• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.474-477
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• 1989

The PDA (Probabilistic Data Association) Filter proposes a new approach to the problem of tracking when the source of the measurement data is uncertain. The PDA filter shows good simulation results in a known clutter density. In this paper the PDA filter has been modified so that it can be applied when the clutter density is not known.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.294-300
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• 2005

Generally, traditional approaches to track the target position are to estimate ranges and bearings by 2-D MUSIC (MUltiple 519na1 Classification) method. and to associate estimates of 2-D MUSIC made at different time points with the right targets by JPDA (Joint Probabilistic Data Association) filter in the near field. However, the disadvantages of these approaches are that these have the data association Problem in tracking multiple targets. and that these require the heavy computational load in estimating a 2-D range/bearing spectrum. In case multiple targets are adjacent. the tracking performance degrades seriously because the estimate of each target's Position has a large error. In this paper, we proposed a new tracking algorithm using Position innovations extracted from the senor output covariance matrix in the near field. The proposed algorithm is demonstrated by the computer simulations dealing with the tracking of multiple closing and crossing targets.

• Journal of Korea Water Resources Association
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• v.55 no.7
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• pp.515-529
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• 2022

Identifying the available water resources amount is an essential process in establishing a sustainable water resources management plan. Dam facility is a major infrastructure storing and supplying water during the dry season, and the water supply yield of the dam varies depending on dam inflow conditions or operation rule. In South Korea, water supply yield of dam is calculated by reservoir simulation based on observed historical dam inflow data. However, the water supply capacity of a dam can be underestimated or overestimated depending on the existence of historical drought events during the simulation period. In this study, probabilistic inflow data was generated and used to estimate the appropriate range of the water supply yield of hydropower dams. That is, a method for estimating the probabilistic dam inflow that fluctuates according to climatic and socio-economic conditions and the range of water supply yield for hydropower dams was presented, and applied to hydropower dams located in the Han river in South Korea. It is expected that the understanding water supply yield of the hydropower dams will become more important to respond to climate change in the future, and this study will contribute to national water resources management planning by providing potential range of water supply yield of hydropower dams.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.155-164
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• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.1
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• pp.16-24
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• 2011

Automotive Radar Systems are currently under development for various applications to increase accuracy and reliability. The target tracking is most important in single or multiple target environments for accuracy. The tracking algorithm provides smoothed and predicted data for target position and velocity(Doppler). To this end, the fixed gain filter(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter) and dynamic filter(Kalman filter, Singer-Kalman filter, etc) are commonly used. Gating is used to decide whether an observation is assigned to an existing track or new track. Gating algorithms are normally based on computing a statistical error distance between an observation and prediction. The data association takes the observation-to-track pairings that satisfied gating and determines which observation-to-track assignment will actually be made. For data association, NNPDA(Nearest Neighbor Probabilistic Data Association) algorithm is proposed. In this paper, we designed a target tracking system developed for an Automotive Radar System. We show the experimental results of the 77GHz FMCW radar sensor on the roads. Four tracking algorithms(${\alpha}{\beta}$ filter, ${\alpha}{\beta}{\gamma}$ filter, 2nd order Kalman filter, Singer-Kalman filter) have been compared and analyzed to evaluate the performance in test scenario.

• Journal of the Korean Data and Information Science Society
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• v.26 no.4
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• pp.857-864
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• 2015

By Wikipedia, data mining is the computational process of discovering patterns in huge data sets involving methods at the intersection of association rule, decision tree, clustering, artificial intelligence, machine learning. Clustering or cluster analysis is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. The similarity measures being used in the clustering may be classified into various types depending on the characteristics of data. In this paper, we computed bounds for similarity measures based on the probabilistic interestingness measure with partially marginal probability such as Peirce I, Peirce II, Cole I, Cole II, Loevinger, Park I, and Park II measure. We confirmed the absolute value of Loevinger measure wasthe upper limit of the absolute value of any other existing measures. Ordering of other measures is determined by the size of concurrence proportion, non-simultaneous occurrence proportion, and mismatch proportion.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.967-970
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• 2000

본 논문에서는 기동하는 표적을 추적하기 위한 표적의 운동 모델링 방법에 대해서 다룬다. 실제 표적의 운동은 진행방향으로의 가속과 이와는 독립적인 방향 전환으로 이루어진다는 점에 착안하여 표적의 진행방향에 따라 동작 잡음의 분산 행렬이 변화하는 표적 중심 모델을 제안하고, 이를 IMMPDAF(Interacting Multiple Model Probabilistic Data Association Filter)에 적용하였다. 모의실험을 통해 기존의 모델을 사용한 IMMPDAF와 비교하였으며, 그 결과 기동 구간의 오차가 30% 정도 줄어들며 추적 실패율도 낮아짐을 볼 수 있었다.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1155-1158
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• 1999

In this paper, we consider the optimal control of detection threshold to minimize the conditional mean-square state estimation error for the probabilistic data association (PDA) filter. Earlier works on this problem involved the cumbersome graphical optimization algorithm or time-consuming numerical optimization algorithm. Using the numerical approximation of information reduction factor, we obtained the closed-form optimal detection threshold. This results are very useful for real-time implemenation.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.7
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• pp.1013-1021
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• 2016

This study developed probabilistic models to predict Salmonella growth in processed meat products formulated with varying concentrations of NaCl and $NaNO_2$. A five-strain mixture of Salmonella was inoculated in nutrient broth supplemented with NaCl (0%, 0.25%, 0.5%, 0.75%, 0.5%, 1.0%, 1.25%, and 1.75%) and $NaNO_2$ (0, 15, 30, 45, 60, 75, 90, 105, and 120 ppm). The inoculated samples were then incubated under aerobic and anaerobic conditions at $4^{\circ}C$, $7^{\circ}C$, $10^{\circ}C$, $12^{\circ}C$, and $15^{\circ}C$ for up to 60 days. Growth (assigned the value of 1) or no growth (assigned the value of 0) for each combination was evaluated by turbidity. These growth response data were analyzed with a logistic regression to evaluate the effect of NaCl and $NaNO_2$ on Salmonella growth. The results from the developed model were compared to the observed data obtained from the frankfurters to evaluate the performance of the model. Results from the developed model showed that a single application of $NaNO_2$ at low concentrations did not inhibit Salmonella growth, whereas NaCl significantly (p<0.05) inhibited Salmonella growth at $10^{\circ}C$, $12^{\circ}C$, and $15^{\circ}C$, regardless of the presence of oxygen. At $4^{\circ}C$ and $7^{\circ}C$, Salmonella growth was not observed in either aerobic or anaerobic conditions. When $NaNO_2$ was combined with NaCl, the probability of Salmonella growth decreased. The validation value confirmed that the performance of the developed model was appropriate. This study indicates that the developed probabilistic models should be useful for describing the combinational effect of $NaNO_2$ and NaCl on inhibiting Salmonella growth in processed meat products.

• Water for future
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• v.4 no.1
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• pp.51-58
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• 1971

Hydrologic data serve as an input to the water resources system. An adequate analysis of hydrologic data is one of the most important steps in the planning of the water resources development program. The natural hydrologic processes, which produce the hydrologic data, are truely 'stochastic' in the sense that natural hydrologic phenomena change with time in accordance with the law of probability as well as with sequential relationship between their occurrences. Therefore, the stochastic approach to the analysis of hydrologic data has become more popular in recent years than the conventional deterministic or probabilistic approach. This paper reviews the mathematical models which can adequately simulate the stochastic behavior of the hydrologic characteristics of a hydrologic system. The actual application of these models in the analysis of hydrologic records(precipipitation and runoff records in particular) is also presented.