This study investigates the risk reduction effect and identifies the optimal capacity of Multi-barrier Accident Coping Strategy (MACST) facilities for nuclear power plants (NPPs) under seismic hazard. The efficacy of MACST facilities in OPR1000 and APR1400 NPP systems is evaluated by utilizing the Improved Direct Quantification of Fault Tree with Monte Carlo Simulation (I-DQFM) method. The analysis encompasses a parametric study of the seismic capacity of two MACST facilities: the 1.0 MW large-capacity mobile generator and the mobile low-pressure pump. The results demonstrate that the optimal seismic capacity of MACST facilities for both NPP systems is 1.5g, which markedly reduces the probability of core damage. In particular, the core damage risk is reduced by approximately 23% for the OPR1000 system, with the core damage fragility reduced by approximately 72% at 1.0g seismic intensity. For the APR1400 system, the implementation of MACST is observed to reduce the core damage risk by approximately 17% and the core damage fragility by approximately 44% under the same conditions. These results emphasize the significance of integrating MACST facilities to enhance the resilience and safety of NPPs against seismic hazard scenarios, highlighting the necessity for continuous adaptation of safety strategies to address evolving natural threats.
PURPOSES : In this study, the existence of an optimal pattern among transition methods applied during changes in traffic signal timing was investigated. We aimed to develop this pattern into an artificial intelligence reinforcement-learning model to assess its effectiveness METHODS : By developing various traffic signal transition scenarios and considering 19 different traffic signal transition situations that can be applied to these scenarios, a simulation analysis was performed to identify patterns through statistical analysis. Subsequently, a reinforcement-learning model was developed to select an optimal transition time model suitable for various traffic conditions. This model was then tested by simulating a virtual experimental center environment and conducting performance comparison evaluations on a daily basis. RESULTS : The results indicated that when the change in the traffic signal cycle length was less than 50% in the negative direction, the subtraction method was efficient. In cases where the transition was less than 15% in the positive direction, the proposed center method for traffic signal transition was found to be advantageous. By applying the proposed optimal transition model selection, we observed that the transition time decreased by approximately 70%. CONCLUSIONS : The findings of this study provide guidance for the next level of traffic signal transitions. The importance of traffic signal transition will increase in future AI-based traffic signal control methods, requiring ongoing research in this field.
Airpower is a crucial force for suppressing military threats and achieving victory in wars. This study evaluates newly introduced fighter forces, considering factors such as fighter performance and power index, operational environment, capacity of each airbase, survivability, and force sustainment capability to determine the optimal deployment plan that maximizes operational effectiveness and efficiency. Research methods include optimization techniques such as MIP(mixed integer programming), allocation problems, and experimental design. This optimal allocation mathematical model is constructed based on various constraints such as survivability, mission criticality, and aircraft's performance data. The scope of the study focuses the fighter force and their operational radius is limited to major Air Force and joint operations, such as air interdiction, defensive counter-air operations, close air support, maritime operations and so on. This study aims to maximize the operational efficiency and effectiveness of fighter aircraft operations. The results of proposed model through experiments showed that it was for superior to the existing deployment plan in terms of operation and sustainment aspects when considering both wartime and peacetime.
인공지능(AI)은 20년 이상 게임 분야에 널리 적용되어 왔다. 그러나 협동(coordination) 게임에서의 AI 에이전트, 특히 경주 게임에서 협동에 대한 연구는 상대적으로 적은 주목을 받아왔다. 이러한 관심의 부족은 불완전한 파트너를 충분히 보완하면서 사용자의 게임 플레이 경험 과 수행 능력 을 저해하지 않아야 하는 복잡성에서 부분적으로 기인한다. 우리는 경주 게임에서 협동 에이전트 의 잠재력을 탐구하고 밝히기 위해, 자동차 컨트롤을 두 개의 서로 다른 에이전트로 나눔으로써 협동 환경을 갖춘 자동차 경주 게임을 개발하였다. 이어서 실험을 통해 다양한 훈련 방법과 파트 너의 정보를 활용하여 에이전트와 파트너의 협동을 평가하였다. 특히, 학습 시 서브-옵티멀 파트 너와 함께하는 것과 에이전트를 해당 파트너에게 맞게 개인화하는 것의 영향을 조사하였다. 연구 결과, 불완전한 파트너와 훈련했을 때 성능이 2%에서 7%까지 향상되었으며, 파트너에게 맞게 개 인화했을 때는 모든 파트너에게 일반화한 경우보다 최대 3점(6.7%)까지 성능이 향상하였다. 본 연구를 통해, AI 에이전트를 개인화하는 것의 잠재력을 보여주었고, 에이전트가 파트너의 불완전 함을 인지하는 것의 장점을 확인하였다. 본 연구가 협 동 게임에서 개인화된 에이전트 연구에 이 바지하기를 기대한다.
Among the different types of seaweed that are cultivated in Korea for food, Capsosiphon fulvescensis the filamentous green alga with the highest production value. However, its harvest yield varies significantly from year to year due to its dependence on the natural seeding method. The present study aimed to identify the conditions affecting the formation of cyst-zygotes that can be utilized as artificial seeds during the life cycle of C. fulvescens. Gametangia and zygotes of C. fulvescens were found to be highly developed at temperatures above 15°C, with a maximum gametangial development rate of about 35% observed after 7 days of culture. The formation of zygotes into cystzygotes was induced within 7 days in all temperature conditions, but after 30 days of culturing, cyst-zygotes germinated into filamentous thalli at temperatures above 20°C, while the most stable formation and stabilization were observed at 15°C. Cystzygotes formed at 15°C showed high growth when they were transferred to 25°C conditions, and zoospores matured inside the cells. The production of cyst-zygotes was mostly influenced by temperature, and a gradual increase in temperature was found to be necessary for the formation and growth of cyst-zygotes. The culture conditions facilitating the formation of cyst-zygotes reported in this study can be useful for the production of artificial seeds and breeding technology for the effective cultivation of seaweed.
Recent advances in computer technology have made it possible to solve numerous challenges but require faster hardware development. However, the size of the classical computer has reached its physical limit, and researchers' interest in quantum computers is growing, and it is being used in various engineering fields. However, research using quantum computing in structural engineering is very insufficient. Therefore, in this paper, the characteristics of qubits, the minimum unit of quantum information processing, were grafted with the crow search algorithm to propose QCSA (quantum crow search algorithm) and compare the convergence performance according to parameter changes. In addition, by performing the optimal design of the example truss structure, it was confirmed that quantum computing can be used in the architectural field.
We aimed to evaluate the effectiveness of ensemble optimal interpolation (EnOI) in improving the analysis of significant wave height (SWH) within wave models using satellite-derived SWH data. Satellite observations revealed higher SWH in mid-latitude regions (30o to 60o in both hemispheres) due to stronger winds, whereas equatorial and coastal areas exhibited lower wave heights, attributed to calmer winds and land interactions. Root mean square error (RMSE) analysis of the control experiment without data assimilation revealed significant discrepancies in high-latitude areas, underscoring the need for enhanced analysis techniques. Data assimilation experiments demonstrated substantial RMSE reductions, particularly in high-latitude regions, underscoring the effectiveness of the technique in enhancing the quality of analysis fields. Sensitivity experiments with varying ensemble sizes showed modest global improvements in analysis fields with larger ensembles. Sensitivity experiments based on different decorrelation length scales demonstrated significant RMSE improvements at larger scales, particularly in the Southern Ocean and Northwest Pacific. However, some areas exhibited slight RMSE increases, suggesting the need for region-specific tuning of assimilation parameters. Reducing the observation error covariance improved analysis quality in certain regions, including the equator, but generally degraded it in others. Rescaling background error covariance (BEC) resulted in overall improvements in analysis fields, though sensitivity to regional variability persisted. These findings underscore the importance of data assimilation, parameter tuning, and BEC rescaling in enhancing the quality and reliability of wave analysis fields, emphasizing the necessity of region-specific adjustments to optimize assimilation performance. These insights are valuable for understanding ocean dynamics, improving navigation, and supporting coastal management practices.
This study aims to develop a deep learning model to monitor rice serving amounts in institutional foodservice, enhancing personalized nutrition management. The goal is to identify the best convolutional neural network (CNN) for detecting rice quantities on serving trays, addressing balanced dietary intake challenges. Both a vanilla CNN and 12 pre-trained CNNs were tested, using features extracted from images of varying rice quantities on white trays. Configurations included optimizers, image generation, dropout, feature extraction, and fine-tuning, with top-1 validation accuracy as the evaluation metric. The vanilla CNN achieved 60% top-1 validation accuracy, while pre-trained CNNs significantly improved performance, reaching up to 90% accuracy. MobileNetV2, suitable for mobile devices, achieved a minimum 76% accuracy. These results suggest the model can effectively monitor rice servings, with potential for improvement through ongoing data collection and training. This development represents a significant advancement in personalized nutrition management, with high validation accuracy indicating its potential utility in dietary management. Continuous improvement based on expanding datasets promises enhanced precision and reliability, contributing to better health outcomes.
PURPOSES : In this study, a preliminary study on the optimal clustering techniques for the preprocessing of pavement management system (PMS) data was conducted using K-means and mean-shift techniques to improve the correlation between the dependent and independent variables of the pavement performance model. METHODS : The PMS data of Jeju Island was preprocessed using the K-means and mean-shift algorithms. In the case of the K-means method, the elbow method and silhouette score were used to determine the optimal number of clusters (K). Moreover, in the case of the mean-shift method, Scott’s rule of thumb and Silverman’s rule of thumb were used to determine the optimal cluster bandwidth. RESULTS : The optimal cluster sets were selected for the rut depth (RD), annual average daily traffic (AADT), and annual maximum temperature (AMT) for each clustering technique, and their similarities with the original data were investigated. Additionally, the correlation improvement between the dependent and independent variables were investigated by calculating the clustering score (CS). Consequently, the K-means method was selected as the optimal clustering technique for the preprocessing of PMS data. The K-means method improved the correlations of more variables with the dependent variable compared to the mean-shift method. The correlations of the variables related to high temperature—such as the annual temperature change, summer days, and heat wave days—were improved in the case wherein the AMT, a climate factor, was used as an independent variable in the K-means clustering method. CONCLUSIONS : The applicability of the clustering methods to preprocessing of PMS data was identified in this study. Improvements in the pavement performance prediction model developed using traditional statistical methods may be identified by developing a model using clustering techniques in a future study.
Democratic People’s Republic of Korea (DPRK) has produced weapon-grade plutonium in a graphite-moderated experimental reactor at the Yongbyon nuclear facilities. The amount of plutonium produced can be estimated using the Graphite Isotope Ratio Method (GIRM), even without considering specific operational histories. However, the result depends to some degree on the operational cycle length. Moreover, an optimal cycle length can maximize the number of nuclear weapons made from the plutonium produced. For conservatism, it should be assumed that the target reactor was operated with an optimal cycle length. This study investigated the optimal cycle length using which the Calder Hall MAGNOX reactor can achieve the maximum annual production of nuclear weapons. The results show that lower enrichment fuel produced a greater number of critical plutonium spheres with a shorter optimal cycle length. Specifically, depleted uranium (0.69wt%) produced 5.561 critical plutonium spheres annually with optimal cycle lengths of 251 effective full power days. This research is crucial for understanding DPRK’s potential for nuclear weapon production and highlights the importance of reactor operational strategy in maximizing the production of weapons-grade plutonium in MAGNOX reactors.
Background: Using cryovial for freezing dog spermatozoa provides a practical method to increase extended sperm volume and shorten the time required for equilibration by using a simple freezing techniques. The purpose of this study was to determine the optimal thawing condition for dog sperm cryopreservation using cryovials. Methods: For sperm freezing, cryovials with 200 × 106 sperm/mL were cooled after the addition of tris egg yolk extender (TEY) at 4℃ for 20 min, then TEY with 4% glycerol was added and equilibrated for another 20 min before being aligned over LN2 vapor for another 20 min and plunged directly into LN2. Spermatozoa were thawed in a water bath at 37℃ for varying times (25 sec, 60 sec, 90 sec, and 120 sec) in the first experiment. In the second experiment, spermatozoa were thawed in a water bath at various temperatures and times (37℃ for 1 min, 37℃ for 1 min with gentle stirring, 24℃ for 24 min, and 75℃ for 20 sec). In these experiments, the effect of thawing conditions on motility parameters, viability (SYBR-14/PI), and acrosome integrity (PSA/ FITC) of spermatozoa were investigated. Results: The post-thaw sperm motility parameters, viability, and acrosome integrity were not significantly different across the experimental groups. Conclusions: In this study, the characteristics of spermatozoa frozen using cryovials were not significantly affected by various thawing conditions.
본 논문에서는 다목적 구조물인 다중연결 해양부유체를 대상으로 변형 기반 모드 차수축소법을 적용하고 차수축소모델의 구조응 답 예측 성능을 향상시키기 위해 유전 알고리즘 기반의 센서 배치 최적화를 수행하였다. 다중연결 해양부유체의 차수축소모델 생성 에 필요한 변형 기반 모드 데이터를 얻기 위해 다양한 규칙파랑하중조건에 대한 유체-구조 연성 수치해석을 수행하고 변형 기반 모드 의 직교성, 자기상관계수를 이용하여 주요 변형 기반 모드를 선정하였다. 다중연결 해양부유체의 경우 차수축소모델의 구조응답 예 측 성능이 계측 및 예측 구조응답 위치에 따라 민감하기 때문에 유전 알고리즘 기반의 최적화를 수행하여 최적의 센서 배치를 도출하 였다. 최적화 결과, 모든 센서 배치 조합에 대한 차수축소모델 생성 및 예측 성능 평가 대비 약 8배의 계산 비용을 절감하였으며, 예측 성능 평가 지표인 평균 제곱근 오차가 초기 센서 배치보다 84% 감소하였다. 또한, 다중연결 해양부유체 모형시험 결과를 이용하여 불 규칙파랑하중에 대한 최적화된 센서 배치의 차수축소모델의 구조응답 예측 성능을 평가 및 검증하였다.
In this study, we propose an optimal design method by applying the Prefabricated Buckling Restrained Brace (PF-BRB) to structures with asymmetrically rigidity plan. As a result of the PF-BRB optimal design of a structure with an asymmetrically rigidity plan, it can be seen that the reduction effect of dynamic response is greater in the case of arrangement considering the asymmetric distribution of stiffness (Asym) than in the case of arrangement in the form of a symmetric distribution (Sym), especially It was confirmed that at an eccentricity rate of 20%, the total amount of reinforced PF-BRBs was also small. As a result of analyzing the dynamic response characteristics according to the change in eccentricity of the asymmetrically rigidity plan, the distribution of the reinforced PF-BRB showed that the larger the eccentricity, the greater the amount of damper distribution around the eccentric position. Additionally, when comparing the analysis models with an eccentricity rate of 20% and an eccentricity rate of 12%, the response reduction ratio of the 20% eccentricity rate was found to be large.
Fish resource surveys were conducted near Jeju Island in June, August and October 2021 using an underwater camera monitoring system, fish pots, and SCUBA diving methods. The efficiency of the methods used to survey fish resources was compared using the number of individuals compared to area per unit time (inds/m3/h) and the number of species compared to area per unit time (spp./m3/h). As a result of comparing the number of individuals compared to the area per unit time (inds/m3/h), the order was underwater camera 214.69, SCUBA diving 124.62, and fish pots 0.57 inds/m3/h. The number of species compared to area per unit time (spp./m3/h) is in the following order: SCUBA diving 0.85, underwater camera 0.38, and fish pots 0.01 spp./m3/h. The fish resource monitoring method using underwater cameras was found to be more efficient in individual counts, and the SCUBA diving method was found to be more efficient in species counts. When considering cost and survey efficiency, the fish resource survey method using underwater cameras was judged to be more effective. The results of this study are expected to be widely used in estimating the population density of fish, which is the core of future fisheries resource surveys.
In this study, various pre-treatment methods were evaluated for microalgae separation. These methods aimed to facilitate safe, rapid, and cost-effective online imaging for real-time observation and cell counting. As pre-treatment techniques, heating, chemical hydrolysis, heating combined with chemical hydrolysis, and sonication were employed. The effectiveness of these methods was evaluated in the context of online imaging quality through experimentation on cultivated microalgae (Chlorella vulgaris and Scenedesmus quadricauda). The chemical treatment method was found to be inappropriate for improving image acquisition. The heating pre-treatment method exhibited a drawback of prolonged cell dispersion time. Additionally, the heating combined with chemical hydrolysis method was confirmed to have the lowest dispersion effect for Chlorella vulgaris. Conversely, ultrasonication emerged as a promising technique for microalgae separation in terms of repeatability and reproducibility. This study suggests the potential for selecting optimal pre-treatment methods to effectively operate real-time online monitoring devices, paving the way for future research and applications in microalgae cultivation and imaging.
본 논문에서는 무도상 철도판형교에 열차하중이 재하되었을 때 변위를 최소화시키는 하부 수평브레이싱의 보강 형상 및 설치 위치를 검토하였다. 우선 거더와 수평 브레이싱으로 연결된 2거더 구조계의 전체 횡좌굴모멘트에 영향을 주는 요소를 검토하였다. 다음 으로는 무도상 철도판형교의 하부를 설치 위치를 달리하여 수평브레이싱으로 보강하였다. 보강된 무도상 철도판형교에 열차하중 및 거 더의 중심과 열차하중의 재하위치간의 편심거리(e)에 따라 발생하는 축방향의 비틀림모멘트를 고려하여 구조해석을 수행하였다. 보강모 델별로 지간 중앙에서의 단면의 중심에서 발생하는 변위를 검토하여 변위를 최소화시키는 모델을 선정하였다. 본 연구를 통하여 무도상 철도판형교에 열차하중 재하시 변위를 최소화시키는 하부 수평브레이싱의 보강 형상 및 설치 위치를 제안하였다.
Hand, foot, and mouth disease (HFMD) is a highly contagious disease with no specific treatment. Since it is common in immunocompromised children under the age of 5, there is a need to develop a safe vaccine. Virus-like particles (VLPs) are similar structures to viruses with the lack of genetic material which makes them impossible to replicate and infect, and therefore have a high level of biological safety and are considered to have high value as vaccines. In this study, the insect virus expression system that is widely used for vaccine and drug production due to its high post-translational modification efficiency, was used to produce VLPs for Coxsackievirus type A6 and A10, which are recently reported to be the main causes of HFMD. For this purpose, the selection of promoters that can control the timing and intensity of expression of 3CD protein, which is essential for VLPs assembly but has been reported to be cytotoxic, was conducted to construct an optimal expression form for HFMD-VLP.