Pub Date : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836398
Hasan Muhammad Kafi, Abu Saleh Musa Miah, Jungpil Shin, Md. Nahid Siddique
Chronic kidney disease (CKD) is heterogeneous disorders that affects the renal functions and structures of millions of people around the globe, and it is one of the leading causes of morbidity and mortality. Given the circumstances, several studies had been conducted in order to detect CKD at an early stage. However, each of these studies has its own set of limitations such as the failure to employ proper methods for coping with missing values, anomalies, and class imbalance problems, overfitting issues, and so on. Taking into account the shortcomings that recent research has uncovered, we propose a novel CKD diagnosis method based on 1D Convolutional Neural Network (1D CNN) that overcomes the aforementioned drawbacks while also significantly improving diagnosis accuracy. The Chronic Kidney Diseases Dataset from the UCI Machine Learning Repository has been used in this study. MissForest imputation, a precise non-parametric missing value imputation process, has been used to handle missing data. Additionally, memory-efficient Isolation Forest has been applied to deal with anomalies. After evaluating the model with chronic kidney disease dataset, our proposed model achieved 99.21 % accuracy which is better than the state of the art method.
{"title":"A Lite-Weight Clinical Features Based Chronic Kidney Disease Diagnosis System Using 1D Convolutional Neural Network","authors":"Hasan Muhammad Kafi, Abu Saleh Musa Miah, Jungpil Shin, Md. Nahid Siddique","doi":"10.1109/icaeee54957.2022.9836398","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836398","url":null,"abstract":"Chronic kidney disease (CKD) is heterogeneous disorders that affects the renal functions and structures of millions of people around the globe, and it is one of the leading causes of morbidity and mortality. Given the circumstances, several studies had been conducted in order to detect CKD at an early stage. However, each of these studies has its own set of limitations such as the failure to employ proper methods for coping with missing values, anomalies, and class imbalance problems, overfitting issues, and so on. Taking into account the shortcomings that recent research has uncovered, we propose a novel CKD diagnosis method based on 1D Convolutional Neural Network (1D CNN) that overcomes the aforementioned drawbacks while also significantly improving diagnosis accuracy. The Chronic Kidney Diseases Dataset from the UCI Machine Learning Repository has been used in this study. MissForest imputation, a precise non-parametric missing value imputation process, has been used to handle missing data. Additionally, memory-efficient Isolation Forest has been applied to deal with anomalies. After evaluating the model with chronic kidney disease dataset, our proposed model achieved 99.21 % accuracy which is better than the state of the art method.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126106844","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836369
Md. Selim Reza, Md. Tawfiq Amin
This paper presents a dual gated n-channel graphene metal-oxide-semiconductor field-effect transistor (MOSFET) with a gapless large-area graphene channel. The semiclassical ballistic model is used in Comsol V5.6 software to calculate the DC characteristics, quantum capacitance, and cut-off frequency for this proposed design. For dual gate formation, SiO2 is used as back gate oxide and HfO2 layer is used as top gate oxide. This proposed Graphene MOSFET is easy to realize and can be easily fabricated by using the recent fabrication technique. The analytical approach shows, Graphene offers less threshold voltage, larger current capability, very little gate capacitance and is having a better cut-off frequency. The excellent characteristics will make the proposed Graphene MOSFET an excellent candidate in future high-speed analog electronic circuits applications.
{"title":"Analytical Modeling and Design Optimization of Dual Gated n-channel Graphene MOSFET","authors":"Md. Selim Reza, Md. Tawfiq Amin","doi":"10.1109/icaeee54957.2022.9836369","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836369","url":null,"abstract":"This paper presents a dual gated n-channel graphene metal-oxide-semiconductor field-effect transistor (MOSFET) with a gapless large-area graphene channel. The semiclassical ballistic model is used in Comsol V5.6 software to calculate the DC characteristics, quantum capacitance, and cut-off frequency for this proposed design. For dual gate formation, SiO2 is used as back gate oxide and HfO2 layer is used as top gate oxide. This proposed Graphene MOSFET is easy to realize and can be easily fabricated by using the recent fabrication technique. The analytical approach shows, Graphene offers less threshold voltage, larger current capability, very little gate capacitance and is having a better cut-off frequency. The excellent characteristics will make the proposed Graphene MOSFET an excellent candidate in future high-speed analog electronic circuits applications.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123683340","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836433
Faisal Bin Ashraf, Tanvinur Rahman Siam, Zulker Nayen, Farhan Uz Zaman
Early detection of myocardial infarction is crucial for necessary medical support and reducing its mortality rate. Every year a huge amount of people are suffering and dying of different heart diseases. The advent of Machine Learning techniques to learn and predict future events based on the data has brought about revolutionary changes in the field of healthcare. These techniques can be used to predict heart disease, and also to identify the type of disease that the patient is suffering from. In this work, we have used a dataset that contains the clinical records of patients who have been admitted into a hospital with a heart problem and experimented with different classification algorithms to predict the type of heart problem that the patient got. We have experimented with the dataset from a different perspectives and a thorough discussion reveals that XGB ensemble classification performs best for this multi-class classification problem. This algorithm gives the best evaluation metric of 99% balanced accuracy, 0.99 ROC AUC, and a perfect F1 score.
{"title":"Identification of Cardiovascular Disorders Using Machine Learning Classification Algorithms","authors":"Faisal Bin Ashraf, Tanvinur Rahman Siam, Zulker Nayen, Farhan Uz Zaman","doi":"10.1109/icaeee54957.2022.9836433","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836433","url":null,"abstract":"Early detection of myocardial infarction is crucial for necessary medical support and reducing its mortality rate. Every year a huge amount of people are suffering and dying of different heart diseases. The advent of Machine Learning techniques to learn and predict future events based on the data has brought about revolutionary changes in the field of healthcare. These techniques can be used to predict heart disease, and also to identify the type of disease that the patient is suffering from. In this work, we have used a dataset that contains the clinical records of patients who have been admitted into a hospital with a heart problem and experimented with different classification algorithms to predict the type of heart problem that the patient got. We have experimented with the dataset from a different perspectives and a thorough discussion reveals that XGB ensemble classification performs best for this multi-class classification problem. This algorithm gives the best evaluation metric of 99% balanced accuracy, 0.99 ROC AUC, and a perfect F1 score.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127976540","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836378
A. Shufian, R. Chowdhury, N. Mohammad, M. Matin
At the beginning of the 21st-century global warming is one of the alarming issues that causes the imbalance of living beings' relations on Earth due to the increase of CO2 and greenhouse gas on burning fossil fuels for electricity generation. With the effect of modernization and industrialization, Bangladesh and many countries worldwide generate power very rapidly from fossil fuels. Due to overuse, the world's fossil reserves will soon be depleted. Considering the above problems, Bangladesh needs to depend entirely on renewable energy (RE) to meet the growing electricity demand. The proposed C2ET strategy will pave the way for a bright future of green energy in Bangladesh, taking into account the various sources of recent power generation and the immense potential of RE. The model will make the entire country's energy system affordable and user-friendly by controlling it through an intelligent energy management system (EMS). The suggested strategy will formulate the future RE mix by thoroughly analyzing Bangladesh's ecological-environmental-economic systems. Following the outline, Bangladesh will meet its electricity demand from about 85% RE and 15% nuclear power by 2050. The power generated from RE will be used in any emergency condition as it will be stored on a short, medium, and long-time basis. There will be no need to generate electricity from fossils. Old and running fossil power plants will be gradually shut down. So, being a developed country, the carbon emissions tax on Bangladesh will no longer be effective. The suggested C2ET would be a ground-breaking and timely solution to preserve the world ecologically pleasant while also keeping up with the rising globalization system without jeopardizing the Earth's equilibrium.
{"title":"Renewable Energy of Bangladesh for Carbon-free Clean Energy Transition (C2ET)","authors":"A. Shufian, R. Chowdhury, N. Mohammad, M. Matin","doi":"10.1109/icaeee54957.2022.9836378","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836378","url":null,"abstract":"At the beginning of the 21st-century global warming is one of the alarming issues that causes the imbalance of living beings' relations on Earth due to the increase of CO2 and greenhouse gas on burning fossil fuels for electricity generation. With the effect of modernization and industrialization, Bangladesh and many countries worldwide generate power very rapidly from fossil fuels. Due to overuse, the world's fossil reserves will soon be depleted. Considering the above problems, Bangladesh needs to depend entirely on renewable energy (RE) to meet the growing electricity demand. The proposed C2ET strategy will pave the way for a bright future of green energy in Bangladesh, taking into account the various sources of recent power generation and the immense potential of RE. The model will make the entire country's energy system affordable and user-friendly by controlling it through an intelligent energy management system (EMS). The suggested strategy will formulate the future RE mix by thoroughly analyzing Bangladesh's ecological-environmental-economic systems. Following the outline, Bangladesh will meet its electricity demand from about 85% RE and 15% nuclear power by 2050. The power generated from RE will be used in any emergency condition as it will be stored on a short, medium, and long-time basis. There will be no need to generate electricity from fossils. Old and running fossil power plants will be gradually shut down. So, being a developed country, the carbon emissions tax on Bangladesh will no longer be effective. The suggested C2ET would be a ground-breaking and timely solution to preserve the world ecologically pleasant while also keeping up with the rising globalization system without jeopardizing the Earth's equilibrium.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130064444","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836380
Md. Mizanur Rahman, Romana Aktar, Samrat Kumar Dey
This paper presents an automatic medicine dispenser prototype. It is a low-cost IoT-based prototype and it can be used by every type of patient especially for the paralyzed, deaf and blind patients. Often people forget to take medicine at right time due to illiteracy, poor-eyesight, or busyness. As a result, getting well is far away, new disease attacks. The main aim of this study is to enable patients to take their medicine on time. To avoid these circumstances an automated medicine dispenser is proposed. Previous works were not very user-friendly and cost a lot some researchers proposed a system that does not work without the internet and none of them focused on the physically disabled patient. In this proposed work all limitations have been fulfilled. Our proposed device gives many facilities to the patient to take medicine at right time. This system provides a voice alarm. Three different colors LEDs, which mention three times period and notified by E-mail in every 15 minutes until patient take medication. The Patient can also check pulse rate and oxygen level using this device. Biometric security is installed so that only authorized persons can access it. It will store medication information on the server that the patient can see at any time. After using this device patient medication forgotten rate is reduced and the habit of the patient is significantly improved.
{"title":"Design and Implementation of a Low-Cost Automated Medicine Dispenser","authors":"Md. Mizanur Rahman, Romana Aktar, Samrat Kumar Dey","doi":"10.1109/icaeee54957.2022.9836380","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836380","url":null,"abstract":"This paper presents an automatic medicine dispenser prototype. It is a low-cost IoT-based prototype and it can be used by every type of patient especially for the paralyzed, deaf and blind patients. Often people forget to take medicine at right time due to illiteracy, poor-eyesight, or busyness. As a result, getting well is far away, new disease attacks. The main aim of this study is to enable patients to take their medicine on time. To avoid these circumstances an automated medicine dispenser is proposed. Previous works were not very user-friendly and cost a lot some researchers proposed a system that does not work without the internet and none of them focused on the physically disabled patient. In this proposed work all limitations have been fulfilled. Our proposed device gives many facilities to the patient to take medicine at right time. This system provides a voice alarm. Three different colors LEDs, which mention three times period and notified by E-mail in every 15 minutes until patient take medication. The Patient can also check pulse rate and oxygen level using this device. Biometric security is installed so that only authorized persons can access it. It will store medication information on the server that the patient can see at any time. After using this device patient medication forgotten rate is reduced and the habit of the patient is significantly improved.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130290852","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836348
Sakhawat Hossen Rakib, S. Masum, Atika Farhana, Md. Aminul Islam, Md. Fokhrul Islam, Md. Taslim Reza
In this work, a cost-effective disinfection system for Coronavirus Disease of 2019 (COVID-19) is proposed to be used inside public transport. The disinfection system is twofold, firstly containing a tower unit where UV-C (Ultraviolet type-C) lamps are positioned in parallel, in such a way that, 360-degree space is covered, and secondly a power unit that incorporates robotics and electrical parts. The $boldsymbol{UVC}$ unit is a separate and movable tower that can be placed anywhere inside a vehicle horizontally or vertically.$boldsymbol{UV}$ lamps in the tower have a $boldsymbol{254 nm}$ wavelength with a total power of 180 Watt. The system can provide a dose of ${it{16.9}mj/cm^{2}}$ within 26.83 seconds if the distance of the targeted surface inside a vehicle from the $boldsymbol{UVC}$ light source is 1.5 meters. Various distances from the $boldsymbol{UV}$ source to the targeted surface inside the vehicle are chosen and calculated the required corresponding times to achieve the required dose to inactivate all viral concentrations. The developed disinfection system not only minimizes the growth of severe acute respiratory syndrome coronavirus 2 $boldsymbol{(SARS-CoV-2}$) by performing robotic features ensuring human detection auto turn off but also utilizes minimum labor work which is vital in the current Covid-19 pandemic.
{"title":"Design of a low cost Ultraviolet Disinfection unit to minimize the cross-contamination of COVID-19 in transport","authors":"Sakhawat Hossen Rakib, S. Masum, Atika Farhana, Md. Aminul Islam, Md. Fokhrul Islam, Md. Taslim Reza","doi":"10.1109/icaeee54957.2022.9836348","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836348","url":null,"abstract":"In this work, a cost-effective disinfection system for Coronavirus Disease of 2019 (COVID-19) is proposed to be used inside public transport. The disinfection system is twofold, firstly containing a tower unit where UV-C (Ultraviolet type-C) lamps are positioned in parallel, in such a way that, 360-degree space is covered, and secondly a power unit that incorporates robotics and electrical parts. The $boldsymbol{UVC}$ unit is a separate and movable tower that can be placed anywhere inside a vehicle horizontally or vertically.$boldsymbol{UV}$ lamps in the tower have a $boldsymbol{254 nm}$ wavelength with a total power of 180 Watt. The system can provide a dose of ${it{16.9}mj/cm^{2}}$ within 26.83 seconds if the distance of the targeted surface inside a vehicle from the $boldsymbol{UVC}$ light source is 1.5 meters. Various distances from the $boldsymbol{UV}$ source to the targeted surface inside the vehicle are chosen and calculated the required corresponding times to achieve the required dose to inactivate all viral concentrations. The developed disinfection system not only minimizes the growth of severe acute respiratory syndrome coronavirus 2 $boldsymbol{(SARS-CoV-2}$) by performing robotic features ensuring human detection auto turn off but also utilizes minimum labor work which is vital in the current Covid-19 pandemic.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132008509","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836333
Shahriar Shanto, Md. Noyan Ali, S. M. M. Ahsan
Iris recognition is a biometrical identifying technique, its intricate patterns are distinctive and durable. It is deemed to be today's most reliable biometric technology. Various characteristics and strategies for iris recognition were proposed over the years. The main vision is to develop a durable and viable system for recognizing the visible spectrum iris images in a low-cost approach, as most available solutions deploy Near Infrared (NIR) cameras for the capture of images of the iris. An erroneous segmentation of the iris may destabilize the whole iris recognition technique. Therefore, a novel technique is presented for segmenting the iris using Circular Hough Transform (CHT) and Canny Edge Detection for the real iris patch. During recognition, a Convolutional Neural Network (CNN) model is introduced to adapt to features through backpropagation with the use of several building blocks such as 2D convolution layers, max-pooling layers, dropout layer and dense layer. This study is mostly on implementing a CNN model to categorize every individual in the whole dataset. In session 1 and session 2, the proposed system obtained promising test accuracy of 95.20% and 99.28%. Several of the leading techniques have been surpassed by this approach. The framework has been primarily tested on the Ubiris v1 and IITD Iris public datasets.
{"title":"An Advanced CNN Based Iris Recognition and Segmentation for Visible Spectrum Images","authors":"Shahriar Shanto, Md. Noyan Ali, S. M. M. Ahsan","doi":"10.1109/icaeee54957.2022.9836333","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836333","url":null,"abstract":"Iris recognition is a biometrical identifying technique, its intricate patterns are distinctive and durable. It is deemed to be today's most reliable biometric technology. Various characteristics and strategies for iris recognition were proposed over the years. The main vision is to develop a durable and viable system for recognizing the visible spectrum iris images in a low-cost approach, as most available solutions deploy Near Infrared (NIR) cameras for the capture of images of the iris. An erroneous segmentation of the iris may destabilize the whole iris recognition technique. Therefore, a novel technique is presented for segmenting the iris using Circular Hough Transform (CHT) and Canny Edge Detection for the real iris patch. During recognition, a Convolutional Neural Network (CNN) model is introduced to adapt to features through backpropagation with the use of several building blocks such as 2D convolution layers, max-pooling layers, dropout layer and dense layer. This study is mostly on implementing a CNN model to categorize every individual in the whole dataset. In session 1 and session 2, the proposed system obtained promising test accuracy of 95.20% and 99.28%. Several of the leading techniques have been surpassed by this approach. The framework has been primarily tested on the Ubiris v1 and IITD Iris public datasets.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123901632","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836387
Sayma Afroza Supti, N. Zaman, Sayemul Islam, A. Podder, A. M. Ibrahim
This paper focuses on selecting the most convenient bioenergy production from four different organic matters: cow dung, food waste, flower waste, and fruit waste. The co-digestion process is used to produce biogas from wastes. Waste decomposes quickly after co-digestion and attains higher methane percentages in a specific time. This paper determines the ability to produce bioenergy considering the attained methane percentage from each waste slurry. A floating drum plant-type portable biogas plant is used in the research work to produce biogas from each waste slurry. A portable biogas analyzer machine is used to measure the percentage of produced methane, carbon dioxide (CO2), oxygen (O2), and hydrogen sulfide (H2S). The result shows that the highest percentage of methane (65.3%) is obtained from food waste slurry within 20 days, whereas cow dung gets the methane percentage as 54%. The calorific value of food waste and cow dung for producing biogas is 333.57 kWh/m3 and 275.4 kWh/m3, respectively that indicates the food waste as the most convenient source of bioenergy generation than others.
{"title":"Selection of Convenient Organic Matters for Bioenergy Generation: A Comparative Approach","authors":"Sayma Afroza Supti, N. Zaman, Sayemul Islam, A. Podder, A. M. Ibrahim","doi":"10.1109/icaeee54957.2022.9836387","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836387","url":null,"abstract":"This paper focuses on selecting the most convenient bioenergy production from four different organic matters: cow dung, food waste, flower waste, and fruit waste. The co-digestion process is used to produce biogas from wastes. Waste decomposes quickly after co-digestion and attains higher methane percentages in a specific time. This paper determines the ability to produce bioenergy considering the attained methane percentage from each waste slurry. A floating drum plant-type portable biogas plant is used in the research work to produce biogas from each waste slurry. A portable biogas analyzer machine is used to measure the percentage of produced methane, carbon dioxide (CO2), oxygen (O2), and hydrogen sulfide (H2S). The result shows that the highest percentage of methane (65.3%) is obtained from food waste slurry within 20 days, whereas cow dung gets the methane percentage as 54%. The calorific value of food waste and cow dung for producing biogas is 333.57 kWh/m3 and 275.4 kWh/m3, respectively that indicates the food waste as the most convenient source of bioenergy generation than others.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125882309","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836346
Sairatun Nesa Soheli, Jahid Hasan
DC-DC buck converters suggested here will be a comprehensive approach for using DC-DC that effectively adapt high voltages to low voltages while ensuring durability and high efficiency. A MOSFET switch, three inductors, a diode, output capacitor, and load resistor are required to construct the suggested converter. The output voltage will be determined by varying the duty cycle, enabling its products to have more battery power, reduce heat, and simulate short devices using more than two inductors. In addition, by using more inductors, higher voltage gain can be achieved, thus achieving higher efficiency. The DC-DC buck converter is constrained by its low duty cycle, which minimizes its application for increased step-down transformations.
{"title":"Investigation of the Suggested DC-DC Buck Converter with Elevated Efficiency","authors":"Sairatun Nesa Soheli, Jahid Hasan","doi":"10.1109/icaeee54957.2022.9836346","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836346","url":null,"abstract":"DC-DC buck converters suggested here will be a comprehensive approach for using DC-DC that effectively adapt high voltages to low voltages while ensuring durability and high efficiency. A MOSFET switch, three inductors, a diode, output capacitor, and load resistor are required to construct the suggested converter. The output voltage will be determined by varying the duty cycle, enabling its products to have more battery power, reduce heat, and simulate short devices using more than two inductors. In addition, by using more inductors, higher voltage gain can be achieved, thus achieving higher efficiency. The DC-DC buck converter is constrained by its low duty cycle, which minimizes its application for increased step-down transformations.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127307850","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 : 2022-02-24DOI: 10.1109/icaeee54957.2022.9836389
Md. Sadman Sakib, M. Islam, S. M. S. H. Tanim, Md. Shafiul Alam, M. Shafiullah, Amjad Ali
Power Quality (PQ) disturbance detection is thought to be a very significant service that many utilities provide for their commercial and industrial customers. PQ disturbances affect the load that is connected to the supply, which is troubling to the consumers. Detection and classification of the electrical problem are very difficult to find out which can cause PQ problems. In this paper, the key PQ issues such as voltage sag, voltage swell, voltage interruption, harmonics, and transient events have been tested. It has been demonstrated that a new approach may be used to identify, localize, and examine the probability of classifying distinct forms of PQ disturbances. The basic idea is to divide a disturbance signal into a transparent and comprehensive representation using DWT and ST. Many mathematical processes are utilized to extract features from these decomposed signals. The signal decomposition technique is integrated with the feed-forward neural network model to develop the power quality problem identifier (detection and classification). The simulation results show that the proposed method is effective. The proposed method is also feasible and promising for real-time applications.
{"title":"Signal Processing-based Artificial Intelligence Approach for Power Quality Disturbance Identification","authors":"Md. Sadman Sakib, M. Islam, S. M. S. H. Tanim, Md. Shafiul Alam, M. Shafiullah, Amjad Ali","doi":"10.1109/icaeee54957.2022.9836389","DOIUrl":"https://doi.org/10.1109/icaeee54957.2022.9836389","url":null,"abstract":"Power Quality (PQ) disturbance detection is thought to be a very significant service that many utilities provide for their commercial and industrial customers. PQ disturbances affect the load that is connected to the supply, which is troubling to the consumers. Detection and classification of the electrical problem are very difficult to find out which can cause PQ problems. In this paper, the key PQ issues such as voltage sag, voltage swell, voltage interruption, harmonics, and transient events have been tested. It has been demonstrated that a new approach may be used to identify, localize, and examine the probability of classifying distinct forms of PQ disturbances. The basic idea is to divide a disturbance signal into a transparent and comprehensive representation using DWT and ST. Many mathematical processes are utilized to extract features from these decomposed signals. The signal decomposition technique is integrated with the feed-forward neural network model to develop the power quality problem identifier (detection and classification). The simulation results show that the proposed method is effective. The proposed method is also feasible and promising for real-time applications.","PeriodicalId":383872,"journal":{"name":"2022 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126840989","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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