• 제목/요약/키워드: Human behavior classification

검색결과 80건 처리시간 0.026초

Seismic vulnerability of reinforced concrete structures using machine learning

  • Ioannis Karampinis;Lazaros Iliadis
    • Earthquakes and Structures
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    • 제27권2호
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    • pp.83-95
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    • 2024
  • The prediction of seismic behavior of the existing building stock is one of the most impactful and complex problems faced by countries with frequent and intense seismic activities. Human lives can be threatened or lost, the economic life is disrupted and large amounts of monetary reparations can be potentially required. However, authorities at a regional or national level have limited resources at their disposal in order to allocate to preventative measures. Thus, in order to do so, it is essential for them to be able to rank a given population of structures according to their expected degree of damage in an earthquake. In this paper, the authors present a ranking approach, based on Machine Learning (ML) algorithms for pairwise comparisons, coupled with ad hoc ranking rules. The case study employed data from 404 reinforced concrete structures with various degrees of damage from the Athens 1999 earthquake. The two main components of our experiments pertain to the performance of the ML models and the success of the overall ranking process. The former was evaluated using the well-known respective metrics of Precision, Recall, F1-score, Accuracy and Area Under Curve (AUC). The performance of the overall ranking was evaluated using Kendall's tau distance and by viewing the problem as a classification into bins. The obtained results were promising, and were shown to outperform currently employed engineering practices. This demonstrated the capabilities and potential of these models in identifying the most vulnerable structures and, thus, mitigating the effects of earthquakes on society.

인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로 (Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support)

  • 이윤경;이인주;신민정;배서연;한소원
    • 인지과학
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    • 제35권1호
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    • pp.23-48
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    • 2024
  • 대형언어모형(LLM)을 현실에 적용하려는 지속적인 노력에도 불구하고, 인공지능이 맥락을 이해하고 사람의 의도에 맞게 사회적 지지를 제공하는 능력은 아직 제한적이다. 본 연구에서는 LLM이 사람의 감정 상태를 추론하도록 유도하기 위해, 심리 치료 이론을 기반으로 한 공감 체인(Chain of Empathy, CoE) 프롬프트 방법을 새로 개발했다. CoE 기반 LLM은 인지-행동 치료(CBT), 변증법적 행동 치료(DBT), 인간 중심 치료(PCT) 및 현실 치료(RT)와 같은 다양한 심리 치료 방식을 참고하였으며, 각 방식의 목적에 맞게 내담자의 정신 상태를 해석하도록 설계했다. CoE 기반 추론을 유도하지 않은 조건에서는 LLM이 사회적 지지를 구하는 내담자의 글에 주로 탐색적 공감 표현(예: 개방형 질문)만을 생성했으며, 추론을 유도한 조건에서는 각 심리 치료 모형을 대표하는 정신 상태 추론 방법과 일치하는 다양한 공감 표현을 생성했다. 공감 표현 분류 과제에서 CBT 기반 CoE는 감정적 반응, 탐색, 해석 등을 가장 균형적으로 분류하였으나, DBT 및 PCT 기반 CoE는 감정적 반응 공감 표현을 더 잘 분류하였다. 추가로, 각 프롬프트 조건 별로 생성된 텍스트 데이터를 정성적으로 분석하고 정렬 정확도를 평가하였다. 본 연구의 결과는 감정 및 맥락 이해가 인간-인공지능 의사소통에 미치는 영향에 대한 함의를 제공한다. 특히 인공지능이 안전하고 공감적으로 인간과 소통하는 데 있어 추론 방식이 중요하다는 근거를 제공하며, 이러한 추론 능력을 높이는 데 심리학의 이론이 인공지능의 발전과 활용에 기여할 수 있음을 시사한다.

어린이집 유아반의 일과 유형분류 및 일과 유형별 교사행동에 관한 연구 (Classification of Daily Routine Types in Child Care Center and Teacher Behaviors Based on Daily Routine Types)

  • 권연희;최목화;박찬화
    • 한국생활과학회지
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    • 제21권5호
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    • pp.837-848
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    • 2012
  • This study evaluated the types of daily routines that occurred in child care centers based on four general categorizations: time spent on indoor free choice activities, outdoor activities, group activities and special activities. In addition, resulting child care teacher behaviors were examined based on daily routine types. A total 23 classes' activity times and teacher behaviors were observed. The collected data were analyzed using descriptive statistics, hierarchical cluster, and Mann-Whitney U. Results indicated that there were 2 principle daily routine, 'indoor/outdoor activity time oriented' and 'group activity time oriented'. Analysis showed that teachers who belonged to the 'indoor/outdoor activity time oriented' type showed more positive affect, positive guidance, neural guidance, and less non-involved behavior. Results suggest the importance of time spent on free choice activities in the context of daily routine for quality childcare.

정신분석적 관점에서의 불안 (Psychoanalytical View of Anxiety)

  • 박용천
    • 대한불안의학회지
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    • 제1권1호
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    • pp.14-17
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    • 2005
  • By the influence of the descriptive approach of DSM-III, the anxiety became the same thing as the anxiety disorder to the clinicians. This unfortunate result sacrificed psychodynamic model of symptom formations and simplified the anxiety as one of the disease entity not as the overdetermined symptoms. These phenomenon awakened the psychoanalytic interest which was in sleep. Freud was the first major articulator of the basic significance of anxiety in human behavior. He attributed the particular quality of the anxiety experience to the trauma of birth, and subsequently to the fear of castration. Such classification of the anxiety according to the psychosexual development is helpful for the clinicians in understanding the origin of anxiety which the patient shows during the psychotherapy. The other analytical view of interpersonal psychoanalysis came from Sullivan. A large part of his therapy is taken up with recognizing and correcting parataxic distortions that interfere with realistic self-appraisal of events and of oneself in relation to others. Perhaps no explanation is the 'most basic' explanation for human anxiety. Anxiety is a multifaceted entity consisting of aspects of realm of discourse. Existential anxiety is inescapable in Western culture but it can be transcended by the cultivation of mind in Eastern culture. The analysts need to stay attuned to their own propensities for anxiety and must permit their own experiences with anxiety to be the grist for the psychotherapeutic mill.

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공연로봇을 위한 인간자세 추정방법 개선에 관한 연구 (A Study on Improvement of the Human Posture Estimation Method for Performing Robots)

  • 박천유;박재훈;한재권
    • 방송공학회논문지
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    • 제25권5호
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    • pp.750-757
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    • 2020
  • 공연에 사용하는 로봇이 인간과의 상호작용하기 위한 기본 성능 중 하나는 인간의 행동을 빠르고 정확하게 파악하는 것이다. 따라서 로봇이 인간의 자세를 추정할 때 자세 인식의 정확도를 높임과 동시에 가능한 빠른 속도로 인식할 수 있어야 한다. 그러나 현재 인공지능 기술의 대표적인 방식인 딥 러닝을 사용하여 인간의 자세를 추정할 경우, 인식의 정확도와 속도라는 두 가지 성능을 동시에 만족하지 못하고 있다. 따라서 사용 목적에 따라 추론정확도가 높은 하향식 자세추정과 처리속도가 빠른 상향식 자세추정 중 하나를 선택해서 사용하는 것이 일반적이다. 본 논문에서는 앞서 언급한 두 가지 방식이 가진 장점을 모두 포함하면서 단점을 보완한 두 가지 방식을 제안한다. 첫 번째는 다중 그래픽 처리 장치를 활용해 상향식 자세추정과 물체검출을 병렬로 사용하는 방식이고, 두 번째는 상향식 자세추정과 단항분류를 융합하는 방식이다. 실험을 통해 두 가지 방식 모두 속도가 개선됨을 증명했다. 공연로봇에 이 두 가지 방식 중 하나를 사용한다면, 관객과 신뢰도 높으며 보다 빠른 상호작용을 수행할 수 있을 것으로 기대된다.

은닉 마코프 모델을 이용한 행동 분류 연구 (A Study on Human Behavior Classification using a Hidden Markov Model)

  • 서정우;오현교;조승호;이호석;문봉희
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2013년도 추계학술발표대회
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    • pp.1354-1357
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    • 2013
  • 최근 다양한 센서들이 일상생활에 활용되어, 일정한 환경에서 사람의 행동을 분류하고 인식하기 위한 연구들이 활발하게 진행되고 있다. 본 연구에서는 2개의 진동센서 값과 1개의 적외선 센서 값을 은닉 마코프 모델에 적용하여 침대 위에 있는 사람의 3가지 행동유형-눕기, 뒤척임, 일어나기-을 분류하고자 한다. 3개 센서 값의 특징들을 기초로 은닉 마코프 모델에 학습시키고, 특징집합과 학습 데이터량을 변화시키면서 사람의 행동유형에 대한 인식 실험을 수행하였다. 특징 개수 혼합에 따른 인식률의 차이는 거의 없는 것으로 나타났으나, 학습 데이터량을 증가시켜 가면서 수행한 실험에서는 인식률이 평균 78.127%로 향상되는 성과를 거두었다.

스포티브 스타일의 패션 이미지 세분화에 따른 선호도 및 구매행동 분석 (A Study of Design Preference and Purchase Behavior by Segmentation of Fashion images on Sportive style)

  • 박숙현;이정민
    • 한국생활과학회지
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    • 제15권4호
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    • pp.585-595
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    • 2006
  • The purpose of this study is to classify the fashion images on sportive style, to find out the difference between the image of sportive style which consumers prefer and the image of sportive style which they want to show and, finally, to analyze their purchase behavior. This research is done with survey method. The subjects of the survey are 835 females in their twenties or their thirties in Pusan area. The data are analyzed with factor analysis, Cronbach's alpha, $X^2$-test, and frequency analysis. The results of this study are as follows: first, sportive style is classified into Sexy, Romantic, Active and Modem image. Second, the results of analysis on consumers' preferring image and their wanting-to-show image to the above-mentioned image classification are as follows: firstly, the subjects' most preferring image and the image which they most want to show is Modem in1age. The second is Sexy image. But the subjects preferred having Modem image. Secondly, consumers' Individuality and apparel's Function are the important reasons to choose the sportive style. Thirdly, Modem image is the most preferred in the images of street wear. Sexy image and Active image are the preferred in the images of sports wear. Third, It is a vivid tone and a dark tone that is the color tone of sportive wear which consumers prefer. They prefer a logo- patterned sports wear, too. The consumers obtain most information on sports wear from sports wear stores. Silhouette is the most decisive design element in consumers' purchasing. The sports wear brands which the subjects prefer are Adidas and Nike.

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Object Detection Based on Deep Learning Model for Two Stage Tracking with Pest Behavior Patterns in Soybean (Glycine max (L.) Merr.)

  • Yu-Hyeon Park;Junyong Song;Sang-Gyu Kim ;Tae-Hwan Jun
    • 한국작물학회:학술대회논문집
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    • 한국작물학회 2022년도 추계학술대회
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    • pp.89-89
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    • 2022
  • Soybean (Glycine max (L.) Merr.) is a representative food resource. To preserve the integrity of soybean, it is necessary to protect soybean yield and seed quality from threats of various pests and diseases. Riptortus pedestris is a well-known insect pest that causes the greatest loss of soybean yield in South Korea. This pest not only directly reduces yields but also causes disorders and diseases in plant growth. Unfortunately, no resistant soybean resources have been reported. Therefore, it is necessary to identify the distribution and movement of Riptortus pedestris at an early stage to reduce the damage caused by insect pests. Conventionally, the human eye has performed the diagnosis of agronomic traits related to pest outbreaks. However, due to human vision's subjectivity and impermanence, it is time-consuming, requires the assistance of specialists, and is labor-intensive. Therefore, the responses and behavior patterns of Riptortus pedestris to the scent of mixture R were visualized with a 3D model through the perspective of artificial intelligence. The movement patterns of Riptortus pedestris was analyzed by using time-series image data. In addition, classification was performed through visual analysis based on a deep learning model. In the object tracking, implemented using the YOLO series model, the path of the movement of pests shows a negative reaction to a mixture Rina video scene. As a result of 3D modeling using the x, y, and z-axis of the tracked objects, 80% of the subjects showed behavioral patterns consistent with the treatment of mixture R. In addition, these studies are being conducted in the soybean field and it will be possible to preserve the yield of soybeans through the application of a pest control platform to the early stage of soybeans.

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인터넷에서 행동 수정 이론을 적용한 체중 감량 상담 방법 개발 (Development of Nutritional Counseling for Weight Reduction based on behavior modification through Internet)

  • 박수진;박선민;최선숙
    • 대한영양사협회학술지
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    • 제7권3호
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    • pp.295-306
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    • 2001
  • The purpose of the study was to develop an internet nutritional counseling program using an expert system to assist obese people to lose weight through behavior modification. The internet counseling program for weight loss was developed by the accumulation of knowledge dealing with eating habits and exercising behaviors in expert system tool, Knowledge Engineering Agent (KEA) by a dietitian without any help of computer expert. To accumulate knowledge into KEA, survey was performed in 150 obese people, dietitians reviewed and consulted each survey case, and the consulted contents were learned and accumulated into KEA. Survey questionnaire was the same as that of the internet consulting program, and it included general characteristics, dietary habits, lifestyle, and exercise patterns related to obesity. Also, the dietitian selected proper factors inferred from the survey questionnaire of each case, and added the conclusions for them. Conclusions were made for helping clients to correct bad eating behaviors and accumulate good behaviors to lose weight. Counseling was divided into two parts; a two-week part and a daily part. Two-week counseling was performed based on 4 step questionnaires, and daily counseling was done for daily food consumption and physical activity. When clients answered survey questionnaires in a counseling internet program, the recommendations on how to eat, to exercise and to deal with stress in a real time for each case, was given. In conclusion, a counseling internet program for weight reduction can be used to give advices how to deal with obesity in a man-to-man way in a real time using KEA where nutritional knowledge based on behavior modification for weight loss was accumulated.

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공간분석을 위한 퍼지분류의 이론적 배경과 적용에 관한 연구 - 경상남도 邑級以上 도시의 기능분류를 중심으로 - (The aplication of fuzzy classification methods to spatial analysis)

  • 정인철
    • 대한지리학회지
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    • 제30권3호
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    • pp.296-310
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    • 1995
  • 본 연구는 퍼지이론을 공간분석에 적용하기 위한 이론적인 배경을 고찰하고, 퍼지 분류법의 특성에 대해 살펴본 것이다. 이를 위해 필자는 공간정보의 모호성에 대해 살펴보 고, 퍼지공간분석의 전제를 설정한 다음 퍼지분류법을 소개하였다. 그리고 퍼지분류법의 특 성을 명확히 하기 위해 경상남도 읍급이상 도시의 산업별 고용비율을 대상으로 퍼지분류를 행한 후, 퍼지분류와 전통적인 군집분석의 결과를 비교하였다. 그 결과, 공간정보의 모호성 은 구체성의 부족, 인간행태, 인내치문제, 분류기준의 부족 등에 의해 발생하는데 기존의 공 간분석기법으로는 공간의 모호성을 반영할 수 없으므로 퍼지기법을 도입한 퍼지공간분석의 필요성이 있음을 확인하였다. 퍼지분류법 중, 퍼지이산분류는 계산절차는 상대적으로 간단하 나 분류결과가 집단간의 점이성을 고려하지 못하며, 퍼지중첩분류는 분류집단간의 점이성은 고려하나 분류결과가 지나치게 많아 적절한 분류수준을 선택하기 어렵고 결과해석이 상대적 으로 난해하다는 문제점이 있음이 밝혀졌다, 또 경남의 도시기능분류는 분류기법에 따라 다 르게 이루어졌지만 창원, 울산, 마산, 진해, 김해, 양산, 웅상, 장승포, 신현으로 구성된 제조 업 군집과 단독군집 충무의 존재가 세 가지 분류 모두에서 공통적으로 확인되었다.

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