• Ocean Systems Engineering
• /
• v.6 no.3
• /
• pp.217-231
• /
• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• Journal of Astronomy and Space Sciences
• /
• v.18 no.2
• /
• pp.109-118
• /
• 2001

KITSAT-1, launched in 1992, passes through Inner Van Allen Radiation Belt in which high energy Protons cause single event upsets(SBUs) in the main memory of KITSAT-1 OBC(On-Board Computer) 186. The present paper compares SEU data from the OBC186 with the AP-8 model of NASA/NSSDC using the Chi-Square method to estimate the SEU threshold energy. Shielding effect by the satellite body has been taken into account to model the proton fluxes at the position of OBC186, and SEUs recorded during the high solar activities have been removed to avoid the spurious result. The result shows that the SEU threshold energy of the main memory of KITSAT-1 OBC186 is estimated to be about $110{pm}10MeV$.

• The Journal of Korean Physical Therapy
• /
• v.35 no.1
• /
• pp.31-35
• /
• 2023

Purpose: This study sought to identify whether fascial therapy using myofascial release (MFR) and Fascial Distortion Model (FDM) techniques affected not only the area where treatment was being given but also remote areas connected to the treatment area by fascial continuity through comparison of the pain pressure threshold (PPT). Methods: The subjects were 16 healthy normal adults in their 20s and 30s who were divided into the MFR and FDM groups before the experiment. The PPT was measured at 4 different points on the body of the subjects. C7, T7, L5, and gastrocnemius along the superficial back line (SBL) before and after the intervention. Results: Only the FDM group subjects showed a significant increase in the PPT at T7 after the intervention. (p<0.05). In addition, the FDM group demonstrated significantly increased PPT at L5 compared to the MFR group. However, neither the FDM nor the MFR group showed a meaningful change in the PPT at the remote area in the lower leg. Conclusion: These findings showed that FDM can affect PPT more and has a positive effect on the pain threshold compared to MFR. However, neither FDM nor MFR showed any effect on the PPT in a remote area.

• Asian-Australasian Journal of Animal Sciences
• /
• v.18 no.8
• /
• pp.1088-1097
• /
• 2005

Main objectives of this study were to investigate accuracy, bias and power of linear and threshold model segregation analysis methods for detection of major genes in categorical traits in farm animals. Maximum Likelihood Linear Model (MLLM), Bayesian Linear Model (BALM) and Bayesian Threshold Model (BATM) were applied to simulated data on normal, categorical and binary scales as well as to disease data in pigs. Simulated data on the underlying normally distributed liability (NDL) were used to create categorical and binary data. MLLM method was applied to data on all scales (Normal, categorical and binary) and BATM method was developed and applied only to binary data. The MLLM analyses underestimated parameters for binary as well as categorical traits compared to normal traits; with the bias being very severe for binary traits. The accuracy of major gene and polygene parameter estimates was also very low for binary data compared with those for categorical data; the later gave results similar to normal data. When disease incidence (on binary scale) is close to 50%, segregation analysis has more accuracy and lesser bias, compared to diseases with rare incidences. NDL data were always better than categorical data. Under the MLLM method, the test statistics for categorical and binary data were consistently unusually very high (while the opposite is expected due to loss of information in categorical data), indicating high false discovery rates of major genes if linear models are applied to categorical traits. With Bayesian segregation analysis, 95% highest probability density regions of major gene variances were checked if they included the value of zero (boundary parameter); by nature of this difference between likelihood and Bayesian approaches, the Bayesian methods are likely to be more reliable for categorical data. The BATM segregation analysis of binary data also showed a significant advantage over MLLM in terms of higher accuracy. Based on the results, threshold models are recommended when the trait distributions are discontinuous. Further, segregation analysis could be used in an initial scan of the data for evidence of major genes before embarking on molecular genome mapping.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.12
• /
• pp.17-23
• /
• 2010

In this paper, a new analytical model for deriving the threshold voltage of a short-channel bulk-type MOSFET is suggested. Using the Fourier coefficient method, the Laplace equation in the oxide region and the Poisson equation in the depleted silicon region have been solved two-dimensionally. Making use of them, the minimum surface potential is derived to describe the threshold voltage. Simulation results show good agreement with the dependencies of the threshold voltage on the various device parameters and applied bias voltages.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.46 no.11
• /
• pp.1-7
• /
• 2009

In this paper, a simple analytical model for deriving the threshold voltage of a short-channel intrinsic-body SDG SOI MOSFET is suggested. Using the iteration method, both Laplace equations in intrinsic silicon body and gate oxide are solved two-dimensionally. Obtained potential distributions in both regions are expressed in terms of fourth and fifth-order of the coordinate perpendicular to the silicon channel direction. Making use of them, the surface potential is obtained to derive the threshold voltage in a closed-form. Simulation results show the fairly accurate dependencies of the threshold voltage on the various device parameters and applied bias voltages.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.45 no.7
• /
• pp.9-16
• /
• 2008

In this paper, a simple analytical model for deriving the threshold voltage of a short-gate SOI MESFET is suggested. Using the iteration method, the Poisson equation in the fully depleted silicon channel and the Laplace equation in the buried oxide region are solved two-dimensionally, Obtained potential distributions in each region are expressed in terms of fifth-order of $\chi$, where $\chi$ denotes the coordinate perpendicular to the silicon channel direction. From them, the bottom channel potential is used to describe the threshold voltage in a closed-form. Simulation results show the dependencies of the threshold voltage on the various device geometry parameters and applied bias voltages.

• Journal of Information Processing Systems
• /
• v.10 no.2
• /
• pp.283-299
• /
• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.167-175
• /
• 2007

Fuzzy logic is used to represent qualitative knowledge and provides interpretability to a controlling system model in bioinformatics. This paper focuses on a bioinformatics data classification which is an important bioinformatics application. This paper reviews the two traditional controlling system models The sequence-based threshold controller have problems of optimal range decision for threshold readjustment and long processing time for optimal threshold induction. And the binary-based threshold controller does not guarantee for early system stability in the GPCR data classification for optimal threshold induction. To solve these problems, we proposes a fuzzy-based threshold controller for ART1 clustering in GPCR classification. We implement the proposed method and measure processing time by changing an induction recognition success rate and a classification threshold value. And, we compares the proposed method with the sequence-based threshold controller and the binary-based threshold controller The fuzzy-based threshold controller continuously readjusts threshold values with membership function of the previous recognition success rate. The fuzzy-based threshold controller keeps system stability and improves classification system efficiency in GPCR classification.

• Journal of Applied Reliability
• /
• v.17 no.3
• /
• pp.246-255
• /
• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.