2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745419
Girish G. Desai, P. Bartakke
{"title":"Real-Time Implementation Of Indian License Plate Recognition System","authors":"Girish G. Desai, P. Bartakke","doi":"10.1109/PUNECON.2018.8745419","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745419","url":null,"abstract":"A simple and fast technique is presented in this paper for Indian license plate recognition system. Using OpenALPR’s software framework and RaspberryPi, a real-time Indian license plate recognition system could be implemented for some application specific purposes. HAAR and LBP features are extracted from the acquired vehicle images and subjected to training of cascade classifiers in order to localize license number plates. The validation process is used to optimally select number of stages of cascade classifiers. The extracted number plates are then utilized for character recognition. Cascade classifier with LBP features is suitable for localization of license plates with accuracy more than 98%. Whereas, the average number plate recognition accuracy is above 96% for images captured from front side. The proposed system has been prototyped using C++ and RaspberryPi 3 and experimental results have been shown for recognition of Indian license plates","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"257 22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121829716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745395
Bhaskar Thakker, A. Mathew, Devi Doriwala
{"title":"Design and Implementation of Voice Recording System Prototype","authors":"Bhaskar Thakker, A. Mathew, Devi Doriwala","doi":"10.1109/PUNECON.2018.8745395","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745395","url":null,"abstract":"Embedded System for recording audio signal finds enormous applications in industry as well as home appliances. Such applications cover secured access to the use of electrical appliances through voice signals to a greater extent. For Such appliances requiring secured access, the speech signal is the simple and easiest option to utilize. Audio recording and storing is a primary requirement for such biometric parameter access. While Digital Signal Processors are costly, design and Implementation of a Voice recording system using 16 bit MSP430 series microcontroller from Texas Instruments is presented here. The complete system with prototype along with the usage of personal computer for this task is presented here.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116063560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745381
D. Patel, Yashesh Panchal, Rushad Wankadia, Krishna Samdani
{"title":"A Study of Blockchain’s Architecture and it’s Applications","authors":"D. Patel, Yashesh Panchal, Rushad Wankadia, Krishna Samdani","doi":"10.1109/PUNECON.2018.8745381","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745381","url":null,"abstract":"Blockchain, the underlying framework of Bitcoin has recently received extensive limelight due to its distributed and decentralized architecture. Unlike other ledger approaches, blockchain guarantees tamper-proof storage of approved transactions. Apart from Bitcoin, Blockchain can serve as a backbone for many applications. The unique properties of Blockchain – decentralized architecture, reliability and immutability, are attracting start-ups to integrate it in their systems rather than relying on centralized services. In this paper, we have done an extensive literature survey of blockchain architecture and it’s applications in various fields and presented our analysis based on parameters like consensus algorithm, viability and implementation.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129488009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745372
Amit Thombre
{"title":"Using Machine Learning to find out When to use Box-Cox Transformation on Time Series Data","authors":"Amit Thombre","doi":"10.1109/PUNECON.2018.8745372","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745372","url":null,"abstract":"The Box-Cox transformation improves the normality of the data. This improvement in normality does not guarantee better forecasting results using ARIMA as compared to when the data transformation is not used. So when should one use the transformation on the data to get good forecasting results? The current study tries to answer this by building a predictive model on a set of independent variables which are the characteristics of the data and the dependent variable which tells if use of Box-Cox transformation for forecasting by ARIMA is useful or not. This model gives 64% accuracy and needs improvement. Along with this, another prediction model is obtained which shows from the characteristics of the data whether the 95% prediction intervals obtained by using Box-Cox transformation are better than the intervals obtained by not using the transformation. This model gives 82% accuracy.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130332425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745392
Rajalakshmi E, Prajakta Kumbhojkar, Shyamsalonee Rawal, Masumi Jain, Sneha K. Thombre
{"title":"Implementation of the RnSIR Model","authors":"Rajalakshmi E, Prajakta Kumbhojkar, Shyamsalonee Rawal, Masumi Jain, Sneha K. Thombre","doi":"10.1109/PUNECON.2018.8745392","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745392","url":null,"abstract":"By etymology, the word viral stems from virus, a term used to describe the spread of effect of infectious symptoms across organisms. On the internet, a piece of content can spread similar to a virus, making people infected as and when they come in contact with it. The infection usually occurs when the user shares it, with its circle of friends and associates on a social network. However, it is possible to predict the reach of information across a number of users in a directed network data set. This is possible through the proposed interface which uses the calculations proposed in the Restrained-Susceptible-Infected-Recovered (RnSIR) model. The interface accepts a data set as an input from the users whilst giving the percentage of information spread in that network as the output. The calculations at the interface back-end are done by using the same algorithms as used by the RnSIR model, to select influential nodes and then calculate the said percentage using them with the help of an algorithm. The interface poses to be useful for tracking the spread of information in a directed network for social media marketing and peripheral tactics.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121801734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745425
A. Pawar, Swati Ahirrao, Prathamesh P. Churi
{"title":"Anonymization Techniques for Protecting Privacy: A Survey","authors":"A. Pawar, Swati Ahirrao, Prathamesh P. Churi","doi":"10.1109/PUNECON.2018.8745425","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745425","url":null,"abstract":"Anonymization is one of fruitful privacy protection technique used in various technology fields such as data mining, cloud computing, big data to secure very sensitive data against third party. In today’s world, the value and the amount of data is increasing, hence the protection of data against all possible threats are equally necessary. This paper focuses a brief on data anonymization and differential privacy techniques. Various anonymization techniques which are researched by various researchers across various fields have limitations such as communication and computation cost overhead, accuracy of results after data Anonymization and possibility of different types of attacks. The paper discussed all these issues and their counter-measures through readings of various papers. Finally, this paper presents detailed discussion about existing anonymization techniques (Data anonymization and differential privacy), their comparative analysis by leaving a footprints of future research directions.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128193006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745396
Himanshu Patel, Nishit Sehgal
{"title":"Using Virtual Memory Compression To Reduce Disk I/O Time and Delay","authors":"Himanshu Patel, Nishit Sehgal","doi":"10.1109/PUNECON.2018.8745396","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745396","url":null,"abstract":"This paper proposes a software based logical/architectural approach to solve a major problem that is improving Computational Efficiency by reducing Disk I/O time for Virtual Memory Page Swapping using Various Compression Algorithms. The logical approach is to compress and decompress pages during swap time to reduce transfer time between the secondary and primary memory. This will reduce lag and will increase computational efficiency by reducing the size of pages which are used more than once due to this whenever those pages are used again, the time taken to swap those pages into primary memory is reduced significantly without changing or modifying the hardware.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130013900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745387
M. Mhetre, S. Jabade, K. Sant, M. Chaudhari, N. Satpute
{"title":"Air Flow Detection in Data Cooling Center: Different Approaches","authors":"M. Mhetre, S. Jabade, K. Sant, M. Chaudhari, N. Satpute","doi":"10.1109/PUNECON.2018.8745387","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745387","url":null,"abstract":"The lone purpose of data center is to handle data flow in different electronics equipment. Maintaining heat balance is a challenging task with monitoring of different parameters in the cooling center to prevent damage to the electronic devices. Air flow detection is a vital parameter for accurate heat detection and increasing the life of the data center. Paper discusses three different approaches for maintaining environment by sensing air pressure variations for air flow detection in the cooling center. The main challenge is of low air velocity up to 5m/s with low pressure up to 10 Pascal. In this challenge, first approach shows the experimentation with obstruction based pressure variation and sensing it with accelerometer. Second approach uses pressure variations generated due to bluff body placed in the air flow path and piezoelectric sensing of air variations. Third approach is evolved on the basis of pitot tube air flow sensing method. Each method is explored and through experimentation proved for its limitations.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131557804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Driving Control Using Emotion Analysis Via EEG","authors":"Chinmayi Bankar, Aditya Bhide, Anuja Kulkarni, Chirag Ghube, Dr Mangesh Bedekar","doi":"10.1109/PUNECON.2018.8745412","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745412","url":null,"abstract":"Driving is a very taxing job as the visual, sensory and motor inputs work in harmony to make driving a successful experience. However, when the harmony is distorted, as in the cases when the driver is frustrated, anxious, the negative mindset can be dangerous as it can lead to potential accidents. Analyzing the emotions of the driver and striving to control them therefore becomes important. The work in this paper focuses on enhancing the current driving system of cars to help reduce the accident rate. It uses analysis of driver emotions via the data obtained from EEG (Electroencephalography) waves and the valence-arousal models for emotion classification. Additionally, the control of emotions is obtained via the concept of music therapy. The proposed approach uses the music system in the car to automatically respond to changes in the emotional state of the driver. The emotion detection would be relatively real time thus efficiently soothing the driver. Moreover, the automatic adjustment of music in consonance with the mood would reduce the manual interfacing of the knobs in the car, thus saving distraction and reducing the chances of accidents.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126116631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2018 IEEE PuneconPub Date : 2018-11-01DOI: 10.1109/PUNECON.2018.8745423
Devika Singh, Divya Singh
{"title":"360 Degree Profiling and Social Linkage Analysis of Persons of Interest","authors":"Devika Singh, Divya Singh","doi":"10.1109/PUNECON.2018.8745423","DOIUrl":"https://doi.org/10.1109/PUNECON.2018.8745423","url":null,"abstract":"Scourge of Terror Incidents is increasing because of advent of newer methodologies, weapons and techniques. National Security Agencies control these insurgent terror incidents by maintaining records of Persons of Interests for their tracking. As the person's data can come from multiple sources and in various formats, therefore analysing it with traditional methods becomes major challenge. Also viewing linkages between different entities becomes cumbersome. This paper presents a Machine learning and Computer Vision driven solution, which will help Security Agencies to combat terrorism. This solution will not only build 360 degree Person's profile but also show his linkages with various Incidents of Interest and Entities of Interest. The solution proposed is efficient in terms of performance and speed because it leverages the power of distributed computing and multithreading. So, we are building a Big Data & AI based distributed high performance system which will characterize the 4 V's of Big Data: Volume, Velocity, Variety and Veracity.","PeriodicalId":166677,"journal":{"name":"2018 IEEE Punecon","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125961811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
