• 영어영문학
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• 제64권1호
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• pp.25-37
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• 2018

The turning point is one of the more evocative concepts in the critic's arsenal, as it is equally suited to the evaluation and analysis of a given moment in one's day as to those of a historical event. But how does one recognize a turning point? As we find ourselves always "in the middest," both spatially and temporally, we inhabit sites that may be points at which many things may be seen to turn. Indeed, it is usually only possible to identify a turning point, as it were, from a distance, from the remove of space and time which allows for a sense of recognition, based in part on original context and in part of perceived effects. In this article, Robert T. Tally Jr. argues that the apprehension and interpretation of a turning point involves a fundamentally critical activity. Examining three models by which to understand the concept of the turning point-the swerve, the trope, and peripety (or the dialectical reversal)-Tally demonstrates how each represents a different way of seeing the turning point and its effects. Thus, the swerve is associated with a point of departure for a critical project; the trope is connected to continuous and sustained critical activity in the moment, and peripety enables a retrospective vision that, in turn, inform future research. Tally argues for the significance of the turning point in literary and cultural theory, and concludes that the identification, analysis, and interpretation of turning points is crucial to the project of criticism today.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1138-1148
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• 2021

In this study, we developed a 'shared-use mobility'-mounted local particulate matter monitoring terminal technology to measure the actual particulate matter concentration around me. As a mobile terminal device in the form of an IoT sensor platform, it is designed to be separated into a control module and a sensor module to minimize interference between sensors and to consider the optimal observation position of each sensor. As a result of the field test, it was confirmed that particulate matter was locally different depending on time and space even within the same area. In addition, it was confirmed that the concentration of particulate matter in the relevant section differed by up to 100 times compared to the surrounding area due to specific sources of particulate matter such as unpaved roads. In addition, we positively reviewed the applicability of the service in the real-time metaverse environment using this result. Through technological advancement and application of multiple shared-use mobilities, we expect to be able to provide new services for practical smart city air environment monitoring, such as localized particulate matter information, air pollution event information, and identification of causes of particulate matter.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.175-175
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• 2023

Detection and monitoring of wildfires are essential for limiting their harmful effects on ecosystems, human lives, and property. In this research, we propose a novel method running in the Google Earth Engine platform for identifying and characterizing burnt regions using a hybrid of Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (multispectral photography) images. The 2022 Uljin wildfire, the severest event in South Korean history, is the primary area of our investigation. Given its documented success in remote sensing and land cover categorization applications, we select the Random Forest (RF) method as our primary classifier. Next, we evaluate the performance of our model using multiple accuracy measures, including overall accuracy (OA), Kappa coefficient, and area under the curve (AUC). The proposed method shows the accuracy and resilience of wildfire identification compared to traditional methods that depend on survey data. These results have significant implications for the development of efficient and dependable wildfire monitoring systems and add to our knowledge of how machine learning and remote sensing-based approaches may be combined to improve environmental monitoring and management applications.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• Steel and Composite Structures
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• 제49권4호
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• pp.407-417
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• 2023

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

• 시스템엔지니어링학술지
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• 제19권2호
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• pp.32-45
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• 2023

Implementing Severe Accident Management (SAM) strategies is crucial for enhancing a nuclear power plant's resilience and safety against severe accidents conditions represented in the analysis of Station Blackout (SBO) event. Among these critical approaches, the In-Vessel Retention (IVR) through External Reactor Vessel Cooling (IVR-ERVC) strategy plays a key role in preventing vessel failure. This work is designed to evaluate the efficacy of the IVR strategy for a high-power density reactor APR1400. The APR1400's plant is represented and simulated under steady-state and transient conditions for a station blackout (SBO) accident scenario using the computer code, ASYST. The APR1400's thermal-hydraulic response is analyzed to assess its performance as it progresses toward a severe accident scenario during an extended SBO. The effectiveness of emergency operating procedures (EOPs) and severe accident management guidelines (SAMGs) are systematically examined to assess their ability to mitigate the accident. A group of associated key phenomena selected based on Phenomenon Identification and Ranking Tables (PIRT) and uncertain parameters are identified accordingly and then propagated within DAKOTA Uncertainty Quantification (UQ) framework until a statistically representative sample is obtained and hence determine the uncertainty bands of key system parameters. The Systems Engineering methodology is applied to direct the progression of work, ensuring systematic and efficient execution.

• 농업과학연구
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• 제50권4호
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• pp.799-808
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• 2023

Globally, abnormal climate phenomena have led to an increase in rainfall intensity, consequently causing a rise in flooding-related damages. Agricultural areas, in particular, experience significant annual losses every year due to a lack of research on flooding in these regions. This study presents a comprehensive analysis of the flood event that occurred on July 16, 2017, in the agricultural area situated in Sindaedong, Heungdeok-gu, Cheongju-si. To achieve this, the EPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) was employed to generate runoff data by rainfall information. The produced runoff data facilitated the identification of flood occurrence points, and the analysis results exhibited a strong correlation with inundation trace maps provided by the Ministry of the Interior and Safety (MOIS). The detailed output of the SWMM model enabled the extraction of time-specific runoff information at each inundation point, allowing for a detailed understanding of the inundation status in the agricultural area over different time frames. This research underscores the significance of utilizing the SWMM model to simulate inundation in agricultural areas, thereby validating the efficacy of flood alerts and risk management plans. In particular, the integration of rainfall data and the SWMM model in flood prediction methodologies is expected to enhance the formulation of preventative measures and response strategies against flood damages in agricultural areas.

• 한국안전학회지
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• 제35권1호
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• pp.107-115
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• 2020

This paper introduces the first vital area identification (VAI) process for the physical protection of nuclear power plants (NPPs) during low power and shutdown (LPSD) operation. This LPSD VAI is based on the 3rd generation VAI method which very efficiently utilizes probabilistic safety assessment (PSA) event trees (ETs). This LPSD VAI process was implemented to the virtual NPP during LPSD operation in this study. Korea Atomic Energy Research Institute (KAERI) had developed the 2nd generation full power VAI method that utilizes whole internal and external (fire and flooding) PSA results of NPPs during full power operation. In order to minimize the huge burden of the 2nd generation full power VAI method, the 3rd generation full power VAI method was developed, which utilizes ETs and minimal PSA fault trees instead of using the whole PSA fault tree. In the 3rd generation full power VAI method, (1) PSA ETs are analyzed, (2) minimal mitigation systems for avoiding core damage are selected from ETs by calculating system-level target sets and prevention sets, (3) relatively small sabotage fault tree that has the systems in the shortest system-level prevention set is composed, (4) room-level target sets and prevention sets are calculated from this small sabotage fault tree, and (5) the rooms in the shortest prevention set are defined as vital areas that should be protected. Currently, the 3rd generation full power VAI method is being employed for the VAI of Korean NPPs. This study is the first development and application of the 3rd generation VAI method to the LPSD VAI of NPP. For the LPSD VAI, (1) many LPSD ETs are classified into a few representative LPSD ETs based on the functional similarity of accident scenarios, (2) a few representative LPSD ETs are simplified with some VAI rules, and then (3) the 3rd generation VAI is performed as mentioned in the previous paragraph. It is well known that the shortest room-level prevention sets that are calculated by the 2nd and 3rd generation VAI methods are identical.

• 한국화재소방학회논문지
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• 제28권6호
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• pp.52-57
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• 2014

본 연구는 건축 구조물의 방화 등으로 인해서 발생한 가연물의 연소현상을 분석하여 화재발생 시점을 예측하기 위한 기초 방안을 제시하였다. 이를 위해서 계단실 화재사고 사례로부터 가연물을 인터폰 개별현관기(이하 '인터폰'으로 표시)로 선정하고 룸코너시험기(room corner test equipment)에서 화재실험을 실시하여 시간 변화에 따른 발열량을 산출하였으며, 화재시뮬레이션 프로그램인 fire dynamics simulator (FDS)를 사용하여 화재성상 변화에 따라서 발화지점 하층부로 연기가 유입되는 시간을 비교하였다. 그 결과 가연물이 ABS 재질로 구성된 인터폰은 계단실 총 체적 공간 $291.3m^3$, 바닥면적 $23.3m^2$, 층간 높이 2.5 m인 경우 발화원의 열 유속 및 환경 조건에 따라서 최대 4.93배 정도 연기 유입 시간이 차이가 나는 것을 확인하였다. 본 연구는 가연물의 열화학적 특성 변화를 고려한 실험 자료를 해석모델에 적용하여 화재감식을 분석적으로 판단하는데 유용한 자료가 될 것으로 사료된다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제35권2호
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• pp.70-80
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• 2008

서비스 지향 아키텍처(Service Oriented Architecture)는 기업 인프라의 복잡성 및 유지비용을 최소화하고, 기업의 생산성과 유연성을 극대화할 수 있는 것으로, 경영환경이 빠르게 급변하는 최근에 떠오른 이슈이다. 엔터프라이즈 수준에서 서비스 지향 아키텍처를 도입하는 전략은 조직의 비즈니스 프로세스를 정의하고 이에 필요한 서비스를 모델링하여, 필요한 서비스를 찾아내거나 개발하는 하향식 전략이 대부분이다. 그러나 대부분의 조직은 SOA를 도입하면서도 기존에 사용하던 컴포넌트 시스템을 최대한 재사용할 수 있기를 바라고 있다. 본 논문에서는 이미 개발된 컴포넌트 기반 시스템에서 입출력 데이타가 아닌 GUI 이벤트 정보를 이용하여 상향식 방법으로, 서비스 재사용성과 유지보수성을 고려하면서 비즈니스 서비스 모델에 적합한 크기의 서비스를 식별할 수 있는 방법을 제안한다. 본 논문에서 제안한 방법은 실제 129개의 GUI와 13개의 컴포넌트를 가진 경영정보시스템에 적용한 결과 기존의 컴포넌트를 기준으로 서비스를 식별하는 것보다 결합도가 5배정도로 약해지면서 3개의 서비스가 명확히 구분되었고, 식별 후 연관관계에 따른 문제점도 약 49%정도 줄어드는 것을 보였다.