• Journal of Labour Economics
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• v.27 no.1
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• pp.27-53
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• 2004

This paper analyzes the two cases of labor disputes (Hyundai Motor in 1998 and Power Generation Companies in 2002) in the period of restructuring, by applying the behavioral theory of labor negotiations as a comparative framework. The paper compares th backgrounds of the labor disputes, core issues, bargaining processes, and evolutionary patterns and consequences of the labor disputes at the two cases. The common features, found in the two dispute cases, are strong mistrust and exclusive bargaining attitude between labor unions and management, little feasibility of contract zone in bargaining proposals by the two parties, heteronomous dispute resolution by the intervention of the government, and the lack of learning effect gained from the experience of labor disputes. This comparative case study identifies that the confrontational labor-management relations at the firm level is re-produced by a regressive process of the following circulation: labor-management distrust $\rightarrow$ interest conflict in bargaining demand $\rightarrow$ exclusive bargaining attitude $\rightarrow$ the experience of antagonistic dispute $\rightarrow$ deepened distrust. In conclusion, four parties-labor unions, management, the government, and public press - are required to make much effort to replace the vicious circle of labor-management confrontation by a virtueous cycle of labor-management cooperation.

• Physical Therapy Korea
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• v.15 no.2
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• pp.11-19
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• 2008

Studies of attentional focus effects, have shown that the performer's attentional focus plays an important role in the performance and learning of motor tasks. We examined the influence of attentional focus on the performance of dual tasks (a postural task and a suprapostural task) and used electromyography (EMG) to examine whether the differences between external and internal focus were also manifest at the neuromuscular level. The subjects (n=40) stood on a balance board (postural task) and held a bar horizontally (suprapostural task). All of the subjects performed under different attentional focus conditions: external (balancer on balance board) or internal (feet) focus on the postural task, and external (balancer on bar) or internal (hand) focus on the suprapostural task. The mean displacement velocity of the bar and the percent reference voluntary contraction (%RVC) of the biceps brachii were reduced when the subjects adopted an external focus on the suprapostural task (p<.05). In addition, the mean displacement velocity of the balance board and %RVC of the tibialis anterior were reduced when the subjects adopted an external focus on the postural task (p<.05). When the subjects adopted an external focus on the suprapostural task, the mean displacement velocity of the balance board and %RVC of the tibialis anterior were also reduced (p<.05). When the subjects' attentional focus was on the postural task, there were no differences in the mean displacement and %RVC of the biceps brachii between attentional focuses. The performance of each task was enhanced when subjects focused on the respective task. The suprapostural task goals had a stronger influence on postural control than vice versa. These results reflect the propensity of the motor system to optimize control processes based on the environmental outcome, or movement effect, that the performer wants to achieve.

• Physical Therapy Rehabilitation Science
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• v.4 no.1
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• pp.28-31
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• 2015

Objective: Psychomotor imagery has been widely used to improve motor performance and motor learning. Recent research suggests that during visualization, changes occur in neurophysiological networks that make physical practice more effective in configuring functional networks for skillful behaviors. The aim of our pilot study was to determine if there was change and to what extent there was differentiation in modulation in electroencephalography (EEG) frequencies between visualizing a state of rest and a state of exercise performance and to identify the preponderant frequency. Design: Quasi-experimental design uncontrolled before and after study. Methods: EEG brain wave activity was recorded from 0-40 Hz from nine cerebral cortical scalp regions F3, Fz, F4, C3, Cz, C4, P3, POz, and P4 with a wireless telemetric EEG system. The subjects, while sitting on a chair with eyes closed, were asked to visualize themselves in a state of routine rest/relaxation and after a period of time in a state of their routine exercise performance. Results: The gamma frequency, 31-40 Hz, (${\gamma}$) was the predominant wave band in differentiation between visualizing a state of rest versus visualizing a state of exercise performance. Conclusions: We suggest these preliminarily findings show the EEG electrocortical activity for athletes is differentially modulated during visualization of exercise performance in comparison to rest with a predominant ${\gamma}$ wave band frequency observed during the state of exercise. Further controlled experimental studies will be performed to elaborate these observations and delineate the significance to optimization of psychomotor exercise performance.

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.81-92
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• 2022

Objectives : This study aimed to investigate the effect of beat-keeping games in smartphone applications on improving executive functions in children with developmental delays. Methods : Three children diagnosed with developmental delay were included in this study. The ABA design used a single-subject experimental research design. The independent variable was the beat-keeping game. The game was held three times a week for a total of seven times for 20 minutes, including breaks. The dependent variable, "Visual-motor speed," was measured every session to assess if the beat-keeping game was effective in improving the participant's executive function. Further, before and after the intervention, "Children's Color Trails Test (CCTT)", "Block design," and "Finding hidden picture" were measured. Results : All three participants showed improvement in the performance of the beat-keeping game and the executive functions of "Visual-motor speed" and visual attention. Conclusions : Based on the results of this study, various effective applications for learning and intervention can be developed and applied to children with developmental delays who have difficulty in motivating themselves and lack attention.

• Molecules and Cells
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• v.43 no.4
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• pp.360-372
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• 2020

The basal ganglia network has been implicated in the control of adaptive behavior, possibly by integrating motor learning and motivational processes. Both positive and negative reinforcement appear to shape our behavioral adaptation by modulating the function of the basal ganglia. Here, we examined a transgenic mouse line (G2CT) in which synaptic transmissions onto the medium spiny neurons (MSNs) of the basal ganglia are depressed. We found that the level of collaterals from direct pathway MSNs in the external segment of the globus pallidus (GPe) ('bridging collaterals') was decreased in these mice, and this was accompanied by behavioral inhibition under stress. Furthermore, additional manipulations that could further decrease or restore the level of the bridging collaterals resulted in an increase in behavioral inhibition or active behavior in the G2CT mice, respectively. Collectively, our data indicate that the striatum of the basal ganglia network integrates negative emotions and controls appropriate coping responses in which the bridging collateral connections in the GPe play a critical regulatory role.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.150-158
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• 2021

Intracranial hemorrhage (ICH) refers to acute bleeding inside the intracranial vault. Not only does this devastating disease record a very high mortality rate, but it can also cause serious chronic impairment of sensory, motor, and cognitive functions. Therefore, a prompt and professional diagnosis of the disease is highly critical. Noninvasive brain imaging data are essential for clinicians to efficiently diagnose the locus of brain lesion, volume of bleeding, and subsequent cortical damage, and to take clinical interventions. In particular, computed tomography (CT) images are used most often for the diagnosis of ICH. In order to diagnose ICH through CT images, not only medical specialists with a sufficient number of diagnosis experiences are required, but even when this condition is met, there are many cases where bleeding cannot be successfully detected due to factors such as low signal ratio and artifacts of the image itself. In addition, discrepancies between interpretations or even misinterpretations might exist causing critical clinical consequences. To resolve these clinical problems, we developed a diagnostic model predicting intracranial bleeding and its subtypes (intraparenchymal, intraventricular, subarachnoid, subdural, and epidural) by applying deep learning algorithms to CT images. We also constructed a visualization tool highlighting important regions in a CT image for predicting ICH. Specifically, 1) 27,758 CT brain images from RSNA were pre-processed to minimize the computational load. 2) Three different CNN-based models (ResNet, EfficientNet-B2, and EfficientNet-B7) were trained based on a training image data set. 3) Diagnosis performance of each of the three models was evaluated based on an independent test image data set: As a result of the model comparison, EfficientNet-B7's performance (classification accuracy = 91%) was a way greater than the other models. 4) Finally, based on the result of EfficientNet-B7, we visualized the lesions of internal bleeding using the Grad-CAM. Our research suggests that artificial intelligence-based diagnostic systems can help diagnose and treat brain diseases resolving various problems in clinical situations.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.

• Journal of Power Electronics
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• v.5 no.2
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• pp.129-141
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• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.99-105
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• 2009

Computer-based learning with the access to World Wide Web has become a fundamental base for adopting beneficial education. It provides significant facilities such as animation and interactive processes that are not possible with textbooks. Web/Internet-enabled applications which is fully controlled and monitored from remote locations are extensively used by a number of Universities, national laboratories and companies for different kinds of applications all over the world. Continuous advances in computers and electronics coupled with drooping prices of hardware have made Web/Internet-based technologies less costly than before, particularly for educational organizations. Thus, it is more affordable to invest in these technologies that are essential for both expanding education over Web and further improving and advancing such technologies the application of remote virtual instruments will be demonstrated in this context along with experiments that can be adopted to be educational experimental lab for Engineering Education students.

• The Korean Journal of Physiology and Pharmacology
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• v.17 no.6
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• pp.505-510
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• 2013

Electroacupuncture (EA) is a modified form of acupuncture that utilizes electrical stimulation. We previously showed that EA stimulated rats were divided into responders that were sensitive to EA and non-responders that were insensitive to EA based on the tail flick latency (TFL) test. The dopamine beta-hydroxylase (DBH) gene was more abundantly expressed in the hypothalamus of responder rats than non-responder rats. To determine whether overexpression of DBH gene expression in the hypothalamus modulate EA analgesia, we constructed a DBH encoding adenovirus and which was then injected into the hypothalamus of SD rats. Microinjection of DBH or control GFP virus into the hypothalamus had no changes on the basal pain threshold measured by a TFL test without EA treatment. However, the analgesic effect of EA was significantly enhanced from seven days after microinjection of the DBH virus, but not after injection of the control GFP virus. DBH expression was significantly higher in the hypothalamus of DBH virus injected rat than control GFP virus or PBS injected rats. Moreover, expression of the DBH gene did not affect the body core temperature, body weight, motor function or learning and memory ability. Although the functional role of DBH in the hypothalamus in the analgesic effect of EA remains unclear, our findings suggest that expression of the DBH gene in the hypothalamus promotes EA analgesia without obvious side-effects.