Ball stud parts are manufactured by a cold forging process, and fastening with other parts is secured through a head part cutting process. In order to improve process quality, stabilization of the forging quality of the head is given priority. To this end, in this study, a predictive model was developed for the purpose of improving forging quality. The prediction accuracy of the model based on 450 data sets acquired from the manufacturing site was low. As a result of gradually multiplying the data set based on FE simulation, it was expected that it would be possible to develop a predictive model with an accuracy of about 95%. It is essential to build automated labeling of forging load and dimensional data at manufacturing sites, and to apply a refinement algorithm for filtering data sets. Finally, in order to optimize the ball stud manufacturing process, it is necessary to develop a quality prediction model linked to the forging and cutting processes.

The growth of the online market is accelerating due to the development of technology and the pandemic era. The delivery service through the courier must be used to deliver the ordered goods to the customer through the online market. With the growth of the online market, the logistics market for delivery is also growing. The traffic and environmental problems are emerging as social issues. Urban logistics technology using underground space based on the urban railway developed to improve logistics efficiency in a metropolitan area and a new alternative to environmental problems. This study proposed a plan to secure system safety through safety analysis based on operational concept definition and scenario analysis by applying model-based perspective analysis to the system under development.

KAERI has planned to carry out a series of dynamic tests using a shaking table and time-history analyses for a channel-type concrete shear wall to investigate its seismic performance because of the recently frequent occurrence of earthquakes in the south-eastern parts of Korea. The overall size of a test specimen is ×× 2500 mm×3500 mm×4500 mm, and it consists of three stories having slabs and walls with thicknesses of 140 mm and 150 mm, respectively. The system identification, FE model updating, and time-history analysis results for a test shear wall are presented herein. By applying the advanced system identification, so-called pLSCF, the improved modal parameters are extracted in the lower modes. Using three FE in-house packages, such as FEMtools, Ruaumoko, and VecTor4, the eigenanalyses are made for an initial FE model, resulting in consistency in eigenvalues. However, they exhibit relatively stiffer behavior, as much as 30 to 50% compared with those extracted from the test in the 1st and 2nd modes. The FE model updating is carried out to consider the 6-dofs spring stiffnesses at the wall base as major parameters by adopting a Bayesian type automatic updating algorithm to minimize the residuals in modal parameters. The updating results indicate that the highest sensitivity is apparent in the vertical translational springs at few locations ranging from 300 to 500% in variation. However, their changes seem to have no physical meaning because of the numerical values. Finally, using the updated FE model, the time-history responses are predicted by Ruaumoko at each floor where accelerometers are located. The accelerograms between test and analysis show an acceptable match in terms of maximum and minimum values. However, the magnitudes and patterns of floor response spectra seem somewhat different because of the slightly different input accelerograms and damping ratios involved.

This study was conducted to determine the possibility of estimating the daily mean temperature for a specific location based on the climatic data collected from the nearby Automated Synoptic Observing System (ASOS) and Automated Weather System(AWS) to improve the accuracy of the climate data in forage yield prediction model. To perform this study, the annual mean temperature and monthly mean temperature were checked for normality, correlation with location information (Longitude, Latitude, and Altitude) and multiple regression analysis, respectively. The altitude was found to have a continuous effect on the annual mean temperature and the monthly mean temperature, while the latitude was found to have an effect on the monthly mean temperature excluding June. Longitude affected monthly mean temperature in June, July, August, September, October, and November. Based on the above results and years of experience with climate-related research, the daily mean temperature estimation was determined to be possible using longitude, latitude, and altitude. In this study, it is possible to estimate the daily mean temperature using climate data from all over the country, but in order to improve the accuracy of daily mean temperature, climatic data needs to applied to each city and province.

본 논문에서는 한국어 쓰기 교육을 위한 교육용 게임으로서 text-to-scene 모델을 제안한다. 사용자 입력 문장에 대해 즉각적인 피드백을 제공하기 위해서, 제안하는 text-to-scene 모델은 사용자 입력 문장의 의미구조를 분석하여 장면을 자동으로 생성한다. 사용자가 문장을 교정하면서 자연스럽게 한국어 쓰기 능력이 향상될 수 있도록, 제안하는 text-to-scene 모델은 정답 장면과 사용자 입력 문장에 대한 장면을 함께 제공하므로, 사용자는 입력 문장의 어느 부분이 잘못되었는지 쉽게 파악하고 문장을 수정할 수 있다. 기존의 text-to-scene 연구에서 정교하게 장면을 생성하기 위해서는 필요한 자원 구축이 어렵고 처리 과정이 매우 복잡하다는 점을 고려하여, 제안하는 text-to-scene 모델은 외국인이 쉽게 이해할 수 있는 수준으로 장면을 단순하게 표현한다. 실험결과 격조사나 문장 요소 생략 등을 고려하여 15개의 단어를 임의로 조합하여 5개 어절 이내의 문장 1,048,576개 문장을 만들어 실험한 결과 제안하는 모델은 한 문장당 평균 14.94ms가 소요하면서 안정적으로 장면을 생성하였다. 외국인을 대상으로 한 작문 시험 결과, 종이를 이용한 작문 결과에서는 10개 문항 중 오답 문장이 평균 4.7개 나왔는데, 제안하는 text-to-scene 모델을 이용한 작문 결과에서는 한 문장 당 평균 1.56회의 미리보기를 하고 문장을 수정하여 0.87개가 나왔다.

광양만 교통안전특정해역은 3개 항로(입항항로, 출항항로, 깊은수심항로)로 구분되어 있으나 입항항로에 삼여 암초와 인공어초의 부설로 선박들이 이 항로를 이용하지 못하고 있다. 삼여 암초와 인공어초 제거에 대한 문제점은 선박운항자뿐만 아니라 항만관계자를 통해 지속적으로 제기되어 왔다. 이 연구는 특정해역 내에 있는 삼여 암초를 제거 전과 후에 대한 안전성 평가 및 항로운영방안에 대한 것으로 선박운항자 위험도 기반 모델을 이용한 해상교통류 시뮬레이션을 수행하였다. 실험결과, 장래의 선박교통량이 현재와 같고 2개 항로를 3개 항로로 운영한다고 가정할 때, 46.4 %(50,000 DWT 이상 선박은 깊은수심항로를 이용)와 57.1 %(10,000 DWT 이상 선박은 깊은수심항로를 이용) 위험 감소 효과가 있는 것으로 나타났다. 또한 교통량이 현재와 같은 상황에서는 50,000 DWT 이상 선박을 깊은수심항로로 통항하게 하는 것이 위험도 분산 측면에서 효과적임을 알 수 있었다. 한편 선박교통량이 현재보다 1.5배 증가한 상황에서는 10,000 DWT 이상 선박을 깊은수심항로로 유도하는 것이 더 효과적이었다. 이 연구는 선박운항자 위험도 기반 모델을 이용한 분석 결과로, 삼여 암초와 인공어초 제거 등에 필요한 비용 대비 효과를 검토한 것이 아님을 밟혀둔다. 본 연구의 결과는 삼여 암초 제거 후 항로 설정과 항로 운영 방안(특히 깊은수심항로 통항선박 제한) 등에 활용이 가능할 것으로 기대된다.

The validity of landfill gas models is an important problem considering that they are frequently used for landfill-site-related policy making and energy recovery planning. In this study, the Monte Carlo method was applied to an landfill gas generation model in order to enhance conformity. Results show that the relative mean deviation between measured data and modeled results (MD) decreased from 19.8% to 11.7% after applying the uncertainty range of Intergovernmental Panel on Climate Change (IPCC) to the methane-generation potential and reaction constants. Additionally, when let reaction constant adjust derived errors from all other modeling components, such as model logic, gauging waste, and measured methane data, MD decreased to 6.6% and the disparity in total methane generation quantity to 2.1%.

Constructions sites are affected by Diversity workplace, complexity of construction, Change of place, Mobility of workers and so on. In a single establishment, Prime contractors and subcontractors have to conduct their work at the same time. There are a lot of unpredictable risks when the construction is running, coordination between contractors is very important to do a risk assessment under the condition. Large Construction companies were investigated by previous studies. Survey research is applied to the risk assessment. In the writing, Risk assessment of the entire lower level. Because of the low level of risk factors to find. Also, There was a limit to investigate accidents. Confirmed that Effort to derive a risk factors were desperately of the risk assessment. Results were obtained through previous studies. The PCM is several experts should be joined. Experts Site Manager, Supervisor, Safety Manager, Director Contractor, Work team leader is required to participate. Construction plans, Process Planning to the risk find beforehand. And Determines how the operations and the control. Also, Made it into the database. and PCRA can be used in the risk assessment was developed.

The defense M&S (Modeling and Simulation) techniques are being used by the ROK Army for developing the efficiency and economics of national defense at operational level. But the problem we have found is the lack of interoperability and reusability in defe

In order to advance the service quality of education, the study is to takes measures on the satisfaction of teachers who are really important personnel resources and can be said internal customers of the education system. Previous studies on the service quality show that most of them focused on students, particularly on the improvement of their satisfaction. Therefore the study tried to measure the satisfaction degrees of teachers, so that it might seek ways for the advancement of the teaching environment and teaching service quality, for which it has utilized the Performance Model developed by Hung et al.(2003). For the purpose, surveys were conducted on 303 teachers of elementary schools and the collected data were analysed with SPSS statistic programme and the Performance Model. As a result a total of 18 items are mentioned as those to be improved. They include : Education Environment, Workplace Conditions, Performance Reward, Budget Arrangement, Welfare System. They are closely related with the two items of Performance Reward and Welfare System. In conclusion, it is confirmed that teachers who belong to the provincial office of education in Gyeongsangbuk-do want the same level of performance reward with that of the other professional groups and they also want to enjoy such a welfare as academic fees for the children who studies at colleges and graduate schools. Therefore it is necessary to improve such complaints that it would give satisfaction to the teachers, the internal customers of the education organization.

구조물에 고유한 진동수,모드형태 및 감쇠비 등과 같은 동적성능치를 추출하기 위하여 25층 및 42층 건물에 대하여 자연진동에 의한 동적계측실험을 수행하였다. 고려된 건물은 주요 횡하중 지지기구로서 코아벽체 혹은 전단벽체가 추가된 철근콘크리트건물이며, 입면 혹은 평면상으로 골조가 혼합된 구조형식을 나타낸다. 특히, 25층 건물은 측면에 위치한 코아벽체 이외에 상부로부터 내려오는 전단벽 구조가 4층 바닥이하에서 골조형식으로 전환되는 복잡한 구조이다. 이와 같은 이유 및 건물 주방향의 유사한 강성배치로 매우 근접하고 혼합된 모드형태가 예상되어 시스템판별 시 어려움이 예상된다. 현재까지 개발된 다양한 시스템판별법을 대상건물의 자연진동 실측기록에 적용하여 모달계수를 유도하였으며, 그 결과를 비교 분석하였다. 3개의 주파수영역 및 4개의 시간영역에 근거한 응답의존 시스템판별법이 고려되었다. 서로 다른 시스템판별법에 의하여 추출된 고유진동수 및 감쇠비는 대체로 상당한 일치를 보였으나, 모드형태는 사용된 방법에 따라 정도가 다르게 불일치를 나타냈다. 실험으로부터 추출한 성능치와 초기 유한요소해석 값을 비교해 본 결과 대상건물 모두 적어도 저차 3개의 고유진동수에서 2배 정도의 차이를 나타냈다. 실험과 해석결과의 일치를 위하여 몇몇 수동모델향상이 시도되었으며, 허용할 만한 결과를 획득하였다. 사용된 시스템판별법에 대하여 각자의 장, 단점에 대하여 기술하였으며, 본 연구와 같은 실제 대형구조물에 대하여 자동모델향상기법을 적용할 시 예상되는 문제점에 대하여 토의하였다.

Many researchers have proved that risk measurement of information systems is a very effective tool for improving confidence of information systems. However, information system risk in Korea still includes many subjective judgements. This study deals with applying a quantitative model to improve risk measurement of information system quality. First of all, we have come up with solutions to improve the evaluation efficiency on risk measurement. We have merged the risk guidelines of COBIT and CMM, and developed a quantified evaluation scheme that call by risk point. We have proved the validity of this model by interviews with experts and by case studies.

공급망상에서 ATP는 단순히 고객에게 납기를 확약해 주는 고객 서비스 기능이 아니다. 이것은 공급 망상에서 ATP Rule을 기반으로 하여 수요와 공급 일치에 도달하기 위한 핵심 기능이다 따라서 SCM Solution을 이용하여 공급 체인 전반에 걸쳐 제품 가용성에 대한 즉시 및 동시 엑세스를 관리하여 기업의 납기 일의 정확도에 대한 최고의 확신을 가져올 수 있으며, SCM Solution을 통해 주문이나 예측 수주로 인하여 새로운 수요가 제품 가용성에 미칠 영향을 결정할 수 있다. 본 논문에서는 공급체인 전체의 통합관리 솔루션을 통하여 SCM에 대한 필요성을 정리하고 ATP관련 데이터를 분석을 수행한다. 이 것을 바탕으로 고객관계 관리( Customer Relationship Management)와 연계하여 세부데이터의 흐름 및 고객 가치를 향상 할 수 있는 ATP Rule을 정의한 후, 본 논문에서는 공급망상에 ATP Rule을 적용하여 ATP관련 데이터를 유연성 있게 취합할 수 있는 방안과 분류체계를 제시한 다단계 ATP모형을 제시 한다.

딥러닝 모델은 주어진 학습용 데이터에서 탐지하고자 하는 물체의 특징을 추출하기 때문에, 딥러닝 모델 학습을 위한 학습용 데이터 구축은 매우 중요하다. 본 연구에서는 균열을 탐지하는 딥러닝 모델의 성능을 향상시키기 위해, 실제 콘크리트 구조물이나 아스팔트 도로 표면에서 자주 발견될 수 있는 나뭇가지, 거미줄, 전선 등을 학습 데이터에 자동으로 포함시키고, negative 영역으로 분류하는 알고리즘을 개발하였다. 제안된 알고리즘을 사용하여 학습된 딥러닝 모델을 실제 도로 표면에 발생한 균열 탐지에 적용하여 실제 균열 탐지에 사용될 수 있음을 보였다.

Last few years, many researches on deep learning-based crack detection model have been reported in order to develop an efficient structure inspection method. While developing crack detection deep learning model, many research results reported the importance of the training data. Since most of the research results only qualitatively discussed the importance of training data, this study examine the influence of the training data by experiment, especially in the case of negative samples such as construction joint, spider web and concrete blocks.

This research presents an method to select explanatory variables to develop deterioration models for bridges. The ranking of candidate variables are estimated using the covariance analysis between the condition ratings and inspection data. To determine the most stationary set of explanatory variables, weighting factors associated with the investigated year and ranking are introduced. Yearly inspected bridge data are classified into multiple subsets using explanatory variables and the deterioration model is developed for each. The condition ratings for individual bridges are predicted using the deterioration model. The prediction error comparison shows that the more representative and stationary explanatory variables are selected when weighing factors are considered.

For a mobile robot that travels along a terrain consisting of various geology, information on tire force and friction coefficient between ground and wheel is an important factor. In order to estimate the lateral force between ground and wheel, a lot of information about the model and the surrounding environment of the vehicle is required in conventional method. Therefore, in this paper, we are going to estimate lateral force through simple model (Minimal Argument Lateral Slip Curve, MALSC) using only minimum data with high estimation accuracy and to improve estimation reliability of the friction coefficient by using the estimated lateral force data. Simulation is carried out to analyze the correlation between the longitudinal and transverse friction coefficients and slip angles to design the simplified lateral force estimation model by analysing simulation data and to apply it to the actual field environment. In order to verify the validity of the equation, estimation results are compared with the conventional method through simulation. Also, the results of the lateral force and friction coefficient estimation are compared from both the conventional method and the proposed model through the actual robot running experiments.

Sensitivity analysis of the WRF model according to the impact of nudging (e.g., nudging techniques and application domains) was conducted during high nocturnal ozone episode to improve the prediction of the regional ozone concentration in the southeastern coastal area of the Korean peninsula. The analysis was performed by six simulation experiments: (1) without nudging (e.g., CNTL case), (2) with observation nudging (ONE case) to all domains (domain 1∼4), (3) with grid nudging (GNE case) to all domains, (4)∼(6) with grid nudging to domain 1, domain 1∼2 and domain 1∼3, respectively (GNE-1, GNE-2, GNE-3 case). The results for nudging techniques showed that the GNE case was in very good agreement with those observed during all analysis periods (e.g., daytime, nighttime, and total), as compared to the ONE case. In particular, the large effect of grid nudging on the near-surface meteorological factors (temperature, relative humidity, and wind fields) was predicted at the coastline and nearby sea during daytime. The results for application domains showed that the effects of nudging were distinguished between the meteorological factors and between the time periods. When applied grid nudging until subdomain, the improvement effects of temperature and relative humidity had differential tendencies. Temperature was increased for all time, but relative humidity was increased in daytime and was decreased in nighttime. Thus, GNE case showed better result than other cases.