• PNF and Movement
• /
• v.10 no.1
• /
• pp.25-33
• /
• 2012

Purpose : The purpose of this study was to compare the effect of treadmill training and cognitive task with in the course of treadmill training at the same time with chronic stroke patients. Methods : Fourteen chronic stroke patients participated. Participants were randomly assigned to the control and experimental group(7 experimental, 7 control). All of participants were in-patients at local hospital and had been receiving a traditional rehabilitation program, five days a week. The both groups have undergone 4weeks. The experimental group trained in treadmill and cognitive task at the same time, but control group trained only treadmill. 10m walking test, Timed Up & Go (TUG) test and 6 Minutes walking(6M walking) test to measure the walking speed, dynamic balance and waling endurance ability were carried out before and after the training. Results : The result of the study were as follow:10m walking test were significantly increased both groups(p<.01), but not significant between groups(p>.05). TUG test were significantly increased both groups(p<.001) and between groups(p<.01). 6M walking test were significantly increased both groups(p<.001), but not significant between groups(p>.05). Conclusion : Ahead of return to the community to patients with stroke, cognitive task with in the course of treadmill training at the same time was effective in improving the dynamic balance ability.

• Korean Journal of Remote Sensing
• /
• v.38 no.1
• /
• pp.1-20
• /
• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Investigative Magnetic Resonance Imaging
• /
• v.26 no.2
• /
• pp.96-103
• /
• 2022

Purpose: The survival of organisms critically depends on avoidance responses to life-threatening stimuli. Information about dangerous situations needs to be remembered to produce defensive behavior. To investigate underlying brain regions to process information of danger, manganese-enhanced MRI (MEMRI) was used in olfactory fear-conditioned rats. Materials and Methods: Fear conditioning was conducted in male Sprague-Dawley rats. The animals received nasal injections of manganese chloride solution to monitor brain activation for olfactory information processing. Twenty-four hours after manganese injection, rats were exposed to electric foot shocks with odor cue for one hour. Control rats were exposed to the same odor cue without foot shocks. Forty-eight hours after the conditioning, rats were anesthetized and their brains were scanned with 9.4T MRI. Acquired images were processed and statistical analyses were performed using AFNI. Results: Manganese injection enhanced brain areas involved in olfactory information pathways in T1 weighted images. Rats that received foot shocks showed higher brain activation in the central nucleus of the amygdala, septum, primary motor cortex, and preoptic area. In contrast, control rats displayed greater signals in the orbital cortex and nucleus accumbens. Conclusion: Nasal delivery of manganese solution enhanced olfactory signal pathways in rats. Odor cue paired with foot shocks activated amygdala, the central brain region in fear, and related brain circuits. Use of MEMRI in fear conditioning provides a reliable monitoring technique of brain activation for fear learning.

• Journal of Interdisciplinary Genomics
• /
• v.4 no.2
• /
• pp.24-30
• /
• 2022

Klinefelter's syndrome (KS) is a syndrome with extra X chromosome(s), in XY individuals, characterized by gynecomastia, small testes, and infertility. Additional X chromosomes can be present as variable karyotypic forms, including mosaicism (47,XXY/46,XY). The reported prevalence of KS ranges from one in 500 to one in 1,000 live males, but is probably underestimated. The classic phenotype is small, firm testes and infertility resulting from seminiferous tubule dysgenesis and androgen deficiency. The spectrum of KS includes tall stature with relatively long legs and arm span, decreased body hair, learning disabilities, behavioral problems, poor motor skills, and other important medical issues, such as metabolic syndrome, diabetes, autoimmune diseases, cardiovascular disease, certain neoplasia. The increased risk of certain medical problems in KS can be attributed to a direct effect of the extra X chromosome, the combined action of multiple genomic and epigenetic factors, or the hormonal imbalances. Typically, chromosome analysis is not ordered for adult patients with general medical conditions, except for suspected cases of hematologic and lymphoid disorders. Even though it was found during work-up for certain disorders in adult patient, most physicians do not suspect KS or consider its impact. Therefore, understanding the pathophysiology and variable manifestation in KS is necessary, and discussions with multidisciplinary teams will help to diagnose and treat males with KS.

• Journal of the Korea Safety Management & Science
• /
• v.24 no.2
• /
• pp.33-39
• /
• 2022

In order to improve the implementation of safety and health education at the site for industrial accident prevention activities, research was conducted to minimize inconvenience and increase utilization by redesigning and developing existing education methods. To date, occupational safety and health education has been conducted without considering the general work characteristics and functional facilities (mechanical, electrical, instrumentation, chemical) of workers (mechanical: turbine, valve, pump, hydraulic system, electrical: generator, breaker, motor, etc.). In particular, plant facilities were classified as mechanical and electrical facilities to improve the methodology for industrial safety and health education for plant maintenance workers. In addition, the "One Page Education Plan" was announced as a learning case because the spread of COVID-19 infectious diseases made it impossible to reduce or control the number of people in all groups and groups. The improvement of this training method will play a major role in improving the effectiveness of safety education in power plant workplaces.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.815-817
• /
• 2022

This paper is about the development of an automatic stair climbing trolley for carrying loads without manpower. The design of tri-wheeled structure and center of mass enable the trolley to move on flat ground and also to ascend stairs by self-balancing. The overall design enables the trolley to avoid collision to walls when the trolley rotates on domestic landings. When the camera recognizes the stair, the sensor measures distance from the trolley to the stair. Then the trolley can move to align itself in the middle of the stair and it starts climbing. It can ascend to a specific floor based on the floor number entered by the user. As a result, the automatic stair climbing trolley is expected to help humans by protecting from accidents of dropping loads and saving their power. It is also expected to use for various purposes such as delivering packages, moving and carrying heavy loads in buildings without elevator.

• Educational Technology International
• /
• v.13 no.2
• /
• pp.283-312
• /
• 2012

Problem-solving ability is one of the most important learning outcomes for students to compete and accomplish in a knowledge-based society. It has been empirically proven that visualization plays a central role in problem-solving. The best performing problem-solver might have a strong visualization tendency. However, there is little research as to what factors of visualization tendency primarily related to problem-solving ability according to phases of problem-solving. The purpose of this study is to identify the relationship between visualization tendency and problem-solving ability, to determine which factors of visualization tendency influence problem-solving ability in each phase of problem-solving, and to examine different problem-solving ability from the perspective of the levels of visualization tendency. This study has found out that visualization tendency has a significant correlation with problem-solving ability. Especially, Generative Visualization and Spatial-Motor Visualization as sub-visualization tendency were more strongly related to each phase of problem-solving. It indicates that visualization tendency to generate and operate mental processing can be considered a major cognitive skill to improve problem-solving ability. Furthermore, students who have high visualization tendency also have significantly higher problem-solving ability than students with low visualization tendency. It shows that the levels of visualization tendency can predict variables related to students' problem-solving ability.

• Asia pacific journal of information systems
• /
• v.29 no.4
• /
• pp.771-788
• /
• 2019

Deep learning techniques such as Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) show superior performance in text classification than traditional approaches such as Support Vector Machines (SVMs) and Naïve Bayesian approaches. When using CNNs for text classification tasks, word embedding or character embedding is a step to transform words or characters to fixed size vectors before feeding them into convolutional layers. In this paper, we propose a parallel word-level and character-level embedding approach in CNNs for text classification. The proposed approach can capture word-level and character-level patterns concurrently in CNNs. To show the usefulness of proposed approach, we perform experiments with two English and three Korean text datasets. The experimental results show that character-level embedding works better in Korean and word-level embedding performs well in English. Also the experimental results reveal that the proposed approach provides better performance than traditional CNNs with word-level embedding or character-level embedding in both Korean and English documents. From more detail investigation, we find that the proposed approach tends to perform better when there is relatively small amount of data comparing to the traditional embedding approaches.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.1
• /
• pp.114-123
• /
• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

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