• Journal of Korean Society on Water Environment
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• v.40 no.3
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• pp.121-129
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• 2024

Harmful cyanobacterial blooms (HCBs) are caused by the rapid proliferation of cyanobacteria and are believed to be exacerbated by climate change. However, the extent to which HCBs will be stimulated in the future due to increased temperature remains uncertain. This study aims to predict the future occurrence of cyanobacteria in the Nakdong River, which has the highest incidence of HCBs in South Korea, based on temperature rise scenarios. Representative Concentration Pathways (RCPs) were used as the basis for these scenarios. Data-driven model simulations were conducted, and out of the four machine learning techniques tested (multiple linear regression, support vector regressor, decision tree, and random forest), the random forest model was selected for its relatively high prediction accuracy. The random forest model was used to predict the occurrence of cyanobacteria. The results of boxplot and time-series analyses showed that under the worst-case scenario (RCP8.5 (2100)), where temperature increases significantly, cyanobacterial abundance across all study areas was greatly stimulated. The study also found that the frequencies of HCB occurrences exceeding certain thresholds (100,000 and 1,000,000 cells/mL) increased under both the best-case scenario (RCP2.6 (2050)) and worst-case scenario (RCP8.5 (2100)). These findings suggest that the frequency of HCB occurrences surpassing a certain threshold level can serve as a useful diagnostic indicator of vulnerability to temperature increases caused by climate change. Additionally, this study highlights that water bodies currently susceptible to HCBs are likely to become even more vulnerable with climate change compared to those that are currently less susceptible.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.5
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• pp.91-101
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• 2014

In this study, we presented a timing verification method for a passenger car diesel engine management system (EMS) using measurement-based worst-case execution time (WCET) analysis. In order to cope with AUTOSAR-compliant software architecture, a development process model is proposed. In the process model, a runnable is regarded as a test unit and its temporal behavior (i.e. maximum observed execution time, MOET) is obtained along with on-target functionality evaluation results during online unit test. Furthermore, a cost-effective framework for online unit test is proposed. Because the runtime environment layer and the standard calibration environment are utilized to implement test interface, additional resource consumption of the target processor is minimized. Using the proposed development process model and unit test framework, the MOETs of 86 runnables for diesel EMS are obtained with 213 unit test cases. Using the obtained MOETs of runnables, the WCETs of tasks are estimated and the schedulability is evaluated. From the schedulability analysis results, the problems of the initially designed schedule table is recognized and it is fixed by redesigning of the runnable mapping and task offset. Through the various test scenarios, the proposed method is validated.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.4
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• pp.467-478
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• 1999

실시간 태스크의 최악 실행시간을 예측할 때 과예측이 발생하는 원인은, 첫째 프로그램의 동적인 최악 실행 행태를 정적으로 분석하는 것이 근본적으로 어렵기 때문이며, 둘째 최근의 RISC 형태 프로세서에 포함되어 있는 파이프라인 실행 구조와 캐쉬 등이 그러한 정적 분석을 더욱 어렵게 만들기 때문이다. 그런데 기존의 연구에서는 각각의 과예측 원인을 해결하기 위한 방법에 대해서만 언급하고 있을 뿐 분석의 정확도에서 각 원인이 차지하는 비중에 대해서는 언급하고 있지 않다. 이에 본 연구에서는 최악 실행시간 예측시 과예측을 유발하는 원인들, 즉 분석 요소들의 영향을 정량적으로 조사함으로써 기존의 최악 실행시간 분석 기법들이 보완해야 할 방향을 제시하고자 한다. 본 연구에서는 실험이 특정 분석 기법에 의존하지 않도록 하기 위하여 시뮬레이션 방법에 기반한다. 이를 위해 분석 요소별 스위치가 포함된 MIPS R3000 프로세서를 위한 시뮬레이터를 구현하였는데, 각 스위치는 해당 분석 요소에 대한 분석의 정확도 수준을 결정한다. 모든 스위치 조합에 대해서 시뮬레이션을 반복 수행한 다음 분산 분석을 수행하여 어떤 분석 요소가 가장 큰 영향을 끼치는지 고찰한다.Abstract Existing analysis techniques for estimating the worst case execution time (WCET) of real-time tasks still suffer from significant overestimation due to two types of overestimation sources. First, it is unavoidably difficult to predict dynamic behavior of programs statically. Second, pipelined execution and caching found in recent RISC-style processors even more complicate such a prediction. Although these overestimation sources have been attacked in many existing analysis techniques, we cannot find in the literature any description about questions like which one is most important. Thus, in this paper, we quantitatively analyze the impacts of overestimation sources on the accuracy of the worst case timing analysis. Using the results, we can identify dominant overestimation sources that should be analyzed more accurately to get tighter WCET estimations. To make our method independent of any existing analysis techniques, we use simulation based methodology. We have implemented a MIPS R3000 simulator equipped with several switches, each of which determines the accuracy level of the timing analysis for the corresponding overestimation source. After repeating simulation for all of the switch combinations, we perform the variance analysis and study which factor has the largest impact on the accuracy of the predicted WCETs.

• Journal of Environmental Science International
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• v.14 no.10
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• pp.979-983
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• 2005

Indoor air quality has been addressed as an important atmospheric environmental issue and has caught attention of the public in recent years in Korea. Good indoor air quality in classrooms favour student's learning ability, teacher and staff's productivity according to other studies. In this study, each classroom at four different schools was chosen for comparison of indoor and outdoor air quality by means of source generation types such as new constructed classroom, using of cleaning agents and purchased furniture. Temperature, relative humidity (RH), carbon dioxide $(CO_2)$, formaldehyde (HCHO), total volatile organic compounds (TVOCs) and particulate matter with diameter less than $10{\mu}m\;(PM_{10})$ were monitored at indoor and outdoor locations during lesson. HCHO was found to be the worst among parameters measured in new constructed classroom, HCHO and TVOCs was worst in classroom with new purchased furniture, and TVOCs was worst in classroom cleaned by cleaning agents, Indoor $(CO_2)$ concentrations often exceeded 1500 ppm indicating importance of ventilation. Active activity of students during break time made the $PM_{10}$ concentration higher than a lesson, Improvements and further researches should be carried out considering indoor air quality at schools is of special concern since children and students are susceptible to poor air quality.

• Safety and Health at Work
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• v.13 no.3
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• pp.326-335
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• 2022

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.961-963
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• 2005

We answer a question raised by P. Brass on the number of maximally repeated sub-patterns in a set of n points in $\mathbb{R}^{d}$. We show that is number, which was conjectured to be polynomial, is in fact $\Theta(2^{\frac{n}{2}})$ in the worst case, regardless of the dimension d.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.3
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• pp.77-86
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• 1994

A New environment SENSATION for circuit optimization and statistical analysis has been developed. It provides real time simulation and includes automatic algorithms to assist for reaching optimal solution. Furthermore, statistical analysis environment is presented which aids in Monte Carlo analysis. worst case corner analysis, and sensitivity analysis. These capabilities faciliate the characterization of the effects of several operating conditions and manufacture process paramenters on the design performances. We verify that the proposed methods can obtain the optimal solution of the objective function through several experimental results.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1141-1144
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• 1998

A new design methodology for the shortchannel CMOS IC-package is presented. It is developed by representing the package inductance with an effective lumpedinductance. The worst case maximum-simultaneous-switching noise (SSN) and gate propagation delay due to the package are modeled in terms of driver geometry, the maximum number of simultaneous switching drivers, and the effective inductance. The SSN variations according to load capacitances are investigated with this model. The package design techniques based on the proposed guidelines are verified by performing HSPICE simulations with the $0.35\mu\textrm{m}$ CMOS model parameters.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.81-87
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• 1993

In this paper robust stability conditions are obtained for linear dynamical systems under structured nonlinear time-varying perturbations, using absolute stability theory and the concept of dissipative systems. The conditions are expressed in terms of solutions to linear matrix inequality(LMI). Based on this result, a synthesis methodology is developed for robust feedback controllers with worst-case H$_{2}$ perforrmance via convex optimization and LMI formulation.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.342-343
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• 2011

본 논문은 풍력발전기의 일반적인 LVRT범위에서 계통의 stability와 quality를 충분히 보장하지 못하는 경우에 해당하는 worst case를 제시하고 전원의 순간 저전압 발생 시나리오를 구성을 바탕으로 2MW급 풍력시뮬레이터를 통한 LVRT 시험을 진행하여 그 결과를 확인한다.