• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.3
• /
• pp.1-8
• /
• 2000

In this paper, we formulate an optimal control problem to obtain the optimal signal strength and detection threshold for tracking with NN filter, First, we predict the tracking performance of NN filter by using the HYCA method. Based on this method, the predicted tracking performance is represented with respect to signal strength and detection threshold. Using this relation, we find the optimal parameters for following three examples： 1) the sequence of optimal detection threshold which minimizes sum of position estimation error； 2) the sequence of optimal detection threshold which minimizes sum of validation gate volume； and 3) the sequence of optimal signal strength and detection threshold which minimizes sum of signal strength.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.396-402
• /
• 2001

In various applications of queueing systems, admission control is often employed. It is known that the threshold-type of admission control is optimal in many practical applications despite its simplicity. However, determining the optimal threshold value is hard in general, because analytical expressions for the stationary queue length distributions are not easily available in most queueing systems. In this paper, to quickly determine the optimal threshold value under threshold-type admission control, we develop a concurrent simulation technique, which can save large amount of CPU time required in simulation, compared to the standard simulation procedure.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2576-2581
• /
• 2003

We consider fault detection and isolation (FDI) problem for inertial navigation systems (INS) which use redundant inertial sensors and propose an FDI method using average of multiple parity vectors which reduce false alarm and wrong isolation, and improve correct isolation. We suggest optimal isolation threshold based on navigation performance, and suggest optimal sample number to obtain short detection time and to enhance detectability of faults little larger than threshold.

• Journal of Applied Reliability
• /
• v.17 no.3
• /
• pp.246-255
• /
• 2017

Purpose: This study proposes the optimal PM (preventive maintenance) policy of leased equipment for lessee's decision-making using two types of reliability condition. Methods: We consider reliability threshold based PM model. Equipment reliability is estimated and used as condition variable. The effect of repair for maintenance is imperfect and represented by age reduction factor. Results: We provide two PM policies. Policy 1 is focused on minimized total cost. This policy guarantees reliability threshold until last maintenance action. Policy 2 focus on maintaining reliability threshold during leased period. The proposed approach provides optimal reliability threshold under number of PM. Through result, we finally construct decision-making process for lessee using reliability threshold and end of reliability. Conclusion: This study provides two PM policy for lessee's decision-making. Through numerical example, we get a result of optimal reliability threshold, number of PM, optimum alternative under lessee's reliability condition.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.1
• /
• pp.255-260
• /
• 2015

Among many optimal threshold criteria from ROC curve, the closest-to-(0,1) and amended closest-to-(0,1) criteria are considered. An ROC curve that passes close to the (0,1) point indicates that two models are well classified. In this case, the ROC curve is located far from the (1,0) point. Hence we propose two criteria: the farthest-to-(1,0) and amended farthest-to-(1,0) criteria. These criteria are found to have a relationship with the KolmogorovSmirnov statistic as well as some optimal threshold criteria. Moreover, we derive that a definition for the proposed criteria with more than two dimensions and with relations to multi-dimensional optimal threshold criteria.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.5
• /
• pp.91-102
• /
• 2020

The study investigates the relationship between the inflation rate and economic growth to find out the optimal inflation threshold for economic growth. Therefore, this study applied an ordinary least square model (OLS) and the ordinal regression model, and collected the time-series data from 1996 to 2017 to test the relationship between inflation and economic growth in the short-term and long-term. The sample fits the model and is statistically significant. The study showed that 96.6% of correlation between inflation rate and economic growth are close and 4.5% of optimal inflation threshold is appropriate for economic growth. It finds that the optimal inflation threshold is base to perform economic growth, besides the inflation rate is positively related to economic growth. The results support the monetary policy appropriately. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; have appropriate policies to regulate inflation to stimulate economic growth over the long term; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the optimal inflation threshold.

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.271-285
• /
• 2009

Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

• Journal of Biomedical Engineering Research
• /
• v.30 no.6
• /
• pp.516-520
• /
• 2009

The purpose of this study is to determine optimal filtering condition and threshold for the detection of gait-cycles for various walkway slopes as well as gait velocities. Ten young healthy subjects with accelerometer system on thigh and ankle walked on a treadmill at 9 conditions (three speeds and three slopes) for 5 minutes. Two direction signals, i.e. anterior-posterior (AP) and superior-inferior (SI) directions, of each sensor (four sensor orientations) were used to detect specific events of gait cycle. Variation of the threshold (from -1G to 1G) and lowpass cutoff frequency (fc) were applied to the event detection and their performance was evaluated according to the error index (EI), which was defined as the combination of the accuracy and false positive rate. Optimal fc and threshold were determined for each slope in terms of the EI. The optimal fc, threshold and their corresponding EI depended much on the walkway slope so that their coefficients of variation (CV) ranged 19~120%. When all data for 3 slopes were used in the identification of optimal conditions for each sensor, the best error indices for all sensor orientations were comparable ranging 1.43~1.76%, but the optimal fc and threshold depended much on the sensor position. The result indicates that the gait-cycle detection robust to walkway slope is possible by threshold method with well-defined filtering condition and threshold.

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

• Journal of the Korea Society of Computer and Information
• /
• v.12 no.6
• /
• pp.167-175
• /
• 2007

Fuzzy logic is used to represent qualitative knowledge and provides interpretability to a controlling system model in bioinformatics. This paper focuses on a bioinformatics data classification which is an important bioinformatics application. This paper reviews the two traditional controlling system models The sequence-based threshold controller have problems of optimal range decision for threshold readjustment and long processing time for optimal threshold induction. And the binary-based threshold controller does not guarantee for early system stability in the GPCR data classification for optimal threshold induction. To solve these problems, we proposes a fuzzy-based threshold controller for ART1 clustering in GPCR classification. We implement the proposed method and measure processing time by changing an induction recognition success rate and a classification threshold value. And, we compares the proposed method with the sequence-based threshold controller and the binary-based threshold controller The fuzzy-based threshold controller continuously readjusts threshold values with membership function of the previous recognition success rate. The fuzzy-based threshold controller keeps system stability and improves classification system efficiency in GPCR classification.