• 한국항만학회지
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• 제12권2호
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• pp.251-260
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• 1998

For the purpose of building the simulation model on cargo handling capacity in container terminal we composed a model of container logistics system which has a 4 subsystem; cargo handling transportation storage and gate complex system. Several data are used in simulation which were gained through a field study and a basic statistic analysis of raw data on BCTOC from January to Jane in 1998. The results of this study are as follows; First average available ratios of each subsystems were 50% for G/C, 57.5% for Y/T, 56% for storage system and 50% for gate complex. And there were no subsystems occurring specific bottleneck. Second comparing the results of simulation to the results of basic statistics analysis we can verifying the suitability of this simulation model. Third comparing the results of this study to the results of existed similar study in 1996, we were able to confirm the changes of container logistics system in BCTOC.

• Child Health Nursing Research
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• 제25권4호
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• pp.425-434
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• 2019

Purpose: The purpose of this study was to construct a structural model that explains the factors affecting aggression among elementary school students and to verify their suitability. Methods: The study period was from June to August 2018. The study subjects were fifth- and sixth-graders at an elementary school. In total, 291 surveys were collected, of which 259 were analyzed. Data were analyzed using SPSS version 24.0 and AMOS version 24.0. Results: The fit of the final model was acceptable ($x^2=160.08$ [p<.001], GFI=.921, AGFI=.869, CFI=.919, SRMR=.057, and RMSEA=.086). Thus, eight of the 10 hypotheses were shown to be statistically significant. Conclusion: The results of this study indicate that positive and open parenting behaviors and training children to engage in self-control are needed to reduce their aggression. In addition, considerable attention and education are required in the home, school, and society so that children can learn to properly recognize and express their emotions and establish suitable beliefs regarding aggressive behavior.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2012년도 제38회 춘계학술대회논문집
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• pp.597-602
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• 2012

화염유도로는 추진기관 시스템 시험설비 요소 중 추진기관시스템, 시험설비, 인적자원의 보호측면에서 매우 중요한 설계대상 중에 하나이다. 본 연구에서는 75톤과 300톤의 추진기관 시스템의 성능을 평가할 시험설비의 화염유도로 설계 방안에 대해 제안하였다. 설비가 구축될 장소의 경사로를 이용하여 화염유도로의 높이를 30m정도로 설계하였다. 개방형과 밀폐형 형상에 따라서 화염유도로의 적합성을 고려하였다. 또한 냉각을 위한 덕트를 core와 side분사 형태에 따라 모델링하였다.

• Steel and Composite Structures
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• 제21권6호
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• pp.1327-1345
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• 2016

$Al_2O_3$/SiC particulate reinforced (Metal Matrix Composites) MMCs which were produced by using stir casting process, bending strength and hardening behaviour were obtained using an analysis of variance (ANOVA) technique that uses full factorial design. Factor variables and their ranges were: particle size $2-60{\mu}m$; the stirring speed 450 rpm, 500 rpm and the stirring temperature $620^{\circ}C$, $650^{\circ}C$. An empirical equation was derived from test results to describe the relationship between the test parameters. This model for the tensile strength of the hybrid composite materials with $R^2$ adj = 80% for the bending strength $R^2$ adj = 89% were generated from the data. The regression coefficients of this model quantify the tensile strength and bending strengths of the effects of each of the factors. The interactions of all three factors do not present significant percentage contributions on the tensile strength and bending strengths of hybrid composite materials. Analysis of the residuals versus was predicted the tensile strength and bending strengths show a normalized distribution and thereby confirms the suitability of this model. Particle size was found to have the strongest influence on the tensile strength and bending strength.

• 항공우주시스템공학회지
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• 제15권4호
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• pp.64-74
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• 2021

Unmanned Aircraft Systems (UAS) are rapidly emerging not only as a key military power, such as surveillance and reconnaissance for military purposes but also as a new air transportation means in the form of Urban Air Mobility (UAM). Currently, airworthiness certification is carried out focused on the verification of technical standards for flight safety suitability of aircraft design in accordance with the Military Aircraft Flight Safety Certification Act and does not employ the model for operational risk assessment for mission areas and airspace. In this study, in order to evaluate the risk of the mission area from the perspective of the UAS operator, a risk assessment simulation has been conducted by applying the Specific Operations Risk Assessment (SORA) model to the operating environment of the Korean military UAS. Also, the validity of the SORA model has been verified through the analysis of simulation results, and a new application plan for airworthiness certification of the military unmanned aerial system has been presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.755-778
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• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• The Plant Pathology Journal
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• 제40권3호
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• pp.290-298
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• 2024

K-Maryblyt has been developed for the effective control of secondary fire blight infections on blossoms and the elimination of primary inoculum sources from cankers and newly emerged shoots early in the season for both apple and pear trees. This model facilitates the precise determination of the blossom infection timing and identification of primary inoculum sources, akin to Maryblyt, predicting flower infections and the appearance of symptoms on various plant parts, including cankers, blossoms, and shoots. Nevertheless, K-Maryblyt has undergone significant improvements: Integration of Phenology Models for both apple and pear trees, Adoption of observed or predicted hourly temperatures for Epiphytic Infection Potential (EIP) calculation, incorporation of adjusted equations resulting in reduced mean error with 10.08 degree-hours (DH) for apple and 9.28 DH for pear, introduction of a relative humidity variable for pear EIP calculation, and adaptation of modified degree-day calculation methods for expected symptoms. Since the transition to a model-based control policy in 2022, the system has disseminated 158,440 messages related to blossom control and symptom prediction to farmers and professional managers in its inaugural year. Furthermore, the system has been refined to include control messages that account for the mechanism of action of pesticides distributed to farmers in specific counties, considering flower opening conditions and weather suitability for spraying. Operating as a pivotal module within the Fire Blight Forecasting Information System (FBcastS), K-Maryblyt plays a crucial role in providing essential fire blight information to farmers, professional managers, and policymakers.

• 한국산학기술학회논문지
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• 제16권12호
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• pp.8753-8759
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• 2015

터빈 발전 사이클에서의 안정적인 발전 출력 유지관리를 위해서는 검증된 성능 측정 데이터 그룹과 이를 바탕으로 한 발전 출력 성능 계산 절차의 수립이 필요하다. ASME PTC(Performance Test Code)의 성능 계산 절차를 기반으로 본 연구에서는 터빈 출력에 의한 발전기 출력 성능 산정을 위해서 터빈 팽창선 모델과 발전기 출력 측정 데이터의 입력 검증 모델을 구성하였다. 또한 불확실한 측정 데이터에 대한 검증 모델도 구성하였다. 지난 연구에서는 신경회로망과 커널 회귀의 학습 방법을 사용하였으나 본 연구에서는 미측정 데이터에 대한 보완을 하기 위하여 서포트 벡터 머신 모델을 사용하여 발전기 출력 계산 데이터의 학습 모델을 구성하였으며, 학습 모델 구성을 위해서 관련 변수의 선정을 위한 절차와 학습 데이터 구간을 설정하는 알고리듬을 개발하였다. 학습의 결과 오차는 약 1% 범위 안에 있게 되어 추정 및 학습 모델로서 유용함을 입증하였다. 이 학습 모델을 사용하여 측정 데이터 중 상실된 부분에 대한 추정 모델을 구성함으로써, 터빈 사이클 보정 성능 계산의 신뢰성을 향상시킬 수 있음을 검증하였다.

• 한국안전학회지
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• 제27권5호
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• pp.148-157
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• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

• 정보처리학회논문지D
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• 제11D권4호
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• pp.885-892
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• 2004

소프트웨어 시험단계에 투입되는 노력의 분포를 추정하는 대표적인 모델로 Weibull 분포(Rayleigh와 지수분포 포함)가 있다. 이 모델은 시험 시작시점에서 실제로 많은 노력이 투입되는 점을 표현하지 못한다. 또한 다양한 형태를 갖고 있는 실제 시험 노력의 분포를 적절히 표현하지 못하고 있다. 이러한 문제점을 해결하기 위해 본 논문은 시그모이드 모델을 제안하였다. 신경망 분야에서 적용되고 있는 시그모이드 함수로부터 소프트웨어 시험 노력을 적절히 표현할 수 있도록 함수 형태를 변형시켰다 제안된 모델은 다양한 분포 형태를 보이고 있는 실제 수행된 소프트웨어 프로젝트로부터 얻어진 6개의 시험 노력 데이터에 적용하여 적합성을 검증하였다. 제안된 시그모이드 모델은 기존의 Weibull 모델보다 성능이 우수하여 소프트웨어 시험노력을 추정하는데 있어 와이블 모델의 대안으로 채택될 수 있을 것이다.