May - 2019 (Volume-9 ~ Issue-5 ~ Series-11)

Paper Type :: Research Paper
Title :: Evaluating Performance of Neural Networks for load Forecasting in IoT
Country :: India
Authors :: Manisha Gaidhane || Ms. Mona Mulchandani || Ms. Priyanka Dudhe
Page No. :: 01-06

Load forecasting is an area of data prediction which uses short term memory models in order to predict an even shorter term data. Usually the extent of forecasting is not more than 2 to 4 weeks at maximum, due to the fact that the amount of load increasing due to an increase in number of household connections is exponential. Thereby researchers usually follow models like neural networks, linear classification, naive bayes, support vector machines and others to predict the load. In this paper, we evaluate the performance of load forecasting using neural network predictor which uses a non-auto regression network or NARNET, and takes into consideration the previous values of the current load values to predict the next load values. The performance evaluation is done on different network configurations, and the results are observed to conclude the best possible configuration for the given load data..

Key words: Load, prediction, neural, configurations

[1]. S. Ruzic, A.Vuckovic, and N. Nikolic, "Climate Sensitive Method for Short-Term Load Forecasting in Electric Power Utility of Serbia", IEEE Transaction on Power Systems, 18:1581– 1586, 200
[2]. D.C. Park, M.A. El-Sharkawi, R.J. Imprints II, L.E. Map book and M.J. Damborg,"Electric load determining utilizing a counterfeit neural system", IEEE Transactions on Power Engineeringvol.6,pp.442-449(1991)
[3]. T. Haida and S. Muto, "Relapse Based Peak Load Forecasting utilizing TransformationTechnique". IEEE Transactions on Power Systems, 9:1788– 1794, 1994.
[4]. Short term load determining utilizing time arrangement displaying with pinnacle load estimation ability", IEEE Transactions on Power Systems, Vol.16, No.3 August 2001
[5]. Mohamed Mohandes, Support vector machines for momentary electrical burden anticipating INTERNATIONAL JOURNAL OF ENERGY RESEARCH Int. J. Vitality Res. 2002;26:335}345(DOI:10.1002/er.787)

Paper Type :: Research Paper
Title :: Mobile Mapping Application for E-land Information
Country :: India
Authors :: Meghana Madhukar Gayakwad || Dr. Sachin Choudhari || Monali Gulhane
Page No. :: 07-11

Mobile phone has permanently transformed the socio economic strata of the society. Mobile phone has allowed a lot of application to be developed and implemented for the benefit of the society. The smart phones have opened a plethora of opportunities and one such area is the land office which caters to provide and regulate the details of land, its sale and purchase etc. A mobile application can be developed which allows the smart phone user to obtain the land record and the details of the owner's that to at the touch of the finger Mobile gadget with android operating system has a locationbased feature that is useful to provide information displayed in a map.E-Land mobile application which aims to simplify the Land.............

Key words: Android, Global position system (GPS), Google Maps. Mobile E-land application

[1]. Vikky, EkoSediyono and AdiSetiawan. "Analysis ofLand Area Caltulation Using of GPS Technology. ", Vol. 9, No. 1, Juli 2017[ 978-1-5090-1648-8/16/$31.00 ©2016 IEEE]
[2]. Kanwalvir Singh , Himanshu Aggarwal Journal of Software Engineering and Applications, 2013, 6,221228 Online April 2013 ( [3]. Rafialy, Leonardo and Sediyono, Eko; Setiawan, Andi, "Pemanfaatan Cloud Computing Dalam GoogleMaps untuk Pemetaan,Informasi,AlihFungsi,LahandiKabupaten,MinahasaTenggara", Seminar NasionalTeknologiInformasi, 2013, pp.52-58
[4]. Sendow, T.K and Longdong, Jefferson. "The Study Mapping ( city case study Manado )". Scientific Journal Media Engineering Vol.2, Numb.1, pp.35-46, March. 2012.
[5]. D. Bort, "Android Is Now Available as Open Source,"Android Open Source Project.

Paper Type :: Research Paper
Title :: Statistical Analysis on Cloud data for improving access Efficiency
Country :: India
Authors :: Ms. Nikita Ashtankar || Ms. Mona Mulchandani
Page No. :: 12-15

Cloud data is of utmost importance due to it's availability and the number of options available to access this data. But, proper data access is required in order to effectively and efficiently read and write on the cloud, for which researchers have developed many techniques in recent years. These techniques have their own pros and cons, and while some are suited for high speed applications, some others are suited for high security ones. In this paper, we compare some standard techniques for cloud data access, and observe which techniques are suited for which kind of environment and are effective under what access conditions, so that the readers can get a concreteestimate about which kind of data access system to deploy under what circumstances on the cloud. We further propose a technique which can be implemented in order to further improve the data access efficiency of the cloud computing deployment architecture

Keywords: Cloud, data, access, efficiency, effectiveness

[1]. Hu Shuijing," Data security: The difficulties of Cloud Computing",IEEE, 2014.
[2]. Nelson Mimura Gonzalez, Marco Antônio Torrez Rojas, Marcos ViníciusMaciel da Silva, "A system for confirmation and approval certifications in distributed computing", IEEE, 2013.
[3]. B.Rimal et al., "A Taxonomy and Survey of Cloud Computing Systems", International Joint Conference on INC, IMS and IDC, 2009.
[4]. Wei Qiu, Carlisle Adams," Exploring User-to-Role Delegation in RoleBased Access Control", IEEE, 2007.
[5]. Xin Zhou,Xiaofei Tang, "Exploration and Implementation of RSA calculation for Encryption and Decryption", IEEE,2011.

Paper Type :: Research Paper
Title :: An Efficient Cloud based Revocable Identity-Based Encryption in Cloud Data Security Authentication and Data Sharing
Country :: India
Authors :: Nikita Daudkar || Pranjal Dhore || Nisha Balani
Page No. :: 16-22

With the rapid development of network bandwidth, the volume of user's data is rising geometrically. User's requirement cannot be satisfied by the capacity of local machine any more. Therefore, people try to find new methods to store their data. Cloud storage is a cloud computing system which provides data storage and management service. With a cluster of applications, network technology and distributed file system technology, cloud storage makes a large number of different storage devices work together coordinately. Nowadays there are a lot of companies providing a variety of cloud storage services, such as Dropbox, Google Drive, iCloud, Amazon Web Services, etc. These companies provide large capacity of storage and various services related to other popular applications, which in turn leads to their success in attracting humorous subscribers. However, cloud storage service still exists a lot of security problems................

Key words: Azure Microsoft Cloud Computing, Cloud Storage, Anonymity

[1]. Azure. (2014) Azure storage service. [Online]. Available:
[2]. Amazon. (2014) Amazon simple storage service (amazon s3). [Online]. Available:
[3]. Shamir, "Identity-based cryptosystems and signature schemes," in Advances in cryptology. Springer, 1985, pp. 47–53.
[4]. G. Anthes, "Security in the cloud," Communications of the ACM, vol. 53, no. 11, pp. 16–18, 2010.
[5]. D. Boneh and M. Franklin, "Identity-based encryption from the weil pairing," SIAM Journal on Computing, vol. 32, no. 3, pp. 586– 615, 2003.

Paper Type :: Research Paper
Title :: Implementing E-assessment using Open CV in ∞Exams
Country :: India
Authors :: Prajakta Pathe || Dr. Sachin Choudhari || Ms. Monali Gulhane
Page No. :: 23-26

This paper features a software system called ∞Exams (Infinity Exams) which supports (primarily in higher education) paper-based examination and makes it easier, more comfortable and speeds up the whole process while keeping every single positive attribute of it but also reducing the number of negative aspects. The approach significantly differs from the ones used in the previous 10+ years which were implemented in such a way that they could not reproduce and replace the traditional paper-based examination model. The heart of the article relies on the most important element of the software which is the image processing flow.The way of conducting testing the knowledge of a person using Multiple Choice Questions (MCQ) has been increased gradually. In Educational industries (like schools and colleges) it is more common now days having tests using multiple choice questions................

Key words: Shortest Path, scale free Network, Secure Routing, Network Simulator.

[1]. Davis, Michelle R. "Online Testing Suffers Setbacks in Multiple States." Education Week 32.30 (2013): 1-18.
[2]. Istvan Vajda, "Computer Aided Teaching of Discrete Mathematics and Linear Algebra", University of Debrecen, PhD Thesis (2012).
[3]. Csink, L., Gyorgy, A., Raincsak, Z., Schmuck, B., Sima, D., Sziklai, Z., & Szoll˝osi, S. "Intelligent assessment systems for elearning." Proc. of the 4-th European Conference on E-Activities, ECOMM-LINE 2003. (2003).
[4]. Gyorgy, A., & Vajda, I. "Intelligent mathematics assessment in eMax." AFRICON 2007. IEEE (2007).
[5]. Sima, D., Schmuck, B., Szoll˝osi, S., & Miklos, A. "Intelligent short text assessment in eMax." Towards intelligent engineering and information technology. Springer Berlin Heidelberg (2009): 435-445. 000304 Á. Tóth et al. • E-assessment using Image Processing in ∞Exams

Paper Type :: Research Paper
Title :: Enhancing the Recognition of Handwritten Scripts Using CNNRNN Hybrid Networks
Country :: India
Authors :: Pranati Paidipati || Dr. Sachin Choudhari || Mr. Ashish Kumbhare
Page No. :: 27-30

Deep learning is the authoritative reach in AI that utilizes neural models inside and out to mirror the elements of human mind, neural systems work in comparable example comprising many concealed layers. Hence, handwritten text recognition is the capacity to transliterate the content info encased in documents or pictures into digital content. The content example can differ from language to language. Handwritten content includes wide set of variations, for instance, couple of dialects have characters disconnected from one another while couple of dialects incorporate cursive organizations. Along these lines, making it profoundly challenging to precisely distinguish transcribed contents...........

Key words: Handwritten Text Recognition, Machine Learning, CNN-RNN networks, Deep Learning, Data Augmentation, Image pre-processing

[1]. Kian Peymani, Mohsen Soryani , From machine generated to handwritten character recognition; a deep learning approach , IEEE 2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA)
[2]. Meiyin Wu, Li Chen, Image recognition based on deep learning, 2015 Chinese Automation Congress
[3]. Mahmoud M. Abu Ghosh, Ashraf Y.Maghari, A comparative Study on Handwritten Digit Recognition using Neural Network, 2017 International Conference on Promising Electronic Technologies.
[4]. Martin Rajnoha, Radim Burget, Malay Kishore Dutta, Handwritten Comenia Script Recognition with Convolutional Neural Network, IEEE 2017 40th International Conference on Telecommunication and Signal Processing.
[5]. T.K Das, Asis Kumar Tripathy and Alekha Kumar Mishra, Optical Character Recognition using Artificial Neural Network, 2017 International Conference on Computer Communication and Information (ICCCI-2017)

Paper Type :: Research Paper
Title :: Use of DNA Computing for Three-Layer Privacy Preserving Cloud Storage Scheme
Country :: India
Authors :: Puransingh Chauhan || Dr. Sachin Chaudhari || Ms. Rana Syeda
Page No. :: 31-36

With the rapid development of network bandwidth, the volume of user's data is rising geometrically. User's requirement cannot be satisfied by the capacity of local machine any more. Therefore, people try to find new methods to store their data. Pursuing more powerful storage capacity, a growing number of users select cloud storage. Storing data on a public cloud server is a trend in the future and the cloud storage technology will become wide spread in a few years. Cloud storage is a cloud computing system which provides data storage and management service. With a cluster of applications, network technology and distributed file system technology, cloud storage makes a large number of different storage devices work together coordinately. Nowadays there are a lot of companies providing a variety of cloud storage services, such as Dropbox, Google Drive, iCloud, Amazon Web Services, etc...........

Key words: UIDAI (Unique Identification Authority of India), Cloud Computing, Cloud Storage, Anonymity

[1]. A.Murugan and R.Thilagavathy," Securing Cloud Data using DNA and Morse code: A Triple Encryption Scheme", International Journal of Control Theory and Applications (IJCTA), vol.10, pp.31-18, Nov 2017.
[2]. Jacob Grasha, and A. Murugan, "A Hybrid Encryption Scheme using DNA Technology" The International Journal of Computer Science and Communication Security (IJCSCS), vol.3 (2), pp.61-65, Feb 2013.
[3]. G. Feng, "A data privacy protection scheme of cloud storage," vol. 14, no. 12, pp. 174–176, 2015

Paper Type :: Research Paper
Title :: Efficient Data Hiding in Encrypted Images Using XORPermutation Method
Country :: India
Authors :: Reysh Chandrikapure || Mr. Pranjal Dhore || Nisha Balani
Page No. :: 37-41

This paper focuses on improvising the quality decrypted images by a classification and permutation method based on separable reversible data hiding in encrypted images. Security of pixel value and its location is the handled by classification permutation encryption in combination with the XOR-encryption. Bits are indiscriminately chosen based on the data-hiding key in the smooth set for embedding further data in the MSB – Most Significant Bit. This paper particularly shows the mid way implementation of the separable reversible data hiding method using XOR and Permutation in images.

Key words: Separable-reversible data hiding, encrypted images, RDH-EI, classification permutation

[1]. F. Huang, J. Huang and Y. Shi, "New framework for reversible data hiding in encrypted domain," IEEE Trans. Inf. Forensics Security, vol. 11, no. 12, pp. 2777-2789, Dec. 2016.
[2]. X. Zhang, "Reversible data hiding in encrypted image," IEEE Signal Process. Lett., vol. 18, no. 4, pp. 255-258, April. 2011.
[3]. W. Hong, T. Chen and H. Wu, "An improved reversible data hiding in encrypted images using side match," IEEE Signal Process. Lett., vol. 19, no. 4, pp. 199-202, April. 2012.
[4]. X. Liao and C. Shu. "Reversible data hiding in encrypted images based on absolute mean difference of neighbouring pixels," J. Vis. Commun. Image Represent., vol. 28, pp. 21-27, 2015.

Paper Type :: Research Paper
Title :: Automating Test Case Creation Using Natural Language Processing
Country :: India
Authors :: Saurabh Mahajann || Ms. Mona Mulchandani || Mr. Samir Ajani
Page No. :: 42-45

In order to point out the defects and errors that were made during the development phases, testing of the any application program is necessary. It's really important to ensure that the application should not result into any failures because it may be very expensive in the future or in the later phases of the development cycle. To test the behavior of the system Quality Analyst constructs a test case on the basis of user story provided or from the Software requirement specification. Similarly a software developer needs to construct the test cases while writing the unit tests. In test driven development test cases are required even before writing a single line of code............

Key words: Natural Language Processing, Test Driven Development, Test Case Generation, Agile Software Development, Software system specification, User Stories

[1] Ahlam Ansari ; Mirza Baig Shagufta ; Ansari Sadaf Fatima ; Shaikh Tehreem , Constructing Test cases using Natural Language Processing ,Third International Conference on Advances in Electrical, Electronics, Information, Communication and Bio- Informatics (AEEICB) 18(2), 2017, 112-116.
[2] W.T. Tsai ; D. Volovik ; T.F. Keefe, Automated test case generation for programs specified by relational algebra queries, IEEE Computer Society's International Computer Software & Applications Conference, 1988
[3] M. Costantino ; R.G. Morgan ; R.J. Collingham ; R. Carigliano , Natural language processing and information extraction: qualitative analysis of financial news articles , Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering (CIFEr), 1997.
[4] Roger Pressman , Software Engineering A Practitioner's Approach 7th Edition , McGraw-Hill, a business unit of The McGraw-Hill Companies, Inc., 1221 Avenue of the Americas, NewYork, NY 10020. Copyright © 2010 by The McGraw-Hill Companies, Inc.
[5] W.J. Book, Modelling design and control of flexible manipulator arms: A tutorial review, Proc. 29th IEEE Conf. on Decision and Control, San Francisco, CA, 1990, 500-506 (8)

Paper Type :: Research Paper
Title :: Sentiment Analysis of Statement
Country :: India
Authors :: Sayali Meshram || Ms. Nisha Balani || Ms. Parul Jha
Page No. :: 46-49

Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. Sentiment analysis is a technology with great practical value; it can solve the phenomenon of network comment information disorderly to a certain extent, and accurate positioning of user information required. Internet has opened the new doors for information exchange and the growth of social media has created unprecedented opportunities for citizens to publicly raise their opinions, but it has serious bottlenecks when it comes to do analysis of these opinions. Even urgency to gain a real time understanding of citizens concerns has grown very rapidly..

Key words: Sentiment analysis, text mining, literature review, Natural Language Processing, Tensor Flow.

[1]. The evolution of sentiment analysis - Mika V. Mäntylä, Daniel Graziotin , MiikkaKuutila (2017)
[2]. Sentiment Analysis of Twitter Data - ApoorvAgarwal, BoyiXie Ilia Vovsha Owen Rambow Rebecca Passonneau, Department of Computer Science, Columbia University, New York
[3]. Research On Sentiment Analysis: The First Decade, Oskar Ahlgren(2015)
[4]. Sentiment analysis: Measuring opinions, Chetashri Bhadanea,Hardi Dalalb, Heenal Doshic, International Conference on Advanced Computing Technologies and Applications (ICACTA-2015)
[5]. A survey on sentiment analysis challenges, Doaa Mohey El-Din Mohamed Hussein, Faculty of Computers and Information, Cairo University, Cairo, Egypt(2016)

Paper Type :: Research Paper
Title :: Language Translation using Predictive Dictionary and Corpus
Country :: India
Authors :: Pinky Gangwani || Prof. Samir Ajani
Page No. :: 50-55

Language is an effective medium of communication. It basically represents the ideas and expressions of human mind. There are more than 5000 languages exist in the world which reflects the linguistic diversity. It is difficult for an individual to know and understand all the languages of the world. Hence, the methodology of language translation (LT) was adopted to communicate the messages from one language to another language. Several online translation tools are now available which support translation of text into one or more languages such as Bing Translator of Microsoft, Google Translate from Google etc. Language Translation (LT) is one of the most important applications and research tasks of NLP which investigates the use
of software to translate text or speech from one natural language to another natural language using computers with or without human assistance..........

Key words: Language Translation (LT), Natural Language Processing (NLP), Dictionary, Phrases, Proverbs, Parts of speech, Translation.

[1] Nirmala Chawla and Bharati Batheja, "Sindhi Devnagri", 2019, pp. 50-52.
[2] Nadeem Jadoon Khan, Waqas Anwar & Nadir Durrani, "Machine Translation Approaches and Survey for Indian Languages", 2017.
[3] ALPAC "Language and Machines: Computers in Translation and Linguistics". A report by the Automatic Language Processing Advisory Committee (Tech. Rep. No. Publication 1416), 2101 Constitution Avenue, Washington D.C., 20418 USA: National Academy of Sciences, National Research Council, 1966.
[4] Balajapally, P., Bandaru, P., Ganapathiraju, M., Balakrishnan, N., & Reddy, R., "Multilingual Book Reader: Transliteration, Wordto- Word Translation and Full-text Translation", 2006.
[5] Dwivedi, S. K., & Sukhadeve, P. P., "Machine Translation System in Indian Perspectives", Journal of Computer Science, 6(10), 1111-1116, 2010.

Paper Type :: Research Paper
Title :: Application of Machine Learning For Survival Analysis- A Review
Country :: India
Authors :: Mrs. R.A.Fadnavis
Page No. :: 56-60

There is exponential growth in data over the last decade. Due to the advancements in various data acquisition and storage technologies, different disciplines have attained the ability to not only accumulate a wide variety of data but also to monitor observations over longer time periods. In many real-world applications, the primary objective of monitoring these observations is to estimate when a particular event of interest will occur in the future. Survival analysis is a model for time until a certain "event.".Time-to-event data encounters several research challenges such as censoring , instance/feature correlations, high-dimensionality, temporal dependencies, and difficulty in acquiring sufficient event data in a reasonable amount of time. The machine learning techniques are being used recently to develop more sophisticated and effective algorithms that either complement or compete with the traditional statistical methods in survival analysis.This paper proposes overview of fundamental and state of art techniques used for survival analysis.

Key words: Survival data; censoring; survival analysis; machine learning, statistical methods

[1]. Kan Ren, Jiarui Qin, Lei Zheng, Zhengyu Yang,Weinan Zhang, Lin Qiu, Yong Yu "Deep Recurrent Survival Analysis" Copyright c 2019, Association for the Advancement of Artificial Intelligence (
[2]. Changhee Lee, William R. Zame, Jinsung Yoon, Mihaela van der Schaar ,DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks", Copyright 2018, Association for the Advancement of Artificial Intelligence
[3]. Stephane Fotso," Deep Neural Networks for Survival Analysis Based on a Multi-Task Framework", arXiv:1801.05512v1 [stat.ML] 17 Jan 2018
[4]. Alaa, A. M., and van der Schaar, M. 2017." Deep multi-task gaussian processes for survival analysis with competing risks" In Proceedings of the 30th Conference on Neural Information Processing Systems (NIPS 2017).
[5]. Ping Wang, Yan Li, Chandan K. Reddy "Machine Learning for Survival Analysis: A Survey, ACM Computing Surveys, Vol. 1, No. 1, Article 1, Publication date: March 2017.

Paper Type :: Research Paper
Title :: Trust-Level Security Based Authentication In Health Data Integration
Country :: India
Authors :: Varsha Katiwal || Ms. Nisha Balani || Ms. Priyanka Dudhe
Page No. :: 61-66

We are requires various health data domains the incorporation of healthcare data from diversified sources. Maintaining record linkage during the integration of medical data is an important research issue. we have given different solutions to this problem that are applicable for developed countries where electronic health record of patients are maintained with identifiers like social security number (SSN), universal patient identifier (UPI), health insurance number, etc. These process cannot be used correctly for record linkage of health data of developing countries because of missing data, ambiguity in patient identification, and high amount of noise in patient data information...........

Key words: Data Security; Health Data Warehouse; Privacy Preserved Record Linkage; Data Mining.

[1]T.R. Sahama, and P.R Croll, ―A Data Warehouse Architecture for Clinical Data Warehousing,‖ Australasian Workshop on Health Knowledge Management and Discovery, 2007.
[2] J. H. Weber-Jahnke & C. Obry ―Protecting privacy during peer-to-peer exchange of medical documents‖, Inf Syst Front (2012), Springer, 14:87–104
[3] H.C. Kum, A. Krishnamurthy, A. Machanavajjhala et. at., ―Privacy preserving interactive record linkage (PPIRL), ‖ J Am Med Inform Assoc vol. 21, 2014, pp. 212–220.
[4] J. Liang, L. Chen, and S. Mehrotra, ―Efficient Record Linkage in Large Data Sets,‖ In Proc. of the Eighth International Conference on Database Systems for Advanced Applications, 2003.
[5] Your medical record is worth more to hackers than your credit card.

Paper Type :: Research Paper
Title :: Secure Authentication For Data Protection Using color schemes (In cloud computing)
Country :: India
Authors :: Gulafshan Shaikh Hasan || Mr. Pranjal Dhore || Ms. Monali Gulhane
Page No. :: 67-70

Due increase in the usage of cloud based systems there is an increase in the amount of information on the cloud and as a result there is need for confidentiality. Most common method used for authentication is textual password. But these passwords are susceptible to shoulder surfing, dictionary attack, eavesdropping. Generally the passwords tend to follow patterns that are easier for attackers to guess. A literature survey shows that text-based password suffer this security problem. Pictographic passwords are provided as replacement to text based passwords. Pictographic passwords may prone to shoulder surfing. Pictographic passwords may suffer with the usability issue. This paper uses color code authentication which provides two step authentication to the user. Each time user logged in with generated one time password........

Key words: Authentication; Cloud; Challenge response; Graphical password; Pictographic; Textual password.

[1]. Morris, Robert, and Ken Thompson. "Password security: A case history." Communications of the ACM 22.11 (1979): 594-597.
[2]. Blonder, G. "United States Patent 5559961." Graphical Passwords (1996).
[3]. Man, Shushuang, Dawei Hong, and Manton M. Matthews. "A Shoulder Surfing Resistant Graphical Password Scheme-WIW." Security and Management. 2003.
[4]. Wiedenbeck, Susan, et al. "PassPoints: Design and longitudinal evaluation of a graphical password system." International Journal of Human-Computer Studies 63.1 (2005): 102-127.
[5]. Thorpe, Julie, and Paul C. van Oorschot. "Graphical Dictionaries and the Memorable Space of Graphical Passwords." USENIX Security Symposium. 2004.

Paper Type :: Research Paper
Title :: Recognition of Plastic Surgical Faces Using Probabilistic Approach: A Survey
Country :: India
Authors :: Kalyani Khobragade || Roshni Khedgaokar
Page No. :: 71-75

Face Recognition is one of the key area of research. Face recognition is challenging due to the wide variety of faces with various condition like aging, pose variation, facial expression, and illumination problem. Plastic surgery, on the other hand is considered as a biggest challenge in face recognition. In this paper, the review of face recognition using different probabilistic approach is presented, where a probabilistic approach like Naïve Bayes classifier is used to recognize the faces with plastic surgery and Expectation Maximization Algorithm (EMA) used to approximate the maximum likelihood function. Expectation Maximization Algorithm is combined with Naïve Bayes classifier so that the recognition rate will be improved and face recognition of plastic surgery faces will be effective, other than the above mention algorithm Neural network classifier will also be consider for face recognition

Key words: Probabilistic approach, Naïve Bayes classifier, Expectation Maximization Algorithm (EMA), Neural Network

[1]. E. B. Putranto, P. A. Situmorang and A. S. Girsang, : Face recognition using eigenface with naive Bayes, 11th International Conference on Knowledge, Information and Creativity Support Systems (KICSS), Yogyakarta, pp. 1-4, (2016).
[2]. Naeem, Muhammad & Qureshi, Imran &Azam, Faisal, Face Recognition Techniques and Approaches: A Survey, Science International (Lahore). 27. 301-305 (2015).
[3]. Ripal Patel, NidghiRathod, Ami Shah,: Comparative Analysis of Face Recognition Approaches: A Survey, International Journal of Computer Applictaions (0975-8887), Volume 57, No. 17, November (2012).
[4]. Satonkar S.S.*, Kurhe A.B, : Challenges in Face Recognition: A Review, International Journal of Advanced Resesrch in Computer Science (IJARCS), Volume 2, No. 4, July-August (2011).
[5]. S. Prince, P. Li, Y. Fu, U. Mohammed and J. Elder,: Probabilistic Models for Inference about Identity, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 1, pp. 144-157, Jan. (2012).

Paper Type :: Research Paper
Title :: Segmentation of Liver Organ using Marker Watershed Transform Algorithm for CT Scan Images
Country :: India
Authors :: Nisha Wankhade || Shraddha Sangewar || Dr. Prema Daigavane
Page No. :: 76-80

The Liver is a largest gland in the body. Distinctdiseases affected on the liver. Liver diseases is one of the most serious health problem worldwide. For detecting the liver diseases the Segmentation Technique is essential. Segmentation is used for the classification of liver diseases. The liver diseases are focal or diffused is easily understood by the physician using segmentation. We use CT scan image for segmentation but the noise is present in the image. Therefore preprocessing is applied on the image for the removal of noise. In this paper, Watershed Transform segmentation Algorithm is used because it produce complete division of images in separate region even if contrast is poor. Therefore this method could be achieved 92.1% accuracy.

Key words: Liver Diseases; Preprossesing; Segmenation; Watershed Transform Algorithm

[1] Suhuai Luo, Jesse S. Jin, Stephan K. Chalup, Guoyu Qian, "A Liver Segmentation Algorithm Based on Wavelets and Machine Learning" The University of Newcastle, Australia 978-0-7695-3645-3/09 $25.00 © 2009 IEEE DOI 10.1109/CINC.2009.225.
[2] Nasrul Humaimi Mahmood, Noraishikin Zulkarnain and Nor Saradatul Akmar Zulkifli "Ultrasound Liver Image Enhancement Using Watershed Segmentation Method" International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 3, May-Jun 2012
[3] Niket Amoda1, Ramesh K Kulkarni2 "Image Segmentation and Detection using Watershed Transform and Region Based Image Retrieval" International Journal of Emerging Trends & Technologyin Computer Science (IJETTCS) ISSN 2278-6856 Volume 2, Issue 2,March – April 2013
[4] Gunasundari S , Janakiraman S, "A Study of Textural Analysis Methods for the Diagnosis of Liver Diseases from Abdominal Computed Tomography", International Journal of Computer Applications (0975 – 8887) Volume 74– No.11, July 2013

Paper Type :: Research Paper
Title :: Reduction of Candidate Set Generation for Association Rule Mining using Cardinality Count Technique
Country :: India
Authors :: Shailendra Shende || Sachin Balvir
Page No. :: 81-84

Since the discovery of large item set in a large database is a computationally expensive process, there are two ways to reduce the computational complexity of frequent itemset generation. The first one is by reducing the number of comparisons. Here instead of matching each candidate itemset against every transaction, we can reduce the number of comparisons by using more advanced data structures, either to store the candidate itemset or to compress the data set. Second approach is by reducing the number of candidate itemsets. The Apriori principle is an effective way to eliminate some of the candidate itemsets without counting their support values. In this paper, we propose efficient algorithms to reduce the number of candidate itemsets for finding the frequent itemset, by enhancing the existing Apriori algorithm using static cardinality count method.

Key words: Association Rule Mining, Cardinality, Frequent Itemset.

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