• 대한가정학회지
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• 제50권8호
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• pp.79-95
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• 2012

The purpose of this study is to seek improvement in clothing life education through a development and application of the clothing life education program for middle schools based on the education and experience in arts & culture. On the basis of art & culture education as well as, Dewey's experience, the clothing life area education program was designed and developed for the 2nd year students in the middle school. This program was applied to 350 students of 9 2nd year classes in M middle school during the 17 periods of clothing life area classes, beginning from May 23rd, 2011 and lasting to September 30th, 2011. The leaner-evaluation was performed in terms of the level of learning interest and academic achievement. To measure the level of academic achievement, a mind-map evaluation was performed and a learning effect survey, which evaluates the level of achievement of learning objectives, was carried out. For the purpose of class observation, classes were filmed and analyzed. Characteristics of a class were recorded on a teacher's diary and was used to support the qualitative evaluation. According to the results, the education program is analyzed as being helpful and useful in student understanding of fiber, textile and, clothes, which are materials and outcomes of culture and art; moreover, they have a historical, cultural and artistic value in themselves. It is also analyzed as being helpful for the development of student aesthetic sensibility and emotion, for the construction of meaningful experience through a learning process, for the improvement of learning interest and the level of academic achievement, and for the positive recognition of the learning effect.

• 한국콘텐츠학회논문지
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• 제20권1호
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• pp.117-126
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• 2020

이 연구는 온라인 토론활동에 대한 학습분석 기반 대시보드 유형이 학습자들의 그룹토론에 미치는 영향을 탐색하기 위해 수행되었다. 대학생 51명을 대상으로 참여도와 상호작용 대시보드를 제공한 집단과 토론주제와 메시지유형 대시보드를 제공한 집단으로 나누어 실험연구를 실시하였다. 먼저 온라인 토론활동에 영향을 미칠 수 있는 컴퓨터 쓰기에 대한 태도, 자기성찰 동기 수준에 대한 사전검사를 실시하였다. 이후 온라인 그룹토론 3회를 실시하였고, 참여도와 상호작용 데이터는 온라인 토론 시스템을 통해 자동으로 수집하였으며, 사후검사를 통해 학습성과 데이터를 수집하였다. 연구 결과 토론주제와 메시지유형 대시보드를 제공 받은 집단 B의 참여도 수준(M=47.56, SD=2.37)이 참여도와 상호작용 대시보드를 제공받은 집단 A의 참여도 수준(M=38.13, SD=2.21) 보다 유의하게 높은 것으로 나타났다. 반면 대시보드 유형이 상호작용과 학습성과에는 영향을 주지 않은 것으로 나타났다. 연구 결과를 종합해 볼 때 참여도와 상호작용에 대한 정보만 제공받은 집단보다 토론내용에 대한 질적 정보가 포함된 토론주제와 메시지유형 대시보드를 제공받은 집단이 토론에 대한 동기부여를 통해 참여도가 높게 나타난 것으로 해석할 수 있다. 이 연구에서는 학습자 특성변인을 고려하지 않고 대시보드 유형에 따른 효과만 검증하고자 하였는데, 선행연구에 의하면, 학습자 특성이 대시보드 활용에 영향을 줄 수 있으므로 추후 연구에서는 학습자 특성에 따른 대시보드 효과에 관한 연구를 수행할 것을 제안한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2022년도 추계학술발표대회
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• pp.478-480
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• 2022

This paper studies human activity image classification using deep transfer learning techniques focused on the inception convolutional neural networks (InceptionV3) model. For this, we used UFC-101 public datasets containing a group of students' behaviors in mathematics classrooms at a school in Thailand. The video dataset contains Play Sitar, Tai Chi, Walking with Dog, and Student Study (our dataset) classes. The experiment was conducted in three phases. First, it extracts an image frame from the video, and a tag is labeled on the frame. Second, it loads the dataset into the inception V3 with transfer learning for image classification of four classes. Lastly, we evaluate the model's accuracy using precision, recall, F1-Score, and confusion matrix. The outcomes of the classifications for the public and our dataset are 1) Play Sitar (precision = 1.0, recall = 1.0, F1 = 1.0), 2), Tai Chi (precision = 1.0, recall = 1.0, F1 = 1.0), 3) Walking with Dog (precision = 1.0, recall = 1.0, F1 = 1.0), and 4) Student Study (precision = 1.0, recall = 1.0, F1 = 1.0), respectively. The results show that the overall accuracy of the classification rate is 100% which states the model is more powerful for learning UCF-101 and our dataset with higher accuracy.

• PNF and Movement
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• 제16권1호
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• pp.105-113
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• 2018

Purpose: The aim of this study was to explore the effects of dynamic balance training on pain, physical function, and dynamic balance in individuals with knee osteoarthritis. Methods: Fourteen patients with knee osteoarthritis participated in this study. The patients were randomly assigned to two groups: an experimental group (n=7) or a control group (n=7). All the patients took part in a lower extremity strength program for 30 min. In addition, the experimental group participated in a 30-min dynamic balance program. Both groups performed the program five times a week for 3 weeks. Outcomes, including the numeric rating scale (NRS), Western Ontario and MacMaster Universities Arthritis Index (WOMAC), and Community Balance and Mobility Scale (CB&M), were measured at baseline and after 3 weeks. Results: Both groups showed pre-to-post intervention improvements on all outcome measures (p<0.05). The experimental group showed a significant improvement in WOMAC (p = 0.00; Z = -2.82) and CB&M (p = 0.03; Z = -2.20) scores after the intervention as compared with those of the control group. Conclusion: The results revealed that dynamic balance training improved physical function, as well as balance ability, in patients with knee osteoarthritis as compared with that of a control group with no balance training.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 추계학술발표대회
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• pp.581-584
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• 2019

Food consumption is growing worldwide every year owing to a growing population. Hence, the increasing population needs the production of sufficient and good quality food products. Strawberry is one of the world's most famous fruit. To obtain the highest strawberry output, we worked with three strawberry varieties supplied with three kinds of nutrient water in a greenhouse and with the outcome of the strawberry production, the highest yielding strawberry variety is detected. This Study uses the nutrient water consumed every day by the highest yielding strawberry variety. The atmospheric temperature, humidity and CO2 levels within the greenhouse are identified and used for the prediction, since the water consumption by any plant depends primarily on weather conditions. Machine learning techniques show successful outcomes in a multitude of issues including time series and regression issues. In this study, daily nutrient water consumption of strawberry plants is predicted using machine learning algorithms is proposed. Four Machine learning algorithms are used such as Linear Regression (LR), K nearest neighbour (KNN), Support Vector Machine with Radial Kernel (SVM) and Gradient Boosting Machine (GBM). Gradient Boosting System produces the best results.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.681-684
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• 2021

In this paper, we study image clustering without labeling using machine learning techniques. We proposed an unsupervised machine learning technique to design an image clustering model that automatically categorizes images into groups. Our experiment focused on inception convolutional neural networks (inception V3) with k-mean methods to cluster images. For this, we collect the public datasets containing Food-K5, Flowers, Handwritten Digit, Cats-dogs, and our dataset Rice Germination, and the owner dataset Palm print. Our experiment can expand into three-part; First, format all the images to un-label and move to whole datasets. Second, load dataset into the inception V3 extraction image features and transferred to the k-mean cluster group hold on six classes. Lastly, evaluate modeling accuracy using the confusion matrix base on precision, recall, F1 to analyze. In this our methods, we can get the results as 1) Handwritten Digit (precision = 1.000, recall = 1.000, F1 = 1.00), 2) Food-K5 (precision = 0.975, recall = 0.945, F1 = 0.96), 3) Palm print (precision = 1.000, recall = 0.999, F1 = 1.00), 4) Cats-dogs (precision = 0.997, recall = 0.475, F1 = 0.64), 5) Flowers (precision = 0.610, recall = 0.982, F1 = 0.75), and our dataset 6) Rice Germination (precision = 0.997, recall = 0.943, F1 = 0.97). Our experiment showed that modeling could get an accuracy rate of 0.8908; the outcomes state that the proposed model is strongest enough to differentiate the different images and classify them into clusters.

• Journal of Power Electronics
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• 제10권6호
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• pp.579-586
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• 2010

This paper presents the organisation and the technical structure of a remote controlled laboratory in the field of high dynamic drives and motion control. It is part of the PEMCWebLab project with the goal of providing students with practical experience on real systems in the field of power electronics and drives. The whole project is based on clear targets and leading ideas. A set of experiments can be remotely performed on a real system to stepwise identify a two axes positioning system and to design different cascaded control loops. Each single experiment is defined by its goals, the content of how to achieve them, and a verification of the results as well as the achieved learning outcomes. After a short description of the PEMCWebLab project, the structure of the remote control is presented together with the hardware applied. One important point is error handling as real machines and power electronics are applied. Finally, a selection of experiments is presented to show the graphical user interface and the sequence of the laboratory.

• Journal of Korean Neurosurgical Society
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• 제65권4호
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• pp.539-548
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• 2022

Objective : Although full-endoscopic lumbar interbody fusion (Endo-LIF) has been tried as the latest alternative technique to minimally invasive transforaminal lumbar interobody fusion (MIS-TLIF) since mid-2010, the evidence is still lacking. We compared the clinical outcome and safety of Endo-LIF to MIS-TLIF for lumbar degenerative disease. Methods : We systematically searched electronic databases, including PubMed, EMBASE, and Cochrane Library to find literature comparing Endo-LIF to MIS-TLIF. The results retrieved were last updated on December 11, 2020. The perioperative outcome included the operation time, blood loss, complication, and hospital stay. The clinical outcomes included Visual analog scale (VAS) of low back pain and leg pain and Oswestry disability index (ODI), and the radiological outcome included pseudoarthosis rate with 12-month minimum follow-up. Results : Four retrospective observational studies and one prospective observational study comprising 423 patients (183 Endo-LIF and 241 MIS-TLIF) were included, and the pooled data analysis revealed low heterogeneity between studies in our review. Baseline characteristics including age and sex were not different between the two groups. Operation time was significantly longer in Endo-LIF (mean difference [MD], 23.220 minutes; 95% confidence interval [CI], 10.669-35.771; p=0.001). However, Endo-LIF resulted in less perioperative blood loss (MD, -144.710 mL; 95% CI, 247.941-41.478; p=0.023). Although VAS back pain at final (MD, -0.120; p=0.586), leg pain within 2 weeks (MD, 0.005; p=0.293), VAS leg pain at final (MD, 0.099; p=0.099), ODI at final (MD, 0.141; p=0.093) were not different, VAS back pain within 2 weeks was more favorable in the Endo-LIF (MD, -1.538; 95% CI, -2.044 to -1.032; p<0.001). On the other hand, no statistically significant group difference in complication rate (relative risk [RR], 0.709; p=0.774), hospital stay (MD, -2.399; p=0.151), and pseudoarthrosis rate (RR, 1.284; p=0.736) were found. Conclusion : Relative to MIS-TLIF, immediate outcomes were favorable in Endo-LIF in terms of blood loss and immediate VAS back pain, although complication rate, mid-term clinical outcomes, and fusion rate were not different. However, the challenges for Endo-LIF include longer operation time which means a difficult learning curve and limited surgical indication which means patient selection bias. Larger-scale, well-designed study with long-term follow-up and randomized controlled trials are needed to confirm and update the results of this systematic review.

• Safety and Health at Work
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• 제9권4호
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• pp.381-387
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• 2018

Background: Physician behaviors that undermine a culture of safety have gained increasing attention as health-care organizations strive to create a culture of safety and reduce medical errors. We developed, implemented, and assessed a course to teach physicians skills regarding effective coping and interpersonal communication skills and present our results regarding outcomes. Methods: We examined a professional development program specifically designed to address unprofessional or distressed behaviors of physicians, and we evaluated the impact on burnout, quality of life, and emotional flooding scores of the physicians. Assessments of burnout, quality of life, and emotional flooding were assessed preintervention and postintervention. Results: Results demonstrated statistically significant reductions over time in physicians' emotional flooding and emotional exhaustion (EE). Specifically, using a Wilcoxon Signed-Rank test, results revealed that flooding scores at follow-up were statistically significantly lower than at baseline, V = 590, p < 0.05, and EE and personal accomplishment distributions were found to significantly deviate from normal as indicated by Shapiroe-Wilks tests (p < 0.05). A Wilcoxon signed-rank test indicated that EE scores were significantly higher at baseline compared to follow-up 1, V = 285, p < 0.05. Conclusion: We conclude that the physician participants who enrolled in the educational skills training program improved scores on emotional flooding and EE and that this may be indicative of improved skills related to their experiences and learning in the program. These improved skills in physicians may have a positive impact on the overall culture of safety in the health system setting.

• Structural Engineering and Mechanics
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• 제87권3호
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• pp.221-229
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• 2023

Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.