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Editor-in-chief Dr. Hari Vasudevan

Convenor DJ-ASCII

Editors Dr. Abhijit Joshi Co-convenor DJ-ASCII

Dr. Narendra Shekokar Co-convenor DJ-ASCII

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Preface

We are pleased to present the proceedings of the State Level Project Competition DJ ASCII. The competition was organized by department of Computer Engineering and Information Technology of SVKM’s Dwarkadas J. Sanghvi College of Engineering on 1st April, 2017 in Mumbai, India.

The main aim of DJ ASCII was to provide a platform for budding engineering students and researchers from all over Maharashtra to share and demonstrate their innovative ideas in the field of latest technology.

We are very happy to say that DJ ASCII has achieved what it had aimed for by receiving an overwhelming response of total 124 participations, out of which 73 were selected after a rigorous review by our panel of expert reviewers. 61 project groups registered for the competition.

The competition received projects primarily in the domains, which were not limited to, Artificial Intelligence, Computing, Human Computer Interactions, Data Mining and Analytics and Network & Security. The projects were presented and demonstrated by students from various engineering institutes in parallel sessions. Students also had presented their project ideas with technical paper and abstract of those papers are published with ISSN number.

We thank our patrons Shri. Amrish R. Patel (President, SVKM), Shri. Bhupesh R. Patel (Join President, SVKM), Shri. Pravin V. Gandhi (Vice President, SVKM), Shri. Sunandan R. Divatia (Hon. Secretary, SVKM), Shri. Jayant P. Gandhi (Hon. Joint Secretary, SVKM), Shri. Shalin S. Divatia (Hon. Joint Secretary, SVKM), Shri. Utpal H. Bhayani (Hon. Treasurer, SVKM), Shri. Harshad H. Shah (Hon. Joint Treasurer, SVKM), Shri. Harit H. Chitalia (Hon. Joint Treasurer, SVKM) and Shri. Bharat M. Sanghvi (In-charge, DJSCE) for their valuable guidance and support. We are extremely grateful to our Management SVKM for their wholehearted support in organizing DJ ASCII.

We thank the advisory committee for their guidance and inputs throughout the organization of the competition. The review committee was very helpful in providing timely and constructive reviews of the papers. We would also like to thank all the students, who participated and showed active interest throughout the competition.

Finally, we thank our fellow members of Technical and Organizing Committee and our student volunteers for the smooth conduct of the competition. Their sincere efforts and contribution have certainly made a huge impact on the success of this event.

We hope you will have a wonderful experience going through the proceedings.

Thank you very much.

Warm regards and good wishes!

Dr. A.R. Joshi Dr. Hari Vasudevan Dr. N.M. Shekokar Convenor, DJ ASCII Co-convenor, DJ ASCII

Committee

Convener Dr. Hari Vasudevan

Principal

Co-Conveners Dr. A.R. Joshi

Vice-Principal (Acad.) & Head, Department of Information Technology

Dr. N.M. Shekokar Head, Department of Computer Engineering

Advisory Committee

Dr. A.C. Daptardar Vice-Principal (Admin.) Dr. Manali J. Godse Professor and Head, Department of Biomedical Engineering Dr. V. Ramesh Professor and Head, Department of Chemical Engineering Dr. A.A. Deshmukh Professor and Head, Department of Electronics and

Telecommunication Engineering Dr. K.N. Vijay Kumar Professor and Head, Department of Mechanical Engineering Prof. P.S. Joshi Head, Department of Electronics Prof. R.S. Khavekar Training and Placement Officer

Technical and Organizing Committee

Dr. Meera Narvekar Prof. Neepa K. Shah Prof. Kiran Bhoumick Prof. Purva P. Raut Prof. Lakshmi D. Kurup Prof. Arjun K. Jaiswal Prof. Anusha Vegesna Prof. Abhijit Patil Prof. Lynette R. D’mello Prof. Sudhir Bagul Prof. Ameyaa Biwalkar Prof. Chirag Desai Prof. Suchita Rane

Dr. Jyoti Joglekar Prof. Vinaya N. Sawant Prof. Harish G. Narula Prof. Khushali P. Deulkar Prof. Harshal D. Dalvi Prof. Chetashri S. Bhadane Prof. Pranjali S. Thakre Prof. Stevina Correia Prof. Pranit Bari Prof. Pankaj Sonawane Prof. Priya Lande Prof. Jennifer Selvaraj Prof. Amruta Patil

Dr. Ram Mangrulkar Prof. Aruna U. Gawade Prof. Kriti Srivastava Prof. Neha A. Katre Prof. Ashok P. Patade Prof. Ruhina B. Karani Prof. Sindhu S. Nir Prof. Mitchell R. D’silva Prof. Deepika Dongre Prof. Pratik Kanani Prof. Nancy Nadar Prof. Dinesh Tharwani

Project Reviewers’ Committee

Mr. Nimish Somaiya Dr. Amiya Tripathi

Ms. Rajashri Rajadhakshya Mr. Sachin Kadam

[vii]

Contents

Preface v Committees vi

1. AEGIS (An Efficient Generic Intelligent System) Harsh Maheshwari, Bansari Kothari, Hardik Jain and Sindhu Nair 1

2. Probability of Plant’s Water Requirement Krusha Doshi, Meghna Jain, Twinkle Pandya and Harish Narula 1

3. A Retrieval Based Neural Conversational Model Chirag Jain, Monik Pamecha and Kiran Bhowmick 2

4. Classification of Accents of English Speakers Kejal Jhaveri, Bhavin Baxi, Karan Nisar and Meera Narvekar 2

5. Object Recognition in an Image Bhavya Shah, Akash Shah and Bhaveen Patel 3

6. Playing Atari Games using Deep Reinforcement Learning Bansi Shah and Drashti Turakhia 3

7. Analyzing Behavioral Attributes of Drivers and Implementing Safe Driving Model Vaibhav Dave, Aditya B. and Yash Panchamia 4

8. Enhanced Sentiment Analysis of Twitter Data Akash Parekh, Sagar Parekh and Kinjal Sanghavi 4

9. Anaphora Resolution in English Text Malabika Sen, Neeti Shah and Lakshmi Kurup 5

10. Solving Medicine Delivery Problems using Blockchain with IoT Fatema Olia, Ilina Gupta, Rachel Menezes and Aruna Gawade 5

11. Segregation of Plastics and Metals from Waste Sample Raj Sadaye, Venkatesh Wagh and Yash Vora 6

12. WALKMATE-A Navigation and Obstacle Detection Aid for the Blind Shivani Bhat, L. Sowmyasree, Chirag Dixit and Harishkandan Somasundaram 6

13. Standalone Device for Home Automation and Personalized Recommendation Sameer Korlahalli, Harsh Parmar, Akshay More and Pranjali Thakre 7

14. A Synopsis of Analytics for a Search Engine Aishwarya Sadasivan, Komal Dhuri, Manaswini Muralidaran and Meghna Mohan 7

15. Providing Personalized Study Material for Learning Disability using Machine Learning Mohit Shah, Meet Shah, Ameya Shirke and Khushali Deulkar 8

16. Document Classification using NLP Payal Jain, Divya Panchal and Abhishek Pandey 8

17. Intelligent Travel Bot using Machine Learning Danish Ali Furniturewala, Sagar Raulo, Siddhant Rele, Neepa Shah and Leena Raut 9

CONTENTS

[viii]

18. Categorization of Wheat Prachi Patel, Aditya Ramnathkar, Hetashavi Shah and Purva Raut 9

19. Automatic Question Generation for E-Learning Systems Riken Shah, Deesha Shah and Lakshmi Kurup 10

20. Interview Bot Vikash Salvi, Adnan Vasanwalla and Niriksha Aute 10

21. Personality Identification using Social Media and its Applications Ria Echhpal, Najeeb Qazi and Rohil Shah 11

22. Sarcasmometer Measuring Sarcasm using Sentiment Analysis and Topic Modeling Namrata Bhan, Janki Joshi, Kena Mehta and Mitchell D’Silva 11

23. Object Recognition and Classification by Image Data Analysis using Machine Learning Algorithm Siddhi Thakkar, Sanket Shah, Niyati Shah and Raj Mehta 12

24. Street Lighting Intensity Controller using Density Mapping Mechanism Rajas Walvalkar, Yogesh Yadav, Abhishek Yedurkar, Sagar Suchak and Swapnil Gharat 12

25. Video Annotation for Active E-Learning Sneha Baviskar, Shamli Dangare, Shruti Gaikwad and Shradhha Gosavi 13

26. Design and Fabrication of Prototype for Automatic Car Parking System using RFID Tagging for Modern Cities (ACPS) Saloji Mohammed, Shaikh Alif, Singh Sudhirkumar and Nabanita Nath Chowdhury 13

27. Treal: Virtual Trial Room using Virtual Reality Rajat Rao, Jinesh Shah and Mayur Chawada 14

28. Smart Cloud Phone Karan A. Shah, Jinay Mehta, Omkar V. Sawant and Laxmi Kurup 14

29. Consumer Credit Default Predictor Yash Poddar, Sanat Shah, Anmol Sheth and Chetashri Bhadane 15

30. Dipriori Yadynesh Desai, Mrunal Medhekar, Disha Mehta and Vinaya Sawant 15

31. Smart Question Paper Generator Jagruti Malani, Shreya Managute, Khushboo Jain and Khushali Deulkar 16

32. Drought Prediction and Management System using Big Data Analytics Benita Jeyakumar, Vinita Rane, Himani Shah, Jayesh Nainani and Nupur Giri 16

33. Prediction and Optimization of Products for Online Sales Shweta Sohani, Neel Shah and Aneri Shah 17

34. Teacher Guardian Log System Abhishek Tiwari 17

35. Duplication Avoidance in Big Data Pravina Vyawahare, Bhavin Bhoi and Pratik Avhad 18

36. Weather Prediction Model: A Data Mining Approach Sudhir Kuwar, Pratiksha Gudme and Manali Band 18

CONTENTS

[ix]

37. Web based Code Testing and Monitoring Engine Adit Shinde, Sushilkumar Takkekar and Ratnesh Dubey 19

38. Graduate Application Evaluation using Machine Learning Varun Kasbekar, Hiral Rayani, Ami Sangani, Neepa Shah, Jemin Jain, Vivek Jain and Srinath Prabhu 19

39. Hybrid Approach to Distributed Document Clustering Varun Kasbekar, Hiral Rayani, Ami Sangani and Neepa Shah 20

40. Agro Analytics: Drought Prediction and Suggestions for Optimal Agricultural Practices Manan Shah, Mihin Sumaria and Mohit Shah 20

41. Portable Book Reader for Visually Impaired Nishi Jain, Mandar Kanade, Harsh R. Mehta and Khushali Deulkar 21

42. VidMute Silence those Annoying Loud Ads Rushabh Dharia and Chirag Jain 21

43. Multiple Object Tracking and Monitoring Shreya Redekar, Nishita Sheth, Nisha Shah and Khushali Deulkar 22

44. MonVoix–An Android Application for Acoustically Challenged People Aishwarya Danoji, Aishwarya Dhage, Rachana Kamat, Priya Puranik and Sharmila Sengupta 22

45. Interpretation of Music Score Sheet to Generate Audio File Bhakti Raichura, Karan Shah and Ronak Thakkar 23

46. Structured Light 3D Scanner (Point Cloud Generation using Triangulation) Kushal Vyas and Ruhina Karani 23

47. Prevention of Accidents While Drunken Driving Kevin Maru, Prathamesh Dongre, Purvi Udhwani and Neha Mundra 24

48. Virtual Try-On of Clothes Aashni Savani, Raj Vastani, Harshal Vora and Ruhina Karani 24

49. Baby Mentor: Learning through Images Jeremy Samuel, Sanket Solanki, Saurabh Patil and Ruhina Karani 25

50. 3D Facial Reconstruction using Skull of a Deceased Person Priya Singh, Lilavati Swamy, Aishwarya Tate and Anam Shah 25

51. Measuring Length of an Infant from its Image using Reference Object and Monitoring Growth Dimpi Dedhia, Nidhi Patel, Kavita Soni, Stevina Correia and Pratik Kanani 26

52. Interactive Learning using Augmented Reality Books Aayushi Vora, Soham Mehta and Pratish Jain 26

53. Reflective Intelligence—An Odroid Based Approach Priti Nalawade, Shraddha Upadhyay, Navin Das and Vijal Jain 27

54. Novel Encryption Technique to Secure Document Data Store Elita Dsouza, Dimpal Jayani, Anuja Patil, Pratik Kanani and Kriti Srivastava 27

CONTENTS

[x]

55. Prevention of Parallel Active Dictionary Attack on WPA2-PSK Wi-Fi Networks Drishti Kakar, Nagendra Kamath, Aneek Guha and N.M. Shekokar 28

56. Design and Overview of a Navigation Application for the Blind Sanjana Panicker, Maitreyi K.V., Merrill Gonsalves, Kane Gonsalves and Sandhya Patil 28

57. Enhancement of Security using Three Level Graphical Authentication Prashant Chiplunkar, Tejal Patil and Sunil Dewoolkar 29

58. Smart Network for Fire Control Heena Tailor, Kashmeera Sawant, Niel Vaishya and Shivani Sherekar 29

59. Puppet Attack and its Detection Manasi Deshmukh, Jash Nichani, Komal Mehta and Aruna Gawde 30

60. Intelligent Ambulance Fleet Management System Monica Chhabria, Latika Wadhwa, Shruti Dhumale and Omkar Patinge 30

61. An Access Control Model for an E-Commerce Business Model using Mongo-DB Khushali Shah, Priyal Shah and Kriti Srivastava 31

AUTHOR INDEX 32

DJ ASCII-17

[1]

PAPER ID: AI02

AEGIS (An Efficient Generic Intelligent System)

Harsh Maheshwari1, Bansari Kothari2, Hardik Jain3 and Prof. Sindhu Nair4

1,2,3,4Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India

E-mail: [email protected], [email protected], [email protected]

AEGIS is an intelligent system that will interactively 1) solve the users query 2) search a piece of information and 3) summarize the most significant information from it. AEGIS has two main components Scrapper and Summarizer. The main concern of extracting information from the web is its structure, thus there is a need for semantic or a systematic way to retrieve and represent relevant data. For finding meaningful information from the discovery patterns in the server web mining is a crucial tool. Web scraping is another method for processing of extracted useful information from HTML pages. It is usually implemented by using a scripting language. The extracted information will then be checked for relevancy. For a text based single document summarization is done on the basis of important information within the document and not generative summarized information. AEGIS will help the user to interact with the PC through voice; also the user will be able to manipulate some hardware settings using voice.

PAPER ID: AI05

Probability of Plant’s Water Requirement

Krusha Doshi1, Meghna Jain2, Twinkle Pandya3 and Prof. Harish Narula4 1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected]

There have been times of acute drought in various regions where agriculture and farming are the main occupations. However, amount of water efficiently used is still questionable. The farmers agree that the plants do not need to be watered on a daily basis. Once in two-three days is the average frequency. However, the exact amount of time required before watering again cannot be properly judged. They need to look for subtle cues and estimate the amount of water required by the plant at that particular stage. This can be fairly inaccurate and can lead to tremendous wastage of water and/or soil erosion. Our main aim is to identify when the plant would require water. This would help novice farmers to make a better estimate and use water judiciously by studying behavioral pattern of the plant to various stimuli such as external temperature, humidity, luminosity, etc. to determine when the plant would need water.

DJ ASCII-17

[2]

PAPER ID: AI06

A Retrieval Based Neural Conversational Model

Chirag Jain1, Monik Pamecha2 and Prof. Kiran Bhowmick3 1,2,3Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India Haptik Infotech Pvt. Ltd., Mumbai, India


In this paper we present an end-to-end retrieval based neural conversational model. Our model replaces the existing rule based approaches used in building conversational bots. We train our network on a large corpus of conversation between users of a personal assistant application and trained agents. Using semantic information from word clusters, we train the conversational model to predict the best match responses from automated cluster messages of responses that have been manually refined.

PAPER ID: AI08

Classification of Accents of English Speakers

Kejal Jhaveri1, Bhavin Baxi2, Karan Nisar3 and Dr. Meera Narvekar4 1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected], [email protected],

[email protected]

One of the most significant topics in automatic speaker and speaker-independent speech recognition systems in recent years is Accent recognition. The growth of voice-controlled technologies has become part of our day to day life, nevertheless variability in speech makes these spoken language technologies relatively difficult. One of the profound variability is accent. By classifying accent types, different models could be developed to handle SI-ASR. Accents can also reveal a lot about a person’s background, such as their native language, place of origin, or ethnic background. Speaker identity verification is also a useful biometric recognition approach. Being able to recognize different type of accents can also improve the quality of speech to text transcription by allowing for specific pre-processing of recordings based on the type of accent. Our goal is to classify various types of accents, specifically foreign accents, according to the native language of the speaker. When a recording of a speaker speaking a known script of English words is given, we would like to predict the speaker’s native language.

DJ ASCII-17

[3]

PAPER ID: AI09

Object Recognition in an Image

Bhavya Shah1, Akash Shah2 and Bhaveen Patel3

1,2,3Department of Information Technology, D.J. Sanghvi College of Engineering, Mumbai, India


The purpose of this project is to build an image classification system that can accurately classify images. For the classification of images, we are using Cifar-10 dataset is a benchmark dataset in image recognition. Particularly we investigated KNN, SVM and CNN of which CNN yields the best result.

PAPER ID: AI10

Playing Atari Games using Deep Reinforcement Learning

Bansi Shah1 and Drashti Turakhia2 1,2Department of Computer Engineering,


Teaching computers to play video games is a complex learning problem that has recently seen increased attention. The project aims to replicate a system that combines deep learning methods and reinforcement learning in order to create a system that is able to learn how to play Atari games on its own. A model free reinforcement methodology named ‘Q-Learning’ is used. Therefore the core algorithm of Deep Reinforcement Learning used is ‘DQN’. DQN incorporated several key features that enabled the power of Deep Neural Networks (DNN) to be combined in a scalable fashion with Reinforcement Learning (RL)—a machine learning framework that prescribes how agents should act in an environment in order to maximize future cumulative reward (e.g., a game score). Foremost among these was a neurobiologically inspired mechanism, termed ‘experience replay’, whereby during the learning phase DQN was trained on samples drawn from a pool of stored episodes. This work offers the demonstration of a general purpose learning agent that can be trained end-to-end to handle a wide variety of challenging tasks, taking in only raw pixels as inputs and transforming these into actions that can be executed in real-time. The system has access only to the visual information i.e. the screen of the game and the scores. Based on these two inputs the system learns to understand which moves are good and which are bad depending on the situation on the screen. The system can be implemented to master several different games and play some of them better than a human player. This result can be seen as a step towards truly intelligent machines and thus it fascinates us. The future goal is to continue to improve the capabilities of these agents to give researchers new ways to make sense of complex large-scale data creating the potential for exciting discoveries.

DJ ASCII-17

[4]

PAPER ID: AI15

Analyzing Behavioral Attributes of Drivers and Implementing Safe Driving Model

Vaibhav Dave1, Aditya B.2 and Yash Panchamia3

1,2,3Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India

E-mail: [email protected]

We have created an embedded system to get the live data stream from the car. The data will highlight the following parameters: (1) Speed of the driver, (2) Proximity with other cars during driving, (3) Turning radius, (4) Acceleration and deceleration values. These parameters are critical to judge the driver for his/ her driving skills and if he/she crosses the permitted limit can be warned or punished for violating the basic rules and regulation of the driving. We propose a solution where in Hidden Markov Models (HMM) are used to categorize and rate a driver's performance based on these parameters. This will help the driver understand and improve his driving technique and will prompt drivers to be more vigilant. Additionally, the solution can be used to detect accidents and collisions by observing the changes in the values of speed and the overall orientation of the vehicle and can then alert nearby authorities to send emergency assistance

PAPER ID: AI16

Enhanced Sentiment Analysis of Twitter Data

Akash Parekh1, Sagar Parekh2 and Kinjal Sanghavi3 1,2,3Fr. Agnel Technical Education, Vashi, Navi Mumbai, India


The advent of the internet and social networking sites such as Facebook, Twitter and Tumblr, has brought a new way of expressing the sentiments of individuals. Global sentiment is a powerful weapon that can be harnessed by the use of Sentiment Analysis techniques. Knowing how the general populace perceives a product or an idea is crucial to the survival of any business. This paper contributes to the sentiment analysis for customers’ review classification which is helpful to analyze the information in the form of the number of tweets where opinions are highly unstructured and are classified into different sentiment classes. This paper aims to perform sentiment analysis beyond the traditional approach of using keywords to determine sentiment polarity and inculcate new techniques for enhancing the accuracy of sentiment analysis like use of emoticons, emotional vectors, popularity of sentence using re tweets.

DJ ASCII-17

[5]

PAPER ID: AI18

Anaphora Resolution in English Text

Malabika Sen1, Neeti Shah2 and Lakshmi Kurup3 UG Student, Assistant Professor,



Chat bots and other interactive applications are not only very trending but also have other important implementations in most of the fields of Natural Language (NLP). Information Extraction from a text, Machine Translation and text summarizations are very complex problems. The system first needs to understand the context in most of these cases. Just like one would wonder what ‘these’ meant by in the previous sentence, many such references are used in everyday language that might cause few words to refer to some other word or phrase. It is easy for humans to interpret what they mean or whom they refer to. But it is not the same case with computers. This problem is known as Anaphora Resolution. We hereby present the proposed methodology in order to solve this problem for an ambiguous language of English.

PAPER ID: AI20

Solving Medicine Delivery Problems using Blockchain with IoT

Fatema Olia1, Ilina Gupta2, Rachel Menezes3 and Prof. Aruna Gawade4 1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected]

This paper describes a safe alternative for monitoring the medicine delivery supply chain. It combines IoT with block chain networks to ensure secure transfer of medicines from manufacturers up to the medicine distributes (e.g.: chemists). It utilises the decentralised nature of the block chain to make sure the data generated cannot be tampered or deleted. It employs a ‘trust-less’ distributed network instead of the existing ‘trust-based’ systems that rely on a central authority to store and validate the data.

DJ ASCII-17

[6]

PAPER ID: AI22

Segregation of Plastics and Metals from Waste Sample

Raj Sadaye1, Venkatesh Wagh2 and Yash Vora3 1,2,3Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected], [email protected]

Waste Disposal has always been a problem in India. By separating wastes into different types we can reuse or recycle some of the waste contents. This project aims at providing an efficacious solution to the problem of segregation of waste. The separation of waste is done based on the output received through various sensors. The proposed system will separate waste into 3 categories Metallic (Re-usable), Plastics and Glass (Recyclable) and other (Passed through without identification) types of waste. Infra-Red sensors can be used to detect the presence of an object within the system. Transparent materials will pass-through this type of light. Inductive sensors can used to detect metallic objects within the waste. Capacitive sensors can be used to detect opaque plastics as well as glass. The system will have a single outlet for dropping the objects. A motor control logic is implemented using the outputs of the sensors the combination of rotation of two motors can be used to separate the waste into different containers. Bipolar stepper motor has been used to implement the separation part. Thus it is a low-cost solution for waste disposal problem.

PAPER ID: AI23

WALKMATE-A Navigation and Obstacle Detection Aid for the Blind

Shivani Bhat1, L. Sowmyasree2, Chirag Dixit3 and Harishkandan Somasundaram4

1,2,3,4Department of Computer Engineering, Vivekanand Education Society's Institute of Technology, Chembur, Mumbai


In an ever growing fast paced world, a disability can be a major setback in a person’s path of progress. Blindness in particular turns even the most rudimentary day to day tasks difficult. While the existing practice of using the white cane or walking stick is commonplace for detection of obstacles/ objects in front of the user, it does not offer any aid in navigation through unknown or new places. On the other hand, devices which aid the visually impaired to navigate do not offer any aid to detect obstacles on the way. Newer technologies available offer a solution to either of the two problems-obstacle detection or navigation-at a high cost that not many could afford. The paper proposes a design for a device which will help them overcome two basic problems visually challenged people face, viz. navigation and obstacle avoidance. The device is a pair of wristbands that when worn on the wrist helps the visually impaired to navigate to the destination through different tactile stimuli. The proposed device is an IoT-based device that will be connected to an android application which will help the person set his path. The hardware module will consist of sensors offering haptic feedback and proximity sensors for obstacle detection. The device will store frequently travelled destinations along with the traversed path for future use.

DJ ASCII-17

[7]

PAPER ID: AI24

Standalone Device for Home Automation and Personalized Recommendation

Sameer Korlahalli1, Harsh Parmar2, Akshay More3 and Prof. Pranjali Thakre4 1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected],

[email protected], [email protected]

Over the years of progress in technology, there have been great paradigm shifts in the way we communicate with devices. In the early stages, it was through physical buttons, then came the revolutionary touch screen, and now speech is fast becoming popular for communication, leading to more and more natural interactions with the device. Voice has been gaining ground as an upcoming mode of communication with the advent of smart assistants in our personal devices such as smartphones. So, one of the practical applications of using this new mode of communication is to automate our home’s appliances with our voice. To extend this application, this ‘home assistant’ can perform web search and give results through voice, and suggest recommendations to the user based on his/her appliance usage and web activity using machine learning. Hence, keeping in mind the increasing use of voice based interaction and also extending the application using machine learning, we are implementing this home automation device.

PAPER ID: AI26

A Synopsis of Analytics for a Search Engine

Aishwarya Sadasivan1, Komal Dhuri2, Manaswini Muralidaran3 and Prof. Meghna Mohan4

1,2,3,4V.E.S.I.T, Chembur, Mumbai–400074 E-mail: [email protected], [email protected],


Our project covers the analytics involved in developing a Search Engine for an E-book portal. The dataset for the same has been extracted from Project Gutenberg. Various front end and back end algorithms have been implemented in order to analyse text. The front end processing includes- Spell Checker, Text Segmentation and Language Modelling. Back end processing includes Similarity Modelling, Clustering and Retrieval of results. The search query entered is processed by the front end algorithms to obtain the most coherent sequence of words in a search query. Subsequently, the backend processing algorithms are executed in order to obtain the similarity between the search query and dataset there by facilitating retrieval of relevant search results. In addition, to visualize the correlations within the dataset we perform clustering.

DJ ASCII-17

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PAPER ID: AI27

Providing Personalized Study Material for Learning Disability using Machine Learning

Mohit Shah1, Meet Shah2, Ameya Shirke3 and Prof. Khushali Deulkar4


E-mail: [email protected], [email protected], [email protected], [email protected]

The objective of the project is to diagnose a child with a learning disability and provide appropriate study material according to his needs. The system is developed with a viewpoint of the intellectual development of an individual suffering from Learning Disability. Earlier the detection of Learning Disability better it is for the student’s growth as a proper remedial therapy can be applied on the student for his intellectual development. The model will first classify a child as learning disabled or not- learning disabled based on certain assessment parameters. Once diagnosed with learning disability, the child is further classified into different types of learning disability like dyslexia, dysgraphia and dyscalculia. The model will also identify the level of Learning Disability and provide the student with study material for improvement. The model is trained using the student’s history and parameters of curriculum-based test to determine the level of Learning Disability. Based on the level of Learning Disability an Individualized Learning Plan will be provided to the children.

PAPER ID: AI29

Document Classification using NLP

Payal Jain1, Divya Panchal2 and Abhishek Pandey3 1,2,3Department of Computer Engineering,


Text Classification is a technique in which an unknown set of documents that are given to the application are classified based on the features (words) that are present in the input document. The very first stage in processing the document is to parse the sentences resent in the document using Natural Language Processing, the sentences are parsed and a syntax tree having the nouns and verbs is made. The document is further parsed using NLP, and taggers (Important words) are generated based on the words extracted in the previous step. In this paper a Fuzzy Similarity Based Concept Mining Model (FSCMM) is proposed to classify an unknown set of documents by preparing on the sentence, document and integrated corpora levels using NLP. The Fuzzy Feature Category Similarity Analyzer (FFCSA) is used to analyze each feature extracted from the Integrated Corpora Feature Vector (ICFV) with the corresponding categories or classes. We will be using Vector Space Model (VSM) to classify the documents using the Term-Frequency and Inverse Document Frequency (IDF, to take into consideration the importance of the words that occur rarely but have a major impact on classification of the document) to make the necessary calculations for the known set of documents and then generate a similarity measure between the documents. The proposed model works efficiently and effectively with high performance and high accuracy results.

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PAPER ID: AI30

Intelligent Travel Bot using Machine Learning

Danish Ali Furniturewala1, Sagar Raulo2, Siddhant Rele3, Prof. Neepa Shah4 and Prof. Leena Raut5 1,2,3,4,5Department of Information Technology,


There are many ways to plan a trip to a destination. The manual way is to book through a travel company, which will give you an itinerary for your tripand the costs involved, another way is to book through an online website, where you can pick a place, look for hotel, book a room and then make travel arrangements to your desired place. The process involved is tedious and involves looking through various booking websites to find the best bang for your buck. We propose a solution which will make this process as smooth as possible through the use of an interactive travel bot deployed on social media platforms. In this travel bot, a user enters a query asking for a place to stay in a location. The travel bot then constructs a person a based on transactional history of the user, for example, hotels that the user has shown interest in previously. Using this persona and our wide and deep network, a personalized recommendation is generated by the system.

PAPER ID: AI31

Categorization of Wheat

Prachi Patel1, Aditya Ramnathkar2, Hetashavi Shah3 and Prof. Purva Raut4 1,2,3,4Department of Information Technology,


Globally, wheat is the leading source of vegetable protein in human food, having a higher protein content than other major cereals, maize or rice. In terms of total production tonnages used for food, India is the second largest producer of wheat in the world. Analysis and Classification of wheat is done visually and manually by human inspectors which is tedious, not accurate and requires an expert judgment. An automated system is introduced which is used for categorization of wheat. The aim of this proposal is to suggest algorithm for identification of wheat using machine learning techniques. This inspection approach based on image analysis and processing has found a variety of different applications in the food industry. This project proposes a model that to identify or recognize the image on the basis of features of wheat grains present in the input image.

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PAPER ID: AI33

Automatic Question Generation for E-Learning Systems

Riken Shah1, Deesha Shah2 and Prof. Lakshmi Kurup3 1,2,3Department Computer Engineering,

D.J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected]

We present a system of automatic MCQs (Multiple Choice Questions) generation in this paper. Given an input text, the system dynamically generates a set of MCQs along with a valid set of distractors. We have used Wikipedia-based dataset, which consists of URLs of Wikipedia articles to train the system. The keywords (important words), which consist of both bigrams and unigrams are extracted and stored in a data structure, along with many other components of the knowledge base. Inverse Document Frequency (IDF) measure is used for ranking the extracted keywords and “Context-Based Similarity’’ approach using Paradigmatic Relation discovery techniques is used for generation of distractors. Also, the runtime execution phase of question generation includes eliminating sentences that start with Discourse Connectives to avoid a question with incomplete information. We have obtained significant accuracy compared to many similar approaches. We observe that results are quite promising considering that there is no human intervention. Especially in MOOCs, the task of automatic question generation can be of quite an importance. It has many applications in Intelligent Tutoring Systems and for self-assessment while learning a new concept. Currently, we have trained our system only for the field of physics, however, due to its generalized nature, it can be extended to any field of study.

PAPER ID: AI34

Interview Bot

Vikash Salvi1, Adnan Vasanwalla2 and Niriksha Aute3 1,2,3Department of Information Technology,


Preparing for Interview is very haptic. It becomes difficult for a person to identify in which skill he/she is lacking and improving that is very important. Interview Bot is an application which helps user to prepare well for the Interview process. Interview Bot mainly focuses on the interview process. User has to provide his/her resume to the bot. Bot will scan the resume and get the information such as skills, marks of various examinations, achievements and certifications, if any, of the user. Bot will perform Text Mining along with NLP on the resume and it will get the intricate details of the user. Once that is done, it scans for the skills and experiences the user has. Accordingly it saves the skills and collects the questions from the database. These questions are asked to user as aptitude test. Crawler is responsible for getting these questions. After crawling, the questions are assigned difficulty level. Based on the user’s level, a set of questions are asked to him/her. User answers questions and after that it displays the score of the user. Based on the user’s answer, difficulty level of question as well as user’s level is updated. Bot then takes the interview of the user, who clears the aptitude test. The bot will be a 3D human model.

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PAPER ID: AI35

Personality Identification using Social Media and its Applications

Ria Echhpal1, Najeeb Qazi2 and Rohil Shah3 1,2,3Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India

Personality of an individual and psychology are widely studied and researched topics. They have primarily dealt with a how a human interacts with his environment, peers and colleagues. His behavior to situations is assessed and based on which, reasonable conclusions about his personality are derived. Twitter is a social media platform, where a user can post what he is thinking in short sentences called “tweets”. These tweets are limited to 140 characters which makes a user to convey his opinions in distinct ways using slang, hashtags and short forms. These specific linguistic features can be used to deduce useful traits of a person. This project would help us know how accurately we can predict a person’s personality using Twitter. Myers-Briggs Type Indicator (MBTI) is a personality test which assigns each person four letter code based on four parameters, thus creating 16 distinct personality types. Analysing the data of users, the expected outcome is to predict accurately the personality. The prediction results of the user’s personality can be used for many applications, such as corporate recruitment, career counselling and even psychological evaluation.

PAPER ID: AI41

Sarcasmometer Measuring Sarcasm using Sentiment Analysis and Topic Modeling

Namrata Bhan1, Janki Joshi2, Kena Mehta3 and Prof. Mitchell D’Silva4 1,2,3,4Department of Information Technology,



Sarcasm is a type of sentiment where the notion that is conveyed is opposite of what it is meant. It is generally used to denote something that is funny or to denote anger or dislike regarding a particular situation. Sarcasm has become a part of our daily lives. It is used in various social networking sites, review posts, entertainment businesses, etc. However, different people have different interpretation of sarcastic texts and this leads to debatable opinions about the product which is being described. Recognizing sarcastic statements can be very useful as it enhances the efficiency of after-sales services or consumer assistance through understanding the intentions and real opinions of consumers when browsing their feedbacks or complaints. In this paper we propose a system that will measure sarcasm using tweets from Twitter. We propose different algorithms to calculate the effect of sarcasm on texts and generate a score. Different features are generated from the received tweets which helps us to generate the score. At the end, we compare the scores from different algorithms to present the most efficient way

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to detect sarcasm. The proposed system also provide a separate portal to check the score of any sentence/text entered by user and determine its score using the most accurate algorithm.

PAPER ID: AI45

Object Recognition and Classification by Image Data Analysis using Machine Learning Algorithm

Siddhi Thakkar1, Sanket Shah2, Niyati Shah3 and Raj Mehta4 1,2,3,4Department of Computer Engineering,

Shah and Anchor Kutchhi Engineering College, Mumbai, India E-mail: [email protected], [email protected],


Digital images are widely used in various applications such as entertainment, security, business purpose, scientific purposes and medical purposes etc. The captured images contain large amount of information. The information in these images are not understandable to the computer system therefore it is extracted by different computer vision methodologies and by optimization techniques for human interpretation. Nowadays there is a major emphasis on extracting information from images. So, some pre-processing enhancement on the image is required which eliminates the noise and prepares the image useful for particular application. In this project work Object recognition and counting number of object of particular class are the main objectives. In the first phase study of different methodologies for recognising the objects of use is done. Various object detection techniques such as morphological operations and Image Segmentation techniques are studied for object recognition. In this project work, in phase I, identifying and extracting of the objects is done. Further these objects will be classified in the classes of interest in phase II. This is performed by using the concepts of Back Propagation Machine Learning Algorithm. Image classification is an important problem for classifying objects of the image under consideration. Various image features are extracted and stored in the database. Further machine learning algorithm such as Back Propagation can be applied for objects classification of different images.

PAPER ID: AI54

Street Lighting Intensity Controller using Density Mapping Mechanism

Rajas Walvalkar1, Yogesh Yadav2, Abhishek Yedurkar3, Sagar Suchak4 and Prof. Swapnil Gharat5

1,2,3,4,5Department of Computer Engineering, Rajiv Gandhi Institute of Technology, Mumbai, India


Object Detection with small computation cost and processing time is a necessity in diverse domains such as: traffic analysis, security cameras, video surveillance etc. With current advances in technology and de-crease in prices of image sensors and video cameras, the resolution of captured images is more than

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1MP and has higher frame rates. Real time video processing with high performance can be achieved with GPU technology. The aim of this study is to evaluate the influence of different image and video resolutions on the processing time, number of objects detections and accuracy of the detected object. MOG2 algorithm is used for processing video input data with GPU module. Fuzzy interference system is used to evaluate the accuracy of number of detected object and to show the difference between CPU and GPU computing methods.

PAPER ID: AI55

Video Annotation for Active E-Learning

Sneha Baviskar1, Shamli Dangare2, Shruti Gaikwad3 and Shradhha Gosavi4

1,2,3,4Department of Computer Engineering E-mail: [email protected], [email protected],


Video annotation functions themselves will be beneficial for students in case of E-Learning or distance learning. The first benefit is the easier browsing of the video lecture. Annotation of video refers to the extraction of the information about video automatically, which can serve as the first step for different data access modalities such as browsing, searching, comparison, and categorization. The use of video lectures in distance learning involves the two major problems of searchability and active user participation. In our project, we will promote the implementation and usage of a collaborative educational video annotation functionality to overcome these two challenges. Different use cases and requirements, as well as details of the implementation, will be explained. We want to indicate not only that students perceive it as useful, but also that the learning effectiveness increases.

PAPER ID: AI56

Design and Fabrication of Prototype for Automatic Car Parking System using RFID Tagging for

Modern Cities (ACPS)

Saloji Mohammed1, Shaikh Alif2, Singh Sudhirkumar3 and Nabanita Nath Chowdhury4

1,2,3,4M.H. Saboo Siddik College of Engineering, Byculla, Mumbai, India

Lack of space availability has always been a problem in urban areas and major cities and to add to it there are cars parked callously on the streets that further limit the space. In order to handle the issue of parking in busy places various types of vehicle parking systems are used worldwide namely Multi-level Automated Car Parking, Automated Car Parking System, Volkswagen Car Parking [1] and many more. The present project work is aimed to develop a reduced working model of a car parking system for parking 6 to 10 cars. It is an amalgamation of the already developed parking systems with the added advantage of reduced space occupancy by the design of a simpler and compact parking system that is

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lifted up and occupies vertical parking space. The project is aimed to develop a car parking system automatically without having driver. In automatic car parking, RFID module is used along with car for finding on which floor, slot the car has to be parked. Here required slot is fixed for some specific car. Here lifting mechanism along with different motors is used for parking a car to required floor & slot. Hence ACPS can be used at busy commercial places, malls, hotels etc. to prevent space shortage.

PAPER ID: C001

Treal: Virtual Trial Room using Virtual Reality

Rajat Rao1, Jinesh Shah2 and Mayur Chawada3



A virtual trial room is the online equivalent of an in-store changing room. It enables shoppers to try on clothes to check one or more of size, fit or style, but virtually rather than physically. Due to the increase interest in augmented reality and Virtual Reality, there have been many applications developed. The current system of Virtual Trial Room is not as attractive as it can be. It lacks participatory interaction from the user point of view. Keeping this in mind, the primary goal of Trial is to interface 3D animation software and gesture recognition hardware to create an interactive trial room environment. VR head gear is used for creating a virtual environment. This application interaction method can be used to make the whole concept of trail rooms more visual, animated and lively rather than the earlier systems.

PAPER ID: C004

Smart Cloud Phone

Karan A. Shah1, Jinay Mehta2, Omkar V. Sawant3 and Prof. Laxmi Kurup4 1,2,3,4Department of Computer Engineering,


Everyday new ideas and fresh concepts ushers in myriad of opportunities to upgrade the technological devices. In a smaller attempt to stand with the changing technologies we came up with such a smartphone unit that does not require processing unit. The mobile device will act as display unit and all the computation part will be offloaded to the server where the OS is setup. This will minimize the usage of resource’s in mobile client.

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PAPER ID: DM01

Consumer Credit Default Predictor

Yash Poddar1, Sanat Shah2, Anmol Sheth3 and Prof. Chetashri Bhadane4 1,2,3,4Department of Computer Engineering,

D.J. Sanghvi College of Engineering, Mumbai–400056 E-mails: [email protected], [email protected]

Credit scoring models are very useful for many practical applications especially for banks and financial institutions. The decision-making process of accepting or rejecting a client’s credit by banks is commonly executed via judgmental techniques and/or credit scoring models. Most banks and financial institutions use the judgmental approach that is based on the 3C’s, 4C’s or 5C’s which are character, capital, collateral, capacity and condition.

Credit scoring is a system creditors use to assign credit applicants to either a ‘‘good credit’’ one that is likely to repay financial obligation or a ‘‘bad credit’’ one who has a high possibility of defaulting on financial obligation. Generally, Linear Discriminant Analysis and logistic regression are two popular statistical tools to construct credit scoring models. However, with the advance in information and computer technology new techniques are appearing under the name of data mining.

Data Mining and Machine Learning algorithms provide not only the classical methods but new novel predictive modeling and classification techniques such as decision tree, neural networks, support vector machine (SVM), and k-nearest neighbors. Our system also uses a Credit scorecard model that is a hybrid model and combines the best of the features to generate higher, accurate and actionable results.

PAPER ID: DM02

Dipriori

Yadynesh Desai1, Mrunal Medhekar2, Disha Mehta3 and Prof. Vinaya Sawant4 1,2,3,4Department of Information Technology,


Modern organizations are geographically distributed. There is lot of online as well as offline purchase of data items taking place. Typically, each site locally stores its ever increasing amount of day-to-day data. Using centralized data mining to discover useful patterns in such organizations' data isn't always feasible because merging data sets from different sites into a centralized site incurs huge network communication costs. Data from these organizations are not only distributed over various locations but also vertically fragmented, making it difficult if not impossible to combine them in a central location. Distributed data mining has thus emerged as an active subarea of data mining research.

Our proposed solution is going to apply the Apriori algorithm in distributed manner on real world large datasets with precision and with great speed. This approach can be used by both online shopping sites and offline marts.

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PAPER ID: DM03

Smart Question Paper Generator

Jagruti Malani1, Shreya Managute2, Khushboo Jain3 and Prof. Khushali Deulkar4



In Current Educational System, Teachers follows manual process for generating question paper which is very tedious and time consuming task. Generating an effective question paper is a task of great importance for any educational institute. Teachers search for the questions in each chapter so that the entire syllabus gets covered in the generated question paper. There are chances of selection of some questions in every examination because of biasing. This paper represents a smart question generation tool that will automatically generate question paper and proposes its use in educational application. The concept of selection by randomization is used. It is made to allow universities to generate question papers with random but even questions to cover most chapters of subject within seconds. The paper is produced by the tool according to standard university format specified by examiner. The smart question generation tool will help generate papers from qualitative perspective and ease out teacher’s tasks to a great extent.

PAPER ID: DM05

Drought Prediction and Management System using Big Data Analytics

Benita Jeyakumar1, Vinita Rane2, Himani Shah3, Jayesh Nainani4 and Dr. Nupur Giri5 1,2,3,4Department of Computer Engineering,

Vivekanand Education Society’s Institute of Technology, Mumbai, India E-mail: [email protected], [email protected], [email protected],


The prediction of occurrence of droughts has been a difficult task for a long time. However, it is necessary that this prediction is done with at most accuracy to prevent loss of life and property. Based on the previous year’s rainfall, temperature and evapotranspiration data, DDI is calculated which is based on SPI, SPEI, PDSI, PHDI and ZIND indices. Training of this proposed index will be done using random forest algorithm and the output will help to predict the severity of drought for the upcoming years. Also, for resource allocation, dynamic quantum size round robin algorithm has been used.

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PAPER ID: DM07

Prediction and Optimization of Products for Online Sales

Shweta Sohani1, Neel Shah2 and Aneri Shah3 1,2,3Department of Computer Engineering,


How to forecast product sales effectively and efficiently in E-commerce is a significant task for E-commerce producers to manage product inventory and design marketing strategies. However, under the uncertainty of product demand, sales prediction is a complex task. The prediction of online sales demands evaluation and accuracy. In this study different data mining prediction models/ algorithms to forecast the online sales and optimise the offers have been used. Although it is difficult to take into account all the features/ attributes that influence the prediction of online sales, an attempt to find the most significant features is made, also few software programs are used to find out the features that are most contributing like R, various data mining techniques/models like decision making tree, F-measure/ F-Score are used to evaluate the sales online. Finally the most significant attributes are selected and the evaluation technique gives us the best F1-Score.

PAPER ID: DM09

Teacher Guardian Log System

Abhishek Tiwari Department of Information Technology,

Thakur College of Engineering & Technology, Mumbai, India E-mail: [email protected]

The product is an entire ERP system which is a feature-rich web application for all the sections in the hierarchy of the college. It deals in the way in which the files are accessed from the MySQL database. The implementation has been carried out purely in Java under the J2EE framework. The product will assist in organized management of the student information handled by their teacher guardians and the higher authorities. The system is an Internet based application that can be accessed by all the legitimate users from wherever they wish to access the system and read/write data based on their privilege. The system is developed entirely for an Engineering college under University guidelines and curriculum to maintain and facilitate easy access to information. For this, the users must be registered with the system after which they can access as well as modify based on the privileges given to them. This system can be used as a smart, knowledge based learning management system. It also includes a Content Management System (CMS) for the same which gives it an upper hand on its dynamicity and future purpose.

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PAPER ID: DM15

Duplication Avoidance in Big Data

Pravina Vyawahare1, Bhavin Bhoi2 and Pratik Avhad3

1,2,3Department of Computer Engineering, Viva Institute of Technology E-mail: [email protected], [email protected], [email protected]

The database is a collection of interconnected data which is managed and retrieved in an efficient manner. The concept of the larger database is large scale database which will consist of many data can be stored in the database system. Duplication of data is a technique for minimizing storage needs by eliminating inordinate data. Data avoidance is rejection of risk, the action that can negatively effect on a larger database system. Duplicate detection is a problem of material or stuff in many kinds of application including user relationship management, confidential information management or data mining. Duplicate detection is a method of detecting or observation of all cases multiple demonstrations in the real-world application. In the existing system, the duplication of data is checked based on string which checked character by character, so it is time-consuming and it occupied more memory. The proposed system is implemented in Hadoop which handle larger database. Its consist detection of duplicate data based on the multiple attributes. In our system, we used data pre-processing is data mining technique that consists transformed row data in the understandable format. We applied Parallel Progressive Sorted Neighborhood Method & Map Reduce algorithm on this data will get a clean database. Hadoop Map-reduce programming allows for the processing of such large data in a completely safe and cost-effective manner. It will provide more manageable space and efficient handling of data.

PAPER ID: DM16

Weather Prediction Model: A Data Mining Approach

Sudhir Kuwar1, Pratiksha Gudme2 and Manali Band3 1,2,3Department of Computer Engineering,

VIVA Institute of Technology, Mumbai, India E-mail: [email protected], [email protected], [email protected]

Data mining is defined as the process of discovering the knowledge from a large amount of data. It is the process of extracting the important information from a huge volume database. The proposed system is developed to make use of data mining approach for the weather prediction. The proposed system predicts the various numerical parameters of weather using the technique of Linear Regression. It also uses the Decision Tree classifier, which trains the system to predict the rainfall. The weather dataset for various cities has been gathered from the year 2010 to 2015. The existing system can yield better results when applied on more cleaner and larger dataset. To overcome this drawback of the previous system the proposed system makes use of the pre-processing techniques to filter the large dataset and make the data more accurate and consistent, which will gradually improves the accuracy of the prediction.

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PAPER ID: DM17

Web based Code Testing and Monitoring Engine

Adit Shinde1, Sushilkumar Takkekar2 and Ratnesh Dubey3 1,2,3Department of Computer Engineering,

Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India E-mail: [email protected]

Practical sessions play an important role in improving the technical knowledge of a student. Most of the colleges follow an offline system for the assessment of practical. An offline assessment of these practical sessions consists of various steps and also has a number of flaws. Grading the students on the basis of these sessions include the steps like compiling the source code, applying different test cases, etc. Which is a lengthy task. The procedure might seem easy if there are a few students but more number of students make this a difficult task. An online assessment tool automates this procedure and makes it more efficient. Students can be graded for a given experiment as soon as they submit their code. The students would be able to improve their grades by submitting better solutions for the same experiment. A solution could be assessed on more number of test cases, even the trivial cases can be covered using an automated assessment tool. By the time a program is evaluated in an offline manner for a few test cases, hundreds of test cases could be evaluated using an online tool. Evaluation using trivial test cases would make the students develop the habit of writing efficient, correct and concise codes. One such auto assessment tool is ‘Codebot’. Codebot allows the faculties to add various experiments to a course and any number of test cases could be added for an experiment. When a student selects a course, he can see a list of experiments to be performed. On submitting a solution for a program, score would be shown on the basis of test cases passed for the given solution. Codebot also gives an additional feature of live code monitoring to the faculties. Using this feature, the faculties can monitor the code being written by a student from a remote computer. Codebot has been written in Nodejs and has used Express framework. MongoDB has been used to support the backend.

PAPER ID: DM19

Graduate Application Evaluation using Machine Learning

Varun Kasbekar1, Hiral Rayani2, Ami Sangani3, Prof. Neepa Shah4, Jemin Jain5, Vivek Jain6 and Srinath Prabhu7

1,2,3,4Information Technology, Department of Information Technology 5,6,7Department of Computer Engineering


[email protected], [email protected],

Application Evaluation is a process of evaluating candidate’s profile for MS with respect to the criteria's of the respective university. An increasing number of engineering undergraduates apply for a master’s degree abroad preferably in United States. However the university standards of evaluating a profile

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changes from university to university. Generally applicants GPA, GRE score, IELTS/ TOEFL scores, work experience, SOPs, LORs, Major and backlogs history plays a major role. University selection alone has already become a big business in India. An applicant normally approaches a counsellor for guidance regarding shortlisting the universities to apply for and related information. This list can vary from counsellor to counsellor and can be error prone as no detailed analytical study of past trends in a university is performed by the counsellor. Also a list of graduate programs suitable for an applicant can be charged Rs.40000 in India. So the applicant has to shell out a huge amount in order to get his/her profile reviewed by a counsellor. So here we would be providing the solution to this problem by creating an Application Evaluation System that would be able to determine whether an applicant would be getting an admit from a university of his choice using Machine Learning.

PAPER ID: DM20

Hybrid Approach to Distributed Document Clustering

Varun Kasbekar1, Hiral Rayani2, Ami Sangani3 and Neepa Shah4 1,2,3Department of Computer Engineering,


The elevation in the field of information technology has resulted in a rapid increase in volumes of data. Due to the enormous data generated, there is a massive demand for computational resources which makes centralized clustering of distributed documents difficult. Therefore distributed document clustering algorithms are required to cluster documents using distributed resources. The proposed hybrid approach comprises of Particle Swarm Optimization (PSO), K-Means clustering and Distributed Latent Semantic Indexing (LSI) algorithm, along with Map Reduce framework for distributed computation. The resultant of this algorithm is expected to deliver great clustering quality and the execution time will be considerably reduced as the dimensionality of documents reduces. The Map Reduce framework is used as a distributed programming model which will improve the speedup of algorithm.

PAPER ID: DM21

Agro Analytics: Drought Prediction and Suggestions for Optimal Agricultural Practices

Manan Shah1, Mihin Sumaria2 and Mohit Shah3 1,2,3Department of Computer Engineering,


Agricultural statistics and forecast is an important resource that the government has not explored commensurate to its impact. The aim of our project, Agro Analytics, is to make this process computerized by implementing principles of data mining and analytics. More specifically, our project aims at targeting the social issue of drought, analyzing data based on amount of rainfall, average

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temperature and pressure, crop produce, agricultural inputs, and similar factors for crops in the state of Maharashtra. Based on the extensive research carried out through this project, effective counter measures and suggestions will be given, which if implemented expeditiously, can help tackling the problem of drought in our state and enable the farmer with the means to ensure a good harvest. Data can be mined and analysed to find various trends and relations, such as–contrast between total irrigation area and type of crop; total principal and non-principal crop amount versus district-wise rainfall etc. The end result of the project will be research based reports specifying these trends, studied and analysed from data taken over the past few years. Actions to minimize the damage of drought and suitable farming techniques will also be suggested.

PAPER ID: HCI03

Portable Book Reader for Visually Impaired

Nishi Jain1, Mandar Kanade2, Harsh R. Mehta3 and Prof. Khushali Deulkar4 1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected], [email protected], [email protected]

For the visually-impaired population, the inability and inaccessibility to read has created a negative impact on their quality of life. The books available are not easily found in separate volumes and there are hardly a few applications available which help in reading the actual book in front of us. So we thought of a portable device which the visually impaired can carry anywhere and at any time and which is feasible to operate. In this paper, we discuss the design and implementation of the device using the OCR engine and the TTS engine (Text-to-Speech) Conversion. We propose a prototype for this portable device. This prototype utilizes an economical approach of being cost-effective. This prototype can be seen as a loop of a user taking snapshots of the text, optical character recognition, Text-to-Speech conversion and finally the process of playing the audio output to the user.

PAPER ID: HCI04

VidMute Silence those Annoying Loud Ads

Rushabh Dharia1 and Chirag Jain2 1,2Department of Computer Engineering,


This paper describes our project “VidMute” which uses Image Processing to mute the advertisements on YouTube. As we all know that advertisements can be very loud and annoying and can disrupt our mood. So we decided to do something about it. Currently VidMute works only when the advertisements are viewed in the full screen mode.

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PAPER ID: HCI06

Multiple Object Tracking and Monitoring

Shreya Redekar1, Nishita Sheth2, Nisha Shah3 and Prof. Khushali Deulkar4 1,2,3,4Department of Computer Engineering,



This project proposes a novel method which assists in tracking and monitoring of multiple objects through a video sequence. The system uses image processing mechanisms to instrument a prediction model which focuses on a number of inter-linked factors for tracking of objects between different frames. The entire system is divided into two phases, the detection phase, where objects are manually detected in the first frame and later, recognised and associated in the consequent frames with image processing techniques. In the second phase, the associated objects are tracked based on their trajectories. In addition to trajectories, for ease of evaluation and tracking, images of the movement of the object along with the respective coordinates are recorded on per second basis. The system is designed to be robust and give positive results even in complex scenarios where a large number of objects are being tracked simultaneously and where the objects face occlusions. This system can be mainly used for security reasons, but when combined with other computing technologies like machine learning, it can facilitate in learning the playing patterns of players in team sports.

PAPER ID: HCI08

MonVoix–An Android Application for Acoustically Challenged People

Aishwarya Danoji1, Aishwarya Dhage2, Rachana Kamat3, Priya Puranik4 and Prof. Sharmila Sengupta5

1,2,3,4,5Department of Computer Engineering, Vivekanand Education Society’s Institute of Technology, Mumbai–400074, India

E-mail: [email protected], [email protected], [email protected], [email protected], [email protected]

Communication is a mode through which people from various socio-economic backgrounds interact with one another to develop a mutual relation. The ability to voice their opinions, ideas and intentions effectively through messages is quite an essential life skill that majority of people possess. However, there exists distinguishable cliques who are devoid of vocalizing their views but they dominate the world of expressions through hand gestures. Acoustically challenged people have to rely on interpreters to blend into a sane conversation with their hearing counterparts and not just be a mute spectator. It is the need of the hour to find a common ground that can release the mute from these shackles. This paper proposes an Android application- ’MonVoix’ for a coherent interpretation of sign language gestures. This application offers users an interface to capture hand gestures through their smart phone. A sequential image processing operations and database emulation is carried out in the backdrop and the

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outcome procured is its corresponding textual meaning. The user can converse with others either by posting the converted text or by attaching as an audio file.

PAPER ID: HCI09

Interpretation of Music Score Sheet to Generate Audio File

Bhakti Raichura1, Karan Shah2 and Ronak Thakkar3 1,2,3Department of Computer Engineering,


Music is considered to be the universal language. Music has a wide variety of applications and can be perceived in aural, visual or written format. One of the major issues faced by a beginner in music is reading music scoresheet. Generally, for beginners it is perplexing to understand which symbol represents which note and it corresponds to which tune. Most beginners face issues deciphering the scoresheet correctly and playing the correct tune which makes it difficult for them to learn and master a particular tune. The proposed system aims at helping beginners in music to learn quickly by generating an audio file as output for the users to listen to, by simple providing a music scoresheet image as input. Segmentation is carried out using Hierarchical Decomposition and segmented symbols are recognized by employing an Artificial Neutral Network coupled with a Boosting algorithm. The proposed system makes use of PCA model followed by SVD for training. The sole purpose is to help users decipher the symphony of music notes from scoresheet.

PAPER ID: HCI10

Structured Light 3D Scanner (Point Cloud Generation using Triangulation)

Kushal Vyas1 and Prof. Ruhina Karani2 1,2Department of Computer Engineering,


The primary objective of this research is to produce a digital means for storing and replicating any real world object. It focuses on a setup capable of analyzing and modelling a general object through triangulations there by estimating the object’s geometry. From the usual stereo setup, we prefer using a single camera coupled with a projector, for faster and efficient reconstruction. The system makes use of structured light for acquisition of geometry. The single view point clouds are then merged together through a rigid body transform, further refined using the iterative closest point algorithm. The end objective is to create a point cloud file of the entire 3D model.(The project was conducted under the auspices of Automata Systems).

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PAPER ID: HCI11

Prevention of Accidents While Drunken Driving

Kevin Maru1, Prathamesh Dongre2, Purvi Udhwani3 and Neha Mundra4

1,2,3,4Department of Computer Engineering, Vivekanand Education Society's Institute of Technology, Chembur, Mumbai, India


This project proposes a model to increase vehicular safety. It basically consists of three modules-Intelligent Headlight Control, Fog Removal, and Drowsiness Detection. Fog Removal has been implemented for a single image using dark channel prior. Intelligent Control of Headlight is implemented using an effective algorithm which uses SVM classifier for training the data to get correct detection of blobs. The proposed model shows an algorithm to detect the Eye Map for eye detection, iris and pupil detection, and analysing the state of the eyes to make the drowsy decision. Finally, the paper shows how to make the required connections on a Raspberry Pi, and get the model effective.

PAPER ID: HCI12

Virtual Try-On of Clothes

Aashni Savani1, Raj Vastani2, Harshal Vora3 and Prof. Ruhina Karani4

1,2,3,4Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected]

Today one of the major problems in the apparel related e-commerce industries is that it is not possible to know how the apparel fits or suits you just by looking at the images. We provide a solution to this problem by the help of virtual try-on system where with the use of image processing methodologies and techniques such as Image Warping and body ratios the user can see how the apparel (i.e. t-shirt) will look on him/her. This will help is making the decisions regarding the purchase of goods online easier and will help the e-commerce industry. The performance of the proposed system is evaluated experimentally on the acquired images in the real life scenario. As per the result, the processing time and the fitting accuracy varies with the image resolution and illumination changes.

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PAPER ID: HCI13

Baby Mentor: Learning through Images

Jeremy Samuel1, Sanket Solanki2, Saurabh Patil3 and Prof. Ruhina Karani4

1,2,3,4Department of Computer Engineering, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India E-mail: [email protected], [email protected],


Technology changes the way how children think, what they learn, and the way they interact with peers and adults. A computer based audio visual learning is often found to be effective for tutoring babies and young children particularly those suffering from learning and mental disabilities. Baby Mentor is a system that ameliorates this concept and makes learning a more interactive and fun based activity by identifying and generating human like description for real world objects like toys, which are commonly used by the children. The proposed system employs SIFT (Scale Invariant Feature Transform) algorithm for feature detection and extraction. The features taken from SIFT is then used to generate vocabulary for Bag of Visual Words Model which is then utilized for generating template-based sentences. These sentences are conveyed through audio devices in a human like voice making the children understand and recognise the object just like how a teacher or parent would teach them.

PAPER ID: HCI14

3D Facial Reconstruction using Skull of a Deceased Person

Priya Singh1, Lilavati Swamy2, Aishwarya Tate3 and Anam Shah4 1,2,3,4Department of Information Technology,


Reconstructing the 3D facial model of an unidentified individual from his skull contributes considerable benefits to terms of archaeology, anthropology and forensic investigation but it is still significantly complicated matter. Computer aided system of 3D facial reconstruction based on skull has a great advantage of reduction in time consumption. Nevertheless, existing results either contain graphical artifacts or reflect incorrectly differences among reconstructed faces. In this paper, we propose a 3D facial reconstruction system from skull that can overcome existing problems. We are using SHA feature extraction since the human skull identification needs the shape of the curves present. Neural Network is also used for estimating the age of the person so as to construct accurate curves of the 3D face.

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PAPER ID: HCI15

Measuring Length of an Infant from its Image using Reference Object and Monitoring Growth

Dimpi Dedhia1, Nidhi Patel2, Kavita Soni3, Prof. Stevina Correia4 and Prof. Pratik Kanani5

1,2,3,4,5Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India

E-mail: [email protected], [email protected], [email protected], [email protected], [email protected]

Keeping a track of an individual's growth is very important considering the importance of growth for maintaining health and nutritional level. This practice is of much more importance in infants because it helps in early detection of the infant's vulnerability to any disorder or disease like thyroid, Celiac disease etc. Length and weight of the baby play an important role in understanding its growth. While measuring the length of the infant using the currently used infantometer or a measuring tape, the pediatricians face difficulties because of the infant's anatomy especially its bow-shaped legs. Forcibly handling them for such measurements may result in causing harm to the baby's fragile bones. Thus automation of such an exhausting task would prove to be of great help to the pediatricians and can lead to faster, more efficient and reduced human efforts. Our system fully automates the task. All the doctor has to do is capture an image and give weight of the baby as an input to the system. The system generated length and weight values are than compared with the standard graph values by the system and the doctor is shown a graph representing the comparison.

PAPER ID: HCI17

Interactive Learning using Augmented Reality Books

Aayushi Vora1, Soham Mehta2 and Pratish Jain3

1,2,3Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India


This paper intends to demonstrate how studying electronic concepts learning can be made easy. Using the augmented reality, the project aims at simplifying the learning process of understanding electronic devices, circuits and concepts. This application can be used by the students, and it will be as simple as just hovering over the text or the image they want to understand. Automatically, the related data will be shown from the application database or from the cloud. The project will enable students to make the concepts clear by simply using the smart phone and the intended electronics book.

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PAPER ID: HCI20

Reflective Intelligence—An Odroid Based Approach

Priti Nalawade1, Shraddha Upadhyay2, Navin Das3 and Vijal Jain4

1,2,3,4Department of Information Technology, Vidyalankar Institute of Technology, Mumbai


The proposed work describes the design of a “Reflective Intelligent System”, an artifact augmented with intelligence to demonstrate personalized services for enhanced comfort. The proposed system aims at detecting the speech based command of the user and displaying the appropriate result on the mirror and provides features like speech recognition, weather and news reports, maps and location, to-do list etc. The proposed system will detect the presence of user by either detecting the user’s face or voice and greet the user and display date, weather, etc. The user can then issue appropriate commands. This project will be completely based on Android OS which will be hosted on Odroid C2.

PAPER ID: NS06

Novel Encryption Technique to Secure Document Data Store

Elita Dsouza1, Dimpal Jayani2, Anuja Patil3, Pratik Kanani4 and Prof. Kriti Srivastava5 1,2,3,4,5Department of Information Technology,


In the rapidly evolving world of technology and the ever-increasing size of datasets, NoSQL databases have become the one-stop solution for any enterprise. However, it has various challenges i.e. it is less secure, authentication is not enabled by default, data transfer is in clear text format. There has been significant increase in the interest shown by researchers for studying Security Issues in NoSQL. Various algorithms and their combinations have been used in existing system to make the database more secure. This paper proposes a system that makes use of Extended Transpose Substitution Folding Shifting (ETSFS) Algorithm to secure hospital-related data as it is extremely critical. It compares ETSFS with other algorithms like AES, DES, RSA, MD5 stating its advantages over the others. To test the vulnerabilities in NoSQL database MongoDB, and to test how ETSFS enforces security over big-data various attacks like NoSQL-injection, scripting attacks, unauthenticated database access has been performed.

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PAPER ID: NS08

Prevention of Parallel Active Dictionary Attack on WPA2-PSK Wi-Fi Networks

Drishti Kakar1, Nagendra Kamath2, Aneek Guha3 and Dr. N.M. Shekokar4



The wireless LAN provides ubiquitous access to the Internet globally, also being extremely user-friendly and cheap. The secure access to the Internet is now of paramount importance. The modern standard used is the Wireless Protected Access 2-Pre-Shared Key (WPA2-PSK), which protects the IEEE802.11 wireless networks. The offline dictionary based attacks on the WPA2-PSK involves the capturing of the four-way handshaking frames transferred between the Access Point (AP) and the wireless client. The online parallel dictionary attack on the WPA2-PSK, however allows the external client to bypass the frame capture phase and continuously inject pass phrases until it is accepted and connection is established. We propose the use of an encrypted global counter in the message exchange of the Extensible Authentication Protocol (EAP) over LAN (EAPoL) framework, the use of SHA-512 in Password Based Key Derivation Function-2 (PBKDF2) and putting a limit on the number of unsuccessful connection attempts to prevent parallel active dictionary attacks on WPA2-PSK Wi-Fi networks.

PAPER ID: NS10

Design and Overview of a Navigation Application for the Blind

Sanjana Panicker1, Maitreyi K.V.2, Merrill Gonsalves3, Kane Gonsalves3 and Prof. Sandhya Patil4

1,2,3,4Department of Computer Engineering, Fr. CRIT, Vashi, Navi Mumbai, India


Navigating brings up challenges for people who are Visually Impaired (VI). It is tough for people with Visual Impairment to move both indoor and outdoor on their own. We aim to address these challenges. Our application provides indoor navigation on a smartphone with the help of Bluetooth Beacons and Indoor Atlas technology. The mobile application provides voice assistance to users to navigate to their destination. The indoor component of the app is to assist members of the Xaviers Resource Centre for the Visually Challenged(XRCVC).This application also provides outdoor help for VI individuals and guides them to the nearest bus stop. GPS will be used for this function. The application aims to facilitate a commuter to reach a bus stop of their choice. It provides information such as bus numbers and

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different routes. Also the application prompts when the arrival of a desired bus stop is expected. The application would be scalable and expandable to add more areas. This application enables VI individuals to travel independently by overcoming many of the obstacles faced by them.

PAPER ID: NS11

Enhancement of Security using Three Level Graphical Authentication

Prashant Chiplunkar1, Tejal Patil2 and Sunil Dewoolkar3

1,2,3Department of Computer Engineering, VIVA Institute of Technology, Mumbai, India


The most familiar authentication technique is to use textual usernames and passwords. This technique possesses many flaws. For e.g. Normally users picks the passwords that are easily remembered but the drawback over here is this password can also be easily guessed by the attackers. On the other hand, if a word is hard to guess, then it's always troublesome to remember. To deal with this problem we've a selection sort of a graphical positive identification which would be hard to guess and though easily remembered by normal users. The Proposed three level authentication system provides graphical passwords which can be easily remembered as well as provides security. In this system 1st level is based on alphanumerical password, 2nd level is based on RGB color pattern and 3rd level is Related images.

PAPER ID: NS19

Smart Network for Fire Control

Heena Tailor1, Kashmeera Sawant2, Niel Vaishya3 and Shivani Sherekar4

1,2,3,4Department of Electronics & Telecommunications, K.C College of Engineering Kopri, Thane


A smart network for fire control is a system which monitors the occurrence of fire and takes necessary steps for fire controlling as well as to provide safe evacuation from the building. The system proposed by us consists of sensors network which will detect gas element released by fire. If fire situation arises, the warning ALARM'S will turn On immediately and sprinklers will also turned ON, to control fire. System tries to reduce casualties due to panic, by determining point of occurrence of fire and it uses indicators to guide the people towards the exist which are safe or unaffected by fire. In such situations, calling for fire brigade is also necessary, which will done automatically by sending SMS to nearest fire station. The system provides Graphical mapping of sensor and indicators on computer which will be located away from building or inside the security room.

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PAPER ID: NS20

Puppet Attack and its Detection

Manasi Deshmukh1, Jash Nichani2, Komal Mehta3 and Prof. Aruna Gawde4


E-mail: [email protected], 2 [email protected], [email protected], [email protected]

Ad-hoc networks are computer networks which are not connected by any kind of cables. Ad-hoc networks are prone to many attacks and one such specific attack is a puppet attack. In this paper, a new DoS attack called puppet attack is presented, which can result in flooding of network due to the attack packets sent by the intruder to the puppet node. This scenario is serious as it exhausts the network communication bandwidth and node energy. A proactive and receptive defense architectures have been coordinated, and arbitrarily collaborates with stochastic nearby node. Cooperative Bait Detection scheme is used to detect the presence of malicious node in the network.

PAPER ID: NS21

Intelligent Ambulance Fleet Management System

Monica Chhabria1, Latika Wadhwa2, Shruti Dhumale3 and Omkar Patinge4

1,2,3,4Department of Computer Engineering, Vivekanand Education Society Institute of Technology, Mumbai, India E-mail: [email protected], [email protected],


The time after a medical mishap if used optimally serves as a measure of the effectiveness of any ambulance service provider system. For a minimal loss of life, recovery actions should be taken in time. In spite of advancement of technology in today’s world, the service providers are not well equipped. Also, problems like routing problems and traffic congestions hamper their speedy recovery action in real time. Our aim is to save maximum number of lives in an emergency by reducing the reaction time by various means. Pre-registration and extracting the real-time location helps to reduce the reaction time. Another approach is by providing the shortest path to the ambulance driver. We identified that the current traffic situation is the biggest challenge for the ambulance to reach in time. Thus coordination with the traffic control room is essential in solving this problem. The proposed system is fully automated and thus allows booking an ambulance, to which system allocates ambulance and informing TCR in case of extreme emergency.

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PAPER ID: NS22

An Access Control Model for an E-Commerce Business Model using Mongo-DB

Khushali Shah1, Priyal Shah2 and Prof. Kriti Srivastava3

1,2,3Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India


The wide proliferation of the Internet has set new requirements for access control policy specification. Due to the demand for ad-hoc cooperation between organizations, applications are no longer isolated from each other. Applying access control policies becomes challenging in a large, heterogeneous, and dynamic environment. Policies, while maintaining their main functionality, go through many minor adaptations, evolving as the environment changes. Current development platforms are web scale, unlike recent platforms which were just network scale. There has been a rapid evolution in computing paradigm that has created the need for data storage as agile and scalable as the applications they support. With NoSQL databases being adopted by an increasing number of organizations, the provision of security for them has become a growing concern. In order to implement a security framework, it is mandatory to provide real time and on-demand access control management approach that should take care of User identity, data integration and sanitation, multi-tenancy, relation between different users and the resources. With the aim of encapsulating persistent goals of policies we introduce extensions in the form of policies.

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Author Index

Aditya, B., 4 Alif, Shaikh, 13 Aute, Niriksha, 10 Avhad, Pratik, 18

Band, Manali, 18 Baviskar, Sneha, 13 Baxi, Bhavin, 2 Bhadane, Chetashri, 15 Bhan, Namrata, 11 Bhat, Shivani, 6 Bhoi, Bhavin, 18 Bhowmick, Kiran, 2

Chawada, Mayur, 14 Chhabria, Monica, 30 Chiplunkar, Prashant, 29 Chowdhury, Nabanita Nath, 13 Correia, Stevina, 26

D’Silva, Mitchell, 11 Dangare, Shamli, 13 Danoji, Aishwarya, 22 Das, Navin, 27 Dave, Vaibhav, 4 Dedhia, Dimpi, 26 Desai, Yadynesh, 15 Deshmukh, Manasi, 30 Deulkar, Khushali, 8, 16, 21, 22 Dewoolkar, Sunil, 29 Dhage, Aishwarya, 22 Dharia, Rushabh, 21 Dhumale, Shruti, 30 Dhuri, Komal, 7 Dixit, Chirag, 6 Dongre, Prathamesh, 24 Doshi, Krusha, 1 Dsouza, Elita, 27 Dubey, Ratnesh, 19

Echhpal, Ria, 11

Furniturewala, Danish Ali, 9

Gaikwad, Shruti, 13 Gawade, Aruna, 5

Gawde, Aruna, 30 Gharat, Swapnil, 12 Giri, Nupur, 16 Gonsalves, Kane, 28 Gonsalves, Merrill, 28 Gosavi, Shradhha, 13 Gudme, Pratiksha, 18 Guha, Aneek, 28 Gupta, Ilina, 5

Jain, Chirag, 2, 21 Jain, Hardik, 1 Jain, Jemin, 19 Jain, Khushboo, 16 Jain, Meghna, 1 Jain, Nishi, 21 Jain, Payal, 8 Jain, Pratish, 26 Jain, Vijal, 27 Jain, Vivek, 19 Jayani, Dimpal, 27 Jeyakumar, Benita, 16 Jhaveri, Kejal, 2 Joshi, Janki, 11

Kakar, Drishti, 28 Kamat, Rachana, 22 Kamath, Nagendra, 28 Kanade, Mandar, 21 Kanani, Pratik, 26, 27 Karani, Ruhina, 23, 24, 25 Kasbekar, Varun, 19, 20 Korlahalli, Sameer, 7 Kothari, Bansari, 1 Kurup, Lakshmi, 5, 10 Kurup, Laxmi, 14 Kuwar, Sudhir, 18

Maheshwari, Harsh, 1 Maitreyi, K.V., 28 Malani, Jagruti, 16 Managute, Shreya, 16 Maru, Kevin, 24 Medhekar, Mrunal, 15 Mehta, Disha, 15

AUTHOR INDEX

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Mehta, Harsh R., 21 Mehta, Jinay, 14 Mehta, Kena, 11 Mehta, Komal, 30 Mehta, Raj, 12 Mehta, Soham, 26 Menezes, Rachel, 5 Mohammed, Saloji, 13 Mohan, Meghna, 7 More, Akshay, 7 Mundra, Neha, 24 Muralidaran, Manaswini, 7

Nainani, Jayesh, 16 Nair, Sindhu, 1 Nalawade, Priti, 27 Narula, Harish, 1 Narvekar, Meera, 2 Nichani, Jash, 30 Nisar, Karan, 2

Olia, Fatema, 5

Pamecha, Monik, 2 Panchal, Divya, 8 Panchamia, Yash, 4 Pandey, Abhishek, 8 Pandya, Twinkle, 1 Panicker, Sanjana, 28 Parekh, Akash, 4 Parekh, Sagar, 4 Parmar, Harsh, 7 Patel, Bhaveen, 3 Patel, Nidhi, 26 Patel, Prachi, 9 Patil, Anuja, 27 Patil, Sandhya, 28 Patil, Saurabh, 25 Patil, Tejal, 29 Patinge, Omkar, 30 Poddar, Yash, 15 Prabhu, Srinath, 19 Puranik, Priya, 22

Qazi, Najeeb, 11

Raichura, Bhakti, 23

Ramnathkar, Aditya, 9 Rane, Vinita, 16 Rao, Rajat, 14 Raulo, Sagar, 9 Raut, Leena, 9 Raut, Purva, 9 Rayani, Hiral, 19, 20 Redekar, Shreya, 22 Rele, Siddhant, 9

Sadasivan, Aishwarya, 7 Sadaye, Raj, 6 Salvi, Vikash, 10 Samuel, Jeremy, 25 Sangani, Ami, 19, 20 Sanghavi, Kinjal, 4 Savani, Aashni, 24 Sawant, Kashmeera, 29 Sawant, Omkar V., 14 Sawant, Vinaya, 15 Sen, Malabika, 5 Sengupta, Sharmila, 22 Shah, Akash, 3 Shah, Anam, 25 Shah, Aneri, 17 Shah, Bansi, 3 Shah, Bhavya, 3 Shah, Deesha, 10 Shah, Hetashavi, 9 Shah, Himani, 16 Shah, Jinesh, 14 Shah, Karan A., 14 Shah, Karan, 23 Shah, Khushali, 31 Shah, Manan, 20 Shah, Meet, 8 Shah, Mohit, 8, 20 Shah, Neel, 17 Shah, Neepa, 9, 19, 20 Shah, Neeti, 5 Shah, Nisha, 22 Shah, Niyati, 12 Shah, Priyal, 31 Shah, Riken, 10 Shah, Rohil, 11 Shah, Sanat, 15

AUTHOR INDEX

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Shah, Sanket, 12 Shekokar, N.M., 28 Sherekar, Shivani, 29 Sheth, Anmol, 15 Sheth, Nishita, 22 Shinde, Adit, 19 Shirke, Ameya, 8 Singh, Priya, 25 Sohani, Shweta, 17 Solanki, Sanket, 25 Somasundaram, Harishkandan, 6 Soni, Kavita, 26 Sowmyasree, L., 6 Srivastava, Kriti, 27, 31 Suchak, Sagar, 12 Sudhirkumar, Singh, 13 Sumaria, Mihin, 20 Swamy, Lilavati, 25

Tailor, Heena, 29 Takkekar, Sushilkumar, 19 Tate, Aishwarya, 25 Thakkar, Ronak, 23

Thakkar, Siddhi, 12 Thakre, Pranjali, 7 Tiwari, Abhishek, 17 Turakhia, Drashti, 3

Udhwani, Purvi, 24 Upadhyay, Shraddha, 27

Vaishya, Niel, 29 Vasanwalla, Adnan, 10 Vastani, Raj, 24 Vora, Aayushi, 26 Vora, Harshal, 24 Vora, Yash, 6 Vyas, Kushal, 23 Vyawahare, Pravina, 18

Wadhwa, Latika, 30 Wagh, Venkatesh, 6 Walvalkar, Rajas, 12

Yadav, Yogesh, 12 Yedurkar, Abhishek, 12

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