• Journal of the Korea Society of Computer and Information
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• v.18 no.10
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• pp.97-107
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• 2013

The latest programming paradigm has been mostly geared toward object-oriented programming and visual programming based on the object-oriented programming. However, object-oriented programming has a more difficult and complicated concept compared with that of existing structural programming technique; thus it has been very difficult to educate students in the IT-related department. This study designed and implemented a Java robot training kit in which the Java virtual machine is built so that it may enhance the desire and motivation of students for learning the object-oriented programming using the training kit which is possible to attach various input and output devices and to control a robot. The developed Java robot training kit is able to communicate with a computer through the USB interface, and it also enables learners to manufacture a robot for education and to practice applied programming because there is a general purpose input and output port inside the kit, through which diverse input and output devices, DC motor, and servo motor can be operated. Accordingly, facing the IT fusion era, the wall between the academic circles and the major becomes lower and the need for introducing education about creative engineering object-oriented programming language is emerging. At this point, the Java robot training kit developed in this study is expected to make a great commitment in this regard.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.87-88
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• 2023

본 논문에서는 COVID-19 팬데믹으로 인해 사회적 거리두기 및 규제조치가 시행되면서 다양한 분야에서 큰 영향을 가져왔다. 변화된 홈트레이닝 분야는 운동기구를 구비하여 개인운동을 통해 건강을 유지하고 있으나 전문적인 교육을 받지 않은 홈트레닝으로 부상 위험에 노출 되고 있다. 요가는 호흡운동과 명상을 지향하는 운동으로 요가의 효과를 얻기 위해 올바른 움직임과 자세가 중요 하다. 본 논문에서는 실시간으로 입력된 영상 프레임을 OpenCV와 MediaPipe를 통해 추출된 주요좌표 값을 벡터 내적공식을 대입, 코사인2법칙을 통해 요가의 올바른 자세를 분석하여 종합적인 정보를 제공하는 요가교정 모델이다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.29 no.3
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• pp.297-320
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• 2018

This study aims to improve the access and retrieval of images and to find a way to effectively generate tags as a tool for providing explanation of images. To do this, this study investigated the features of human tagging and machine tagging, and compare and analyze them. Machine tags had the highest general attributes, some specific attributes and visual elements, and few abstract attributes. The general attribute of the human tag was the highest, but the specific attribute was high for the object and scene where the human tag constructor can recognize the name. In addition, sentiments and emotions, as well as subjects of abstract concepts, events, places, time, and relationships are represented by various tags. The tag set generated through this study can be used as basic data for constructing training data set to improve the machine learning algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.681-683
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• 2022

코로나 19 로 인해 사회적으로 활동 범위에 제약이 많아져 신체 노화가 진행중인 노년층의 심각한 운동 부족 현상 발생했다. 이에 따라 본 연구는 스마트 미러 트레이닝 프로그램의 범람 속에 신체적인 불편함을 가지고 있는 노인의 건강 증진에 주목하여 스마트 미러와 노인 자세 탐지, 자세 정확성 판단 시스템을 기반으로 한 자세 분류 서비스 제공 프로그램을 제안한다. 스마트 미러에 탑재된 카메라로 받아온 영상을 MoveNet 과 머신러닝 모델을 사용하여 사용자의 동작을 파악하는 방식으로 활동 프로그램을 진행한다. 향후 디지털 소외 계층의 사용 및 노인 자세 데이터 분석에 활용할 수 있을 것으로 기대한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.73-76
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• 2013

This paper proposes a tongue and its direction recognition algorithm which compares and estimates pixel distribution in the mouth area. As the size of smart phones grows, facial gesture control technology for a smart phone is required. Firstly, the nose area is detected and the mouth area is detected based on the ratio of the nose to mouth. After detecting the mouth area, it is divided by a pattern of grid and the distribution of pixels having the similar color to the tongue is tested for each segment. The recognition rate was nearly 80% in the experiments performed with five researchers among our laboratory members.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.341-342
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• 2021

본 논문에서는 운동 관련 빅데이터를 적용한 인공지능을 활용하여 개개인에게 알맞은 운동 루틴을 추천해 주는 비대면 방식 PT를 제안한다. 이 정책은 '건강한 사람이 앱을 만나 더 건강해진다.'는 모토를 중심으로, 홈 트레이닝을 하고 싶지만 운동방법을 모르는 사람들로 하여금 자신에게 맞추어진 루틴 구성을 통해 운동 수행능력의 효율성을 높이고, 잘못된 자세로 인한 부상 등을 최소화한다. 또한 이 정책은 기존의 일일이 사용자가 입력해야 했던 시스템들에서 머신러닝을 통한 AI 알고리즘을 통한 추천을 통해 비대면 방식의 수동적인 운동 방식에서 AI가 트레이너 역할을 해주는 방식으로 사용자와 상호작용하고, 정확한 운동 목표를 추천함으로써 운동 지속성과 동기성을 부여한다. 본 논문에서는 프로토타입을 통해 제안하는 AI를 적용한 맞춤 헬스 정책이 기존의 헬스 앱 업계에서 시장성을 보일 수 있다는 가능성에 의의를 둔다.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.151-157
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• 2014

Recently UAV(unmanned aerial vehicle) is frequently used not only for military purpose but also for civil purpose. UAV automatically navigates following the coordinates input in advance using GPS information. However it is impossible when GPS cannot be received because of jamming or external interference. In order to solve this problem, we propose a real-time segmentation and classification algorithm for the specific regions from UAV image in this paper. We use the super-pixels algorithm using graph-based image segmentation as a pre-processing stage for the feature extraction. We choose the most ideal model by analyzing various color models and mixture color models. Also, we use support vector machine for classification, which is one of the machine learning algorithms and can use small quantity of training data. 18 color and texture feature vectors are extracted from the UAV image, then 3 classes of regions; river, vinyl house, rice filed are classified in real-time through training and prediction processes.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.4
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• pp.183-194
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• 2020

Recently, the number of hip dysplasia (DDH) that occurs during infant and child growth has been increasing. DDH should be detected and treated as early as possible because it hinders infant growth and causes many other side effects In this study, two modelling techniques were used for multiple training techniques. Based on the results after the first transformation, the training was designed to be possible even with a small amount of data. The vertical flip, rotation, width and height shift functions were used to improve the efficiency of the model. Adam optimization was applied for parameter learning with the learning parameter initially set at 2.0 x 10e-4. Training was stopped when the validation loss was at the minimum. respectively A novel image overlay system using 3D laser scanner and a non-rigid registration method is implemented and its accuracy is evaluated. By using the proposed system, we successfully related the preoperative images with an open organ in the operating room

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.761-766
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• 2023

In this paper, TI was measured to classify the presence or absence of mild left ventricular diastolic dysfunction. Of the total 306 data, 206 were used as training data and 100 were used as test data, and the machine learning models used for classification used SVM and KNN. As a result, it was confirmed that SVM showed relatively higher accuracy than KNN and was more useful in diagnosing the presence of left ventricular diastolic dysfunction. In future research, it is expected that classification performance can be further improved by adding various indicators that evaluate not only TI but also cardiac function and securing more data. Furthermore, it is expected to be used as basic data to predict and classify other diseases and solve the problem of insufficient medical manpower compared to the increasing number of tests.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.83-88
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• 2023

In this paper, we developed a workout and diet assistance application to meet the growing demand for workout and dietary support services due to the increase in the home training population. The application analyzes the user's workout posture in real-time through the camera and guides the correct posture using guiding lines and voice feedback. It also classifies the foods included in the captured photos, estimates the amount of each food, and calculates and provides nutritional information such as calories. Nutritional information calculations are executed on the server, which then transmits the results back to the application. Once received, this data is presented visually to the user. Additionally, workout results and nutritional information are saved and organized by date for users to review.