Recent earthquakes in Korea, like Gyeongju and Pohang, have highlighted the need for accurate seismic hazard assessment. The lack of substantial ground motion data necessitates stochastic simulation methods, traditionally used with a simplistic point-source assumption. However, as earthquake magnitude increases, the influence of finite faults grows, demanding the adoption of finite faults in simulations for accurate ground motion estimates. We analyzed variations in simulated ground motions with and without the finite fault method for earthquakes with magnitude (Mw) ranging from 5.0 to 7.0, comparing pseudo-spectral acceleration. We also studied how slip distribution and hypocenter location affect simulations for a virtual earthquake that mimics the Gyeongju earthquake with Mw 5.4. Our findings reveal that finite fault effects become significant at magnitudes above Mw 5.8, particularly at high frequencies. Notably, near the hypocenter, the virtual earthquake’s ground motion significantly changes using a finite fault model, especially with heterogeneous slip distribution. Therefore, applying finite fault models is crucial for simulating ground motions of large earthquakes (Mw ≥ 5.8 magnitude). Moreover, for accurate simulations of actual earthquakes with complex rupture processes having strong localized slips, incorporating finite faults is essential even for more minor earthquakes.

The stochastic method is applied to simulate strong ground motions at seismic stations of seven metropolises in South Korea, creating an earthquake scenario based on the causative fault of the 2016 Gyeongju earthquake. Input parameters are established according to what has been revealed so far for the causative fault of the Gyeongju earthquake, while the ratio of differences in response spectra between observed and simulated strong ground motions is assumed to be an adjustment factor. The calculations confirm the applicability and reproducibility of strong ground motion simulations based on the relatively small bias in response spectra between observed and simulated strong ground motions. Based on this result, strong ground motions by a scenario earthquake on the causative fault of the Gyeongju earthquake with moment magnitude 6.5 are simulated, assuming that the ratios of its fault length to width are 2:1, 3:1, and 4:1. The results are similar to those of the empirical Green’s function method. Although actual site response factors of seismic stations should be supplemented later, the simulated strong ground motions can be used as input data for developing ground motion prediction equations and input data for calculating the design response spectra of major facilities in South Korea.

Recently, a study of prognosis and health management (PHM) was conducted to diagnose failure and predict the life of air craft engine parts using sensor data. PHM is a framework that provides individualized solutions for managing system health. This study predicted the remaining useful life (RUL) of aeroengine using degradation data collected by sensors provided by the IEEE 2008 PHM Conference Challenge. There are 218 engine sensor data that has initial wear and production deviations. It was difficult to determine the characteristics of the engine parts since the system and domain-specific information was not provided. Each engine has a different cycle, making it difficult to use time series models. Therefore, this analysis was performed using machine learning algorithms rather than statistical time series models. The machine learning algorithms used were a random forest, gradient boost tree analysis and XG boost. A sliding window was applied to develop RUL predictions. We compared model performance before and after applying the sliding window, and proposed a data preprocessing method to develop RUL predictions. The model was evaluated by R-square scores and root mean squares error (RMSE). It was shown that the XG boost model of the random split method using the sliding window preprocessing approach has the best predictive performance.

The stochastic point-source model has been widely used in generating artificial ground motions, which can be used to develop a ground motion prediction equation and to evaluate the seismic risk of structures. This model mainly consists of three different functions representing source, path, and site effects. The path effect is used to emulate decay in ground motion in accordance with distance from the source. In the stochastic point-source model, the path attenuation effect is taken into account by using the geometrical attenuation effect and the inelastic attenuation effect. The aim of this study is to develop accurate equations of ground motion attenuation in the Korean peninsula. In this study, attenuation was estimated and validated by using a stochastic point source model and observed ground motion recordings for the Korean peninsula.

농업은 고용, 식량 및 생계를 목적으로 하는 카메룬 경제의 중심이다. 그러나 카메룬 농업은 낮은 생산성, 비효율성 및 수입에 의존하여 전염병에 시달리고 있다. 이러한 이유로 본 연구는 카메룬 북서부 지역의 쌀 농가의 기술적 효율성을 조사했다. 구조화된 설문지와 인터뷰를 사용하여 144명의 농부로부터 데이터를 수집했다. 기술 통계 및 확률적 프런티어 분석을 사용하여 데이터를 분석하였다. 확률적 프런티어 분석의 결과는 분산 매개 변수 (시그마 제곱 및 감마)가 통계적으로 유의하다는 것을 보여준다. 농장 규모, 비료, 노동 및 제초제의 계수는 긍정적이고 중요했다. 평균 기술 효율성 수준이 84%로 나타낸 것은 가용 자원을 효율적으로 활용한다면 쌀 농민의 기술 효율성을 16%로 증가할 수 있다. 비효율성 모델은 신용 액세스가 기술적 비효율 성과 부정적인 관련이 있는 중요한 요소임을 보여준다. 이 결과는 농민에게 생산성을 향상시키기 위해 신용을 제공하려는 정부의 노력 (SEMRY, UNVDA, ARFIC및 2세대 농업)과 일치한다.

Process mining is an analytical technique aimed at obtaining useful information about a process by extracting a process model from events log. However, most existing process models are deterministic because they do not include stochastic elements such as the occurrence probabilities or execution times of activities. Therefore, available information is limited, resulting in the limitations on analyzing and understanding the process. Furthermore, it is also important to develop an efficient methodology to discover the process model. Although genetic process mining algorithm is one of the methods that can handle data with noises, it has a limitation of large computation time when it is applied to data with large capacity. To resolve these issues, in this paper, we define a stochastic process tree and propose a tabu search-genetic process mining (TS-GPM) algorithm for a stochastic process tree. Specifically, we define a two-dimensional array as a chromosome to represent a stochastic process tree, fitness function, a procedure for generating stochastic process tree and a model trace as a string of activities generated from the process tree. Furthermore, by storing and comparing model traces with low fitness values in the tabu list, we can prevent duplicated searches for process trees with low fitness value being performed. In order to verify the performance of the proposed algorithm, we performed a numerical experiment by using two kinds of event log data used in the previous research. The results showed that the suggested TS-GPM algorithm outperformed the GPM algorithm in terms of fitness and computation time.

충돌 피항 동작은 선박 간 끊임없이 영향을 주고받는다. 특히 다수의 선박이 조우하는 경우, 상대 선박의 피항 의도를 파악하고 서로에게 얼마나 영향을 미치는 지를 파악하는 것은 어려운 일이다. 이를 위해 분산 확률 탐색 알고리즘이 제안되었다. 분산 확률 탐색 알고리즘은 이웃 선박과 반복적인 메시지 교환을 통해 비용을 가장 크게 낮출 수 있는 코스를 탐색 후 확률과 제한 조건에 따라 기존의 코스를 유지할지 아니면 새로운 코스를 선택할지를 결정한다. 그러나 분산 확률 탐색 알고리즘에 사용된 파라미터가 충돌 피항에 어떠한 영향을 미치는지 증명되지 않았다. 본 논문에서는 분산 확률 탐색 알고리즘의 파라미터와 가중치가 충돌 피항에 어떠한 영향을 미치는지 분석하였다. 또한 타선과의 피항 거리를 조절하기 위한 충격 흡수 영역을 소개한다. 실험 방법은 두 선박이 조우할 수 있는 세 가지 상황, 즉 정면에서 조우하는 상황, 횡단하는 상황, 추월하는 상황에 파라미터와 가중치의 변수들을 조합하여 실험을 진행하였다. 각 상황 당 8,000회, 총 24,000회의 실험이 진행되었다. 실험 결과 모든 실험에서 한 건의 충돌도 발생하지 않았다. 선박이 목적지에 큰 가중치를 줄 경우, 즉 이기적인 행동을 할 경우, 비용은 증가함을 보였다. 타선의 움직임을 더 길게 예측할수록 항행 거리, 메시지 교환 횟수는 작아지는 경향을 보였다.

다수의 선박이 조우하였을 경우, 충돌 피항을 위해 상대 선박의 의도를 파악하는 것은 매우 중요한 문제이다. 또한 다수의 선박의 의도를 동시에 고려하여 충돌 피항 계획을 세우는 것은 항해사에게 큰 부담이 될 수 있다. 이를 위해 분산 알고리즘이 제안 되었다. 분산 알고리즘은 각각의 선박이 다수의 상대 선박과 정보 교환을 통해 안전한 코스를 탐색할 수 있도록 한다. 본 논문에서는 분산 알고리즘의 하나인 분산 확률 탐색 알고리즘을 선박 충돌 피항에 적용하였다. 분산 확률 탐색 알고리즘에서 선박은 비용 감소가 가장 큰 코스와 기존의 코스를 확률과 제한 조건에 따라 선택한다. 분산 확률 탐색 알고리즘은 확률과 제한 조건에 따라 다섯 가지 종류로 나눠진다. 본 논문에서는 다섯 가지 종류의 분산 확률 탐색 알고리즘을 선박 충돌 피항을 위해 적용하였으며 선박 충돌 피항에 미치는 영향을 분석하였다. 또한 어떠한 분산 확률 탐색 알고리즘이 충돌 피항에 적합한지를 실험하였다. 실험 결과 다섯 가지 버전의 분산 확률 탐색 알고리즘에서 A와 B방식이 효과적으로 선박 충돌 피항을 수행하였다. 본 알고리즘은 분산 시스템 환경에서 선박 충돌 방지를 위해 적용 가능할 거라 기대된다.

PURPOSES: This paper develops a new stochastic approach to analyze the pavement-vehicle interaction model with a certain roughness and elasticity for the pavement foundation, thereby accommodating the deflection of the pavement, and to identify the road subsidence zone represented with a sudden changes in the elasticity of the foundation. METHODS: In the proposed model, a quarter-car model was combined with a filtered white noise model of road roughness and a two-layer foundation (Euler-Bernoulli beam for the top surface and Winkler foundation to represent the sub-structure soil). An augmented state-space model for the subsystems was formulated. Then, because the input is White noise and the system is represented as a single system, the Lyapunov equation governing the covariance of the system’s response was solved to obtain a structurally weak zone index (WZI). RESULTS: The results showed that the WZI from the pavement-vehicle interaction model is sensitive enough to identify road subsidence. In particular, the WZI rapidly changed with a small change in foundation elasticity, indicating that the model has the potential to detect road subsidence in the early stage. CONCLUSIONS: Beacause of the simplicity of the calculation, the proposed approach has potential applications in managing road conditions while a vehicle travels along the road and detecting road subsidence using a device with an on-board computational capability, such as a smart phone.

본 연구에서는 역량스펙트럼법을 이용해 얻어진 구조물의 성능점을 확률적으로 평가하는 방법을 제시하였다. ATC-40에 따라 역량스펙트럼법을 이용하여 4층 1경간 철골구조물의 성능점을 산정하였다. 요구스펙트럼을 이용하여 구조물의 성능한계를 초과하는지 여부를 분석하기 위해 구조부재의 소성변형각으로부터 정의되는 구조물의 성능한계에 대해 한계변위를 도출하였다. 또한 설계응답스펙트럼과 유사한 응답스펙트럼을 가지는 인공지진파 30개를 선정하여 스펙트럼 가속도에 따른 각 성능한계의 초과여부를 통해 fragility curve를 도출하였다. 관측된 초과확률을 이용하여 fragility curve를 도출하기 위해 maximum likelihood method를 사용하였다. 각 성능한계점에 대응하는 설계응답스펙트럼의 응답가속도값에서 성능한계점을 초과할 확률은 존재하는 것으로 확인되었다. 본 방식은 구조물의 성능점에 대해 지진파의 불확실성을 고려한 확률적 평가가 가능하고, 시간증분해석이 필요하지 않아 해석시간을 상당부분 단축시킬 수 있다는 장점이 있다.

The purpose of this study is to analyze the efficiency of distant-water longline fishing vessels in the Pacific Ocean and the gap in efficiencies among individual vessels. In order to estimate the efficiency, the dependent variable is set as an amount of catch and independent variables include number of crew, number of hooks, number of vessel size, and vessels engine power associated with fishing activities of distant water longline fisheries. Analytical result was shown as follows: first, the average efficiency of distant-water longline fishing vessels in the Pacific Ocean was found to be 94%. Second, the number of hooks were found to be statistically significant in each input variable and the appropriate control of the number of hooks would be expected to have a positive effect on the efficiency. Third, the relationship between the age of a vessel and the efficiency was not found statistically.

PURPOSES : This study is aimed at development of a stochastic pavement deterioration forecasting model using National Highway Pavement Condition Index (NHPCI) to support infrastructure asset management. Using this model, the deterioration process regarding life expectancy, deterioration speed change, and reliability were estimated. METHODS: Eight years of Long-Term Pavement Performance (LTPP) data fused with traffic loads (Equivalent Single Axle Loads; ESAL) and structural capacity (Structural Number of Pavement; SNP) were used for the deterioration modeling. As an ideal stochastic model for asset management, Bayesian Markov multi-state exponential hazard model was introduced. RESULTS: The interval of NHPCI was empirically distributed from 8 to 2, and the estimation functions of individual condition indices (crack, rutting, and IRI) in conjunction with the NHPCI index were suggested. The derived deterioration curve shows that life expectancies for the preventive maintenance level was 8.34 years. The general life expectancy was 12.77 years and located in the statistical interval of 11.10-15.58 years at a 95.5% reliability level. CONCLUSIONS : This study originates and contributes to suggesting a simple way to develop a pavement deterioration model using the total condition index that considers road user satisfaction. A definition for level of service system and the corresponding life expectancies are useful for building long-term maintenance plan, especially in Life Cycle Cost Analysis (LCCA) work.

In recent years, business environment is faced with multi uncertainty that have not been suffered in the past. As supply chain is getting expanded and longer, the flow of information, material and production is also being complicated. It is well known that development service industry using application software has various uncertainty in random events such as supply and demand fluctuation of developer’s capcity, project effective date after winning a contract, manpower cost (or revenue), subcontract cost (or purchase), and overrun due to developer’s skill-level. This study intends to social contribution through attempts to optimize enterprise’s goal by supply chain management platform to balance demand and supply and stochastic programming which is basically applied in order to solve uncertainty considering economical and operational risk at solution supplier. In Particular, this study emphasizes to determine allocation of internal and external manpower of developers using S&OP (Sales & Operations Planning) as monthly resource input has constraint on resource’s capability that shared in industry or task. This study is to verify how Stochastic Programming such as Markowitz’s MV (Mean Variance) model or 2-Stage Recourse Model is flexible and efficient than Deterministic Programming in software enterprise field by experiment with process and data from service industry which is manufacturing software and performing projects. In addition, this study is also to analysis how profit and labor input plan according to scope of uncertainty is changed based on Pareto Optimal, then lastly it is to enumerate limitation of the study extracted drawback which can be happened in real business environment and to contribute direction in future research considering another applicable methodology.

본 논문에서는 저차원 확률 함수를 사용하여 연속적인 선형 공극비 기울기를 갖는 기능경사재료 형태의 가상 시편을 제작 하였다. 실제 물 시멘트 비가 다른 두 종류 시멘트 풀 시편의 X-선 CT 단면 이미지를 통해 3차원 공극 분포 모델을 제작하 여 이를 기반으로 가상 시편을 제작하였다. 가상 시편이 두 실제 시편 사이에 위치하도록 공극 분포 특성을 저차원 확률 함 수와 공극비 기울기로 구성하였다. 공극 분포의 기울기는 연속적인 형태의 수직 방향의 선형 공극비 기울기로 구현하며, 이 를 위해 확률적 최적화의 목적 함수로 저차원 확률 함수와 공극비 기울기에 관한 함수를 사용하였다. 가상 시편 내 공극 분 포 특성 확인을 위해 본 연구에서는 투기율 분석을 유한요소해석을 통해 수행하였다. 공극 분포 특성과 투기율 해석 결과를 비교하여 가상 시편이 갖는 공극 분포 특성이 투기율에 미치는 영향을 확인하고, 투기율의 실제 실험 결과와 해석 결과의 비 교를 통해 해석 결과의 타당성을 입증하였다.

기후변화 등으로 인해 폭풍해일의 피해가 증대하고 있어, 재현기간에 기초한 폭풍해일고의 추정은 새로운 연안 구조물의 설 계 및 개발 관점뿐만 아니라 기존 구조물의 안정성을 평가하는데 중요하다. 현재 우리나라의 설계해면은 과거 태풍을 이용한 극치 분 석을 이용하여 추정되지만, 이 경우 자료의 부족으로 재현기간이 큰 경우 오차의 원인이 될 수 있으며, 추계학적 접근은 하나의 대안 이 될 수 있다. 본 연구에서는 폭풍해일에 취약한 경기만 지역의 폭풍 해일고 추정을 위해 결정론적 수치 모형인 SLOSH 모형과 가상 태풍을 위한 몬테카를로 시뮬레이션의 결합을 통하여 추계학적 접근 방법을 제시하였다. 모멘트법에 의해 결정된 파라메터를 이용하 여 Weibull 분포를 통해 추계학적 해일고가 추정되었으며, 제시된 폭풍 해일고는 연안 지역 구조물 설계를 위한 대안이 될 수 있다.

We develop an optimization algorithm for a periodic review inventory system under a stochastic budget constraint. While most conventional studies on the periodic review inventory system consider a simple budget limit in terms of the inventory investment being less than a fixed budget, this study adopts more realistic assumption in that purchasing costs are paid at the time an order is arrived. Therefore, probability is employed to express the budget constraint. That is, the probability of total inventory investment to be less than budget must be greater than a certain value assuming that purchasing costs are paid at the time an order is arrived. We express the budget constraint in terms of the Lagrange multiplier and suggest a numerical method to obtain optional values of the cycle time and the safety factor to the system. We also perform the sensitivity analysis in order to investigate the dependence of important quantities on the budget constraint. We find that, as the amount of budget increases, the cycle time and the average inventory level increase, whereas the Lagrange multiplier decreases. In addition, as budget increases, the safety factor increases and reaches to a certain level. In particular, we derive the condition for the maximum safety factor.

본 연구에서는 뇌우 돌풍 발생일의 시계열을 통해 뇌우 돌풍 발생에 대한 전조현상을 분석하였다. 돌풍이 관측된 날에 뇌전현상의 유무에 따라 뇌우에 의한 돌풍과 다른 요인으로 인해 발생한 돌풍을 분류하였으며, 뇌우 돌풍 발생일의 시계열을 분석하여 뇌우 돌풍 발생 이전에 급격한 풍속이 상승하는 비정상적(non-stationary) 시계열 특성을 보임을 확인하였다. 뇌우 돌풍 발생 시점을 기준으로 이전 풍속의 이동평균을 이용하여 풍속의 급격한 상승시점을 분석 하였으며, 이동평균의 시계열을 일반적 함수형태로 표현하였다. 이 결과를 이용하여 뇌우 돌풍 발생 이전 급격한 풍속이 상승하는 시점의 확률분포를 분석하고 이동평균의 단위시간 별 뇌우 돌풍 발생확률에 의한 위험평가 기법을 제시하였다.

We estimated decreasing rate of indoor air pollutants with are airborne bacteria, airborne fungi, formaldehyde, total volatile organic compounds, PM10, and PM2.5 in 10 children’s hospitals and 6 childbirth houses located in Seoul and Gyeonggi-do from November to December in 2012. Sectional period was respectively divided for operating and non-operating the air cleaners. There was a trend that concentration of surveyed pollutants in children’s hospitals and childbirth houses during operating period decreased among indoor air. We used Monte-Calro simulation to remove uncertainty and identify efficiency of eliminated pollutants such as surveyed pollutants by the air cleaners. Average efficiency of removal were 61.39 ± 21.42% for airborne bacteria, 71.77 ± 19.65% for airborne fungi, 73.37 ± 24.62% for formaldehyde, 71.20 ± 25.96% for total volatile organic compounds, 65.16 ± 23.80% for PM10, and 71.06 ± 23.97% for PM2.5.