• PNF and Movement
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• 제21권1호
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• pp.129-137
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• 2023

Purpose: The physical therapy diagnosis process requires high-level background knowledge, the ability to obtain added information from patients, accurate examination skills, and a framework for transforming thoughts into a diagnostic decision. Thus, the physical therapy diagnostic process is highly complicated and difficult work. To function as autonomous professionals, physical therapists must develop effective clinical diagnosis skills. As such, mobile application aids can help with accurate and scientific diagnoses. Therefore, this study aims to develop and evaluate the usability of a mobile application for physical therapy diagnoses. Methods: In this study, a diagnostic application was developed using App Inventor, the development environment was the Chrome web browser for Windows 10, and the mobile application was run on a Google Pixel 5. The developed application was evaluated for usability by 20 physical therapists with more than 5 years of clinical experience in the musculoskeletal physical therapy field, and a usability evaluation was conducted using a 5-point Likert scale for accuracy, convenience, satisfaction, and usability. The collected Likert scores were converted into percentages and analyzed as descriptive statistics. Results: The graphical user interface consisted of an initial screen with program guidance, 18 screens presenting the algorithm, and 12 screens presenting the estimated diagnosis based on the algorithm. As such, the usability evaluation of the developed application was as follows: accuracy 100%, convenience 90%, satisfaction 91%, and usability 88%. Conclusion: The newly developed mobile application for physical therapeutic diagnoses has a high accuracy, and it will aid in building an easy and reliable physical therapy diagnosis system.

• 영어어문교육
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• 제12권1호
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• pp.103-129
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• 2006

This paper presents a case study of the effectiveness of debate class in promoting speaking skills of advanced learners. The researcher adopted English debate techniques in an English speaking class during four-week teacher training program and investigated how teachers responded to the new technique. Forty-five middle and high school teachers participated in the study and classroom observation, pre-survey, post-survey, and focus group interviews were used as the major research methods. The teacher pre-survey results presented that teachers prefer a conversation class where they can directly acquire proper sentence patterns and speaking strategies rather than spend time in performing communicative events. The results of the focus group interview and post-survey confirmed that a debate class can meet this specific teachers' needs. Most teachers responded positively to the debate classes since: 1) debate techniques are relatively new ideas to Korean teachers; 2) debate techniques require speed and accuracy in speech; thus teachers could learn to present their ideas logically and efficiently in a limited time through repeated argument exercises. The study result implies that debate technique can be an effective vehicle in an EFL context to promote advanced learners' logical thinking skills and logical English sentence structures.

• 아동학회지
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• 제30권1호
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• pp.59-75
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• 2009

The purpose of this study was to verify the validity and reliability for the Test of Oral Reading and Comprehension Skill (Gardner, 2000) for Korean lower level elementary school children. Subjects were 122 first to third grade students, tested individually. The vocabulary and comprehension sub-tests of K-WISC III and the reading comprehension test of Basic Academic Skills Assessment (Kim, 2000) were used to verify concurrent validity. Internal reliability was determined by internal consistency coefficients. Results verified concurrent validity. Test scores differed significantly by grade level. Test reliability was also confirmed. In conclusion, the Oral Reading and Comprehension Skill Test (Gardner, 2000) is reliable and valid for examination of reading comprehension skills for Korean lower level elementary school children.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.159-168
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• 2022

No one denies the importance of online courses, which provide a very important alternative, especially for students who have jobs that prevent them from attending face-to-face in traditional classes; Engagement is one of the most important fundamental variables that indicate the course's success in achieving its objectives. Therefore, the current study aims to build a model using machine learning to predict student engagement in online courses. An online questionnaire was prepared and applied to the students of Jouf University in the Kingdom of Saudi Arabia, and data was obtained from the input variables in the questionnaire, which are: specialization, gender, academic year, skills, emotional aspects, participation, performance, and engagement in the online course as a dependent variable. Multiple regression was used to analyze the data using SPSS. Kegel was used to build the model as a machine learning technique. The results indicated that there is a positive correlation between the four variables (skills, emotional aspects, participation, and performance) and engagement in online courses. The model accuracy was very high 99.99%, This shows the model's ability to predict engagement in the light of the input variables.

• International Journal of Computer Science & Network Security
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• 제24권5호
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• pp.53-63
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• 2024

Alzheimer's disease is a brain disorder that worsens over time and affects millions of people around the world. It leads to a gradual deterioration in memory, thinking ability, and behavioral and social skills until the person loses his ability to adapt to society. Technological progress in medical imaging and the use of artificial intelligence, has provided the possibility of detecting Alzheimer's disease through medical images such as magnetic resonance imaging (MRI). However, Deep learning algorithms, especially convolutional neural networks (CNNs), have shown great success in analyzing medical images for disease diagnosis and classification. Where CNNs can recognize patterns and objects from images, which makes them ideally suited for this study. In this paper, we proposed to compare the performances of Alzheimer's disease detection by using two deep learning methods: You Only Look Once (YOLO), a CNN-enabled object recognition algorithm, and Visual Geometry Group (VGG16) which is a type of deep convolutional neural network primarily used for image classification. We will compare our results using these modern models Instead of using CNN only like the previous research. In addition, the results showed different levels of accuracy for the various versions of YOLO and the VGG16 model. YOLO v5 reached 56.4% accuracy at 50 epochs and 61.5% accuracy at 100 epochs. YOLO v8, which is for classification, reached 84% accuracy overall at 100 epochs. YOLO v9, which is for object detection overall accuracy of 84.6%. The VGG16 model reached 99% accuracy for training after 25 epochs but only 78% accuracy for testing. Hence, the best model overall is YOLO v9, with the highest overall accuracy of 86.1%.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.451-452
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• 2006

According to the demand of high productivity, the interest of manufacturing skills is growing in the industrial society. Especially the long spindle becomes important these days. The rotating accuracy of the spindle concerns the centrifugal force. In detail explaining, it is influenced by the speed of the spindle. In this study, we would show changes of the distance caused by a rotating speed of the spindle using a software, $ADAMS^{(R)}$. And because of the gravity of the spindle's mass, we would find the static droop of the long spindle.

• 한국어교육
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• 제25권1호
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• pp.29-52
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• 2014

The purpose of this paper is to suggest a discourse analysis activity that can be used in the stage after performing tasks in task-based Korean speaking class and show its pedagogical advantages. A discourse analysis activity is an metadiscourse activity in which learners speak what they have spoken. By analyzing discourse and performing tasks again, learners can enhance their fluency and accuracy, make their knowledges in target language more stable and extend them, and develop problem solving skills. Consequently, this facilitates learners' acquisition of Korean language. This paper reviewed theoretical background of proposing discourse analysis activity, suggested the pedagogical advantages of the analysis, and examined discourse analysis activity in Korean speaking class. And it included the discourse sample of learners in actual class.

• 디지털산업정보학회논문지
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• 제19권2호
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• pp.135-145
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• 2023

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.

• Spatial Information Research
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• 제11권4호
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• pp.327-340
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• 2003

공간데이터베이스의 품질평가는 공간데이터베이스의 특징에 따라 적절한 품질요소와 평가방법이 적용되어야 한다. 본 연구에서는 공간데이터베이스의 하나인 토지데이터베이스에 대한 구체적인 품질평가 방안을 제시하는데 목적을 두고 있다. 이를 위하여 토지데이터베이스를 구성하는 지형데이터베이스, 지적데이터베이스, 용도지역지구 데이터베이스의 구축 단계별 품질요소를 선정하고, 선정된 품질요소에 대하여 평가방법을 제시하였다. 토지데이터베이스의 품질요소는 위치정확성, 속성정확성, 일관성, 완결성, 시간정확성, 신뢰성, 이력 등이며, 다양한 통계적 및 수학적 방법들을 검토하여 각 품질요소의 객관적인 측정방법을 제안하였다.

• 대한조선학회논문집
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• 제53권4호
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• pp.275-281
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• 2016

One of the most important things for quality to meet ship-production schedule is an accuracy control. A ship is assembled by welding through whole production process, so it is important that loss by correction will not happen as much as possible by using some engineering skills like reverse design, reverse setting and margin for thermal shrinkage. These efforts are a quite effective in fabrication stages, but not in erection stages. If a ship block which consists of common steel is exposed to directional solar radiation, its dimensional accuracy will change high as time by its thermal expansion coefficient. Therefore, the measuring work would be often done at dawn or evening even with having a very accurate device. In this study, an FE analysis method is developed to solve this problem. It can change measured data affected by solar thermal distortion to ones not, even though ship-block is measured at an arbitrary time. It will use the time when measuring, the direction of block and the weather record by satellites. It is confirmed by a comparison between measured data of a ship-block and the result by suggested analysis method. Furthermore, a pre-processing system is also developed for fast application of the suggested analysis method.