iosr-JCE   Volume-21 ~ Issue-3 ~ May-June 2019

Abstract: The human brain tumor is great threat in the world. Now-a-days it is detected in the early age people. So brain tumor treatment has been a challenge to medical science. . If it is detected at an early stage than the chances of saving a life are increased. In this work the proposed strategy to detect and extraction of human brain tumor from patient's Magnetic Resonance Imaging (MRI) scan images of the brain. The essential steps of this paper are image preprocessing, segmentation and feature extraction. First of all, consider MR images of brain tumor as input and convert to gray scale images. The images were filtered by low pass filter for noise removal. Then..........

Keywords: brain tumor, segmentation, magnetic resonance imaging (MRI).

[1]. W. Gonzalez, "Digital Image Processing", 2nd ed. Prentice Hall, Year of Publication 2008, Page no 378
[2]. S. Murugavalli, V. Rajamani, "A high speed parallel fuzzy c-mean algorithm for brain tumour segmentation"," BIME Journal", Vol. no: 06, Issue (1), Dec., 2006
[3]. Hardik Modi, Neha Baraiya, Himanshu Patel. An Efficacious Graphical User Interface Implementation for Automatic Classification of Brain Tumor from Magnetic Resonance Imaging Images Using Image Processing
[4]. Rajesh C. Patil, Dr. A. S. Bhalchandra. Brain Tumour Extraction from MRI Images Using MATLAB
[5]. Yogita Sharma, Parminder Kaur. Detection and Extraction of Brain Tumor from MRI Images Using K-Means Clustering and Watershed Algorithms

Abstract: Biometric authentication has been incredibly useful in services such as access control to authenticate individuals based on their biometric traits. Unlike password or identity documents, biometric traits, such as fingerprint, iris and behavioral characteristic are physically linked to an individual that cannot be easily manipulated. The traditional biometric authentication model uses a server-centric model, where a service provider maintains the biometric database and is totally responsible for the security of templates. The end-users have to fully trust the provider in storing, processing and managing their private templates. As a result the end-user templates could be compromised by outside attackers or even the service provider itself. As a result we propose a user-centric biometric authentication scheme that enables end users to encrypt their own templates with our proposed lightweight encryption scheme at the time of authentication

Key Words: User centric model, Biometric Authentication, Encryption, Decryption, AES Algorithm

[1]. Author A.k. Jain Nandakumar and A. Ross "50 years of biometric research : Accomplishments,challeges,and opportunities." Pattern Recognition Letters Vol.79 pp. 80-105.Elsevier 2016.
[2]. A.K. Jain and K .Nandakumar, "Biometric Authentication : System Security User Privacy." IEEE Computer . Vol 45 no .11. pp 87-91. IEEE 2012.
[3]. S.Rane, Y.Wang S.C. Draper , and P.Ishwar , "Secure biometric : concepts ,authentication architecture , and challenges," IEEE signal processing Magazine vol. 30. No. 51-64 , IEEE 2013.
[4]. M. Naehrig, K. Lauter, and V. Vaikuntnathan, "Can homomorphic encryption be practical?." in proceedings of the 3rd ACM workshop on Cloud Computing Security Workshop, pp 113-124, ACM, 2011.
[5]. J. Katz, A. Sahai, and B. Waters, "Predicate encryption supporting disjunction, polynomial equations, and inner products." In Advances in Cryptology-EUROCRYPT 2008, pp. 457-473, Springer, 2009...

Abstract: In this process, mobile device and service are nowadays improved our learning capacity is highly enhanced. This technology growth and learning methods are very highly improved. At that time, some activities and learning capacity features are lagging to improve our knowledge. Children are most interested to use the mobile device. When due to the rapid growth of technology the teaching and learning system is totally different and also the formal teaching method is changed from mobile device. The teaching method for Tamil language system is lagging to know the children via the mobile device.so, this application is helpful to.........

Key Words: Android Studio, Android Application, Pre and Primary Children, Tamil Language

[1]. Nur Sauri Yahaga, "Mobile Learing Application for Children: Belajar Bersama Dino", Elsevier, The International Conference on Communication and Media, (2014) October.
[2]. Olisah Kingsley S and Mohamed Ismail Z, "Web Based E- learning System for Pre-school Kids", International Journal of Information Syatem and Engineering, Research Paper,Vol. 3,no.1. (2015) January, pp. 213-232.
[3]. Radoslava Kraleva, Velin Kralev,"A Conceptual Design of Mobile Learning Applications for Preschool Children ",International Journal of Computer Science and Information Security, Vol. 14, No. 5, May(2016).
[4]. Celal OZTURK, "An M-Learning Tool for Pre-school kids", Computer Engineering Department, Conference Paper,(2015) April.
[5]. Georgia K. Kokkalia and Athanasios S. Drigas, "Mobile Learning for Special Preschool Education", International Journal of Interactive Mobile Technologies, ResearchGate,Vol. 10, (2016) January, pp. 67-74....

Abstract: Malware is any type of program that is intended to wreak havoc to the computer system and network. Examples of malware are bot, ransomware, adware, keyloggers, viruses, trojan horses, worms and others. The exponential growth of malware is posing a great danger to the security of confidential information. The problem with many of the existing classification algorithms is their low performance in term of their ability to detect and prevent malware from infecting the computer system. There is an urgent need to evaluate the performance of the existing Machine Learning classification.........

Key Words: Malware, classification algorithms, Random Forest, AdaBoost, Bagging, Naïve Bayes

[1]. Sanjay Chakrabortya and Lopamudra Dey. A rule-based probabilistic technique for malware code detection. Multiagent and Grid Systems – An International Journal, IOS Press, 12, 2016, pp. 271–286 271. DOI 10.3233/MGS-160254
[2]. Y. Zhou, Z. Wang, W. Zhou, and X. Jiang. Hey, you, get off of my market: Detecting malicious apps in official and alternative android markets. in NDSS, vol. 25, no. 4, 2012, pp. 50–52.
[3]. D. Keragala. Detecting malware and sandbox evasion techniques, SANS Institute InfoSec Reading Room, 2016. URL: https://www.sans.org/reading-room/whitepapers/ forensics/detecting-malware-sandbox-evasion-techniques-36667.
[4]. Sharif, M., Yegneswaran, V., Saidi, H., Porras, P., and Lee, W. Eureka: A framework for enabling static malware analysis. In Computer security-ESORICS 2008, pages 481- 500. Springer.
[5]. Moser, A., Kruegel, C., and Kirda, E. Limits of static analysis for malware detection. In Computer security applications conference, ACSAC 2007. Twenty-third annual, 2007, pages 421-430...

Abstract: The declining rate of student graduation in today's higher institutions of learning has become a major source of concern to educational authorities, school administration and parents. While school administrators are trying to increase the rate of graduation, students are dropping out at an alarming rate. The ability to correctly predict student's graduation time after admission into graduate program is critical for educational institutions because it allows for developing strategic programs that will aid or improve students' performances towards graduating on time (GOT)..........

Key Words: Prediction, Artificial neural networks, Graduation on Time.

[1]. Ismail, F.B. and A. Marwan, Advance Intelligent Performance' Prediction System.
[2]. Karamouzis, S.T. and A. Vrettos. An artificial neural network for predicting student graduation outcomes. in Proceedings of the World Congress on Engineering and Computer Science. 2008. Citeseer.
[3]. Vandamme, J.P., N. Meskens, and J.F. Superby, Predicting academic performance by data mining methods. Education Economics, 2007. 15(4): p. 405-419.
[4]. Miñano, P., R. Gilar-Corbi, and J.L. Castejón, A structural model of cognitive-motivational variables as explanatory factors of academic achievement in Spanish language and mathematics. 2012.
[5]. Shahiri, A.M. and W. Husain, A review on predicting student's performance using data mining techniques. Procedia Computer Science, 2015. 72: p. 414-422...

Abstract: The sentiment discourse (i.e. responses and replay) on the social Network sites such as, Facebook, Twitter, YouTube, Forums, etc., forms the outbreaks of ample of opinionated thread chains. To get a complete message, every single opinionated text under these chains has to be seen interdependently. However, it is problematic to get a complete message from such threaded opinion chains, solely by applying the state-of-the-art computational linguistic techniques being utilized under opinion mining. In this paper, an opinion-oriented graph-based summarizing model from an opinionated discourse text of social network site is proposed. The major novelty of this paper is the use of back-trace enabled rule based opinion-oriented graph approach. Experiments are conducted and..........

Key Words: back-tracing; discourse; opinion oriented-graph; social network; thread

[1]. A. Ahmad. "Is Twitter a useful tool for journalists?" Journal of Media Practice, vol. 11, no.2, pp. 145–155,2010
[2]. A. Ahmad. "Whats in a tweet?" foreign correspondents use of social media. Journalism Practice, vol. 7, no. 1 pp. 33–46,2013
[3]. M. L. Sheffer and B. Schultz. Paradigm shift or passing fad? twitter and sports journalism. International Journal of Sports Communication, vol.3, no. 4, pp. 472–484,2010
[4]. Lucia C. Passaro, Alessandro Bondielli and Alessandro Lenci, "A Topic-Annotated Facebook Corpus for Emotion Detection and Sentiment Analysis",2015
[5]. Márton, "Beyond Sentiment: Social Psychological Analysis of Political Facebook Comments in Hungary", 2015..

Abstract: The best brands know that staying on top of the whole sale process is serious to closing the deal. But how can you keep on top of your sales process if you do not participate every step of the way. Product distribution place is an important step that is often overlooked where brands choose the least or easiest option instead of developing a legitimate distribution strategy. In this paper, we will tell you everything you need to know about product distribution places, ranging from different distribution strategies to who is responsible in the business, so you can improve your distribution strategy to achieve the highest performance on the shelf. Our strategies going to focus on the customer's eyes moving during the shopping occur for three categories children, adults and elders..

Key Words: Data Mining, analysis criteria, Eye Movementanalytics, Technology for Data Mining Analytics

[1]. Role of Data mining in analyzing consumer's online buying behavior, International Journal of Business and Management Invention ISSN (Online): 2319 –8028, ISSN (Print): 2319 –801Xwww.ijbmi.org || Volume 6 Issue 11 || November. 2017 || PP—45-51, https://www.ijbmi.org/papers/Vol(6)11/Version-3/G0611034551.pdf
[2]. https://www.123rf.com/photo_12640668_little-boy-sitting-alone-on-hunkers-in-big
[3]. https://www.klipfolio.com/blog/sales-analytics-12-metrics
[4]. https://www.scienceofpeople.com/read-people-eyes/
[5]. https://www.slideshare.net/Keyesscientist/consumer-behavior-research-of-carrefour-uae-dubai.

Abstract: Over few years, Cloud Radio Access Network (C-RAN) is proposed as architectonics for 5G cellular networks that brings the adaptability and activity of wireless communications. With the amazing advance in adaptable cartage and services, it is virtualization technology to the cloud accretion based radio admission networks for accomplishing top ashen ability with low cost. In this paper, the virtualization technologies in CCRANs are surveyed, including the arrangement architecture, key enabling techniques, challenges, and accessible issues Adaptable casework accept become capital allotment in the era of 5G networks. The adaptable arrangement will be based on cloud computing, IoT, user-centric services, and adaptable communication. Cloud account is all-..........

[1]. A.Cisco, "Cisco beheld networking index: Anticipation and methodology, 2011–2016," CISCO White paper, 2012.
[2]. D. Pompili, A. Hajisami, and T. X. Tran, "Elastic ability appliance framework for top accommodation and activity ability in Cloud RAN," IEEE Commun. Mag., vol. 54, no. 1, pp. 26–32, 2016.
[3]. T. X. Tran and D. Pompili, "Dynamic Radio Cooperation for User-Centric Cloud-RAN with Accretion Ability Sharing," IEEE Trans. on Wireless Commun., 2017, to appear.
[4]. M. Peng, Y. Li, Z. Zhao, and C. Wang, "System architectonics and key technologies for 5G amalgamate cloud radio admission networks," IEEE Network, vol. 29, no. 2, pp. 6-14, Mar. 2015. doi: 10.1109/MNET.2015.7064897.
[5]. M. Peng and W. Wang, "Technologies and standards for TDSCDMA evolutions to IMT Advanced," IEEE Communications Magazine, vol. 47, no. 12, pp. 50-58, Dec. 2009. doi: 10.1109/MCOM.2009.5350368.

Abstract: Human life is in danger due to human activities and natural disaster. Disaster is a one type of event which effects human life in terms of life and wealth like 6500 people died in 2017 in Asian continent due to 200 disaster and also billion dollars economic loses. But, no one can avoid disaster until we live on the lap of nature. We can only minimize the loss of life and economic losses by using scientific based proper plan with the help of computer, information communication technology (ICT) and Artificial Intelligence. All most all private and government agencies like Indian Meteorological department (IMD), National remote sensing agency (NRSA), The Central water commission.......

Keywords: ICT, GIS, RS, AI, human life, economic loses etc.

[1]. http://www.habitat.org/lc/TheForum/english/pdf/Forum_Vol19_1.pdf
[2]. http://restoreyoureconomy.org/disaster-overview/phases-of-disaster/
[3]. http://www.undp.org/content/dam/india/docs/hazaras_disasters_and_your_community_a_primer_for_parliamentarians.pdf
[4]. http://www3.weforum.org/docs/Harnessing_Artificial_Intelligence_for_the_Earth_report_2018.pdf
[5]. https://www.indiatoday.in/india/story/india-lost-80-bn-due-to-disasters-in-last-20-years-un-report 1366521-2018-10-11

Abstract: In the computing scene, cyber security is going through enormous changes in technology and its operations of late, and data science is driving the change. Removing security event models or pieces of information from cyber security data and building looking at data-driven model, is the best approach to make a security system modernized and insightful. To fathom and analyze the genuine wonders with data, diverse intelligent methodologies, machine learning strategies, cycles and systems are used, which is routinely known as data science. In this paper, we study cyber security data science, where the data is being gathered from critical cyber security sources, and the investigation features the latest data-driven models for giving seriously convincing security courses of action. The possibility of cyber security data science licenses making the computing collaboration more critical and vigilant when stood out from customary ones in the space of cyber security.

Keywords: Computing, Data, Security.

[1]. Alexa top sites. Retrieved April 14, 2016 from http://www.alexa.com/topsites.
[2]. Geoip lookup service. Retrieved April 14, 2016 from http://geoip.com/.
[3]. D. Bekerman. Network features. Retrieved April 14, 2016 from http://www.ise.bgu.ac.il/dima/network traffic features set.pdf.
[4]. D. Bekerman, B. Shapira, L. Rokach, and A. Bar. Unknown malware detection using network traffic classification. In Proc. of IEEE Conference on Communications and Network Security (CNS), 2015.
[5]. V. Brik, S. Banerjee, M. Gruteser, and S. Oh. Wireless device identification with radiometric signatures. In Proc. of ACM conference on Mobile computing and networking, 2012

Abstract: Fairchild semiconductors (established in 1957) imagined the primary Integrated Circuit in 1959 that denoted the microprocessor history. In 1968, Gordan Moore, Robert Noyce, and Andrew Forest left the Reasonable kid semiconductors and began their own organization: Integrated Gadgets (Intel). In 1971, the main microprocessor Intel 4004 was imagined. A microprocessor is otherwise called a central processing unit in which quantities of peripherals' are manufactured on a solitary chip. It has ALU (arithmetic and logic unit), a control unit, registers, bus systems, and a clock to perform computational errands. This article discusses an overview of microprocessor history and its generations.

Keywords: Processor, CPU, Generation, Chip

[1]. Hewlett-Packard Development Company. AMD Opteron and Intel Xeon x86 for CPUs. 21st Euromicro International Conference on Parallel, Distributed, and processors in industry- standard servers. Technology 2012.
[2]. Kamanashis B. & Ashraful Md. I., "Hardware Virtualization Support in Intel, AMD And IBM Power Processors. (IJCSIS) International Journal of Computer Science and Information Security Vol. 4, No. 1 & 2, 2014
[3]. Weng, Ning, and Tilman Wolf. "Pipelining vs. multiprocessors choosing the right network processor system topology." Proc. of Advanced Networking and Communications Hardware Workshop (ANCHOR 2014) 2014.
[4]. Jing Fu and Hagsand, Olof, " Designing and Evaluating Network Processor Applications, IEEE Workshop on High Performance Switching and Routing: Hong Kong, PEOPLES R CHINA, MAY 12-14, 2015, 2015, 142-146
[5]. Crowley, Patrick "Characterizing processor architectures for programmable network interfaces.", ACM International Conference on Supercomputing 25th Anniversary Volume. 2014.

Abstract: Presently, it has become relatively easy to gather feedback from farmers through micro-blogging websites. Over the years, a trend has emerged where individuals proficient in multiple languages often switch between them to express themselves on social media platforms. In this study, the authors have collected comments related to agriculture that exhibit code-mixing, specifically incorporating Hindi content. They performed language identification, normalization, and created a Hindi code-mixed dictionary. They subsequently tested various models trained on Hindi code-mixed data using LSTM, CNN and Naive Bayes techniques for sentiment analysis, finding improved results with their implemented model......

Keywords: Sentiment Analysis, Hindi, LSTM, Naive Bayes, CNN, Agriculture.

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