Pub Date : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350866
Md Mahmud, S. Motakabber, A. Alam, A. Nordin
Currently, brushless direct current (BLDC) motors are becoming popular in electric vehicles, automation systems and industrial applications. Basically, the BLDC motors are a special type of electronically controlled electric motor systems. In fact, the successful advancement of electronic technology has made these motors a reality. Without an electronic controller, it is impracticable to run this motor. Thus, it is easily conceivable that the motor controller plays an important role in the overall performance of BLDC motors. Many types of controllers have already been developed for these motors. However, poor efficiency, complexity, bulky size, slow response time, etc. are still challenging tasks to solve these problems. Various algorithms are proposed for designing the controller. Proportional Integral Derivative (PID) controller is the most common control system for the BLDC motor. If the PID controller is modified with a new algorithm, better results can be obtained from the BLDC motor. In this study, a Flower Pollination Algorithm (FPA) has been proposed for the controller to control the speed of BLDC motor. The best outcome of this research is stable is speed and reduce rising time. This study was done by using MATLAB/ Simulink software. The results show a new direction in the improvement of the controller design.
{"title":"Utilizing of Flower Pollination Algorithm for Brushless DC Motor Speed Controller","authors":"Md Mahmud, S. Motakabber, A. Alam, A. Nordin","doi":"10.1109/ETCCE51779.2020.9350866","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350866","url":null,"abstract":"Currently, brushless direct current (BLDC) motors are becoming popular in electric vehicles, automation systems and industrial applications. Basically, the BLDC motors are a special type of electronically controlled electric motor systems. In fact, the successful advancement of electronic technology has made these motors a reality. Without an electronic controller, it is impracticable to run this motor. Thus, it is easily conceivable that the motor controller plays an important role in the overall performance of BLDC motors. Many types of controllers have already been developed for these motors. However, poor efficiency, complexity, bulky size, slow response time, etc. are still challenging tasks to solve these problems. Various algorithms are proposed for designing the controller. Proportional Integral Derivative (PID) controller is the most common control system for the BLDC motor. If the PID controller is modified with a new algorithm, better results can be obtained from the BLDC motor. In this study, a Flower Pollination Algorithm (FPA) has been proposed for the controller to control the speed of BLDC motor. The best outcome of this research is stable is speed and reduce rising time. This study was done by using MATLAB/ Simulink software. The results show a new direction in the improvement of the controller design.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121366907","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}
Air movement through the respiratory system generates sound commonly known as breath sounds or Lung sounds (LS). Auscultation can detect abnormalities in airflow in the respiratory system, which is caused by lung diseases. Change in airflow patterns can also change the sounds generated in the respiratory process, causing abnormal or adventitious Lung sounds. Traditional analog auditory stethoscopes require profound concentration by expert physicians and acquired data can't be stored. In this paper, a non-invasive, non-hazardous way of collecting and analyzing lung sounds by the Digital signal processing (DSP) method is proposed. Lung sounds collected by the auscultation process were then digitized. Various features (Rms, Zero Crossings, Turn Count, Mean, Variance, Form Factor) were extracted from the digitized data stream using DSP methods. The developed system uses significant components like-(1) traditional listening, (2) visual presentation of raw data, and (3) extracted features using DSP methods, which then can be used for assessment of lung diseases.
{"title":"Assessment of Lung Diseases from Features Extraction of Breath Sounds Using Digital Signal Processing Methods","authors":"Shamiha Binta Manir, Mahima Karim, Md. Adnan Kiber","doi":"10.1109/ETCCE51779.2020.9350861","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350861","url":null,"abstract":"Air movement through the respiratory system generates sound commonly known as breath sounds or Lung sounds (LS). Auscultation can detect abnormalities in airflow in the respiratory system, which is caused by lung diseases. Change in airflow patterns can also change the sounds generated in the respiratory process, causing abnormal or adventitious Lung sounds. Traditional analog auditory stethoscopes require profound concentration by expert physicians and acquired data can't be stored. In this paper, a non-invasive, non-hazardous way of collecting and analyzing lung sounds by the Digital signal processing (DSP) method is proposed. Lung sounds collected by the auscultation process were then digitized. Various features (Rms, Zero Crossings, Turn Count, Mean, Variance, Form Factor) were extracted from the digitized data stream using DSP methods. The developed system uses significant components like-(1) traditional listening, (2) visual presentation of raw data, and (3) extracted features using DSP methods, which then can be used for assessment of lung diseases.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114935898","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}
The use of wireless sensors is increasing day by day. Different types of wireless sensors are being used in fisheries sectors to monitor the water quality, growth of the fish, and health of the fish. Due to a brupt changes in water quality parameters, the rapid outbreak of fish disease has become a significant constraint for this sector's sustainability. Development of an early monitoring system of fish culture parameters through high resilience and efficiency wireless sensor networks (WSN) effectively assess water quality regulators instantly and thus take proper actions for sustainable management of freshwater resources. However, current observation systems only consider the data from a single sensor. We designed a data fusion model using Dempster-Shafer theory (DST) to fuse the monitoring sensor data from different sensors to calculate the fish's sustainable environment. Moreover, we evaluated our monitoring system results for different scenarios using the standard performance metrics, i.e., specificity, sensitivity, a ccuracy, and F-Score were calculated using the True Positives (TP), False Positive (LIP), True Negative (TN), and False Negative (LIN) values. Our model's finding shows that fusing data from different sensors provide a more accurate result for monitoring the water's sustainability.
{"title":"Sensor Data Fusion for Monitoring Water Quality Toward Sustainable Freshwater Fisheries","authors":"Quazi Sunjida Shawket Rupok, Kamrul Hassan Suman, Md. Nazmus Sakib, Juhi Agarwal","doi":"10.1109/ETCCE51779.2020.9350876","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350876","url":null,"abstract":"The use of wireless sensors is increasing day by day. Different types of wireless sensors are being used in fisheries sectors to monitor the water quality, growth of the fish, and health of the fish. Due to a brupt changes in water quality parameters, the rapid outbreak of fish disease has become a significant constraint for this sector's sustainability. Development of an early monitoring system of fish culture parameters through high resilience and efficiency wireless sensor networks (WSN) effectively assess water quality regulators instantly and thus take proper actions for sustainable management of freshwater resources. However, current observation systems only consider the data from a single sensor. We designed a data fusion model using Dempster-Shafer theory (DST) to fuse the monitoring sensor data from different sensors to calculate the fish's sustainable environment. Moreover, we evaluated our monitoring system results for different scenarios using the standard performance metrics, i.e., specificity, sensitivity, a ccuracy, and F-Score were calculated using the True Positives (TP), False Positive (LIP), True Negative (TN), and False Negative (LIN) values. Our model's finding shows that fusing data from different sensors provide a more accurate result for monitoring the water's sustainability.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122997075","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 : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350894
S. A. Bakar, M. S. Hitam, W. Yussof, M. Y. Mukta
Image corner detection is a principal task for successful pattern recognition and identification. Finding corners of a shape usually involve two steps, firstly, shape segmentation and, secondly, locating corners in its boundary. This paper presents a robust method for detecting shape corner points using enhanced curvature properties. Numerous applications like image retrieval, object recognition, and motion tracking uses these corner points, which contain essential information about their location or position in a particular shape. Six existing shape detectors and descriptors, i.e., the Harris, SUSAN, Harris-Laplace, CSS, SIFT, and global and local curvature properties (GLCP), have been compared with the proposed shape detection method yielding its performance. The binary image dataset has been utilised as a benchmark to test the experiment. The experiment exhibits a significant number of true corners of the shape and outperforms the existing methods in terms of accuracy and reliability.
{"title":"Shape Corner Detection through Enhanced Curvature Properties","authors":"S. A. Bakar, M. S. Hitam, W. Yussof, M. Y. Mukta","doi":"10.1109/ETCCE51779.2020.9350894","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350894","url":null,"abstract":"Image corner detection is a principal task for successful pattern recognition and identification. Finding corners of a shape usually involve two steps, firstly, shape segmentation and, secondly, locating corners in its boundary. This paper presents a robust method for detecting shape corner points using enhanced curvature properties. Numerous applications like image retrieval, object recognition, and motion tracking uses these corner points, which contain essential information about their location or position in a particular shape. Six existing shape detectors and descriptors, i.e., the Harris, SUSAN, Harris-Laplace, CSS, SIFT, and global and local curvature properties (GLCP), have been compared with the proposed shape detection method yielding its performance. The binary image dataset has been utilised as a benchmark to test the experiment. The experiment exhibits a significant number of true corners of the shape and outperforms the existing methods in terms of accuracy and reliability.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126217112","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 : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350906
N. Roslan, N. F. M. Fauzi, M. Ridzuan
Reliability evaluation is one of the fundamental methods in determining the stability of the distribution network. The variety of techniques in evaluating the reliability has increased as time passes, and the development of the distribution system also becomes more complex. Any network once it is starting to operate, the time for the network to fail, increases as the time passes, mostly when operated for a long time. Hence, it becomes a questionable situation whether the network will keep functioning without any fault or else there will be faults that occur between the operation times. Thus, due to that, the reliability evaluation was used to estimate the reliability of the network. Hence, based on the current evaluation methods, which methods suitable to evaluate the distribution networks without neglecting the distribution network's complexity. Two methods were used: Sequential Monte Carlo (SMC) and Nonsequential Monte Carlo (NSMC). These two methods are used to determine the efficiency of output and to check whether both methods suitable to apply for the current distribution system. IEEE-14 buses are used to simulate the reliability of the network and the efficiency of reliability output. It is expected both methods produce almost the same result. Based on the output, the values for the reliability indices (SAIFI, SAIDI, CAIDI) for this simulation are different due to the simulation process. Practically based on the output, it shows that the SMC method is more suitable to evaluate the distribution system since it pictures the real situation because of the time-based simulation.
{"title":"Sequential and Nonsequential Monte Carlo in Assessing Reliability Performance of Distribution Network","authors":"N. Roslan, N. F. M. Fauzi, M. Ridzuan","doi":"10.1109/ETCCE51779.2020.9350906","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350906","url":null,"abstract":"Reliability evaluation is one of the fundamental methods in determining the stability of the distribution network. The variety of techniques in evaluating the reliability has increased as time passes, and the development of the distribution system also becomes more complex. Any network once it is starting to operate, the time for the network to fail, increases as the time passes, mostly when operated for a long time. Hence, it becomes a questionable situation whether the network will keep functioning without any fault or else there will be faults that occur between the operation times. Thus, due to that, the reliability evaluation was used to estimate the reliability of the network. Hence, based on the current evaluation methods, which methods suitable to evaluate the distribution networks without neglecting the distribution network's complexity. Two methods were used: Sequential Monte Carlo (SMC) and Nonsequential Monte Carlo (NSMC). These two methods are used to determine the efficiency of output and to check whether both methods suitable to apply for the current distribution system. IEEE-14 buses are used to simulate the reliability of the network and the efficiency of reliability output. It is expected both methods produce almost the same result. Based on the output, the values for the reliability indices (SAIFI, SAIDI, CAIDI) for this simulation are different due to the simulation process. Practically based on the output, it shows that the SMC method is more suitable to evaluate the distribution system since it pictures the real situation because of the time-based simulation.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115903261","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}
Energy efficiency in cloud data-centers is an incredibly significant issue in recent cloud computing research. High consumption of power and improper utilization of physical resources are the main drawbacks in cloud architecture. The idle virtual machines tend to consume 50%-70% of the total server energy which ultimately leads to an imbalance and lack of enough power for the actively working machines. In this paper, a new evolutionary computational approach of the Ant Colony System (ACS) algorithm has been applied to address such problem. Inspired by the promising performance of Ant Colony Optimization (ACO) algorithm, one similar but more efficient algorithm has been developed that not only deals with the problem of high consumption of energy but also addresses the Virtual Machine Placement (VMP) problem. This new concept has been named the Active & Idle Virtual Machine Migration (AIVMM) algorithm. It effectively migrates the idle virtual machines from an actively working server and places them in an inactive server with the objective of reducing power interruption for the active machines. The results depict that the AIVMM when implemented with OEMACS results in a hybrid algorithm which outperforms the conventional methods and offers more significant savings of data center energy and resources.
{"title":"Active & Idle Virtual Machine Migration Algorithm- a new Ant Colony Optimization approach to consolidate Virtual Machines and ensure Green Cloud Computing","authors":"Md. Kaviul Hossain, Mutasimur Rahman, Azrin Hossain, Samin Yeaser Rahman, Md. Motaharul Islam","doi":"10.1109/ETCCE51779.2020.9350915","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350915","url":null,"abstract":"Energy efficiency in cloud data-centers is an incredibly significant issue in recent cloud computing research. High consumption of power and improper utilization of physical resources are the main drawbacks in cloud architecture. The idle virtual machines tend to consume 50%-70% of the total server energy which ultimately leads to an imbalance and lack of enough power for the actively working machines. In this paper, a new evolutionary computational approach of the Ant Colony System (ACS) algorithm has been applied to address such problem. Inspired by the promising performance of Ant Colony Optimization (ACO) algorithm, one similar but more efficient algorithm has been developed that not only deals with the problem of high consumption of energy but also addresses the Virtual Machine Placement (VMP) problem. This new concept has been named the Active & Idle Virtual Machine Migration (AIVMM) algorithm. It effectively migrates the idle virtual machines from an actively working server and places them in an inactive server with the objective of reducing power interruption for the active machines. The results depict that the AIVMM when implemented with OEMACS results in a hybrid algorithm which outperforms the conventional methods and offers more significant savings of data center energy and resources.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132226114","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 : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350911
Abu Hasnat Md Rhydwan, Md Mashrur Sakib Choyon, Md. Nashif Iftekhar, Asm Mehedi Hasan Sad, Dip Nandi
The 21st century has seen a significant increase in worldwide electricity consumption with the invention of new technologies. Meeting the increasing power demand efficiently with the classic grid arrangement has become more challenging. To meet this energy demand, following the worldwide trend of grid modernization, Bangladesh is also looking forward to upgrading their existing grid infrastructure into the smart grid. To ameliorate that process, this paper proposes a model of a consortium blockchain from the perspective of Bangladesh. Unlike the existing grids, the proposed smart grid will be able to ensure user security with the help of state-of-the-art technologies. The proposed system will provide features like easier grid integration of different renewable sources, bidirectional power flow to the grid, and smart energy monitoring. To solve the data vulnerability issues and to defend against denial of services and malware attacks on the smart grid, the proposed grid will store its data in a consortium blockchain, which is one of the most secure technologies and only the grid authority will have full access over their user's data. Furthermore, a secure transaction method has been proposed in this paper, that will ensure the integrity of the transaction between the grid authority and the consumers.
{"title":"Smart Grid Implementation with Consortium Blockchain: A Proposed Model for Bangladesh","authors":"Abu Hasnat Md Rhydwan, Md Mashrur Sakib Choyon, Md. Nashif Iftekhar, Asm Mehedi Hasan Sad, Dip Nandi","doi":"10.1109/ETCCE51779.2020.9350911","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350911","url":null,"abstract":"The 21st century has seen a significant increase in worldwide electricity consumption with the invention of new technologies. Meeting the increasing power demand efficiently with the classic grid arrangement has become more challenging. To meet this energy demand, following the worldwide trend of grid modernization, Bangladesh is also looking forward to upgrading their existing grid infrastructure into the smart grid. To ameliorate that process, this paper proposes a model of a consortium blockchain from the perspective of Bangladesh. Unlike the existing grids, the proposed smart grid will be able to ensure user security with the help of state-of-the-art technologies. The proposed system will provide features like easier grid integration of different renewable sources, bidirectional power flow to the grid, and smart energy monitoring. To solve the data vulnerability issues and to defend against denial of services and malware attacks on the smart grid, the proposed grid will store its data in a consortium blockchain, which is one of the most secure technologies and only the grid authority will have full access over their user's data. Furthermore, a secure transaction method has been proposed in this paper, that will ensure the integrity of the transaction between the grid authority and the consumers.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127528224","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 : 2020-12-21DOI: 10.1109/etcce51779.2020.9350902
{"title":"International Conference on Emerging Technology in Computing, Communication and Electronics","authors":"","doi":"10.1109/etcce51779.2020.9350902","DOIUrl":"https://doi.org/10.1109/etcce51779.2020.9350902","url":null,"abstract":"","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050864","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 : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350884
Md. Kafiul Islam, A. Rastegarnia
EEG recordings are usually affected by various artifact types come from non-neural sources and make it difficult for accurate signal classification in the later stage. Thus reliably detecting and removing artifacts from EEG by an automated signal processing algorithm is an active research area. In this paper we have developed a wavelet based artifact removal algorithm from EEG data that selects the best (optimal) threshold parameters, and hence consequently provides the best performance of artifact removal. In the proposed algorithm we choose to sweep both the wavelet filter parameter and threshold parameters until the best accuracy and/or least distortion is achieved by making a decision based on a reference dataset. The criteria for optimized selection are based on the metrics that quantify both amount of artifact removal and amount of distortion in the signal in both time and frequency domain. The algorithm is tested on synthesized EEG data that include different artifact templates and thus quantifies the performance based on several time and frequency domain measures. The achieved results prove that by selecting the optimum mother wavelet and parameter values adaptively would give the best performance both with regard to amount of artifact removal and least signal distortion compared with selecting any predefined mother wavelet and/or constant threshold parameter. This research would help the EEG signal analysis community a platform to work further in future on such problem to be able to properly select the wavelet parameters.
{"title":"Wavelet-based Artifact Removal Algorithm for EEG Data by Optimizing Mother Wavelet and Threshold Parameters","authors":"Md. Kafiul Islam, A. Rastegarnia","doi":"10.1109/ETCCE51779.2020.9350884","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350884","url":null,"abstract":"EEG recordings are usually affected by various artifact types come from non-neural sources and make it difficult for accurate signal classification in the later stage. Thus reliably detecting and removing artifacts from EEG by an automated signal processing algorithm is an active research area. In this paper we have developed a wavelet based artifact removal algorithm from EEG data that selects the best (optimal) threshold parameters, and hence consequently provides the best performance of artifact removal. In the proposed algorithm we choose to sweep both the wavelet filter parameter and threshold parameters until the best accuracy and/or least distortion is achieved by making a decision based on a reference dataset. The criteria for optimized selection are based on the metrics that quantify both amount of artifact removal and amount of distortion in the signal in both time and frequency domain. The algorithm is tested on synthesized EEG data that include different artifact templates and thus quantifies the performance based on several time and frequency domain measures. The achieved results prove that by selecting the optimum mother wavelet and parameter values adaptively would give the best performance both with regard to amount of artifact removal and least signal distortion compared with selecting any predefined mother wavelet and/or constant threshold parameter. This research would help the EEG signal analysis community a platform to work further in future on such problem to be able to properly select the wavelet parameters.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115830177","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 : 2020-12-21DOI: 10.1109/ETCCE51779.2020.9350887
N. A. Nadzri, M. M. Saari, Mohd Aufa Hadi Putera Zaini, N. H. Ramlan, Zulkifly Aziz
Eddy current testing (ECT) is a technique that is used to identify deficiencies and faulty in metallic components including aircraft, piping, bridges, and other civil engineering structures. Early detection of cracks is essential for ensuring structural integrity, safety, and reliability before it reaches the point of fracture. ECT method becomes common in NDT because it can detect a defect in conductive materials. Crack can exist in any form of size and shape either on surface or subsurface components where it can contribute to the complete fracture. The development of an ECT probe for the evaluation of backside defects in the galvanized steel plate is discussed in this paper. The ECT probe is developed based on fluxgate sensors for identifications of defects. The ECT probe that was created is assessed by executing a phase-sensitive detection technique at the excitation field of 70 Hz to 310 Hz. The efficiency of the magnetic probe is estimated by identifying the existence of slits based on the changes of the magnetic response where the induced eddy current is caused. Using the developed magnetic probe, the signal intensity is evaluated on the backside of the sample plate. The results show a signal change in the crack area. The integrated ECT probe is expected to be applied for the evaluation of backside inaccuracies.
{"title":"Detection of Back-Side Cracks in Steel Structure Using A Differential Eddy Current Testing Probe","authors":"N. A. Nadzri, M. M. Saari, Mohd Aufa Hadi Putera Zaini, N. H. Ramlan, Zulkifly Aziz","doi":"10.1109/ETCCE51779.2020.9350887","DOIUrl":"https://doi.org/10.1109/ETCCE51779.2020.9350887","url":null,"abstract":"Eddy current testing (ECT) is a technique that is used to identify deficiencies and faulty in metallic components including aircraft, piping, bridges, and other civil engineering structures. Early detection of cracks is essential for ensuring structural integrity, safety, and reliability before it reaches the point of fracture. ECT method becomes common in NDT because it can detect a defect in conductive materials. Crack can exist in any form of size and shape either on surface or subsurface components where it can contribute to the complete fracture. The development of an ECT probe for the evaluation of backside defects in the galvanized steel plate is discussed in this paper. The ECT probe is developed based on fluxgate sensors for identifications of defects. The ECT probe that was created is assessed by executing a phase-sensitive detection technique at the excitation field of 70 Hz to 310 Hz. The efficiency of the magnetic probe is estimated by identifying the existence of slits based on the changes of the magnetic response where the induced eddy current is caused. Using the developed magnetic probe, the signal intensity is evaluated on the backside of the sample plate. The results show a signal change in the crack area. The integrated ECT probe is expected to be applied for the evaluation of backside inaccuracies.","PeriodicalId":234459,"journal":{"name":"2020 Emerging Technology in Computing, Communication and Electronics (ETCCE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114253785","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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