Pub Date : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209530
Anoosha Tahir, B. Wajid, Faria Anwar, F. G. Awan, Umar Rashid, Fareeha Afzal, Abdul Rauf Anwar, Imran Wajid
Knowledge of survivability is crucial for cancer patients and their families. This paper employs the Surveillance, Epidemiology, and End Results (SEER) database to predict the survivability of colon cancer patients. The research presents four experiments each improving over the previous one, attempting to develop the optimal model. Here (i) experiment 1 conducts regression analyses; (ii) experiment 2 conducts multinomial classification; (iii) experiment 3 emphasizes a multi-tier prediction framework and lastly; (iv) experiment 4 concludes by developing a hybrid model for better prediction of survivability.
{"title":"Survivability Period Prediction in Colon Cancer Patients using Machine Learning","authors":"Anoosha Tahir, B. Wajid, Faria Anwar, F. G. Awan, Umar Rashid, Fareeha Afzal, Abdul Rauf Anwar, Imran Wajid","doi":"10.1109/ICEPECC57281.2023.10209530","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209530","url":null,"abstract":"Knowledge of survivability is crucial for cancer patients and their families. This paper employs the Surveillance, Epidemiology, and End Results (SEER) database to predict the survivability of colon cancer patients. The research presents four experiments each improving over the previous one, attempting to develop the optimal model. Here (i) experiment 1 conducts regression analyses; (ii) experiment 2 conducts multinomial classification; (iii) experiment 3 emphasizes a multi-tier prediction framework and lastly; (iv) experiment 4 concludes by developing a hybrid model for better prediction of survivability.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116503167","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209475
Muhammad Hamza, S. Bazai, Muhammad Imran Ghafoor, Shafi Ullah, Saira Akram, Muhammad Shahzeb Khan
The content creation industry is rapidly growing in various fields such as entertainment, education, and social media platforms. There has been an increasing trend in recent years to generate content using AI algorithms. Generative Adversarial Networks (GANs) are a powerful method for generating realistic samples to meet the increasing demand for data. Many variations of GANs models have been proposed and are covered in multiple review papers. This paper presents a systematic literature review of GANs video generation models. First, the models are categorized into general GANs, image GANs, Video GANs, and Unconditional and Conditional GANs. Next, the paper summarizes the improvements made in GANs related to image synthesis and identifies areas where video synthesis has not yet been fully explored. A comprehensive systematic review of Video GANs is then presented by categorizing them into unconditional and conditional GANs. The datasets used in video generation are also discussed in the paper. The conditional models are further explained in sections that are categorized as images, audio, and videos. Lastly, the paper concludes with a discussion of the limitations of GANs and the future work needed in this area.
{"title":"Generative Adversarial Networks (GANs) Video Framework: A Systematic Literature Review","authors":"Muhammad Hamza, S. Bazai, Muhammad Imran Ghafoor, Shafi Ullah, Saira Akram, Muhammad Shahzeb Khan","doi":"10.1109/ICEPECC57281.2023.10209475","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209475","url":null,"abstract":"The content creation industry is rapidly growing in various fields such as entertainment, education, and social media platforms. There has been an increasing trend in recent years to generate content using AI algorithms. Generative Adversarial Networks (GANs) are a powerful method for generating realistic samples to meet the increasing demand for data. Many variations of GANs models have been proposed and are covered in multiple review papers. This paper presents a systematic literature review of GANs video generation models. First, the models are categorized into general GANs, image GANs, Video GANs, and Unconditional and Conditional GANs. Next, the paper summarizes the improvements made in GANs related to image synthesis and identifies areas where video synthesis has not yet been fully explored. A comprehensive systematic review of Video GANs is then presented by categorizing them into unconditional and conditional GANs. The datasets used in video generation are also discussed in the paper. The conditional models are further explained in sections that are categorized as images, audio, and videos. Lastly, the paper concludes with a discussion of the limitations of GANs and the future work needed in this area.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114637040","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209514
Waseem Abbas, Zubair Mehmood, Jehanzeb Irshad, Muhammad Wasif
5G is the wireless technology in which millimeter waves are used for communication between the devices. Balun is a passive device necessary for efficient power transfer from one building block of the transceiver to the other. In this paper an unbalance to balance power conversion is achieved using balun at 120 GHz. The designed balun has about 1 dB amplitude error for bandwidth from 85 GHz to 150 GHz whereas the phase error is observed +/-5°. The overall form factor of the designed balun is 2.9 nm2 which is the least possible size for balun design at this frequency range.
{"title":"Design of 120 GHz Balun for 5G Transceiver Chips","authors":"Waseem Abbas, Zubair Mehmood, Jehanzeb Irshad, Muhammad Wasif","doi":"10.1109/ICEPECC57281.2023.10209514","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209514","url":null,"abstract":"5G is the wireless technology in which millimeter waves are used for communication between the devices. Balun is a passive device necessary for efficient power transfer from one building block of the transceiver to the other. In this paper an unbalance to balance power conversion is achieved using balun at 120 GHz. The designed balun has about 1 dB amplitude error for bandwidth from 85 GHz to 150 GHz whereas the phase error is observed +/-5°. The overall form factor of the designed balun is 2.9 nm2 which is the least possible size for balun design at this frequency range.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"624 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116874291","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209479
Didik Sudarmadi, I. Garniwa
Hundreds of off-grid small power systems are located in a remote area of Indonesia, supplied by Diesel Generator (DG). The conversion plan of DG to Renewable Energy Sources (RES) generation becomes essential in increasing reliability, economic value, and environmental soundness. An example of the project is discussed through a short study on the pre-feasibility of Hybrid Renewable Energy System (HRES) utilization in Gili Ketapang island. The study considers techno-economic analysis and size optimization by using Homer Pro software. The calculation result is obtained using an assumption of fuel cost at 0.472 ${$}$/L on the studied HRES. The optimized configuration shows a better performance in the following indicators: net present cost (NPC), cost of electricity (COE), return on investment (ROI), renewable fraction (RF), and CO2 emission compared to the existing system. The study also provides the calculation that uses a nonsubsidized fuel cost assumption at 1.1 ${$}$/L. The latter result has a different optimized configuration in which ROI and environmental performances are better than the optimized configuration in the previous result.
{"title":"Optimal Sizing and Techno-economic Analysis of Hybrid Renewable Energy System for Off-grid Remote Areas in Indonesia","authors":"Didik Sudarmadi, I. Garniwa","doi":"10.1109/ICEPECC57281.2023.10209479","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209479","url":null,"abstract":"Hundreds of off-grid small power systems are located in a remote area of Indonesia, supplied by Diesel Generator (DG). The conversion plan of DG to Renewable Energy Sources (RES) generation becomes essential in increasing reliability, economic value, and environmental soundness. An example of the project is discussed through a short study on the pre-feasibility of Hybrid Renewable Energy System (HRES) utilization in Gili Ketapang island. The study considers techno-economic analysis and size optimization by using Homer Pro software. The calculation result is obtained using an assumption of fuel cost at 0.472 ${$}$/L on the studied HRES. The optimized configuration shows a better performance in the following indicators: net present cost (NPC), cost of electricity (COE), return on investment (ROI), renewable fraction (RF), and CO2 emission compared to the existing system. The study also provides the calculation that uses a nonsubsidized fuel cost assumption at 1.1 ${$}$/L. The latter result has a different optimized configuration in which ROI and environmental performances are better than the optimized configuration in the previous result.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123057518","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209518
Mishal Waqar, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz
Among Women, Breast cancer is one of the maximum occurring diseases. Many women die every year because of breast cancer globally. Early prediction and diagnosis of this disease can prevent death in the end. The survival rate increases on detecting breast cancer early as better treatment can be provided. Development in prediction and diagnosis is necessary for the life of people. A higher amount of accuracy in the prediction of breast cancer is necessary for the treatment aspects and also for the survivability of patients. It is apparent that there are different techniques available in breast cancer detection but machine learning algorithms can bring a large contribution to the process of prediction and early diagnosis of breast cancer. In this study, we use a Wisconsin dataset which was collected from a scientific dataset of 569 breast cancer. Out of 569 patients, 63% were diagnosed with benign and 37% were diagnosed with malignant cancer. The benign tumor grows slowly and does not spread. We apply five machine learning algorithms to this dataset and train a model for predicting malignant and benign tissues (BCs). Algorithms are K-Nearest neighbor, Support vector machine, Decision tree, Deep learning, and Random-forest respectively. The effectiveness of these algorithms is evaluated in terms of accuracy, F measure, confusion matrix, and specificity. By comparing the results deep learning classifier gives the highest accuracy and outclass all the other classifiers by attaining an accuracy of 9S.l3%. SVM gives an accuracy of 97.66% whereas KNN gives an accuracy of 95.79% etc.
{"title":"An Applied Artificial Intelligence Aided Technique for Effective Classification of Breast Cancer","authors":"Mishal Waqar, A. Rehman, Sabeen Javaid, Tahir Muhammad Ali, Ali Nawaz","doi":"10.1109/ICEPECC57281.2023.10209518","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209518","url":null,"abstract":"Among Women, Breast cancer is one of the maximum occurring diseases. Many women die every year because of breast cancer globally. Early prediction and diagnosis of this disease can prevent death in the end. The survival rate increases on detecting breast cancer early as better treatment can be provided. Development in prediction and diagnosis is necessary for the life of people. A higher amount of accuracy in the prediction of breast cancer is necessary for the treatment aspects and also for the survivability of patients. It is apparent that there are different techniques available in breast cancer detection but machine learning algorithms can bring a large contribution to the process of prediction and early diagnosis of breast cancer. In this study, we use a Wisconsin dataset which was collected from a scientific dataset of 569 breast cancer. Out of 569 patients, 63% were diagnosed with benign and 37% were diagnosed with malignant cancer. The benign tumor grows slowly and does not spread. We apply five machine learning algorithms to this dataset and train a model for predicting malignant and benign tissues (BCs). Algorithms are K-Nearest neighbor, Support vector machine, Decision tree, Deep learning, and Random-forest respectively. The effectiveness of these algorithms is evaluated in terms of accuracy, F measure, confusion matrix, and specificity. By comparing the results deep learning classifier gives the highest accuracy and outclass all the other classifiers by attaining an accuracy of 9S.l3%. SVM gives an accuracy of 97.66% whereas KNN gives an accuracy of 95.79% etc.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131321966","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209527
Hamad Ud Din, Wasif Muhammad, N. Siddique, M. J. Irshad, Ali Asghar, M. W. Jabbar
This Early in the $20^{mathrm{t}mathrm{h}}$ century, research on smooth pursuit began. Nowadays, it may be found in everything from little robots to sophisticated automation projects. There are now many study studies in this area, but they are all reward-based conventionally, which is not biologically feasible. In these techniques, the robot performs an action, and the agent determines the next course of action based on the performance and a certain kind of positive or negative reward. The reward in this thesis is derived from the sensory space rather than the action space, which enables the robot to predict the reward without any prior defined reward. PC/BC-DIM, a new Deep Inverse Reinforcement Learning (DIRL) technique, is presented. Rather than relying on previously specified rewards, PC/BC-DIM assesses the prediction error between certain inputs and determines whether or not to update the weight. It was controlled independently and successfully arrived at the target place, yielding satisfying results. The iCub humanoid robot simulator is used to evaluate the performance of the suggested system.
{"title":"Development of Visual Smooth Pursuit Model Using Inverse Reinforcement Learning For Humanoid Robots","authors":"Hamad Ud Din, Wasif Muhammad, N. Siddique, M. J. Irshad, Ali Asghar, M. W. Jabbar","doi":"10.1109/ICEPECC57281.2023.10209527","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209527","url":null,"abstract":"This Early in the $20^{mathrm{t}mathrm{h}}$ century, research on smooth pursuit began. Nowadays, it may be found in everything from little robots to sophisticated automation projects. There are now many study studies in this area, but they are all reward-based conventionally, which is not biologically feasible. In these techniques, the robot performs an action, and the agent determines the next course of action based on the performance and a certain kind of positive or negative reward. The reward in this thesis is derived from the sensory space rather than the action space, which enables the robot to predict the reward without any prior defined reward. PC/BC-DIM, a new Deep Inverse Reinforcement Learning (DIRL) technique, is presented. Rather than relying on previously specified rewards, PC/BC-DIM assesses the prediction error between certain inputs and determines whether or not to update the weight. It was controlled independently and successfully arrived at the target place, yielding satisfying results. The iCub humanoid robot simulator is used to evaluate the performance of the suggested system.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130153597","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209468
M. N. Mamat, M. N. Abdullah, S. Kaharuddin, D. Ishak
Net Zero emissions are achievable if all stakeholders contribute to achieving the objective. As the energy industry is one of the major contributors to the production of greenhouse gases, moving from conventional fossil fuels to sustainable and clean energy is one of the measures. The ability to generate electricity by harvesting energy from methods including mechanical, vibrational, and solar irradiation has a lot of potential. However, the energy spectrum of the source is extremely unstable, which is a drawback to energy collection. The output voltage of the transducer may be chaotic or steady, and a DC/DC converter is required to filter and regulate it. To accomplish the regulation challenge, a variety of converter topologies and feedback control techniques have been devised. This study examines the stability of SEPIC-Boost converters with open loop and negative feedback built in their design, given constant and chaotic input from energy collecting sources. Given that it is one of the most efficient tuning techniques, PID feedback control based on modified Ziegler-Nichols tuning is chosen. The results showed that the proposed system performed poorly under both chaotic and constant input situations when run without feedback control. Massive overshoot of 19% and undervalue of 8.5% were observed. However, when both input conditions were given to the SEPIC-Boost converter, the system operated flawlessly under PID feedback control. With less than 1% of the ripple, the output reached the desired stability and it did not experienced any overshoots or undervalues when it was in use.
{"title":"Evaluation of SEPIC-Boost Converter’s Stability Under Constant and Chaotic Input Conditions","authors":"M. N. Mamat, M. N. Abdullah, S. Kaharuddin, D. Ishak","doi":"10.1109/ICEPECC57281.2023.10209468","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209468","url":null,"abstract":"Net Zero emissions are achievable if all stakeholders contribute to achieving the objective. As the energy industry is one of the major contributors to the production of greenhouse gases, moving from conventional fossil fuels to sustainable and clean energy is one of the measures. The ability to generate electricity by harvesting energy from methods including mechanical, vibrational, and solar irradiation has a lot of potential. However, the energy spectrum of the source is extremely unstable, which is a drawback to energy collection. The output voltage of the transducer may be chaotic or steady, and a DC/DC converter is required to filter and regulate it. To accomplish the regulation challenge, a variety of converter topologies and feedback control techniques have been devised. This study examines the stability of SEPIC-Boost converters with open loop and negative feedback built in their design, given constant and chaotic input from energy collecting sources. Given that it is one of the most efficient tuning techniques, PID feedback control based on modified Ziegler-Nichols tuning is chosen. The results showed that the proposed system performed poorly under both chaotic and constant input situations when run without feedback control. Massive overshoot of 19% and undervalue of 8.5% were observed. However, when both input conditions were given to the SEPIC-Boost converter, the system operated flawlessly under PID feedback control. With less than 1% of the ripple, the output reached the desired stability and it did not experienced any overshoots or undervalues when it was in use.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":" 46","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120935283","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209482
M. M. Gujja, D. Ishak
PMBLDC motor is vital in this modern industrial age. It has vast applications and most preferable compared to the conventional DC motor for its less noise, electrical commutation, and high speed. Therefore, the need to design a driver circuit with good control capability cannot be over emphasized. This work aims to design both the six-and four-switch driver circuits for effective PMBLDC motor control. An optimization technique was employed to smoothen and enhance the system’s performance. The simulation output of both the driving strategy was analysed and the system settling time, overshoot, undershoot and rise time were matched to choose the most effective driver circuit with the best control approach. The resultant output also shows the Six-Switch Three-Phase Driver Circuit (SSTPDC) is better in terms of speed, stability, rise time and settling time when matched to the Four-Switch Three-Phase Driver Circuit (FSTPDC). However, the FSTPDC is cost-effective and less structure complex. It is worth knowing that both driving strategies have good reference tracking.
{"title":"Comparative Evaluation and Analysis of Six- and Four-Switch Drivers for PMBLDC Motor Control","authors":"M. M. Gujja, D. Ishak","doi":"10.1109/ICEPECC57281.2023.10209482","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209482","url":null,"abstract":"PMBLDC motor is vital in this modern industrial age. It has vast applications and most preferable compared to the conventional DC motor for its less noise, electrical commutation, and high speed. Therefore, the need to design a driver circuit with good control capability cannot be over emphasized. This work aims to design both the six-and four-switch driver circuits for effective PMBLDC motor control. An optimization technique was employed to smoothen and enhance the system’s performance. The simulation output of both the driving strategy was analysed and the system settling time, overshoot, undershoot and rise time were matched to choose the most effective driver circuit with the best control approach. The resultant output also shows the Six-Switch Three-Phase Driver Circuit (SSTPDC) is better in terms of speed, stability, rise time and settling time when matched to the Four-Switch Three-Phase Driver Circuit (FSTPDC). However, the FSTPDC is cost-effective and less structure complex. It is worth knowing that both driving strategies have good reference tracking.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124418691","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209481
T. Hussein, D. Ishak
In this paper, a hybrid pattern consisting of the optimal features of the SMA algorithm, and the GA algorithm are used to calculate the optimal switching angles for a three-phase multi-level inverter (MLI). These angles are used to remove a selected number of unwanted harmonics, thus reducing the total harmonics distortion (THD) to a significant value. The topology for the three-phase MLI is used to operate the least number of switches to increase the efficiency compared to the traditional three-phase inverter. A 23-level three-phase inverter is investigated and simulated in MATLAB Simulink environment using resistive, inductive, and non-linear loads. The results are presented for the voltages and currents of the inverter and the load, as well as the frequency spectrum analysis to compare the THD values for the two algorithms and the hybrid pattern.
{"title":"Three-phase MLI with Reduced Number of Switches and Hybrid Optimized Switching","authors":"T. Hussein, D. Ishak","doi":"10.1109/ICEPECC57281.2023.10209481","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209481","url":null,"abstract":"In this paper, a hybrid pattern consisting of the optimal features of the SMA algorithm, and the GA algorithm are used to calculate the optimal switching angles for a three-phase multi-level inverter (MLI). These angles are used to remove a selected number of unwanted harmonics, thus reducing the total harmonics distortion (THD) to a significant value. The topology for the three-phase MLI is used to operate the least number of switches to increase the efficiency compared to the traditional three-phase inverter. A 23-level three-phase inverter is investigated and simulated in MATLAB Simulink environment using resistive, inductive, and non-linear loads. The results are presented for the voltages and currents of the inverter and the load, as well as the frequency spectrum analysis to compare the THD values for the two algorithms and the hybrid pattern.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130298576","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 : 2023-03-08DOI: 10.1109/ICEPECC57281.2023.10209448
Muhammad Hassan Mursal, Usama Ahmed, Muhammad Ziad Nayyer
Cloud federation has enabled organizations to adopt collaborative services for sharing data and workloads across various platforms. Induction of federation members may require some verifications and predictions related to capacity and capability of these members for compensating such types of workloads. However, the nature of federated services require stringent methods to keep track of dynamically forming resource clusters for forecasting their behavior. Recent literature has mostly focused on the applicability of forecasting algorithms based on static datasets with little or no applicability to real time scenarios. Proposed research has utilized a real world application of Clouds4Coordination (C4C) federation system. A resource forecasting strategy using two well-known algorithms, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) has been proposed for collaborative clouds used in Architecture, Engineering and Construction (AEC) industry. The results have shown that no single algorithm is sufficient enough to deal with dynamic scenarios of cloud federation. Moreover, the selection of algorithm is highly dependent upon the type and duration of prediction required i.e. short term or long term as required by the user.
{"title":"Resource Availability Forecasting for Federated Clouds","authors":"Muhammad Hassan Mursal, Usama Ahmed, Muhammad Ziad Nayyer","doi":"10.1109/ICEPECC57281.2023.10209448","DOIUrl":"https://doi.org/10.1109/ICEPECC57281.2023.10209448","url":null,"abstract":"Cloud federation has enabled organizations to adopt collaborative services for sharing data and workloads across various platforms. Induction of federation members may require some verifications and predictions related to capacity and capability of these members for compensating such types of workloads. However, the nature of federated services require stringent methods to keep track of dynamically forming resource clusters for forecasting their behavior. Recent literature has mostly focused on the applicability of forecasting algorithms based on static datasets with little or no applicability to real time scenarios. Proposed research has utilized a real world application of Clouds4Coordination (C4C) federation system. A resource forecasting strategy using two well-known algorithms, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) has been proposed for collaborative clouds used in Architecture, Engineering and Construction (AEC) industry. The results have shown that no single algorithm is sufficient enough to deal with dynamic scenarios of cloud federation. Moreover, the selection of algorithm is highly dependent upon the type and duration of prediction required i.e. short term or long term as required by the user.","PeriodicalId":102289,"journal":{"name":"2023 International Conference on Energy, Power, Environment, Control, and Computing (ICEPECC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121418513","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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