Pub Date : 2019-04-01DOI: 10.1109/ICIICT1.2019.8741502
S. S. S., Shameem Ansar A, Manu J. Pillai
Wireless Sensor Networks have a great impact in day to day life of a human being because of its self-learning and processing capability. Every system is changing to autonomous due to the introduction of such networks. Real time monitoring of agricultural system, hospital system, healthcare, vehicular system etc. become very easy and could reduce the interference of human beings to such systems due to the evolution of Wireless Sensor Networks. Nodes in these networks have limited power to operate and we need to reduce the power consumption and maximize the lifetime. Formation of clusters in such networks can help each node to operate and communicate in an energy efficient manner. There are several clustering techniques are available in such networks, according to the applications.
{"title":"LEACH based clustering protocols in Wireless Sensor Networks","authors":"S. S. S., Shameem Ansar A, Manu J. Pillai","doi":"10.1109/ICIICT1.2019.8741502","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741502","url":null,"abstract":"Wireless Sensor Networks have a great impact in day to day life of a human being because of its self-learning and processing capability. Every system is changing to autonomous due to the introduction of such networks. Real time monitoring of agricultural system, hospital system, healthcare, vehicular system etc. become very easy and could reduce the interference of human beings to such systems due to the evolution of Wireless Sensor Networks. Nodes in these networks have limited power to operate and we need to reduce the power consumption and maximize the lifetime. Formation of clusters in such networks can help each node to operate and communicate in an energy efficient manner. There are several clustering techniques are available in such networks, according to the applications.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"77 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":"116985497","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/ICIICT1.2019.8741435
S. Sithara Fairooz, K.T Haneesh Babu
Normally application driven by low power source must require an energy conversion system to meet its load demand. This paper presents a buck boost inverter which possess high gain and does conversions in single stage itself. This inverter deploy a coupled inductor to attain high gain. This topology have diverse benefits like moderate losses while switching and size is densed. Modes of operation and theoretical analysis are given. Verified MATLAB/SIMULINK results are also given.
{"title":"A single phase coupled inductor based buck boost inverter","authors":"S. Sithara Fairooz, K.T Haneesh Babu","doi":"10.1109/ICIICT1.2019.8741435","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741435","url":null,"abstract":"Normally application driven by low power source must require an energy conversion system to meet its load demand. This paper presents a buck boost inverter which possess high gain and does conversions in single stage itself. This inverter deploy a coupled inductor to attain high gain. This topology have diverse benefits like moderate losses while switching and size is densed. Modes of operation and theoretical analysis are given. Verified MATLAB/SIMULINK results are also given.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"5 4 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":"117030318","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/ICIICT1.2019.8741418
S. Shoba, R. Rajavel
Fusion plays an important role to retrieve the single output data from the input data set and in turn improves the quality of the results. Single channel based separation of speech process is to separate the utter speech from the composite speech recorded with a single mic. This research work proposed a weight fusion scheme to combine the voiced matrix and unvoiced speech matrix obtained using feature based single channel speech separation systems. The voiced segment matrix obtained using periodicity features and unvoiced segment matrix obtained using onset/offset feature are combined using the proposed weight fusion principle. The proposed system is evaluated using the standard speech and noise database. The experimental outcome results of the weight fusion system reveal that there is a better improvement than the other speech separation systems
{"title":"Weight Fusion Scheme for single channel based CASA system","authors":"S. Shoba, R. Rajavel","doi":"10.1109/ICIICT1.2019.8741418","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741418","url":null,"abstract":"Fusion plays an important role to retrieve the single output data from the input data set and in turn improves the quality of the results. Single channel based separation of speech process is to separate the utter speech from the composite speech recorded with a single mic. This research work proposed a weight fusion scheme to combine the voiced matrix and unvoiced speech matrix obtained using feature based single channel speech separation systems. The voiced segment matrix obtained using periodicity features and unvoiced segment matrix obtained using onset/offset feature are combined using the proposed weight fusion principle. The proposed system is evaluated using the standard speech and noise database. The experimental outcome results of the weight fusion system reveal that there is a better improvement than the other speech separation systems","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"1 4 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":"125918645","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/ICIICT1.2019.8741491
Rohit Pathar, Abhishek Adivarekar, Arti Mishra, A. Deshmukh
The human emotion recognition has attracted interest of many problem solvers in the field of artificial intelligence. The emotions on a human face say so much about our thought process and give a glimpse of what's going on inside the mind. Real time emotion recognition is to acquaint the machine with human like ability to recognize and analyse human emotions. This project aims to categorize a facial image into one of the seven emotions which we are considering in this study, by building a multi class classifier. In this paper we are using convolutional neural networks (CNNs) for training over gray scale images obtained from fer2013 dataset. We experimented with different depths and max pooling layers to get the best accuracy and ultimately achieving 89.98% accuracy. To combat overfitting, we have used technique like dropout. We are also analyzing the performance of different network architectures like shallow network and modern deep network in recognizing human emotion. We also present the real-time implementation of emotion recognition in web-camera which provides accurate results for multiple faces simultaneously. The results obtained from the research are quite interesting.
{"title":"Human Emotion Recognition using Convolutional Neural Network in Real Time","authors":"Rohit Pathar, Abhishek Adivarekar, Arti Mishra, A. Deshmukh","doi":"10.1109/ICIICT1.2019.8741491","DOIUrl":"https://doi.org/10.1109/ICIICT1.2019.8741491","url":null,"abstract":"The human emotion recognition has attracted interest of many problem solvers in the field of artificial intelligence. The emotions on a human face say so much about our thought process and give a glimpse of what's going on inside the mind. Real time emotion recognition is to acquaint the machine with human like ability to recognize and analyse human emotions. This project aims to categorize a facial image into one of the seven emotions which we are considering in this study, by building a multi class classifier. In this paper we are using convolutional neural networks (CNNs) for training over gray scale images obtained from fer2013 dataset. We experimented with different depths and max pooling layers to get the best accuracy and ultimately achieving 89.98% accuracy. To combat overfitting, we have used technique like dropout. We are also analyzing the performance of different network architectures like shallow network and modern deep network in recognizing human emotion. We also present the real-time implementation of emotion recognition in web-camera which provides accurate results for multiple faces simultaneously. The results obtained from the research are quite interesting.","PeriodicalId":118897,"journal":{"name":"2019 1st International Conference on Innovations in Information and Communication Technology (ICIICT)","volume":"53 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":"126958024","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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