{"title":"Power Management in DC Microgrid Based on Distributed Energy Sources’ Available Virtual Generation","authors":"Avula Rohit Kumar, Vikas Gupta, D. Saxena","doi":"10.1109/ICAECT54875.2022.9808030","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808030","url":null,"abstract":"A power algorithm strategy is presented along with a DC microgrid model with Distributed Energy Resources (DERs) with PV source, Wind source and Energy Storage System (ESS). By utilizing the source power to its maximum capabilities, this power flow approach aids in overcoming power sharing among DERs and DC bus voltage regulation. The power algorithm uses virtual generation, which is defined by the extra power of the source beyond the average power rating. This virtual generation is used to generate a reference value. The virtual generation from each source is determined by the power supply available to the source. The proposed control algorithm strategy improves the lifespan of ESS by reducing its charging/ discharging cycles. This also reduces the stress on the interfacing converters and DC bus voltage regulation. The proposed control algorithm and microgrid model are implemented in MATLAB simulation.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114275820","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}
Tashreef Abdullah Araf, A. Siddika, Sadullah Karimi, Md. Golam Rabiul Alam
{"title":"Real-Time Face Emotion Recognition and Visualization using Grad-CAM","authors":"Tashreef Abdullah Araf, A. Siddika, Sadullah Karimi, Md. Golam Rabiul Alam","doi":"10.1109/ICAECT54875.2022.9807868","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807868","url":null,"abstract":"One of the most indicative ways of communication is facial expressions. The Face attributes are the contended mode to specify human sensitivity. Hence facial emotion recognition is necessary for human-machine interaction systems. The AI nowadays can also understand emotions verifying facial movement and intimation like a human brain does. But tracing the mechanism of AI is challenging as most of the AI methods are referred to as \"Black box\". To perceive the insights of AI algorithms the term Explainable AI has been brought to light. Explainable AI is a need to implement and build proper, fair, and responsible models that can even be flexible to use on a large production basis. In this paper, Cascade Classifier for emotion recognition and Grad-CAM for visualization of model detection has been employed. The region of interest of the face is located to extract features which are categorized into 7 classes. The results obtained are appreciable and can be applied in works relating to human expression detection.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116125128","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}
A. Shanmuga Sundaram Devi, A. T, R. Satpathy, Malabika Nayak, M. Reka, Prakash Kumar Mohapatra
{"title":"Prediction of Maintenance Time and IoT Device Failures using Artificial Intelligence","authors":"A. Shanmuga Sundaram Devi, A. T, R. Satpathy, Malabika Nayak, M. Reka, Prakash Kumar Mohapatra","doi":"10.1109/ICAECT54875.2022.9808060","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808060","url":null,"abstract":"The real-time mechatronic system is critical in today's industry for increasing productivity and product quality to meet consumer demands. The quality of a product is largely determined by the quality of the machines employed in the manufacturing process. The reliability prediction model's accuracy is improved by sorting the submodules systematically and feeding the qualitative and quantitative fault data acquired into it. Fault detection and reliability forecasting modules are included in this model. Predictive maintenance aims to reduce equipment downtime and lessen the impact of failures by scheduling maintenance activities prior to the commencement of failures. This hastened the implementation of Genetic algorithms based on artificial intelligence and machine learning to predict equipment problems. For software fault prediction, a Bayes Decision classifier is used in this study to find error probabilities and integrals using feature and classifier data, this work explains how to make basic predictions about software errors. Chernoff Bound and Bhattacharyya Bound are also discussed in the suggested software error prediction using fault-predictable zone. Software errors can be predicted using a new Bayesian decision procedure that incorporates error probabilities and integrals from a machine learning model.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125330441","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":"Deep Learning Approach for Sentimental Analysis of Hotel Review on Bengali text","authors":"Jannatul Jahan Bonny, Nuzhat Jabeen Haque, Md. Rohmat Ulla, P. Kanungoe, Zahid Hassan Ome, Mohd. Istiaq Hossain Junaid","doi":"10.1109/ICAECT54875.2022.9808001","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808001","url":null,"abstract":"We live in an age of technology. Technology is advancing day by day. People in India (Kolkata), Bangladesh, who use the Bengali language as a communication language, use the internet daily. Internet users are increasing day by day. Moreover, people like to visit many tourist places. So, they have to stay in a hotel or resort. They give various reviews on websites and many social media. But not everybody gives thoughts in the English language. People in Bangladesh, India (Kolkata) give reviews in Bengali. So, this is hard to detect for the hotel management system. So, in this paper, we are planning to build a model that can analyze the Bengali text and detect whether the reviews are bad or good since there is no work on Bengali text in this particular area. The datas are collected by surveys, various social media reviews, ratings, etc., and then label those data. After cleaning and extracting multiple features, the datas were trained into DL(Deep Learning) and ML(Machine Learning) models. At the end, it is found that the Long Term Short Term (LSTM) comparatively gives better results than other models. This work will create a significant effect on the hotel and tourism industries.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126625306","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}
D. Lavanya, D. Derwin, R. Remya, B. Shan, O. Singh, Umamaheswari. K
{"title":"Diagnosis of Early-Stage Diabetic Retinopathy in Digital Fundus Images","authors":"D. Lavanya, D. Derwin, R. Remya, B. Shan, O. Singh, Umamaheswari. K","doi":"10.1109/ICAECT54875.2022.9807977","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807977","url":null,"abstract":"Diabetic Retinopathy (DR) is a chronic disease that may cause vision loss in diabetic patients. A regular eye screening is essential to grade the stages of DR such as Microaneurysms (MAs), exudates and drusen in retinal images acquired using fundus camera. Microaneurysm is an early stage of DR, characterized by small red spots on the retina due to blood and fluid leakage from the weak capillary wall. Hence early detection is vital in preventing the diabetic retinopathy and this article explores an automatic screening system that focus on the early detection of DR which is referred as Microaneurysm. The proposed automatic decision system follow the stages of acquisition of color fundus images, pre-processing the input fundus image, manual selection of Microaneurysm area by Region Of Interest (ROI) and classification of diabetic retinopathy is more helpful for early detection and analysis of diabetic retinopathy. The detection process comprises of image pre-processing, feature extraction and classification methods. The proposed method has been applied to color fundus image in feature extraction, classification and provided with improved outcomes for detecting Microaneurysm.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127720323","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":"On-board Health Prognosis of Lithium-Ion Battery Based on the Estimation of Internal Resistance Under Resistive and Inductive Loading Conditions","authors":"Pranjal Barman, Sushanta Bordoloi, C. Hazarika","doi":"10.1109/ICAECT54875.2022.9807976","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807976","url":null,"abstract":"In this work an effective health indicator to assess the useful battery life of lithium-ion battery under resistive and inductive loading conditions is presented. The health indicator in the form of battery internal resistance is derived from the experimentally obtained real time battery information in multiple charging-discharging cycles. Relying on the proposed health indicator, the state of health and end of life of the battery can be predicted at reasonable accuracy. The work also includes several sets of experimental data from the battery at different loading conditions within a particular range of operating temperature. A model-based prediction approach to forecast the battery health is derived from the dynamically changing internal resistance at different discharging instances. In this article, a simple and cost effective experimental set-up with necessary acquisition method is presented which extracts the battery information for proper analysis. The effectiveness and adaptability of the developed method is demonstrated in terms of experimental results, case studies and analysis.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125864670","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 Prediction of GaN HEMTs Using Angelov and Curtice Models","authors":"Famin Rahman Rakib, Refat Uddin Rafi, M. Alim","doi":"10.1109/ICAECT54875.2022.9808081","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808081","url":null,"abstract":"The performance of GaN HEMTs is projected in this paper with experimental evaluation using the Angelov model and the Curtice model of FETs. Two Angelov model parameters (α, λ) and three Curtice model parameters (of α, λ, and β) are used to match the experimental findings of the dc characteristics to articulate and specify their impacts on the linear and saturation zones. A computational comparison between the projected performance has been showcased. Moreover, by comparing the simulated and experimental data for both models, a good match in transconductance and output conductance was observed. In all models, the DC findings of the examined GaN HEMT were very similar.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126859328","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":"DTC-SVM Control of Induction Motor Based on Dragonfly Optimization Algorithm","authors":"Amirah J. Mohammed, R. Hassan","doi":"10.1109/ICAECT54875.2022.9807894","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807894","url":null,"abstract":"In this work a performance investigation of the modified Direct Torque Control based on Space Vector Modulation (DTC-SVM) control algorithm has been performed. The investigation process was accomplished by comparing the performance of this algorithm by two methods for tuning the parameters of its controllers. In the first method, the parameters of the Proportional Integral (PI) controllers were tuned by trial and error. The second method was to utilizes the Dragonfly optimization method (DF) for tuning these parameters. The DTC-SVM supplies a desired switching pulses to the 3-phase 3-level Flying Capacitor Inverter (TLFCI). The concerned inverter drives a 3-phase induction motor to achieve the desired speed and to reduce the ripples of the flux and torque. The DTC-SVM control and the DF algorithms are implemented using MATLAB/Simulink program. The simulation process is carried out for verifying the performance of these two control systems. With the DTC-SVM based on DF, the optimization process is accomplished firstly to extract the PIs parameters. These extracted parameters were employed in the DTC-SVM control system. Simulation results show an acceptable performance for the control systems with the DTC-SVM based on DF being the best in reducing torque ripples.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124428025","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 of CMOS IR-UWB Transmitter with UWB Antenna","authors":"Shanjida Akter, P. K. Saha, Tawfiq Amin","doi":"10.1109/ICAECT54875.2022.9808031","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808031","url":null,"abstract":"Ultra-Wideband (UWB) communication has emerged as a high-potential wireless technology. Networks, detection and ranging, image processing and positioning systems all benefit greatly from it. Impulse radio ultra-wideband (IR-UWB) signals have a very wide transmission bandwidth and a very fast data throughput across short distances. The analysis and design of transmitter circuits and antennas for IR-UWB applications are discussed in this work. The circuits in concern are UWB signal generating circuits and UWB antenna, which work together to create entire UWB transmitter. This research focuses on UWB system that uses information-carrying ultra-short low-power pulses to transmit data using Gaussian monocycle pulse which is implemented in 90 nm CMOS technology and using Advanced Design System (ADS) software. The simulation shows 508 mV peak to peak pulse amplitude and the pulse width of 150 ps for the 1st derivative Gaussian monocycle pulse. Total power consumption of the transmitter circuit is also very low. The suggested IR-UWB transmitter offers an appealing technique of generating UWB signals for UWB communications and radar detection application.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121941188","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}
N. Ramesh, C. V. Sai Karthik, Jampani Yugesh, B. Vani, B. N. Manjunatha Reddy
{"title":"Analysis of Potential Regions for Maritime using QGIS Tool","authors":"N. Ramesh, C. V. Sai Karthik, Jampani Yugesh, B. Vani, B. N. Manjunatha Reddy","doi":"10.1109/ICAECT54875.2022.9808015","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808015","url":null,"abstract":"The paper explains the advancement of seafood production using remote sensing methods virtually. It is an attempt to coordinate the gauging rules as well as GIS to determine an appropriate basis for arranging drifting enclosures in the seaward climate, which could serve as a model for comparable cases. Now a days due to more population the agriculture food is not sufficient for the survival of the human beings. So, people are checking for the alternatives and marine aqua culture is the fast-growing food resources. Marine aqua culture has high value of species for the food supplies and also has negative impact on water supply .The main objective of this paper is to use GIS software to create environmental models for the development of seafood and to enhance food production .The analysis of variance revealed critical spatial variation for ocean surface current, total suspended matter, and chlorophyll-a .By using GIS software we are collecting the parameters of the oceans and check the suitable locations for seafood production. Coastal mariculture is presently confronting huge tensions, particularly from the anthropogenic exercises, variable climate, and multi-client struggle.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122266629","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}