• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.56-63
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• 2007

In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and con-nected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based tex-ture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a 'aligns games.' The results show that the system process more than 30 frames/sec on PC for the $320{\times}240$ size input image and supply a user-friendly and convenient access to a computer in real-time operation.

• PNF and Movement
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• v.2 no.1
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• pp.25-33
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• 2004

Purpose : The purpose of this article is to summarize the characteristics of isotonic combination. Method : Some studies of the motor unit activation patterns during isometric, concentric, and eccentric actions, neural strategies in the control of muscle force, and concentric versus combined concentric-eccentric training were reviewed. Results & Conclusions : Eccentric torque may be relatively higher than concentric torque for two potential reasons: 1) stretch responses in the antagonist are not elicited to restrain the motion as can occur concentrically and 2) stretch responses in the agonist may augment eccentric torque production. Concentric-eccentric training has a greater influence on functional capacity than that of concentric training. Both maximal force and average force throughout the motion were significantly higher when the dynamic action was started with preactivation as compared to the mode without preactivation. The peak torques observed during the concentric phase of the eccentric-concentric muscle actions were higher than those noted in the pure concentric contraction.

• Therapeutic Science for Rehabilitation
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• v.2 no.1
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• pp.13-23
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• 2013

Constraint-Induced Movement Therapy(CIMT) is considered as one of the most interesting upper extremity rehabilitation in the field of neurorehabilitation. CIMT is an intensive training provided in the affected upper limb for 6 hours a day, 5 days a week for 2 weeks, while unaffected arm is restrained for 90% of waking hours. Recently, instead of CIMT, modified Constraint-Induced Movement Therapy(mCIMT) has been applied because of the clinical limitations of CIMT. CIMT or mCIMT studies have used various outcome instruments to measure different aspects of upper limb function after intervention. There are various kinds of evaluation tools to measure different aspects of upper limb function after CIMT intervention. It has been proven that Pediatric Motor Activity Log(PMAL), Quality of Upper Extremities Skills Test(QUEST), Melbourne Assessment of Unilateral Upper Limb Function(MAULF), Assisting Hand Assessment (AHA) are effective. The purpose of this study was to investigate the cortical change in children with hemiplegic cerebral palsy after CIMT. As a result, use-dependent cortical reorganization was revealed. Also, increased activity of the contralateral motor cortex and decreased activity of the ipsilateral cortex were found. It supports the mechanism of cortical reorganization, the principles of neural plasticity and specifically activation of the contralateral cortex, for improving upper limb function after CIMT.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2002.10a
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• pp.156-156
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• 2002

The goal of this study is to develop a biomarker used in monitoring abnormal behaviors of Japanese medaka (Oryzias latipes) as a model organism caused by hazardous chemicals that are toxic and persistent in the ecosystem. A widely used insecticide, diazinon (O, O-diethyl O- (2-isopropyl-4-methyl-6-pyrimidinyl) phosphorothioate), is highly neurotoxic to fish, and it is also well known that it causes vertebral malformation and behavioral changes of fish at relatively low concentrations. The fish behaviors were observed on a real time basis using an image processing and automatic data acquisition system. The genes potentially involved in the abnormal behaviors were cloned using suppression subtractive hybridization (SSH) technique. The untreated individuals showed common behavioral characteristics. When the test fish was affected by diazinon at a concentration of 0.1 and 1 ppm, some specific patterns were observed in its behavioral activity and locomotive tracks. The typical patterns were enhanced surfacing activity, opercular movement, erratic movement, tremors and convulsions as reported previously. The number of genes up-regulated tty diazinon treatment were 97 which includes 27 of unknown genes. The number of down-regulated genes were 99 including 60 of unknown genes. These gene expression patterns will be analyzed by the artificial neural networks such as self organization map (SOM) and multilayer perceptron (MLP), revealing the role of genes responsible for the behaviors. These results may provide molecular biological and neurobehavioral bases of a biomonitoring system for diazinon using a model organism such as fish.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.561-568
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• 2021

In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movement speed in real time. CNN-based deep learning algorithms and conventional dense optical flows have a large consumption time, making it difficult to detect objects and estimate its movement speed in real time. In this paper, using a single camera image, fast object detection was performed using the YOLOv5 algorithm, a deep learning algorithm, and fast estimation of the speed of the object was performed by using a local dense optical flow modified from the existing dense optical flow based on the detected object. Based on this algorithm, we present a system that can predict the collision time and probability, and through this system, we intend to contribute to prevent tram accidents.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.85-95
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• 2021

Recently, as data mining and artificial neural network techniques are developed, analyzing large amounts of data is proposed to reduce the dimension of the data. In general, empirical orthogonal function (EOF) used to reduce the dimension in the ocean data and recently, Self-organizing maps (SOM) algorithm have been investigated to apply to the ocean field. In this study, both algorithms used the monthly Sea level anomaly (SLA) data from 1993 to 2018 around the East Asia Coasts. There was dominated by the influence of the Kuroshio Extension and eddy kinetic energy. It was able to find the maximum amount of variance of EOF modes. SOM algorithm summarized the characteristic of spatial distributions and periods in EOF mode 1 and 2. It was useful to find the change of SLA variable through the movement of nodes. Node 1 and 5 appeared in the early 2000s and the early 2010s when the sea level was high. On the other hand, node 2 and 6 appeared in the late 1990s and the late 2000s, when the sea level was relatively low. Therefore, it is considered that the application of the SOM algorithm around the East Asia Coasts is well distinguished. In addition, SOM results processed by SLA data, it is able to apply the other climate data to explain more clearly SLA variation mechanisms.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.10a
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• pp.23-24
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• 2003

The goal of this study is to develop a biomarker used in monitoring abnormal behaviors of Japanese medaka (Oryzias latipes) as a model organism caused by hazardous chemicals. Japanese medaka was treated by copper and fluoranthene of appropriate sublethal concentrations after starvation for 48 hr. In this study we investigated neural toxicity of copper and fluoranthene in Japanese medaka (Oryzias latipes) along with comparative analysis of corresponding behavioral responses. The untreated individuals showed common behavioral characteristics (i.e., smooth and linear movements). Locomotive activity of the fish was monitored using an image processing and automatic data acquisition system. When treated with copper (100 ppb), the fish showed shaking patterns more frequently. As the concentration of copper increased to 1,000 ppb, activity decreased, and the fish showed an erratic movement. The treated with fluoranthene, however, showed stopping and abrupt change of orientation (100 ppb), and severely reduced locomotive activity and enhanced surfacing activity (1,000 ppb).

• PNF and Movement
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• v.5 no.1
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• pp.9-17
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• 2007

Purpose : The purpose of this study was to test the effect of balance training for proprioceptive and vestibular sensory stimulation and therapeutic environment on expression of BDNF after traumatic brain injury in the rat. Subject : Twelve Sprague-Dawley rats were randomly assigned into group I and group II. After traumatic brain injury, group I was housed in standard cage for 7 days. Group II was housed in therapeutic cage after balance training for 7 days. Method : Traumatic brain injury was induced by weight drop model and after operation they were housed in individual standard cages for 24 hours. After 7th day, the rats were sacrificed and cryostat coronal sections were processed individually in goat polyclonal anti-BDNF antibody. The morphologic characteristics and the BDNF expression were investigated in injured hemisphere section from immunohistochemistry using light microscope. Result : Immunohistochemical response of BDNF in lateral nucleus, purkinje cell layer, superior vestibular nucleus and pontine nucleus appeared very higher in group II than in group I Conclusion : The present result revealed that simultaneously application of balance training for proprioceptive and vestibular sensory stimulation input and therapeutic environment in traumatic brain injured rats is enhance expression of BDNF and it is facilitates neural plasticity.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.249-258
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• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.

• The Korean Journal of Physiology and Pharmacology
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• v.17 no.4
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• pp.299-306
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• 2013

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been widely used as a treatment for the movement disturbances caused by Parkinson's disease (PD). Despite successful application of DBS, its mechanism of therapeutic effect is not clearly understood. Because PD results from the degeneration of dopamine neurons that affect the basal ganglia (BG) network, investigation of neuronal responses of BG neurons during STN DBS can provide informative insights for the understanding of the mechanism of therapeutic effect. However, it is difficult to observe neuronal activity during DBS because of large stimulation artifacts. Here, we report the observation of neuronal activities of the globus pallidus (GP) in normal and PD model rats during electrical stimulation of the STN. A custom artifact removal technique was devised to enable monitoring of neural activity during stimulation. We investigated how GP neurons responded to STN stimulation at various stimulation frequencies (10, 50, 90 and 130 Hz). It was observed that activities of GP neurons were modulated by stimulation frequency of the STN and significantly inhibited by high frequency stimulation above 50 Hz. These findings suggest that GP neuronal activity is effectively modulated by STN stimulation and strongly dependent on the frequency of stimulation.