• Journal of Space Technology and Applications
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• v.2 no.2
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• pp.67-80
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• 2022

The missile early-warning satellite systems have been developed and upgraded by some space-developed nations, under the inevitable trend that the space is more strongly considered as another battle field than before. As the key function of such a satellite-based early warning system, the prediction algorithm of the missile flight trajectory is studied in the paper. In particular, the evolution computation, receiving broad attention in the artificial intelligence area, is applied to the proposed prediction method so that the global optimum-like solution is found avoiding disadvantage of the previous non-linear optimization search tools. Moreover, using the prediction simulator of the launch vehicle flight trajectory which is newly developed in C# and Python, the paper verifies the performance and the feature of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1130-1133
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• 2003

The goal of this research is developing advanced lane detecting algorithm for unmanned vehicle. Previous lane detecting method to bring on error become of the lane loss and noise. Therefore, new algorithm developed to get exact information of lane. This algorithm can be used to AGV(Autonomous Guide Vehicle) and LSWS(Lane Departure Warning System), ACC(Adapted Cruise Control). We used 1/10 scale RC car to embody developed algorithm. A CCD camera is installed on top of vehicle. Images are transmitted to a main computer though wireless video transmitter. A main computer finds information of lane in road image. And it calculates control value of vehicle and transmit these to vehicle. This algorithm can detect in input image marked by 256 gray levels to get exact information of lane. To find the driving direction of vehicle, it search line equation by curve fitting of detected pixel. Finally, author used median filtering method to removal of noise and used characteristic part of road image for advanced of processing time.

• Journal of the Korean Data and Information Science Society
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• v.24 no.2
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• pp.223-233
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• 2013

At local emerging stock markets such as Korea, Hong Kong, Singapore and Taiwan, foreign investors (FI) are recognized as important investment community due to the globalization and deregulation of financial markets. Therefore, it is required to monitor the behavior of FI against a sudden enormous selling stocks for the concerned local governments or private and institutional investors. The main aim of this study is to propose an early warning system (EWS) which purposes issuing a warning signal against the possible massive selling stocks of FI at the market. For this, we suggest machine learning algorithm which predicts the behavior of FI by forecasting future conditions. This study is empirically done for the Korean stock market.

• Journal of Korean Academy of Nursing
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• v.44 no.2
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• pp.219-227
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• 2014

Purpose: To assess whether the Modified Early Warning Score (MEWS) predicts the need for intensive care unit (ICU) transfer for patients with severe sepsis or septic shock admitted to general wards. Methods: A retrospective chart review of 100 general ward patients with severe sepsis or septic shock was implemented. Clinical information and MEWS according to point of time between ICU group and general ward group were reviewed. Data were analyzed using multivariate logistic regression and the area under the receiver operating characteristic curves with SPSS/WIN 18.0 program. Results: Thirty-eight ICU patients and sixty-two general ward patients were included. In multivariate logistic regression, MEWS (odds ratio [OR] 2.02, 95% confidence interval [CI] 1.43-2.85), lactic acid (OR 1.83, 95% CI 1.22-2.73) and diastolic blood pressure (OR 0.89, 95% CI 0.80-1.00) were predictive of ICU transfer. The sensitivity and the specificity of MEWS used with cut-off value of six were 89.5% and 67.7% for ICU transfer. Conclusion: MEWS is an effective predictor of ICU transfer. A clinical algorithm could be created to respond to high MEWS and intervene with appropriate changes in clinical management.

• Journal of Digital Policy
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• v.2 no.4
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• pp.33-39
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• 2023

With a continuous occurrence of right-turn traffic accidents at intersections, there is an increasing demand for measures to address these incidents. In response, a technology has been developed to detect the presence of pedestrians through object detection in CCTV footage at right-turn areas and display warning messages on the screen to alert drivers. The YOLO (You Only Look Once) model, a type of object detection model, was employed to assess the performance of object detection. An algorithm was also devised to address misidentification issues and generate warning messages when pedestrians are detected. The accuracy of recognizing pedestrians or objects and outputting warning messages was measured at approximately 82%, suggesting a potential contribution to preventing right-turn accidents

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.897-900
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• 2000

본 논문에서는 종방향 충돌경보 및 회피시스템(FCWA ; forward collision warning and avoidance)의 일환으로 가변적인 경사도를 가지는 고속도로상의 차선, 차량, 그리고 도로의 곡률을 효과적으로 검출할 수 있는 알고리듬을 제안하였다. 먼저 2D 영상좌표계에 나타나는 투영효과를 제거하기 위한 역투영(IPM; inverse perspective mapping)기법을 소개하였다. 또한 IPM과 필터로부터 차선과 차량을 효과적으로 검출할 수 있는 알고리듬을 소개하였다. 마지막으로 경사가 있는 실제도로영상에 대한 IMP의 수정된 파라미터 보정에 대한 개념 및 실제도로의 곡률 검출을 위한 기하학적 함수 추정기법을 설명하였다 실험결과 제안한 알고리듬이 실제도로영상에서 차선, 차량, 그리고 곡률의 검출에 효과적임을 확인할 수 있었다.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.849-854
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• 2007

This paper describes design and tuning of a full-range Adaptive Cruise Control (ACC) with collision avoidance. The control scheme is designed to control the vehicle so that it would feel natural to the human driver and passengers during normal safe driving situations and to avoid rear-end collision in vehicle following situations. In this study, driving situations are determined using a non-dimensional warning index and time-to-collision (TTC). A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC System. An ECU-Brake Hardware-in-the-loop Simulation (HiLS) was developed and used for an evaluation of ACC System. The ECU-Brake HiLS results for alternative driving situation are compared to manual driving data measured on actual traffic way. The ACC/CA control logic implemented in an ECU was tested using the ECU-Brake HiLS in a real vehicle environment.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.6
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• pp.517-523
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• 2010

In this paper, we proposed an algorithm to detect aggressive driving status by analysing six kinds of driving patterns, which was achieved by comparing for the feature vectors using mahalanobis distance. The first step is to construct feature matrix of $6{\times}2$ size using frequency response of the time-series accelerometer data. Singular value decomposition makes it possible to find the dominant eigenvalue and its corresponding eigenvector. We use the eigenvector as the feature vector of the driving pattern. We conducted real experiments using three drivers to see the effects of recognition. Although there exists differences from individual drivers, we showed that driving patterns can be recognized with about 80% accuracy. Further research topics will include the development of aggressive driving warning system by improving the proposed technique and combining with post-processing of accelerometer signals.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.722-728
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• 1998

In this paper real-time estimation methods for identifying the tire-road friction coefficient are presented. Taking advantage of the Magic Formula Tire Model, the similarity technique and the specific model for the vehicle dynamics, a reduced order observer/filtered-regressor-based method is proposed. The Proposed method is evaluated on simulations of a full-vehicle model with an eight state nonlinear vehicle/transmission model and nonlinear suspension model. It has been shown through simulations that it is possible to estimate the tire-road friction from measurements of engine rpm, transmission output speed and wheel speeds using the proposed identification method. The proposed method can be used as a useful option as a part of vehicle collision warning/avoidance systems and will be useful in the implementation of a warning algorithm since the tire-road friction can be estimated only using RPM sensors.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.43-47
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• 1998

In this paper we present the method that improve alarm security system using the electronic circuits added the emergency lamp by our proposed Algorithms. In conventional method the emergency lamp of warning & alarm system was not executed perfectly its performance because of battery with short life. For improving this problem we, using Peripheral Interface Controller IC, designed the circuit added the emergency lamp for an warning & alarm system and for prevent from stopping the electric current, and compared our proposed method with conventional method. By designing the circuit to stop up over charge we can extend life of battery, use of a stoppage of electric current in emergency and according to the lightness around. Therefore we are very convenient and profitable in our life. In this future we will study the method to lower the cost of architecture for practical utilization.