• 기본간호학회지
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• 제7권1호
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• pp.109-121
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• 2000

Increasingly nursing science is embracing the concepts and methodology derived from psycho-neuroimmunology. It has been previously shown that stress increases and immune function declines in students undergoing examinations. To date, however, no many studies have been reported on stress levels, immune function and interventions in Korean students undergoing their first clinical nursing rotation. It was proposed that nursing students during their first clinical rotation experience increase in stress because of the novelty of the situation and their lack of clinical knowledge. It was also hypothesized that biofeedback and progressive relaxation, methods of self-regulation of involuntary autonomic nervous system responses, would reduce the stress response. The purpose of this study is to test the effectiveness of progressive muscle laxation using biofeedback The effectiveness of the experimental methods was tested by measuring the degree of symptoms of stress (SOS) and the values of ephinephrine, pulse rate, blood pressure and natural killer cells. The subjects of this study were thirty nursing students divided into two groups: experimental group was progressive muscle relaxation group using biofeedback and control group. This study was conducted for 8 weeks of clinical practice. Biofeedback training was done by software developed by J&J company (1-410 form for progressive muscle training). Progressive muscle relaxation training according to Jacobson's Theory was done by messaged word from biofeedback. The data was analyzed using Chronbach' ${\alpha}$ and t-test of the SPSS program and the significance level of statistics was 5%. The results of the study were : 1) The progressive muscle relaxation training using biofeedback was effective for the reduction of symptoms of stress(t=-4.248, p<.001) under clinical practice stress conditions. 2) The progressive muscle relaxation training using biofeedback was not effective for the values of epinephrine(t=-1.294, p=.206). 3) The progressive muscle relaxation training using biofeedback was effective for the reduction of systolic blood pressure (t=-2.757, p=.01). 4) The progressive muscle relaxation training using biofeedback was effective for the reduction of diastolic blood pressure (p=-2.032, 0=.05). 5) The progressive muscle relaxation training using biofeedback was not effective for the reduction of pulse rate(t=-15, p=.988). 6) The progressive muscle relaxation training using biofeedback was effective for the maintenance of natural killer cells (t=2.381, p=02). The first clinical rotation for student nurses is a stressful experience as seen by the rise in the SOS in the control group. Biofeedback using progressive muscle relaxation were effective in preventing the rise of symptoms of stress and the blood pressure means when comparing the pre to post clinical experience, The mean natural killer cell count was depressed in the control group but not significantly different in the experimental groups, It is proposed here that stress via the hypothalamic - pituitary - adrenal axis suppressed the NK cell count whereas the relaxation methods prevented the rise in stress and the resulting immune depression. We recommend relaxation techniques using biofeedback as a health promotion technique to reduce psychological stress. In summary. the progressive muscle relaxation training using biofeedback was effective for the reduction of symptoms of stress under clinical practice stress conditions.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회B
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• pp.2154-2159
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• 2007

The potential of using a double-faced wall stagnation flow burner in mass production of carbon nanotubes was evaluated experimentally and computationally. With nitrogen-diluted premixed ethylene-air flames established on the Nickel-coated stainless steel double-faced wall, the propensities of carbon nanotube formation were experimentally determined using SEM and FE-TEM images and Raman spectroscopy, while the flame structure was computationally predicted using a 3-dimensional CFD code with a reduced reaction mechanism. The uniformity and yields of synthesized carbon nanotubes were evaluated in terms of the flame stretch rates. Results show substantial increase of area on the wall surface where uniform carbon nanotubes are synthesized with using the double-faced wall stagnation flow burner due to enhanced uniformity of temperature distribution along the wall surface and support the potential of using a double-faced wall stagnation flow burner in mass production of carbon nanotubes.

• 치과방사선
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• 제22권1호
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• pp.128-136
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• 1992

This study was undertakened to investigate the change of image characteristics on dental films according to the process of using time of processing solution in automatic processor. Base + fog density, film density and subject contrast were measured with the digital densitometer, the pH of developing and fixing solution were measured with Digital pH / ION Meter. The following results were obtained: 1. Base + fog density was increased with the process of using time of the processing solution and was over the maximum permissible base + fog density 0.25 from the 3rd day. 2. Film density was increased with the process of using time of the processing solution. 3. Subject contrast was decreased with the process of using time of the processing solution. 4. The pH of the developing solution was decreased with the process of using time, the pH of the fixing solution was increased.

• 제어로봇시스템학회논문지
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• 제19권3호
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• pp.240-247
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• 2013

This paper proposes an optimal three-dimensional coordinate implementation of the vision sensor using two CCD cameras. The PBVS (Position based visual servoing) is implemented using the positional information obtained from images. Stereo vision by PBVS method that has enhanced every frame using calibration parameters is effective in the distance calculation. The IBVS (Image based visual servoing) is also implemented using the difference between reference and obtained images. Stereo vision by IBVS method calculates the distance using rotation angle of motors that correspond eyes and neck without enhanced images. The PBVS method is compared with the IBVS method in terms of advantages, disadvantages, computing time, and performances. Finally, the IBVS method is applied for the dual arm manipulator on the mobile inverted pendulum. The autonomous mobile inverted pendulum is successfully demonstrated using the center of the manipulator's mass.

• 한국농공학회논문집
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• 제56권4호
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• pp.29-39
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• 2014

In this study, we performed a non-stationary frequency analysis using a power model and the model was applied for Seoul, Daegu, Daejeon, Mokpo sites in Korea to estimate the probable precipitation amount at the target years (2020, 2050, 2080). We used the annual maximum precipitation of 24 hours duration of precipitation using data from 1973 to 2009. We compared results to that of non-stationary analyses using the linear and logistic regression. The probable precipitation amounts using linear regression showed very large increase in the long term projection, while the logistic regression resulted in similar amounts for different target years because the logistic function converges before 2020. But the probable precipitation amount for the target years using a power model showed reasonable results suggesting that power model be able to reflect the increase of hydrologic extremes reasonably well.

• ETRI Journal
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• 제29권2호
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• pp.189-200
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• 2007

This paper addresses the localization and navigation problem in the movement of service robots by using invisible two dimensional barcodes on the floor. Compared with other methods using natural or artificial landmarks, the proposed localization method has great advantages in cost and appearance since the location of the robot is perfectly known using the barcode information after mapping is finished. We also propose a navigation algorithm which uses a topological structure. For the topological information, we define nodes and edges which are suitable for indoor navigation, especially for large area having multiple rooms, many walls, and many static obstacles. The proposed algorithm also has the advantage that errors which occur in each node are mutually independent and can be compensated exactly after some navigation using barcodes. Simulation and experimental results were performed to verify the algorithm in the barcode environment, showing excellent performance results. After mapping, it is also possible to solve the kidnapped robot problem and to generate paths using topological information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• 한국컴퓨터정보학회논문지
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• 제22권2호
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• pp.21-27
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• 2017

In this paper, we propose a pupil detection method using PCA(principal component analysis) and Hough transform. To reduce error to detect eyebrows as pupil, eyebrows are detected using projection function in eye region and eye region is set to not include the eyebrows. In the eye region, pupil candidates are detected using rank order filter. False candidates are removed by using symmetry. The pupil candidates are grouped into pairs based on geometric constraints. A similarity measure is obtained for two eye of each pair using PCA and hough transform, we select a pair with the smallest similarity measure as final two pupils. The experiments have been performed for 1000 images of the BioID face database. The results show that it achieves the higher detection rate than existing method.

• 한국전기전자재료학회논문지
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• 제20권1호
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• pp.65-73
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• 2007

Pattern classification of single and multiple discharge sources was applied using a wavelet image signal method in which a feature extraction was applied using a hidden sub-image. A feature extracting method that used vertical and horizontal images using an MSD method was applied to an averaging process for the scale of pulses for the phase. A feature extracting process for the preprocessing of the input of a neural network was performed using an inverse transformation of the horizontal, vertical, and diagonal sub-images. A back propagation algorithm in a neural network was used to classify defective signals. An algorithm for wavelet image processing was developed. In addition, the defective signal was classified using the extracted value that was quantified for the input of a neural network.

• 전자공학회논문지B
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• 제31B권1호
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• pp.81-87
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• 1994

This paper describes the recognition of the printed Hanguel(Korean Character) using Neural Network. In this study, Neural network is used in only specific classification. Hanguel is classified globally by using template matching. Neural network is learned using the segmented grapheme. The grapheme of Hanguel is segmented using the structural method. Neural network is constructed, which is corresponded to the kind and the shape of graphemes. Each neural network is multi layer perceptron. The learning algorithm is the modified error back propagation using descending epsilon method. With five test character sets, the recognition rate of 94.95% is obtained.