• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2003년도 추계 학술대회논문집
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• pp.200-205
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• 2003

The Canard rotor/wing (CRW) aircraft concepts offer great potential for application by allowing the use of a common propulsion system for high-speed cruise and low-speed powered lift. Using the rotor for lift in both flight modes increases its utility. In the hovering mode, the exhausted gas from an gas turbine engine is accelerated through the duct system and it provides the tipjet power for rotor system enough to lift the aircraft. In the cruise mode, the rotor is fixed and the exhausted gas is extracted through the main nozzle, such that the aircraft is able to flight with high speed. The duct system was designed using 1-D fanno line flow theory and empirical data. However, the empirical data of the pressure loss coefficient for various bending and dividing ducts were not enough to design our duct system adaptively. Therefore, using 3-D CFD analysis we obtained the pressure loss coefficient for our duct models and chose the appropriate bending or diving duct type. In this paper, we used the CFD-ACE+ software package for the CFD analysis and the modeling of duct system. Through the 3-D CFD analysis, we investigated also the pressure loss and the velocity distributions of the designed whole duct system as well as the blade duct. Comparing the 3-D CFD result with 1-D analysis result, we lessened the uncertainty of the designed duct system and speculated the problem that was not concerned in design state.

• 대한가정학회지
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• 제38권12호
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• pp.29-45
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• 2000

The purposes of this study were to determine what factors influence risk perceptions of females and males for milk produced using food-related biotechnology, to test whether risk perceptions or other factors influence self-protection actions and to estimate milk demand response in light of self-protection actions and other economic and demographic factors. The expected utility model was applied to explain the way consumers would take self-protection actions regarding risk perceptions and to drive milk demand. Telephone interviews were conducted and the data were collected from households(females=1,029, males=437) nationwide in the U.S. And the data were analyzed by Heckman two-step method using the software package LIMDEP. Risk perceptions were found to be influenced not by demographic factors but by outrage factors as well as attitudinal factors in both females and males, although some factors were different. In addition, risk perceptions and labeling availability were found to significantly influence self-protection actions in both groups. Furthermore, as an important concern in this study, self-protection action was found to significantly influence milk demand in only male group, implying a consistent behavior of males. Also milk price and household size were found to significantly influence milk demand in both groups. In fact, the results did demonstrate that labeling availability significantly influenced self-protection actions. That is, in markets where labeled laternatives were present, concerned consumers were more likely to self protect by substituting to these products. A policy implication of this result is that labeling food products produced using biotechnology enhances consumer choice. Hence, consumer could express a more accurate demand response and reduce the perceived food safety risk. Furthermore, education for females might be necessary to have a consistent behavior because self-protection action did not significantly influence female's milk demand, though they have greater risk perceptions than males have.

• 한국정보전자통신기술학회논문지
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• 제13권3호
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• pp.206-211
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• 2020

얼굴검출 과정은 영상 모니터링에서 매우 중요한 과정이며 생체 인식 기술의 한 종류이다. 검출과정은 변수가 많고 복잡하여 하드웨어가 발전하고 있는 근래에 와서 소프트웨어적인 발전이 이루어지고 있다. CCTV를 이용하는 분야 중 얼굴 검출 기술은 얼굴을 분석하기 이전에 실행되는 과정으로 영상에서 얼굴이 있는 곳을 찾아내는 기술이다. 사람의 얼굴은 조명이나 피부 색, 방향과 각도, 표정 등 여러 가지 환경적 조건에 따라 민감한 반응을 하기 때문에, 얼굴 검출에 관한 연구는 많은 어려움이 있다. 얼굴 검출 기술의 활용성과 중요성은 시간이 지날수록 각광받고 있으나, 얼굴 검출 이전에 선행되어야 하는 얼굴 영역 검출 기술에 대해서는 간과하는 측면이 많다. 본 논문의 시스템은 AdaBoost detector에서 검출 못하는 기울어진 얼굴을 검출할 수 있어 다른 사물의 검출도 같은 기술을 사용할 수 있을 것이다.

• 대한원격탐사학회지
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• 제35권4호
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• pp.573-587
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• 2019

A multi-temporal approach using remotely sensed time series data obtained over multiple years is a very useful method for monitoring land covers and land-cover changes. While spectral-based methods at any particular time limits the application utility due to instability of the quality of data obtained at that time, the approach based on the temporal profile can produce more accurate results since data is analyzed from a long-term perspective rather than on one point in time. In this study, a multi-temporal approach applying a multi-periodic harmonic model is proposed for classification of remotely sensed data. A harmonic model characterizes the seasonal variation of a time series by four parameters: average level, frequency, phase, and amplitude. The availability of high-quality data is very important for multi-temporal analysis.An satellite image usually have many unobserved data and bad-quality data due to the influence of observation environment and sensing system, which impede the analysis and might possibly produce inaccurate results. Harmonic analysis is also very useful for real-time data reconstruction. Multi-periodic harmonic model is applied to the reconstructed data to classify land covers and monitor land-cover change by tracking the temporal profiles. The proposed method is tested with the MODIS and GOCI NDVI time series over the Korean Peninsula for 5 years from 2012 to 2016. The results show that the multi-periodic harmonic model has a great potential for classification of land-cover types and monitoring of land-cover changes through characterizing annual temporal dynamics.

• Journal of Korean Neurosurgical Society
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• 제62권1호
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• pp.83-89
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• 2019

Objective : This study is a retrospective cost-benefit analysis of cervical anterior interbody fusion and cervical artificial disc replacement, which are the main surgical methods to treat degenerative cervical disc disease. Methods : We analyzed 156 patients who underwent anterior cervical disc fusion and cervical artificial disc replacement from January 1, 2008 to December 31, 2009, diagnosed with degenerative cervical disc disorder. In this study, the costs and benefits were analyzed by using quality adjusted life year (QALY) as the outcome index for patients undergoing surgery, and a Markov model was used for the analysis. Only direct medical costs were included in the analysis; indirect medical costs were excluded. Data were analyzed with TreeAge Pro $2015^{TM}$ (TreeAge Software, Inc, Williamstown, MA, USA). Results : Patients who underwent cervical anterior fusion had a total cost of KRW 2501807/USD 2357 over 5 years and obtained a utility of 3.72 QALY. Patients who underwent cervical artificial disc replacement received 4.18 QALY for a total of KRW 3685949/USD 3473 over 5 years. The cumulative cost-effectiveness ratio of cervical spine replacement surgery was KRW 2549511/QALY (USD 2402/QALY), which was lower than the general Korean payment standard. Conclusion : Both cervical anterior fusion and cervical artificial disc replacement are cost-effective treatments for patients with degenerative cervical disc disease. Cervical artificial disc replacement may be an effective alternative to obtain more benefits.

• 국제물리치료학회지
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• 제12권1호
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• 융합신호처리학회논문지
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• 제23권2호
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• pp.62-69
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• 2022

의료현장에서는 최근 디지털 헬스케어의 중요성이 대두되면서, 다양한 형태의 생체신호 측정 관련 연구가 활발히 진행되고 있다. 생체신호 중 가장 중요한 신호로 심전도를 들 수 있으며, 특히 부정맥 환자에 있어 심전도 신호의 연속 모니터링은 매우 중요하다. 부정맥은 동결절(sinus node), 동빈맥(sinus tachycardia), 심방조기수축(atrial premature beat, APB), 심실세동 (ventricular fibrillation) 등으로 그 발병원에 따른 형태가 다양하며, 발병 이후의 예후가 좋지 않으므로 일상 중 연속 모니터링은 부정맥의 조기 진단과 치료방향 설정에서 매우 중요하다. 부정맥 환자의 심전도 신호는 매우 불안정하며, 부정맥을 자동 검출하기 위한 주요 특징점으로 작용하는 정확한 R-peak 포인트의 검출이 어렵다. 본 연구에서는 연속 측정하는 홀터 심전도 모니터링 기기와 분석용 소프트웨어를 개발하였으며, 부정맥 데이터베이스를 통해 심전도 신호의 R-peak 효용성을 확인하였다. 향후 연구에서는 다양한 발병원인으로 인한 부정맥의 형태적 구분 및 예측을 위한 알고리즘과 임상 데이터에 근거한 유효성 검증에 관한 추가 연구가 필요하다.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.634-639
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• 2013

The aim of the study is to develop the 3D visualization of Building Information Model and integrated 4D model for optimization of resources in the construction project. This study discuss the process of methodology and creation of 4D model of the project and simulate it to monitor the workflow at the site. Different stages of the construction process and activities are generated by using Revit and MS Project. MS project has been used for creation of the schedules and these are linked with the Revit for 3D modeling. The time used as the fourth dimension and 4D model created by using Navisworks Time liner software. Narges shopping center is presented as a case study to realize the actual uses and benefits of Building Information Model (BIM). Narges shopping mall is located in Tehran, Iran. As a part of Hekmat master plan, Narges shopping center is an 11 stores building with a total area of 30000 Sq.m. This shopping and entertainment center is comprised of 150 retails and two multi-use public halls with a capacity of 400 persons each and underground parking with total 400 parking space. The main purpose of architecture was to create an urban public center along with its revolving, spiral like form and an ever changing continuous façade by means of different colors, materials, which is in harmony with the other building of the master plan. The approximate cost of the project is $17 million and duration of the project schedule is 30 months. The developed Building Information Model enabled us to identify the potential collisions or clashes between various structural and architectural systems. 4D model has been used for limiting the interaction between subcontractors installing the different systems so rework could be avoided and productivity maximized. It is also observed that the utility of BIM for construction stimulation and clash detection is the best suitable method. Clash detection before the implementation of work is highly recommended to avoid rework.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제34권4호
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• pp.192-203
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• 2023

Digital therapeutics based on software, such as artificial intelligence, virtual reality, games, and smartphone applications, are in the spotlight as new therapeutic alternatives in child and adolescent psychiatry. It draws attention to overcoming conventional therapeutics' limitations, such as toxicity, cost, and accessibility, and encourages patients to participate in the treatment attractively. The growth potential of the digital therapeutics market for psychiatric disorders in children and adolescents in Korea and abroad has been highlighted. Clinical studies and Food and Drug Administration approvals for digital therapeutics have increased, and cases approved by the Ministry of Food and Drug Safety have emerged in Korea. As seen above, digital transformation in child and adolescent psychiatry will change treatment paradigms significantly. Therefore, as this new field has just begun to emerge, it is necessary to verify the effectiveness and scope of the application of digital therapeutics and consider preparing a compensation system and institutional arrangements. Accordingly, this study analyzed the development trends and application status of digital therapeutics in children and adolescents and presented limitations and development directions from the perspective of application in healthcare. Further, the study is expected to identify the utility and limitations of digital therapeutics for children and adolescents and establish effective application measures.

• 한국BIM학회 논문집
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• 제13권3호
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.