, Van Deursen, A and Roest, D 2012. Invariant-Based automated testing of modern web applications. IEEE Trans. Soft. Engg. 38(1): 35-53.
  [4] Rattan, R 2013. Performance evaluation and comparison of software testing tool. Int. J. Inform Comp. Technol. 3(7): 711-716.
  [5] Shahid, M 2011. A study on test coverage in software testing. Int. Conf. on Telecommunication Technol. Appl. Vol. 5.
  [6] Nirmal Kumar and B G Geetha. 2014. Working with IBM Rational Functional Tester: A Software Testing Tool. Journal of Academia and Industrial Research. 2(12):669-674.
  

  Citation
  Chandraprakash Patidar, "A Report on Latest Software Testing Techniques and Tools," International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.50-52, 2013