• 산업경영시스템학회지
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• 제17권32호
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• pp.209-220
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• 1994

In this paper, we study the timing and equipment of replacement. Those affect both available possibility and technological levels of new equipments in the future. These problems are classified according to technological levels and in consequence generated four circumstance. Models are formulated in this research. These are able to make us decision which we replace equipment at the first time. A method is suggested to find the optimal age for replacement at given each circumstance. A solution procedure and numerical example are given.

• 디지털융복합연구
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• 제17권9호
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• pp.135-145
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• 2019

장기불황으로 인해 한국 청년실업률이 수년간 10% 안팎의 높은 수준을 유지하고 있는 가운데, 주요 경제활동 인구인 30~40대의 실업률이 최근 상승세를 보이고 있다. 정부의 기존 청년 중심의 고용촉진 및 실업복지 정책을 30~40대를 포함한 다양한 연령층으로 확대 강화하기 위해서는 각 연령층에 대한 실업예측 모형 연구가 필요하다. 이에 본 연구에서는 한국 통계청 실업률 자료와 구글 검색어를 활용하여 한국 30~40대 연령층에 특화된 실업률 예측모형을 개발하고자 하였다. 실업률 자료와 계절성 자기회귀누적이동평균 모형을 활용하여 기초모형(Model 1)을 다중선형회귀 모형으로 추정하였으며, 개선된 모형을 구하고자 구글 검색 질의어 정보를 Model 1에 추가 활용하였다(Model 2). 그 결과, 30대와 40대 연령층 모두 구글 검색 질의어를 추가 활용한 Model 2가 Model 1보다 우수한 예측력을 보였다. 이는 웹 검색 질의어가 여전히 한국의 실업률 예측모형을 개선하는 데 유의미함을 의미한다. 본 연구는 실질적인 활용을 위해 추가적인 연구가 필요하지만, 연령대별 실업률 예측 연구에 기여할 것으로 판단된다.

• Journal of Oral Medicine and Pain
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• 제6권1호
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• pp.5-8
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• 1981

The author had sellected stone models of upper premolar teeth from 20 age to 60 ages in male, and studied the attrition pattern of upper premolar teeth having attention to teeth cups on the stone model. All of the attrition patterns were divided (into) 14 forms. The results were as follows : 1. Attrition patterns of upper premolar teeth were divided into 14 forms. 2. Being compared with age group, early attrition pattern (M) showed decreasing tendency and late attrition pattern (A) showed incresing tendency by aging.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 춘계학술발표대회
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• pp.483-486
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• 2020

Age estimation and gender classification for human is a classic problem in computer vision. Almost research focus just only one task and the models are too heavy to run on low-cost system. In our research, we aim to apply multitasking learning to perform both task on a lightweight model which can achieve good precision on embedded system in the real time.

• 산업기술연구
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• 제25권B호
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• pp.73-80
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• 2005

Durability of concrete structures is seriously compromised by cracking at early-age concretes, particularly in high-strength or high-performance concrete structures. Since early-age cracking is influenced by various factors that affect the hydration process, early-age shrinkage and stress/strain development, the behavior at early-age is highly complex and no rational methodologies for its control have yet been established. Concrete structures often present volumetrical changes particularly due to thermal and moisture related shrinkages. Volumetric instability is detrimental to the performance and durability of concrete structures because structural elements are usually restrained. These restrained shrinkages develope tensile stresses which often results in cracking in combination with the low fracture resistance of concrete. Early-age defects in high-performance concrete due to thermal and autogenous deformation shorten the life cycle of concrete structures. Thus, it is necessary to examine the behavior of early-age concrete at the stages of design and construction. The purpose of this study was to propose a shrinkage models of VES-LMC (very-early strength latex-modified concrete) at early-age considering thermal deformation and autogenous shrinkage.

• Computers and Concrete
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• 제18권1호
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• pp.1-16
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• 2016

In this study, an Artificial Neural Network (ANN) and Adaptive Network-based Fuzzy Inference Systems (ANFIS) prediction models for flexural strength of the cement mortars have been developed. For purpose of constructing this models, 12 different mixes with 144 specimens of the 2, 7, 28 and 90 days flexural strength experimental results of cement mortars containing pure Portland cement (PC), blast furnace slag (BFS), waste tire rubber powder (WTRP) and BFS+WTRP used in training and testing for ANN and ANFIS were gathered from the standard cement tests. The data used in the ANN and ANFIS models are arranged in a format of four input parameters that cover the Portland cement, BFS, WTRP and age of samples and an output parameter which is flexural strength of cement mortars. The ANN and ANFIS models have produced notable excellent outputs with higher coefficients of determination of $R^2$, RMS and MAPE. For the testing of dataset, the $R^2$, RMS and MAPE values for the ANN model were 0.9892, 0.1715 and 0.0212, respectively. Furthermore, the $R^2$, RMS and MAPE values for the ANFIS model were 0.9831, 0.1947 and 0.0270, respectively. As a result, in the models, the training and testing results indicated that experimental data can be estimated to a superior close extent by the ANN and ANFIS models.

• Computers and Concrete
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• 제21권4호
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• pp.463-470
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• 2018

In the present study, soft computing i.e., machine learning techniques and regression models algorithms have earned much importance for the prediction of the various parameters in different fields of science and engineering. This paper depicts that how regression models can be implemented for the prediction of compressive strength of concrete. Three models are taken into consideration for this; they are Gaussian Process for Regression (GPR), Multi Adaptive Regression Spline (MARS) and Minimax Probability Machine Regression (MPMR). Contents of cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate and age in days have been taken as inputs and compressive strength as output for GPR, MARS and MPMR models. A comparatively large set of data including 1030 normalized previously published results which were obtained from experiments were utilized. Here, a comparison is made between the results obtained from all the above mentioned models and the model which provides the best fit is established. The experimental results manifest that proposed models are robust for determination of compressive strength of concrete.

• Biomolecules & Therapeutics
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• 제16권4호
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• pp.312-319
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• 2008

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by hyperactivity, inattention, and impulsiveness. Current estimates suggest that 4-12% of school age children are affected by ADHD, which hampers proper social relationship and achievements in school. Even though the exact etiology of the disorder is still in the middle of active investigation, the availability of pharmacological treatments for the disorder suggest that at least the symptoms of ADHD are manageable. To develop drugs with higher efficacy and fewer side effects, it is essential to have appropriate animal models for in vivo drug screening processes. Good animal models can also provide the chances to improve our understanding of the disease processes as well as the underlying etiology of the disorder. In this review, we summarized current animal models used for ADHD research and discussed the point of concerns about using specific animal models.

• 아동학회지
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• 제33권3호
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• pp.131-148
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• 2012

This study examines the scientific concept development of young children in terms of the day-night cycle. The subjects consisted of 180 three-, four-, and five-year-old children from two kindergartens and one children's center located in Seoul and Jeju. Individual interviews were conducted to collect verbal and pictorial responses on the day-night cycle. The scientific concepts on the day-night cycle are classified five stages including : no recognition, egocentric concept, initial mental models, synthetic mental models, and scientific mental models. Using two-way ANOVA, scores for the types of concept on the day-night cycles were then analyzed according to both the ages and genders of the children. The results reveal the existence of significant differences in terms of the types of concept of young children according to age. Most three-year-olds children had no recognition. Most three, four, and five-year-old children revealed egocentric concepts. Four-year-old children revealed that were in the initial stages of experiencing the mental models and synthetic mental models of the day-night cycle. Five-year-old children revealed that they were in the early stages of experiencing the initial, synthetic, scientific mental models of the day-night cycle. The results suggest appropriate ways of science education for young children based on the development of scientific concepts of the day-night cycle.

• 대한인간공학회지
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• 제22권1호
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• pp.17-29
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• 2003

This study was initiated to develop a methodology for devising Korean virtual models for apparel shopping at internet shopping site. The data base for this study was the Korean National Anthropometric Survey in 1997. The subjects were 493 women and 626 men in 20's. The researchers also measured 88 males and females in age 20's to suggest back and front depth proportions which are not available from the survey. The virtual models' figure types were classified by the heights, drop value and bust(chest) girth. It was evaluated whether it is needed to separate figure type with bust(chest) girth. The body sizes of virtual models were suggested for side view model and front view model in 13cm height. Four female virtual models were suggested for front view and side view. Eight male virtual models were suggested for front view and side view. Each virtual model's height, breadth and depth proportions were calculated. Shoulder breadth. Bust(chest) breadth, waist breadth, hip breadth and proportions were calculated for front view model. The bust(chest) depth, waist depth, abdomen depth, hip depth and proportions were calculated for side view model. Height proportions were suggested for female and male virtual models.