{"title":"Evaluating the Semantic Property in an E-Learning Ontology","authors":"Amit Kumar Bajpai, R. Pandey, S. Tripathi","doi":"10.1109/CSNT51715.2021.9509729","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509729","url":null,"abstract":"In the context of the present e-learning system where data are available in the designated cloud /server. The tendency is towards accessing meaningful data: users are sending a request to the cloud to return an answer as per the request processed. The search engines start to process the request as per requirements tendered by the users. As per the behaviour of the search engines, it starts to search based on objects and return series of similar data. Further returned data may and may not be relevant thereafter another process starts like search within search till the exact information be finding. Here it is found that there is a drawback in the search engine which search information is based on keywords. To resolve the problems some added definition is required to be assigned to the present web documents so that they can support human and machine both. In another word further, it may be defined to establish the relationship to obtain more accurate information. Now thus it may begin how ontology can be helpful and supportive to obtain semantic information. Ontologies may be defined as such technologies which establish the relationship between two objects to support the machine and the user both. So that for the representation of the concepts which mean clear connection and relationship with objects it is considered to use ontology in the context of syntactic and semantic work-frame.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116876386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Objective Emperor Penguin Optimizer for Tuning the Quality-of-Service in Cloud Computing","authors":"Harsimran Kaur, R. S. Bhadoria","doi":"10.1109/CSNT51715.2021.9509727","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509727","url":null,"abstract":"In the present situation, researchers have the task of developing a high quality features based cloud computing system in the real world if service is desired on request. Quality of service (QoS) describes such parameters which carry out the non-functional activities for any real time based systems. Such services are normally sufficient to achieve these QoS. Most of the information technology (IT) companies offer different cloud based services to its customers. There is no standard methodology available for calculating the actual use of cloud based resources and determining the rankings. From the customers’ point of view, it is not an easy task to find the reliable service provider that meets customer’s needs. This paper presents the QoS parameter especially on ‘throughput’ using Cloud Rank 3 with aid of Multi-Objective Emperor Penguin Optimizer (MOEPO) approach. This approach helps in finding the adorable and competent cloud service provider (CSP) available in the market. The different experiments have been carried out with actual QoS results, using Amazon EC2 services and its comparison.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128378972","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal K-Means Clustering Algorithm for Weblog Mining","authors":"Vipin Jain, K. Kashyap","doi":"10.1109/CSNT51715.2021.9509644","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509644","url":null,"abstract":"World wide web (WWW) generates a huge number of unstructured data and information. The information is stored in weblog file. Weblogs information can be analyzed and visualized by various clustering algorithm. In this work, the k-means clustering algorithm is applied for grouping of the users with similar interest based on accessing of similer information. The optimal value of k is also determined by Elbow method to obtained optimal numbers of clusters. Clustering results are analyzed by various values of k. Comparative analysis ofvarious methods used for selecting the optimal number of clusters are also analyzed.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127611976","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}
B. Pandey, Vaishnavi Bisht, D. M. Akbar Hussain, Mohsin Jamil, M Zahid Hasan
{"title":"Energy-efficient implementation of AES algorithm on 16nm FPGA","authors":"B. Pandey, Vaishnavi Bisht, D. M. Akbar Hussain, Mohsin Jamil, M Zahid Hasan","doi":"10.1109/CSNT51715.2021.9509662","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509662","url":null,"abstract":"Cryptographic algorithms ensure security of data in CPSs, IoT and SCADA systems and platforms. Some researchers ascertained that the security processes have extensive effects on battery life of a device and FPGAs present a novel resolution for augmenting the performance of devices and the AES algorithm offers means to secure data transmission. In this research, we have analyzed the power consumption of the AES algorithm on 16nm Kintex Ultrascale+ FPGA for 5 different IO Standards to determine the least power consuming and an energy efficient architecture for its implementation. We have used Xilinx Vivado 2018.2 ISE for all the observations done in this work. Out of 5 IO Standards analyzed, POD12 and HSTL_I_12 IO Standards consumed least power and LVCMOS consumed maximum power. At output load of 10000pF, there is 94.92% savings in total on-chip power utilization when we migrate our design from LVCMOS18 to HSTL_I_12 and 94.88% savings in total on-chip power utilization when we migrate our design from LVCMOS18 to POD12. For further reducing the power consumption, different Green Computing techniques like frequency scaling, thermal scaling, clock gating etc can be applied. We may also execute our work on 3-D and 4-D ICs. The outcomes gained in this paper can assist in a more energy efficient FPGA implementation of AES.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128112146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Study of Bug Manifestion Process for Ensuring Software Quality","authors":"Raj Kumar, Sanjay Singla","doi":"10.1109/CSNT51715.2021.9509676","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509676","url":null,"abstract":"The effect of programming bugs on the current framework disappointments is of crucial anxiety. Numerous bugs are identified and expelled through testing, while others don't show up effectively at improvement time and show themselves just as operative disappointments. Other than the significance of understanding the bug highlights from the software engineer point of view. This paper researches the attributes of the bug appearance process. Different types of the errors in different stages and depending on different environment are outlined in the present paper.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129989688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Application of AI in Video Games to Improve Game Building","authors":"Tanvi Rath, N. Preethi","doi":"10.1109/CSNT51715.2021.9509685","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509685","url":null,"abstract":"Video Games Industry has been welcoming AI like any other industry for various tasks, AI in gaming helps to convey a much more realistic gaming experience, amplify player interaction and satisfaction over extensive periods. Additionally, the gaming industry is utilizing Artificial Intelligence to liberate its staff by making game development automated, quicker, and less expensive. In this work an experiment is described using Deep Neural Network and Statistical techniques for forecasting the location of an object in future frames of a video, it focuses on the engineering phase of the game, the proposed model combines future prediction of object location which helps to build the infinite universe in the videogame without any additional videos frames of the input video or hard coding any scenes to build the scenes further.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128898382","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}
Neeraj Sharma, Pratyush Sethi, Jasroop Singh Chadha, P. Lalwani
{"title":"Comprehensive Analysis of Feature Selection on Early Heart Strok Prediction","authors":"Neeraj Sharma, Pratyush Sethi, Jasroop Singh Chadha, P. Lalwani","doi":"10.1109/CSNT51715.2021.9509629","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509629","url":null,"abstract":"A stroke is a medicinal exigency and requires early prognosis in accordance with damage to the brain from intrusion of its blood circulation, therefore, early diagnosis helps, medical health professionals to save human lives. This aim can be achieved using the various machine learning techniques. In this research article, machine learning models are deployed on well known heart stroke classification data-set. In addition, effect of well established feature selection technique also observed on aforementioned machine learning models. In the experimental analysis, machine learning models with standard feature selection technique are tested on the data-set, namely, framingham, and obtained results are evaluated using the confusion metrics including recall, F1-score, precision and accuracy. From the obtained results, it is observed that Random Forest (RF) and Extra Trees (ET) performed the best with PCA (Principle component analysis), giving the highest accuracy of 88.91 %.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"66 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131859010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Architectural framework for Multi sensor Data fusion and validation in IoT Based system","authors":"S. Sindhu, M. Saravanan","doi":"10.1109/CSNT51715.2021.9509613","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509613","url":null,"abstract":"The IoT Based system is expected to be a tipping point for many applications such as Aircraft, Medical diagnosis, Autonomous systems, Military and defense services. Over the past few years, IoT based applications are witnessing the results of multiple sensors, which plays a vital role in decision making. The proposed work suggests the layered architectural framework and guidelines for modeling multi sensor-based applications. The application that involves multiple meshed IoT systems generates voluminous data that needs to be handled in the right way to make the correct decision. The conventional multiple data fusion methods are application-specific. The primary objective of our work is to narrate the handling of a larger number of data generated from multiple sensors and addressing the problems in data fusion for sensitive IoT based applications. In addition to that comparative analysis of various sensor fusion and validation, techniques are surveyed.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133753338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An assessment of various clustering techniques for VANET","authors":"Atul Barve, P. S. Patheja","doi":"10.1109/CSNT51715.2021.9509728","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509728","url":null,"abstract":"Vehicular Adhoc Network (VANET) is a technology where various vehicles on the road use Wireless Adhoc network technique for making communication among them for better driving environment and laser probability of roadside accidents. The vehicles are considered as wireless mobile nodes. These mobile nodes will form a network using various network topologies. These vehicles will communicate with each other using wireless communication technology. Intelligent Transportation System (ITS) is an application which plans to offer inventive types of assistance to traffic the board. The wireless nodes are allowed to communicate in about short range so vehicle networks are further divided in the clusters to make communication among neighbors’ vehicles within the cluster. The formation of clusters is based on various parameters like speed, direction, density, velocity etc. These clusters are variable in nature, so maintaining a cluster head in a cluster is a very tedious task. This paper surveys various clustering adopted in the VANET with their possible benefits and drawbacks.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133812747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An Intelligent System to Forecast COVID-19 Pandemic using Hybrid Neural Network","authors":"Supriya Vanahalli, Preethi N","doi":"10.1109/CSNT51715.2021.9509622","DOIUrl":"https://doi.org/10.1109/CSNT51715.2021.9509622","url":null,"abstract":"A current outbreak known as COVID-19 has been discovered from the coronavirus was informed by WHO. COVID-19 is a universal pandemic that has brought out the best and the worst of humanity. Due to an increase in the cases daily, COVID-19 is creating a menace to public health and establishes a disruption of the social and economic development of the countries. The problem is the hospitals are not able to provide proper facilities and treatments on time due to the lack of facilities in India. The purpose of this project to build an efficient hybrid deep learning model for forecasting the COVID-19 pandemic with multiple features that are responsible for the spread of COVID-19 in the top five states in India. In particular, a hybrid model that incorporates Auto-Regressive Integrated Moving Average and Long-term Short Memory is been used to forecast confirmed cases. The linear and non-linear dependencies in the dataset is been dealt with by an ARIMA-LSTM hybrid model. As a result, when compared to the outcomes of ARIMA, LSTM models independently, the hybrid model was giving better results and was performing well in forecasting COVID-19 cases. Through this, the policymakers will get prior information on COVID-19 cases in states which will help the government and healthcare departments to take prominent measures to prevent it.","PeriodicalId":122176,"journal":{"name":"2021 10th IEEE International Conference on Communication Systems and Network Technologies (CSNT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115800044","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}