Pub Date : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007240
M. S. Arsha, Jawad Arif, Zubair Rehman
Lithium Ion batteries have found their applications in consumer electronics, the defense sector, Photovoltaic (PV) systems, and Electric Vehicles (EV) due to their immense benefits when compared to their counterparts such as high charge density, life cycles, long battery life, and low discharge. Due to the boom in EVs and increasing demand for energy storage options, a lot of research is being carried out to increase the capacity of Li-ion batteries with decreased size and charging rates. For that, electrode material composition, ratios, and electrolytes play a vital role to get the best from the Li-ion battery fabrication in terms of energy density. In this study, the half-cell (Coin) fabrication method is presented for academic researchers and industrial R&D for material selection. The study presents the complete method of fabrication of Li-ion coin cells for the researchers to enable them to fabricate their high-quality half-coin cells with good reproducibility of half cells. The study also presents the chemistry of the electrochemical cells and requirements of the material selection for Anode, cathode, and electrolyte. By following the mentioned method, Half-cell is fabricated. The equivalent model of the Li-ion half-cell is discussed along with Galvanostatic measurements at different C rates. It was verified that the higher the C rates, the lower the capacity of the cell.
{"title":"Robust Method of Lithium Ion Coin Half-Cell Fabrication","authors":"M. S. Arsha, Jawad Arif, Zubair Rehman","doi":"10.1109/ETECTE55893.2022.10007240","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007240","url":null,"abstract":"Lithium Ion batteries have found their applications in consumer electronics, the defense sector, Photovoltaic (PV) systems, and Electric Vehicles (EV) due to their immense benefits when compared to their counterparts such as high charge density, life cycles, long battery life, and low discharge. Due to the boom in EVs and increasing demand for energy storage options, a lot of research is being carried out to increase the capacity of Li-ion batteries with decreased size and charging rates. For that, electrode material composition, ratios, and electrolytes play a vital role to get the best from the Li-ion battery fabrication in terms of energy density. In this study, the half-cell (Coin) fabrication method is presented for academic researchers and industrial R&D for material selection. The study presents the complete method of fabrication of Li-ion coin cells for the researchers to enable them to fabricate their high-quality half-coin cells with good reproducibility of half cells. The study also presents the chemistry of the electrochemical cells and requirements of the material selection for Anode, cathode, and electrolyte. By following the mentioned method, Half-cell is fabricated. The equivalent model of the Li-ion half-cell is discussed along with Galvanostatic measurements at different C rates. It was verified that the higher the C rates, the lower the capacity of the cell.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":" 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132075099","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007285
Ayesha Mariam, Memoona Mushtaq, M. Iqbal
Modern Artificial Intelligence (AI) developments urge that the evolved technology will impact our daily lives. Speculation drawn from AI literature proves that AI is growing rapidly. Due to AI, a lot of attention is derived to security surveillance. Implementation of AI in monitoring terms, is costly as it requires many infrastructures and human resources. Also, monitoring of one or multiple cameras feeds for a single source without missing the important points is nearly impossible. There is a need for real security system that is cheaper yet competent. It should manage a fast and easy way to moderate in an emergency cases like fire or weapon detection. Drones are widely used in security surveillance as they cut the cost of human resources. Also it gives fast and efficient responses in critical situations. Proposed methodology is used to avoid cases like fire breakout or intruder in sensitive areas. It contains Unnamed Arial Vehicle (UAV) for real time detection, recognition and monitoring. The video stream obtained by UAV is processed using proposed technique and results are made for three types of detection. These three detection types are Intruder, Object, and Smoke & fire. The results of them are send to control unit so that it can perform some action according to the situation. The accuracy of the suggested technique is measured both in regular and extreme situations, which is 98.93% in regular and extreme cases, 97.82% for smoke and fire & 91.63% for intruder cases.
{"title":"Real-Time Detection, Recognition, and Surveillance using Drones","authors":"Ayesha Mariam, Memoona Mushtaq, M. Iqbal","doi":"10.1109/ETECTE55893.2022.10007285","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007285","url":null,"abstract":"Modern Artificial Intelligence (AI) developments urge that the evolved technology will impact our daily lives. Speculation drawn from AI literature proves that AI is growing rapidly. Due to AI, a lot of attention is derived to security surveillance. Implementation of AI in monitoring terms, is costly as it requires many infrastructures and human resources. Also, monitoring of one or multiple cameras feeds for a single source without missing the important points is nearly impossible. There is a need for real security system that is cheaper yet competent. It should manage a fast and easy way to moderate in an emergency cases like fire or weapon detection. Drones are widely used in security surveillance as they cut the cost of human resources. Also it gives fast and efficient responses in critical situations. Proposed methodology is used to avoid cases like fire breakout or intruder in sensitive areas. It contains Unnamed Arial Vehicle (UAV) for real time detection, recognition and monitoring. The video stream obtained by UAV is processed using proposed technique and results are made for three types of detection. These three detection types are Intruder, Object, and Smoke & fire. The results of them are send to control unit so that it can perform some action according to the situation. The accuracy of the suggested technique is measured both in regular and extreme situations, which is 98.93% in regular and extreme cases, 97.82% for smoke and fire & 91.63% for intruder cases.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123711110","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007319
Zainab Ali, Noman Naseer, Hammad Nazeer
Heart problems have proven to be lethal all around the world. Cardiovascular diseases like cardiac rhythm disorders, heart failure, congenital heart diseases, etc. are the leading cause of death. In this disease, the heart fails to provide enough blood to other body regions to allow it to perform its regular functions. Cardiovascular disease is detected by traditional invasive procedures such as CT and angiography but they have their limitation to combat such problems and limitations, therefore early and precise diagnosis of this disease is needed for avoiding further damage to patients and protecting their lives in advance. The modern world required intelligent and modern solutions thus in this regard computational strategies built on intelligent machine learning systems have been discovered to be more accurate and effective in the identification of heart disease. This study aimed to develop a system that integrates multiple machine learning algorithms, including K-nearest Neighbor, Naïve Byes, Linear Regression, Decision Tree, and Random Forest, which are used to detect cardiovascular disease. Five machine learning algorithm models were developed and their performances were observed based on several other performance indicators like accuracy, Precision, F1-score, Macro Average, and Weighted average among two target classes i.e. Presence and absence of cardiovascular disease. Classification reports generated against each model were utilized to assess the efficacy and strength of the constructed model.
{"title":"Cardiovascular Disease Detection Using Multiple Machine Learning Algorithms and their Performance Analysis","authors":"Zainab Ali, Noman Naseer, Hammad Nazeer","doi":"10.1109/ETECTE55893.2022.10007319","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007319","url":null,"abstract":"Heart problems have proven to be lethal all around the world. Cardiovascular diseases like cardiac rhythm disorders, heart failure, congenital heart diseases, etc. are the leading cause of death. In this disease, the heart fails to provide enough blood to other body regions to allow it to perform its regular functions. Cardiovascular disease is detected by traditional invasive procedures such as CT and angiography but they have their limitation to combat such problems and limitations, therefore early and precise diagnosis of this disease is needed for avoiding further damage to patients and protecting their lives in advance. The modern world required intelligent and modern solutions thus in this regard computational strategies built on intelligent machine learning systems have been discovered to be more accurate and effective in the identification of heart disease. This study aimed to develop a system that integrates multiple machine learning algorithms, including K-nearest Neighbor, Naïve Byes, Linear Regression, Decision Tree, and Random Forest, which are used to detect cardiovascular disease. Five machine learning algorithm models were developed and their performances were observed based on several other performance indicators like accuracy, Precision, F1-score, Macro Average, and Weighted average among two target classes i.e. Presence and absence of cardiovascular disease. Classification reports generated against each model were utilized to assess the efficacy and strength of the constructed model.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127847032","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007334
Muhammad Tahir Abbas, R. Badar
Since their inception, fuzzy logic and its variants involving neural networks have witnessed tremendous applications in the area of identification and control of nonlinear dynamic plants. Fuzzy logic being the universal approximator becomes more powerful when combined with inherent learning capability of Neural Networks (NNs). This research presents a novel adaptive fuzzy control based on Functional Link NNs (FLNNs). The Laguerre orthogonal polynomials have been used for functional expansion of FLNNs. The parameter adaptation and thus the shape of the membership functions and weights of the polynomials of FLNNs are adapted online based on gradient descent optimization technique. Finally, the proposed control scheme has been checked for its performance using comparative evaluation with conventional control schemes applied to different nonlinear plants. The nonlinear time domain simulation results and their quantitative analysis validate the superior performance of the proposed adaptive fuzzy FLNN control.
{"title":"Functional Link NN based Adaptive Fuzzy Control for Nonlinear Dynamic Systems","authors":"Muhammad Tahir Abbas, R. Badar","doi":"10.1109/ETECTE55893.2022.10007334","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007334","url":null,"abstract":"Since their inception, fuzzy logic and its variants involving neural networks have witnessed tremendous applications in the area of identification and control of nonlinear dynamic plants. Fuzzy logic being the universal approximator becomes more powerful when combined with inherent learning capability of Neural Networks (NNs). This research presents a novel adaptive fuzzy control based on Functional Link NNs (FLNNs). The Laguerre orthogonal polynomials have been used for functional expansion of FLNNs. The parameter adaptation and thus the shape of the membership functions and weights of the polynomials of FLNNs are adapted online based on gradient descent optimization technique. Finally, the proposed control scheme has been checked for its performance using comparative evaluation with conventional control schemes applied to different nonlinear plants. The nonlinear time domain simulation results and their quantitative analysis validate the superior performance of the proposed adaptive fuzzy FLNN control.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130375284","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007317
Muhammad Saad Amin, Luca Anselma, A. Mazzei
Information extraction is one of the core fundamentals of natural language processing. Different recurrent neural network-based models have been implemented to perform text classification tasks like named entity recognition (NER). To increase the performance of recurrent networks, different factors play a vital role in which activation functions are one of them. Yet, no studies have perfectly analyzed the effectiveness of the activation function on Named Entity Recognition based classification task of textual data. In this paper, we have implemented a Bi-LSTM-based CRF model for Named Entity Recognition on the semantically annotated corpus i.e., GMB, and analyzed the impact of all non-linear activation functions on the performance of the Neural Network. Our analysis has stated that only Sigmoid, Exponential, SoftPlus, and SoftMax activation functions have performed efficiently in the NER task and achieved an average accuracy of 95.17%, 95.14%, 94.38%, and 94.76% respectively.
{"title":"The Role of Activation Function in Neural NER for a Large Semantically Annotated Corpus","authors":"Muhammad Saad Amin, Luca Anselma, A. Mazzei","doi":"10.1109/ETECTE55893.2022.10007317","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007317","url":null,"abstract":"Information extraction is one of the core fundamentals of natural language processing. Different recurrent neural network-based models have been implemented to perform text classification tasks like named entity recognition (NER). To increase the performance of recurrent networks, different factors play a vital role in which activation functions are one of them. Yet, no studies have perfectly analyzed the effectiveness of the activation function on Named Entity Recognition based classification task of textual data. In this paper, we have implemented a Bi-LSTM-based CRF model for Named Entity Recognition on the semantically annotated corpus i.e., GMB, and analyzed the impact of all non-linear activation functions on the performance of the Neural Network. Our analysis has stated that only Sigmoid, Exponential, SoftPlus, and SoftMax activation functions have performed efficiently in the NER task and achieved an average accuracy of 95.17%, 95.14%, 94.38%, and 94.76% respectively.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131837038","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007386
Ghulam Ruqeyya, Tehmina Hafeez, Sanay Muhammad Umar Saeed, Aleeza Ishwal
Modern era has changed the lifestyle of the people with technological advancement. Video games have become an integral part of daily entertainment for society. This study proposes an engagement index for a video game using electroencephalography (EEG) and compares its result with existing indices available in the literature. This study employs the use of a 14-channel Emotiv EPOC headset for evaluating the engagement of the players in a video game. The study utilizes the dataset of 10 volunteer participants available on Kaggle. Previously available engagement index calculation techniques utilized three or more features while we propose the use of only two features i.e., theta AF3 and alpha P7 for the calculation of the player's engagement index. Results depict that our proposed index is statistically similar to previous indices, while it needs only two electrodes to gauge player engagement. Additionally, these indices can also differentiate between an expert and a novice player. Thus, it is a step towards the improvement of player experience using dynamic difficulty adjustment (DDA).
{"title":"EEG-based Engagement Index for Video Game Players","authors":"Ghulam Ruqeyya, Tehmina Hafeez, Sanay Muhammad Umar Saeed, Aleeza Ishwal","doi":"10.1109/ETECTE55893.2022.10007386","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007386","url":null,"abstract":"Modern era has changed the lifestyle of the people with technological advancement. Video games have become an integral part of daily entertainment for society. This study proposes an engagement index for a video game using electroencephalography (EEG) and compares its result with existing indices available in the literature. This study employs the use of a 14-channel Emotiv EPOC headset for evaluating the engagement of the players in a video game. The study utilizes the dataset of 10 volunteer participants available on Kaggle. Previously available engagement index calculation techniques utilized three or more features while we propose the use of only two features i.e., theta AF3 and alpha P7 for the calculation of the player's engagement index. Results depict that our proposed index is statistically similar to previous indices, while it needs only two electrodes to gauge player engagement. Additionally, these indices can also differentiate between an expert and a novice player. Thus, it is a step towards the improvement of player experience using dynamic difficulty adjustment (DDA).","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"65 Pt 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123799117","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007417
Ehtasham Naseer, Abdul Basit, Muhammad Khurram Bhatti, M. A. Siddique
Nitrogen dioxide (NO2) is one of the six gaseous air pollutants that need regular monitoring in big cities around the world. It contributes to particle pollution and can trigger chemical reactions that lead to increased concentration of ozone in the troposphere. Lahore, a metropolitan city of Pakistan is among the most polluted cities in the world. Area-wide monitoring of NO2 is necessary in this region to devise a long-term emission control policy. However, it lacks a dense network of ground-based air quality monitoring stations (AQMS), which is need of the hour. The installation of AQMS requires huge financial resources. In this paper, we investigate a machine learning-based approach to estimate surface level concentration of NO2 using remote sensing and modeled meteorological data. We use multiple linear regression (M1) and a polynomial fitted regression (M2) techniques to model ambient NO2, using remotely sensed vertical column density (VCD) of NO2, acquired by tropospheric monitoring instrument (TROPOMI), onboard Sentinel 5P satellite, and modeled meteorological parameters such as surface pressure, dew point temperature, and wind speed. Results show that M2 outperformed M1 with an $mathbf{R}^{2}$ value of 0.49 and root mean square error (RMSE) value of $mathbf{19}.mathbf{27} mu mathbf{g}/mathbf{m}^{3}$. There is a moderate positive correlation between in-situ measurements and remotely sensed VCD of NO2, which makes it an interesting problem that needs to be explored further to achieve desirable results.
二氧化氮(NO2)是世界各大城市需要定期监测的六种气态空气污染物之一。它会造成颗粒物污染，并可能引发化学反应，导致对流层臭氧浓度增加。拉合尔是巴基斯坦的一个大都市，是世界上污染最严重的城市之一。为了制定长期的排放控制政策，有必要在该地区进行全区域的二氧化氮监测。然而，它缺乏一个密集的地面空气质量监测站(AQMS)网络，这是当前需要的。AQMS的安装需要巨大的财政资源。在本文中，我们研究了一种基于机器学习的方法，利用遥感和模拟气象数据来估计地表NO2浓度。利用Sentinel 5P卫星对流层监测仪器(TROPOMI)遥感获取的NO2垂直柱密度(VCD)数据，并模拟地表压力、露点温度和风速等气象参数，采用多元线性回归(M1)和多项式拟合回归(M2)技术对环境NO2进行建模。结果表明，M2优于M1，其$mathbf{R}^{2}$值为0.49，均方根误差(RMSE)值为$mathbf{19}。mathbf{27} mu mathbf{g}/mathbf{m}^{3}$。NO2的原位测量值与遥感VCD之间存在适度的正相关关系，这是一个有趣的问题，需要进一步探索才能取得理想的结果。
{"title":"Machine Learning for Area-Wide Monitoring of Surface Level Concentration of NO2 Using Remote Sensing Data","authors":"Ehtasham Naseer, Abdul Basit, Muhammad Khurram Bhatti, M. A. Siddique","doi":"10.1109/ETECTE55893.2022.10007417","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007417","url":null,"abstract":"Nitrogen dioxide (NO2) is one of the six gaseous air pollutants that need regular monitoring in big cities around the world. It contributes to particle pollution and can trigger chemical reactions that lead to increased concentration of ozone in the troposphere. Lahore, a metropolitan city of Pakistan is among the most polluted cities in the world. Area-wide monitoring of NO2 is necessary in this region to devise a long-term emission control policy. However, it lacks a dense network of ground-based air quality monitoring stations (AQMS), which is need of the hour. The installation of AQMS requires huge financial resources. In this paper, we investigate a machine learning-based approach to estimate surface level concentration of NO2 using remote sensing and modeled meteorological data. We use multiple linear regression (M1) and a polynomial fitted regression (M2) techniques to model ambient NO2, using remotely sensed vertical column density (VCD) of NO2, acquired by tropospheric monitoring instrument (TROPOMI), onboard Sentinel 5P satellite, and modeled meteorological parameters such as surface pressure, dew point temperature, and wind speed. Results show that M2 outperformed M1 with an $mathbf{R}^{2}$ value of 0.49 and root mean square error (RMSE) value of $mathbf{19}.mathbf{27} mu mathbf{g}/mathbf{m}^{3}$. There is a moderate positive correlation between in-situ measurements and remotely sensed VCD of NO2, which makes it an interesting problem that needs to be explored further to achieve desirable results.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127480267","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007318
Hichem Boubakar, M. Abri, A. Akram, M. Benaissa, Sarosh Ahmad
In this paper, a new technique for bandpass filter minimization is presented. This technique uses ellipsoidal-shaped complementary split-ring resonators (ECSRR) loaded onto a half-mode substrate-integrated waveguide (HMSIW) structure. One ECSRR is loaded into the upper conductive layer while the other is loaded into the lower one. A comparison is made between the simulation results of a filter with one ECSRR and a filter with the proposed new technique. The efficiency of using the additional ECSRR is shown, and the filter design for both cases performed well. Moreover, the results are validated using two different simulation software. The proposed device has many possible applications in modern communication systems and upcoming communications innovations.
{"title":"HMSIW Miniaturized Bandpass Filter Loaded with Two Elliptic Complementary Split-Ring Resonators for S-Band Applications","authors":"Hichem Boubakar, M. Abri, A. Akram, M. Benaissa, Sarosh Ahmad","doi":"10.1109/ETECTE55893.2022.10007318","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007318","url":null,"abstract":"In this paper, a new technique for bandpass filter minimization is presented. This technique uses ellipsoidal-shaped complementary split-ring resonators (ECSRR) loaded onto a half-mode substrate-integrated waveguide (HMSIW) structure. One ECSRR is loaded into the upper conductive layer while the other is loaded into the lower one. A comparison is made between the simulation results of a filter with one ECSRR and a filter with the proposed new technique. The efficiency of using the additional ECSRR is shown, and the filter design for both cases performed well. Moreover, the results are validated using two different simulation software. The proposed device has many possible applications in modern communication systems and upcoming communications innovations.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131611373","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007364
S. S. Farooq, Junaid Attique, S. A. Ahmad, M. Farooq, Mumtaz A. Qaisrani
Solar power being the most promising form of renewable energy, sun trackers significantly increase the photovoltaic (PV) system's ability to generate power. A dual-axis solar tracker is proposed here in order to demonstrate effective solar power. To maximize power output, the tracker actively monitors the sun and adjusts its location at the desired angle for maximum output. Light dependant resistors and Arduino-operated control circuit drive linear manipulators for the movement of solar panels, a cloud monitoring system is attached here for the power generation and load of varying information. Static and dynamic variations of the panel were done and maximum power and efficiency was recorded and analyzed.
{"title":"Performance Analysis Of Dual Axis Solar Tracking System Actuated Through Serial Manipulators","authors":"S. S. Farooq, Junaid Attique, S. A. Ahmad, M. Farooq, Mumtaz A. Qaisrani","doi":"10.1109/ETECTE55893.2022.10007364","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007364","url":null,"abstract":"Solar power being the most promising form of renewable energy, sun trackers significantly increase the photovoltaic (PV) system's ability to generate power. A dual-axis solar tracker is proposed here in order to demonstrate effective solar power. To maximize power output, the tracker actively monitors the sun and adjusts its location at the desired angle for maximum output. Light dependant resistors and Arduino-operated control circuit drive linear manipulators for the movement of solar panels, a cloud monitoring system is attached here for the power generation and load of varying information. Static and dynamic variations of the panel were done and maximum power and efficiency was recorded and analyzed.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130643361","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 : 2022-12-02DOI: 10.1109/ETECTE55893.2022.10007361
Salman Khan, Muhammad Sohail Anwar Malik, S. Ahmad, Massab Junaid, Sadia Bakhtiar
The development of self, low-power, and wireless electronic devices or systems has led to a strong interest in the field of energy harvesting and the development of mini generators. To power small electronic devices, energy is harvested from ambient energy sources using piezoelectric energy harvesting (PEH) materials. For this purpose, parametric investigation of a bimorph morph beam with a tip mass at the free end was performed using the Simscape model. Due to the excitation of the external sinusoidal force, the beam deforms and becomes polarized. An electric circuit was used to extract the voltage to power small electronic devices (SEDs), or it can also be stored in a battery for later utilization. First, a beam of six different PEMs was studied, and found that PZT-5A has the highest output voltage. Then the PZT-5A was further investigated to see the effect of length, width, thickness of PEM, tip mass, and frequency of excitation force on the output voltage generation. The results show that the length, width, excitation frequency, and amplitude of the excitation force, tip mass, and thinner PEM can increase output voltage generation. Energy harvesting is one of the basic desires for the Internet of Things (IoT) and 5G to power sensors, micro-electro-mechanical systems (MEMS), and other small electronic devices.
{"title":"Modeling and Parametric Investigation of Vibration Energy Harvesting using Bimorph Piezoelectric Beam with a Tip Mass","authors":"Salman Khan, Muhammad Sohail Anwar Malik, S. Ahmad, Massab Junaid, Sadia Bakhtiar","doi":"10.1109/ETECTE55893.2022.10007361","DOIUrl":"https://doi.org/10.1109/ETECTE55893.2022.10007361","url":null,"abstract":"The development of self, low-power, and wireless electronic devices or systems has led to a strong interest in the field of energy harvesting and the development of mini generators. To power small electronic devices, energy is harvested from ambient energy sources using piezoelectric energy harvesting (PEH) materials. For this purpose, parametric investigation of a bimorph morph beam with a tip mass at the free end was performed using the Simscape model. Due to the excitation of the external sinusoidal force, the beam deforms and becomes polarized. An electric circuit was used to extract the voltage to power small electronic devices (SEDs), or it can also be stored in a battery for later utilization. First, a beam of six different PEMs was studied, and found that PZT-5A has the highest output voltage. Then the PZT-5A was further investigated to see the effect of length, width, thickness of PEM, tip mass, and frequency of excitation force on the output voltage generation. The results show that the length, width, excitation frequency, and amplitude of the excitation force, tip mass, and thinner PEM can increase output voltage generation. Energy harvesting is one of the basic desires for the Internet of Things (IoT) and 5G to power sensors, micro-electro-mechanical systems (MEMS), and other small electronic devices.","PeriodicalId":131572,"journal":{"name":"2022 International Conference on Emerging Trends in Electrical, Control, and Telecommunication Engineering (ETECTE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130752776","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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