Pub Date : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262314
S. Padmapriya, R. Valli, M. Jayekumar
Vehicular Adhoc Networks (VANETs) ensures road safety by communicating with a set of smart vehicles. VANET is a subset of Mobile Adhoc Networks (MANETs). VANET enabled vehicles helps in establishing communication services among one another or with the Road Side Unit (RSU). Information transmitted in VANET is distributed in an open access environment and hence security is one of the most critical issues related to VANET. Although each vehicle is not a source of all communications, most contact depends on the information that other vehicles receive from it. That vehicle must be able to assess, determine and respond locally on the information obtained from other vehicles to protect VANET from malicious act. Of this reason, message verification in VANET is more difficult due to the protection and privacy issues of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.
{"title":"Monitoring Algorithm in Malicious Vehicular Adhoc Networks","authors":"S. Padmapriya, R. Valli, M. Jayekumar","doi":"10.1109/ICSCAN49426.2020.9262314","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262314","url":null,"abstract":"Vehicular Adhoc Networks (VANETs) ensures road safety by communicating with a set of smart vehicles. VANET is a subset of Mobile Adhoc Networks (MANETs). VANET enabled vehicles helps in establishing communication services among one another or with the Road Side Unit (RSU). Information transmitted in VANET is distributed in an open access environment and hence security is one of the most critical issues related to VANET. Although each vehicle is not a source of all communications, most contact depends on the information that other vehicles receive from it. That vehicle must be able to assess, determine and respond locally on the information obtained from other vehicles to protect VANET from malicious act. Of this reason, message verification in VANET is more difficult due to the protection and privacy issues of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"26 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86638949","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262330
Pugazhenthi A, L. S. Kumar
This paper presents algorithms for extraction of clouds from INSAT-3D satellite image over the Indian region. The K-Means and Fuzzy C-Means clustering algorithms are applied on INSAT-3D satellite images on some specific dates and time in the year 2017, when the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite crosses the Indian region. Prior to this, the number of cluster segments k is selected from the MODIS Aqua sensor's cloud product. The result of segmentation algorithms is validated by comparing with the cloud optical thickness of the MODIS data. The comparison shows that INSAT-3D cloud segmentation matches well with the cloud optical thickness of the MODIS data.
{"title":"Cloud Extraction from INSAT-3D Satellite Image by K-Means and Fuzzy C-Means Clustering Algorithms","authors":"Pugazhenthi A, L. S. Kumar","doi":"10.1109/ICSCAN49426.2020.9262330","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262330","url":null,"abstract":"This paper presents algorithms for extraction of clouds from INSAT-3D satellite image over the Indian region. The K-Means and Fuzzy C-Means clustering algorithms are applied on INSAT-3D satellite images on some specific dates and time in the year 2017, when the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite crosses the Indian region. Prior to this, the number of cluster segments k is selected from the MODIS Aqua sensor's cloud product. The result of segmentation algorithms is validated by comparing with the cloud optical thickness of the MODIS data. The comparison shows that INSAT-3D cloud segmentation matches well with the cloud optical thickness of the MODIS data.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"45 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88300422","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262441
G. Sharmila, S. Karthika, V. Rajesh, A. Yuvarani, E. Sangeetha
Aging Macular Deterioration (AMD) is a leading eye problem most commonly experienced by the old age people. If the problem is untreated over a prolonged time period, it results in permanent blindness. This eye problem is caused due to the damage of macula lutea which is a central region of retina needs for visualizing very fine details. However, only early detection can exhibit it from becoming severe and protect vision. This method proposes an automatic screening of all the three stages of AMD (i.e.) early (DMD), intermediate and late (WMD) using Convolutional Neural Network. A set of 400 color fundus images are taken for experimentation out of which 190 images are affected AMD images and 210 images are non-AMD images. Here, first the images are subjected to an image segmentation technique which adds-on the advantage of improving the accuracy of the system. Fuzzy c-means clustering is used as the image segmentation technique. Then the segmented images were trained and experimented using Convolutional Neural Network. This work thus obtained an overall accuracy of about 95.65%. The experimental results verify the effectiveness of this method.
{"title":"Computer Aided Diagnosis of Aging Macular Deterioration Via Convolutional Neural Network","authors":"G. Sharmila, S. Karthika, V. Rajesh, A. Yuvarani, E. Sangeetha","doi":"10.1109/ICSCAN49426.2020.9262441","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262441","url":null,"abstract":"Aging Macular Deterioration (AMD) is a leading eye problem most commonly experienced by the old age people. If the problem is untreated over a prolonged time period, it results in permanent blindness. This eye problem is caused due to the damage of macula lutea which is a central region of retina needs for visualizing very fine details. However, only early detection can exhibit it from becoming severe and protect vision. This method proposes an automatic screening of all the three stages of AMD (i.e.) early (DMD), intermediate and late (WMD) using Convolutional Neural Network. A set of 400 color fundus images are taken for experimentation out of which 190 images are affected AMD images and 210 images are non-AMD images. Here, first the images are subjected to an image segmentation technique which adds-on the advantage of improving the accuracy of the system. Fuzzy c-means clustering is used as the image segmentation technique. Then the segmented images were trained and experimented using Convolutional Neural Network. This work thus obtained an overall accuracy of about 95.65%. The experimental results verify the effectiveness of this method.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88316638","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262304
M. Lambay, S. Pakkir Mohideen
Healthcare industry is an indispensable entity in the real world where large volumes of data is accumulated from time to time. Such data assumes characteristics of big data and it is desirable to analyze it and bring about latent relationships among variables in the healthcare data. Data in healthcare industry is rich in useful information. However, a comprehensive big data approach is essential to mine the data and acquire business intelligence. There are many use cases of big data analytics. However, in healthcare industry it is imperative to have knowledge-driven recommendations that help all stakeholders. With the emergence of cloud computing, big data analytics has become a reality. Distributed programming frameworks like Hadoop and Spark, to mention few, are available with associated Distributed File System (DFS) to manage big data. Many researchers contributed towards developing algorithms based on machine learning which is part of Artificial Intelligence (AI). Since healthcare industry is one of the sources of big data, it needs distributed environments for processing. Big data analytics is essential to analyze healthcare data in a comprehensive manner. The cloud computing and big data ecosystem is playing favorable role in realizing big data analytics for healthcare recommendations. A typical recommender system in healthcare industry is supposed to produce recommendations in various aspects of the domain. This paper throws light into different recommenders in healthcare domain that use big data analytics to generate recommendations. It not only provides useful insights but also discussed research gaps that can be used to investigate further to improve the state of the art.
{"title":"Big Data Analytics for Healthcare Recommendation Systems","authors":"M. Lambay, S. Pakkir Mohideen","doi":"10.1109/ICSCAN49426.2020.9262304","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262304","url":null,"abstract":"Healthcare industry is an indispensable entity in the real world where large volumes of data is accumulated from time to time. Such data assumes characteristics of big data and it is desirable to analyze it and bring about latent relationships among variables in the healthcare data. Data in healthcare industry is rich in useful information. However, a comprehensive big data approach is essential to mine the data and acquire business intelligence. There are many use cases of big data analytics. However, in healthcare industry it is imperative to have knowledge-driven recommendations that help all stakeholders. With the emergence of cloud computing, big data analytics has become a reality. Distributed programming frameworks like Hadoop and Spark, to mention few, are available with associated Distributed File System (DFS) to manage big data. Many researchers contributed towards developing algorithms based on machine learning which is part of Artificial Intelligence (AI). Since healthcare industry is one of the sources of big data, it needs distributed environments for processing. Big data analytics is essential to analyze healthcare data in a comprehensive manner. The cloud computing and big data ecosystem is playing favorable role in realizing big data analytics for healthcare recommendations. A typical recommender system in healthcare industry is supposed to produce recommendations in various aspects of the domain. This paper throws light into different recommenders in healthcare domain that use big data analytics to generate recommendations. It not only provides useful insights but also discussed research gaps that can be used to investigate further to improve the state of the art.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"15 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77397989","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262367
H. Rosi, Ramachandram Ethrajavalli, Mohammed Iqbal Janci
Owing to their peculiar properties nanoparticles of cerium oxide have gained tremendous attention in recent years. As such, bacteria, fungus and algae are used for the development of CeO2 NPs through the use of both intracellular and extracellular microbial or enzyme cells, proteins and other biomolecule compounds. In this paper we use Sargassum wightii Greville, a biological extract, to synthesize cerium oxide (CeO2) nanoparticles. Algal-biogenic metal oxide synthesis nanoparticles is a safe and economical procedure due to the formation of compact, small nanoparticles. A number of advanced devices, such as UV-visible spectrophotometers, XRD, FTIR and SEM spectroscopy have been identified for prepared CeO2 NPs. Cerium oxide particles were studied for the antioxidant properties and their antioxidant potency was examined using an in vitro system. The antioxidant strength tests for insoluble solids were conducted using an modified DPPH process. DPPH spray increases with particle size decrease.
{"title":"Synthesis Of Cerium Oxide Nanoparticles Using Marine Algae Sargassum Wightii Greville Extract: Implications For Antioxidant Applications","authors":"H. Rosi, Ramachandram Ethrajavalli, Mohammed Iqbal Janci","doi":"10.1109/ICSCAN49426.2020.9262367","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262367","url":null,"abstract":"Owing to their peculiar properties nanoparticles of cerium oxide have gained tremendous attention in recent years. As such, bacteria, fungus and algae are used for the development of CeO2 NPs through the use of both intracellular and extracellular microbial or enzyme cells, proteins and other biomolecule compounds. In this paper we use Sargassum wightii Greville, a biological extract, to synthesize cerium oxide (CeO2) nanoparticles. Algal-biogenic metal oxide synthesis nanoparticles is a safe and economical procedure due to the formation of compact, small nanoparticles. A number of advanced devices, such as UV-visible spectrophotometers, XRD, FTIR and SEM spectroscopy have been identified for prepared CeO2 NPs. Cerium oxide particles were studied for the antioxidant properties and their antioxidant potency was examined using an in vitro system. The antioxidant strength tests for insoluble solids were conducted using an modified DPPH process. DPPH spray increases with particle size decrease.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"1 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90088173","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262294
Vishnu H Lal, G. Varaprasad
This paper discusses the various student satisfaction studies carried out in the context of higher education and its meta- analysis. To achieve this objective, 172 studies linked to student satisfaction were identified from Web of Science, and bibliometric analysis was done on the same. The papers were examined to determine the nature of the study and the dimensions studied by the authors. Various analyses like keyword, citations, author, etc. were carried out, and conclusions were drawn from the same. This study will aid future researchers in having an idea about the nature of studies carried out in the past and how-to extent it further.
本文讨论了在高等教育背景下开展的各种学生满意度研究及其元分析。为了实现这一目标，我们从Web of Science中找出了172项与学生满意度相关的研究，并对其进行了文献计量学分析。对论文进行了检查，以确定研究的性质和作者研究的维度。对关键词、引文、作者等进行了各种分析，并从中得出结论。这项研究将帮助未来的研究人员了解过去开展的研究的性质，以及如何进一步扩大研究范围。
{"title":"A meta-analytic review of student satisfaction studies in higher education","authors":"Vishnu H Lal, G. Varaprasad","doi":"10.1109/ICSCAN49426.2020.9262294","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262294","url":null,"abstract":"This paper discusses the various student satisfaction studies carried out in the context of higher education and its meta- analysis. To achieve this objective, 172 studies linked to student satisfaction were identified from Web of Science, and bibliometric analysis was done on the same. The papers were examined to determine the nature of the study and the dimensions studied by the authors. Various analyses like keyword, citations, author, etc. were carried out, and conclusions were drawn from the same. This study will aid future researchers in having an idea about the nature of studies carried out in the past and how-to extent it further.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"14 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73050617","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262401
S. Sandhiya, U. Palani
In recent days, Data stream mining is important for many of the real time and IOT based applications. Online feature selection is the one big topic of data stream mining which attracted researchers with intensive interest. This technique reduces the dimensionality of the streaming features by excluding inappropriate and redundant features. The researchers have proposed many online feature selection algorithm for streaming features like Grafting, Alpha-investing, OSFS, OGFS and SAOLA. Based on above studies the exiting algorithm has limitation over prediction accuracy and the large number of selected features. To overcome the limitations of above mentioned approaches, we propose an online feature selection algorithm for streaming features called Heuristic Online Streaming Feature Selection (HOSFS) which has advantages on choosing features from streaming features and omits the irrelevant and redundant features in real-time by using self-adaption sliding window protocol, and Heuristic function. The HOSFS algorithm assigns heuristic value to the features using the trained heuristic function and selects features with higher heuristic value where other features are considered as irrelevant features. This proposed technique results reduced number of strongly related features and obtains greater prediction accuracy with optimal features. HOSFS algorithm efficiency was tested with three different Health care datasets using MOA tools. Through the experimental outcomes, HOSFS has greater prediction accuracy and reduced number of selected features than alpha - investing, OSFS, and SAOLA.
{"title":"A Novel HOSFS Algorithm for Online Streaming Feature Selection","authors":"S. Sandhiya, U. Palani","doi":"10.1109/ICSCAN49426.2020.9262401","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262401","url":null,"abstract":"In recent days, Data stream mining is important for many of the real time and IOT based applications. Online feature selection is the one big topic of data stream mining which attracted researchers with intensive interest. This technique reduces the dimensionality of the streaming features by excluding inappropriate and redundant features. The researchers have proposed many online feature selection algorithm for streaming features like Grafting, Alpha-investing, OSFS, OGFS and SAOLA. Based on above studies the exiting algorithm has limitation over prediction accuracy and the large number of selected features. To overcome the limitations of above mentioned approaches, we propose an online feature selection algorithm for streaming features called Heuristic Online Streaming Feature Selection (HOSFS) which has advantages on choosing features from streaming features and omits the irrelevant and redundant features in real-time by using self-adaption sliding window protocol, and Heuristic function. The HOSFS algorithm assigns heuristic value to the features using the trained heuristic function and selects features with higher heuristic value where other features are considered as irrelevant features. This proposed technique results reduced number of strongly related features and obtains greater prediction accuracy with optimal features. HOSFS algorithm efficiency was tested with three different Health care datasets using MOA tools. Through the experimental outcomes, HOSFS has greater prediction accuracy and reduced number of selected features than alpha - investing, OSFS, and SAOLA.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"6 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74070358","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262350
T. K. Das, A. Tripathy, Kathiravan Srinivasan
Shopping is really fascinating and alluring; at the same time, it involves getting tired due to standing in a long queue for the bill and payment process. Hence, it is proposed to design a smart trolley which can take care of shopping and billing. By this, the customer can walk straightaway into the shop, purchase products using the smart trolley and walk out of the shop. He gets the e-bill through the mail, and he can view his purchase details using the shop's website. In order to realize this, we need an Arduino board, Radio-Frequency Identification (RFID) reader, RFID tag, LCD display, ESP8266 Wi-Fi module, database manager and a website to maintain product and customer details, which can be accessed by the admin anywhere in the world. This is an IOT based system where the trolley can interact with the network spread worldwide.
{"title":"A Smart Trolley for Smart Shopping","authors":"T. K. Das, A. Tripathy, Kathiravan Srinivasan","doi":"10.1109/ICSCAN49426.2020.9262350","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262350","url":null,"abstract":"Shopping is really fascinating and alluring; at the same time, it involves getting tired due to standing in a long queue for the bill and payment process. Hence, it is proposed to design a smart trolley which can take care of shopping and billing. By this, the customer can walk straightaway into the shop, purchase products using the smart trolley and walk out of the shop. He gets the e-bill through the mail, and he can view his purchase details using the shop's website. In order to realize this, we need an Arduino board, Radio-Frequency Identification (RFID) reader, RFID tag, LCD display, ESP8266 Wi-Fi module, database manager and a website to maintain product and customer details, which can be accessed by the admin anywhere in the world. This is an IOT based system where the trolley can interact with the network spread worldwide.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73402120","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262313
Soumita Biswas, Anuran Mitra, Sovan Mistry, T. Chowdhury, Soumodip Sinha, Ani Biswas, Raja Karmakar
Inter-Basic Service Sets (BSSes) interference and interference inside a BSS are unavoidable since the quantity of non-overlapping channels for wireless networks is limited; and multiple BSSes form an Extended Service Set (ESS). Nowadays, due to the rapid growth in the use of wireless devices like smart phones, laptop etc., access points (APs) in public areas are overheaded with a huge number of Internet accesses requested by users. When many wireless devices are assembled together to get and offer services, allocation and sharing of wireless channels become a critical issue since all wireless devices want to access the channel simultaneously and transmit data. Therefore, collisions occur in acquiring the channel and consequently, unfairness in channel access increases, which leads to the degradation of throughput fairness in wireless networks. This paper addresses aforesaid issue to propose a mechanism, called FairIN, to provide fairness in throughput such that all wireless stations can get an equal access of the channel. In FairIN, we design two mechanisms to handle the fairness inside a BSS and among APs separately. The performance analysis of FairIN through simulation in an IEEE 802.11ac network shows that FairIN can improve throughput fairness in infrastructure-based wireless networks.
{"title":"FairIN: Throughput Fairness in Infrastructure-Based Wireless Access Networks","authors":"Soumita Biswas, Anuran Mitra, Sovan Mistry, T. Chowdhury, Soumodip Sinha, Ani Biswas, Raja Karmakar","doi":"10.1109/ICSCAN49426.2020.9262313","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262313","url":null,"abstract":"Inter-Basic Service Sets (BSSes) interference and interference inside a BSS are unavoidable since the quantity of non-overlapping channels for wireless networks is limited; and multiple BSSes form an Extended Service Set (ESS). Nowadays, due to the rapid growth in the use of wireless devices like smart phones, laptop etc., access points (APs) in public areas are overheaded with a huge number of Internet accesses requested by users. When many wireless devices are assembled together to get and offer services, allocation and sharing of wireless channels become a critical issue since all wireless devices want to access the channel simultaneously and transmit data. Therefore, collisions occur in acquiring the channel and consequently, unfairness in channel access increases, which leads to the degradation of throughput fairness in wireless networks. This paper addresses aforesaid issue to propose a mechanism, called FairIN, to provide fairness in throughput such that all wireless stations can get an equal access of the channel. In FairIN, we design two mechanisms to handle the fairness inside a BSS and among APs separately. The performance analysis of FairIN through simulation in an IEEE 802.11ac network shows that FairIN can improve throughput fairness in infrastructure-based wireless networks.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"31 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75066733","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262275
G. Vengatesh, R. Rajesh, T. Naveenkumar
This article is to improve communication with the children affected with cerebral palsy by using a computer vision. cerebral palsy is a permanent movements disorder that appears in childhood. It affects their movements, sensation, and speaking so the children differ from normal children. The technology can improve communication between the children and parents by using an open cv python programming and convolutional neural network(CNN). It detects the facial expression and body pattern of the children to give accurate results of the emotion or needs of the children. then it intimates the alert message to the parents through the mobile application.
{"title":"An Intelligent Computer Vision for Children Affected with Cerebral Palsy","authors":"G. Vengatesh, R. Rajesh, T. Naveenkumar","doi":"10.1109/ICSCAN49426.2020.9262275","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262275","url":null,"abstract":"This article is to improve communication with the children affected with cerebral palsy by using a computer vision. cerebral palsy is a permanent movements disorder that appears in childhood. It affects their movements, sensation, and speaking so the children differ from normal children. The technology can improve communication between the children and parents by using an open cv python programming and convolutional neural network(CNN). It detects the facial expression and body pattern of the children to give accurate results of the emotion or needs of the children. then it intimates the alert message to the parents through the mobile application.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"8 38 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81664878","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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