Pub Date : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974505
S. Parihar, S. Borana, S. K. Yadav
Remote sensing data increasingly used to identify and map open water bodies at comprehensive scales. The Jodhpur city experienced high urbanization in last one decade with population about 13Lakhs, and therefore needs effective public amenities alongwith safe water. In this research, compared accessible surface water bodies mapping approaches using seven spectral indices, viz. normalized difference water index (NDWI), tasseled cap wetness index (TCW), automated water extraction index (AWEIsh and AWEInsh), modified normalized difference water index (MNDWI), Water ratio index (WRI) and normalized difference vegetation index (NDVI) as well as two medium resolution sensors (Sentinel-2A and Landsat 8 OLI). The combinations of different water algorithms and satellite sensors were used to evaluate accuracy of the open water body. The results confirmed that water algorithms have high accuracies with Kappa Coefficients ranging from 0.12 to 0.98. The MNDWI water algorithms performed better than other water indices algorithms, and could be associated with pure water dominance in study area.The resultant water mapping from Sentinel-2A (10m) data has superior accuracies than Sentinel-2 (20m) and Landsat 8 OLI (30m). This research illustrates the enhanced performance in Sentinel-2A (10m) and Sentinel-2A (20m) for mapping of water body. The present study shows the availability of alternate water resources, which shall also be useful during frequent maintenance work of Rajeev Gandhi canal which supply water to whole city. The nearest neighbour technique is used to resample Sentibel-2A (10m) data of the visible and near IR bands to 20 m resolution bands to perform further analysis and comparisons.
{"title":"Comparative Evaluation of Spectral Indices and Sensors for Mapping of Urban Surface Water Bodies in Jodhpur Area : Smart & Sustainable Growth","authors":"S. Parihar, S. Borana, S. K. Yadav","doi":"10.1109/ICCCIS48478.2019.8974505","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974505","url":null,"abstract":"Remote sensing data increasingly used to identify and map open water bodies at comprehensive scales. The Jodhpur city experienced high urbanization in last one decade with population about 13Lakhs, and therefore needs effective public amenities alongwith safe water. In this research, compared accessible surface water bodies mapping approaches using seven spectral indices, viz. normalized difference water index (NDWI), tasseled cap wetness index (TCW), automated water extraction index (AWEIsh and AWEInsh), modified normalized difference water index (MNDWI), Water ratio index (WRI) and normalized difference vegetation index (NDVI) as well as two medium resolution sensors (Sentinel-2A and Landsat 8 OLI). The combinations of different water algorithms and satellite sensors were used to evaluate accuracy of the open water body. The results confirmed that water algorithms have high accuracies with Kappa Coefficients ranging from 0.12 to 0.98. The MNDWI water algorithms performed better than other water indices algorithms, and could be associated with pure water dominance in study area.The resultant water mapping from Sentinel-2A (10m) data has superior accuracies than Sentinel-2 (20m) and Landsat 8 OLI (30m). This research illustrates the enhanced performance in Sentinel-2A (10m) and Sentinel-2A (20m) for mapping of water body. The present study shows the availability of alternate water resources, which shall also be useful during frequent maintenance work of Rajeev Gandhi canal which supply water to whole city. The nearest neighbour technique is used to resample Sentibel-2A (10m) data of the visible and near IR bands to 20 m resolution bands to perform further analysis and comparisons.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122127749","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974528
Chinkit Manchanda, Rajat Rathi, Nikhil Sharma
Traffic congestion is a common affair in the big cities and towns. This issue is the outcome of the rapid increase in the population and increasing number of vehicles, so predicting the level of traffic congestion will be beneficial for every individual. However, interpretation and implementation of traffic state can be exceptionally tough. With this pace of increasing vehicles, existing algorithms may come up with some limitations due to various aspects of features which we cannot process. In this paper, we introduce a Hybrid Deep Neural Network (HDNN) for forecasting the traffic conditions on roads with the images using Convolutional Neural Network (CNN) and predicting road accident statistics of a particular area on a specific time. This model will exploit the development of algorithms in machine learning and majorly grasping over the Deep learning algorithm CNN. Experimental results show superior results of traffic conditions prediction and road accidentsanalysis, HDNN outshine the standard benchmark for the level of traffic congestion.
{"title":"Traffic Density Investigation & Road Accident Analysis in India using Deep Learning","authors":"Chinkit Manchanda, Rajat Rathi, Nikhil Sharma","doi":"10.1109/ICCCIS48478.2019.8974528","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974528","url":null,"abstract":"Traffic congestion is a common affair in the big cities and towns. This issue is the outcome of the rapid increase in the population and increasing number of vehicles, so predicting the level of traffic congestion will be beneficial for every individual. However, interpretation and implementation of traffic state can be exceptionally tough. With this pace of increasing vehicles, existing algorithms may come up with some limitations due to various aspects of features which we cannot process. In this paper, we introduce a Hybrid Deep Neural Network (HDNN) for forecasting the traffic conditions on roads with the images using Convolutional Neural Network (CNN) and predicting road accident statistics of a particular area on a specific time. This model will exploit the development of algorithms in machine learning and majorly grasping over the Deep learning algorithm CNN. Experimental results show superior results of traffic conditions prediction and road accidentsanalysis, HDNN outshine the standard benchmark for the level of traffic congestion.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127502250","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974483
Amandeep Kaur, D. Chahal, LATIKA KHARB
With the advent of LPG Policy many foreign firms have invested in India and home country firms too have expanded their operations outside the nation which results in greater inflow and outflow of foreign currency and INR giving rise to currency fluctuations, these fluctuations were exposed to more volatility after the US financial crisis of 2008. The increased risk exposure can be mitigated by employing techniques such as hedging, speculation and by using instruments like Futures and Forward contracts. Currency futures have been considered as the best instruments for managing risk against foreign currency exchange rate volatility. Keeping this into consideration the present paper analyses the efficiency of random walk hypothesis by testing currency futures in weak form efficiency post financial crisis of 2008. The sample includes the monthly closing price indices for the period January 2009 to March 2019. The hypothesis tested is whether the currency futures USD/INR are weak form efficient. Statistical tools employed in the study encompasses Runs Test, Autocorrelation Function, Kolmogorov-Smirnov Test (K-S Test), Augmented Dickey Fuller Test (ADF Test), and Ljung Box Test. The results of the employed tests provide evidence on the non-randomness of the time series.
{"title":"Weak Form Efficiency Of Currency Futures: Evidence From India","authors":"Amandeep Kaur, D. Chahal, LATIKA KHARB","doi":"10.1109/ICCCIS48478.2019.8974483","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974483","url":null,"abstract":"With the advent of LPG Policy many foreign firms have invested in India and home country firms too have expanded their operations outside the nation which results in greater inflow and outflow of foreign currency and INR giving rise to currency fluctuations, these fluctuations were exposed to more volatility after the US financial crisis of 2008. The increased risk exposure can be mitigated by employing techniques such as hedging, speculation and by using instruments like Futures and Forward contracts. Currency futures have been considered as the best instruments for managing risk against foreign currency exchange rate volatility. Keeping this into consideration the present paper analyses the efficiency of random walk hypothesis by testing currency futures in weak form efficiency post financial crisis of 2008. The sample includes the monthly closing price indices for the period January 2009 to March 2019. The hypothesis tested is whether the currency futures USD/INR are weak form efficient. Statistical tools employed in the study encompasses Runs Test, Autocorrelation Function, Kolmogorov-Smirnov Test (K-S Test), Augmented Dickey Fuller Test (ADF Test), and Ljung Box Test. The results of the employed tests provide evidence on the non-randomness of the time series.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"21 23","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114049965","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974537
V. Rohilla, Ms Sanika Singh kumar, Sudeshna Chakraborty, Ms. Sanika Singh
Clustering is one the one of the most important technique of data mining. It is used in many applications like fraud detection, image processing, bioinformatics etc. It has been used in various domains. Many types of the clustering techniques are the following like hierarchical, partitional, spectral clustering, density clustering, grid clustering, model based clustering etc. Bisecting K-Means comes under partitional clustering. It gives better performane, when huge data is used. There are many approached that are developed in the similar domain.One of the technique is Text Mining through which useful information is extracted through text. One of the important concept is statistical pattern mining through which important information is extracted by planning different trends and patterns. Input text patterns are structured that are derived from structured data and corresponding output is generated. The steps of text mining are categories of text, clustering text, extraction, summarization of text, E-R modeling. The various steps of text analysis are retrieval of information, lex. analysis for distribution of word freq. distribution study, recognition of pattern,tagging, extraction of information, techniques of data mining and also link analysis, association, visual. and predictive analyt. In the given paper bisect. K Means algorithm is presented which has the features of k-Means and hierar. clustering.
{"title":"Data Clustering using Bisecting K-Means","authors":"V. Rohilla, Ms Sanika Singh kumar, Sudeshna Chakraborty, Ms. Sanika Singh","doi":"10.1109/ICCCIS48478.2019.8974537","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974537","url":null,"abstract":"Clustering is one the one of the most important technique of data mining. It is used in many applications like fraud detection, image processing, bioinformatics etc. It has been used in various domains. Many types of the clustering techniques are the following like hierarchical, partitional, spectral clustering, density clustering, grid clustering, model based clustering etc. Bisecting K-Means comes under partitional clustering. It gives better performane, when huge data is used. There are many approached that are developed in the similar domain.One of the technique is Text Mining through which useful information is extracted through text. One of the important concept is statistical pattern mining through which important information is extracted by planning different trends and patterns. Input text patterns are structured that are derived from structured data and corresponding output is generated. The steps of text mining are categories of text, clustering text, extraction, summarization of text, E-R modeling. The various steps of text analysis are retrieval of information, lex. analysis for distribution of word freq. distribution study, recognition of pattern,tagging, extraction of information, techniques of data mining and also link analysis, association, visual. and predictive analyt. In the given paper bisect. K Means algorithm is presented which has the features of k-Means and hierar. clustering.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128495219","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974495
J. Kaur, J. Singh
For processing any natural language processing application, the knowledge of structure of sentence including its boundaries plays a vital role. Incorrect sentence boundary may lead to wrong outputs and hence decreasing the performance of NLP systems. Detecting sentence boundaries in code mixed social media text is not an easy task. People generally omits the boundary markers and use punctuation for other stylistic tasks. We propose a deep neural network approach for sentence boundary marking as well as suggesting appropriate punctuation mark in code mixed social media text. We experimented with single layer bidirectional and two layer bidirectional models. Both word sequence and character sequence are experimented. Bidirectional model using character sequence out performs all other models for sentence boundary detection as well as end marker suggestion.
{"title":"Deep Neural Network Based Sentence Boundary Detection and End Marker Suggestion for Social Media Text","authors":"J. Kaur, J. Singh","doi":"10.1109/ICCCIS48478.2019.8974495","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974495","url":null,"abstract":"For processing any natural language processing application, the knowledge of structure of sentence including its boundaries plays a vital role. Incorrect sentence boundary may lead to wrong outputs and hence decreasing the performance of NLP systems. Detecting sentence boundaries in code mixed social media text is not an easy task. People generally omits the boundary markers and use punctuation for other stylistic tasks. We propose a deep neural network approach for sentence boundary marking as well as suggesting appropriate punctuation mark in code mixed social media text. We experimented with single layer bidirectional and two layer bidirectional models. Both word sequence and character sequence are experimented. Bidirectional model using character sequence out performs all other models for sentence boundary detection as well as end marker suggestion.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128614417","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974515
Tushar Bhardwaj, Himanshu Upadhyay, S. Sharma
The user’s request changes dynamically in service-based cloud applications, which requires optimal amount of computing resources to meet service-level agreements (SLAs). The existing server-side resource allocation mechanisms have limitations in provisioning the required resources to handle the incoming load on the basis of user’s requests. To overcome the aforementioned situation, cloud computing provides ample amount of computing resources to meet the SLAs. There are possibilities that cloud resources might not be properly utilized and might suffer over and under utilization. In this study, the authors have proposed an autonomous resource allocation mechanism, that automatically provisions (allocate and de-allocate) the required computing resources as per the load. The primary goal of this study is to improve the virtual resource utilization and response time with respect to the existing methods. The proposed model leverages the simple heuristic with response time and the number of virtual machines as the parameters. Finally, the results have shown that the response time and resource utilization have been improved.
{"title":"Autonomic Resource Allocation Mechanism for Service-based Cloud Applications","authors":"Tushar Bhardwaj, Himanshu Upadhyay, S. Sharma","doi":"10.1109/ICCCIS48478.2019.8974515","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974515","url":null,"abstract":"The user’s request changes dynamically in service-based cloud applications, which requires optimal amount of computing resources to meet service-level agreements (SLAs). The existing server-side resource allocation mechanisms have limitations in provisioning the required resources to handle the incoming load on the basis of user’s requests. To overcome the aforementioned situation, cloud computing provides ample amount of computing resources to meet the SLAs. There are possibilities that cloud resources might not be properly utilized and might suffer over and under utilization. In this study, the authors have proposed an autonomous resource allocation mechanism, that automatically provisions (allocate and de-allocate) the required computing resources as per the load. The primary goal of this study is to improve the virtual resource utilization and response time with respect to the existing methods. The proposed model leverages the simple heuristic with response time and the number of virtual machines as the parameters. Finally, the results have shown that the response time and resource utilization have been improved.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128490316","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974468
Shubham Mishra, Zeesha Mishra, B. Acharya
A high-speed cryptography algorithm is the necessity of today’s world to communicate between two resource-constrained tools. We have proposed a 128-bit block size and 256-bit key size LEA cipher for high speed and throughput purpose. High speed is an essential requirement with the secure transmission of information. Pipelining is the best way to achieve these requirements with higher throughput. The implementation results have shown that this method has a higher capability of speed and throughput as compared to previous ciphers. LEA has security against all existing cipher attacks and compatible with both hardware and software. Proposed work is 73.7% and 62.85% improved version of compared paper for respectively throughput and speed.
{"title":"A High Throughput And Speed Architecture of Lightweight Cipher LEA","authors":"Shubham Mishra, Zeesha Mishra, B. Acharya","doi":"10.1109/ICCCIS48478.2019.8974468","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974468","url":null,"abstract":"A high-speed cryptography algorithm is the necessity of today’s world to communicate between two resource-constrained tools. We have proposed a 128-bit block size and 256-bit key size LEA cipher for high speed and throughput purpose. High speed is an essential requirement with the secure transmission of information. Pipelining is the best way to achieve these requirements with higher throughput. The implementation results have shown that this method has a higher capability of speed and throughput as compared to previous ciphers. LEA has security against all existing cipher attacks and compatible with both hardware and software. Proposed work is 73.7% and 62.85% improved version of compared paper for respectively throughput and speed.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121250451","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974474
Indrani Das, Sanjoy Das, S. Sahana, Ashwini Kumar
The growing use of networking in almost every possible field, data transferring or data sharing has become an essential need. All kinds of users directly or indirectly involved in data transfer. But data transferring is susceptible to various risks i.e. hacking of potential data, tempering, etc. Various services based on data sharing or transferring across the network needs security and reliability of the system. Most of the stakeholders may not be fully aware about the fact that their communication is unsecure. Users are relying upon the system they are using and assume that their ongoing communication is secure.Generally, data categorized into text and image messages. There are many works on securing of text message through encryption has been achieved in last decades. But securing images are differs in many ways from that because text. Nowadays, securing image is necessary and quite in demand. In this paper, we have proposed an image encryption algorithm to secure image while being transmitted in two layers.
{"title":"A Two layer secure image encryption technique","authors":"Indrani Das, Sanjoy Das, S. Sahana, Ashwini Kumar","doi":"10.1109/ICCCIS48478.2019.8974474","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974474","url":null,"abstract":"The growing use of networking in almost every possible field, data transferring or data sharing has become an essential need. All kinds of users directly or indirectly involved in data transfer. But data transferring is susceptible to various risks i.e. hacking of potential data, tempering, etc. Various services based on data sharing or transferring across the network needs security and reliability of the system. Most of the stakeholders may not be fully aware about the fact that their communication is unsecure. Users are relying upon the system they are using and assume that their ongoing communication is secure.Generally, data categorized into text and image messages. There are many works on securing of text message through encryption has been achieved in last decades. But securing images are differs in many ways from that because text. Nowadays, securing image is necessary and quite in demand. In this paper, we have proposed an image encryption algorithm to secure image while being transmitted in two layers.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115219081","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974465
Divyansh Puri, B. Bhushan
With the new emerging technologies of this era, demands are increasing, concerning the increase in the population, Consumer desires everything to be high tech and automatized, Which leads to more sophisticated systems, WSNs or the wireless sensor networks can overcome these complications, Regardless sensors should be able to deliver diverse services, To make that possible Machine Learning techniques have been introduced which can help in efficient working of WSNs at a very low cost by stabilizing the energy and thus increasing the life span of the Wireless Sensor Networks, machine learning helps in various WSN applications some of those applications have been discussed further in this paper, there are various types of machine learning methods used in this paper and their comparisons have been given in tabular form.
{"title":"Enhancement of security and energy efficiency in WSNs: Machine Learning to the rescue","authors":"Divyansh Puri, B. Bhushan","doi":"10.1109/ICCCIS48478.2019.8974465","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974465","url":null,"abstract":"With the new emerging technologies of this era, demands are increasing, concerning the increase in the population, Consumer desires everything to be high tech and automatized, Which leads to more sophisticated systems, WSNs or the wireless sensor networks can overcome these complications, Regardless sensors should be able to deliver diverse services, To make that possible Machine Learning techniques have been introduced which can help in efficient working of WSNs at a very low cost by stabilizing the energy and thus increasing the life span of the Wireless Sensor Networks, machine learning helps in various WSN applications some of those applications have been discussed further in this paper, there are various types of machine learning methods used in this paper and their comparisons have been given in tabular form.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122442730","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974529
Avantika Singh, Aakriti Mathur, Nitasha Hasteer
Technology is the most revolutionary and confidence inspiring step taken by mankind. The evolution of technology with the combination of health care has proven to be beneficial in every possible field spanning across all branches of medicine from progressive to in-born abnormalities affecting humans. In order to cater to the sector of people with in-born diseases specifically Autism, a certain kind of assistive technology is accessible that is, Augmentative and Alternative Communication (AAC). This paper introduces an android application AutistiCare targeting children of age 4 to 12 years old. It has features like information around us and caters to the health of the child. There are fun learning games which help the child build skills and coordination. AutistiCare aims at creating friendly yet informative interface for children who have been diagnosed with Autism. On the usage of the designed system, this study advocates the usability of android based application for bridging the learning gap for autistic children and brings forth the research direction in the field.
{"title":"Bridging Learning Gap for Autism Spectrum Disorder","authors":"Avantika Singh, Aakriti Mathur, Nitasha Hasteer","doi":"10.1109/ICCCIS48478.2019.8974529","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974529","url":null,"abstract":"Technology is the most revolutionary and confidence inspiring step taken by mankind. The evolution of technology with the combination of health care has proven to be beneficial in every possible field spanning across all branches of medicine from progressive to in-born abnormalities affecting humans. In order to cater to the sector of people with in-born diseases specifically Autism, a certain kind of assistive technology is accessible that is, Augmentative and Alternative Communication (AAC). This paper introduces an android application AutistiCare targeting children of age 4 to 12 years old. It has features like information around us and caters to the health of the child. There are fun learning games which help the child build skills and coordination. AutistiCare aims at creating friendly yet informative interface for children who have been diagnosed with Autism. On the usage of the designed system, this study advocates the usability of android based application for bridging the learning gap for autistic children and brings forth the research direction in the field.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122567352","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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