{"title":"High Efficiency Control with Optimum Speed Prediction for Interior Permanent Magnet Synchronous Motor in Electric Vehicle applications","authors":"A. A, A. Vijayakumari","doi":"10.1109/ICCMC48092.2020.ICCMC-000190","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000190","url":null,"abstract":"This paper attempts to design and develop a high efficiency control for Interior Permanent Magnet Synchronous Motor (IPMSM) in electric vehicle applications. The concept behind high efficiency control is minimization of the total losses incur in the machine accounting the inverter and the battery losses. Losses are estimated through equations which are formulated based on the loss model of the motor. With the optimized loss, a stator current vector is identified through an optimization process which is the minimum possible current which produces the demanded torque. This work fuses the high efficiency control together with optimum speed prediction based on road conditions. The speed prediction algorithm recommends a reference speed at which the motor is expected to run to obtain maximum efficiency. The electric vehicle is modelled with different road gradients to result the total tractive power required for any operating conditions. Performance of the proposed control scheme is validated by simulation in MATLAB/Simulink platform with a 27kW IPMSM working on different road grads. The total energy consumption of the IPMSM considered is compared with other high efficiency control and the results are tabulated","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258899","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 Concise Survey of Self-tuning Methodologies for Proportional Integral Derivative Control system","authors":"N. Sridhar, Ashutosh Srivastava","doi":"10.1109/ICCMC48092.2020.ICCMC-000136","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000136","url":null,"abstract":"The primary aim of this research paper is to provide a comprehensive reference source for researchers working with self-tuning Proportional Integral Derivative (PID) control systems and also, offers the study on such self-tuning methodology. The need for our survey arises because the autotuning of PID control system may give a good set-point tracking and interruption rejection, which is used under traditional as well as advanced PID control systems for different control applications from long time. Correctly chosen self-tuning method may provide a proficient performance, stability and robustness in the PID controlled system. The survey has been carried into categories based on classical techniques developed for the PID self-tuning and optimization techniques applied for self-tuning mechanism for the better transient and steady state characteristics. Also, an assessment among different self-tuning techniques for PID Control system have been studied and analyzed under this survey.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133783157","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}
R. Devika, Gannamani Gehnavi Devi, Haseena, V. Subramaniyaswamy
{"title":"Decision Support System for Efficient Township Building Energy Management using a Fuzzy Logic Controller","authors":"R. Devika, Gannamani Gehnavi Devi, Haseena, V. Subramaniyaswamy","doi":"10.1109/ICCMC48092.2020.ICCMC-00071","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00071","url":null,"abstract":"Recently most of the modern industries or buildings are aiming at efficient usage of the power energy available without compromising on occupant comfort. The energy once distributed cannot be stored back. The best way for efficient usage is an intelligent way of the distribution of power. This can be achieved through Decision support systems. These expert systems help in decision making activities to make decisions on the amount of distribution of power based on the conditions prevailing. DSSs are very much essential and emerging technology in industrial automation. This paper describes how the decision on energy distribution activities can be taken using fuzzy logic controllers with the help of clustering algorithms and association rule mining.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133274282","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}
M. Anagha, Rakesh Lepakshi, V. Goutham, V. Thavish, T. G. Keerthan Kumar
{"title":"Packet Injection and Dos Attack Controller Software(PDACS) Module to Handle Attacks in Software Defined Network","authors":"M. Anagha, Rakesh Lepakshi, V. Goutham, V. Thavish, T. G. Keerthan Kumar","doi":"10.1109/ICCMC48092.2020.ICCMC-000179","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000179","url":null,"abstract":"Software Defined Networking technology is a methodology for network management which provides programmatically proficient network configuration so that performance of the network and monitoring is enhanced. Nowadays, most of the industrial control applications which are in need of fault tolerance makes use of Software Defined Networking technology. But the only open question in the research community is about the security of the Software Defined Network architecture. The Software Defined Network architecture is prone to attacks by malicious users which rule out the competent service level of Software Defined Network by consumption of resources in the data plane and affecting the network services in the control plane. PDACS is a software embedded to the Software Defined Network architecture to protect the controller. In this proposed work, PDACS will be simulated to effectively stop the attack and improve the performance of the controller under malicious attacks like packet injection and DOS attack. Zodiac FX switch, the switch used for implementing Software Defined Network in real time is used in order to connect the hosts and controller systems. Finally, it is ensured that PDACS will not compromise though there is high packet injection and DOS attack.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116782043","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":"Blockchain Technology in Data Management","authors":"N.Arunkumar, P.Sivaprakasam","doi":"10.1109/ICCMC48092.2020.ICCMC-00039","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00039","url":null,"abstract":"The introduction of cryptocurrency based decentralized applications and data storage has been illustrating the importance of blockchain technology to the industries. Blockchain technology as a platform allows creating a distributed and replicated ledger of transactions. Blockchain provides a guarantee of tamper resistance for the data generated from various processes to compile massive datasets. Since the data is huge in size and grows exponentially with time, the data management should be efficient to store or process it. We survey the different standards of data processing works in several research directions for bringing the blockchain execution closer to the various domains of databases and its operations. Furthermore, the proposed research work also discusses about the performance, challenges, and future research directions.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122402934","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 Evaluation of Different Extraction Methods and Support Vector Machine Kernels for Vehicle Type Classification","authors":"N. R, J. Stephen, N. Nandakumar, Remya Nair T","doi":"10.1109/ICCMC48092.2020.ICCMC-000129","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000129","url":null,"abstract":"Traffic surveillance and monitoring is effective when the vehicles are accurately classified. It comes into effect when it is applied at toll booth centers, parking areas, security system, accident prevention etc. Several algorithms have been used for classification of vehicles till date. We use LBP, LDP and HOG methods in our paper to process the image which is taken at different angles at a fixed size (100*100 px) and extract vehicle’s feature information concerning their length, width and number of tyres, color, model to decide the type of vehicle. SVM classifier is used for the classification of the dataset. The VID dataset made by collecting various images is used for monitoring the processes. This paper compares the 3 feature extraction methods and concludes that HOG with SVM is the best among them which gives the highest accuracy of 95.3% to classify the type of vehicle.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130080405","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 Review on ARC Flash Analysis and Calculation Methods","authors":"B. Rubini, R. Krishnakumar","doi":"10.1109/ICCMC48092.2020.ICCMC-000181","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000181","url":null,"abstract":"Analysis of an Arc detection system consider the standards, responsibility, sensitivity, security of overall system protection methods. This arc flash detection system coordinate different sections like as relay section, circuit breaker section, switchgear components withstanding capability at fault level, load section, neutral grounding section. The fast Arc detection and trip times are evaluated by Present state of optical fault detection sensors are implemented for fast identification and tripping of arc functions. Optical fault detection Sensors have some disadvantages are compare to conventional and other types. This sensors not only detect the Arc lighting sometimes it will detect lightning flash or welding. Conventional types are taking more time for tripping compared to sensor types. The combinational study needed for each type of arc detection schemes to avoid the nuisance tripping because it will affect the overall stability of the system. Different fault levels before and after arc ignition system need to maintain reliability of the system safely and securely.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130378001","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}
Sandip Omprakash Patil, V. S. Sajith Variyar, K. P. Soman
{"title":"Speed Bump Segmentation an Application of Conditional Generative Adversarial Network for Self-driving Vehicles","authors":"Sandip Omprakash Patil, V. S. Sajith Variyar, K. P. Soman","doi":"10.1109/ICCMC48092.2020.ICCMC-000173","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-000173","url":null,"abstract":"The intervention of AI technology and self-driving vehicles changed the transportation systems. The current self-driving vehicles demand reliable and accurate information from various functional modules. One of the major modules accommodated in vehicles is object detection and classification. In this paper a speed bump detection approach is developed for slow moving electric vehicle platform. The developed system uses monocular images as input and segment the speed bump using GAN network. The results obtained by new approach show that the GAN network is capable of segmenting various types of speed bumps with good accuracy. This new alternative approach shows the ability of GANs for speed bump detection application in self-driving vehicles.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605715","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}
Chiranjit R Patel, Vivek Urankar, Vivek B A, V. Bharadwaj
{"title":"Vedic Multiplier in 45nm Technology","authors":"Chiranjit R Patel, Vivek Urankar, Vivek B A, V. Bharadwaj","doi":"10.1109/ICCMC48092.2020.ICCMC-0004","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-0004","url":null,"abstract":"Multipliers in a digital processor remains as a core of mathematical computing paradigm. In ancient times Vedic mathematicians developed basic multiplication algorithms. This study focuses on optimizing area and designing the multiplier in 45 nanometer CMOS technology. Layout design and verification of a 4-bit multiplier is carried out. Operating voltage ranges from 0.9V to 1.1V, this aids in low power operation or the multiplier. Consuming 3.795uW of power in the highest constraint situation. \"Layout Versus Schematic\" and \"Design Rule Check\" (LVS & DRC) are the two software verification tools used to verify the integrated circuit design. Delay and power analysis of the multiplier using Cadence virtuoso manager are discussed. Delay of the proposed 4-bit multiplier in 45nm CMOS technology multiplier is 250ps by including all constraints.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126492151","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":"Support Vector Machine based Word Embedding and Feature Reduction for Sentiment Analysis-A Study","authors":"P. P. Shelke, Ankita N. Korde","doi":"10.1109/ICCMC48092.2020.ICCMC-00035","DOIUrl":"https://doi.org/10.1109/ICCMC48092.2020.ICCMC-00035","url":null,"abstract":"Sentiment analysis (SA), also called as opinion mining is the technique used to bring together the opinions of a specific entity or feature from reviews dataset. The opinions of other users help in performing the decision making process. This paper studies different methods that are aimed at performing sentiment analysis. These approaches vary from semantic based methods, machine learning, neural networks, and syntactical methods with each having its own strength. Although hybrid approach also exists, the main idea is to combine the strengths of two or more methods to increase the accuracy. A framework in which sentiment analysis is done by using the proposed word embedding and feature reduction techniques. Word embedding is a technique in which low-dimensional vector representation of words is provided. Feature reduction method employs a support vector machine (SVM) classifier. The framework will perform sentiment analysis of user opinions by using a machine learning approach and provides a recommendation system for the ease of decision making to users.","PeriodicalId":130581,"journal":{"name":"2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128909935","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}