Pub Date : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781889
M. Goh, H. T. Yew, Seng Kheau Chung, A. Kiring, Abbas Ibrahim Mbulwa
5G is growing globally, and the handover performance is needed to be updated and improved to adapt to new changes in telecommunication. 5G are considered small cell networks that are anticipated to have a short dwell time for users that move at high speed, like a vehicle traversing the 5G cell at a rate of 40km/h and above. It induces unnecessary handover that causes poor user experience and waste of network resources. This research tackles the problem by proposing a new handover algorithm that integrates a travel distance prediction method with AHP-TOPSIS (Analytic Hierarchy Process - Techniques for Order Preference by Similarity for an Ideal Solution) decision making. The proposed algorithm has successfully reduced the unnecessary handover in 5G networks up to 89.75% compared to the conventional TOPSIS method.
5G在全球发展，需要更新和提高切换性能，以适应电信的新变化。5G被认为是小型蜂窝网络，对于高速移动的用户来说，预计停留时间较短，就像车辆以40公里/小时以上的速度穿越5G蜂窝一样。导致不必要的切换，导致用户体验差，浪费网络资源。本研究提出了一种新的切换算法，该算法将旅行距离预测方法与AHP-TOPSIS (Analytic Hierarchy Process - Techniques for Order Preference by Similarity for an Ideal Solution)决策相结合。与传统的TOPSIS方法相比，该算法成功地将5G网络中不必要的切换减少了89.75%。
{"title":"AHP-TOPSIS Based Handover Algorithm with Distance Prediction for 5G Networks","authors":"M. Goh, H. T. Yew, Seng Kheau Chung, A. Kiring, Abbas Ibrahim Mbulwa","doi":"10.1109/CSPA55076.2022.9781889","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781889","url":null,"abstract":"5G is growing globally, and the handover performance is needed to be updated and improved to adapt to new changes in telecommunication. 5G are considered small cell networks that are anticipated to have a short dwell time for users that move at high speed, like a vehicle traversing the 5G cell at a rate of 40km/h and above. It induces unnecessary handover that causes poor user experience and waste of network resources. This research tackles the problem by proposing a new handover algorithm that integrates a travel distance prediction method with AHP-TOPSIS (Analytic Hierarchy Process - Techniques for Order Preference by Similarity for an Ideal Solution) decision making. The proposed algorithm has successfully reduced the unnecessary handover in 5G networks up to 89.75% compared to the conventional TOPSIS method.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115490447","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781910
Rajeswari Raju, Nur Syahirah Mokhtar, I. Yassin, Sritharan Sangaran, S. N. S. Yasin, Siti Nurul Hayatie Ishak
Heart diseases are leading cause of death for men, and women around the world. Traditionally, to detect heart disease, heart condition checking is a must, but this method is costly, inconvenient, and takes some time. An alternative and a simpler method is the iridology method. Iridology is a study of the human iris to determine any abnormalities that happened in the organ’s functions. This study presents an implementation of computerized iridology in detecting heart disease. The system is designed with several stages such as pre-processing, segmentation region of interest, feature extraction, and classification using an Artificial Neural Network. Gray Level Co-Occurrence Matrix (GLCM) is used in feature extraction to extract the features from the segmented image while the Artificial Neural Network Backpropagation algorithm used as a classifier to create the prediction model for the system. The prediction model was evaluated using the 10-Fold Cross-Validation method. 50 patient data with 27 patients of a normal heart condition and another 23 patients of abnormal heart condition was used and the data been divided into 45 training data (90%) and 5 testing data (10%). The highest classification accuracy obtained is 95.56%.
{"title":"Heart Disease Detection using Iridology with ANN","authors":"Rajeswari Raju, Nur Syahirah Mokhtar, I. Yassin, Sritharan Sangaran, S. N. S. Yasin, Siti Nurul Hayatie Ishak","doi":"10.1109/CSPA55076.2022.9781910","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781910","url":null,"abstract":"Heart diseases are leading cause of death for men, and women around the world. Traditionally, to detect heart disease, heart condition checking is a must, but this method is costly, inconvenient, and takes some time. An alternative and a simpler method is the iridology method. Iridology is a study of the human iris to determine any abnormalities that happened in the organ’s functions. This study presents an implementation of computerized iridology in detecting heart disease. The system is designed with several stages such as pre-processing, segmentation region of interest, feature extraction, and classification using an Artificial Neural Network. Gray Level Co-Occurrence Matrix (GLCM) is used in feature extraction to extract the features from the segmented image while the Artificial Neural Network Backpropagation algorithm used as a classifier to create the prediction model for the system. The prediction model was evaluated using the 10-Fold Cross-Validation method. 50 patient data with 27 patients of a normal heart condition and another 23 patients of abnormal heart condition was used and the data been divided into 45 training data (90%) and 5 testing data (10%). The highest classification accuracy obtained is 95.56%.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115548452","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781898
M. Man, W. A. W. A. Bakar, Mohd. Kamir B. Yusof, Tengku Hanizar Tengku Awang, Terry Yeow
Mobile user is getting increase in number for various reasons. With these increase in trending, there’s a proportionate need to invent a faster and easier mechanism in developing the mobile application (apps). This paper presents the Multiple Dynamic Flip Algorithm (MDFA), a new algorithm in developing mobile-based applications that serves as the mobile apps framework. The algorithm developed allows the data to be stored in the database and the administration of the system can only change the data according to the categories of data that have been systematically arranged in the database. The modified custom data will continue to be updated through the mobile application that has been developed. This method allows changes to information and data to be done automatically without requiring users to run back to mobile- based programming. For information, usually the process of updating information needs to be generated back in mobile- based programming and needs to be uploaded back in the play store or apple store and users must download the application software back. By using this MDFA algorithm, the problem is no longer needed and can be solved more quickly. This MDFA has been tested in the development of two mobile-based applications, namely eMobile Anti-Drug Awareness for Agensi Anti Dadah Kebangsaan (AADK) and Bread on Mobile (BOM).
{"title":"MDFA: A New Multiple Dynamic Flip Algorithm for Mobile-based Apps Development","authors":"M. Man, W. A. W. A. Bakar, Mohd. Kamir B. Yusof, Tengku Hanizar Tengku Awang, Terry Yeow","doi":"10.1109/CSPA55076.2022.9781898","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781898","url":null,"abstract":"Mobile user is getting increase in number for various reasons. With these increase in trending, there’s a proportionate need to invent a faster and easier mechanism in developing the mobile application (apps). This paper presents the Multiple Dynamic Flip Algorithm (MDFA), a new algorithm in developing mobile-based applications that serves as the mobile apps framework. The algorithm developed allows the data to be stored in the database and the administration of the system can only change the data according to the categories of data that have been systematically arranged in the database. The modified custom data will continue to be updated through the mobile application that has been developed. This method allows changes to information and data to be done automatically without requiring users to run back to mobile- based programming. For information, usually the process of updating information needs to be generated back in mobile- based programming and needs to be uploaded back in the play store or apple store and users must download the application software back. By using this MDFA algorithm, the problem is no longer needed and can be solved more quickly. This MDFA has been tested in the development of two mobile-based applications, namely eMobile Anti-Drug Awareness for Agensi Anti Dadah Kebangsaan (AADK) and Bread on Mobile (BOM).","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121635161","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9782018
T. J. Daim, R. A. Lee
Human-computer interaction (HCI) is a term that refers to a set of methods and techniques that enable humans to connect with machines and computers. Based on Hand Gesture Recognition (HGR), HCI enables a naturally occurring contactless interface, bringing humans closer to a more natural way of communication. Numerous studies have identified the potential of Impulse Radio-Ultra Wide Band (IR-UWB) radar sensor-based HGR as a future enabler for a diverse variety of applications. This work presents the development of a method to utilise an IR-UWB radar sensor to recognise and classify hand gesture speeds. The findings of the performance tests reveal a very high degree of confidence and accuracy in recognising and classifying hand gestures speeds.
{"title":"Hand Gesture Speed Recognition and Classification using IR-UWB Radar Sensor","authors":"T. J. Daim, R. A. Lee","doi":"10.1109/CSPA55076.2022.9782018","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9782018","url":null,"abstract":"Human-computer interaction (HCI) is a term that refers to a set of methods and techniques that enable humans to connect with machines and computers. Based on Hand Gesture Recognition (HGR), HCI enables a naturally occurring contactless interface, bringing humans closer to a more natural way of communication. Numerous studies have identified the potential of Impulse Radio-Ultra Wide Band (IR-UWB) radar sensor-based HGR as a future enabler for a diverse variety of applications. This work presents the development of a method to utilise an IR-UWB radar sensor to recognise and classify hand gesture speeds. The findings of the performance tests reveal a very high degree of confidence and accuracy in recognising and classifying hand gestures speeds.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121642570","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781984
A. S. A. Sukor, Mohamad Naim Muhamad, M. N. Ab Wahab
Quality of water applied to the agriculture sector is one of the factors for agriculture farming to be successful. The use of bad quality irrigation water can cause soil problems. In general, determining water quality model is one of the many interests as it can be used to classify the conditions of water. This project focuses on developing the in-situ sensing system of water quality sensors that can detect parameters of water quality such as pH level, electric conductivity, temperature and total dissolved solid. To validate the approach, there are three types of water samples in a dataset that was collected which include water pipes, soap water and drain water. The types of machine learning models used for classification process are Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree. The performance showed that SVM model was the highest, ANN was intermediate, and Decision Tree was the lowest. This shows that the SVM model of machine learning approach is the most suitable to be used as the classification model to classify the status of water quality.
{"title":"Development of In-situ Sensing System and Classification of Water Quality using Machine Learning Approach","authors":"A. S. A. Sukor, Mohamad Naim Muhamad, M. N. Ab Wahab","doi":"10.1109/CSPA55076.2022.9781984","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781984","url":null,"abstract":"Quality of water applied to the agriculture sector is one of the factors for agriculture farming to be successful. The use of bad quality irrigation water can cause soil problems. In general, determining water quality model is one of the many interests as it can be used to classify the conditions of water. This project focuses on developing the in-situ sensing system of water quality sensors that can detect parameters of water quality such as pH level, electric conductivity, temperature and total dissolved solid. To validate the approach, there are three types of water samples in a dataset that was collected which include water pipes, soap water and drain water. The types of machine learning models used for classification process are Artificial Neural Network (ANN), Support Vector Machine (SVM), and Decision Tree. The performance showed that SVM model was the highest, ANN was intermediate, and Decision Tree was the lowest. This shows that the SVM model of machine learning approach is the most suitable to be used as the classification model to classify the status of water quality.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115940817","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781980
Jude Michael R. Apoloni, Sean Derrick G. Escueta, Julius T. Sese
Image processing is the utilization of a computer to process digital images through an algorithm. This method can also be used in detecting the security features of banknotes to tell if the banknote is authentic or counterfeit. Using algorithms such as Canny Edge Detection, Hough Line Transform, Optical Character Recognition and K-Means Clustering to detect Philippine currency banknote level 1 security features such as watermark, asymmetrical serial number, see-through print, and security thread. Canny Edge Detection would be used to detect edges and curves found on the banknotes. Hough Line Transform would be used to detect straight lines found on the banknotes. Optical Character Recognition (OCR) would be used to distinguish text found on the banknotes. K-means clustering would be used to detect color ranges used by the banknotes by means of vector quantization. The tests yield a result of 100% for 200-peso banknotes, 97.50% for 500-peso and 1000-peso banknotes, 96.67% for 50-peso banknotes 91.82% for 20-peso banknotes, and 91.67% for 100-peso banknotes, which has a mean average of 95.86% which is significantly higher than the average accuracy from previous studies of 86.27%.
{"title":"Philippine Currency Counterfeit Detector using Image Processing","authors":"Jude Michael R. Apoloni, Sean Derrick G. Escueta, Julius T. Sese","doi":"10.1109/CSPA55076.2022.9781980","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781980","url":null,"abstract":"Image processing is the utilization of a computer to process digital images through an algorithm. This method can also be used in detecting the security features of banknotes to tell if the banknote is authentic or counterfeit. Using algorithms such as Canny Edge Detection, Hough Line Transform, Optical Character Recognition and K-Means Clustering to detect Philippine currency banknote level 1 security features such as watermark, asymmetrical serial number, see-through print, and security thread. Canny Edge Detection would be used to detect edges and curves found on the banknotes. Hough Line Transform would be used to detect straight lines found on the banknotes. Optical Character Recognition (OCR) would be used to distinguish text found on the banknotes. K-means clustering would be used to detect color ranges used by the banknotes by means of vector quantization. The tests yield a result of 100% for 200-peso banknotes, 97.50% for 500-peso and 1000-peso banknotes, 96.67% for 50-peso banknotes 91.82% for 20-peso banknotes, and 91.67% for 100-peso banknotes, which has a mean average of 95.86% which is significantly higher than the average accuracy from previous studies of 86.27%.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"216 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132228373","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781999
M. N. Mohammed, M. Alfiras, S. Al-Zubaidi, Omar Ismael Al-Sanjary, E. Yusuf, M. Abdulrazaq
With the rise and spread of 2019 novel coronavirus (2019-nCoV), also called severe acute respiratory syndrome coronavirus 2, there is a global health emergency (SARS-CoV-2). Because of the epidemic of new coronavirus disease-2019, clinics and institutions' isolation facilities have generated a massive amount of clinical waste (COVID-19). The biggest contributors to waste volume are personal protective equipment, test strips, medical facemasks, and hand gloves. As garbage functions as a carrier for SARS-CoV-2, it could result in the exponential spread of this devastating disease. Furthermore, proper COVID-waste disposal is urgently required to reduce the risk of pandemic propagation and to ensure long-term treatment of the disease environmental threats. In order to combat the lack of specialized antiviral therapy, it is critical to create new balance techniques and guarantee that existing ones are effective in the field. The objective of this study is to design and develop an intelligent Robot that can collect medical waste from COVID-19 isolation wards and then dispose it of in an environment friendly manner. Furthermore, the focus of this research is to use IoT-based robot technology to design sprinkling with UV devices for antiseptic-disinfection. This study may be useful to avoid and control the pandemic of compatible episodes in the future.
{"title":"2019 Novel Coronavirus Disease (Covid-19): Toward a Novel Design for Smart Waste Management Robot","authors":"M. N. Mohammed, M. Alfiras, S. Al-Zubaidi, Omar Ismael Al-Sanjary, E. Yusuf, M. Abdulrazaq","doi":"10.1109/CSPA55076.2022.9781999","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781999","url":null,"abstract":"With the rise and spread of 2019 novel coronavirus (2019-nCoV), also called severe acute respiratory syndrome coronavirus 2, there is a global health emergency (SARS-CoV-2). Because of the epidemic of new coronavirus disease-2019, clinics and institutions' isolation facilities have generated a massive amount of clinical waste (COVID-19). The biggest contributors to waste volume are personal protective equipment, test strips, medical facemasks, and hand gloves. As garbage functions as a carrier for SARS-CoV-2, it could result in the exponential spread of this devastating disease. Furthermore, proper COVID-waste disposal is urgently required to reduce the risk of pandemic propagation and to ensure long-term treatment of the disease environmental threats. In order to combat the lack of specialized antiviral therapy, it is critical to create new balance techniques and guarantee that existing ones are effective in the field. The objective of this study is to design and develop an intelligent Robot that can collect medical waste from COVID-19 isolation wards and then dispose it of in an environment friendly manner. Furthermore, the focus of this research is to use IoT-based robot technology to design sprinkling with UV devices for antiseptic-disinfection. This study may be useful to avoid and control the pandemic of compatible episodes in the future.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133766677","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781931
N. Hambali, Muhammad Hafizi Ab Manan, Nurul Nadia Mohammad
Temperature is the most critical characteristic in the steam distillation process since it directly affects the amount of oil produced and its quality. This paper presents the nonlinear modelling and Fuzzy Logic Control (FLC) for steam temperature control of the distillation process. Pseudo Random Binary Sequence (PRBS) and Multi-level Pseudo Random Sequence (MPRS) were used for nonlinear modelling of the steam temperature. The suitable transfer function for Nonlinear AutoRegressive with eXogenous input (NARX) modelling was selected with a high percentage of fitness and low value of mean square error. Proportional Integral Derivative (PID) and FLC control tuning method was design based on the estimated transfer function. Then, triangular and trapezoidal type of Membership Function (MF) is used in an FLC system that consists of 2 inputs and 1 output, which are error, derivative error, and voltage, respectively. 7MF with 49 fuzzy rules was used to perform the FLC. The simulation result reported that FLC with MPRS input signal presented better performance with 2364 s rise time, 2914 s peak time without overshoot and concluded as faster response to control the steam temperature compared to FLC and PID with PRBS input signal.
{"title":"Nonlinear Modelling and Fuzzy Control of Steam Temperature for Distillation Column Pilot Plant","authors":"N. Hambali, Muhammad Hafizi Ab Manan, Nurul Nadia Mohammad","doi":"10.1109/CSPA55076.2022.9781931","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9781931","url":null,"abstract":"Temperature is the most critical characteristic in the steam distillation process since it directly affects the amount of oil produced and its quality. This paper presents the nonlinear modelling and Fuzzy Logic Control (FLC) for steam temperature control of the distillation process. Pseudo Random Binary Sequence (PRBS) and Multi-level Pseudo Random Sequence (MPRS) were used for nonlinear modelling of the steam temperature. The suitable transfer function for Nonlinear AutoRegressive with eXogenous input (NARX) modelling was selected with a high percentage of fitness and low value of mean square error. Proportional Integral Derivative (PID) and FLC control tuning method was design based on the estimated transfer function. Then, triangular and trapezoidal type of Membership Function (MF) is used in an FLC system that consists of 2 inputs and 1 output, which are error, derivative error, and voltage, respectively. 7MF with 49 fuzzy rules was used to perform the FLC. The simulation result reported that FLC with MPRS input signal presented better performance with 2364 s rise time, 2914 s peak time without overshoot and concluded as faster response to control the steam temperature compared to FLC and PID with PRBS input signal.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114837173","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9782029
A. Mohammed, N. Al-Shamaa, Ayad Al-dujaili
Permanent Magnet Direct Current (PMDC) motors have been broadly used in mechanical and electrical fields that integrate several applications. This type of motor is subjected to disturbances or sudden changes in loads, and motor speed control is necessary under these conditions. In this paper, we have implemented traditional controllers’ Proportional Integral Derivative (PID) and advanced controllers Super-Twisting Sliding Mode Control (STSMC) and Sliding Mode Control (SMC) through tuning Particle Swarm Optimization (PSO) that used to control the speed of the PMDC motor. According to the results that appeared in the simulations in the MATLABSimulink software, STSMC has superiority compared to other controllers in improving the performance of the speed control for PMDC motors. An experimental setup for PMDC motor by proposed controllers to validate the simulated results in the real environment based on the Arduino UNO interface device. Experimental results confirmed the advantages of employing the STSMC technique over other controllers in improving the performance of speed control for PMDC motors to attain the required speed in the least amount of time and rapid rejection of disturbances in the load.
{"title":"Super-Twisting Sliding Mode Control of Permanent Magnet DC Motor","authors":"A. Mohammed, N. Al-Shamaa, Ayad Al-dujaili","doi":"10.1109/CSPA55076.2022.9782029","DOIUrl":"https://doi.org/10.1109/CSPA55076.2022.9782029","url":null,"abstract":"Permanent Magnet Direct Current (PMDC) motors have been broadly used in mechanical and electrical fields that integrate several applications. This type of motor is subjected to disturbances or sudden changes in loads, and motor speed control is necessary under these conditions. In this paper, we have implemented traditional controllers’ Proportional Integral Derivative (PID) and advanced controllers Super-Twisting Sliding Mode Control (STSMC) and Sliding Mode Control (SMC) through tuning Particle Swarm Optimization (PSO) that used to control the speed of the PMDC motor. According to the results that appeared in the simulations in the MATLABSimulink software, STSMC has superiority compared to other controllers in improving the performance of the speed control for PMDC motors. An experimental setup for PMDC motor by proposed controllers to validate the simulated results in the real environment based on the Arduino UNO interface device. Experimental results confirmed the advantages of employing the STSMC technique over other controllers in improving the performance of speed control for PMDC motors to attain the required speed in the least amount of time and rapid rejection of disturbances in the load.","PeriodicalId":174315,"journal":{"name":"2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129591161","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 : 2022-05-12DOI: 10.1109/CSPA55076.2022.9781986
Naga Nishkala, A. Chaudhary, Harshit Raj, Gayathri Krithiwas, N. B
In this paper, a semi-autonomous solution has been proposed where bite points or entry and exit points were calculated around a wounded region for the purpose of suturing. These bite points were calculated on either side of the wound at a distance of at least 3 mm from the center of the wound along its length. A user-friendly interface that has been provided can help assist the medical staff to manually perform segmentation of the wound and generate the optimal best-fit curve which are the prerequisites to the calculation of bite points. The final results obtained were validated on a scale of 0 to 10 by doctors who have had an average of 25 years of practice in the medical field. A score of 7.89 was obtained for the above-mentioned algorithm.
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