• 제목/요약/키워드: Predictive Variables

검색결과 754건 처리시간 0.026초

Validity of Breast Cancer Symptom Questionnaire and Its Relationship With Breast Ultrasonography in Young Female Night Workers

  • Chae, Chang-Ho
    • Safety and Health at Work
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    • 제11권3호
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    • pp.361-366
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    • 2020
  • Background: This study aimed to identify the validity of breast cancer symptom questionnaire of worker's special health examination and its relationship with breast ultrasonography findings in young female night workers. Methods: The breast cancer symptom questionnaire data of worker's special health examination and breast ultrasonography results in young female shift workers who worked in one electronic manufacture company were collected from 2014 to 2018. Results: Of the 857 workers, 18 had a Breast Imaging Reporting and Database System category 4 or higher. Among other variables, shift work tenure alone was associated with the risk of having a Breast Imaging Reporting and Database System category higher than 4. The sensitivity, specificity, positive predictive value, and negative predictive value of the symptom questionnaire were 16.7%, 87.7%, 2.8%, and 98.0%, respectively. Conclusion: The current breast cancer symptom questionnaire of the worker's special health examination is inappropriate due to its low sensitivity and positive predictive value. In the future, female night workers will need alternative measures for more accurate screening for breast cancer.

기러기 아빠의 건강관련 삶의 질 예측모형 구축 (Predictive model of Health-related Quality of Life of Korean Goose daddies)

  • 차은정
    • 성인간호학회지
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    • 제24권4호
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    • pp.428-437
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    • 2012
  • Purpose: The purpose of the study was to develop a predictive model of Health-related Quality of Life (HRQoL) for Korean Goose daddies - they live alone in Korea to support their families who moved overseas for children's education. Methods: Data were collected from 151 goose daddies from May to June of 2011 by using the structured self-reported questionnaires. The collected data were analyzed using SAS program (version 9.2) and SAS CALIS procedure. Results: Frequency of exercise, monthly income, depression, perceived physical health, and perceived mental health had direct effects on HRQoL and Depression was the variable accounting for major total effect on HRQoL. It could be explained that predictor variables accounted for 76% of the health-related quality of life. Conclusion: In order to improve Goose daddies' HRQoL, predictive factors, such as age, exercise, nutritional status, monthly income, depression, perceived physical health, and perceived mental health, should be considered. Furthermore, should the need of the exercise and diet program, early detection of depression and the treatment for it be emphasized. Also, there is a need to establish institutional structures to support goose daddies in adversity.

대형 컨테이너선의 해치 코밍 FCA 맞대기 용접부의 횡 방향 잔류응력 예측에 관한 연구 (A Study on the Predicting Transverse Residual Stress at the Ultra Thick FCA Butt Weldment of Hatch Coaming in a Large Container Vessel)

  • 신상범;이동주;이주성
    • Journal of Welding and Joining
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    • 제28권4호
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    • pp.33-40
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    • 2010
  • The purpose of this study is to establish a predictive equation of transverse residual stress at the thick FCA butt weldment of large container vessel. The variables used were restraint degree, yield strength of base material, thickness of weldment and welding heat input. Restraint degree at the thick weldment of container ship having the various welding sequence was calculated using FEA. From the result, the H-type specimen was designed to reproduce the level of restraint degree at the actual weldment of containership. Based on the results, the predictive equations of the mean value and the distribution of transverse residual stress at each location of the weldment were established using dimensional analysis and multiple-regression method. The predictive equations were verified by comparing with those measured by XRD in the actual weldment of the ship.

퍼지모델을 이용한 비선형 공정의 적응 모델예측제어에 관한 연구 (A Study on an Adaptive Model Predictive Control for Nonlinear Processes using Fuzzy Model)

  • 박종진;우광방
    • 한국지능시스템학회논문지
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    • 제6권2호
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    • pp.97-105
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    • 1996
  • 본 논문에서는 퍼지모델을 이용한 비선형 공정의 적응모델예측제어가 제안된다. 모델예측제어의 저긍구조는 순환 퍼지모델링을 통해 구현된다. 사용된 퍼지모델의 후건부가 입, 출력 변수의 선형식이기 때문에, 전체 공정의 모델을 구하고 이를 이용하여 미래 공정출력을 구한 후 비용함수를 최로로하는 제어법칙은 일반형 예측제어(GPC)와 같은 형태가 된다. 제안된 적응 퍼지모델 예측제어는 퍼지모델이 가지는 본래적인 비선형성으로 인해 비선형공정을 우수한 성능으로 제어한다. 공정제어입력의 변화량을 출력값으로 하는 적응 퍼지모델 예측제어(AFMPC)인 경우, 상수의 기준입력에 대해 정상상태가 없고 매우 우수한 성능을 보인다. 제안된 제어구조의 특성 및 성은 비선형 공정의 모의 실험에 의해 검증한다.

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SHAP을 활용한 벌크선 메인엔진 연료 소모량 예측연구 (A Study on the Prediction of Fuel Consumption of Bulk Ship Main Engine Using Explainable Artificial Intelligence)

  • 김현주;박민규;이지환
    • 한국항해항만학회지
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    • 제47권4호
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    • pp.182-190
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    • 2023
  • 본 연구에서는 벌크 선박의 연료 소비를 예측하기 위해 XGBoost와 SHapley Additive exPlanation (SHAP)을 사용하는 예측 모델을 제안한다. 기존 연구에서도 선박 엔진 데이터와 기상데이터를 활용하였지만 선박 연료소모량 예측 모델에 대한 예측 결과의 신뢰성과 예측 모델 구현에 사용된 변수들에 대한 설명이 부족한 한계가 있었다. 이러한 문제를 해결하기 위해 본 연구에서는 XGBoost와 SHAP를 사용하여 예측 모델을 개발하였다. 이 연구는 연구 배경, 범위, 관련 규정 및 이전 연구들, 그리고 연구 방법론에 대한 소개를 제공하며, 또한 벌크선 데이터 정제 방법과 예측 모델 결과의 검증을 설명한다.

Attention 기반 Encoder-Decoder 모델을 활용한작물의 생산량 예측 (Forecasting Crop Yield Using Encoder-Decoder Model with Attention)

  • 강수람;조경철;나명환
    • 품질경영학회지
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    • 제49권4호
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    • pp.569-579
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    • 2021
  • Purpose: The purpose of this study is the time series analysis for predicting the yield of crops applicable to each farm using environmental variables measured by smart farms cultivating tomato. In addition, it is intended to confirm the influence of environmental variables using a deep learning model that can be explained to some extent. Methods: A time series analysis was performed to predict production using environmental variables measured at 75 smart farms cultivating tomato in two periods. An LSTM-based encoder-decoder model was used for cases of several farms with similar length. In particular, Dual Attention Mechanism was applied to use environmental variables as exogenous variables and to confirm their influence. Results: As a result of the analysis, Dual Attention LSTM with a window size of 12 weeks showed the best predictive power. It was verified that the environmental variables has a similar effect on prediction through wieghtss extracted from the prediction model, and it was also verified that the previous time point has a greater effect than the time point close to the prediction point. Conclusion: It is expected that it will be possible to attempt various crops as a model that can be explained by supplementing the shortcomings of general deep learning model.

A Study of Performance Monitoring and Diagnosis Method for Multivariable MPC Systems

  • Lee, Seung-Yong;Youm, Seung-Hun;Lee, Kwang-Soon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2612-2616
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    • 2003
  • Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

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인공 신경망을 이용한 채소 단수 예측 모형 개발: 고추를 중심으로 (Development of Yield Forecast Models for Vegetables Using Artificial Neural Networks: the Case of Chilli Pepper)

  • 이춘수;양성범
    • 한국유기농업학회지
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    • 제25권3호
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    • pp.555-567
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    • 2017
  • This study suggests the yield forecast model for chilli pepper using artificial neural network. For this, we select the most suitable network models for chilli pepper's yield and compare the predictive power with adaptive expectation model and panel model. The results show that the predictive power of artificial neural network with 5 weather input variables (temperature, precipitation, temperature range, humidity, sunshine amount) is higher than the alternative models. Implications for forecasting of yields are suggested at the end of this study.

정보구조 설계를 위한 계층적 탐색모델 개발 및 적용 (Development and Application of Hierarchical Information Search Model(HIS) for Information Architecture Design)

  • 김인수;김봉건;최재현
    • 대한인간공학회지
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    • 제23권3호
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    • pp.73-88
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    • 2004
  • This study was contrived Hierarchical Information Search (HIS) model. HIS model is based on a “cognitive process” in which model, comprising basic human information processing mechanize and information interaction. Its process include 3 semantic cognitive processes: Schema-Association LTM, Form Domain, and Alternative Selection. Design methodology consists to elicitate memory, thinking and cognitive response variables. In case study, menu structure of mobile phone was applied. In result, a correlation between predictive error rate and real error rate was .892. and a correlation between selective and real reaction time was .697. This present to suggest a model of how the methodology could be applied to real system design effectively when this was used. HIS model could become one of the most important factors for success of product design. In the perspective, the systemic methodology would contribute to design a quantitative and predictive system.

헬리콥터의 비행영역제한 알고리즘 설계 (Design of Envelope Protection Algorithm for Helicopters)

  • 고준수;박성수;김경목
    • 한국항공운항학회지
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    • 제23권2호
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    • pp.63-68
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    • 2015
  • This paper presents the algorithm for envelope protection of helicopters. The algorithm consists of two feedback control loops: inner loop and outer loop. As an inner loop control, model following control is designed to meet the ADS-33 handling qualities specification by minimizing the tracking errors between the responses of the actual model and those of the command filter. In order to implement envelope protection, saturation limiter is imposed to command channels in command filter, whose limits are computed corresponding to the envelope limit. Fast model predictive control is designed as an outer loop control to deal with saturation constraints generated by the inner loop envelope protection and also imposed by outer loop envelope protection variables. Simulation results show that the proposed algorithm yields good envelope protection performance.