• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.898-905
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• 2005

Iris recognition Is that identifies a user based on the unique iris muscle patterns which has the functionalities of dilating or contracting pupil region. Because it is reported that iris recognition is more accurate than other biometries such as face, fingerprint, vein and speaker recognition, iris recognition is widely used in the high security application domain. However, if unnecessary information such as eyelid and eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate iris code including eyelash and eyelid, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelid by using pyramid searching parabolic deformable template. In addition, we detect the eyelash by using the eyelash mask. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.3\%$ compared to that not using it.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.358-365
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• 2020

To describe how to perform urological evaluation in children with tethered cord syndrome (TCS). Although a common manifestation of TCS is the development of neurogenic bladder in developing children, neurosurgeons often face difficulty in detecting urological problems in patients with TCS. From a urological perspective, diagnosis of TCS in developing children is further complicated due to the differentiation between neurogenic bladder dysfunctions and transient bladder dysfunctions owing to developmental problems. Due to the paucity of evidence regarding evaluation prior to and after untethering, I have shown the purpose and tools for evaluation in my own practice. This may be tailored to the types of neurogenic bladder, developmental status, and risks for deterioration. While the urodynamic study (UDS) is the gold standard test for understanding bladder function, it is not a panacea in revealing the nature of bladder dysfunction. In addition, clinicians should consider the influence of developmental processes on bladder function. Before untethering, UDS should reveal synergic urethral movement, which indicates an intact sacral reflex and lack of TCS. Postoperatively, the measurement of post-void residual urine volume is a key factor for the evaluation of spontaneous voiders. In case of elevation, fecal impaction, which is common in spinal dysraphism, should be addressed. In patients with clean intermittent catheterization, the frequency-volume chart should be monitored to assess the storage function of the bladder. Toilet training is an important sign of maturation, and its achievement should be monitored. Signs of bladder deterioration should be acknowledged, and follow-up schedule should be tailored to prevent upper urinary tract damage and also to determine an adequate timing for intervention. Neurosurgeons should be aware of urological problems related to TCS as well as urologists. Cooperation and regular discussion between the two disciplines could enhance the quality of patient care. Accumulation of experience will improve follow-up strategies.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.215-224
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• 2011

There have been studying many researches to detect human body and to track one with increasing interest on human and computer interaction. In this paper, we propose the algorithm that automatically extracts joints, linked points of human body, using the ratio of human body under single camera and tracks object. The proposed method gets the difference images of the grayscale images and ones of the hue images between input image and background image. Then the proposed method composes the results, splits background and foreground, and extracts objects. Also we standardize the ratio of human body using face' length and the measurement of human body and automatically extract joints of the object using the ratio and the corner points of the silhouette of object. After then, we tract the joints' movement using block-matching algorithm. The proposed method is applied to test video to be acquired through a camera and the result shows that the proposed method automatically extracts joints and effectively tracks the detected joints.

• The Journal of Korean Medicine
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• v.37 no.1
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• pp.125-134
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• 2016

Objectives: The aim of this study is to develop diagnostic questionnaires for the lumbar movement system impairment syndrome. Methods: We had reviewed the previous study and literature and organized various checkable items for differential diagnosis of five different lumbar movement system impairment syndromes. Next, we selected items which can be developed as questionnaire items. Finally, we conducted face validity study with eight Korean medicine doctors and survey research for the importance score of the items with three experts. Results: We developed a diagnostic questionnaire as followings: 6 items for lumbar extension syndrome; 5 items for lumbar flexion syndrome; 6 items for lumbar rotation syndrome. With the 2 rounds of survey research, we could bridge the differences of the importance score of each items. Conclusions: Questionnaire for the diagnosis of movement system impairment syndrome was developed. With this questionnaire, objective diagnosis of lumbar movement system impairment syndrome can be expected. This tool may also be used for detecting sub-health status of musculoskeletal systems.

• Smart Structures and Systems
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• v.15 no.4
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• pp.997-1018
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• 2015

Structural health monitoring along with damage detection and assessment of its severity level in non-accessible reinforced concrete members using piezoelectric materials becomes essential since engineers often face the problem of detecting hidden damage. In this study, the potential of the detection of flexural damage state in the lower part of the mid-span area of a simply supported reinforced concrete beam using piezoelectric sensors is analytically investigated. Two common severity levels of flexural damage are examined: (i) cracking of concrete that extends from the external lower fiber of concrete up to the steel reinforcement and (ii) yielding of reinforcing bars that occurs for higher levels of bending moment and after the flexural cracking. The purpose of this investigation is to apply finite element modeling using admittance based signature data to analyze its accuracy and to check the potential use of this technique to monitor structural damage in real-time. It has been indicated that damage detection capability greatly depends on the frequency selection rather than on the level of the harmonic excitation loading. This way, the excitation loading sequence can have a level low enough that the technique may be considered as applicable and effective for real structures. Further, it is concluded that the closest applied piezoelectric sensor to the flexural damage demonstrates higher overall sensitivity to structural damage in the entire frequency band for both damage states with respect to the other used sensors. However, the observed sensitivity of the other sensors becomes comparatively high in the peak values of the root mean square deviation index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2185-2191
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• 2015

With the advance of the environment where we can get various multimedia contents, adult image detection has become an important issue these days. In this paper, we suggest a method of robustly detecting navel areas from input images which can be usefully utilized in adult image detection. The suggested algorithm first extracts face regions and extracts candidate nipple areas using a nipple map. Our method then selects only actual nipple regions by filtering candidate areas with geometrical features and an average nipple filter. Subsequently, the method robustly detects navel areas by using the structural relation with the nipple areas and applying edge and saturation images. Experimental results show that the suggested algorithm can effectively detect navel regions.

• The Korean Journal of Financial Management
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• v.20 no.1
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• pp.305-329
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• 2003

This work analyzes the influence of the dollar and yen currency on the rate of return of the individual firms and its symmetries based on the data from Jan. 5 1987 to Dec. 28, 2001. GARCH and autoregressive error models were used for on the daily data, due to the heteroscedascity and autoregression of the error terms, and as for the monthly data, this paper follows the autoregressive error models. Daily data fumed out to be a better explanatory variable in detecting exchange rate exposure, and EGARCH(1, 1) and GJR-GRARCH(1, 1) have higher competence in analyzing the daily data. Also, most of the exposed firms have been exposed in the negative region, and appreciation of exchange rate does not help enhancing the asset value of the domestic value. Analysis on the asymmetries let us conclude that high proportion of domestic firms face asymmetric exchange rate exposure, and that the pricing-to-market theory carries more conviction than the real option theory. Furthermore, monthly data are more precise in analysis of asymmetries.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.643-650
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• 2013

In this paper, we propose a novel method for enhancing the detection speed and rate by reducing the computation in Hough Circle Transform on real-time iris detection of smartphone camera image. First of all, we find a face and eyes from input image to detect iris and normalize the iris region into fixed size to prevent variation of size for iris region according to distance from camera lens. Moreover, we carry out histogram equalization to get regular image in bright and dark illumination from smartphone and calculate minimal iris range that contains iris with the distance between corner of the left eye and corner of the right eye on the image. Subsequently, we can minimize the computation of iris detection by applying Hough Circle Transform on the range including the iris only. The experiment is carried out in two case with bright and dark illumination. Our proposed method represents that detection speed is 40% faster and detection rate is 14% better than existing methods.

• Journal of Preventive Medicine and Public Health
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• v.37 no.4
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• pp.373-380
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• 2004

Objectives : There has been gradually increasing concern about the adverse health effects of electromagnetic radiation originating from cell phones which are widely used in modern life. Cell phone radiation may affect human health by increasing free radicals of human blood cells. This study has been designed to identify DNA damage of blood cells by electromagnetic radiation caused by cell phone use. Methods : This study investigated the health effect of acute exposure to commercially available cell phones on certain parameters such as an indicator of DNA damage for 14 healthy adult volunteers. Each volunteer during the experiment talked over the cell phone with the keypad facing the right side of the face for 4 hours. The single cell gel electrophoresis assay (Comet assay), which is very sensitive in detecting the presence of DNA strand-breaks and alkali-labile damage in individual cells, was used to assess peripheral blood cells (T-cells, B-cells, granulocytes) from volunteers before and after exposure to cell phone radiation. The parameters of Comet assay measured were Olive Tail Moment and Tail DNA %. Results : The Olive Tail Moment of B-cells and granulocytes and Tail DNA % of B-cells and granulocytes were increased by a statistically significant extent after 4-hour use of a cell phone compared with controls. Conclusion : It is concluded that cell phone radiation caused the DNA damage during the 4 hours of experimental condition. Nonetheless, this study suggested that cell phone use may increase DNA damage by electromagnetic radiation and other contributing factors.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.10
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• pp.323-328
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• 2020

Recently, new approaches that significantly improve performance in object detection and recognition using deep learning technology have been proposed quickly. Of the various techniques for object detection, especially facial object detection (Faster R-CNN, R-CNN, YOLO, SSD, etc), SSD is superior in accuracy and speed to other techniques. At the same time, multiple object detection networks are also readily available. In this paper, among object detection networks, Mobilenet v2 network is used, models combined with SSDs are trained, and methods for detecting objects at a rate of four times or more than conventional performance are proposed using TensorRT engine, and the performance is verified through experiments. Facial object detector was created as an application to verify the performance of the proposed method, and its behavior and performance were tested in various situations.