Volume-04 , Special Issue-01 , Feb - 2016 Go Back

In this paper we have proposed a improvised version of Round Robin Scheduling Algorithm by calculating Dynamic Time Quantum (DTQ) and taking into consideration the priorities assigned with the processes. We have compared the performance of the proposed Advanced Priority Based Dynamic Round Robin Scheduling Algorithm (APBDRR) with the performances of Round Robin Algorithm (RR), Improved Shortest Remaining Burst Round Robin Algorithm (ISRBRR) and Efficient Dynamic Round Robin Algorithm (EDRR). Experimental results show that the proposed algorithm performs better than these algorithms in terms of Average Waiting Time(AWT) and Average Turnaround Time(ATAT).

CPU Scheduling; Round Robin Scheduling; Priority Scheduling; Waiting Time; Turnaround Time; Time Quantum; Priority, Advanced Priority Based Dynamic Round Robin Scheduling Algorithm

[1]. Sanjay Kumar Panda and Saurav Kumar Bhoi, “An Effective Round Robin Algorithm using Min-Max Dispersion Measure”, International Journal on Computer Science and Engineering, 4(1), pp. 45-53, January 2012.
[2]. Pallab Banerjee, Probal Banerjee, Shweta Sonali Dhal, “Comparative Performance Analysis of Average Max Round Robin Scheduling Algorithm (AMRR) using Dynamic Time Quantum with Round Robin Scheduling Algorithm using Static Time Quanmtum”, International Journal of Innovative Technology and Exploring Engineering, 1(3), pp. 56-62, August 2012.
[3]. P.Surendra Varma, “A Finest Time Quantum for Improving Shortest Remaining Burst Round Robin (SRBRR) Algorithm”, Journal of Global Research in Computer Science, 4 (3), pp. 10-15, March 2013.
[4].
[5]. Raman, Dr.Pradeep Kumar Mittal, “An Efficient Dynamic Round Robin CPU Scheduling Algorithm (EDRR)”, International Journal of Advanced Research in Computer Science and Software Engineering, 4(5), pp. 907-910, May 2014.
[6]. Silberschatz, A., P.B. Galvin and G. Gagne, Operating Systems Concepts. 7th Edn., John Wiley and Sons, USA., ISBN: 13: 978-0471694663, pp. 944.
[7]. Rakesh Mohanty, H. S. Behera, Khusbu Patwari, Monisha Dash, “Design and Performance Evaluation of a New Proposed Shortest Remaining Burst Round Robin (SRBRR) Scheduling Algorithm”, Proc. of International Symposium on Computer Engineering & Technology 2010, Vol 17, pp. 126-137, 2010 .
[8]. R. J. Matarneh, “Seif-Adjustment Time Quantum in Round Robin Algorithm Depending on Burst Time of the Now Running Proceses”, American Journal of Applied Sciences, 6(10), pp. 1831-1837, 2009.
[9]. H. S. Behera, R. Mohanty, and D. Nayak, “A New Proposed Dynamic Quantum with Re-Adjusted Round Robin Scheduling Algorithm and Its Performance Analysis”, International Journal of Computer Applications, 5(5), pp. 10-15, August 2010.

Debasmita Saha, Ardhendu Mandal , "Design and performance evaluation of Advanced Priority Based Dynamic Round Robin Scheduling Algorithm (APBDRR)", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.78-84, 2016.

Medical image processing is a huge and challenging research field. Cancer of the breast is the most common among women in world wide. Mammography is a effectivediagnostic and screening tool to detect breast cancer at early stage. Mammograms use doses of ionizing radiation to create images like all X-rays. These images are then analyzed for any abnormal findings. Multiple research studies have been developed to improve cancer detection,diagnosis and evaluation.Over the last decade there has been a marked increased in the use of mammography to detect breast cancer. Various segmentation techniques have been used for detection of breast tumor from mammographic image in last decade. In this paper a method has been proposed based on histogram segmentation to detect the breast cancer from Mammographic images. The whole procedure has been done in MATLAB.

Mammogram, Breast Cancer, Histogram Peak Slicing, Histogram Thresholding

[1] G.BharathaSreeja, Dr. P. Rathika, Dr. D. Devaraj“Detection of Tumours in Digital Mammograms Using Wavelet Based Adaptive Windowing Method”I.J.Modern Education and Computer Science, Vol.(03), pp. 57-65 April 2012
[2] http://seer.cancer.gov/statfacts/html/breast.html [Accessed on 15/01/2016].
[3] http://www.nationalbreastcancer.org/breast-cancer-diagnosis [Accessed on 15/01/2016].
[4] http://breast-cancer.ca/abnorm-mams[Accessed on 15/01/2016]
[5] Kai-yang Li, Zheng Dong, “A Novel Method of Detecting Calcifications from Mammogram Images Based on Wavelet and Sobel Detector,” Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference, pp.1503 – 1508, June 2006.
[6] Diyana, W.M., Besar, R., “Methods for clustered microcalcifications detection in digital mammograms,” ISSPIT,Vol.(02), pp.99 - 104 Dec.2004.
[7] Songyang Yu, Ling Guan, “A CAD system for the automatic detection of clustered microcalcifications in digitized mammogram films” IEEE Transactions on Medical Imaging, Vol.( 19(02)), pp. 115 - 126, Feb. 2000
[8] Auephanwiriyakul, S., Attrapadung, S., Thovutikul, S., Theera- Umpon N., “Breast Abnormality Detection in Mammograms Using Fuzzy Inference System,” Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference , pp. 155-160, May.2005.
[9] https://en.wikipedia.org/wiki/Image_noise[Accessed on 14/01/2016]
[10] KanishkaSarkar, ArdhenduMandal and Rakesh Kumar Mandal, “Brain Tumor Detection from T1 Weighted MRI Using Histogram Peak Difference Threshold”, Proc. of National Conference on Research Trends in Computer Science and Application (NCRTCSA-2015),pp.32-37, Nov. 07, 2015

Probal Dutta, Kanishka Sarkar, Ardhendu Mandal, "Segmentation of Breast Tumor from Mammographic Images Using Histogram Peak Slicing Threshold", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.85-92, 2016.

Now-a day e-learning is getting popularity than the traditional learning methods. Internet or Intranet is the main communication media in case of e-learning. Since, the access of Internet is very easy now-a-daysand the new generation is so much efficient about the using of Internet, so, the security plays a vital role in case of e-learning. To provide authenticity, we can apply DES algorithm during the transmission of mark sheet from developer to student, two main components of e-learning. The object oriented analysis and design of any system, makes a better understanding of the system and adjustable with the real world. The fundamental characteristic of object oriented analysis is to provide data hiding, encapsulation, data abstraction etc.We can define so many types of metrics like size metric, coupling metric, cohesion metric, inheritance metric etc. in metric analysis. Other than CK metric and MOOD metric, there are also some other object oriented metrics like Lorenz and Kidd, Harrison, Counsell and Nithi etc. We will find the values of different metrics in respect of the DES algorithm regarding the transmission of study material from developer to student.

E-learning, DES Algorithm, Class Hierarchy Diagram, Object-Oriented Metrics

[1]. Weippl, R.E., Security in E-Learning (Springer, 2005)
[2]. Andrew, S. Tanenbaum (2005), Computer Networks, Pearson Prentice Hall
[3]. Behrouz, AForouzan (2006), Data Communication and Networking, Tata McGraw Hill
[4]. S. Karforma and S. Banerjee, “Object Oriented Implementation of DES forSecurity in E-Learning”, Asian Resonance, vol-III, Issue-IV, Oct-14, pp: 12-20
[5]. [http://ce.sharif.edu/courses/8586/1/ce924/resources/root/4.%20Kamandi_OOMetrics.pdf
[6]. K.K.Aggarwal, Y. Singh, A. Kaur, R. Malhotra, “Empirical study of object oriented metrics”, Journal of Object Technology, ETH Zurich, Chair of Software Engineering, Vol. 5, No. 8, November-December 2006, pp: 149-173
[7]. Rajib Mall, Fundamentals of Software Engineering (Prentice Hall of India, New Delhi, 2006)
[8]. Karforma S. and Mukhopadhyay S., A Study on the application of Cryptography in E-Commerce, The University of Burdwan, West Bengal, India, July-2005
[9]. Muktamyee S., An overview of Object Oriented Design Metrics, (Master Thesis) Department of Computer Science, Umeå University, Sweden June 23, 2005
[10]. www.psu.edu/courses/infsy/infsy570_rxo4/metrics/metrics.ppt
[11]. http://techterms.com/definition/class
[12]. Balagurusami E., Object oriented programming with C++ (Tata McGraw Hill, New Delhi, 2006)
[13]. A. Kamandi, “Object Oriented Metrics”, Sharig University of technology, spring 2007
[14]. S. Karforma and S. Banerjee, “Object oriented metric based analysis of ElGamal digital signature algorithm for study material authentication”, IJSTM, vol-4, special issue-1, sept-15, pp: 522-530

Soumendu Banerjee, Sunil Karforma, "Object Oriented Metrics Based Analysis of DES algorithm for secure transmission of Mark sheet in E-learning", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.93-98, 2016.

Handwritten Character Recognition (HCR) is the ability of a computer to receive and interpret handwritten input captured by as digital cameras or other devices.Recognition of handwritten characters by computer is a serious problem because there are a many variety of writing styles, character shapes written by different individuals. The main objective of our project is to recognize the handwritten characters present in a bank cheque. Paper cheques still play a big role in the non-cash transactions in the world even after the arrival of credit cards, debit cards and other electronic means of payment. Huge volumes of handwritten bank cheques are processed manually every day in developing countries. The present cheque processing procedure requires a bank employee to read and manually enter the information present on a cheque (or its image) and also verify the entries like signature and date. An attempt is made in this project to recognize the characters present payee name and in the cheque amount by using image processing techniques on handwritten cheque images. The system uses broad steps like thresholding, image segmentation, thinning and pattern matching for extraction of characters. The pattern matching is done using graph based method. Graph matching techniques areintroduced to compute the similarity of characters extracted from bank cheque with theinformation of characters store in the database.

Segmentation, Thinning, Scaling, Pattern matching, COG, complete Bipartite Graph, Adjacency matrix

[1]. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 3rd Edition, Prentice Hall, 2009.
[2]. Youssef EsSaady, Ali Rachidi, Mostafa El Yassa, DrissMammass, “AmazighHandwritten Character Recognition based on Horizontal and Vertical Centerline of Character”, International Journal of Advanced Science and Technology Vol. 33, August, 2011
[3]. R. Palacios, A. Gupta, P. S. Wang, “Handwritten Bank Cheqe Recognition”,International Journal of Image and Graphics, Vol. 4, No. 2 (2004)
[4]. R. Jayadevan, S. R. Kolhe, P. M. Patil, U. Pal, “Automatic processing of handwritten bank cheque images: a survey”
[5]. B. R. Ghosh, S. Banerjee, S. Dey, S. Ganguli, S. Sarkar, “Off-Line Signature Verification System Using Weighted Complete Bipartite Graph”, 2nd International Conference on Business and Information Management (ICBIM), ISBN : 478-1-4799-3264-1/14/$31.00 ©2014 IEEE pp.109-113.
[6]. Otsu, N.: A threshold selection method from gray-level histograms, IEEE Trans. Sys., Man., pp.62–66.
[7]. B. Chanda and D. D. Majumder, Digital Image Processing and Analysis. Prentice Hall India, 2009.

Siddhartha Banerjee, Bibek Ranjan Ghosh, Arka Kundu, "Handwritten Character Recognition from Bank Cheque", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.99-104, 2016.

The increasing demand for food production due to the rising population has necessitated the use of advanced and efficient methods in the production process. Fishing in the coast (marine fishing) has also seen the same change, from rudimentary methods to use of data collected from various ocean monitoring platforms. The spatial data collected from these platforms require processing using dedicated systems running the required algorithms to ultimately acquire the information that help the fishing community to land the best catch with minimal effort and resources. This type of Geographic Information System (GIS) is being exploited for fishing in various parts of the world and this paper is aimed at understanding how such a system is employed and how they have rendered results (in Indian context) that would otherwise have been remotely achievable.

Geographical Information System (GIS); Remote Sensing (RS);Fishing Industry

[1] Butler, Mouchot, Barale & LeBlanc. The application of Remote Sensing Technology to Marine Fisheries: An Introductory Manual.
[2] Shibendu Sarkar Ray, Dept. of Agriculture & Cooperation, New Delhi, India. Remote Sensing Applications: Indian Experience.
[3] Dr. P. U. Zacharia. Present and Future Scenario of Indian Marine Fisheries.
[4] Planning Commission, Govt. of India. Report on the Working Group on “Development and Management of Fisheries and Aquaculture”.
[5] Chandasudha Goswami& Dr. V. S. Zade. Statistical Analysis of Fish Production in India.
[6] Indian Space Research Organisation (ISRO). Repot of the Working Group on “Space”, 11th Five Year Plan Proposals (2007-2012).
[7] ICFS, 7:30 PM, 25-11-2015, Fisheries and Fishing Communities in India. Retrieved from official website http://indianfisheries.icsf.net/
[8] National Remote Sensing Center (NRSC), ISRO, 10:30 PM, 25-11-2015. Satellite Data Products and Services. Retrieved from NRSC official website http://www.nrsc.gov.in/Data_Products_Services_Satellite.html.
[9] Dept. of Agriculture, Dept. of Animal Husbandry, Dairying and Fisheries, Govt. of India. Handbook of Fisheries Statistics, 2014.
[10] Dr. Paul R. Baumann, State University of New York. Introduction to Remote Sensing.
[11] G. Subbaraju, Central Marine Research Institute, Cochin. Remote Sensing in Marine Fisheries - Indian Experience.
[12] ISRO, 7:30 PM, 25-11-2015, Applications. Retrieved from official websitehttp://www.isro.gov.in/applications/satellite-aided-search-and-rescue

Dilip Roy Chowdhury, Charan Kumar Rai, Prajeet Sharma, "Remote Sensing Applied in Marine Fishing: A Review on Indian Marine Fishing Industry Context", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.105-111, 2016.