2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)最新文献_第3页

Breast Cancer Prediction using Feature Selection and Classification with XGBoost 基于XGBoost的特征选择与分类的乳腺癌预测

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111901

Raye Haarika, T. Babu, Rekha R Nair, R. M.

引用次数: 2

Analysis of Modulation schemes Using Rayleigh and AWGN channel for wireless sensor nodes in Internet of Things 基于Rayleigh和AWGN信道的物联网无线传感器节点调制方案分析

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111921

R. Mahapatra, N. Shet, G. S. Satapathi, B. Patro, Dipika Satapathy

引用次数: 0

Solving Roulette Wheel Selection Method using Swarm Intelligence for Trajectory Planning of Intelligent Systems 基于群智能的轮盘选择方法求解智能系统的轨迹规划

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111861

S. K. Gupta, Waseem Ahmad, Dimitrios Alexios Karras, Alex Khang, Chandra kumar Dixit, Bhadrappa Haralayya

{"title":"Solving Roulette Wheel Selection Method using Swarm Intelligence for Trajectory Planning of Intelligent Systems","authors":"S. K. Gupta, Waseem Ahmad, Dimitrios Alexios Karras, Alex Khang, Chandra kumar Dixit, Bhadrappa Haralayya","doi":"10.1109/ICRTEC56977.2023.10111861","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111861","url":null,"abstract":"Intelligent Systems is a defined methodical technique to solving major and somewhat complicated issues that consistently and reliably produces consistent and reliable outcomes. Understanding and benefiting from one's own experiences are two key components of intelligence, as defined by a variety of dictionaries. However, there are alternative connotations, such as the ability to learn and retain knowledge; mental ability; the ability to adapt rapidly and successfully to a new situation, etc. Intelligent systems are difficult to define and are the topic of much discussion. Intelligence may be measured in terms of a system's ability to adapt and learn from its environment, as well as its ability to handle uncertainty and inaccurate information. Using kinematic constraints such as geometric, physical, and temporal restrictions, intelligent systems attempt to design a path across a workspace that is both optimum and collision-free. When compared to motion planning, where dynamics must be taken into account, the primary goal of path planning is to discover the quickest and most efficient route while also accurately modeling the surrounding environment. In this paper, we make use of Swarm Intelligence for solving the problem of path planning in Intelligent Systems. Use of Roulette Wheel Selection algorithm is done to find the optimal path. The efficiency of the model is proved by making use of Swarm Intelligent algorithms. Comparative results are obtained for all the algorithms and it could be claimed that the Firefly algorithm performs better than the other algorithms for our proposed trajectory planning algorithm.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130369743","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

Performance Analysis of Half-Bridge LC Resonant Converter for UPS Battery Charging Application 半桥LC谐振变换器在UPS电池充电中的性能分析

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111860

Shubham Subhas Borkar, G. K P

引用次数: 0

A novel optimization approach using multi-objective PSO incorporated with SEPIC and buck-boost converters for renewable energy sources 基于SEPIC和降压变换器的可再生能源多目标粒子群优化方法

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111898

Parthasarathy P, H. Harsha, Manjunath V Gudur, N. L, Mahesh B. Neelagar, Sreekantha B

{"title":"A novel optimization approach using multi-objective PSO incorporated with SEPIC and buck-boost converters for renewable energy sources","authors":"Parthasarathy P, H. Harsha, Manjunath V Gudur, N. L, Mahesh B. Neelagar, Sreekantha B","doi":"10.1109/ICRTEC56977.2023.10111898","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111898","url":null,"abstract":"Dynamic conduct of sunlight-based vitality asset involves the need of hearty controllers that can merge to the Maximum Power Point (MPP) toward augment vitality reap. As of late, the sun powered vitality has turned out to be a standout amongst the most critical elective wellsprings of electric vitality, so it is vital to work Photovoltaic (PV) board at the ideal point to get the conceivable greatest productivity. In this article it particularly shows another improvement way to deal with expand the energy of a PV board utilizing Multi-objective Particle Swarm Optimization (PSO) advancement alongside buck-boost converters. The strategy which depends on target work speaks to the yield energy of the PV board and limitations, equity and imbalance. An enhanced SEPIC converter that joins a fixed step Model Predictive Controller (MPC), to accelerate the control circle which connected to a buck boost converter was investigated in this research article. The proposed system is of higher viability and strength over ordinary strategy and it separates most extreme information voltage and less total harmonic distortion in output. To check the converter's operation, the simulation result from MATLAB/SIMULINK is used.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114512344","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

Artificial Neural Network Based Classification Of Motor Imagery EEG Signals For Efficient Brain Computer Interface System 基于人工神经网络的高效脑机接口系统运动图像脑电信号分类

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111856

S. G, S. J

{"title":"Artificial Neural Network Based Classification Of Motor Imagery EEG Signals For Efficient Brain Computer Interface System","authors":"S. G, S. J","doi":"10.1109/ICRTEC56977.2023.10111856","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111856","url":null,"abstract":"Brain Computer Interface (BCI) systems are evolving rapidly these days because of its ability to restore independence to individuals with severe disabilities. BCI system measures the activity of the brain signal, analyses, interprets and converts them to possible actions. Motor Imagery (MI) based Electroencephalogram (EEG) signals are used widely for the development of robust BCI system. The challenges faced by MI based EEG signals are inter-subject variability, non-linearity, unpredictable and complexities in data acquisition from the subjects. In this paper, MI based EEG signals are used for the design of BCI system. The proposed work focuses on designing an accurate classifier based on Artificial Neural Network (ANN). The proposed model is trained, tested and validated on publicly available EEG dataset 'BCICompetition IV dataset 2a [7]. The efficiency of the system is evaluated based on the performance metrics such as accuracy, kappa, precision and recall. The experimental finding suggests that the proposed work for the classification of MI-EEG signals can be expanded for the creation of a reliable BCI system.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131374582","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 Deep Learning-Based Convolution Neural Networks to Forecast Wind Energy 基于深度学习的卷积神经网络预测风能

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111917

S. Kannan, P. D, Dhenesh Kumar. S, S. S

引用次数: 1

Gear Fault Diagnosis Using SVM Based on Empirical Mode Decomposition 基于经验模态分解的支持向量机齿轮故障诊断

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111852

Akhil V M, Pavan Pundalik Mangaji, Rahul N Murthy, Rakesh D, Shridatta Hegde, Sukesh V Devadiga

引用次数: 0

EVAS - Emergency Vehicle Alert System using LoRa for automobiles EVAS -使用LoRa的汽车紧急车辆警报系统

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111859

Sanjay S Tippannavar, Puneeth K M, Yashwanth S D, Madhu Sudan M P, Chandrashekar Murthy B N, Vinay Prasad M S

{"title":"EVAS - Emergency Vehicle Alert System using LoRa for automobiles","authors":"Sanjay S Tippannavar, Puneeth K M, Yashwanth S D, Madhu Sudan M P, Chandrashekar Murthy B N, Vinay Prasad M S","doi":"10.1109/ICRTEC56977.2023.10111859","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111859","url":null,"abstract":"Modern vehicles are constructed with interiors that are noticeably quieter than in the past. The quiet cars are to blame for the absence of outside sounds, including sirens. Since cities are congested and noisy, it is challenging for drivers to hear and differentiate the siren over the loud background noise, which makes it challenging for them to drive safely. Furthermore, the presence of large, tall buildings in cities obstructs siren sound transmission. The sound of the siren often goes along the street. The siren sound travels ineffectively around corners. Sound waves do, however, prefer to keep moving along the previously unobstructed route. Sound waves may bounce off of buildings and, to a certain extent, can travel around corners. The Emergency Vehicle Alert System (EVAS) is successful in transmitting a signal beyond of a siren's audible range. The signal might be sent using one of the several easily available communication frequencies. Communication frequencies have a wider transmission range than siren sounds, which can only transmit information over short distances. Amplifiers may be used to reach the busiest downtown areas where tall buildings could interfere with transmission frequencies. A light, audio recording, alphanumeric display, or any well-known notification method might be used to transmit the notice warning. One or more notice warnings may be used in combination for the driver's quicker perception. As sound isolation improves, the emergency vehicle warning system's effectiveness declines. The sensitivity of emergency vehicles is reduced as a result of the longer emergency response times and driving risks. This concept describes a novel system that would enhance the present alarm systems of emergency vehicles and address the acoustic isolation problem. An alarm system transmits signals from one or more emergency vehicles to the nearby commuter cars.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125910535","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

Image Denoising Using Feature Map Based Convolutional Neural Networks 基于特征映射的卷积神经网络图像去噪

2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC) Pub Date : 2023-02-10 DOI: 10.1109/ICRTEC56977.2023.10111929

A. Ravi, Gnanasree Dupaguntla, Devi Krishna Tadepalli, Swetha Vissamsetti, Radha Krishna Achanta

{"title":"Image Denoising Using Feature Map Based Convolutional Neural Networks","authors":"A. Ravi, Gnanasree Dupaguntla, Devi Krishna Tadepalli, Swetha Vissamsetti, Radha Krishna Achanta","doi":"10.1109/ICRTEC56977.2023.10111929","DOIUrl":"https://doi.org/10.1109/ICRTEC56977.2023.10111929","url":null,"abstract":"Noise corruption is inexorable in image recognition and it may heavily agitate the optical features of the capturing image. Convolutional Neural Networks (CNNs) have acquired good contemplation in the research of denoising. They possess various approaches to removing noise from a degraded image and to reconstruct an image with high visual quality. Because of its stratified learning and self-operating feature extraction capabilities, CNN has become useful for Machine Vision tasks. Furthermore, these methods mostly train a specified model for every noise level and desire multiple methods for denoising images with various noise levels. Large feature sets result in producing a noise effect, which causes an over-fitting of the network. A new method of Feature Map Based Convolution Neural Network (FMBCNN) has been introduced for image denoising. The quantitative analysis is performed by calculating four metrics of MSE (Mean Square Error), PSNR (Peak Signal to Noise Ratio), SSIM (Structural Similarity Index), and Entropy. They put forward a building block for Convolutional Neural Networks that tends to increase channel interdependencies at nearly no cost of computation. The weights accompanying a kernel also called a mask, are tuned to choose features dynamically. The performance of classification, segmentation, and detection modules is heavily influenced by feature selection.","PeriodicalId":217375,"journal":{"name":"2023 International Conference on Recent Trends in Electronics and Communication (ICRTEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130500413","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