2023 International Conference on Inventive Computation Technologies (ICICT)最新文献_第4页

The State-of-the-art Energy Management Strategy in Hybrid Electric Vehicles for Real-time Optimization 面向实时优化的混合动力汽车能量管理策略

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134496

Swathi Dasi, Rajendar Sandiri, T. Anuradha, T. Santhi Sri, Sankararao Majji, K. Murugan

{"title":"The State-of-the-art Energy Management Strategy in Hybrid Electric Vehicles for Real-time Optimization","authors":"Swathi Dasi, Rajendar Sandiri, T. Anuradha, T. Santhi Sri, Sankararao Majji, K. Murugan","doi":"10.1109/ICICT57646.2023.10134496","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134496","url":null,"abstract":"Oil consumption is rising faster in India than in any other major economy. There appears to be a need for 9.8 million barrels of oil per day by the year 2040. In light of rising pollution levels, many countries are advocating for Gridable Electric Vehicles (GEVs). This study focuses on the role that GEVs can play in aiding the MGCS by controlling an Intelligent Energy Management System (IEMS) while in transit. Additionally, the energy consumption rate (ECR) of the battery and battery stress of vehicle are of greater significance in the analysis of Hybrid Electric Vehicles (HEVs) with the goal of enhancing driving range and battery life span. New developments in automotive technology aim to lower emissions and stress on the vehicle's battery. The overarching goal of this work is to create optimization and prediction models for examining the impact of control elements like EMCS, vehicle model, and SoC of ESSs on vehicle performance like energy consumption rate (ERR) and battery stress. It also discusses howto decide which car controls to use to optimise performance. Design of experiment (DoE) methods are used to examine the cumulative effect of control factors on vehicle performances.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116003724","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}

引用次数: 1

On Automatic Target Recognition (ATR) using Inverse Synthetic Aperture Radar Images 基于逆合成孔径雷达图像的自动目标识别(ATR)

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134428

T. Sudarson Rama Perumal, G. Gaurav, V. L. Helen Josephine, R. Joshua Samuel Raj

{"title":"On Automatic Target Recognition (ATR) using Inverse Synthetic Aperture Radar Images","authors":"T. Sudarson Rama Perumal, G. Gaurav, V. L. Helen Josephine, R. Joshua Samuel Raj","doi":"10.1109/ICICT57646.2023.10134428","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134428","url":null,"abstract":"Inverse Synthetic Aperture Radar (ISAR) is used to image sea surface targets during day/night and all-weather capabilities for applications such as coastal surveillance, ship self-defense, suppression of drug trafficking etc. Hence automating classification of ships by means of machine learning methods has become more significant. Typical classification approaches consist of pre-processing, feature extraction and processing by classifiers. Image processing techniques are applied for pre-processing ISAR images. Transformation invariant features are then extracted to which classifiers such as SVM, Neural Networks (NNs) are applied The performance of these algorithms depend on the manually chosen features and is trained to perform well for different target profiles. The target image (profile of target) varies depending on the target type, aspect angle and motion introduced due to different sea states. In addition, Deep learning methods are also being explored for classification of ships. The challenge is to classify ships for different sea conditions and image acquisition parameters with limited database and processing resource.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123685427","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}

引用次数: 0

A Proficient Test Data Compression and Decompression System for Enhanced Test Competence in SOC Testing 高效测试数据压缩与解压缩系统，提高SOC测试能力

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134445

D. J. Jhancy Mabel, M. C. Viola Stella Mary

引用次数: 0

Design and Implementation of IoT Enabled Grass Cutting Robot Powered by Solar PV System 基于太阳能光伏系统的物联网割草机器人的设计与实现

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134306

Mohan Kumar R, V. S., Kathirvel C, Rubia Gandhi R R, D. N, Senthilkumar T

{"title":"Design and Implementation of IoT Enabled Grass Cutting Robot Powered by Solar PV System","authors":"Mohan Kumar R, V. S., Kathirvel C, Rubia Gandhi R R, D. N, Senthilkumar T","doi":"10.1109/ICICT57646.2023.10134306","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134306","url":null,"abstract":"The conventional energy sources are diminishing, and researches try to make the most use of renewable energy sources. This proposed method was designed to have a solar-powered grass-cutting robot that can run by utilizing the solar energy as primary energy source and facilitates to avoid obstacles. The usage of electricity and fuel is avoided since solar energy is being used for the proposed system. The blade is coupled with DC motor to cut the grass and Battery Operated (BO) motor was utilized for controlling the directions of cutter. These motors and the energy from the solar panel are interfaced with the NodeMCU microcontroller. The directions of the robot's wheels and the On/Off process of the cutter is controlled by a mobile application which is called Remote XY. This mobile app is connected to the wi-fi network of the microcontroller. A robot is a system that executes specific tasks with little or no human intervention at high accuracy and precision. This proposed system is based on a working principle of a grass cutter robot, and it involves less human intervention and operates at high accuracy in the respective application. This grass cutter robot can be accessed in all directions with the help of the Internet of Things (IoT). IoT is used to connect and operate the robot through mobile applications.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124707814","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}

引用次数: 0

An Evaluation of Stock Market Prediction using Supervised Machine Learning Techniques 用监督式机器学习技术评估股市预测

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10133970

P. Sagar, Chennappagari Maheshbabu, Gilaka Venkata Siva Teja, C. Vishnu, Derangula Venkat Sai, C. Mahesh

{"title":"An Evaluation of Stock Market Prediction using Supervised Machine Learning Techniques","authors":"P. Sagar, Chennappagari Maheshbabu, Gilaka Venkata Siva Teja, C. Vishnu, Derangula Venkat Sai, C. Mahesh","doi":"10.1109/ICICT57646.2023.10133970","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10133970","url":null,"abstract":"Stock market prediction is a technique recently used to predict the future price of the stock. This research study mainly focuses on comparing the performance of Support vector machine and Long Short Term Memory (LS TM) in stock prediction. However, LS TM faces two challenges during the prediction of the stock market: Overfitting and Feature Engineering, when it is trained on the existing data it cannot be reflect on the current market trends. It requires a lot of training data to impact the performance. To overcome these limitations and improve accuracy, SVM has been selected to predict stock market prices. By comparing both of them respectively to each other helps to measure the performance of various algorithms. Here, the accuracy is used as a metric for evaluation of the efficiency of algorithms. To achieve this, supervised machine learning techniques like Support Vector Machine(S VM), Linear Regression and Decision Trees are used to forecast the stock value of a company. Then, the data is preprocessed and split into training and testing sets. Then, a collection of supervised machine learning mechanisms like SVM are employed. The results show that Support Vector Machine delivers better performance with an accuracy of 91%.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128606618","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}

引用次数: 0

Design of a Real-Time GAN based Speech Recognizer for Consumer Electronics 消费类电子产品实时GAN语音识别器的设计

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134295

Pubali Roy, Pranav M Bidare, P. Bharadwaj, M. J

{"title":"Design of a Real-Time GAN based Speech Recognizer for Consumer Electronics","authors":"Pubali Roy, Pranav M Bidare, P. Bharadwaj, M. J","doi":"10.1109/ICICT57646.2023.10134295","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134295","url":null,"abstract":"Modern consumer electronics including automotive electronics, televisions, microwave ovens, music systems, refrigerators with speech controlled features and hands-free operation have spearheaded research in designing smart electronic devices for consumers. Real-time speech recognizer is the main module for these systems and a lot of research is in progress with the design of real-time speech recognizers with a quicker recognition time being considered as one of the challenges. Generative Adversarial Networks (GAN) are mainly used with two dimensional signals such as image for applications such as recognition, synthesis, translation etc. In this paper, an attempt is made to design and evaluate a real-time GAN based pattern recognizer for one-dimensional speech signal. In order to achieve this, the one-dimensional speech signal is first converted into a two dimensional spectrogram and fed to the GAN model for recognition. The proposed speech recognizer yielded a maximum recognition accuracy of 100% with a recognition time of 49.10ms per word. The proposed work can be easily employed to design various smart consumer electronics.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127430260","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}

引用次数: 0

Efficient Machine Learning Algorithm for Future Gold Price Prediction 未来黄金价格预测的高效机器学习算法

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134197

M. Ghute, M. Korde

引用次数: 0

Smart Solar Powered System for Unauthorized Logging 用于未经授权采伐的智能太阳能系统

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134127

S. Murali, S. Shri, P. Roshini, C. Rubavathi, R. Krishnan, K. Narayanan

引用次数: 1

Real-Time Data Cloud Transmission and Early Warning Algorithm for Outdoor Sports with Smart Glasses 智能眼镜户外运动实时数据云传输及预警算法

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/ICICT57646.2023.10134159

Gen Li

{"title":"Real-Time Data Cloud Transmission and Early Warning Algorithm for Outdoor Sports with Smart Glasses","authors":"Gen Li","doi":"10.1109/ICICT57646.2023.10134159","DOIUrl":"https://doi.org/10.1109/ICICT57646.2023.10134159","url":null,"abstract":"Through the review analysis, it is evident that most of the current big data mining methods are based on known abnormal characteristics for big data mining. Existing algorithms ignore relevant information and prior information, which reduces the reliability and efficiency of big data mining and increases the overhead of processing big data, resulting in a decrease in the overall availability and performance of big data. Hence, real-time data cloud transmission and the early warning algorithm for outdoor sports with smart glasses is studied. This research study presents 2 aspects of novelty: (1) For the data cloud transmission, the UDT is selected, the application program also uses the UDT socket interface to transmit data, and the UDT calls UDP through the Socket interface provided by the operating system. Then, the OBEX is combined to improve the efficiency. (2) For the early warning algorithm, we consider using the grid space as the clustering area to then reduce the time spent on retrieving the clustering area, ensuring high-precision picking of the clustering center and greatly improving the efficiency. Through the comparison simulation under different data sets, the missing and false alarm tests are both satisfactory.","PeriodicalId":126489,"journal":{"name":"2023 International Conference on Inventive Computation Technologies (ICICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132442863","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}

引用次数: 0

Message from the Conference Chair 会议主席致辞

2023 International Conference on Inventive Computation Technologies (ICICT) Pub Date : 2023-04-26 DOI: 10.1109/icict57646.2023.10134204

引用次数: 0