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2016 International Conference on Robotics, Automation and Sciences (ICORAS)最新文献

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Signal-to-noise ratio estimation technique for SEM image using B-spline 基于b样条的扫描电镜图像信噪比估计技术
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872617
Z. X. Yeap, K. Sim, C. Tso
{"title":"Signal-to-noise ratio estimation technique for SEM image using B-spline","authors":"Z. X. Yeap, K. Sim, C. Tso","doi":"10.1109/ICORAS.2016.7872617","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872617","url":null,"abstract":"A new signal-to-noise ratio (SNR) estimation technique is proposed for the scanning electron microscope image. Based on only a single image, an estimation technique named B-spline is proposed. Three existing techniques are applied to compare with the performance of the proposed method in terms of the zero-offset point, SNR and percentage error. They are the nearest neighborhood, first order interpolation, and a combination of these two methods. A t-test is conducted on the proposed method. Noise variance is estimated from the SNR calculated and a Wiener filter will be used to filter the noise with the filtered images being similar to noise-free images.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126137942","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}
引用次数: 1
Investigation of electrochemical characterization of agarose gel for model of human head correlated to lightning currents 雷电电流相关人体头部模型琼脂糖凝胶的电化学表征研究
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872622
N. Yusof, E. Supriyanto, D. Dewi
{"title":"Investigation of electrochemical characterization of agarose gel for model of human head correlated to lightning currents","authors":"N. Yusof, E. Supriyanto, D. Dewi","doi":"10.1109/ICORAS.2016.7872622","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872622","url":null,"abstract":"Problems arisen in biomedical field have given an influence to the development of engineering devices which can especially solve special problems. Lightning injury is one of the special cases occurred that has some reasons which are not yet understood. Tissue diagnostic procedure is really beneficial in treating the diseases; hence further study concerning this procedure is required in electrochemical measurements. Electrical properties of tissue are the primary properties for the study in the current distribution through human body which is correlated to lightning current. Based on previous studies, human head is always the common contact point of lightning injury. Thus, this leads to the investigations of corresponding lightning injury through human body. This thesis focuses on the fabrication of tissue samples including the brain, skull and scalp phantom as a human head model. The fabrication is characterized based on electrochemical impedance spectroscopy (EIS) measurements against the frequency range from 100Hz to 1MHz to recognize the electrical properties and analyze the ion charge distribution by the diffusion rate of tissue phantom samples to contribute the stability poses. The measurements are conducted to determine the electrical conductivity, resistivity, relative permittivity and dissipation factor that affect the concentration of electrolyte. From this research, it is verified that the electrical properties show a comparable result with previous studies. It is also proven that the diffusion rate accelerates in higher concentration of solvent, confirming that all tissue phantoms are stable according to the tissue properties.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117186910","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}
引用次数: 0
Classification of EEG signals for brain-computer interface applications: Performance comparison 脑机接口应用的脑电信号分类:性能比较
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872610
M. Z. Ilyas, P. Saad, M. I. Ahmad, A. Ghani
{"title":"Classification of EEG signals for brain-computer interface applications: Performance comparison","authors":"M. Z. Ilyas, P. Saad, M. I. Ahmad, A. Ghani","doi":"10.1109/ICORAS.2016.7872610","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872610","url":null,"abstract":"This paper presents a comparison of Electroencephalogram (EEG) signals classification for Brain Computer-Interfaces (BCI). At present, it is a challenging task to extract the meaningful EEG signal patterns from a large volume of poor quality data and simultaneously with the presence of artifacts noises. Selection of the effective classification technique of the EEG signals at classification stage is very important to get the robust BCI system. Support Vector Machine (SVM), k-Nearest Neighbour (k-NN), Multi-Layer Perceptron Artificial Neural Network (MLP-ANN) and Logistic Regression (LR) were evaluated in this paper. A BCI competition IV — Dataset 1 is used for testing the classifiers. It is shown that LR and SVM are the most efficient classifier with the highest accuracy of 73.03% and 68.97%.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":" 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132011918","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}
引用次数: 30
A rapid medical image noise variance estimation method 一种快速的医学图像噪声方差估计方法
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872628
F. F. Ting, K. Sim, E. K. Wong
{"title":"A rapid medical image noise variance estimation method","authors":"F. F. Ting, K. Sim, E. K. Wong","doi":"10.1109/ICORAS.2016.7872628","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872628","url":null,"abstract":"Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the image through GWLC. A performance comparison between our proposed method and referred method are carried out. GWLC outperforms other related methods.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125297759","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}
引用次数: 6
Signal-to-noise ratio estimation technique for SEM image using linear regression 基于线性回归的扫描电镜图像信噪比估计技术
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872602
Z. X. Yeap, K. Sim, C. Tso
{"title":"Signal-to-noise ratio estimation technique for SEM image using linear regression","authors":"Z. X. Yeap, K. Sim, C. Tso","doi":"10.1109/ICORAS.2016.7872602","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872602","url":null,"abstract":"This paper proposes a new signal-to-noise ratio (SNR) estimation technique on scanning electron microscope (SEM) image, using linear regression. The method is based on the single image approach. Four good quality images are used to compare the proposed method and the existing methods: nearest neighborhood, first order interpolation and piecewise cubic Hermite interpolation. The results are compared in terms of estimation peaks, SNR and SNR in dB. In this paper four random selected images are used to present the performance of the proposed method. The method gives better estimation compared to existing methods. Statistical test shows that the estimation results are similar to the original.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"8 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120847039","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}
引用次数: 2
Improving iterative back projection super resolution model via anisotropic diffusion edge enhancement 利用各向异性扩散边缘增强改进迭代反投影超分辨模型
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872612
A. Nazren, S. Yaakob, R. Ngadiran, M. B. Hisham, N. M. Wafi
{"title":"Improving iterative back projection super resolution model via anisotropic diffusion edge enhancement","authors":"A. Nazren, S. Yaakob, R. Ngadiran, M. B. Hisham, N. M. Wafi","doi":"10.1109/ICORAS.2016.7872612","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872612","url":null,"abstract":"This improving technique based on combining an Iterative Back Projection (IBP) super resolution method with Anisotropic Diffusion (AD) technique for overcoming IBP weaknesses. The IBP has specialty to remove a reconstruction error and blurry effect iteratively manner in image registration place. However, it has a weakness from avoiding result image from chessboard effect and lost high frequency information. For this reason, this super resolution approach requires an edge enhancement technique to complement the weakness. Anisotropic diffusion is edge enhancement techniques and it has benefited to estimate a piecewise smooth image from a noisy input image. This paper proposed to integrate Anisotropic Diffusion techniques in IBP registration stages with an improvement in the IBP flow process model. This improvement in IBP model produced a result image in better appearing output with preserves high frequency information and less number of iteration process reconstruction.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121113948","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}
引用次数: 5
Potentiality of small wind turbines along highway in Malaysia 马来西亚高速公路沿线小型风力涡轮机的潜力
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872634
A. A. Al-Aqel, B. Lim, E. E. M. Noor, Tze Chuen Yap, S. Alkaff
{"title":"Potentiality of small wind turbines along highway in Malaysia","authors":"A. A. Al-Aqel, B. Lim, E. E. M. Noor, Tze Chuen Yap, S. Alkaff","doi":"10.1109/ICORAS.2016.7872634","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872634","url":null,"abstract":"Vehicle-induced turbulent airflow by the traffic in the highways is one of the sources of wind energy which can be harvested to supply the power to the highway lighting and telecommunication signaling. This work focuses on the assessment of potentiality of implementing small scale wind turbines along the highways in Malaysia. The study was started by conducting wind speed measurements adjacent to the highway at Lebuh SPA (Sungai Udang — Paya Rumput — Ayer Keroh Highway), a major highway in Malacca state, Malaysia. Three positional parameters have been investigated for suitable placement of the wind turbines. They are: the lateral distances from the road shoulder, the heights from the ground, and the orientation of the wind turbines relatives to the road. The former two parameters were set at 0.5 m, 1.0 m and 1.5 m for each position; while the latter was varied at perpendicular, 45°, and parallel to the road. The measurements were conducted using hot-wire anemometers. The results showed that the optimum positions for the wind turbine is at 1.0 m from the lateral distance and the height above the ground, respectively, and the optimum orientation is found to be 45° from the road at which the horizontal axis wind turbines (HAWT) can be directed. The large size vehicles such as lorries and busses were observed to produce higher wind speed as compared to the smaller ones. The results were further verified by using numerical simulation work through ANSYS Fluent.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"142 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116580310","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}
引用次数: 14
Adaptive pixel targeting and filtering with adjacency variations in second-order derivatives of pixel values for SEM images 扫描电镜图像像素值二阶导数邻接变化的自适应像素定位与滤波
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872624
W. T. Chan, Kok-Swee Sim
{"title":"Adaptive pixel targeting and filtering with adjacency variations in second-order derivatives of pixel values for SEM images","authors":"W. T. Chan, Kok-Swee Sim","doi":"10.1109/ICORAS.2016.7872624","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872624","url":null,"abstract":"The proposed method utilizes histograms of second-order derivatives of the values of the pixels in an SEM image. The histograms of second-order values can express the variation in pixel values due to the effect of noise. The histograms are used as the basis for a technique to target pixels for filtering. To control the number of pixels which are targeted so as to minimize blurring of edges, a curve-fitted profile is imposed on the histograms in order to select pixels based on the differences between their second-order derivatives and those of their neighbours. The proposed method is found to be more effective at higher levels of additive noise.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134051988","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}
引用次数: 1
Threading implementation on different hardware for travel time estimation purpose 在不同硬件上的线程实现，用于行程时间估计
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872607
I. Iszaidy, R. Ngadiran, R. B. Ahmad, M. Jais, D. Shuhaizar
{"title":"Threading implementation on different hardware for travel time estimation purpose","authors":"I. Iszaidy, R. Ngadiran, R. B. Ahmad, M. Jais, D. Shuhaizar","doi":"10.1109/ICORAS.2016.7872607","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872607","url":null,"abstract":"The travel time estimation is one of traffic management system which provide time taken from one point to another point. Travel time estimation system consists of an embedded platform with image sensor for detecting and tracking the vehicle. Due to limited resources of embedded board, it makes challenging to measure the travel time especially for fast moving vehicle. Capturing system required a high capturing rate of the camera to capture most current frame for fast moving vehicle. Threading is implemented in this system to improve embedded board resource utilization and input-output latency between camera and embedded board. In this paper, the threading technology is applied to two types of Raspberry Pi model and the performance of the embedded board is recorded and analyzed.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116322917","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}
引用次数: 0
Kinect-based framework for enhanced learning of disabled students 促进残疾学生学习的kinect框架
2016 International Conference on Robotics, Automation and Sciences (ICORAS) Pub Date : 2016-11-01 DOI: 10.1109/ICORAS.2016.7872608
M. S. M. Too, P. T. Ong, S. H. Lau, R. K. Y. Chang, K. S. Sim
{"title":"Kinect-based framework for enhanced learning of disabled students","authors":"M. S. M. Too, P. T. Ong, S. H. Lau, R. K. Y. Chang, K. S. Sim","doi":"10.1109/ICORAS.2016.7872608","DOIUrl":"https://doi.org/10.1109/ICORAS.2016.7872608","url":null,"abstract":"Educating students with disabilities is different from those without disabilities. Students with disabilities would require modifications and different methods of teaching thin the traditional method. Current learning methods in Malaysia make use of the traditional pencil-and-paper method, which is a hassle. Furthermore, the different styles of learning are often neglected. Although there are attempts to use other learning tools to assist these students, they are often costly. This paper proposes an alternative learning method via Microsoft Kinect. An overview of the research framework and proposed system will be detailed. The expected main outcome from this project is the design of the proposed cost effective framework using Kinect. The framework would include new alternative method of delivering subjects to physically disabled students rather than the current method. The proposed framework also contributes to the motivation factors that drive the students to perform, and the suitability of multiple learning styles utilizing the same classroom tool.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122640060","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}
引用次数: 3
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