Pub Date : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257848
Y. L. Chong, R. Chin
Electrical Impedance Tomography (EIT) is an imaging technique which is used in both industrial process and medical imaging, as it is non-invasive and versatile. One of the factors that contribute to image quality is electrode. This work investigates the effect of the different number of electrodes on EIT reconstructed images for various widths of electrodes. Spectral analyses, sensitivity analyses and spatial resolution analyses were used to study the influence of the different numbers of electrodes for different electrode widths. From the results of spectral analysis, the magnitude of singular value is higher as the number of electrodes increases, which indicates higher stability of measurements obtained. On the contrary, the percentage of stable measurements decrease significantly as the number of electrodes increase. In the sensitivity analyses, the results show that there are noticeable differences in sensitivity magnitude for models with the different number of electrodes. However, when comparing models with the same number of electrodes but with different widths, there are negligible differences. From the spatial resolution analyses, the results are inconclusive as the spatial resolution produced is fairly similar for models with the different number of electrodes for fixed electrode widths. This trend is observed when comparing models with the same number of electrodes but with different electrode widths. All these analyses have to be considered when deciding on electrode configuration, taking into account the influences of both the number of electrodes and the dimension of electrodes used.
{"title":"An Investigation of the Effect of Different Number of Electrodes on EIT Reconstructed Images","authors":"Y. L. Chong, R. Chin","doi":"10.1109/IICAIET49801.2020.9257848","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257848","url":null,"abstract":"Electrical Impedance Tomography (EIT) is an imaging technique which is used in both industrial process and medical imaging, as it is non-invasive and versatile. One of the factors that contribute to image quality is electrode. This work investigates the effect of the different number of electrodes on EIT reconstructed images for various widths of electrodes. Spectral analyses, sensitivity analyses and spatial resolution analyses were used to study the influence of the different numbers of electrodes for different electrode widths. From the results of spectral analysis, the magnitude of singular value is higher as the number of electrodes increases, which indicates higher stability of measurements obtained. On the contrary, the percentage of stable measurements decrease significantly as the number of electrodes increase. In the sensitivity analyses, the results show that there are noticeable differences in sensitivity magnitude for models with the different number of electrodes. However, when comparing models with the same number of electrodes but with different widths, there are negligible differences. From the spatial resolution analyses, the results are inconclusive as the spatial resolution produced is fairly similar for models with the different number of electrodes for fixed electrode widths. This trend is observed when comparing models with the same number of electrodes but with different electrode widths. All these analyses have to be considered when deciding on electrode configuration, taking into account the influences of both the number of electrodes and the dimension of electrodes used.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"183 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115025151","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 : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257852
Naoto Kosaka, Yumi Wakita
We develop a conversation support system for the public community. Our concept is that supporting elderly person's active life by assisting human-to-human conversation is more effective than providing a speech dialogue system. To use a conversation support system in an actual restaurant or lounge environment, it is necessary to separate the conversation of the target near the microphone from the ambient noise. We have already proposed the identification method of the utterances spoken between near a microphone and far from it using the standard deviation values of the fundamental frequency (SD-F0) and those of the speech power level (SD-SP) for each utterance. In the paper, we evaluate the effectiveness of our identification method for an actual free conversation using Support Vector Machine(SVM) method. As a result, the precision rate of the utterances near the microphone is 87.8%. This means that the identification method using the standard deviations of the fundamental frequency and speech power would be effective even if they are used in real environments. However, the performance depends on the utterances lengths, the F0 value's stability of the utterance part of over the threshold and the position of the microphones. In future, it evaluation should be done using more number of speakers and variable situations to define a suitable system specification.
{"title":"Evaluating target utterance identification method using practical free conversation","authors":"Naoto Kosaka, Yumi Wakita","doi":"10.1109/IICAIET49801.2020.9257852","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257852","url":null,"abstract":"We develop a conversation support system for the public community. Our concept is that supporting elderly person's active life by assisting human-to-human conversation is more effective than providing a speech dialogue system. To use a conversation support system in an actual restaurant or lounge environment, it is necessary to separate the conversation of the target near the microphone from the ambient noise. We have already proposed the identification method of the utterances spoken between near a microphone and far from it using the standard deviation values of the fundamental frequency (SD-F0) and those of the speech power level (SD-SP) for each utterance. In the paper, we evaluate the effectiveness of our identification method for an actual free conversation using Support Vector Machine(SVM) method. As a result, the precision rate of the utterances near the microphone is 87.8%. This means that the identification method using the standard deviations of the fundamental frequency and speech power would be effective even if they are used in real environments. However, the performance depends on the utterances lengths, the F0 value's stability of the utterance part of over the threshold and the position of the microphones. In future, it evaluation should be done using more number of speakers and variable situations to define a suitable system specification.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127077819","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 : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257811
M. Dabbagh, Mohsen Kakavand, Mohammad Tahir, A. Amphawan
Recent years have witnessed a sizeable growth of Blockchain applications in enterprises. Blockchain is transforming the traditional approach of storing and managing data in a single location into a decentralized ledger. Although many industries are keen on adopting Blockchain technology for enhanced transaction transparency, the performance of the current Blockchain platforms is still perplexing to stakeholders. Therefore, this research aims to conduct an empirical study to evaluate the performance of two prominent Blockchain platforms, Hyperledger Fabric and Ethereum. The performance evaluation is based on measuring four metrics including success rate, average latency, throughput, and resource consumption. The experimental results of executing 100 transactions show that Hyperledger Fabric generally surpasses Ethereum against the four performance metrics. The presented results in this research would assist practitioners in their decision-making process of adopting the ideal Blockchain platform into their IT systems based on application requirements.
{"title":"Performance Analysis of Blockchain Platforms: Empirical Evaluation of Hyperledger Fabric and Ethereum","authors":"M. Dabbagh, Mohsen Kakavand, Mohammad Tahir, A. Amphawan","doi":"10.1109/IICAIET49801.2020.9257811","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257811","url":null,"abstract":"Recent years have witnessed a sizeable growth of Blockchain applications in enterprises. Blockchain is transforming the traditional approach of storing and managing data in a single location into a decentralized ledger. Although many industries are keen on adopting Blockchain technology for enhanced transaction transparency, the performance of the current Blockchain platforms is still perplexing to stakeholders. Therefore, this research aims to conduct an empirical study to evaluate the performance of two prominent Blockchain platforms, Hyperledger Fabric and Ethereum. The performance evaluation is based on measuring four metrics including success rate, average latency, throughput, and resource consumption. The experimental results of executing 100 transactions show that Hyperledger Fabric generally surpasses Ethereum against the four performance metrics. The presented results in this research would assist practitioners in their decision-making process of adopting the ideal Blockchain platform into their IT systems based on application requirements.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122290904","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 : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257830
G. M. Abro, V. Asirvadam, S. Zulkifli
This work presents performance analysis between conventional fuzzy-based sliding mode control (F-SMC) and single-dimension fuzzy-sliding mode control (SDF-SMC) for an underactuated quadrotor craft. It has been observed that fuzzy logic control (FLC) can resolve various issues of sliding mode controller (SMC) for the quadrotor, such as reduction in chattering noise or Zeno phenomenon. However, FLC increases required computational power and processing time, which directly rely on the list of rules defined for the FLC. These rules trigger the gains of the SMC. This paper presents an approach to convert the conventional FLC two-dimensional rule-based table into a single-dimension table, leading to a control algorithm referred to as single-input fuzzy-sliding mode control. Numerical simulation work has been implemented on MATLAB-Simulink software, which demonstrates the same control performance of the SDF-SMC as the conventional F-SMC, but with the improvement of reduced computational power and processing time.
{"title":"Single-Input Fuzzy-Sliding Mode Control for an Underactuated Quadrotor Craft","authors":"G. M. Abro, V. Asirvadam, S. Zulkifli","doi":"10.1109/IICAIET49801.2020.9257830","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257830","url":null,"abstract":"This work presents performance analysis between conventional fuzzy-based sliding mode control (F-SMC) and single-dimension fuzzy-sliding mode control (SDF-SMC) for an underactuated quadrotor craft. It has been observed that fuzzy logic control (FLC) can resolve various issues of sliding mode controller (SMC) for the quadrotor, such as reduction in chattering noise or Zeno phenomenon. However, FLC increases required computational power and processing time, which directly rely on the list of rules defined for the FLC. These rules trigger the gains of the SMC. This paper presents an approach to convert the conventional FLC two-dimensional rule-based table into a single-dimension table, leading to a control algorithm referred to as single-input fuzzy-sliding mode control. Numerical simulation work has been implemented on MATLAB-Simulink software, which demonstrates the same control performance of the SDF-SMC as the conventional F-SMC, but with the improvement of reduced computational power and processing time.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129086334","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 : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257860
Ivan Yong-Sing Lau, T. Chua, W. Lee, Chya-Wei Wong, T. Toh, H. Ting
Measurement of the gait parameter typically requires a combination of force plate and motion tracking system, which restricts the calculated value to the laboratory environment. The possibility of a portable tracking system has been investigated in some recent studies, such as Microsoft Kinect sensors. The present research collaborated with Sibu Hospital and KPJ Sibu Specialist Hospital to collect the data from subjects. Concurrently, the law of cosine and dot cross product was used as primary measures to determine the scalar value of vector knee, ankle, and hip and the angle that formed by knee, ankle, and hip. The result generated by the proposed knee osteoarthritis severity diagnostics system is presented, specifically, demonstrate the analysis algorithm of various gait parameters system. In summary, Microsoft Kinect v2 sensor can be utilised in the present research to capture subject movement, and a knee osteoarthritis severity diagnostics system is proposed as clinically feasible options for gait analysis.
{"title":"Kinect-Based Knee Osteoarthritis Gait Analysis System","authors":"Ivan Yong-Sing Lau, T. Chua, W. Lee, Chya-Wei Wong, T. Toh, H. Ting","doi":"10.1109/IICAIET49801.2020.9257860","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257860","url":null,"abstract":"Measurement of the gait parameter typically requires a combination of force plate and motion tracking system, which restricts the calculated value to the laboratory environment. The possibility of a portable tracking system has been investigated in some recent studies, such as Microsoft Kinect sensors. The present research collaborated with Sibu Hospital and KPJ Sibu Specialist Hospital to collect the data from subjects. Concurrently, the law of cosine and dot cross product was used as primary measures to determine the scalar value of vector knee, ankle, and hip and the angle that formed by knee, ankle, and hip. The result generated by the proposed knee osteoarthritis severity diagnostics system is presented, specifically, demonstrate the analysis algorithm of various gait parameters system. In summary, Microsoft Kinect v2 sensor can be utilised in the present research to capture subject movement, and a knee osteoarthritis severity diagnostics system is proposed as clinically feasible options for gait analysis.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126114206","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 : 2020-09-26DOI: 10.1109/IICAIET49801.2020.9257863
Pooi Shiang Tan, K. Lim, C. Lee
This paper presents a video-based human action recognition method leveraging deep learning model. Prior to the filtering phase, the input images are pre-processed by converting them into grayscale images. Thereafter, the region of interest that contains human performing action are cropped out by a pre-trained pedestrian detector. Next, the region of interest will be resized and passed as the input image to the filtering phase. In this phase, the filter kernels are trained using Sparse Autoencoder on the natural images. After obtaining the filter kernels, convolution operation is performed in the input image and the filter kernels. The filtered images are then passed to the feature extraction phase. The Histogram of Oriented Gradients descriptor is used to encode the local and global texture information of the filtered images. Lastly, in the classification phase, a Modified Hausdorff Distance is applied to classify the test sample to its nearest match based on the histograms. The performance of the deep learning algorithm is evaluated on three benchmark datasets, namely Weizmann Action Dataset, CAD-60 Dataset and Multimedia University (MMU) Human Action Dataset. The experimental results show that the proposed deep learning algorithm outperforms other methods on the Weizmann Dataset, CAD-60 Dataset and MMU Human Action Dataset with recognition rates of 100%, 88.24% and 99.5% respectively.
{"title":"Human Action Recognition with Sparse Autoencoder and Histogram of Oriented Gradients","authors":"Pooi Shiang Tan, K. Lim, C. Lee","doi":"10.1109/IICAIET49801.2020.9257863","DOIUrl":"https://doi.org/10.1109/IICAIET49801.2020.9257863","url":null,"abstract":"This paper presents a video-based human action recognition method leveraging deep learning model. Prior to the filtering phase, the input images are pre-processed by converting them into grayscale images. Thereafter, the region of interest that contains human performing action are cropped out by a pre-trained pedestrian detector. Next, the region of interest will be resized and passed as the input image to the filtering phase. In this phase, the filter kernels are trained using Sparse Autoencoder on the natural images. After obtaining the filter kernels, convolution operation is performed in the input image and the filter kernels. The filtered images are then passed to the feature extraction phase. The Histogram of Oriented Gradients descriptor is used to encode the local and global texture information of the filtered images. Lastly, in the classification phase, a Modified Hausdorff Distance is applied to classify the test sample to its nearest match based on the histograms. The performance of the deep learning algorithm is evaluated on three benchmark datasets, namely Weizmann Action Dataset, CAD-60 Dataset and Multimedia University (MMU) Human Action Dataset. The experimental results show that the proposed deep learning algorithm outperforms other methods on the Weizmann Dataset, CAD-60 Dataset and MMU Human Action Dataset with recognition rates of 100%, 88.24% and 99.5% respectively.","PeriodicalId":300885,"journal":{"name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125831758","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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