iosr-JCE   Volume-19 ~ Issue-1 ~ Jan-Feb 2017

Abstract: Today, the importance of information and accessing information is increasing rapidly. With the advancement of technology, one of the greatest means of achieving knowledge are, computers have entered in many areas of our lives. But the most important of them are the communication fields. This study will be a practical guide for understanding how to assemble and analyze various parameters in network performance evaluation and when designing a network what is necessary to looking for to remove the consequences of degrading performance...........

Keyword: Router, Network Performance Evaluation, eNSP, Packet Tracer

[1]. OLIVIER BONAVENTURE (2015), Computer Networking : Principles, Protocols and Practicehttp://www.computerhope.com/ jargon/n/network.htm.pdf
[2]. JD MEIER (2015) https://www.quora.com/What-is-the-difference-between-performance-testing- load-test.
[3]. İTÜBİDB (2015) Captive Portal (Restriction Portal). İstanbul. http://bidb.itu.edu.tr/seyirdefteri/blog/2013/09/07/captive-portal-(k%C4%B1s%C4%B1tlama-portal%C4%B1)
[4]. MEGEP. (2015). Wireless Network Systems. http://www.megep.meb.gov.tr /mte_program_modul/moduller_pdf/Kablosuz%20A% C4%9F%20Siste
[5]. CISCO (2015) VLANTrunk Protocol. Cisco: http://www.cisco.com/c/en/us/support/docs/lan- switching/vtp/10558-21.html#req adresinden alındı

Abstract: Breast cancer can be considered one of the most dangerous types of cancer among women. Early detection of breast cancer leads to significant improvements in treatment. Digital mammograms are one of the most effective means for detecting breast cancer in early stages. In this paper, an efficient system based on performing professional pre-processing phase and on applying Discrete Cosine Transform (DCT) for features extraction, and support vector machine has been used for classification into benign and malignant. We have used Mias data set for experimentation purpose. We tune the coefficients of DCT to get the best sensitivity, specificity, positive predicitivity, and accuracy results. We reach 100% performance rate in some cases.

Keywords: Breast Cancer, Mammogram, Discrete Cosine Transform, Svm, Mias Data Set.

[1]. Priyanka, Diganbar: Digital mammography: A review on detection of breast cancer, International Journal of Advanced Research in
Computer and Communication Engineering, Vol. 5, Issue 1, Jan 2016.
[2]. Talha, et al. : Classification of breast mammograms into benign and malignant, International Journal of Multimedia and Ubiquitous
Engineering, Vol. 7, No. 2, 2012
[3]. Jaffar, et al.: DCT Features based malignancy and abnormality type detection method for mammograms, International Journal of
Innovative Computing, Information and control, Vol. 7, No. 9, 2011.
[4]. Rashed et al., : Mutiresolution mammogram analysis in multilevel decomposition, Pattern Recognition Letters, Vol. 28,2007.
[5]. Talha, : Classification of mammograms for breast cancer detection using fusion of discrete cosine transform and discrete wavelet
transform features, Biomedical Research Vol. 27, No.2, 2016.

Abstract: This paper addresses the issues and techniques for Property/Casualty actuaries applying data mining methods. Data mining means the effective unknown pattern discovery from a large amount database. It is an interactive knowledge discovery procedure which is includes data acquisition, data integration, data exploration, model building, and model validation. The paper provides an overview of the data discovery method and introduces some important data mining method for application to insurance concluding cluster discovery approaches.

Keyword: Kdd,weka,gnu

[1]. Smita R. Londhe, Rupali A. Mahajan and Bhagyashree J. Bhoyar," Overview on Methods for Mining High Utility Itemset from Transactional Database", International Journal of Scientific Engineering and Research (IJSER) www.ijser.in, Volume 1 Issue 4, December 2013
[2]. K. Umamaheswari and Dr. S. Janakiraman," Role of Data mining in Insurance Industry", An international journal of advanced computer technology, 3 (6), June-2014 (Volume-III, Issue-VI), pp: 961- 966.
[3]. A. B. Devale and Dr. R. V. Kulkarni," APPLICATIONS OF DATA MINING TECHNIQUES IN LIFE INSURANCE", International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.2, No.4, July 2012, pp: 31- 40.
[4]. Ruxandra PETRE," Data Mining Solutions for the Business Environment", Database Systems Journal vol. IV, no. 4/2013, pp:21-31
[5]. Dr. Sudhir B. Jagtap and Dr. Kodge B. G," Census Data Mining and Data Analysis using WEKA", (ICETSTM – 2013) International Conference in "Emerging Trends in Science, Technology and Management-2013, Singapore, Census Data Mining and Data Analysis using WEKA, pp: 35-40.