단안 영상의 3차원 기하학적 구조 추정 기술과 적용사례

최지원,안일구,정찬호,김창익 대한전자공학회 2011 전자공학회지 Vol.38 No.2

심전도 기반의 심장 질환 분류를 위한 신호 특징 추출 시스템 개발

최지원,권오윤,권준환,오경택,유선국 한국멀티미디어학회 2023 멀티미디어학회논문지 Vol.26 No.1

In this paper, we propose a signal-based feature detection system for the early diagnosis of heart disease. The purpose of this study is to develop a compact healthcare system that extracts features from ECG signals. Therefore, the performance of the Tompkins algorithm, which is widely known as a signal-based feature detection algorithm, and the deep learning model of prior research are compared. In addition, by verifying the performance of the deep learning model by applying the Haar wavelet transform to the preprocessing, we determine the optimal feature detection model applicable to the healthcare system in terms of speed and accuracy. All algorithms and models were developed using Matlab on Window, and performance was compared on Jetson nano and Raspberry pi embedded boards. As a result, the best model in terms of speed and accuracy is the Haar wavelet bidirectional long short-term memory model, which quickly performs classification prediction with almost 97% accuracy. The advantage of this study is that it quickly performs classification prediction with high accuracy compared to existing healthcare systems that use algorithms that cause signal distortion. Therefore, cardiovascular diseases can be predicted and monitored based on the feature regions detected in this study. The data used are the MIT-BIH Arrhythmia Database and the Normal Sinus Rhythm Database. If additional patient data are established and verified in the future, it will be possible to use them not only in real life but also in clinical settings.

트라우마 상담에서 이야기치료와 브레인스포팅(Brainspotting)의 적용 가능성 고찰

최지원 한국실천신학회 2023 신학과 실천 Vol.- No.84

The purpose of this study is to examine the potential applicability of narrative therapy and Brainspotting, as suitable approaches for trauma counseling. To achieve this, the literature review was conducted to discuss the characteristics of narrative therapy for trauma counseling, and to investigate the conceptual understanding, case application, and prior research on Brainspotting. The results of this study are as follows: First, an important variable in trauma counseling is the reconstruction of brain memories. Second, the goal of narrative therapy and brainspotting in trauma counseling is brain plasticity. Third, in both narrative therapy and brainspotting, a therapeutic relationship and a stable relationship are important points of contact. Fourth, when dealing with meaningful stories in trauma counseling, it brings about optimized results in managing and coordinating the functions of the brain and mind. This study has implications that the therapeutic effect may be promoted when story therapy and brainspotting are applied in trauma counseling. In conclusion, this study can have significance as a basis for the possibility of integrating narrative therapy and brainspotting in future trauma counseling and as a basic exploratory study. As the purpose of trauma counseling is to restore the damaged brain and reconstruct the memories and narratives stored in the brain after the formation of a stable relationship, it repeats special skills or behaviors after forming a safe relationship, and deals with changes in brain structure and function as important. Through brain-based trauma counseling, clients experience plasticity of the brain and improve self-regulation ability. This brain-altering exercise can strengthen connections between different areas of the brain and change brain structure through the process of having conversations in a counseling relationship and reprocessing emotional memories visually. In this respect, it is intended to reveal that narrative therapy and brainspotting are effective in trauma counseling in terms of reconstructing memories, plasticity of the brain, and tuning through safe therapeutic relationships.

공심채 추출물(IAE)의 LPS로 유도된 미세아교세포에서의Nrf2기전을 통한 항염증 효과

최지원,최상윤,허진영 한국식생활문화학회 2023 韓國食生活文化學會誌 Vol.38 No.5

Ipomoea aquatic is a leafy vegetable of the Convolvulaceae family, and is a tropical plant widely inhabiting southernChina and Southeast Asia, and is widely known as Morning Glory in the West. In this study, the anti-inflammatory effectsof ethyl acetate extract from Ipomoea aquatic extracts (IAE) were tested against lipopolysaccharide (LPS)-induced activationmicroglia BV2 cells. The production of nitric oxide (NO) and cell viability were measured using the Griess reagent and MTTassay, respectively. Inflammatory cytokine [interleukin (IL)-6, tumor necrosis factor (TNF)-, and interleukin-1 (IL-1)]were detected qPCR in LPS induced BV-2 cells. Subsequently, nuclear factor (NF)-B, mitogen-activated protein kinases(MAPKs), and nuclear factor erythroid-2-related factor 2 (Nrf2) were analyzed through western blot analyses andimmunofluorescence. Ipomoea aquatic down-regulated of inflammatory markers and up-regulated anti-inflammatory andanti-oxidants in BV2 cells.

초중등학교 학습조직화 관련 국내 연구동향 분석

최지원,김도기 한국교육행정학회 2022 敎育行政學硏究 Vol.40 No.3

The purpose of this study was to collect and select academic papers and degree papers on learning organizations in elementary and secondary schools published in Korea since 1990, analyze them according to the criteria to examine the trend of related research, and present implications for future related studies based on the results. 80 studies related to learning organizations in elementary and secondary schools published in Korea from 1990 to 2021 were selected as analysis targets, and research trend was analyzed based on years, topics, methods, and characteristics of researchers. As a result, studies related to learning organizations in elementary and secondary schools have repeatedly increased or decreased within a certain range for 31 years and then decreased again over the past 5 years. Also, studies have mainly been conducted to set the change level to learning organization as a variable and identify the influences with teacher-related and school-related variables. In research methods, quantitative research has been conducted the most, and most of studies were conducted at elementary schools. Most of the researchers majored in educational administration. In the future, studies on school learning organizations should be activated, the contents and methods of studies should be diversified, and the school level to be studied should be expanded. 본 연구는 1990년 이후 국내에서 발표된 초중등학교 학습조직에 대한 학술논문과 학위논문을 수집 및 선별하고, 이를 준거에 따라 분석하여 관련 연구의 동향을 살펴보고, 그 결과를 토대로 향후 초중등학교 학습조직 관련 연구에 시사점을 제시하는 것을 목적으로 하였다. 이를 위하여 1990년 이후부터 2021년까지 국내에서 발표된 초중등학교 학습조직 관련 연구 80편을 분석 대상으로 선정하고, 선행연구를 토대로 연구연도, 연구주제, 연구방법, 연구대상, 연구자 특성을 기준으로 하여 연구동향을 분석하였다. 연구 결과, 초중등학교 학습조직 관련 연구는 31년간 일정 범위 내에서 증감폭을 반복하다가 최근 5년간 다시 감소하는 추세를 보였다. 연구주제로는 학습조직으로 변화한 정도, 즉 학습조직화 수준을 변인으로 설정하고 여러 교사 및 학교 변인들과의 영향관계를 파악하려는 연구가 주로 이루어졌다. 연구방법으로는 양적연구가 가장 많이 수행되었으며, 초등학교급에서 가장 많은 연구가 이루어졌다. 연구자는 교육행정학 전공자가 대부분이었으나, 교육학의 여러 분야에서 두루 연구된 것으로 파악되었다. 연구 결과를 바탕으로 국내 초중등학교 학습조직 연구의 특징을 도출하고, 추후 학교 학습조직 연구의 시사점으로 연구의 활성화, 연구 내용과 방법의 다양화, 연구 대상 학교급의 확장 등을 제시하였다.

친밀한 관계에서 허세와 내숭이 관계 지속 의도에 미치는 영향 : 기대 위반 이론을 중심으로

최지원,허경호 한국소통학회 2017 한국소통학회 학술대회 Vol.2017 No.10

先天性 12指腸閉鎖症을 兼한 中腸廻轉 異常의 一治驗 例

崔至源,黃完性,金在燮,李永麟 醫藥係社 1963 綜合 醫學 Vol.8 No.8

인공지능 기반 밭작물 생산량 모니터링 기술 동향

최지원,김성윤,권경도,조수빈,조은아,김건우,조병관 경상국립대학교 농업생명과학연구원 2023 농업생명과학연구 Vol.57 No.5

식량 작물의 확보 및 생산량 예측은 국가 발전에 있어 필수적이며, 국가 경제뿐만 아니라 전 세계 식량 안보에 기여 한다. 최근 환경오염으로인한 이상기후는 식량 작물 생산량에 직ㆍ간접적으로 부정적 영향을 끼치고 있어, 작물 수확량 예측 불확실성이 높아지고 있다. 특히, 노지 작물의경우 생산량 감소와 품질 저하 문제가 화두 되고 있다. 이러한 문제는 농가들뿐만 아니라 소비자들에게도 큰 피해를 안겨주고 있다. 이러한 생산량예측 이슈를 해결하기 위해 최근에는 인공지능 기술이 농업 분야에도 활발히 적용되고 있다. 작물 수확량의 정확한 예측을 위한 머신러닝 기반연구가 집중적으로 수행되고 있다. 따라서, 본 연구에서는 이와 같은 인공지능 기반의 노지 작물 수확량 예측 기술(머신러닝, 딥러닝, 하이브리드모델 등) 현황 및 작물 수확량에 가장 영향을 많이 끼치는 모델 파라미터 등을 조사하였다. Securing food crops and predicting its productivity are essential for national development and contribute not only to the nationaleconomy, but also to global food security. Recent abnormal weather patterns caused by environmental pollution directly and indirectlyaffect food crop production, leading to increased uncertainty in crop yield predictions. In particular, because of the abnormal weatherconditions, the low productivity and quality of field crops has attracted substantial attentions in agricultural industry. This issues notonly affect farmers, but also cause significant damage to consumers. To solve the prediction issues, various artificial intelligence technologieshave recently been actively applied in the field of agriculture. To accomplish this, machine learning-based researches on accurately predictingcrop yields are being intensively conducted. Therefore, in this study, we investigated the current status of AI-based field crop yieldprediction technologies (such as machine learning, deep learning, and hybrid models) and major parameters that have the greatest impacton crop yield.

急性 蟲垂炎手術前後에 있어서의 電解質 變動에 關하여

崔至源 醫藥係社 1963 綜合 醫學 Vol.8 No.1

공동주택 내 환기방법별 실내 라돈농도 저감 비교

최지원,홍형진,김가현,윤성원,이철민 환경독성보건학회 2021 한국독성학회 심포지움 및 학술발표회 Vol.2021 No.10