Siddharth Tripathi, M. Gumma, Srinivasarao Potarlanka
{"title":"Virtual design optimization of a BLDC motor for a two wheeler electric cargo vehicle","authors":"Siddharth Tripathi, M. Gumma, Srinivasarao Potarlanka","doi":"10.1109/ASIANCON55314.2022.9909490","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909490","url":null,"abstract":"This paper focuses on developing an optimized design of a brushless DC motor (BLDCM) for an electric two-wheeler cargo vehicle. Designing an electric motor for a two-wheeler presents several challenges as the design must be highly optimized for size, mass and cost while also delivering the required torque and speed at various loads and road gradients. The motor design presented in this paper takes the aforementioned considerations into account and focuses on the optimization of motor design. The optimization of motor design is performed using response surface methodology while considering the design of the motor as a multiple response problem. The designed motor is further analyzed using 2-D finite element analysis (FEA) and the performance charts of the motor are obtained.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117010549","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":"Human-Face Image Retrieving Based Texture Feature Extraction Method","authors":"Shaimaa Hameed Shaker","doi":"10.1109/ASIANCON55314.2022.9908713","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908713","url":null,"abstract":"The face image retrieval solutions are widely studied, Although it deal with different facial features and difficulties to retrieve facial images due to the similarity of these features. This paper introduces a solution of human face-images retrieval based on a combination feature extraction methods where there are some challenges related with human-face image detection and then retrieving. Human face-images retrieving used in various fields like justification, Criminal Evidence and law inspections and robotic intelligence. The research-proposal contributes to conquer on a number of confronts in images of human-face detections then accurate retrieving in acceptable time. So this work deals with getting higher rate of recognition using a combination method of Gray-Level-Co-occurrence-Matrix(GLCM) and Local-Binary-Patterns (LBP) as feature-descriptors and classifiers to develop face-image recognition. First of all some previous processing techniques of image to detect the centre of face image then GLCM calculation method involves process of gray image, after that a number of statistical-texture attributes and 2nd order-attributes are obtained. The LBP technique acts as feature extraction after the representation of a human-face image, and finally the classification. The histograms are finding of blocks of an image of human-face. Then retrieve human-face image based minimum difference between attributes of a strange human-face image with the features of familiar images. All findings of this work were evaluate using MSE, Chi-square test and PSNR. Olivetti Research Laboratory ORL human-face images dataset used in this proposal. The experiments showed that the combination technique detecting the human-faces grows accuracy rate, and effectiveness. The results show increase in recognition exactitude to be 98%.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116651495","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 Air Substrate Microstrip Patch Antenna for N77 Band Application","authors":"Nalin Saxena","doi":"10.1109/ASIANCON55314.2022.9909247","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909247","url":null,"abstract":"A low cost compact microstrip patch antenna is developed using air as substrate. The antenna is fed diagonally using a coaxial cable. The antenna has a VSWR <2 from 3.23 GHz to 4.2 GHz. Air has been used to cut down the cost of the antenna and to make the antenna more rugged the patch is made of 1 mm thickness. The maximum gain varies between 8.1 dBi to 9 dBi. The antenna is designed and simulated in CST microwave studio.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438597","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}
Ashish Ranjan, Namrata K. Pathare, S. Dhavale, Suresh Kumar
{"title":"Performance Analysis of YOLO Algorithms for Real-Time Crowd Counting","authors":"Ashish Ranjan, Namrata K. Pathare, S. Dhavale, Suresh Kumar","doi":"10.1109/ASIANCON55314.2022.9909018","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909018","url":null,"abstract":"Real-time head detection with counting based on crowded scenes is a very challenging and computationally complex task in the case of lengthy surveillance videos. Existing head detection methods suffer from slow detection and a high rate of missed detection, especially in the case of congested crowd regions as well as occluded heads. In this work, we performed performance analysis of various YOLO (You Look Only Once) architectures for real-time head detection and counting. We evaluated different YOLO architectures on standard datasets like SCUT_HEAD_A, SCUT_HEAD_B, and the Brainwash dataset. After experimental analysis, it is found that YOLOR outperforms by providing an mAP value of 0.91, 0.92, and 0.95 on the SCUT_HEAD_A dataset, SCUT_HEAD_B dataset, and Brainwash dataset, respectively..","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"619 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116077958","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":"Design and Analysis of A Dual Band MIMO Antenna Array for 5G Mobile Phone","authors":"Shweta J. Meshram, G. D. Nagoshe","doi":"10.1109/ASIANCON55314.2022.9909389","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909389","url":null,"abstract":"The small and efficient antenna having multi-input and multi output communication capability is the need of the time. Considering this as motivation, A Dual band MIMO Antenna Array for 5G Mobile Phone is disclosed through this research paper. The proposed assumptions are simulated using Ansys HFSS simulation tool. The performance of the proposed design are evaluated using different restrictions like Voltage Standing Wave Ratio (VSWR), 2 Dimensional Radiation Pattern and 3 Dimensional Radiation Pattern, Return Loss, Bandwidth and Gain.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114391161","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":"Design and Implementation of Spherical Dielectric Resonator Antenna for Vehicular Applications","authors":"S. Sharma, R. Yaduvanshi","doi":"10.1109/ASIANCON55314.2022.9909180","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909180","url":null,"abstract":"With the invention of autonomous vehicles, the automobile industry has made a huge mark all over the world. A self-driving car, also known as an autonomous car, is a vehicle that can sense its surroundings and operate safely with little or no human interaction. Its goal is to reduce the number of people killed or injured in car accidents, particularly those caused by driver distraction. The objective of this paper is to design a spherical dielectric resonator vehicular antenna (SDRA) at 24 GHz for Light Detection and Ranging (LIDAR) application and amateur radio. Antenna so designed has high efficiency with novel geometry. It is compact in shape with high gain.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"61 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114438362","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 Cyberbullying Using Machine Learning and Deep Learning Algorithms","authors":"A. G, D. Uma","doi":"10.1109/ASIANCON55314.2022.9908898","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908898","url":null,"abstract":"Use of digital technologies lead to the development of cyberbullying and social media has become a major source for it compared to mobile phones, platforms such as gaming and messaging. Cyberbullying can take several forms that includes sexual remarks, threats, hate mails and posting false things about someone which can be seen and read by millions of people. Compared to traditional bullying, cyberbullying has a longer lasting effect on the victim which can affect them physically or emotionally or mentally or in all the forms. Number of suicides due to cyberbullying has increased in recent years and India is one among the four countries that has more number of cases in cyberbullying. Prevention of cyberbullying has become manda-tory in universities and schools due to rising cases since 2015. This paper aims to detect cyberbullying comments automatically using Machine learning and Deep learning techniques. Metrics such as accuracy, precision, recall and F1-score used to evaluate the model performance. It is found that Gated Recurrent Unit, a deep learning technique outperformed all the other techniques which are considered in this paper with an accuracy of 95.47%.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114510960","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":"Design and Implementation of Artificial Retinal Photoreceptors","authors":"Manishika Tripathi, R. Yaduvanshi","doi":"10.1109/ASIANCON55314.2022.9909222","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909222","url":null,"abstract":"The electromagnetic modeling of human retinal photoreceptors is being introduced as an antenna concept. The most conventional models have not been analysed in the case of electromagnetic spectrum issues specially antenna behaviour. These common commercial models include Argus I, Argus II (the second sight), Alpha-IMS, fractal prosthesis (FracRet AIM), etc. In this paper, the proposed model is based on dielectric resonator antenna (DRA) for retina photoreceptors of human eye (cones and rods) is being analysed in the frequency range (400-750 THz). A CDRA operating at 8.72 GHz has been simulated and fabricated. Single rod photoreceptor cell is represented by a cylindrical DRA which is simulated at 454.6THz using CST software. The results show that the model is basically good for vision spectrum. It is being indicated by proper S1,1 (return loss below -10dB in majority of the band) with invaluable resonances in a wide range of frequencies from 400THz to 750THz (vision spectrum), suitable Z1,1 (input impedance), gain and compact size.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126786410","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":"Implementation and Performance Analysis of EPLL Based Field Oriented Control Algorithm for Speed Control in Electrified Transportation Systems","authors":"Sushil Karvekar, P. Joshi","doi":"10.1109/ASIANCON55314.2022.9909052","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9909052","url":null,"abstract":"The paper presents performance analysis of speed control techniques for Induction motor and BLDC motor using EPLL based field oriented control algorithm. EPLL is an adaptive notch filter used for parameter estimation and synchronizing the control signals in rotating reference frame. It improves the overall efficiency by reducing the computational burden during the estimation of parameters. The simulation for speed control of these ac motors is implemented using Matlab/Simulink and the results demonstrate the effectiveness of the proposed system. The hardware implementation of the speed control strategy for BLDC motor is presented using C2000 DSP microcontrollers and DRV8301 based inverter. The real-time implementation of control algorithm using DSP controller is discussed for speed control of BLDC motor.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126991781","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}
Manjunath R. Kounte, Niran N, Pranav Hegde, Nisha R Dandur, N. S
{"title":"Drone-based Detection and Geo-Mapping of Wastes, Weeds and Diseases in Plants using Deep Learning","authors":"Manjunath R. Kounte, Niran N, Pranav Hegde, Nisha R Dandur, N. S","doi":"10.1109/ASIANCON55314.2022.9908781","DOIUrl":"https://doi.org/10.1109/ASIANCON55314.2022.9908781","url":null,"abstract":"It has been recognised in recent years how detrimental pollution has been to the environment, as evidenced by global warming and a decline in the standard of living in developing nations. When it comes to pollution, plastic pollution is one of the most serious issues that humanity has created. Apart from the fact that plastics are non-biodegradable, they also reduce plant yields and deplete soil fertility. To avoid this situation, waste management education is required. It is critical to eliminate these contaminants prior to their ability to seep deeply into the soil. Weeds are unwelcome plants that grow in close proximity to other plants. They not only supplant healthy plants in terms of development, but also feed on them, robbing them of nutrients and resulting in a significant decrease in agricultural production. Another factor complicating agricultural production is the presence of plant diseases. Scientists are engaged in a variety of endeavours, including forecasting illnesses, predicting their potential, and identifying diseases before they become fatal.Our new method employs a first-of-its-kind strategy that involves mapping a region using a drone’s vector and then detecting map errors using the UDP stream from the drone’s camera, a first in the industry. This data is analysed in real time using Nvidia Deep Stream. To train our data-set, we will use a custom-built Sequential Convolution Neural Network.","PeriodicalId":429704,"journal":{"name":"2022 2nd Asian Conference on Innovation in Technology (ASIANCON)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125955226","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}