Day 2 Tue, March 22, 2022最新文献

{"title":"Real Time Air Quality Evaluation Model using Machine Learning Approach","authors":"G. Arun, S. Rathi","doi":"10.36548/jitdw.2022.1.003","DOIUrl":"https://doi.org/10.36548/jitdw.2022.1.003","url":null,"abstract":"In recent years, the world is being industrialized day-by-day which ultimately compels our concentration towards air quality. A gradual increase in population along with the raise in usage of vehicles and consumption of conventional energy leads to air pollution which subsequently accelerates the deterioration of air quality. And air pollution has its severe impact on human health. Many researchers have proposed various methodologies for predicting and forecasting the air quality. But it is rather important to predict the future air quality in order to reduce its impact. Therefore, this paper proposes an air quality evaluation system for future prediction. The current experiment includes three modules namely Preparation of Data, Forecasting AQI and Evaluating Air Quality. Data preparation is collecting real time data and formatting it as an input to next module. Sparse Spectrum GPR (SSGPR) is used in this study to forecast, whereas cloud model to evaluate air quality. The proposed model is capable of modelling the fuzziness and randomness. Finally, the entire model is evaluated using performance metrics like MAE, RSME and MAPE.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79476325","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":"Building Estimation Prediction Using Machine Learning","authors":"N. Santhosh, V. Gopalakrishnan, D. Rajkumar","doi":"10.36548/jitdw.2022.1.004","DOIUrl":"https://doi.org/10.36548/jitdw.2022.1.004","url":null,"abstract":"Nowdays, everybody hopes for a house that suits their way of life and gives conveniences as per their requirements. Building costs continue to change often which demonstrates that costs are frequently overstated. There are many elements that must be thought about at anticipating building costs, for example, area, number of rooms, cover region, how old the property is, and other fundamental neighborhood conveniences. In this paper, CatBoost algorithm alongside Robotic Process Automation are involved for continuous information extraction. Mechanical Process Automation includes the utilization of programming robots to robotize the assignments of information extraction while machine learning algorithm is utilized to anticipate building costs concerning the dataset. Machine Learning is firmly connected with insights, which focus on making forecasts with the help of PCs. There is an assortment of uses of Machine Learning, for example, sifting of messages, where it is challenging to foster a traditional calculation to successfully play out the errand. Machine Learning algorithms are absolutely founded on information, and are a high level rendition of the normal calculation. It makes programs \"more intelligent\" by permitting them to naturally gain from the information given by people. The algorithm is predominantly separated into two stages i.e., training stage and testing stage. Comprehensively there are three sorts of calculations that are fundamentally utilized on information such as, supervised, unsupervised and reinforcement learning algorithms.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86273307","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":"Performance Analysis of Multi-Layered Clustering Routing Protocol for Wireless Sensor Networks","authors":"W. S. Kiran","doi":"10.36548/jsws.2022.1.002","DOIUrl":"https://doi.org/10.36548/jsws.2022.1.002","url":null,"abstract":"Wireless Sensor Networks are the most efficient networks today, and they are used in many industrial, medical, and security applications. The major drawback of the sensor network is energy consumption due to the smaller size of the sensor node. To overcome the energy consumption, this paper proposes a new routing protocol called Multi-Layered Clustering Routing Protocol. This proposed routing protocol contributes to network’s long life and energy efficiency. During data transmission between the source and destination, the clustering approach is used in each layer. This assists in identifying the level of energy at each sensor node, which results in energy consumption reduction. Experimental results analyse the performance of the proposed routing protocol, that regulates the energy consumption and improves the network lifetime compared to the existing techniques.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"87 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76010089","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":"Bridgeless Isolated CUK Converter Using BLDC Motor","authors":"K. Lokesh, E. Latha Mercy, D. Poovizhi, B. Indhumathi","doi":"10.36548/jtcsst.2022.1.003","DOIUrl":"https://doi.org/10.36548/jtcsst.2022.1.003","url":null,"abstract":"The CUK topology is used to propose three novel rectifiers with single phase AC-DC Power Factor Correction (PFC) without a bridge. When compared to a standard CUK Power Factor Correction rectifier, the lack of enhanced heat control and reduced conduction losses are achieved by using the current flows; there are only two semiconductor switches and one input diode bridge channel throughout each period of the switching cycles. The proposed topologies are made to operate in the mode of discontinuous conduction, resulting in a deciding element of almost unity as well as low input current Harmonic Distortion in total. Additional benefits in Discontinuous Conduction Mode operating includes zero current is switched on in the power switches, and in the output diode, zero current is turned off, as well as simplified control circuitry. The power switch can be turned on or off.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87585890","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":"Step Incremental Conductance MPPT for Solar PV System Based on Fuzzy Logic Controller","authors":"Harshini Siva, S. Balaraman","doi":"10.36548/jtcsst.2022.1.004","DOIUrl":"https://doi.org/10.36548/jtcsst.2022.1.004","url":null,"abstract":"Due to strong industrial expansion, the need for electrical power has increased in recent years. As more than just a by-product of this increased dependence on fossil fuels, resource depletion occurs, and renewable sources such as solar, wind, and wave energy sources have begun to operate as an electricity source and are now playing a key role. Solar energy has been widely used in power systems, particularly in the form of photovoltaic (PV) generating units. Control scheme is a technique for obtaining electricity from a solar photovoltaic system under changing environmental circumstances. The proposed research compares two control methods: incremental conductance algorithm and fuzzy logic, in order to maximise the efficiency of a solar PV system. The algorithms described above change the switching frequency of the power converter to monitor a solar PV array's global MPP. In MATLAB/Simulink, the simulation is run, and the performance is evaluated. The simulated findings imply that the fuzzy logic controller performs better than the incremental conductance technique.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82047978","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":"Data Preparation and Quality Challenges for the Personality Recognition in Indian Languages using Machine Learning and Deep Learning Approaches","authors":"Jayshri P. Patil, Jikitsha R. Sheth","doi":"10.36548/jismac.2022.1.004","DOIUrl":"https://doi.org/10.36548/jismac.2022.1.004","url":null,"abstract":"Information about the user and their feelings, thoughts, and emotions are expressed through the status, comments, and updates on social media or other platforms. These user-generated contents are an important source for recognizing a user’s personality. Due to the increase in the amount of various Indian language contents on social media, there is a necessity to recognize personality from Indian languages. The challenges have increased in the collection and generation of datasets due to the lack of resources for Indian languages. In the field of personality recognition, the researchers have utilized machine learning and deep learning techniques to infer users’ personalities. The machine learning and deep learning models require enough labeled data for the training. Unlike traditional machine learning, deep learning techniques automatically generate features and require a significant amount of labeled data. For the personality recognition task from the Indian language, no sufficient annotated dataset is available and data preparation for the personality recognition task in the language has become a critical issue. This paper represents the existing gold standard dataset for personality recognition in English and also focuses on the challenges of a large amount of labeled data preparation in the Indian language.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"29 2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76024530","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":"DDoS Detection using Machine Learning Techniques","authors":"R. Amrish, K. Bavapriyan, V. Gopinaath, A. Jawahar, C. Vinoth Kumar","doi":"10.36548/jismac.2022.1.003","DOIUrl":"https://doi.org/10.36548/jismac.2022.1.003","url":null,"abstract":"A Distributed Denial of Service (DDoS) attack is a type of cyber-attack that attempts to interrupt regular traffic on a targeted server by overloading the target. The system under DDoS attack remains occupied with the requests from the bots rather than providing service to legitimate users. These kinds of attacks are complicated to detect and increase day by day. In this paper, machine learning algorithm is employed to classify normal and DDoS attack traffic. DDoS attacks are detected using four machine learning classification techniques. The machine learning algorithms are tested and trained using the CICDDoS2019 dataset, gathered by the Canadian Institute of Cyber Security. When compared against KNN, Decision Tree, and Random Forest, the Artificial Neural Network (ANN) generates the best results.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75252604","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 Survey on Wireless Network Intrusion Detection","authors":"S. Maheswari, J. C. Miraclin Joyce Pamila","doi":"10.36548/jsws.2022.1.001","DOIUrl":"https://doi.org/10.36548/jsws.2022.1.001","url":null,"abstract":"Artificial Intelligence (AI) discoveries have intensified in recent years as a result of the industry’s widespread adoption of this technology. The important field of AI is neural networks, that allow commercial usage of capabilities that were previously unattainable through computer use. One of the domains in which neural network is widely studied for increasing general security and data privacy is IDS. Using various machine learning approaches, this article provides a complete review of recent research on neural network topologies and types of intrusion detection systems.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84853407","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":"Detection of White Blood Cell Cancer using Deep Learning using Cmyk-Moment Localisation for Information Retrieval","authors":"M. Muthumanjula, Ramasubramanian Bhoopalan","doi":"10.36548/jismac.2022.1.006","DOIUrl":"https://doi.org/10.36548/jismac.2022.1.006","url":null,"abstract":"Medical diagnosis, notably concerning tumors, has been transformed by artificial intelligence as well as deep neural network. White blood cell identification, in particular, necessitates effective diagnosis and therapy. White Blood Cell Cancer (WBCC) comes in a variety of forms. Acute Leukemia Lymphocytes (ALL), Acute Myeloma Lymphocytes (AML), Chronic Leukemia Lymphocytes (CLL), and Chronic Myeloma Lymphocytes (CML) are white blood cell cancers for which detection is time-consuming procedure, vulnerable to sentient as well as equipment blunders. Despite just a comprehensive review with a competent examiner, it can be hard to render a precise conclusive determination in some cases. Conversely, Computer-Aided Diagnosis (CAD) may assist in lessening the number of inaccuracies as well as duration spent in diagnosing WBCC. \u0000Though deep learning is widely regarded as the most advanced method for detecting WBCCs, the richness of the retrieved attributes employed in developing the pixel-wise categorization algorithms has a substantial relationship with the efficiency of WBCC identification. The investigation of the various phases of alterations related with WBC concentrations and characteristics is crucial to CAD. Leveraging image handling plus deep learning technologies, a novel fusion characteristic retrieval technique has been created in this research. The suggested approach is divided into two parts: 1) The CMYK-moment localization approach is applied to define the Region of Interest (ROI) and 2) A CNN dependent characteristic blend strategy is utilized to obtain deep learning characteristics. The relevance of the retrieved characteristics is assessed via a variety of categorization techniques. The suggested component collection approach versus different attributes retrieval techniques is tested with an exogenous resource. With all the predictors, the suggested methodology exhibits good effectiveness, adaptability, including consistency, exhibiting aggregate categorization accuracies of 97.57 percent and 96.41 percent, correspondingly, utilizing the main as well as auxiliary samples. This approach has provided a novel option for enhancing CLL identification that may result towards a more accurate identification of malignancies.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"136 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76569342","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":"Adoption of Proprietary Online Education Software Compared to Free And Open-Source Software in Indian colleges","authors":"Shubhraj Sehgal, A. Gupta, Alka Singh, Preeti Singh","doi":"10.36548/jitdw.2022.1.001","DOIUrl":"https://doi.org/10.36548/jitdw.2022.1.001","url":null,"abstract":"Adoption of online learning tools is still in the nascent stage in India. Use of such tools has been sporadic and patchy at best. The Covid pandemic of 2020 forced the institutions to shut down which resulted in the sudden adoption of such software. The education market in India is dominated by free & open-source software also known as FOSS while proprietary software solutions take a back seat. This research focuses on the impacts of proprietary education software in easing the learning process for children as well as grad-students, and how these tools impact engagement and learnability. Moreover, a retrospective study of an open-source tool present in the market and the comparison of it with the proposed system have been presented. Further, an example of a proposed system of how a simple system can be created in-house and at minimal cost to serve as a proprietary solution for all online educational needs of the pupils has been demonstrated.","PeriodicalId":10940,"journal":{"name":"Day 2 Tue, March 22, 2022","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86545922","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}