• 한국수자원학회:학술대회논문집
• /
• 한국수자원학회 2009년도 학술발표회 초록집
• /
• pp.2200-2204
• /
• 2009

In this paper the analysis of natural cause of Beijing Storm inundation and the effect of the human activities has been taken. Flood risk can hardly be eliminated solely by projects. Pre-warning system established is an efficient measure to minimize the influence of flood. Several main functions of this system and their examples are described in the paper, such as: monitoring, forecast, scheme, warning, dynamic decision-making and information publication.

• The Journal of Asian Finance, Economics and Business
• /
• 제4권1호
• /
• pp.39-49
• /
• 2017

This study develops an early warning system (EWS) to prevent the banking crisis. The proposed system incorporates both the perspective of crises and fundamental characteristics of the banking system in each economy. A fuzzy logic method with data from 1990-2009 is employed to construct the EWS of banking crisis based on 21 pre-determined variables from the aspect of total economy, financial and banking sectors. Our results show: Firstly, South Korea recorded higher probability to have a banking crisis in 1997 as there was large foreign debt in dollars. Secondly, China, Australia and New Zealand banking systems appear to be vulnerable to the crisis in 2007. The surge of China export, FDIs and booming stock market were signs of a heated economy. Australia with high commodity prices was also vulnerable to crisis. Thirdly, Australia, China, Japan and New Zealand banking systems appear to be exposed to the higher chance of a crisis in 2010. Japan with deflation coupled with expensive yen did not augur well for its export. Overall, the findings show that in Asian Financial Crisis 1997/98 and Global Financial Crisis 2008/09, many economies are exposed to a higher probability of having the crisis and this shows an urgent need of having surveillance in these economies.

• 지질공학
• /
• 제34권2호
• /
• pp.173-191
• /
• 2024

Landslides pose significant threats to many countries globally, yet the development and implementation of effective landslide early warning systems (LEWS) remain challenging due to multifaceted complexities spanning scientific, technological, and political domains. Addressing these challenges demands a holistic approach. Technologically, integrating thresholds, such as rainfall thresholds, with real-time data within accessible, open-source software stands as a promising solution for LEWS. This article introduces LandScient_EWS, a PHP-based program tailored to address this need. The software facilitates the comparison of real-time measured data, such as rainfall, with predefined landslide thresholds, enabling precise calculations and graphical representation of real-time landslide advisory levels across diverse spatial scales, including regional, basin, and hillslope levels. To illustrate its efficacy, the program was applied to a case study in Medellin, Colombia, where a rainfall event on August 26, 2008, triggered a shallow landslide. Through pre-defined rainfall intensity and duration thresholds, the software simulated advisory levels during the recorded rainfall event, utilizing data from a rain gauge positioned within a small watershed and a single grid cell (representing a hillslope) within that watershed. By identifying critical conditions that may lead to landslides in real-time scenarios, LandScient_EWS offers a new paradigm for assessing and responding to landslide hazards, thereby improving the efficiency and effectiveness of LEWS. The findings underscore the software's potential to streamline the integration of rainfall thresholds into both existing and future landslide early warning systems.

• 정보처리학회논문지B
• /
• 제16B권1호
• /
• pp.35-46
• /
• 2009

본 논문에서는 차량에 설치된 카메라를 활용하여 차선을 추출하고, 차량이탈을 검출하기 위한 방법에 대해서 논의한다. 하드웨어 기술의 발달로 지능형 자동차에 대한 연구가 활발히 진행됨에 따라서, 카메라를 활용한 차선인식 및 차량이탈검출과 관련하여 다양한 알고리즘들이 제시 되었다. 그러나 이들 연구에서는 영상에서 2개의 차선을 모두 찾아야 하기 때문에 처리속도 및 실제 운행환경에서의 다양한 여건으로 인하여 검출률이 떨어진다는 문제점이 있다. 본 논문에서는 빠른 속도와 높은 검출률을 위해 단일차선을 추출하고, 중심점 분석을 통한 차선이탈검출 알고리즘을 제안한다. 카메라의 기하학적 모델링을 통하여 차선이 존재하는 관심영역을 설정하고, 원본 이미지를 이등분한 후에 허프변환(Hough Transform)을 사용하여 한 차선의 일부를 찾아낸 후에, 일정 크기로 복원한다. 복원한 차선을 설정된 중심점과의 거리계산을 통하여 차선이탈을 판단한다. 실차실험을 통하여 제안한 알고리즘을 기존의 알고리즘과 비교 검증을 수행하였고, 이를 통하여 제안된 알고리즘이 빠르고 정확함을 보였다.

• 전기학회논문지
• /
• 제63권4호
• /
• pp.526-533
• /
• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• 한국가스학회지
• /
• 제16권6호
• /
• pp.102-106
• /
• 2012

이 논문의 목적은 현장에서 발생되는 자동차 에어백 시스템의 고장사례를 모아 분석하고 연구하는 것이다. 첫 번째 사례에서는 에어백 시스템의 클럭 스프링과 에어 백 모듈 사이 배선 핀의 납땜부가 이탈되어, 배선 접촉불량에 의해 핀이 흔들릴 때마다 에어백의 작동불량 현상이 발생되는 것을 확인하였다. 두 번째 사례에서는 에어백 컴퓨터 내부의 단품 소자의 손상으로 인해 에어백 작동불량 현상이 발생된 것을 확인하였다. 세 번째 사례에서는 조수석 시트 벨트 프리텐셔너(pre-tensioner)의 내부 핀과 저항을 연결해 주는 납땜부 이탈로 인해 에어백 경고등이 점등된 것을 확인하였다. 네 번째 사례에서는 승용자동차가 화물자동차의 후면을 추돌하였을 때 때 범퍼는 상대편 차량보다 낮아 아래로 끼어들게 된다. 이 때 사고의 충격은 차량의 프레임부분에 전달되지 않기 때문에 충격센서가 설치된 프레임부분에 충격이 적게 전달되어 에어백이 작동하지 않은 것을 확인하였다.

• 생태와환경
• /
• 제41권4호
• /
• pp.466-471
• /
• 2008

Little is known about DNA-level and physiological levels for health assessments of stream or river environments. Recently, comet assay, so called Single Cell Gel Electrophoresis (SCGE) is introduced for assessments of DNA damage in the medical science, food science and mammal toxicology. The comet assay is known as a biomarker which is one of the best barometers in assessing the DNA damage by oxidative stress. In this study, we conducted the comet assay using sentinel species, Zacco platypus, as one of the pre-warning alarm systems for the aquatic ecosystem health assessments and also applied it to Gap Stream as a model system. Tail extent moments in the S1 and S2 were 5.20 and 9.90 respectively and the moment was 19.89 in the S3. Statistical ANOVA in the tail moments showed a significant difference (n=75, p<0.05) between S1 and S3. Also, the proportions of DNA in the tail were 14.47, 23.64, and $30.04{\mu}m$ in the upstream (control site), midstream, downstream sites, respectively. Our results in the downstream were accord with previous studies of individual-level, population-level, and community-level in Gap Stream. Our results suggest that the comet assay may be used as an important tool for diagnosing ecological health of aquatic ecosystems in the level of DNA.

• 한국정밀공학회지
• /
• 제16권10호
• /
• pp.25-34
• /
• 1999

In this paper, an algorithm is presented to recognize lane and obstacles based on highway road image. The road images obtained by a video camera undergoes a pre-processing that includes filtering, edge detection, and identification of lanes. After this pre-processing, a part of image is grouped into 27 sub-windows and fed into a three-layer feed-forward neural network. The neural network is trained to indicate the road direction and the presence of absence of an obstacle. The proposed algorithm has been tested with the images different from the training images, and demonstrated its efficacy for recognizing lane and obstacles. Based on the test results, it can be said that the algorithm successfully combines the traditional image processing and the neural network principles towards a simpler and more efficient driver warning of assistance system

• 한국정밀공학회지
• /
• 제30권2호
• /
• pp.164-170
• /
• 2013

The latest vehicle yields a superior safety and reduction of driving burden by monitoring the driving state of vehicle and its environment with various sensors. To detect other vehicles and objects of the rear left and right-side blind spot area of driver, provide the information about a existence of objects inside the blind spot, and give a signal to avoid collision, this study proposes the intelligent outside rear-view mirror system. This study proposes SILS system with PreScan and Matlab/Simulink to verify practical applicability of developed BSDS. PreScan yields realistic driving environments and road conditions and vehicle model dynamics and collision warning is controlled by Matlab/Simulink.

• Smart Structures and Systems
• /
• 제33권5호
• /
• pp.365-374
• /
• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. 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.