• Smart Structures and Systems
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• v.13 no.6
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• pp.1041-1063
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• 2014

This work introduces a two-module robotic pipe inspection system with ultrasonic NDE device to evaluate the integrity of pipe structures. The proposed robotic platform has high mobility. The two module mobile robot platform overcomes pipe obstacle structures such as elbow, or T-branch joints by cooperative maneuvers. Also, it can climb up the straight pipeline at a fast speed due to the wheel driven mechanism. For inspection of pipe structure, SH-waves generated by EMAT are applied with additional signal processing methods. A wavelet transform is implemented to extract a meaningful and specific signal from the superposed SH-wave signals. Intensity ratio which is normalized the defect signals intensity by the maximum intensity of directly transmitted signals in the wavelet transforms spectrum is applied to evaluate defects quantitatively. It is experimentally verified that the robotic ultrasonic inspection system with EMAT is capable of non-destructive inspection and evaluation of defects in pipe structure successfully by applying signal processing method based on wavelet transform.

• Journal of the Ergonomics Society of Korea
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• v.32 no.6
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• pp.549-555
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• 2013

Objective: The purpose of this study was to compare the performance of drilling on the ceiling in three different postures (standing, standing on the ladder and supine on the height adjusted board) and the subjective responses of perceived discomfort after the drilling. Background: Overhead work has been identified as a major occupational risk factor and has been a main research subject. Method: Ten young participants drilled 20 holes at the pre-marked places on the ceiling in three different postures. The drilling duration, resting and drilling heart rate were measured. The levels of perceived discomfort at neck, shoulder, elbow, hand and overall body were asked at the end of each task. Results: The working posture affected the heart rate after the drilling. Perceived discomfort in the neck decreased significantly in supine compared to drilling on the ladder. Conclusion: The results of this study suggest that drilling in supine can be an alternative way to reduce the drilling heart rate and the level of perceived discomfort in the neck without sacrificing the productivity. Application: The results of this study would be considered when drilling on the ceiling is required in construction workers.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.11 no.3
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• pp.281-291
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• 2004

Purpose: This study was done to investigate the effects of a rehabilitation program including Koryo Hand-Acupuncture on physical function, self-esteem, and quality of life of post-stroke elderly patients. Method: A nonequivalent control group pre-post test research design was used. Participants in the study were 44 post-stroke elderly people (22 in an experimental group, 22 in a control group) enrolled in a social welfare center and a hospital in K city. Data were collected from April 6 to August 20, 2004. The program consisted of Koryo Hand-Acupuncture, ROM exercise, health education and supportive care. The analyses were carried using frequencies, percentages, $x^2$-test, Fisher exact and t-test with SPSS 10.0. Results: The patients in the experimental group, who took part in the 10-weeks rehabilitation program including Koryo Hand-Acupuncture, had significant increases in shoulder joint flexion, shoulder joint abduction, elbow joint flexion, hip joint flexion, knee joint flexion, knee joint extension, flexibility, self-esteem and quality of life as compared to the control group. Conclusion: These results suggest that a rehabilitation program including Koryo Hand-Acupuncture may be utilized as an effective nursing program to improve physical function, self-esteem and quality of life for post-stroke elderly patients.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.6 s.261
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• pp.710-717
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• 2007

This paper presents plastic limit loads and approximate J-integral estimates for circumferential part-through surface crack at the interface between elbows and pipes. Based on finite element limit analyses using elastic-perfectly plastic materials, plastic limit moments under in-plane bending are obtained and it is found that they are similar those for circumferential part-through surface cracks in the center of elbow. Based on present FE results, closed-form limit load solutions are proposed. Welds are not explicitly considered and all materials are assumed to be homogeneous. And the method to estimate the elastic-plastic J-integral for circumferential part-through surface cracks at the interface between elbows and straight pipes is proposed based on the reference stress approach, which was compared with corresponding solutions fur straight pipes.

• Korean Journal of Applied Biomechanics
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• v.30 no.2
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• pp.165-172
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• 2020

Objective: The purpose of this study was to provide quantitative and objective data of throwing movement in baseball catcher through biomechanical analysis. Method: Eight high school baseball catchers (age: 17.3±0.7 yrs, height: 175.3±4.5 cm, weight: 82.5±9.0 kg, Career: 7.4±2.1 yrs) participated and 3-dimentional motion capture system and electromyography (EMG) were used in this study. Results: The maximum center of mass position displacement was observed in forward direction. The linear velocity magnitude of the upper extremity segments were showed as "wrist>elbow>shoulder" which is indicative of kinematic chain. For kinetic EMG data, we also observed the greater muscle activation in the left brachioradial and erector spine muscles muscle that during throwing movement. Conclusion: We expect that biomechanical data from this study will provide important training implications to baseball coaches and trainers in order to effectively train their baseball catchers.

• Nuclear Engineering and Technology
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• v.52 no.5
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• pp.984-994
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• 2020

It is reported that about 20% of accidents at nuclear power plants in Korea and abroad are caused by human error. One of the main factors contributing to human error is fatigue, so it is necessary to prevent human errors that may occur when the task is performed in an improper state by grasping the status of the operator in advance. In this study, we propose a method of evaluating operator's fitness-for-duty (FFD) using various parameters including eye movement data, subjective fatigue ratings, and operator's performance. Parameters for evaluating FFD were selected through a literature survey. We performed experiments that test subjects who felt various levels of fatigue monitor information of indicators and diagnose a system malfunction. In order to find meaningful characteristics in measured data consisting of various parameters, hierarchical clustering analysis, an unsupervised machine-learning technique, is used. The characteristics of each cluster were analyzed; fitness-for-duty of each cluster was evaluated. The appropriateness of the number of clusters obtained through clustering analysis was evaluated using both the Elbow and Silhouette methods. Finally, it was statistically shown that the suggested methodology for evaluating FFD does not generate additional fatigue in subjects. Relevance to industry: The methodology for evaluating an operator's fitness for duty in advance is proposed, and it can prevent human errors that might be caused by inappropriate condition in nuclear industries.

• Advances in robotics research
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• v.2 no.3
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• pp.237-245
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• 2018

This study evaluates the efficacy of a class robust control scheme namely active force control in performing a joint based trajectory tracking of an upper limb exoskeleton in rehabilitating the elbow joint. The plant of the exoskeleton system is obtained via system identification method whilst the PD gains were tuned heuristically. The estimated inertial parameter that enables the AFC disturbance rejection effect is attained by means of a non-nature based metaheuristic optimisation technique known as simulated Kalman filter (SKF). It was demonstrated from the present investigation that the proposed PDAFC scheme outperformed the classical PD algorithm in tracking the prescribed trajectory both in the presence and without the presence of disturbance attributed by the mannequin limb weights (1 kg and 1.5 kg) that mimics the weight of actual human limb weight. Therefore, it is apparent from the results obtained from the present study that the proposed control scheme, i.e., PDAFC is suitable for the application of exoskeleton for stroke rehabilitation.

• Nuclear Engineering and Technology
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• v.51 no.2
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• pp.561-572
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• 2019

In the design criterion for the nuclear power plant piping system, the limit state of the piping against an earthquake is assumed to be plastic collapse. The failure of a common piping system, however, means the leakage caused by the cracks. Therefore, for the seismic fragility analysis of a nuclear power plant, a method capable of quantitatively expressing the failure of an actual piping system is required. In this study, it was conducted to propose a quantitative failure criterion for piping system, which is required for the seismic fragility analysis of nuclear power plants against critical accidents. The in-plane cyclic loading test was conducted to propose a quantitative failure criterion for steel pipe elbows in the nuclear power plant piping system. Nonlinear analysis was conducted using a finite element model, and the results were compared with the test results to verify the effectiveness of the finite element model. The collapse load point derived from the experiment and analysis results and the damage index based on the stress-strain relationship were defined as failure criteria, and seismic fragility analysis was conducted for the piping system of the BNL (Brookhaven National Laboratory) - NRC (Nuclear Regulatory Commission) benchmark model.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.45-52
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• 2022

With the development of artificial intelligence analysis methods, especially machine learning, various fields are widely expanding their application ranges. However, in the case of classical music, there still remain some difficulties in applying machine learning techniques. Genre classification or music recommendation systems generated by deep learning algorithms are actively used in general music, but not in classical music. In this paper, we attempted to classify opera among classical music. To this end, an experiment was conducted to determine which criteria are most suitable among, composer, period of composition, and emotional atmosphere, which are the basic features of music. To generate emotional labels, we adopted zero-shot classification with four basic emotions, 'happiness', 'sadness', 'anger', and 'fear.' After embedding the opera libretto with the doc2vec processing model, the optimal number of clusters is computed based on the result of the elbow method. Decided four centroids are then adopted in k-means clustering to classify unsupervised libretto datasets. We were able to get optimized clustering based on the result of adjusted rand index scores. With these results, we compared them with notated variables of music. As a result, it was confirmed that the four clusterings calculated by machine after training were most similar to the grouping result by period. Additionally, we were able to verify that the emotional similarity between composer and period did not appear significantly. At the end of the study, by knowing the period is the right criteria, we hope that it makes easier for music listeners to find music that suits their tastes.

• Journal of Distribution Science
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• v.20 no.6
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• pp.1-10
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• 2022

Purpose: This research proposes a new modified Recency-Frequency-Monetary (RFM) model by extending the model with spatial analysis for supporting decision-makers in discovering the promotional target market. Research design, data and methodology: This quantitative research utilizes data-mining techniques and the RFM model to cluster a university's provider schools. The RFM model was modified by adapting its variables to the university's marketing context and adding a district's potential (D) variable based on heatmap analysis using Geographic Information System (GIS) and K-means clustering. The K-prototype algorithm and the Elbow method were applied to find provider school clusters using the proposed RFM-D model. After profiling the clusters, the target segment was assigned. The model was validated using empirical data from an Indonesian university, and its performance was compared to the Customer Lifetime Value (CLV)-based RFM utilizing accuracy, precision, recall, and F1-score metrics. Results: This research identified five clusters. The target segment was chosen from the highest-value and high-value clusters that comprised 17.80% of provider schools but can contribute 75.77% of students. Conclusions: The proposed model recommended more targeted schools in higher-potential districts and predicted the target segment with 0.99 accuracies, outperforming the CLV-based model. The empirical findings help university management determine the promotion location and allocate resources for promotional information distribution and student recruitment.