• 동의생리병리학회지
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• 제30권2호
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• pp.124-130
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• 2016

The aim of this study was to suggest the future direction of diagnostic and evaluative pattern identification questionnaire (PIQ) by reviewing the state of development and utilization of PIQ according to Korean classification of disease-U (KCD-U). We surveyed the database of OASIS, NDSL, KISS, DBPIA, and Pub-med to know the kinds of developed and developing PIQ of Korean medicine. We used 'Pattern Identification' and 'Questionnaire' to find suitable papers. The inclusion criteria met 47 cases. The number of PIQ before 2000yrs, between 2001 to 2005, 2006-2010, 2011-2015 were 2, 5, 18, 22cases. The number of PIQ belonged to the disease of Korean medicine, the pathological symptom of korean medicine, the Sasang constitutional pattern identification and etc according to KCD-U were 20(42.6%), 8(17%), 9(19.1%) and 10(21.3%). Twenties among forty seven PIQ were validated, and the rest of them were not validated. The distribution of the numbers of PIQ were significantly different according to KCD-U (p=0.003). The direction of Utilization of PIQ was 36 questionnaires in diagnosing PI, 14 cases in evaluating health state, 4cases in evaluating effects of a treatment and 8 ones in diagnosing Sasang constitutional types. This study reveals the status on validated and non-validated PIQ of Korean medicine and suggests the basic information for the direction of developing PIQ in the future.

• 사상체질의학회지
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• 제26권2호
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• pp.133-145
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• 2014

Objectives In this study, we tried to examine that Sasang Constitutional differences affect the direction of the treatment of anger by comparing the effect of mindfulness meditation for anger scale in accordance with the difference of the constitution. Methods We analysed 105 college student's Constitution by Questionnaire for the Sasang Constitution Classification II and the effect of mindfulness meditation for anger by State-Trait Anger Expression Inventory Korean version(STAXI-K), Korean Version of the Behavioral Anger Response Questionnaire(K-BARQ). Volunteers who participated in this study were 105 people, except for person that did not properly entered the anger scale and Questionnaire for the Sasang Constitution Classification II, the subjects of analysis for State-Trait Anger Expression Inventory Scale were 45 and for the Behavioral Anger Scale were 49. Results & Conclusions The result of the effects of mindfulness meditation according to Sasang Constitution was as follows. The tendency to try to disperse and avoid the anger was increased through meditation for all subjects. The diffusion of male subjects and the avoidance of female subjects was increased. The effect of meditation on anger did not differ according to Sasang Constitution, constitutional differences did not affect the effects of meditation. The tendency of avoidance of anger was increased in Soyangin, Anger-out was decreased and the tendency of avoidance and diffusion of anger were decreased in Taeeumin through meditation.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.260-268
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• 2022

The article considers the training, competitiveness of specialists, professional mobility, professionalism and competence of specialists in the context of distance learning. The advantages of distance learning are shown. The characteristic features of distance learning in the preparation of students and in the implementation of these technologies in the educational process of higher educational institutions are determined. Competitiveness, professional mobility, professionalism and competence of a specialist are qualities that determine a person's life and work success. Professional mobility is interpreted as a systemic quality of a specialist's personality, which includes a whole range of knowledge, skills, abilities, personal qualities, value orientations, and so on. The vision of mobility of specialists by foreign scientists is presented. It is noted that the classification of professional mobility presented in the article makes it possible to organize various movements from a single position, to present them as separate manifestations of the general process of professional and pedagogical mobility, to determine which type of mobility ensures the performance of certain social functions. It was found that mobility can be differentiated into differentiated and intergeneration. According to the subject, individual and group mobility are distinguished; according to the direction - internal and external. The classification of employees according to their attitude to mobility is shown, which can be divided into the following groups: actually mobile; potentially mobile; actually stable; potentially stable.

• 한국컴퓨터정보학회논문지
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• 제27권6호
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• pp.43-52
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• 2022

사람이 느끼는 피로는 다양한 생체신호로부터 측정이 가능한 것으로 알려져 있으며, 기존 연구는 질병과 관련된 심각한 피로수준을 산정하는데 주된 목적을 두고 있다. 본 연구에서는 피실험자의 영상을 이용하여 딥러닝 기반의 영상 분석 기술을 적용, 피로 여부를 판단하기 위한 모델을 제안한다. 특히 화상 분석에서 통상적으로 사용되는 객체 인식, 요소 추출과 함께 영상 데이터의 시계열적 특성을 고려하여 방법론을 교차한 3개 분석모델을 제시했다. 다양한 피로상황에서 수집된 정면 얼굴 영상 데이터를 이용하여 제시된 모델을 실험하였으며, CNN 모델의 경우 0.67의 정확도로 피로 상태를 분류할 수 있어 영상 분석 기반의 피로 상태 분류가 유의미하다고 판단된다. 또한 모델별 학습 및 검증 절차 분석을 통해 영상 데이터 특성에 따른 모델 적용방안을 제시했다.

• 대한토목학회논문집
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• 제8권1호
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• pp.61-68
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• 1988

본(本) 연구(硏究)에서는 군용전차의 교량통과시 노후도(老朽度)를 비롯한 각종 저항(抵抗) 및 하중(荷重)관련 불확실량(不確實量)을 체계적으로 포함한 한계상태모형(限界狀態模型)을 유도하고, 실용적이며 진보된 2차(次)모멘트 신뢰성(信賴性) 이론(理論)을 사용하여 군용교량(軍用橋梁) 및 일반교량(一般橋梁)의 신뢰성(信賴性)에 기초한 안전도(安全度) 분석방법(分析方法)과 하중저항계수(荷重抵抗係數) 형식의 급수계산방법(級數計算方法)을 제안(提案)하였다. 본(本) 연구(硏究)에서 제안(提案)하는 안전도(安全度) 분석(分析) 및 내하급수(耐荷級數) 판정방법(判定方法)을 몇 개의 실제 교량에 적용하여 보았다. 본(本) 연구(硏究)의 결과 현행 재래식 허용응력개념에 의한 NATO 급수계산방법은 실내하력(實耐荷力) 판정(判定)이 아닌 명목적인 급수판정방법에 불과함을 알 수 있으며, 따라서 본 연구에서 제시(提示)한 신뢰성방법(信賴性方法)에 의한 안전도(安全度) 분석방법(分析方法)과 하중(荷重)-저항계수(抵抗係數)형 급수 계산방법이나 이에 대응하는 합리적인 허용응력법(許容應力法)에 의한 실내하급수(實耐荷級數) 계산방법(計算方法)의 도입이 시급하다고 본다.

• 방송공학회논문지
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• 제22권6호
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• pp.693-701
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• 2017

본 논문은 스파이크그램과 심층 신경망을 이용한 새로운 음악 장르 분류 방법을 제안한다. 인간의 청각 시스템은 최소 에너지와 신경 자원을 사용하여 최대 청각 정보를 뇌로 전달하기 위하여 입력 소리를 시간과 주파수 영역에서 부호화한다. 스파이크그램은 이러한 청각 시스템의 부호화 동작을 기반으로 파형을 분석하는 기법이다. 제안하는 방법은 스파이크그램을 이용하여 신호를 분석하고 그 결과로부터 장르 분류를 위한 핵심 정보로 구성된 특성 벡터를 추출하고, 이를 심층 신경망의 입력 벡터로 사용한다. 성능 측정에는 10개의 음악 장르로 구성된 GTZAN 데이터 세트를 사용하였고, 제안 방법이 기존 방법에 비해 낮은 차원의 특성 벡터를 사용하여 우수한 성능을 제공하는 것을 확인하였다.

• 한국멀티미디어학회논문지
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• 제14권9호
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• pp.1190-1201
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• 2011

본 연구는 간호사 및 간호학생을 위한 간호진단, 간호중재, 간호결과 분류체계의 간호과정 프로그램을 모바일 응용 기반으로 개발하였다. 연구재료는 표준화된 분류체계인 북미간호진단협의회의 간호진단 분류체계와 아이오와 대학을 중심으로 개발된 간호중재 분류체계, 간호결과 분류체계를 사용하였다. 기존 연구 방법은 간호과정의 일부분만을 선택하여 개발하므로 환경에 제한적인 프로그램으로 임상에 일반화시켜 환자들에게 적용하기 어려웠다. 그러나 본 연구는 진단-결과-중재의 전체를 연계시킨 프레임워크를 개발하므로 어떠한 임상환경에서도 적용이 가능한 가이드라인으로 개발하였다. 개발된 프로그램은 한글판으로 3월부터 앱 스토어에 등록되었으며 간호교육 도구로 적극적으로 활용되기를 기대한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.426-429
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• 2006

Flood caused by Typhoon and severe rain during summer is the most destructive natural disasters in Korea. Almost every year flood has resulted in a big lost of national infrastructure and loss of civilian lives. It usually takes time and great efforts to estimate the flood-related damages. Government also has pursued proper standard and tool for using state-of-art technologies. High resolution satellite imagery is one of the most promising sources of ground truth information since it provides detailed and current ground information such as building, road, and bare ground. Once high resolution imagery is utilized, it can greatly reduce the amount of field work and cost for flood related damage assessment. The classification of high resolution image is pre-required step to be utilized for the damage assessment. The classified image combined with additional data such as DEM and DSM can help to estimate the flooded areas per each classified land use. This paper applied object-oriented classification scheme to interpret an image not based in a single pixel but in meaningful image objects and their mutual relations. When comparing it with other classification algorithms, object-oriented classification was very effective and accurate. In this paper, IKONOS image is used, but similar level of high resolution Korean KOMPSAT series can be investigated once they are available.

• Healthcare Informatics Research
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• 제24권4호
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• pp.309-316
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• 2018

Objectives: Both the valence and arousal components of affect are important considerations when managing mental healthcare because they are associated with affective and physiological responses. Research on arousal and valence analysis, which uses images, texts, and physiological signals that employ deep learning, is actively underway; research investigating how to improve the recognition rate is needed. The goal of this research was to design a deep learning framework and model to classify arousal and valence, indicating positive and negative degrees of emotion as high or low. Methods: The proposed arousal and valence classification model to analyze the affective state was tested using data from 40 channels provided by a dataset for emotion analysis using electrocardiography (EEG), physiological, and video signals (the DEAP dataset). Experiments were based on 10 selected featured central and peripheral nervous system data points, using long short-term memory (LSTM) as a deep learning method. Results: The arousal and valence were classified and visualized on a two-dimensional coordinate plane. Profiles were designed depending on the number of hidden layers, nodes, and hyperparameters according to the error rate. The experimental results show an arousal and valence classification model accuracy of 74.65 and 78%, respectively. The proposed model performed better than previous other models. Conclusions: The proposed model appears to be effective in analyzing arousal and valence; specifically, it is expected that affective analysis using physiological signals based on LSTM will be possible without manual feature extraction. In a future study, the classification model will be adopted in mental healthcare management systems.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권10호
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• pp.437-446
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• 2022

보이스피싱 통화 내용을 탐지하고 분류하는데 핵심 엔진으로 최신 머신러닝(ML) 및 딥러닝(DL) 알고리즘과 결합된 자연어 처리(NLP)의 텍스트 분류 작업이 널리 사용된다. 비대면 금융거래의 증가와 더불어 보이스피싱 통화 내용 분류에 대한 많은 연구가 진행되고 양호한 성과를 보이고 있지만, 최신 NLP 기술을 활용한 성능 개선의 필요성이 여전히 존재한다. 본 논문은 KorCCVi라는 레이블이 지정된 한국 보이스 피싱 데이터의 텍스트 분류를 기반으로 여러 다른 최신 알고리즘과 비교하여 사전 훈련된 한국어 모델 KoBERT의 한국 보이스 피싱 탐지 성능을 벤치마킹한다. 실험 결과에 따르면 KoBERT 모델의 테스트 집합에서 분류 정확도가 99.60%로 다른 모든 모델의 성능을 능가한다.