S. Yadav, Meet Timbadia, Ajit Yadav, Rohit Vishwakarma, Nikhilesh Yadav
{"title":"Crime pattern detection, analysis & prediction","authors":"S. Yadav, Meet Timbadia, Ajit Yadav, Rohit Vishwakarma, Nikhilesh Yadav","doi":"10.1109/ICECA.2017.8203676","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8203676","url":null,"abstract":"Crimes are a social irritation and cost our society deeply in several ways. Any research that can help in solving crimes quickly will pay for itself. About 10% of the criminals commit about 50% of the crimes [9]. The system is trained by feeding previous years record of crimes taken from legitimate online portal of India listing various crimes such as murder, kidnapping and abduction, dacoits, robbery, burglary, rape and other such crimes. As per data of Indian statistics, which gives data of various crime of past 14 years (2001–2014) a regression model is created and the crime rate for the following years in various states can be predicted [8]. We have used supervised, semi-supervised and unsupervised learning technique [4] on the crime records for knowledge discovery and to help in increasing the predictive accuracy of the crime. This work will be helpful to the local police stations in crime suppression.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130011417","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":"Neural networks through stock market data prediction","authors":"Rohit Verma, Pkumar Choure, Upendra Singh","doi":"10.1109/ICECA.2017.8212717","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212717","url":null,"abstract":"In the proposed work, we presented an Artificial Neural Network approach to predict the stock market indices. We outlined the design of the Neural Network model with its salient features and customizable parameters. A number of the activation functions are implemented along with the options for the cross validation sets. We finally test our algorithm on the Nifty stock index dataset where we predict the values on the basis of values from the past days. We achieve a best case accuracy of 96% on the dataset.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127196152","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":"Network performance in IEEE 802.11 and IEEE 802.11p cluster based on VANET","authors":"Vibhavarsha Prakaulya, Neelu Pareek, Upendra Singh","doi":"10.1109/ICECA.2017.8212713","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212713","url":null,"abstract":"Vehicular ad hoc networks (VANET) are an emerging class of the wireless networks that have emerged because of the recent advances in the wireless technology. VANET is an enhanced form of the Mobile Ad-hoc Network (MANET). The IEEE 802.11standard is based on CSMA/CD and used in both MANET and VANET. An enhanced version IEEE 802.11p is developed for VANET. VANET is a special type of an Intelligent Transport System (ITS), where the mobile nodes are cars, two wheelers, trucks, buses etc., that move on well organized and predefined roads in both the directions at a very high speed. For following the traffic rules, the vehicles provide communication with each other directly (Inter Vehicle Communication-IVC) or indirectly through the Road Side Unit (RSU). Usually thevehicles, which move outside the city area, do not get the response from the RSUas its availability is limited in that area. An attempt has been made to create a new clustering concept for this purpose, which can be applied to a newly created Simple High Way Mobility Model, to increase the speed of the vehicle communication. Thus, this paper focuses the performance of the Packet Delivery Time, Packet Delay Time, Throughput and end to end delay using IEEE 802.11p. This is compared with the values obtained for IEEE802.11 in VANET Environment.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130957306","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":"LS and MMSE estimation with different fading channels for OFDM system","authors":"Manisha B. Sutar, V. S. Patil","doi":"10.1109/ICECA.2017.8203641","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8203641","url":null,"abstract":"In wireless communication system, the multipath channels introduce frequency selectivity and time varying properties in OFDM symbols which causes Inter-Carrier Interference (ICI) within symbols. For mitigation of such impairments caused by the fading channels, channel estimation is imperative. In present work, two main block-type pilot symbols assisted Least Square (LS) and Minimum Mean Square Error (MMSE) channel estimation techniques for two fading channel models, Rayleigh and Rician are implemented. The bit error rate characteristic performance for both estimators is compared for slow fading channel models with different symbol mapping techniques. The results show that the MMSE estimator has good performance for both Rayleigh and Rician channels as compared to LS estimator. However, MMSE estimator has higher complexity than that of LS.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128611732","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":"LED propeller display with android application","authors":"H. Kashyap, A. Jain, A. Shukla, Manisha Gururani","doi":"10.1109/ICECA.2017.8212800","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212800","url":null,"abstract":"This paper mainly emphasizes on the POV (Persistence of Vision) technology with the help some mechanical arrangement, LED, equipment required, and consequently general cost is sliced to extremely moderate cost. Additionally, support and repairing of the display is easy to the point for anybody having a little electronics education can deal with this. All the synchronizing can be executed through programming. It is made utilizing ATmega328 microcontroller, this project utilize the rule of Space Multiplexing and persistence of vision. This propeller display will be mechanically examined and shows the characters in advanced arrangement and data to be shown can be either fed by assembly level program or by an android application using Bluetooth. Produced using scrap it can be utilized anyplace and all over and the most astounding certainty about this propeller display is its perfectly clear. This propeller comprises of only 8 RGB LEDs which are arranged on to demonstrate the display. For building this project, necessity is only an Arduino board, a position encoder, and LEDs. This display can demonstrate the messages, which will require 665 LEDs. So equipment and cost minimization is accomplished.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128166991","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":"Neural network method through facial expression recognition","authors":"Kavita Kushwah, Vikrant Sharma, Upendra Singh","doi":"10.1109/ICECA.2017.8212721","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212721","url":null,"abstract":"Humans are capable to produce thousands of facial actions during communication that vary in intensity, complexity and meaning. The purpose of this paper is to recognize the human emotions in terms of happy, sad, surprise, neutral and disgust. Its aim is to recognize the facial expression stored in a database. It uses a set of single static image with different expression labels as the training database. The purposed system depends upon the human face, as we know face also reflects the human brain activities or emotions. In this paper, the neural network has been used for better results. In the end of the paper comparisons of existing Human Emotion Recognition System has been made with new one.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114262325","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":"Power management for electric vehicle with PID and Fuzzy logic controllers","authors":"S. K. Jha, A. Yadav, P. Gaur","doi":"10.1109/ICECA.2017.8212731","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212731","url":null,"abstract":"Electric vehicle technology is becoming increasingly important as it takes care of the environmental issues related to ICE vehicle and reduces the dependency on oil. Electric vehicle being greatly dependent on the limited electrical energy provided by a battery, the power flow efficiency is very important in this context. The major contribution of this work is to propose a power management strategy using PID controller and Fuzzy logic controller so that the performance of electric vehicle is comparable to that of an IC engine vehicle. This has been achieved for two processes, forward driving and regenerative braking using the principle of voltage matching. The system parameters observed are, namely: vehicle power, vehicle torque, vehicle speed, efficiency achieved, demand voltage, which have been simulated in time domain for input road torque and road speed. The result obtained from PID controlled system is compared to that of Fuzzy Logic controlled system.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114583641","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}
Ranjith, Saheer Anas, Ibrahim Badhusha, Zaheema Ot, K. Faseela, Minnuja Shelly
{"title":"Cloud based automated irrigation and plant leaf disease detection system using an android application","authors":"Ranjith, Saheer Anas, Ibrahim Badhusha, Zaheema Ot, K. Faseela, Minnuja Shelly","doi":"10.1109/ICECA.2017.8212798","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212798","url":null,"abstract":"Due to drastic climatic changes and scarcity of water, the need for proper and sustainable irrigation methods is of high demand. The water demand for plants varies from place to place with the changes in soil content, texture, climatic factors and so on. The plants need to be irrigated according to their water requirements at that climatic conditions. As like as the water requirements, plant diseases are also a factor that keeps the plants not growing properly. Also, a variety of plant leaf diseases have also been detected nowadays. In this paper, a novel smart irrigation system has been proposed which can control the irrigation automatically using an android mobile application. Apart from this, the photos of plant leaves are captured and are sent to the cloud server, which is further processed and compared with the diseased plant leaf images in the cloud database. Based on the comparison a list of plant diseases suspected are given to the user via the android mobile application.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125858253","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":"Stock market predication using a linear regression","authors":"Dinesh Bhuriya, Girish Kaushal, Ashish Sharma, Upendra Singh","doi":"10.1109/ICECA.2017.8212716","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212716","url":null,"abstract":"It is a serious challenge for investors and corporate stockholders to forecast the daily behavior of stock market which helps them to invest with more confidence by taking risks and fluctuations into consideration. In this paper, by applying linear regression for forecasting behavior of TCS data set, we prove that our proposed method is best to compare the other regression techniquemethod and the stockholders can invest confidentially based on that.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654424","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":"Ensuring data security in cloud based social networks","authors":"A. Praveena, S. Smys","doi":"10.1109/ICECA.2017.8212819","DOIUrl":"https://doi.org/10.1109/ICECA.2017.8212819","url":null,"abstract":"Nowadays, Online Social Networks is one of the important terms we hear, which allows its users to connect by various link types. Everyday application developers come up with new social networking sites. Consequently, these websites gain huge profit just by providing a platform for the users to communicate. It has already become an important integral part of our daily lives, enabling us to contact our friends and families on time. Since the count of the users of social networks is increasing drastically, storage of such huge amount of data is difficult to accomplish. As a solution, Cloud provides a platform to store this tiny amount of data. More and more social network data has been made publicly available and analyzed in one way or another. However, the issues in securing the data and privacy of users in cloud-based social networks persist. Users are unaware of these issues. They share various pictures, videos and personal data on the networking site which prevail even after deletion. But some of the information revealed is meant to be private hence social network data has led to the risk of leakage of confidential information of individuals. This is because they collect huge personal data and users take risks of trusting them. Since more personalized information is shared with the public, violating the privacy of a target user become much easier. Hence, security of the social networking data stored in the cloud is one of the major issues in cloud-based social networks. In this paper, we propose a framework for secure storing of data on the cloud-based social networks. The framework encrypts the data before storing it in the cloud, and the data is decrypted only with the private key of the user, making the data secure in the cloud. The proxy re-encryption scheme is used to re-encrypt the data to make it more secure.","PeriodicalId":222768,"journal":{"name":"2017 International conference of Electronics, Communication and Aerospace Technology (ICECA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125211485","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}