• Geomechanics and Engineering
• /
• 제30권6호
• /
• pp.489-502
• /
• 2022

In this study, a Gaussian process regression (GPR) model as well as six GPR-based metaheuristic optimization models, including GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, and GPR-SSO, were developed to predict fly-rock distance in the blasting operation of open pit mines. These models included GPR-SCA, GPR-SSO, GPR-MVO, and GPR. In the models that were obtained from the Soungun copper mine in Iran, a total of 300 datasets were used. These datasets included six input parameters and one output parameter (fly-rock). In order to conduct the assessment of the prediction outcomes, many statistical evaluation indices were used. In the end, it was determined that the performance prediction of the ML models to predict the fly-rock from high to low is GPR-PSO, GPR-GWO, GPR-MVO, GPR-MFO, GPR-SCA, GPR-SSO, and GPR with ranking scores of 66, 60, 54, 46, 43, 38, and 30 (for 5-fold method), respectively. These scores correspond in conclusion, the GPR-PSO model generated the most accurate findings, hence it was suggested that this model be used to forecast the fly-rock. In addition, the mutual information test, also known as MIT, was used in order to investigate the influence that each input parameter had on the fly-rock. In the end, it was determined that the stemming (T) parameter was the most effective of all the parameters on the fly-rock.

• Nuclear Engineering and Technology
• /
• 제54권12호
• /
• pp.4698-4707
• /
• 2022

As part of the ICRP Task Group 103 project, we developed ten thyroid models for the pediatric mesh-type reference computational phantoms (MRCPs). The thyroid is not only a radiosensitive target organ needed for effective dose calculation but an important source region particularly for radioactive iodines. The thyroid models for the pediatric MRCPs were constructed by converting those of the pediatric voxel-type reference computational phantoms (VRCPs) in ICRP Publication 143 to a high-quality mesh format, faithfully maintaining their original topology. At the same time, we improved several anatomical parameters of the thyroid models for the pediatric MRCPs, including the mass, overlying tissue thickness, location, and isthmus dimensions. Absorbed doses to the thyroid for the pediatric MRCPs for photon external exposures were calculated and compared with those of the pediatric VRCPs, finding that the differences between the MRCPs and VRCPs were not significant except for very low energies (<0.03 MeV). Specific absorbed fractions (target ⟵ thyroid) for photon internal exposures were also compared, where significant differences were frequently observed especially for the target organs/tissues close to the thyroid (e.g., a factor of ~1.2-~327 for the thymus as a target) due mainly to anatomical improvement of the MRCP thyroid models.

• 아태비즈니스연구
• /
• 제15권2호
• /
• pp.207-222
• /
• 2024

Purpose - This study investigates whether the lagged price difference ratio between preferred and common stocks is related to the return and closing price of the preferred stock using three panel models. Design/methodology/approach - As a first step, we use a two-way fixed effect panel model with stationary preferred stock returns as a dependent variable. For robustness, we then apply the autoregressive distributed lag model (ARDL) and error correction model (ECM) with nonstationary closing prices of the preferred stocks as a dependent variable and compare the results of each model. The ARDL and ECM models provide an advantage of estimating a long-run equilibrium equation together if a long-run relationship exists between the two time-series variables compared to the fixed effect model. Findings - Our sample consists of 107 preferred stocks with at least four years of daily observations as of the end of December 2023. The coefficients of the error correction terms in the ARDL and ECM models are highly statistically significant, approximately -0.08. This indicates that the disequilibrium between the closing prices of common and preferred stocks adjusts by about 8% per day toward equilibrium. In all three models, the price difference ratio on day t-1 was statistically significant in explaining the preferred stock returns or closing prices on day t, implying that trading based on the previous day's price difference ratio is effective for one day. Research implications or Originality - Furthermore, the returns on preferred stocks are higher for firms with a lower proportion of foreign investors or a lower foreign market capitalization of preferred stocks. This suggests that foreign investors with informational advantages do not actively engage in profit-taking by trading preferred stocks, thus not narrowing the price difference. In summary, the recent surge in preferred stock prices is likely driven mainly by the irrational behavior of retail investors.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제6권4호
• /
• pp.189-196
• /
• 2017

버스정보시스템은 버스도착시간 예측과 같은 버스와 관련한 여러 정보를 제공한다. BIS는 우리나라 거의 모든 도시에 구축되어 있고 대중교통의 편의성 개선에 능동적인 역할을 하고 있다. 현재 BIS 시스템에서 버스 도착 예정시간을 예측하기 위하여 사용되는 대표적인 방법으로는 이동평균필터, Kalman Filter, 회귀 모형 등이 있다. 버스 도착 시간 예측의 정확성은 BIS 시스템에서 고려하고 있는 교통 상황이나 예측 알고리즘에 따라 차이가 크다. 현재 BIS에서 사용하는 예측 기법은 구간 통과 시간과 거리만을 이용한다. 그러나 도착시간 예측은 교통흐름, 신호주기, 이상 상황, 데이터 결측 등에 큰 영향을 받는다. 버스 도착 시간 예측의 정확도를 높이기 위해서는 위의 문제를 고려하여 모델링해야 하는 어려움이 있다. 은닉 마르코프 모델은 이와 같은 다양한 상황을 효과적으로 모델링 할 수 있다. 따라서 버스 도착 시간 예측의 정확도를 높이기 위해 도착시간에 대한 HMM 예측 모델을 구축했다. 이 모델에서는 순천시의 2015년 한 해 동안 수집한 데이터가 이용되었으며, 순천시에는 2298개의 정류장과 217개의 노선이 있다. 모델은 주중과 주말의 패턴을 다르게 적용하며, 다른 구간과 시간에 대해 모델이 적용된다. 본 논문에서는 버스정보시스템에 은닉 마르코프 모델 적용방법과 검증을 통해 버스정보시스템에서 사용 중인 이동평균필터, Kalman Filter, 회귀 모형을 사용한 예측 방법 보다 정밀한 정확도를 얻는 방법을 제안한다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
• /
• 제5권6호
• /
• pp.727-737
• /
• 1999

프로세스 중심 소프트웨어 개발 환경(PSEE : Process-centered Software Engineering Environment)은 소프트웨어 개발자를 위한 여러가지 정보의 제공과 타스크의 수행, 소프트웨어 개발 도구의 수행 및 제어, 필수적인 규칙이나 업무의 수행등과 같은 다양한 행위를 제공하는 프로세스 모형의 수행을 통하여 소프트웨어 개발 행위를 지원한다. SEED(Software Engineering Environment for Development)는 효율적인 소프트웨어 개발과 프로세스 모형의 수행을 제어하기 위해 ETRI에서 개발된 PSEE이다.본 논문에서는 SEED에서 프로세스 모형을 설계하기 위해 사용되는 SimFlex 프로세스 프로그래밍 언어와, 수행지원시스템인 SEED Engine의 구현에 대하여 기술한다. SimFlex는 간단한 언어 구조를 가진 프로세스 프로그래밍 언어이며, 적절한 적합화를 통하여 다른 PSEE에서 사용될 수 있다. SimFlex 컴파일러는 SimFlex에 의해 기술된 프로세스 모형을 분석하고, 모형의 오류를 검사하며, SEED Engine에 의해 참조되는 중간 프로세스 모형을 생성한다. 중간 프로세스 모형을 사용하여 SEED Engine은 외부 모니터링 도구와 연관하여 사용자를 위한 유용한 정보뿐만 아니라 SimFlex에 의해 기술된 프로세스 모형의 자동적인 수행을 제공한다. SimFlex 언어와 수행지원 시스템의 지원을 통하여 소프트웨어 프로세스를 모형화하는데 드는 비용과 시간을 줄일 수 있으며, 편리하게 프로젝트를 관리하여 양질의 소프트웨어 생산물을 도출할 수 있다. Abstract Process-centered Software Engineering Environments(PSEEs) support software development activities through the enaction of process models, providing a variety of activities such as supply of various information for software developers, automation of routine tasks, invocation and control of software development tools, and enforcement of mandatory rules and practices. The SEED(Software Engineering Environment for Development) system is a PSEE which was developed for effective software process development and controlling the enactment of process models by ETRI.In this paper, we describe the implementation of the SimFlex process programming language used to design process models in SEED, and its runtime support system called by SEED Engine. SimFlex is a software process programming language to describe process models with simple language constructs, and it could be embedded into other PSEEs through appropriate customization. The SimFlex compiler analyzes process models described by SimFlex, check errors in the models, and produce intermediate process models referenced by the SEED Engine. Using the intermediate process models, the SEED Engine provides automatic enactment of the process models described by SimFlex as well as useful information for agents linked to the external monitoring tool. With the help of the SimFlex language and its runtime support system, we can reduce cost and time in modeling software processes and perform convenient project management, producing well-qualified software products.

• 응용통계연구
• /
• 제29권7호
• /
• pp.1347-1359
• /
• 2016

혼합회귀모형은 반응 변수와 공변량 사이의 관계를 규명하는 유용한 통계적 모형으로 여러 분야에서 사용되어지고 있다. 하지만 실제로 혼합회귀모형을 이용하여 분석을 하는 과정에서 공변량이 결측값을 포함하는 문제는 흔하게 발생하며, 발생하는 결측의 유형 또한 다양하게 나타난다. 이러한 경우에 있어서 본 논문에서는 최대우도추정량을 구하기 위한 EM 알고리즘을 제안하고자 한다. 제안된 EM 알고리즘의 효용성을 모의실험을 통해 확인하였으며 또한 사례연구를 통해 제시된 방법이 어떻게 사용될수 있는지와 그 효용성을 함께 확인하였다.

• Structural Engineering and Mechanics
• /
• 제60권3호
• /
• pp.471-488
• /
• 2016

This study predicts the strength of rotary brace damper by analyzing a new set of probabilistic models using the usual method of multiple linear regressions (MLR) and advanced machine-learning methods of multivariate adaptive regression splines (MARS), Rotary brace damper can be easily assembled with high energy-dissipation capability. To investigate the behavior of this damper in structures, a steel frame is modeled with this device subjected to monotonic and cyclic loading. Several response parameters are considered, and the performance of damper in reducing each response is evaluated. MLR and MARS methods were used to predict the strength of this damper. Displacement was determined to be the most effective parameter of damper strength, whereas the thickness did not exhibit any effect. Adding thickness parameter as inputs to MARS and MLR models did not increase the accuracies of the models in predicting the strength of this damper. The MARS model with a root mean square error (RMSE) of 0.127 and mean absolute error (MAE) of 0.090 performed better than the MLR model with an RMSE of 0.221 and MAE of 0.181.

• 한국공간구조학회논문집
• /
• 제13권1호
• /
• pp.97-104
• /
• 2013

Recent tall buildings tend to have unconventional shapes as a prevailing, which is effective for suppressing across-wind responses. Suppression of across-wind responses is a major factor in tall building projects, and the so called aerodynamic modification method is comprehensively used. The purpose of the present study is to investigate the pressure fluctuations on tapered and setback tall buildings, including peak pressures, power spectra and coherences through the synchronous multi-pressure sensing system techniques. And flow measurements around the models were conducted to investigate the condition of vortex shedding. The results show that by tapering and setback, different distributions of mean pressure coefficients at leeward surface were found, which is caused by the geometric characteristics of the models. And the power spectra of wind pressures at sideward surface become wideband and the peak frequencies are different depending on heights, which makes the correlation near the Strouhal component low or even negative. The differences in shedding frequencies were also confirmed by the flow fields around the models.

• 정보처리학회논문지B
• /
• 제19B권3호
• /
• pp.177-182
• /
• 2012

본 논문에서는 대규모 실내 환경에서 WiFi 모듈이 내장된 스마트폰 사용자의 위치를 추적하기 위한 효과적인 이동 모델과 관측 모델을 제시한다. 제안하는 세 가지 부속 이동 모델들은 보행자의 움직임에 대한 더 정확한 예상 확률 분포를 제공한다. 또, 가우시안 보간법 기반의 관측 모델은 훈련 데이터 의 수집이 이루어지지 않은 지역들에 대해서도 관측 우도 계산을 가능하게 한다. 파티클 필터 프레임워크 속에 이와 같은 이동 모델과 관측 모델을 결합함으로써, 본 연구의 위치 추적 알고리즘은 대규모 실내 환경들에서도 스마트폰 사용자의 위치를 정확하게 추적할 수 있다. 한 복층 건물에서 안드로이드 스마트폰으로 수행한 실험을 통해, 본 연구에서 제안한 WiFi 위치 추적 알고리즘의 성능을 확인할 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제10권1호
• /
• pp.272-287
• /
• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.