• 한국건설관리학회:학술대회논문집
• /
• 한국건설관리학회 2006년도 정기학술발표대회 논문집
• /
• pp.137-142
• /
• 2006

비용과 공기는 수익과 직접적인 상관관계를 갖는 중요한 요소로 성공적인 프로젝트를 위해서는 이들에 대한 정확한 예측이 이루어져야 한다. 현재 최종 공사비와 공기 예측을 목적으로 EVMS(Earned Value Management System)가 범용적으로 활용되고 있지만, 기존에 제시된 공사비 및 공기 예측모텔은 선형적인 예측방식을 사용하기 때문에 예측결과가 부정확하고 시공업체의 성향, 프로젝트의 특성, 진도율에 따른 변화 등을 고려하지 못하는 한계가 있었다. 본 연구에서는 건설산업의 다양한 특성이 반영될 수 있도록 PB-S curve와 다중회귀분석을 이용한 진행단계별 공사비 및 공기의 기울기 예측모델을 제안하고 이를 동해 최종 공사비 및 공기를 예측하고자 한다. 이를 위하여 국내 건설업체로부터 23건의 도로공사 EVMS 자료를 활용하여 공사 진행단계별 기울기 예측을 위한 회귀분석방정식을 도출하고, 활용성을 검증하였다.

• 의학교육논단
• /
• 제26권1호
• /
• pp.70-76
• /
• 2024

This study investigates whether personality characteristics and learning behaviors can predict medical students' academic achievement in Korea, specifically in terms of successfully completing medical school without delays or achieving a high grade point average (GPA) in their final year. In May 2018, 316 medical students took the Multi-Dimensional Learning Strategy Test, 2nd edition, which provided data on their personality and learning behavioral characteristics. Their final year's GPA and any delays in completing medical school were ascertained by reviewing all electronic academic records of each semester they had been enrolled. The combination of personality and learning behavioral characteristics was significantly associated with completing medical school without delays, even after adjusting for sex and admission path. A multiple logistic regression analysis showed that the adjusted odds ratios and 95% confidence intervals for completing medical school without delays were 1.52 (95% confidence interval [CI], 0.83-2.78) and 3.64 (95% CI, 1.70-7.82) for "others" and "both high" categories, respectively, when compared with the "both low" category. For 235 students who completed medical school without delays, their learning behavioral characteristics (scores) were significantly associated with their final year's GPA even after adjusting for sex, admission path, and personality characteristics (scores) as determined by the multiple linear regression analysis. This study suggests that individual personality and learning behavior characteristics are predictors of medical students' academic achievement. Therefore, interventions such as personalized counseling programs should be provided in consideration of such student characteristics.

• 한국농공학회논문집
• /
• 제55권5호
• /
• pp.25-35
• /
• 2013

In swine house, dust generation comes from various sources and is known to be harmful both for the animals and the farmers because the dust contains biological and gaseous matters. When farmers are constantly exposed to the dusts, they can suffer chronic or acute respiratory symptoms and have high probability of manifesting various diseases. To address this problem, understanding of the mechanism of dust generation is very important. In this paper, the dust concentration of inhalable, respirable, TSP and $PM_{10}$ were monitored and analyzed according to the pig-activity level, ventilation quantity and feeding method in fattening pig house. From the measured results, in case of the concentration of TSP, an inverse-linear relation with ventilation rate ($R^2=0.88$) and linear relation with the installation height of feed supply pipe ($R^2=0.73$) were determined. However in case of the concentration of $PM_{10}$, no particular relationship with the variables was observed. Using the concentration of inhalable and respirable dust based on the pig-activity level, multi-variate regression analysis was conducted and results have shown that the movement of pigs can contribute to the dust generation (p＜0.05, $R^2=0.71$, 0.61). The relationship determined between dust generation and environmental variables investigated in this study is very significant and useful in conducting dust-reduction researches.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
• /
• pp.701-702
• /
• 2021

The purpose of the study was to identify fiber changes induced by electrical stimulation of a certain neural substrate in the rat brain. In the stimulation group, the peripheral nerve was injured and the brain area associated to inhibit sensory information was electrically stimulated. There were sham and sham stimulation groups as controls. Then high-field diffusion tensor imaging (DTI) was acquired. 35 features were taken from the DTI measures from 7 different brain pathways. To compare the efficacy of the classification for 3 animal groups, the linear regression analysis (LDA) and the machine learning technique (MLP) were applied. It was found that the testing accuracy by MLP was about 77%, but that of accuracy by LDA was much higher than MLP. In conclusion, machine learning algorithm could be used to identify and predict the changes of the brain white matter in some situations. The limits of this study will be discussed.

• Korean Journal of Radiology
• /
• 제24권11호
• /
• pp.1131-1141
• /
• 2023

Objective: Cortical iron deposition has recently been shown to occur in Alzheimer's disease (AD). In this study, we aimed to evaluate how cortical gray matter iron, measured using quantitative susceptibility mapping (QSM), differs in the clinical cognitive impairment spectrum. Materials and Methods: This retrospective study evaluated 73 participants (mean age ± standard deviation, 66.7 ± 7.6 years; 52 females and 21 males) with normal cognition (NC), 158 patients with mild cognitive impairment (MCI), and 48 patients with AD dementia. The participants underwent brain magnetic resonance imaging using a three-dimensional multi-dynamic multi-echo sequence on a 3-T scanner. We employed a deep neural network (QSMnet+) and used automatic segmentation software based on FreeSurfer v6.0 to extract anatomical labels and volumes of interest in the cortex. We used analysis of covariance to investigate the differences in susceptibility among the clinical diagnostic groups in each brain region. Multivariable linear regression analysis was performed to study the association between susceptibility values and cognitive scores including the Mini-Mental State Examination (MMSE). Results: Among the three groups, the frontal (P < 0.001), temporal (P = 0.004), parietal (P = 0.001), occipital (P < 0.001), and cingulate cortices (P < 0.001) showed a higher mean susceptibility in patients with MCI and AD than in NC subjects. In the combined MCI and AD group, the mean susceptibility in the cingulate cortex (β = -216.21, P = 0.019) and insular cortex (β = -276.65, P = 0.001) were significant independent predictors of MMSE scores after correcting for age, sex, education, regional volume, and APOE4 carrier status. Conclusion: Iron deposition in the cortex, as measured by QSMnet+, was higher in patients with AD and MCI than in NC participants. Iron deposition in the cingulate and insular cortices may be an early imaging marker of cognitive impairment related neurodegeneration.

• 한국지하수토양환경학회지:지하수토양환경
• /
• 제13권4호
• /
• pp.1-7
• /
• 2008

본 연구에서는 복합토양층(조립질 모래, 세립질 모래, 실트 점토의 혼합토)에서 수행된 현장추적자시험과 3개 토양층에서 채취된 시료를 이용한 실내주상실험의 자료를 이용하여, 복합토양층의 수리분산특성을 분석하였다. 토양층별 투수성과 유동 분석에 의해, 유효공극률이 낮은 실트 점토의 혼합토와 세립질 모래에서 평균선형유속이 높고, 유효공극률이 큰 조립질 모래에서는 수리전도도가 높은 것을 알 수 있었다. 평균토양입경에 따른 수리전도도 함수는 Y=$3.49{\times}10^{-8}e^{15320x}$로 추정되었으며 결정계수는 0.90이었다. 평균토양입경에 따른 평균선형유속 함수는 Y=$1.88{\times}10^{-7}e^{11459x}$로 추정되었으며, 결정 계수는 0.81이었다. 그리고 평균토양입경에 따른 종분산지수 함수는 Y = 0.00256$e^{5971x}$이었으며, 결정계수는 0.98 정도로 나타났다. 평균선형유속과 종분산지수의 선형회귀분석 결과, 함수는 Y = 21.7527x+0.0063로 추정되었으며 결정계수는 0.9979로서 매우 높게 나타났다. 본 연구에서 산정된 현장규모/실내쥬모의 종분산지수비는 54.09로서 규모종속효과를 나타내었다. 현장추적자시험을 실시하여 산정한 종분산지수(1.39m)가 Xu와 Eckstein(1995)의 방법에 의해 산정된 종분산지수(0.186m)에 비해 7.47배 정도 크게 나타났다. 이는 시험 대수층 내 중 조립질 모래층에서의 우세한 확산 흐름에 의한 것이다.

• 전기학회논문지
• /
• 제60권8호
• /
• pp.1606-1616
• /
• 2011

The blood pressure measuring equipment, which is being supplied and used most widely by being recognized convenience and accuracy now generally, is oscillometric blood pressure monitor. However, a change in blood pressure is basically influenced by diverse elements such as each individual's physiological status and physical condition. Thus, the measurement of blood pressure, which used single element called oscillation in blood pressure of being conveyed to cuff, is not considered on physiological elements such as cardiovascular system status and blood vessel stiffness index, and on external elements, thereby being quite in error. Accordingly, this study detected diverse bio-signals and body informations in each individual as the measurement subject such as ECG, PPG, and Korotkoff Sound in order to enhance convenience and accuracy of measuring blood pressure in the complex measurement equipment, thereby having extracted regression method for compensation in error of oscillometric blood pressure measurement on the wrist, and having improved accuracy of measuring blood pressure. To verify a method of improving accuracy, the blood pressure value in each of SBP, DBP, MAP was acquired through 4-stage experimental procedure targeting totally 51 subjects. Prior to experiment, the subjects were divided into two groups such as the experimental group for extracting regression method and the control group for verifying regression method. Its error was analyzed by comparing the reference blood pressure value, which was obtained through the auscultatory method, and the oscillometric blood pressure value on the wrist. To reduce the detected error, the blood pressure compensation regression method was calculated through multiple linear regression analysis on elements of blood pressure, individual body information, PTT, HR, K-Sound PSD change. Verification was carried out on improving significance and accuracy by applying the regression method to the data of control group. In the experimental results, as a result of confirming error on the reference blood pressure value in SBP, DBP, and MAP, which were acquired through applying regression method, the results of $-0.47{\pm}7.45$ mmHg, $-0.23{\pm}7.13$ mmHg, $0.06{\pm}6.39$ mmHg could be obtained. This is not only the numerical value of satisfying the sphygmomanometer reference of AAMI, but also shows the lower result than the numerical value in SBP : $-2.5{\pm}12.2$ mmHg, DBP : $-7.5{\pm}8.4$ mmHg, which is the mean error in the experimental results of Brram's research for verifying accuracy of Omron RX-M, which shows relatively high accuracy among wrist sphygmomanometers. Thus, the blood pressure compensation could be confirmed to be made within significant level.

• 지능정보연구
• /
• 제26권1호
• /
• pp.23-45
• /
• 2020

기업의 경쟁력 확보를 위해 판별 알고리즘을 활용한 의사결정 역량제고가 필요하다. 하지만 대부분 특정 문제영역에는 적합한 판별 알고리즘이 어떤 것인지에 대한 지식은 많지 않아 대부분 시행착오 형식으로 최적 알고리즘을 탐색한다. 즉, 데이터셋의 특성에 따라 어떠한 분류알고리즘을 채택하는 것이 적합한지를 판단하는 것은 전문성과 노력이 소요되는 과업이었다. 이는 메타특징(Meta-Feature)으로 불리는 데이터셋의 특성과 판별 알고리즘 성능과의 연관성에 대한 연구가 아직 충분히 이루어지지 않았기 때문이며, 더구나 다중 클래스(Multi-Class)의 특성을 반영하는 메타특징에 대한 연구 또한 거의 이루어진 바 없다. 이에 본 연구의 목적은 다중 클래스 데이터셋의 메타특징이 판별 알고리즘의 성능에 유의한 영향을 미치는지에 대한 실증 분석을 하는 것이다. 이를 위해 본 연구에서는 다중 클래스 데이터셋의 메타특징을 데이터셋의 구조와 데이터셋의 복잡도라는 두 요인으로 분류하고, 그 안에서 총 7가지 대표 메타특징을 선택하였다. 또한, 본 연구에서는 기존 연구에서 사용하던 IR(Imbalanced Ratio) 대신 시장집중도 측정 지표인 허핀달-허쉬만 지수(Herfindahl-Hirschman Index, HHI)를 메타특징에 포함하였으며, 역ReLU 실루엣 점수(Reverse ReLU Silhouette Score)도 새롭게 제안하였다. UCI Machine Learning Repository에서 제공하는 복수의 벤치마크 데이터셋으로 다양한 변환 데이터셋을 생성한 후에 대표적인 여러 판별 알고리즘에 적용하여 성능 비교 및 가설 검증을 수행하였다. 그 결과 대부분의 메타특징과 판별 성능 사이의 유의한 관련성이 확인되었으며, 일부 예외적인 부분에 대한 고찰을 하였다. 본 연구의 실험 결과는 향후 메타특징에 따른 분류알고리즘 추천 시스템에 활용할 것이다.

• 센서학회지
• /
• 제17권6호
• /
• pp.406-413
• /
• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• 한국학교ㆍ지역보건교육학회지
• /
• 제20권2호
• /
• pp.109-124
• /
• 2019

Purpose: The purpose of this study was to compare the happiness level of one-person households according to gender in Korea and identify factors influencing householders' happiness. Methods: This was a descriptive correlational study design using the 2017 Community Health Survey data. The participants were 8,724 male and 16,810 female individuals in one-person households. Complex samples descriptive statistics, cross analysis, general linear model, and multi-order regression were conducted to identify the health status, health behavior, and factors influencing happiness. Results: The mean score of happiness was higher in female than male individuals. The main factors of happiness of male householders were suicide thought experience, subjective health level, and experience of having necessary medical services. The main factors of happiness of female householders were suicide thought experience, household income, depression experience. Conclusion: It is necessary to develop and implement nursing interventions and policies according to priorities for the happiness of one-person householders.