• Title/Summary/Keyword: 공학적 경험모델

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Prediction of burial depth over time evolution at seabed (해저면에서 시간변화에 따른 매몰심 변화 예측)

  • Seungho Lee;Hyoseob Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.476-476
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    • 2023
  • 해저면에 놓인 물체는 주변의 국소 흐름 변화에 의해 해저면 전단응력이 국부적으로 변화하는 과정에서 침식과 퇴적이 발생하게 되면서 해저면 지형의 변화에 의해 움직임이 발생한다. 이때 물체의 크기, 무게, 밀도와 형상에 따라 구름, 미끄러짐, 액상화 현상 또한 동반 될 수 있다. 본 연구에서는 해저면에 놓인 물체의 시간변화에 따른 매몰심 변화를 예측하고자 하였다. 물체는 원형 단면의 실린더 형태로 고려했다. 시간변화에 따른 매몰심 변화를 평형 매몰심으로의 접근속도에 관련된 인수와 매몰심 변화량으로 기본방적식을 구성하였고, 이를 유한 차분식으로 수립하였다. 최종 평형 매몰심 계산은 Friedrichs et al.(2016)의 경험식을 사용하였다. 앞선 연구에서 김효섭 등(2016)은 시간에 따른 세굴심 변화 모델 STEP-K를 제시한 바 있다. 시간변화에 따른 연직방향 실린더 주변에서의 국소세굴심을 예측하는 기법으로, 해저면에 놓인 수평방향 물체 주변의 매몰심 발달을 예측하기 위해 매몰 발생에 대한 시간의 척도를 새롭게 제안하였다. STEP-K에서 사용했던 KC수를 대신해 흐름-단주기 파랑 공조시의 해저면의 전단응력을 대표할 수 있는 대표전단응력을 사용할 수 있게 하였다. 보정계수를 통해 현장 또는 실험실 단위의 자료가 가용한 경우 식을 보정할 수 있다. 제안한 매몰심 예측기법은 Elmore et al.(2007)의 매몰실험 관측자료를 활용하여 보정하였다. 결과적으로 보정자료에 대한 시간에 따른 매몰심의 변화양상을 잘 재현하였으며, 향후 우리나라 해양환경 자료를 활용한 보정을 통해 적용성을 높일 수 있을 것으로 기대된다.

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A Development of Quantitative Analysis Model for the Policy Analysis in Feasibility Study Using the Performance Assessment Method (성능평가기법을 활용한 타당성조사 정책적 분석단계의 정량적 의사결정모델 개발 - 복수대안의 타당성 평가를 중심으로 -)

  • Lim, Yong-Soo;Song, Hyun-Young;Jeong, Han-Kee;Jeong, Min-Chul;Kong, Jung-Sik
    • Korean Journal of Construction Engineering and Management
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    • v.12 no.2
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    • pp.89-100
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    • 2011
  • As an impactive factor on industries and national economy, The Social Overhead Capital(SOC) is major factor to determine the national competitiveness and the investment of SOC is essential for its economic growth. Accordingly, introduction of the preliminary feasibility study and establishment of legal institutionalization and evaluation system has been carried out and reviewed since 1999. Nevertheless of these efforts, basic problems such as lack of scientific method for investment evaluation and loss of effectiveness on feasibility studies are continuously being brought up. Moreover, as the preliminary study to improve the mentioned problems is mainly focused on the economic and estimated demand analysis, the study of policy analysis, the most important phase during a feasibility study, is still insufficient. Therefore, in this paper, a quantitative decision-making model, to which the performance assessment method of Value Engineering(VE) is applied, is developed and proposed to improve the policy analysis of (preliminary) feasibility study that requires combining with relative studies, to induce quantitative analysis method, and to contribute the improvement of value on the political aspect for SOC investment goals and use as a strategic decision-making method by systematic analysis.

A study on the rock mass classification in boreholes for a tunnel design using machine learning algorithms (머신러닝 기법을 활용한 터널 설계 시 시추공 내 암반분류에 관한 연구)

  • Lee, Je-Kyum;Choi, Won-Hyuk;Kim, Yangkyun;Lee, Sean Seungwon
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.469-484
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    • 2021
  • Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, Vp, Vs, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

Dynamic Adjustment of the Pruning Threshold in Deep Compression (Deep Compression의 프루닝 문턱값 동적 조정)

  • Lee, Yeojin;Park, Hanhoon
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.3
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    • pp.99-103
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    • 2021
  • Recently, convolutional neural networks (CNNs) have been widely utilized due to their outstanding performance in various computer vision fields. However, due to their computational-intensive and high memory requirements, it is difficult to deploy CNNs on hardware platforms that have limited resources, such as mobile devices and IoT devices. To address these limitations, a neural network compression research is underway to reduce the size of neural networks while maintaining their performance. This paper proposes a CNN compression technique that dynamically adjusts the thresholds of pruning, one of the neural network compression techniques. Unlike the conventional pruning that experimentally or heuristically sets the thresholds that determine the weights to be pruned, the proposed technique can dynamically find the optimal thresholds that prevent accuracy degradation and output the light-weight neural network in less time. To validate the performance of the proposed technique, the LeNet was trained using the MNIST dataset and the light-weight LeNet could be automatically obtained 1.3 to 3 times faster without loss of accuracy.

Real Time SW Sizing Model for FP-Based Fintech Software Development Project (FP 기반의 핀테크 소프트웨어 개발 프로젝트 실시간 규모 산정 모델)

  • Koo, Kyung-Mo;Yoon, Byung-Un;Kim, Dong-Hyun
    • Journal of Convergence for Information Technology
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    • v.11 no.10
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    • pp.36-44
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    • 2021
  • Estimation on SW Sizing applied to fintech is very difficult, a task requiring long time, it is difficult for client companies and developer companies to accurately calculate the size of software development. The size is generally estimated based on the experience of project managers and the general functional scoring method. In this paper, propose a model that can be applied to fintech development projects by quantitatively calculating the required functions from the user's point of view, measuring the scale, and calculating the scale in real time. Through the proposed model, the amount of work can be estimated prior to development and the size can be measured, and the M/M and the estimated quotation amount can be calculated based on the program list by each layer. In future studies, by securing size computation data on existing the Fintech Project in mass, research on accurate size computation would be required.

Spudsville: Designing a Minecraft Game for learning teaching English as a Second Language (스퍼드빌: 제2언어로서의 영어학습을 위한 마인크래프트 게임 설계)

  • Baek, Youngkyun;Kim, Jeongkyoum;Sam, Eisenberg
    • Journal of Convergence for Information Technology
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    • v.12 no.4
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    • pp.143-157
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    • 2022
  • The aim of this study is to design Spudsville, an immersive game environment in Minecraft that can effectively help learners acquire the English language. To create a successful learning experience using Minecraft, the researchers adopted the Agile Model and the Design Thinking approach. The researchers first conducted an analysis through an extensive literature review in order to assess the learners' needs. Afterwards, they designed and developed a Minecraft world based on the data collected during the analysis phase. The researchers learned that implementing constructivist and behaviorist approaches has benefits, even though applying a cognitivist-learning model to Spudsville could have provided the researchers with more insight on how learner processes information. Making these adjustments could improve Spudsville's effectiveness and could potentially help the ways in which gamified learning aids with language acquisition.

Dental Surgery Simulation Using Haptic Feedback Device (햅틱 피드백 장치를 이용한 치과 수술 시뮬레이션)

  • Yoon Sang Yeun;Sung Su Kyung;Shin Byeong Seok
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.6
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    • pp.275-284
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    • 2023
  • Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.

Analysis of Per-Position Characteristics Recognized by Tenure Women Managers (근속 여성관리자가 인식하는 직위별 특성 분석)

  • Jeong, Ji-ae
    • Journal of Practical Engineering Education
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    • v.11 no.1
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    • pp.105-115
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    • 2019
  • This study focused on the importance of job position as a role model for female career adaptation. To do this, we used the KWMP data to conduct a Multinomial logit analysis to examine the influence factors of the tenure women managers. As a result, first, section chief position showed a low level of life satisfaction and showed difficulty of beginner's manager. Second, it is predicted that the position of the Deputy Head of Department will establish the identity of work as an intermediate manager. Third, head of department Director showed a high age, target status, possibility of achieving the target, and duration of the next job. Fourth, executive level has the least average experience of discrimination on monthly average wage. It was suggested that it is important to develop individual career by recognizing that the organizational atmosphere and personnel management are lower than those of the other positions. It was found that age, organizational atmosphere and personnel management, goal status, possibility of achieving goals, next job tenure period, monthly average wage, welfare, and life satisfaction factors were the most influential factors in women career adjustment. Finally, implications and limitations were discussed based on the results of this study.

Analysis of the Good Job Condition of Which Young People Think and the Impact of Job Search Behavior on Employment (청년들이 생각하는 좋은 일자리 조건과 직업탐색행동이 취업에 미치는 영향 분석)

  • Chang, Wook-hee
    • Journal of Practical Engineering Education
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    • v.13 no.2
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    • pp.351-368
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    • 2021
  • This paper is meaningful in that it empirically studies the good job condition of which young people think and the impact of job search behavior on employment. In addition, employment status and additional job search performance were set as performance variables. The main research results of this study are as follows. First, as for the good job condition considered by young people, wages and salaries in terms of companies, job stability in terms of environment, and work-life balance in terms of individuals were found. Second, job search behavior was found to be a key variable influencing employment status and job search performance. Third, it was found that job-search stress injures employment. Finally, work experience promotes employment and job search performance. Therefore, to increase the employment success rate of young people, above all, various supports for increasing the frequency of young job seekers' active job search behavior are needed. To this end, it suggests that it is necessary to develop a customized youth policy service model and to provide systematic services to meet the needs of young people.

The Statistical Model of Fourier Acceleration Spectra according to Seismic Intensities for Earthquakes in Korea (국내 지진의 진도별 가속도 푸리에스펙트럼 통계모델)

  • Yun, Kwan-Hee;Pakr, Dong-Hee;Park, Se-Moon
    • Journal of the Earthquake Engineering Society of Korea
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    • v.13 no.6
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    • pp.11-25
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    • 2009
  • A method of instrumentally estimating the seismic intensity (MMI) based on Fourier Acceleration Spectrum, which is the so-called 'FAS MMI method' of Sokolov and Wald (2002), was considered for its applicability to Korea. In order to implement the FAS MMI method, the empirical models of mean (m) and standard deviation (${\sigma}$) for Korea were derived for MMI ${\leq}$ IV according to individual seismic intensity by using the site-consistent horizontal FAS of 580 records from 65 isoseismal maps prepared based on the reported MMI of Korea Meteorological Administration. The site-consistent FAS at a site were obtained by correcting the observed FAS for the difference of the site amplification function relative to that of the target site of Class D station (Yun and Suh, 2007) which was evaluated to be a representative site for the generic soil profile of Korea. The FAS m model for MMI ${\leq}$ IV follows the overall linear relation in log space according to seismic intensities, featuring the FAS mean model for MMI = IV similar to that of the global model of Sokolov and Wald (2002). The ${\sigma}$-values of the FAS model are found to be greater than those of the global model for MMI ${\geq}$ V, while significantly lower than those of the global model for MMI = IV.