• Asian Pacific Journal of Cancer Prevention
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• v.14 no.6
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• pp.3743-3746
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• 2013

Background: Of patients with non small cell lung cancer (NSCLC), around one third are locally advanced at the time of diagnosis. Because only a proprotion of stage III patients can be cured by surgery, in order to improve the outcomes, sequential or concurrent chemoradiation, or concurrent chemoradiation with induction or consolidation is offered to the patients with locally advanced NSCLC. Today, PET combined with computerized tomography (PET-CT) is accepted as the most sensitive technique for detecting mediastinal lymph node and extracranial metastases from NSCLC. We aimed to compare PET-CT and conventional staging procedures for decisions regarding curative treatment of locally advanced NSCLC. Materials and Methods: A total of 168 consecutive patients were included from Acibadem Kayseri Hospital, Acibadem Adana Hospital and Kayseri Research and Training Hospital in this study. Results: While the median PFS was $13.0{\pm}1.9$ months in the PET-CT group, it was only $6.0{\pm}0.9$ in the others (p<0.001). The median OS values were $20.5{\pm}15.6$ and $11.5{\pm}1.5$ months, respectively (p<0.001). Discussion: As a result, we found that staging with PET CT has better results in terms of survival staging. This superiority leads to survival advantage in patients with locally advanced NSCLC.

• Nutrition Research and Practice
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• v.5 no.3
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• pp.205-213
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• 2011

Exercise training (ET) and selenium (SEL) were evaluated either individually or in combination (COMBI) for their effects on expression of glucose (AMPK, PGC- $1{\alpha}$, GLUT-4) and lactate metabolic proteins (LDH, MCT-1, MCT-4, COX-IV) in heart and skeletal muscles in a rodent model (Goto-Kakisaki, GK) of diabetes. Forty GK rats either remained sedentary (SED), performed ET, received SEL, ($5\;{\mu}mol{\cdot}kg$ body $wt^{-1}{\cdot}day^{-1}$) or underwent both ET and SEL treatment for 6 wk. ET alone, SEL alone, or COMBI resulted in a significant lowering of lactate, glucose, and insulin levels as well as a reduction in HOMA-IR and AUC for glucose relative to SED. Additionally, ET alone, SEL alone, or COMBI increased glycogen content and citrate synthase (CS) activities in liver and muscles. However, their effects on glycogen content and CS activity were tissue-specific. In particular, ET alone, SEL alone, or COMBI induced upregulation of glucose (AMPK, PGC-la, GLUT-4) and lactate (LDH, MCT-1, MCT-4, COX-IV) metabolic proteins relative to SED. However, their effects on glucose and lactate metabolic proteins also appeared to be tissue-specific. It seemed that glucose and lactate metabolic protein expression was not further enhanced with COMBI compared to that of ET alone or SEL alone. These data suggest that ET alone or SEL alone or COMBI represent a practical strategy for ameliorating aberrant expression of glucose and lactate metabolic proteins in diabetic GK rats.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.198-208
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• 2010

The purpose of this study was examined the effects of the K-MBSR program according to the length of the training period. Three versions of the K-MBSR program were compared: a 4-week program composed of formal meditation an 8-week program with official meditation and a 12-week program that combined the 4-week and 8-week programs. The 4-week K-MBSR program did not result in a significant decrease in depression, anxiety, or negative emotion. The 8-week and 12-week K-MBSR programs decreased the score of depression significantly, and the effect continued until 8 months. The effect of the 12-week K-MBSR program was greaterthan the effect of the 8-week program, but not significantly. The result of this study indicates that the effect of the 4-week K-MBSR program appears insignificant. The effects of the 8-week and 12-week programs are almost the same, but the effect of 12-week K-MBSR program showed a slightly greater effect in the post-test and 8-month test. The findings were discussed the effect of k-MBSR Program and recommendations for further research.

• Safety and Health at Work
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• v.9 no.2
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• pp.172-179
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• 2018

Background: Insufficient training in infection control and occupational health among healthcare workers (HCWs) in countries with high human immunodeficiency virus (HIV) and tuberculosis (TB) burdens requires attention. We examined the effectiveness of a 1-year Certificate Program in Occupational Health and Infection Control conducted in Free State Province, South Africa in an international partnership to empower HCWs to become change agents to promote workplace-based HIV and TB prevention. Methods: Questionnaires assessing reactions to the program and Knowledge, Attitudes, Skills, and Practices were collected pre-, mid-, and postprogram. Individual interviews, group project evaluations, and participant observation were also conducted. Quantitative data were analyzed using Wilcoxon signed-rank test. Qualitative data were thematically coded and analyzed using the Kirkpatrick framework. Results: Participants recruited (n = 32) were mostly female (81%) and nurses (56%). Pre-to-post-program mean scores improved in knowledge (+12%, p = 0.002) and skills/practices (+14%, p = 0.002). Preprogram attitude scores were high but did not change. Participants felt empowered and demonstrated attitudinal improvements regarding HIV, TB, infection control, and occupational health. Successful projects were indeed implemented. However, participants encountered considerable difficulties in trying to sustain improvement, due largely to lack of pre-existing knowledge and experience, combined with inadequate staffing and insufficient management support. Conclusion: Training is essential to strengthen HCWs' occupational health and infection control knowledge, attitudes, skills, and practices, and workplace-based training programs such as this can yield impressive results. However, the considerable mentorship resources required for such programs and the substantial infrastructural supports needed for implementation and sustainability of improvements in settings without pre-existing experience in such endeavors should not be underestimated.

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.223-229
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• 2019

The number of knee-related disease patients and knee joint surgeries is steadily increasing every year, and for knee rehabilitation training for these knee joint patients, it is necessary to strengthen the muscle of vastus medialis and quadriceps femoris. However, because of the cost and time-consuming difficulties of receiving regular hospital treatment in the course of knee rehabilitation, we developed knee exoskeleton using rapid prototype for knee rehabilitation with feedback from the electromyogram (EMG) and inertia motion unit (IMU) sensor. The modules was built on the basis of EMG and an IMU sensor applied complementary filter, measuring muscle activity in the vastus medialis and the range of joint operation of the knee, and then performing the game based on this measurement. The IMU sensor performed up to 97.2% accuracy in experiments with ten subjects. The functional game contents consisted of an exergaming platform based on EMG and IMU for the real-time monitoring and performance assessment of personalized isometric and isotonic exercises. This study combined EMG and IMU-based functional game with knee rehabilitation training to enable voluntary rehabilitation training by providing immediate feedback to patients through biometric information, thereby enhancing muscle strength efficiency of rehabilitation.

• Journal of Power Electronics
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• v.17 no.4
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• pp.1014-1026
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• 2017

The traditional fault diagnosis method for photovoltaic (PV) inverters has a difficult time meeting the requirements of the current complex systems. Its main weakness lies in the study of nonlinear systems. In addition, its diagnosis time is long and its accuracy is low. To solve these problems, a hidden Markov model (HMM) is used that has unique advantages in terms of its training model and its recognition for diagnosing faults. However, the initial value of the HMM has a great influence on the model, and it is possible to achieve a local minimum in the training process. Therefore, a genetic algorithm is used to optimize the initial value and to achieve global optimization. In this paper, the HMM is combined with a genetic algorithm (GHMM) for PV inverter fault diagnosis. First Matlab is used to implement the genetic algorithm and to determine the optimal HMM initial value. Then a Baum-Welch algorithm is used for iterative training. Finally, a Viterbi algorithm is used for fault identification. Experimental results show that the correct PV inverter fault recognition rate by the HMM is about 10% higher than that of traditional methods. Using the GHMM, the correct recognition rate is further increased by approximately 13%, and the diagnosis time is greatly reduced. Therefore, the GHMM is faster and more accurate in diagnosing PV inverter faults.

• Structural Engineering and Mechanics
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• v.77 no.1
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• pp.47-56
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• 2021

This paper deals with damage detection using a Gapped Smoothing Method (GSM) combined with deep learning. Convolutional Neural Network (CNN) is a model of deep learning. CNN has an input layer, an output layer, and a number of hidden layers that consist of convolutional layers. The input layer is a tensor with shape (number of images) × (image width) × (image height) × (image depth). An activation function is applied each time to this tensor passing through a hidden layer and the last layer is the fully connected layer. After the fully connected layer, the output layer, which is the final layer, is predicted by CNN. In this paper, a complete machine learning system is introduced. The training data was taken from a Finite Element (FE) model. The input images are the contour plots of curvature gapped smooth damage index. A free-free beam is used as a case study. In the first step, the FE model of the beam was used to generate data. The collected data were then divided into two parts, i.e. 70% for training and 30% for validation. In the second step, the proposed CNN was trained using training data and then validated using available data. Furthermore, a vibration experiment on steel damaged beam in free-free support condition was carried out in the laboratory to test the method. A total number of 15 accelerometers were set up to measure the mode shapes and calculate the curvature gapped smooth of the damaged beam. Two scenarios were introduced with different severities of the damage. The results showed that the trained CNN was successful in detecting the location as well as the severity of the damage in the experimental damaged beam.

• Journal of Korean Physical Therapy Science
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• v.28 no.3
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• pp.11-29
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• 2021

Background: The purpose of this study is to investigate the effects of virtual reality on gait, balance, and upper extremity functions compared to other independent variables or no variables. Additionally, the possibility of virtual reality for stroke patients was discussed. Design: Meta-analysis. Methods: The search for this study was a search term that combined stroke, virtual reality, and training, and the electronic search was conducted through EMBASE, MEDLINE, and Cochrane Library. As a result of the search, 21 studies satisfying the selection criteria of the target study were confirmed as the final analysis target. This study consisted of 21 randomized experimental studies and 21 randomized controlled trials, and the total number of participants was 642. [Experimental group (n=314), control group (n=328); total 642]. As a result of the study, upper extremity function was assessed using a box and block test, a modified Ashworth scale, and a scale including range of motion. The balance was evaluated by the berg balance scale. Gait was a Timed Up and Go test (TUG), stride length, and gait function. Scales including a walking rate scale were evaluated. The effect size for the intervention of the analytical study was meta-analyzed with the RevMan 5.3.3 program of the Cochrane library. Results: The results of the study showed that the function of walking was statistically significant. Balance showed statistically significant results. The upper extremity function showed no statistically significant results. Conclusion: Through this rehabilitation treatment by applying virtual reality environment to the rehabilitation of stroke patients in the future can be proposed as an effective intervention method for the balance and gait function of stroke patients.

• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.207-213
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• 2007

In this research, we propose an efficient Speech/Music discrimination method that uses spectrum analysis and neural network. The proposed method extracts the duration feature parameter(MSDF) from a spectral peak track by analyzing the spectrum, and it was used as a feature for Speech/Music discriminator combined with the MFSC. The neural network was used as a Speech/Music discriminator, and we have reformed various experiments to evaluate the proposed method according to the training pattern selection, size and neural network architecture. From the results of Speech/Music discrimination, we found performance improvement and stability according to the training pattern selection and model composition in comparison to previous method. The MSDF and MFSC are used as a feature parameter which is over 50 seconds of training pattern, a discrimination rate of 94.97% for speech and 92.38% for music. Finally, we have achieved performance improvement 1.25% for speech and 1.69% for music compares to the use of MFSC.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.4
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• pp.437-448
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• 2015

In this paper, smartphone based measuring device was developed by integration of several sonsors such as moving, temperature, pulsation, respiration and hearing and sever/client programs was developed for the data acquisition and communication between smartphone and server computer. Then, the concept of CSI(combined safety index) was proposed for the comprehensive diagnositcs of workers status. For the validation of the proposed concept, the real data was acquired by boarding at training ship of korea maritime and ocean university. The acquired data was analyzed with the stochastical method of regressionn, then the meaningful result was driven that could explain the relation between the risky situation and the measured chronical data.