• 한국건설관리학회논문집
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• 제1권3호
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• pp.75-80
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• 2000

공간의 분할이 많은 건축공사에서는 반복적 특성으로 인해 공정계획상에 다수의 대안이 존재한다. 공사기간은 각 액티비티의 기간뿐 아니라 반복되는 액티비티의 배열방법에 의해서도 많은 영향을 받는다. 본 연구는 각 액티비티에 적정한 선행 액티비티를 할당함으로써 여유시간을 최소화하는 공정계획기법을 제시하는 것을 목적으로 진행되었다. Line of Balance 기법을 기본으로 하는 기존연구와는 달리 본 연구에서는 AON방식의 네트워크 기법을 기본으로 하여 공간과 자원의 두 축 사이에 액티비티를 배열하였다. 각 액티비티별로 자원과 공간의 양방향으로 가장 적절한 선행 액티비티를 검색하여 여유시간을 최소화한다. 본 연구에서 제시한 액티비티 배열방법을 공동주택공사 건설공사를 대상으로 적용한 결과, 액티비티 배열을 달리함에 따라서 다수의 대안이 존재함을 확인할 수 있었으며 그중 적정대안을 찾아낼 수 있었다. 본 기법은 공동주택공사와 같은 다수의 유사공간으로 구성된 건설공사의 공정 계획에 도움을 줄 수 있을 것으로 판단된다.

• 한국지능시스템학회논문지
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• 제18권4호
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• pp.512-517
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• 2008

사회고령화, 장애인구 증가는 장애인을 위해 특화된 서비스를 제공하기 위한 유비쿼터스 컴퓨팅 관련기술의 개발이 필요함을 나타낸다. 이를 위해 기존의 일방적인 관계가 아닌 사용자와 유비쿼터스 환경간의 상호작용이 지원되는 상황인식 및 서비스 추론 기술의 개발이 필요하다. 기존의 상황인식과 관련 연구는 불확실한 실세계를 도메인으로 하기 때문에 전문가 시스템을 바탕으로 베이지안 네트워크(이하, BN)와 같은 확률 기반 표현 모델을 통해 주어진 상황을 인식하였다. 본 논문에서는 다변화하는 환경과 사용자나 개발자의 개입을 최소화한 상태에서의 상황인식을 고려하여 장애활동보조 서비스 어플리케이션 도메인을 정의하고 온톨로지를 기반으로 상황정보 모델을 정의한다. 결정된 상황정보모델을 이용해 BN의 구조학습을 적용한 후 응용서비스 개발의 차원에서 장애인을 위한 서비스, Activity를 결정한다. 최종적으로 BN의 Conditional Probability Table를 적절하게 정의한 후 주어지는 임의의 상황에서의 사용자의 Activity와 Service 상태변수 값을 확률 값을 표현함으로써 상황인식의 결과를 도출한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권3호
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• pp.197-201
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• 2006

In the implementation of a smart home, activity recognition technology using simple sensors is very important. In this paper, we propose a new activity recognition method based on Bayesian network (BN). The structure of the BN is learned by K2 algorithm and is composed of sensor nodes, activity nodes and time node whose state is quantized with reasonable interval. In the proposed method, the BN has less complexity and provides better activity recognition rate than the previous method.

• 센서학회지
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• 제16권6호
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• pp.467-474
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• 2007

The real-time monitoring about the activity of the human provides useful information about the activity quantity and ability. The present study implemented a small-size and low-power acceleration monitoring system for convenient monitoring of activity quantity and recognition of emergent situations such as falling during daily life. For the wireless transmission of acceleration sensor signal, we developed a wireless transmission system based on a wireless sensor network. In addition, we developed a program for storing and monitoring wirelessly transmitted signals on PC in real-time. The performance of the implemented system was evaluated by assessing the output characteristic of the system according to the change of posture, and parameters and acontext recognition algorithm were developed in order to monitor activity volume during daily life and to recognize emergent situations such as falling. In particular, recognition error in the sudden change of acceleration was minimized by the application of a falling correction algorithm

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.82-86
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• 2021

The article analyzes the psychological and pedagogical scientific literature on the problem of motivation of students' educational activity, compiled and implemented a diagnostic research program, studied the system of conditions for the development of motivation for educational activity of students, compiled and implemented a program for the development of motivation for educational activity of students, highlighted the features of motivation for educational activity of students and conducted a comparative study analysis.

• International Journal of Advanced Culture Technology
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• 제10권4호
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• pp.361-368
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• 2022

This study seeks to determine the research trend of late adolescents by utilizing big data. Also, seek for research trends related to activity participation, treatment, and mediation to provide academic implications. For this process, gathered 1.000 academic papers and used TF-IDF analysis method, and the topic modeling based on co-occurrence word network analysis method LDA (Latent Dirichlet Allocation) to analyze. In conclusion this study conducted analysis of activity participation, treatment, and mediation of late adolescents by TF-IDF analysis method, co-occurrence word network analysis method, and topic modeling analysis based on LDA(Latent Dirichlet Allocation). The results were proposed through visualization, and carries significance as this study analyzed activity, treatment, mediation factors of late adolescents, and provides new analysis methods to figure out the basic materials of activity participation trends, treatment, and mediation of late adolescents.

• 융합신호처리학회논문지
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• 제23권4호
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• pp.234-240
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• 2022

본 논문은 직종별 근무 환경에 따른 상대적 운동량을 고려한 맞춤형 AI 운동 추천 서비스 방법을 제안한다. 가속도 및 자이로 센서를 활용하여 수집된 데이터를 18가지 일상생활의 신체활동으로 분류한 WISDM 데이터베이스를 기반으로 전신, 하체, 상체의 3가지 활동으로 분류한 후 인식된 활동 지표를 통해 적절한 운동을 추천한다. 본 논문에서 신체활동 분류를 위해서 사용하는 1차원 합성곱 신경망(1D CNN; 1 Dimensional Convolutional Neural Network) 모델은 커널 크기가 다른 다수의 1D 컨볼루션(Convolution) 계층을 병렬적으로 연결한 컨볼루션 블록을 사용한다. 컨볼루션 블록은 하나의 입력 데이터에 다층 1D 컨볼루션을 적용함으로써 심층 신경망 모델로 추출할 수 있는 입력 패턴의 세부 지역 특징을 보다 얇은 계층으로도 효과적으로 추출 할 수 있다. 제안한 신경망 모델의 성능 평가를 위해서 기존 순환 신경망(RNN; Recurrent Neural Network) 모델과 비교 실험한 결과 98.4%의 현저한 정확도를 보였다.

• 한국보건간호학회지
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• 제29권3호
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• pp.488-502
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• 2015

Purpose: This study was conducted to determine the neighborhood environmental factors associated with physical activity among adults living in rural communities. Methods: A cross-sectional descriptive survey was conducted with a convenience sample of 201 adults living in three Ri in Y-city, Gyeonggi-do. Data were collected from face-to-face interview by trained interviewers and were analyzed using a zero-inflated negative binominal regression model. Results: Participants reported engaged in moderate or vigorous physical activity was 76.1%; 10.5% of participants reported that they met moderate physical activity recommendations and 14.5% of participants reported that they met vigorous physical activity recommendations. Zero-inflated negative binominal regression analysis showed association of increasing days of physical activity with social cohesion (${\beta}=.130$, p=.005), social network (${\beta}=-.096$, p=.003), and safety for crime (${\beta}=-.151$, p=.036), and no days of physical activity was associated with no attainment of education and marginally associated with increasing BMI. Conclusion: Neighborhood environmental factors including social cohesion, social network, and crime for safety were significantly associated with physical activity of rural adults. Community health nurses should expand an approach for individual behavior change to incorporate rural adults' specific neighborhood environmental factors into physical activity interventions.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.612-613
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• 2015

As a construction project is recently becoming large-scaled and complex, construction process plan and management for successful performance of a construction project has become more important. Especially a reasonable estimation plan of activity duration is required because the activity duration is directly related to the determination of the entire project duration and budget. However, the activity duration is used to estimate by the experience of a construction manager and past construction records. Furthermore, the prediction of activity duration is more difficult because there is some uncertainty caused by various influencing factors in a construction project. This study suggests an estimation model of construction activity duration using neural network theory for a more systematic and objective estimation of each activity duration. Because suggested model estimates the activity duration by a reasonable schedule plan, it is expected to reduce the error between planning duration and actual duration in a construction project. And it can be a more systematic estimation method of activity duration comparing to the estimation method by experience of project manager.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.39-42
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• 1996

Modeling techniques such as linear regression have been used to predict hurricane activity many months in advance of the start of the hurricane season with some success. In this paper, we construct feedforward neural networks to model Atlantic basin hurricane activity and compare the predictions of our neural network models to the predictions produced by statistical models found in the weather forecasting literature. We find that our neural network models produce reasonably accurate predictions that, for the most part, compare favorably to the predictions of statistical models.