Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157715
Y. Reddy, M. L. Ramanaiah
The Economic load dispatch (ELD) optimally allocating available generating units based on required load demand by satisfying the constraints. Based on the input output characteristics of boiler-turbine-generator set the operating cost is a convex cost function. Under practical condition including the valve point effect (VPE), ramp rate limits (RRL), prohibited operating zones (POZs) and multiple fuels makes the cost function as non-convex and ELD is a complex problem. In order to handle complex ELD problem, a novel human intelligence-based metaheuristic optimization technique called the mountaineering team-based optimization (MTBO) algorithm is proposed in this paper. The MTBO algorithm is based on the social behaviour of people as they climb mountains. In order to solve optimization problems, the proposed MTBO algorithm captures the phases of the regular and guided movement of climbers based on the leader's experience, barriers to reaching the peak and becoming stuck in local optimality, and the coordination and social cooperation of the group to protect members from natural hazards. To evaluate the efficiency of the suggested algorithm, three different cases are considered to solve the ELD problem. The MTBO method outperforms the competition in terms of robustness, ease of implementation, effective optimization performance for optimal global solutions.
{"title":"Solving Economic Load Dispatch Problem with Mountaineering Team-Based Optimization Technique","authors":"Y. Reddy, M. L. Ramanaiah","doi":"10.1109/ICEEICT56924.2023.10157715","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157715","url":null,"abstract":"The Economic load dispatch (ELD) optimally allocating available generating units based on required load demand by satisfying the constraints. Based on the input output characteristics of boiler-turbine-generator set the operating cost is a convex cost function. Under practical condition including the valve point effect (VPE), ramp rate limits (RRL), prohibited operating zones (POZs) and multiple fuels makes the cost function as non-convex and ELD is a complex problem. In order to handle complex ELD problem, a novel human intelligence-based metaheuristic optimization technique called the mountaineering team-based optimization (MTBO) algorithm is proposed in this paper. The MTBO algorithm is based on the social behaviour of people as they climb mountains. In order to solve optimization problems, the proposed MTBO algorithm captures the phases of the regular and guided movement of climbers based on the leader's experience, barriers to reaching the peak and becoming stuck in local optimality, and the coordination and social cooperation of the group to protect members from natural hazards. To evaluate the efficiency of the suggested algorithm, three different cases are considered to solve the ELD problem. The MTBO method outperforms the competition in terms of robustness, ease of implementation, effective optimization performance for optimal global solutions.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"723 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126460219","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157290
Megala G, N. Kumari
Brain Tumor is a major disease that affected in children and adults. This happens when changes occur in brain cell development and may lead the cells to partition uncontrolled and turbulently. Misclassification of these tumor cells may lead to consequences. The main objective of our examination is to distinguish the powerful and prescient calculation for the identification of bosom malignant growth, utilizing AI calculations, and figure out the best way concerning exactness and accuracy. DeepGAN is a neural network model proposed for identifying and detecting brain Tumors in the MRI images of patients. The raw MRI images are preprocessed and then passed to the generator and discriminator of the proposed model in order to extract salient features and detect a tumor. The proposed model is evaluated on computing precision, recall, specificity, sensitivity, and accuracy. From the experimental results, the DeepGAN model outperforms with 99% of accuracy on detecting tumors.
{"title":"DeepGAN: An Enhanced Approach for Detecting Brain Tumor","authors":"Megala G, N. Kumari","doi":"10.1109/ICEEICT56924.2023.10157290","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157290","url":null,"abstract":"Brain Tumor is a major disease that affected in children and adults. This happens when changes occur in brain cell development and may lead the cells to partition uncontrolled and turbulently. Misclassification of these tumor cells may lead to consequences. The main objective of our examination is to distinguish the powerful and prescient calculation for the identification of bosom malignant growth, utilizing AI calculations, and figure out the best way concerning exactness and accuracy. DeepGAN is a neural network model proposed for identifying and detecting brain Tumors in the MRI images of patients. The raw MRI images are preprocessed and then passed to the generator and discriminator of the proposed model in order to extract salient features and detect a tumor. The proposed model is evaluated on computing precision, recall, specificity, sensitivity, and accuracy. From the experimental results, the DeepGAN model outperforms with 99% of accuracy on detecting tumors.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115852605","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 nation's ability to obtain electrical energy determines its socio economic progress. While keeping in mind different operational and technological restrictions, planning for distribution system expansion considers the services that must be installed for the distribution networks to manage the expected load demand. When distributed generation sources (DGs) are integrated, distribution network efficiency is increased, power losses are decreased, and voltage magnitude is also enhanced. In this paper, Wind Turbine Generator (WTG) as renewable energy source of four different types are integrated under two unique control scheme in conventional radial distribution topology. A statistical analysis of WTG integration is carried out for conventional 34 bus radial distribution system using ETAP simulation package on single and multiple locations. Voltage magnitude were analyzed under critical, marginal and nominal level before and after integrating DGs in test system. In addition to this loss reduction is also noted and analyzed while incorporating different types of WTGs.
{"title":"Statistical Impact Analysis of Integration of different types of WTG on Radial Distribution System","authors":"Ankush Tandon, Pooja Jain, Abhinav Goyal, Aditya Sharma, Anoop Gupta, Anmay Kapoor","doi":"10.1109/ICEEICT56924.2023.10157080","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157080","url":null,"abstract":"A nation's ability to obtain electrical energy determines its socio economic progress. While keeping in mind different operational and technological restrictions, planning for distribution system expansion considers the services that must be installed for the distribution networks to manage the expected load demand. When distributed generation sources (DGs) are integrated, distribution network efficiency is increased, power losses are decreased, and voltage magnitude is also enhanced. In this paper, Wind Turbine Generator (WTG) as renewable energy source of four different types are integrated under two unique control scheme in conventional radial distribution topology. A statistical analysis of WTG integration is carried out for conventional 34 bus radial distribution system using ETAP simulation package on single and multiple locations. Voltage magnitude were analyzed under critical, marginal and nominal level before and after integrating DGs in test system. In addition to this loss reduction is also noted and analyzed while incorporating different types of WTGs.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121475243","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10156924
Batool Hatem Akar AlKfari, R. K. Ajeena
One of the most popular algorithm security solutions for ensuring the enforgeability and non-repudiation of digital data is the elliptic curve digital signature technique. The scalar multiplication process is strongly reliant on it for speed. The proposed BRH curve is used to implement the digital signature algorithm to give alternative version of elliptic curve digital signature algorithm (ECDSA). Using BRH-digital signature algorithm (BRH-DSA) reduces calculating the addition and doubling operations of points that are lying on BRH curve. On BRH-DSA, more secure communications for encryption schemes are been done in compare to the original ECDSA.
{"title":"On Applying the BRH Curve in Digital Signature Scheme","authors":"Batool Hatem Akar AlKfari, R. K. Ajeena","doi":"10.1109/ICEEICT56924.2023.10156924","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10156924","url":null,"abstract":"One of the most popular algorithm security solutions for ensuring the enforgeability and non-repudiation of digital data is the elliptic curve digital signature technique. The scalar multiplication process is strongly reliant on it for speed. The proposed BRH curve is used to implement the digital signature algorithm to give alternative version of elliptic curve digital signature algorithm (ECDSA). Using BRH-digital signature algorithm (BRH-DSA) reduces calculating the addition and doubling operations of points that are lying on BRH curve. On BRH-DSA, more secure communications for encryption schemes are been done in compare to the original ECDSA.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132798973","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157340
Deepali Pathak, SriHarsha Vardhan, A. Dutta
In this paper, a low cost, highly efficient and compact monopole antenna for Industrial, Scientific, and Medical (ISM) applications is presented. A new spiral coil rectangular shape structure possessing meander lines is designed to achieve a resonance at 0.915 GHz response with an Omni-directional radiation pattern. The proposed architecture makes the miniaturization by turning the conducting transmission lines as coil to both left and right part of the feedline to follow symmetry in current distribution. The ground plane has been adjusted in such a way to get proper impedance because if the area of ground plane increases input impedance shift to inductive region and resonant frequency decreases respectively. Ansys HFSS 3D High Frequency Simulation Software has been used to carry out the analysis of the presented antenna. The overall volume of the proposed antenna is 4.5 X 4.5 cm2 whereas the FR4 material is used as a substrate with a relative permittivity and loss tangent of 4.4 and 0.025, correspondingly. The peak gain of 0.88 dBi is achieved with a radiation efficiency of 80 to 98% for the desired band.
本文提出了一种低成本、高效率、紧凑的单极天线，用于工业、科学和医疗(ISM)应用。设计了一种具有弯曲线的新型螺旋线圈矩形结构，以实现0.915 GHz的全向辐射响应。所提出的结构通过将导电传输线作为线圈旋转到馈线的左右两端以遵循电流分布的对称性来实现小型化。由于地平面面积增大，输入阻抗向感应区偏移，谐振频率减小，因此对地平面进行了调整，得到了合适的阻抗。利用Ansys HFSS三维高频仿真软件对所设计的天线进行了分析。所提出天线的总体体积为4.5 X 4.5 cm2，而FR4材料用作衬底，相应的相对介电常数和损耗正切为4.4和0.025。峰值增益为0.88 dBi，期望波段的辐射效率为80%至98%。
{"title":"Design of a Compact and Efficient Monopole Antenna for ISM Band Applications","authors":"Deepali Pathak, SriHarsha Vardhan, A. Dutta","doi":"10.1109/ICEEICT56924.2023.10157340","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157340","url":null,"abstract":"In this paper, a low cost, highly efficient and compact monopole antenna for Industrial, Scientific, and Medical (ISM) applications is presented. A new spiral coil rectangular shape structure possessing meander lines is designed to achieve a resonance at 0.915 GHz response with an Omni-directional radiation pattern. The proposed architecture makes the miniaturization by turning the conducting transmission lines as coil to both left and right part of the feedline to follow symmetry in current distribution. The ground plane has been adjusted in such a way to get proper impedance because if the area of ground plane increases input impedance shift to inductive region and resonant frequency decreases respectively. Ansys HFSS 3D High Frequency Simulation Software has been used to carry out the analysis of the presented antenna. The overall volume of the proposed antenna is 4.5 X 4.5 cm2 whereas the FR4 material is used as a substrate with a relative permittivity and loss tangent of 4.4 and 0.025, correspondingly. The peak gain of 0.88 dBi is achieved with a radiation efficiency of 80 to 98% for the desired band.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134462945","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157679
M. Deepak, G. Janaki, C. Bharatiraja
The wide band gap devices Gallium Nitride (GaN) and Silicon Carbide (SiC) solutions are becoming more popular in high-voltage power electronic applications. Also, they provide lower switching losses and the ability to increase switching frequencies. On the other hand, magnet less induction motor (IM) drive offers superior performance compared to other electrical machines. This paper proposed a hybrid combination of IM and bidirectional DC-DC power converters in Electric Vehicles (EVs) that helps to improve the overall performance. Therefore, improving IM and DC-DC converter topologies is essential in the future development of EV infrastructure. The integrated module reduces the cost, volume, weight, and compact size to increase the performance and consistency of the vehicle. As a solution, an IM-based DC-DC dual active bridge bidirectional converter analyzes the dynamic behavior of the machine. The implementation of this work is executed using MATLAB software. The simulation results show that the suggested design of the IM and power converter module has greater efficiency.
{"title":"Performance Analysis on Induction Motor Integrated Wide Band Gap Bidirectional Converter for Low Power Traction Applications","authors":"M. Deepak, G. Janaki, C. Bharatiraja","doi":"10.1109/ICEEICT56924.2023.10157679","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157679","url":null,"abstract":"The wide band gap devices Gallium Nitride (GaN) and Silicon Carbide (SiC) solutions are becoming more popular in high-voltage power electronic applications. Also, they provide lower switching losses and the ability to increase switching frequencies. On the other hand, magnet less induction motor (IM) drive offers superior performance compared to other electrical machines. This paper proposed a hybrid combination of IM and bidirectional DC-DC power converters in Electric Vehicles (EVs) that helps to improve the overall performance. Therefore, improving IM and DC-DC converter topologies is essential in the future development of EV infrastructure. The integrated module reduces the cost, volume, weight, and compact size to increase the performance and consistency of the vehicle. As a solution, an IM-based DC-DC dual active bridge bidirectional converter analyzes the dynamic behavior of the machine. The implementation of this work is executed using MATLAB software. The simulation results show that the suggested design of the IM and power converter module has greater efficiency.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133538854","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157578
Shuprajhaa T, Mathav Raj J, S. P., Sheeba K N, Dhayalini K
India is the largest producer of bananas, con-tributing to 1/5th of the world production. Traditional Indian banana varieties have their own health benefits and consumer preferences. Grading of ripening stages is essential for quality check during handling and export as well as domestic market consumer acceptance. The proposed work is aimed to develop a smart phone based mobile application capable of identification of various traditional Indian banana varieties along with the grading of its ripening stages. Image processing is the better choice for identification of banana varieties and the determination of colour dependent ripening stages. Combining multiple aspects of deep learning inclusive of Convolution neural network (CNN) and eXtreme Gradient Boosting (XGboost) algorithm (CNN-XGBoost), a varietal identification and ripeness grading model is developed. Images of the banana fruits are fed to the network, where the CNN acts as the trainable feature extractor of the images and XGboost in the last layer of the CNN acts as the identifier of variety and ripening stage. The identification accuracy of the proposed model is 95 % which is higher than other techniques such as Gaussian Naive Bayes classifier (66 %), support vector classifier (83.5 %) and k-nearest neighbourhood algorithm (90 %). The developed model is deployed into smart phone based mobile application to facilitate non-invasive varietal identification of banana fruits. The developed app is capable to identify various unique Indian traditional banana varieties and could provide detailed insights on the ripening stages. The computational complexity of the developed model is also lesser which reduces the computational burden of the mobile application. The developed mobile application could be of great help to the consumers to decide upon the right variety and the optimal stage of ripening to be consumed for their dietary requirement.
{"title":"Deep learning based mobile application for varietal identification and ripeness grading of traditional Indian banana varieties","authors":"Shuprajhaa T, Mathav Raj J, S. P., Sheeba K N, Dhayalini K","doi":"10.1109/ICEEICT56924.2023.10157578","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157578","url":null,"abstract":"India is the largest producer of bananas, con-tributing to 1/5th of the world production. Traditional Indian banana varieties have their own health benefits and consumer preferences. Grading of ripening stages is essential for quality check during handling and export as well as domestic market consumer acceptance. The proposed work is aimed to develop a smart phone based mobile application capable of identification of various traditional Indian banana varieties along with the grading of its ripening stages. Image processing is the better choice for identification of banana varieties and the determination of colour dependent ripening stages. Combining multiple aspects of deep learning inclusive of Convolution neural network (CNN) and eXtreme Gradient Boosting (XGboost) algorithm (CNN-XGBoost), a varietal identification and ripeness grading model is developed. Images of the banana fruits are fed to the network, where the CNN acts as the trainable feature extractor of the images and XGboost in the last layer of the CNN acts as the identifier of variety and ripening stage. The identification accuracy of the proposed model is 95 % which is higher than other techniques such as Gaussian Naive Bayes classifier (66 %), support vector classifier (83.5 %) and k-nearest neighbourhood algorithm (90 %). The developed model is deployed into smart phone based mobile application to facilitate non-invasive varietal identification of banana fruits. The developed app is capable to identify various unique Indian traditional banana varieties and could provide detailed insights on the ripening stages. The computational complexity of the developed model is also lesser which reduces the computational burden of the mobile application. The developed mobile application could be of great help to the consumers to decide upon the right variety and the optimal stage of ripening to be consumed for their dietary requirement.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125182144","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157149
A. Manuel, Madhukumar S, B. Pramanick
Biosensors have a high potential for openly acknowl-edging and analyzing various anomalies related to the human body, particularly diseases like cancer. Lung cancer (LC) rates as a significant cause of mortality and a major obstacle to raising life expectancy in every nation. The death rate may be decreased to some extent by earlier detection as most LC patients are diagnosed at the advanced stages.LC can be treated using a variety of techniques used to screen for cancer based on tumor size. The available methods are expensive and not suitable for widespread screening as they are time-consuming and have a high rate of false-positive results. Therefore, it is required to design a simple, cost-effective, early detection platform to improve clinical prognosis and survival rates. Molecular biomarkers (BM) come into the picture, acetone, pentane, ethanol, and isoprene are the four carbonyl volatile organic compounds (VOCs) associated with LC, and depending on the kind of cancer, different concentration ranges exist. In contrast to healthy people, LC patients must have distinct metabolic pathways that lead to VOC production or metabolism. Compared to Gold (Au) interdigitated electrodes (IDE), TiO2 with the Glassy carbon sensing layer exhibits significant deflection in the change of resistance with the aid of Glassy carbon IDE. This combination including glassy carbon IDE provides a broad range of use in creating biosensors.
{"title":"Design and Analysis of Glassy Carbon Material towards the Development of Biosensors for EarlyDetection of Lung Cancer","authors":"A. Manuel, Madhukumar S, B. Pramanick","doi":"10.1109/ICEEICT56924.2023.10157149","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157149","url":null,"abstract":"Biosensors have a high potential for openly acknowl-edging and analyzing various anomalies related to the human body, particularly diseases like cancer. Lung cancer (LC) rates as a significant cause of mortality and a major obstacle to raising life expectancy in every nation. The death rate may be decreased to some extent by earlier detection as most LC patients are diagnosed at the advanced stages.LC can be treated using a variety of techniques used to screen for cancer based on tumor size. The available methods are expensive and not suitable for widespread screening as they are time-consuming and have a high rate of false-positive results. Therefore, it is required to design a simple, cost-effective, early detection platform to improve clinical prognosis and survival rates. Molecular biomarkers (BM) come into the picture, acetone, pentane, ethanol, and isoprene are the four carbonyl volatile organic compounds (VOCs) associated with LC, and depending on the kind of cancer, different concentration ranges exist. In contrast to healthy people, LC patients must have distinct metabolic pathways that lead to VOC production or metabolism. Compared to Gold (Au) interdigitated electrodes (IDE), TiO2 with the Glassy carbon sensing layer exhibits significant deflection in the change of resistance with the aid of Glassy carbon IDE. This combination including glassy carbon IDE provides a broad range of use in creating biosensors.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131673712","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10157499
Malhar Bangdiwala, Sakshi Mahadik, Yashvi Mehta, A. Salunke
This paper discusses the increasing use of machine learning (ML) models in the retail industry to improve the shopping experience of customers. The focus is on virtual trial rooms, self-checkout, and personalized recommendations. Virtual trial rooms allow customers to try on clothes virtually, while self-checkout provides a faster and more convenient checkout process. Personalized recommendations based on customers' purchase history and preferences can also improve the overall shopping experience. The paper reviews literature on the use of ML models and mentions advanced models that map clothes correctly to customers' pictures and use geolocation in barcode scanners to avoid long waiting queues.
{"title":"ML-Based Retail Innovations: Virtual Fitting, Scanning and Recommendations","authors":"Malhar Bangdiwala, Sakshi Mahadik, Yashvi Mehta, A. Salunke","doi":"10.1109/ICEEICT56924.2023.10157499","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10157499","url":null,"abstract":"This paper discusses the increasing use of machine learning (ML) models in the retail industry to improve the shopping experience of customers. The focus is on virtual trial rooms, self-checkout, and personalized recommendations. Virtual trial rooms allow customers to try on clothes virtually, while self-checkout provides a faster and more convenient checkout process. Personalized recommendations based on customers' purchase history and preferences can also improve the overall shopping experience. The paper reviews literature on the use of ML models and mentions advanced models that map clothes correctly to customers' pictures and use geolocation in barcode scanners to avoid long waiting queues.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132136780","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}
Pub Date : 2023-04-05DOI: 10.1109/ICEEICT56924.2023.10156915
K. Kousalya, K Dinesh, B. Krishnakumar, K. G, Kowsika C, Ponmathi K
Data analyzing is the process of analyzing the dataset to make inferences from the information available. The main aim is to apply statistical analysis and technologies on data to solve problems. Thus, researchers introduce various algorithms for analysis the data. But the existing algorithms have not achieve the expected outcome. Thus, the proposed work also addresses to the improve the mechanism for analysis the dataset for the prediction of an optimal algorithm for diagnosis of Chronic Obstructive Pulmonary Disease (COPD). Airflow into and out of the lungs is impeded by COPD. Long-term exposure to irritating gases or particles, most typically from cigarette smoke, is frequently the cause. People with COPD have a higher risk of developing heart disease, lung cancer, and a variety of other disorders. Here this work compares various machine learning algorithms for the huge volume of medical data with multiple attributes. The objective is to predict the algorithm which has the highest accuracy. With the help of analytics of the chosen dataset, the above-mentioned models are deployed and compared for the prediction of the algorithm with the highest accuracy rate of 97%.
{"title":"Prediction of Optimal Algorithm For Diagnosis of Chronic Obstructive Pulmonary Disease","authors":"K. Kousalya, K Dinesh, B. Krishnakumar, K. G, Kowsika C, Ponmathi K","doi":"10.1109/ICEEICT56924.2023.10156915","DOIUrl":"https://doi.org/10.1109/ICEEICT56924.2023.10156915","url":null,"abstract":"Data analyzing is the process of analyzing the dataset to make inferences from the information available. The main aim is to apply statistical analysis and technologies on data to solve problems. Thus, researchers introduce various algorithms for analysis the data. But the existing algorithms have not achieve the expected outcome. Thus, the proposed work also addresses to the improve the mechanism for analysis the dataset for the prediction of an optimal algorithm for diagnosis of Chronic Obstructive Pulmonary Disease (COPD). Airflow into and out of the lungs is impeded by COPD. Long-term exposure to irritating gases or particles, most typically from cigarette smoke, is frequently the cause. People with COPD have a higher risk of developing heart disease, lung cancer, and a variety of other disorders. Here this work compares various machine learning algorithms for the huge volume of medical data with multiple attributes. The objective is to predict the algorithm which has the highest accuracy. With the help of analytics of the chosen dataset, the above-mentioned models are deployed and compared for the prediction of the algorithm with the highest accuracy rate of 97%.","PeriodicalId":345324,"journal":{"name":"2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129084086","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}
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