Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741485
A. Sharaf, Shameem Ansar A, Manu J. Pillai
Wireless sensor network consist of small sensing devices also known as nodes capable of sensing environmental and physical parameters like temperature, humidity etc. and send the information to a central node known as sink or base station. Since the sensors are limited in energy, minimizing the energy dissipation and increasing the network lifetime is the key challenge faced by wireless sensor networks. In WSN, cluster based routing schemes are used for reducing energy consumption by data aggregation at intermediate nodes. Various traditional and meta-heuristic approaches for clustering are already implemented. But finding an optimal clustering and routing path is an NP-hard problem. Meta-heuristic algorithms such as genetic algorithm can be used in large scale wireless sensor networks to find the optimal clustering and routing scheme. In this paper a detailed study of state-of-the art genetic algorithm based clustering techniques in wireless sensor networks with their objective, characteristics etc. are presented. Different parameters used for the construction of the fitness function are also analyzed.
{"title":"Genetic Algorithm Based Clustering Techniques in Wireless Sensor Networks: A Comprehensive Study","authors":"A. Sharaf, Shameem Ansar A, Manu J. Pillai","doi":"10.1109/ICIICT1.2019.8741485","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741485","url":null,"abstract":"Wireless sensor network consist of small sensing devices also known as nodes capable of sensing environmental and physical parameters like temperature, humidity etc. and send the information to a central node known as sink or base station. Since the sensors are limited in energy, minimizing the energy dissipation and increasing the network lifetime is the key challenge faced by wireless sensor networks. In WSN, cluster based routing schemes are used for reducing energy consumption by data aggregation at intermediate nodes. Various traditional and meta-heuristic approaches for clustering are already implemented. But finding an optimal clustering and routing path is an NP-hard problem. Meta-heuristic algorithms such as genetic algorithm can be used in large scale wireless sensor networks to find the optimal clustering and routing scheme. In this paper a detailed study of state-of-the art genetic algorithm based clustering techniques in wireless sensor networks with their objective, characteristics etc. are presented. Different parameters used for the construction of the fitness function are also analyzed.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131404793","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741354
Aarathi M R, Jini Raju
Image registration is considered as an important research direction in image processing and computer vision. Image registration is the method of arranging, matching and overlaying two or more images of a scene which are captured from similar scenes, but not same scenes. Images captured at different times from different viewpoint may vary in contrast, color or brightness. Image registration transfers the color style of target images to the reference image selected from one of these captured images. This paper evaluates the performance of different descriptors like SIFT, SURF, FREAK using SIFT, FREAK using SURF and CNN in generating matching images. Different performance measures like SSIM, MSSSIM, CSSS, MSE, PSNR, UQI and RMSE are used to compare the matching image with the input reference image to determine the visual quality and structural similarity. Experimental results show that FREAK using SURF outperforms other descriptors in the case of structural similarity and visual quality.
{"title":"Influence of Different Descriptors to Enhance Image Registration Techniques Using FREAK: Case Study","authors":"Aarathi M R, Jini Raju","doi":"10.1109/ICIICT1.2019.8741354","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741354","url":null,"abstract":"Image registration is considered as an important research direction in image processing and computer vision. Image registration is the method of arranging, matching and overlaying two or more images of a scene which are captured from similar scenes, but not same scenes. Images captured at different times from different viewpoint may vary in contrast, color or brightness. Image registration transfers the color style of target images to the reference image selected from one of these captured images. This paper evaluates the performance of different descriptors like SIFT, SURF, FREAK using SIFT, FREAK using SURF and CNN in generating matching images. Different performance measures like SSIM, MSSSIM, CSSS, MSE, PSNR, UQI and RMSE are used to compare the matching image with the input reference image to determine the visual quality and structural similarity. Experimental results show that FREAK using SURF outperforms other descriptors in the case of structural similarity and visual quality.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126635754","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}
Pub Date : 2019-04-01DOI: 10.1109/iciict1.2019.8741430
College of Engineering and Technology, Chennai (Approved by AICTE, Affiliated to Anna University, Chennai Accredited by NAAC with 'A' Grade ISO 9001:2015 Certified) College Road, Avadi, Chennai 600 054. Phone : 044 26558089 / 98402 68061 www.spcet.ac.in / email : idict2019@gmail.com St. Peter’s College of Engineering and Technology, Chennai (Approved by AICTE, A ffiliated to Anna University, Chennai Accredited by NAAC w ith 'A' Grade & ISO 9001:2015 Certified) College Road, Avadi, Chennai • 600 054.
{"title":"ICIICT 2019 Cover Page","authors":"","doi":"10.1109/iciict1.2019.8741430","DOIUrl":"https://doi.org/10.1109/iciict1.2019.8741430","url":null,"abstract":"College of Engineering and Technology, Chennai (Approved by AICTE, Affiliated to Anna University, Chennai Accredited by NAAC with 'A' Grade ISO 9001:2015 Certified) College Road, Avadi, Chennai 600 054. Phone : 044 26558089 / 98402 68061 www.spcet.ac.in / email : idict2019@gmail.com St. Peter’s College of Engineering and Technology, Chennai (Approved by AICTE, A ffiliated to Anna University, Chennai Accredited by NAAC w ith 'A' Grade & ISO 9001:2015 Certified) College Road, Avadi, Chennai • 600 054.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116274679","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741448
Dr.LAKSHMI PRABHA KARUPPIAH, S. Selvan
Delay Tolerant Networks(DTNs) characterized by long delays and intermittent connectivity provides communication even in areas, earlier considered inaccessible. Protocols meant for Internet cannot be used directly because of the above mentioned characteristics and the development of new protocols is important to improve the Quality of Service (QoS) of DTNs.Optimal Energy Consumption Protocol(OECP) for QoS improvement in DTNs is proposed. Number of encounters, residual hop count, expected delay and residual energy are the metrics considered to identify the next node to forward the message packet. Fuzzy logic is used to aggregate data of the above mentioned parameters, and this computational value is used to identify the forwarding node. The process of identifying the forwarding node is continued til the destination node is found.Simulation experiments done using NS 2 proves that OECP has higher packet delivery ratio and lower energy consumption, end to end delay, when compared with the two existing routing protocol for DTNs. Statistical analysis using one way ANOVA with Tukey HSD method was done to prove that proposed protocol has significant performance over the other two protocols Epidemic and OOF.
{"title":"Optimal Energy Consumption Protocol To Improve Qos In Delay Tolerant Networks","authors":"Dr.LAKSHMI PRABHA KARUPPIAH, S. Selvan","doi":"10.1109/ICIICT1.2019.8741448","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741448","url":null,"abstract":"Delay Tolerant Networks(DTNs) characterized by long delays and intermittent connectivity provides communication even in areas, earlier considered inaccessible. Protocols meant for Internet cannot be used directly because of the above mentioned characteristics and the development of new protocols is important to improve the Quality of Service (QoS) of DTNs.Optimal Energy Consumption Protocol(OECP) for QoS improvement in DTNs is proposed. Number of encounters, residual hop count, expected delay and residual energy are the metrics considered to identify the next node to forward the message packet. Fuzzy logic is used to aggregate data of the above mentioned parameters, and this computational value is used to identify the forwarding node. The process of identifying the forwarding node is continued til the destination node is found.Simulation experiments done using NS 2 proves that OECP has higher packet delivery ratio and lower energy consumption, end to end delay, when compared with the two existing routing protocol for DTNs. Statistical analysis using one way ANOVA with Tukey HSD method was done to prove that proposed protocol has significant performance over the other two protocols Epidemic and OOF.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114534920","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741481
V. Ceronmani Sharmila, S. Monesh, R. Aayush, G. Karesh, I. Ibrahim
Smart Card technology is used to getting the ticket by withdrawing money from passenger’s e-wallet inside the smart card instead of transaction of direct money, loss of coin change is prevented. The smart card is scanned using the app by the conductor and after entry of passenger details the device will generate the tickets and money will be directly debited from their E-wallets. This technology is processed by the module in which the fare calculations are programmed. In addition to this a new feature is added that is if the passenger doesn’t buy the tickets within a specific time a beep sound will be emitted and the particular person must buy the tickets. By this many frauds can be stopped.
{"title":"Digitized Bus Ticketing Framework","authors":"V. Ceronmani Sharmila, S. Monesh, R. Aayush, G. Karesh, I. Ibrahim","doi":"10.1109/ICIICT1.2019.8741481","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741481","url":null,"abstract":"Smart Card technology is used to getting the ticket by withdrawing money from passenger’s e-wallet inside the smart card instead of transaction of direct money, loss of coin change is prevented. The smart card is scanned using the app by the conductor and after entry of passenger details the device will generate the tickets and money will be directly debited from their E-wallets. This technology is processed by the module in which the fare calculations are programmed. In addition to this a new feature is added that is if the passenger doesn’t buy the tickets within a specific time a beep sound will be emitted and the particular person must buy the tickets. By this many frauds can be stopped.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114658775","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741439
Vidya Moni
The objective of this research was to generate an indicator of global political stability, by predicting the annual S&P 500 stock market index. This was done through machine learning, using a genetic programming approach, creating an algorithm with a template that takes into account the previous years' data of S&P 500 stock index, gold prices, the number of casualties in U.S. wars, crude oil prices, Dow Jones Industrial Average and rates of inflation in U.S. The prediction of this algorithm was highly accurate, within 14%.
{"title":"Machine Learning to Predict Annual Stock Market Index - a Genetic Programming Approach","authors":"Vidya Moni","doi":"10.1109/ICIICT1.2019.8741439","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741439","url":null,"abstract":"The objective of this research was to generate an indicator of global political stability, by predicting the annual S&P 500 stock market index. This was done through machine learning, using a genetic programming approach, creating an algorithm with a template that takes into account the previous years' data of S&P 500 stock index, gold prices, the number of casualties in U.S. wars, crude oil prices, Dow Jones Industrial Average and rates of inflation in U.S. The prediction of this algorithm was highly accurate, within 14%.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128944098","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741483
S. Arivazhagan, W. L. Lilly Jebarani, R. Newlin Shebiah, S. Vineth Ligi, P. V. Hareesh Kumar, K. Anilkumar
Synthetic Aperture Radar images have potential applications in the surveillance scenario and hence automated target detection algorithms prove to be a useful tool in monitoring and crime control as well as in marine traffic management. The advancements in marine trade have lead to the increase in the number of ships in the world waters. The usage of satellite-based radar images have become well known for maritime surveillance as ship detection is relatively simple and independent of the climatic conditions. Ships can be easily discerned in the SAR images due to their bright intensity which results due to the strong radar backscatter from their metal surface. These are the significant pixels in an image which can be gathered to detect the ship targets. During heavy sea state conditions and presence of speckle noise, sea ice and coastline structure, the ship detection process is affected since these non-ship features in the sea also exhibit high intensities in the SAR image. These false alarms have to be reduced. So, in this work a Significance based ship detection algorithm followed by a discrimination stage using ensemble classifier is proposed to differentiate the ship and non-ship targets. To enhance the ship detection process, the images are subjected to ridgelet transform based despeckling. The efficacy of the proposed Significance based target detection is proved by the obtained results.
{"title":"Significance based Ship Detection from SAR Imagery","authors":"S. Arivazhagan, W. L. Lilly Jebarani, R. Newlin Shebiah, S. Vineth Ligi, P. V. Hareesh Kumar, K. Anilkumar","doi":"10.1109/ICIICT1.2019.8741483","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741483","url":null,"abstract":"Synthetic Aperture Radar images have potential applications in the surveillance scenario and hence automated target detection algorithms prove to be a useful tool in monitoring and crime control as well as in marine traffic management. The advancements in marine trade have lead to the increase in the number of ships in the world waters. The usage of satellite-based radar images have become well known for maritime surveillance as ship detection is relatively simple and independent of the climatic conditions. Ships can be easily discerned in the SAR images due to their bright intensity which results due to the strong radar backscatter from their metal surface. These are the significant pixels in an image which can be gathered to detect the ship targets. During heavy sea state conditions and presence of speckle noise, sea ice and coastline structure, the ship detection process is affected since these non-ship features in the sea also exhibit high intensities in the SAR image. These false alarms have to be reduced. So, in this work a Significance based ship detection algorithm followed by a discrimination stage using ensemble classifier is proposed to differentiate the ship and non-ship targets. To enhance the ship detection process, the images are subjected to ridgelet transform based despeckling. The efficacy of the proposed Significance based target detection is proved by the obtained results.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121860676","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741357
N. P, Faheem Ali T
Nowadays high gain boost converters are efficient for many applications. This work introduces a high gain ultra boost converter with voltage regulation by increasing voltage gain and reducing voltage stress across the switch. This converter uses an autotransformer with coupled inductor integrating on the same core to achieve high output voltage about ten times of input voltage without using endmost duty cycle. And also a Switched/Diode voltage multiplier cell is using in coupled magnetic circuit to recycle the leakage energy. Methods used here for voltage regulations are Line regulation and Reference regulation. The simulation of proposed converter is verified using MATLAB/SIMULINK software. Modes of operation and analysis of the converter are also discussed.
{"title":"High Gain Ultra Boost Converter With Voltage Regulation","authors":"N. P, Faheem Ali T","doi":"10.1109/ICIICT1.2019.8741357","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741357","url":null,"abstract":"Nowadays high gain boost converters are efficient for many applications. This work introduces a high gain ultra boost converter with voltage regulation by increasing voltage gain and reducing voltage stress across the switch. This converter uses an autotransformer with coupled inductor integrating on the same core to achieve high output voltage about ten times of input voltage without using endmost duty cycle. And also a Switched/Diode voltage multiplier cell is using in coupled magnetic circuit to recycle the leakage energy. Methods used here for voltage regulations are Line regulation and Reference regulation. The simulation of proposed converter is verified using MATLAB/SIMULINK software. Modes of operation and analysis of the converter are also discussed.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123347752","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}
Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741470
M. Surekha, S. M. Roomi, J. Vignesh Kanna, S. M. Ebenezer
In hilly regions, frequent drizzling interrupts the daily activities of human beings and can also be deceptive. In this work, we develop a feature descriptor by Histogram of Radon Projection (HRP) to detect drizzle/rain. To compute this feature descriptor, initially we detect fine edges in an image utilizing the sobel gradient operator. Then the resultant image is divided into smaller cells and for each cell we estimate the count of radon transform values for different orientations and the weighted average for each transform coefficients are accumulated into bins. Finally, we use this radon feature descriptor to detect whether drizzling occurs in a given frame or not using Support Vector Machine (SVM).
{"title":"Drizzle Detection through Histogram of Radon Projection (HRP)","authors":"M. Surekha, S. M. Roomi, J. Vignesh Kanna, S. M. Ebenezer","doi":"10.1109/ICIICT1.2019.8741470","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741470","url":null,"abstract":"In hilly regions, frequent drizzling interrupts the daily activities of human beings and can also be deceptive. In this work, we develop a feature descriptor by Histogram of Radon Projection (HRP) to detect drizzle/rain. To compute this feature descriptor, initially we detect fine edges in an image utilizing the sobel gradient operator. Then the resultant image is divided into smaller cells and for each cell we estimate the count of radon transform values for different orientations and the weighted average for each transform coefficients are accumulated into bins. Finally, we use this radon feature descriptor to detect whether drizzling occurs in a given frame or not using Support Vector Machine (SVM).","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122922593","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}
Pub Date : 2019-04-01DOI: 10.1109/iciict1.2019.8741471
{"title":"ICIICT 2019 Table of Contents","authors":"","doi":"10.1109/iciict1.2019.8741471","DOIUrl":"https://doi.org/10.1109/iciict1.2019.8741471","url":null,"abstract":"","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"29 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124142352","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}
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