• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.398-403
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• 2006

In this paper, we describe a fuzzy threshold selection technique for feature extraction in digital color images. this is achieved by the formulation a fuzzy inference system that evaluates threshold for feature configurations. The system uses two fuzzy measures. They capture desirable characteristics of features such as dependency of local intensity and continuity in an image. We give a graphical description of a nonlinear sketch feature extraction filter and design the fuzzy inference system in terms of the characteristics of the feature. Through the design, we provide selection method on the choice of a threshold to achieve certain characteristics of the extracted features. Experimental results show the usefulness of our fuzzy threshold inference approach which is able to extract features without human intervention.

• Journal of the Korean Society of Radiology
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• v.9 no.2
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• pp.73-77
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• 2015

In order to observe the detailed structure of the detector, it was CT scanned to reproduce the detailed structure of the crystal shapes and traverse layer using the Monte Carlo calculation applying the detector model. The uncertainty of measurement was lowered by adjusting the detector core by the edge effect at a higher energy (400 keV or higher) through the offset of peak efficiency of the gamma ray at low energy. It was confirmed that there was the appropriate matching with spatial dependency using the PENELOPE calculation. That was achieved by adjusting the parameters describing the crystal core and rounding of edge and crystal core.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.

• Journal of IKEEE
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• v.16 no.4
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• pp.375-381
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• 2012

In this paper, we present an implementation of Viola-Jones algorithm in a multi-core SoC by using skin color information and a parallel processing method. In order to reduce unnecessary operations and improve the detection speed, we adopted a face detection algorithm based on skin color and deleted background image. The algorithm is functionally divided into several parts taking account of the size and the dependency so that the divided functions can be proceeded in parallel. Experiment results in SoC with built-in Cortex-A9 multi core show that it is about 1.8 times faster than the existing algorithm which is not divided.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.1-12
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• 2020

In the medical field, numerical imbalance of data due to differences in disease prevalence is a common problem. It reduces the performance of a artificial intelligence network, leading to difficulties in learning a network with good performance. Recently, generative adversarial network (GAN) technology has been introduced as a way to address this problem, and its ability has been demonstrated by successful applications in various fields. However, it is still difficult to achieve good results in solving problems with performance degraded by numerical imbalances because the image resolution of the previous studies is not yet good enough and the structure in the image is modeled locally. In this paper, we propose a multi-scale conditional generative adversarial network based on attention mechanism, which can produce high resolution images to solve the numerical imbalance problem of chest X-ray image data. The network was able to produce images for various diseases by controlling condition variables with only one network. It's efficient and effective in that the network don't need to be learned independently for all disease classes and solves the problem of long distance dependency in image generation with self-attention mechanism.

• The Journal of Korean Society for Radiation Therapy
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• v.24 no.2
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• pp.175-181
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• 2012

Purpose: This study aimed to analyze the influence of aquaplastic mask which is used for the radiotherapy for patients with head and neck cancer on patient positioning by analyzing the results of 2D/2D matching with the use of Exactrac 6D couch system. Materials and Methods: 2D/2D matching-based Image guidance was performed with the use of Exactrac 6D couch system on a total of 14 patients with head and neck cancer who received radiotherapy at this hospital in a period from June 2010 to June 2011. The adjusted 6D values obtained after the image guidance were classified into values related with patients and values not related with patients as to the correlation between the results. Results: In the analysis of the relation of each adjusted value to patients, the coefficient of determination ($R^2$) of longitudinal and pitch direction was 0.76, of longitudinal and yaw direction was 0.48, and of pitch and yaw direction was 0.42 although the coefficient of determination for above factors was 0.03 or less when the dependency of patients was excluded. Conclusion: It was demonstrated that intrinsic factors of aquaplastic mask had influence on the immobilization of patients by aquaplastic mask although various factors related with patients had influence on the immobilization of patients. It is believed that if these factors are adjusted, the treatment of patients with head and neck cancer can be more accurate.

• Korean Journal of Applied Biomechanics
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• v.16 no.4
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• pp.153-164
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• 2006

This thesis is focused on kinematical and kinematical analysis of each types(Type #1 : use both swing of arm and reaction of knee, Type #2 : Use only swing of arm, not reaction of knee, type #3 : Neither use of swing of arm nor reaction of knee) of vertical jumps according to gender of High School Students. The subjects of this study is High School Student's male and female, 5 each, for analyzation of actions 3D image analyzing and GRF machines were used. To identify the differences of analyzed variables, an independent T-test on gender, an One-way ANOVA on types were used. Summery of the results are stated below. first of all, female students showed differences on Hip Joint angle and Joint Velocity from male students on Kimentic Variable. So training on hip joint force of flection and extension of female students is needed. Both male and female students showed relatively bigger result of arm's Angular Momentum than thigh's Angular Momentum on Type #1. This is regarded of faster Joint Velocity of Arm. Bigger result of female students of arm's contribution on Type #1 than male students can be said as Female student's weaker hip joint's angular muscle force than male student's, so the dependency of arm is heavier than male students. In Kinetic variable, GRF showed bigger result on male students than female students. So female students need to enhance joint's torque to increase GRF than male students. On vertical Impulse, high numeric data of last two reaction of tiptoe of vertical GRF and antero-posterior GRF helped increasing impulse by extending action time of force.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.458-463
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• 2016

In this paper, the fuzzy structure model for the consciousness structure of social workers related to the elder abuse factors was derived and analyzed. The characteristics of the model was obtained as follows. First, the elder abuse behavior at the top layer was related to the attitude of the elderly and the work overload of social workers. Second, the attitude of the elderly and the work overload of social workers at the middle layer were related to the personality of social worker, the physical and mental dependency of client, and the personality of client. Third, the personality of social worker, the knowledge of the elderly, the personality of client, and the physical and psychological dependence of the client affected directly the elder abuse behavior without going through the middle layer. Fourth, the work overload of social workers at the middle layer was affected the attitude of the elderly. Finally, the age of social workers, the working image, the job training, and provision of punishment to the social workers were the isolated layer, in which the relationship between the elder abuse behavior and related factors was not found.

• Korean Journal of Metals and Materials
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• v.48 no.3
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• pp.203-209
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• 2010

An application of the instrumented indentation technique has been expanded from the measurements of hardness and elastic modulus to the analysis of residual stress. A slope of the indentation loading curve increases (or decreases) according to compressive (or tensile) residual stress. A theoretical equation has been established for quantifying residual stress from the slope change. However, a precise observation of the remnant indents is indispensible because the theoretical approach needs actual contact information. In addition, the conventional hardness test is still used for predicting the residual stress distribution of welded joints. Thus, we observed the three-dimensional morphologies of the remnant indents formed on artificial stress states and analyzed stress effects on morphological recovery of the indents. First, a depth recovery ratio, which has been regarded as a sensitive stress indicator, did not show a clear dependency with the residual stress. Thus an analysis on volumetric recovery was tried in this study and yielded a inverse proportional behavior with the residual stress. In addition, an elastic to plastic volume recovery ratio showed more significant correlation with the residual stress.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.515-525
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• 2020

This study investigates the potential of bidirectional long short-term memory (Bi-LSTM) for efficient modeling of temporal information in crop classification using multitemporal remote sensing images. Unlike unidirectional LSTM models that consider only either forward or backward states, Bi-LSTM could account for temporal dependency of time-series images in both forward and backward directions. This property of Bi-LSTM can be effectively applied to crop classification when it is difficult to obtain full time-series images covering the entire growth cycle of crops. The classification performance of the Bi-LSTM is compared with that of two unidirectional LSTM architectures (forward and backward) with respect to different input image combinations via a case study of crop classification in Anbadegi, Korea. When full time-series images were used as inputs for classification, the Bi-LSTM outperformed the other unidirectional LSTM architectures; however, the difference in classification accuracy from unidirectional LSTM was not substantial. On the contrary, when using multitemporal images that did not include useful information for the discrimination of crops, the Bi-LSTM could compensate for the information deficiency by including temporal information from both forward and backward states, thereby achieving the best classification accuracy, compared with the unidirectional LSTM. These case study results indicate the efficiency of the Bi-LSTM for crop classification, particularly when limited input images are available.