• 대한가정학회지
• /
• 제33권2호
• /
• pp.29-41
• /
• 1995

This research paper investigates the overall level of the consumer's satisfaction and complaint with medical services, relationships of them and the relationships of socio-demographic variables to them. Data were collected from 523 clients in Ulsan city. Results show that socio-demographic variables appear to have a little predictive power and consumer satisfaction variables are related to private consumer complaint.

• 한국물환경학회지
• /
• 제39권1호
• /
• pp.46-60
• /
• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• 기본간호학회지
• /
• 제6권2호
• /
• pp.267-276
• /
• 1999

The purpose of this study was to identify risk factors predictive of alterations in skin integrity during the intraoperative period. The predictive risk factors were studied for intraoperative pressure sores from December 1998 through January 1999. A sample of 220 patients was selected from the operating room schedule of a University Hospital in Pusan. There were two criteria in including patients : the operation lasted longer than 2 hours and the absence of skin break-down according to NPUAP criteria. The data were analized by SPSS/PC, Stepwise multiple logistic regression was used to identify the variables which were predictive of alterations in skin integrity. Of the 220 patients studied, 41 patients (18.6%) developed stage 1 pressure sores in the immediate postoperative period. In relation to skin changes, three independent variables emerged from the stepwise multiple logistic regression as being significant (p<0.05). Factors predictive of pressure sore formation included low serum albumin(p=0.000), prone position while undergoing surgery(p=0.0004), time on the operating table(p=0.0165). Among the intrinsic factors, serum albumin was the most significant causal factor in pressure sores development in the intra-operative period. Pressure and shearing force were the most significant extrinsic factors in pressure sores development. From the results of this study we concluded that the primary nursing goal is the maintenance of the proper patient' position during the intraoperative period. Also imperative for sore prevention is the reduction of surgery time and improving preoperative nutritional status.

• Korean Chemical Engineering Research
• /
• 제58권2호
• /
• pp.248-256
• /
• 2020

본 연구에서는 폭발위험장소의 방폭설비 설치를 위해 필요한 가스폭발위험범위 예측모델 개발을 수행하였다. 이를 위해 12개의 가연성가스에 대한 1,200개의 폭발위험범위 데이터를 생성하였다. 가스폭발위험범위를 출력변수로 설정하였고 데이터 생성과정에서 필요한 12개의 변수를 입력변수로 설정하였다. 다중 회귀, 주성분 회귀, 인공신경망 기법을 이용해 예측모델을 개발하였다. 각각 모델의 예측 성능을 비교한 결과, 평균절대퍼센트오차(MAPE)는 각각 44.2%, 49.3%, 5.7%이고 평균제곱근오차(RMSE)는 1.389 m, 1.602 m, 0.203 m로 나타났다. 결과를 통해 인공신경망이 가장 우수한 성능을 보여주었고 가스폭발위험범위 예측을 위한 최적 모델이라는 것을 확인하였다.

• 한국컴퓨터그래픽스학회논문지
• /
• 제23권4호
• /
• pp.21-29
• /
• 2017

예측 시각적 분석 연구는 다양한 대화식 데이터 탐색 기법을 사용하여 예측 결과의 불확실성을 줄이는데 중점을 두었다. 대화식 탐색 기법의 목적은 변수간의 관계를 이해하고 알려지지 않은 변수를 예측하기 위한 적합한 모델을 선택함으로서 의사결정권자의 수준에 따른 예측결과의 품질 차이를 줄이는 것이다. 하지만 청소년 신체 성장 데이터와 같이 전체적인 추세가 알려지지 않은 시계열 데이터를 설명할 수 있는 예측 모델을 만드는 것은 어렵다. 본 논문에서는 불확실한 추세를 가지는 시계열 데이터 단편에서 물리적 성장 값을 예측하기 위한 새로운 예측 방법을 제안한다. 새로운 예측 방법은 특정 시점에서의 데이터 분포를 추정하는 방법으로 실험결과 기존 회귀 모델보다 높은 정확도를 갖는다. 또한 우리는 예측 모델링 과정에서 발생 가능한 불확실성을 최소화 할 수 있는 시각적 분석 방법을 제안한다.

• 산업융합연구
• /
• 제20권12호
• /
• pp.179-186
• /
• 2022

본 연구에서는 태블릿PC 중고제품의 거래 시, 판매자와 구매자 모두에게 판매가격을 제시할 수 있는 예측모형을 개발하는 것을 목표로 한다. 모형 개발을 위하여 실제 태블릿PC 중고거래 데이터와 제품에 대한 상세 정보를 추가 수집한 데이터를 사용하였다. 데이터 분석을 통하여 여러 가지 예측모형을 개발하였으며, 이 중 태블릿PC 중고가격 예측 성능이 가장 뛰어난 모형을 최종 예측모형으로 선택하였다. 구체적으로 중고 태블릿의 판매가격을 종속변수로 하고, 통합된 데이터에서 판매가격과 연관성이 있는 변수들을 독립변수로 한 다중선형회귀모형, 교호작용을 포함한 다중선형회귀모형, 그리고 각 모형에서 단계적 변수 선택법을 통해 얻은 모형들을 고려하였다. 이들 모형 중 교차타당성을 통해 최종적으로 예측 성능이 가장 뛰어난 모형을 태블릿PC 중고가격을 예측하는 모형으로 선택하였다. 본 연구를 통하여 중고제품 판매가격을 예측하고 판매자와 구매자에게 적절한 중고 거래 가격을 제시해 볼 수 있을 것이다.

• Clinical Endoscopy
• /
• 제57권4호
• /
• pp.476-485
• /
• 2024

Background/Aims: Sedation has become a standard practice for patients undergoing gastrointestinal (GI) endoscopy. However, considering the serious cardiopulmonary adverse events associated with sedatives, it is important to identify patients at high risk. Machine learning can generate reasonable prediction for a wide range of medical conditions. This study aimed to evaluate the risk factors associated with sedation during GI endoscopy and develop a predictive model for hypoxia during endoscopy under sedation. Methods: This prospective observational study enrolled 446 patients who underwent sedative endoscopy at the Korea University Ansan Hospital. Clinical data were used as predictor variables to construct predictive models using the random forest method that is a machine learning algorithm. Results: Seventy-two of the 446 patients (16.1%) experienced life-threatening hypoxia requiring immediate medical intervention. Patients who developed hypoxia had higher body weight, body mass index (BMI), neck circumference, and Mallampati scores. Propofol alone and higher initial and total dose of propofol were significantly associated with hypoxia during sedative endoscopy. Among these variables, high BMI, neck circumference, and Mallampati score were independent risk factors for hypoxia. The area under the receiver operating characteristic curve for the random forest-based predictive model for hypoxia during sedative endoscopy was 0.82 (95% confidence interval, 0.79-0.86) and displayed a moderate discriminatory power. Conclusions: High BMI, neck circumference, and Mallampati score were independently associated with hypoxia during sedative endoscopy. We constructed a model with acceptable performance for predicting hypoxia during sedative endoscopy.

• 대한방사선기술학회지:방사선기술과학
• /
• 제42권3호
• /
• pp.187-194
• /
• 2019

The purpose of this study was to evaluate the pathologic results of hepatic parenchyma parameters such as liver parenchyma, liver surface, liver margin and liver, portal vein, spleen size, And to evaluate the usefulness of fibrosis progression and hepatic ultrasonography. The sensitivity, specificity, positive predictive value, and prognostic value according to the stage of fibrosis and grade of inflammation were divided into two groups according to the morphologic variable "A" through ultrasound and "B" We evaluated the predictive value and predicted the variables to evaluate fibrosis in clinical diagnosis and treatment of patients with chronic liver disease. The sensitivity and specificity of hepatic fibrosis in hepatic morphologic variables and other size variables were highest in liver surface and edge. The morphologic parameters used in the evaluation of fibrosis were clinically relevant in distinguishing the fibrosis stage from the results of liver biopsy.

• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2021년도 학술발표회
• /
• pp.205-205
• /
• 2021

Surface soil moisture, which governs the partitioning of precipitation into infiltration and runoff, plays an important role in the hydrological cycle. The assimilation of satellite soil moisture retrievals into a land surface model or hydrological model has been shown to improve the predictive skill of hydrological variables. This study aims to improve streamflow prediction with Weather Research and Forecasting model-Hydrological modeling system (WRF-Hydro) by assimilating Soil Moisture Active and Passive (SMAP) data at 3 km and analyze its impacts on hydrological components. We applied Cumulative Distribution Function (CDF) technique to remove the bias of SMAP data and assimilate SMAP data (April to July 2015-2019) into WRF-Hydro by using an Ensemble Kalman Filter (EnKF) with a total 12 ensembles. Daily inflow and soil moisture estimates of major dams (Soyanggang, Chungju, Sumjin dam) of South Korea were evaluated. We investigated how hydrologic variables such as runoff, evaporation and soil moisture were better simulated with the data assimilation than without the data assimilation. The result shows that the correlation coefficient of topsoil moisture can be improved, however a change of dam inflow was not outstanding. It may attribute to the fact that soil moisture memory and the respective memory of runoff play on different time scales. These findings demonstrate that the assimilation of satellite soil moisture retrievals can improve the predictive skill of hydrological variables for a better understanding of the water cycle.

• 제어로봇시스템학회논문지
• /
• 제19권5호
• /
• pp.429-434
• /
• 2013

This paper proposes a CPSO (Cooperative Particle Swarm Optimization)-based MPC (Model Predictive Control) scheme to deal with formation control problem of multiple nonholonomic mobile robots. In a distributed MPC framework, each robot needs to optimize control input sequence over a finite prediction horizon considering control inputs of the other robots where their cost functions are coupled by the state variables of the neighboring robots. In order to optimize the control input sequence, a CPSO algorithm is adopted and modified to fit into the formation control problem. Experiments are performed on a group of nonholonomic mobile robots to demonstrate the effectiveness of the proposed CPSO-based MPC for multi-robot formation.