{"title":"MAQ system development in mobile ad-hoc networks using mobile agents","authors":"Mamata Rath, M. R. Panda","doi":"10.1109/IC3I.2016.7918791","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918791","url":null,"abstract":"To furnish protected and efficient routine activities in cluster based Mobile Adhoc Networks (MANETs), a Mobile Agent based QoS (MAQ) scheme using clustering algorithm for real time data communication has been designed in this paper. A Mobile agent architecture is projected in a way that it remains associated with the cluster head of every cluster and when real time application gets notified in these clusters then the proposed system gets activated to hold up prioritized service to these applications including checking and monitoring the flow qualities for real time applications. JADE (Java Agent Development Environment) based prioritized proposal at the mobile agent has been implemented in the proposed system. As this is an application oriented approach, so the overall network performance significantly improves resulting better throughput and packet delivery ratio. Prioritized functionalities relating to end-to-end delay, jitter in video streaming and power saving policies during real-time data transmission are controlled by operational modules defined in the mobile agent.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130218817","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":"Cut detection and secure routing in wireless sensor networks","authors":"Pradnya Wagh, Pratik Mahamuni, Kaustubh Rajeshirke","doi":"10.1109/IC3I.2016.7917949","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917949","url":null,"abstract":"Wireless sensor network will become isolated in various associated segments because of the disappointment of some of its hubs, which is known as a “cut”. In this paper, authors acknowledge the issue of distinguishing cuts by the remaining hubs of a wireless sensor network. System proposes an estimation which grants every hub to identify at the time of accessibility to an extremely assigned hub has been lost, and one or more hubs (that are connected with the unique hub after the cut) to recognize the cut's event. The calculation is passed on and strange: every hub needs to relate with simply those hubs that are within its correspondence range. The estimation relies on upon the iterative calculation of an invented “electrical potential” of the hubs. The combining rate of the concealed iterative arrangement is self-governing of the size as well as network structure. Also this system implements a lightweight encryption algorithm to rout data securely in the network and enhance the system performance.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134541355","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":"Named entity recognition model for Punjabi language: A survey","authors":"Pawandeep Kaur, Amandeep Kaur","doi":"10.1109/IC3I.2016.7919047","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7919047","url":null,"abstract":"Information extraction is the sub topic of Artificial Intelligence method. Recognition of named entity tags for computer using NLP (Natural language processing) is very important. It is very first step in recognition of unstructured content. For classification and identification of given number of tasks for any data, named entity recognition can be used as a subtask for extraction of information. There are numerous methods that help in applying NE process. In this paper various methods of NER have been presented and various issues related to Punjabi language has been discussed.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131618334","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":"Rough-set and artificial neural networks based image classification","authors":"D. Vasundhara, M. Seetha","doi":"10.1109/IC3I.2016.7917931","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917931","url":null,"abstract":"Spatial image classification meant to the mechanism of extracting meaningful knowledge information classes from spatial images dataset. Many traditional pixel based image classification techniques such as Support Vector Machines (SVM), ANN, Fuzzy methods, Decision Trees (DT) etc. exist. The performance and accuracy of these image classification methods depends upon the network structure and number of inputs. Here, in this paper, we have proposed an step-wise mechanism to significantly improve the classification performance of neural network, that uses rough sets approach for purpose of features/attributes selection of image pixels. The complexity analysis of the proposed algorithm and the comparison of mechanism, presented here, with existing classification techniques based on features over the interest area is carried out.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131742057","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":"Integration of PLC based offline impedance matching system for ICRH experiments","authors":"R. Joshi, H. M. Jadav, A. Mali, S. Kulkarni","doi":"10.1109/IC3I.2016.7918027","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918027","url":null,"abstract":"Ion Cyclotron Resonance Heating (ICRH) system has two different impedance matching systems for RF transmission. One is offline matching which has been used before applying the experimental shots. Another is online impedance matching which has been used during experimental shot. Offline matching network consists of two coarse tuner, static stubs and coarse phase shifter which are identical in both the transmission lines. There are motorized arrangement installed in each stubs and phase shifters. Both static and coarse stubs are used to vary length in order to match the source impedance with load impedance. Phase shifter is used for matching impedance via varying the phase of the power. Programmable Logic Controller (PLC) based instrumentation has been implemented for the system. Offline matching should be operated below 1 kHz frequency in order to move stepper motors using square pulses employed to motor controller. In existing system this operation has been carried out by VME instrumentation and control. In order to reduce load on VME, PLC based system has been designed and integrated with VME based DAC. SIMATIC Windows Control Center (WinCC) software has been used as SCADA i.e. front end user interface. WinCC SCADA can communicate with OPC (Open Process Control) server using different PLC signals. This paper describes technical details, design and development of PLC based offline impedance matching system using WinCC as SCADA. The developed system has proved accurate and reliable in use of application as per system requirement. The SCADA system also shows motor frequency and motor speed profile with upper and lower limits. It logs data at the end of operation by which it retrieve the last run status of each motor when it starts again.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132635343","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":"Routing in WSN network using neural Network (NN) and SPEED protocol","authors":"Manpreet Kaur, Anjana Sharma","doi":"10.1109/IC3I.2016.7917952","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917952","url":null,"abstract":"Routing stands for the sending the required data to the destination in such a manner that it reaches efficiently with high throughput and accuracy. The data is transferring over the network each sensor use some energy in receiving data, sending data. The life of the network depend how much energy used up in each transmission. The problem occurs when the transmission path meets with some sort of failure like path failure or node goes to sleep mode. The focus, however, has been given to the routing protocols which might differ depending on the application and network architecture. In this paper, we have proposed the state-of-the-art routing technique using SPEED protocol and NN technique to choose an alternative path in WSNs.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130869370","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":"A defensive timestamp approach to detect and mitigate the Sybil attack in vanet","authors":"Shikha Sharma, Shivani Sharma","doi":"10.1109/IC3I.2016.7917994","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917994","url":null,"abstract":"Sybil attack is an encounter in which the personality of a assaulter is contaminated into huge number of incognito personality which is produced to build up the route of the network. In this paper, we deliberate the timestamp approach for Sybil attack in associated system, self correlate network, and cordial network system. Also assorted mechanisms to extenuate the Sybil attack are evaluated, we have proposed timestamp approach for prevention and detection of Sybil attack. We have compared our result with EBRS Approach our approach shows better results as compared to previous approach.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115410705","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}
Anita Chaudhari, Brinzel Rodrigues, Shraddha S. More
{"title":"Automated IOT based system for home automation and prediction of electricity usage and comparative analysis of various electricity providers: SmartPlug","authors":"Anita Chaudhari, Brinzel Rodrigues, Shraddha S. More","doi":"10.1109/IC3I.2016.7917995","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7917995","url":null,"abstract":"Energy crisis is one of the prime challenges being faced by many of the countries in the world today. Industrial development and population growth has tremendously increased the demand for energy to a huge extent. Many researchers and developers have come up with effective systems so as deal with this problem. A lot of techniques have been suggested such as an Energy monitoring system which is an efficient technique to monitor the devices present inside a house or industries and provide notification about their abnormal behavior. Main aim of this project is to design a SmartPlug: energy monitoring and control system which can control the devices, show power consumed by the devices and calculate electricity bills based on the total energy usage depending upon different vendors available. Our system includes a Raspberry pi, Arduino board and sensors which will be connected to each and every device. We have developed a website so that the user can just login and have information about the energy consumption by all the devices. A graphical representation of the power consumed by the devices will make the user aware if power consumed by any device exceeds a certain level. This system can reduce the electricity bills to a large extent and will prove beneficial for the users as well. It is not restricted to limited devices and thus can also be used in industries by using more Raspberry pi micro-controllers.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115578177","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}
M. Sajjan, Lingangouda Kulkarni, B. Anami, N. G. Gaddagimath
{"title":"A comparative analysis of color features for classification of bulk chilli","authors":"M. Sajjan, Lingangouda Kulkarni, B. Anami, N. G. Gaddagimath","doi":"10.1109/IC3I.2016.7918002","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918002","url":null,"abstract":"The Paper work presents an approaches to classify chilli class from their bulk sample chilli images using RGB and HSI and L∗a∗b Model colour features. A rule based algorithm is implemented taking into account, best RGB, HSI and L∗a∗b colour features, 9 colour features were computed for R-(red), G-(green), B-(Blue), H-(hue), S-(saturation), I-(intensity), L-(brightness), a-(chromaticity layer red&green), b-(chromaticity layer blue&yellow) images from each image samples. Best features were used as an input to classifier and tests were performed to identify best classification model. R-Average, Hue-Average, a-average Hue-mean, L∗_mean, a∗_mean and standard deviation values are considered for Rule Based Classification, We have considered four different varieties of Chilli, with stalk and without stalk. The recognition rate for RGB colour features chilli with stalk is 70.% and for chilli without stalk is 85% is obtained. The recognition rate for HSI colour features, chilli with stalk is 80% and for chilli without stalk is 90% is obtained. The recognition rate for L∗a∗b colour features chilli with stalk is 85% and for chilli without stalk is 95% is obtained.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115795191","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}
M. J. Yashaswini, V. S. Vishnu, B N Annapuma, Tanik R Prasad
{"title":"The performance of multi-layer neural network on face recognition system","authors":"M. J. Yashaswini, V. S. Vishnu, B N Annapuma, Tanik R Prasad","doi":"10.1109/IC3I.2016.7918000","DOIUrl":"https://doi.org/10.1109/IC3I.2016.7918000","url":null,"abstract":"Biometrics and Pattern Recognition have various applications that are found and brought into real-time application use. Face recognition consist mainly of three stages namely: Pre-processing, Feature Extraction and Classification. Neural Networks basically deals with adaptation, classification and rendering noisy values to optimal solution. In this work we illustrate performance and accuracy of the above approaches. Subspace is a plane embedded in a higher dimensional vector space, PCA is a standout amongst the best systems that have been utilized in image recognition and compression while KPCA is utilized in ascertaining PCA conversion in a mapping space by a nonlinear mapping function. FFNN is used for pattern recognition, FNN frequently have at least one hidden layers of sigmoid neurons followed by a yield layer of linear neurons. Multiple layers of neurons with nonlinear transfer function permits the system to learn connections amongst information and yield vectors. LVQ learn to characterize input vectors into target classes picked by the user.","PeriodicalId":305971,"journal":{"name":"2016 2nd International Conference on Contemporary Computing and Informatics (IC3I)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124581214","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}