• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.39-42
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• 1994

An automatic multi-threshold algorithm for segmentation of 2D ultrasound images based on average filtering and the characteristics of speckle noise in 2D ultrasound image is proposed. To do this, we investigate the histogram of difference between $7{\times}7$ averaging histogram and $3{\times}3$ averaging histogram. And, we find zero crossing points in the positive portion of the differenced histogram and select middle points of the zero crossing points. We assign these selected points to characteristic points. The thresholds are the center of two characteristic points. Then we segment 2D ultrasound image by using these thresholds and extract edges from applying edge operator to optimal segmented image. Experimental results show that the segmented regions are devided accurately around the homogeneous region.

• Industrial Engineering and Management Systems
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• v.10 no.4
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• pp.272-278
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• 2011

Decision tree as a classification tool is being used successfully in many areas such as medical diagnosis, customer churn prediction, signal detection and so on. The main advantage of decision tree classifiers is their capability to break down a complex structure into a collection of simpler structures, thus providing a solution that is easy to interpret. Since decision tree is a top-down algorithm using a divide and conquer induction process, there is a risk of reaching a local optimal solution. This paper proposes a procedure of optimally determining thresholds of the chosen variables for a decision tree using an adaptive particle swarm optimization (APSO). The proposed algorithm consists of two phases. First, we construct a decision tree and choose the relevant variables. Second, we find the optimum thresholds simultaneously using an APSO for those selected variables. To validate the proposed algorithm, several artificial and real datasets are used. We compare our results with the original CART results and show that the proposed algorithm is promising for improving prediction accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1217-1233
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• 2015

The paper studies characteristics of the minimum mean-square error symmetric scalar quantizers for the generalized gamma, Bucklew-Gallagher and Hui-Neuhoff probability density functions. Toward this goal, asymptotic formulas for the inner- and outermost thresholds, and distortion are derived herein for nonuniform quantizers for the Bucklew-Gallagher and Hui-Neuhoff densities, parallelling the previous studies for the generalized gamma density, and optimal uniform and nonuniform quantizers are designed numerically and their characteristics tabulated for integer rates up to 20 and 16 bits, respectively, except for the Hui-Neuhoff density. The assessed asymptotic formulas are found consistently more accurate as the rate increases, essentially making their asymptotic convergence to true values numerically acceptable at the studied bit range, except for the Hui-Neuhoff density, in which case they are still consistent and suggestive of convergence. Also investigated is the uniqueness problem of the differentiation method for finding optimal step sizes of uniform quantizers: it is observed that, for the commonly studied densities, the distortion has a unique local minimizer, hence showing that the differentiation method yields the optimal step size, but also observed that it leads to multiple solutions to numerous generalized gamma densities.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.176-181
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• 2002

In this paper, we consider the optimal control of detection threshold to minimize the conditional expectation of mean-square state estimation error for a 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 suboptimal detection threshold in a closed-form. This results are very useful for real- time implementation.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1521-1530
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• 2014

The ROC analysis is considered for multiple class diagnosis. There exist many criteria to find optimal thresholds and measure the accuracy of diagnostic tests for k dimensional ROC analysis. In this paper, we proposed a diagnostic accuracy measure called the correct classification simple rate, which is defined as the summation of true rates for each classification distribution and expressed as a function of summation of sequential true rates for two consecutive distributions. This measure does not weight accuracy across categories by the category prevalence and is comparable across populations for multiple class diagnosis. It is found that this accuracy measure does not only have a relationship with Kolmogorov - Smirnov statistics, but also can be represented as a linear function of some optimal threshold criteria. With these facts, the suggested measure could be applied to test for comparing multiple distributions.

• The Journal of Engineering Geology
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• v.20 no.1
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• pp.89-100
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• 2010

Although various methods for determination of damage threshold in rock have been suggested, clear damage thresholds were determined by some methods, but different thresholds were measured by other methods. We determined the damage thresholds in Hangdeung granite using all the methods suggested, and investigated the best methods, applicability and errors of each method. The crack initiation threshold and the crack damage threshold which are important in investigation of characteristics of crack development and failure were verified by field strength ratio method and long-term constant load test. The crack closure stress and the crack initiation stress were 57.5 MPa and 77.6 MPa, and the most exact values were yielded by crack volumetric strain. The secondary crack initiation stress was 90.6 MPa and AE event count and AE event count rate were the effective methods. The volumetric stiffness, AE event count and AE event count rate were the most effective methods for determination of crack coalescence threshold and crack coalescence stress was 110.3 MPa. The crack damage stress was 127.5 MPa and was measured correctly by volumetric stiffness and AE event count rate. The ratio between crack initiation stress and uniaxial compressive strength was 0.47 which was very similar with the FSR value of 0.46. The ratio between crack damage stress and uniaxial compressive strength was almost the same as the ratio between long-term strength and uniaxial compressive strength, indicating that the crack initiation stress and the crack damage stress measured were correct.

• The KIPS Transactions:PartC
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• v.18C no.3
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• pp.127-134
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• 2011

Malicious botnet has been used for more malicious activities, such as DDoS attacks, sending spam messages, steal personal information, etc. To prevent this, many studies have been preceded. But malicious botnets have evolved and evaded detection systems. In particular, HTTP GET Request attack that exploits the vulnerability of the application layer is used. ALAB of ALADDIN proposed by ETRI is DDoS attack detection system that HTTP GET, Incomplete GET request flooding attack detection algorithm is applied. In this paper, we extend Incomplete GET detection algorithm of ALAB and derive the optimal configuration parameters to verify the validity of the algorithm ALAB by the study of the normal and attack packets.

• Atmosphere
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• v.21 no.4
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• pp.497-506
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• 2011

Korean mid- and upper-level aviation turbulence guidance (KTG) system is developed using the unified model (UM)-based regional data assimilation and prediction system (RDAPS) of the Korea Meteorological Administration. The KTG system includes three steps. First, the KTG system calculates a suite of diagnostics in the UM-RDAPS domain. Second, component diagnostics that have different units and numerical magnitudes are normalized into the values between 0 and 1, according to their own thresholds in the KTG system. Finally, normalized diagnostics are combined into one KTG predictor by measuring the weighting scores based on the probability of detection, which is calculated using the observed pilot reports (PIREPs) exclusively of moderate-or-greater (MOG) and null (NIL) intensities. To investigate the optimal performance of the KTG system, two types (RD-KTG and UM-KTG) of the KTG systems are developed and evaluated using the PIREPs over Korea and East Asia. Component diagnostics and their thresholds in the RD-KTG are founded on the 8-yrs (2002.12-2010.11) MM5-based RDAPS (previous version of the RDAPS; ${\Delta}x$ = 30 km) and PIREPs data, while those in the UM-KTG are based on the 6 months (2010.12-2011.5) UM-based RDAPS (${\Delta}x$ = 12 km) and PIREPs data. In comparison between the RD-KTG and UM-KTG, overall performance of the UM-KTG (0.815) is better than that of the RD-KTG (0.79) during the recent 6 months, because forecasting skill for the upper-level wind is higher in the UM-RDAPS than in the MM5-RDAPS. It is also found that the UM-KTG is more efficient than the RD-KTG according to the statistical evaluations and sensitivity tests to the number of component diagnostics.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.1
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• pp.159-170
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• 2013

The effect of climate change on urban woody plants remains difficult to predict in urban areas. Depending on its tolerances, a plant species may stay and survive or stay with slowly declining remnant populations under a changing climate. To predict those vulnerabilities on urban woody plants, this study suggests a basic bioclimatic envelop model of heat requirements, cold tolerance, chilling requirements and moisture requirements that are well documented as the 'climatic niche'. Each component of the 'climatic niche' is measured by the warmth index, the absolute minimum temperature, the number of chilling weeks and the water balance. Regarding the utility of the developed model, the selected urban plant's present probabilities are suggested in the future climate of Seoul. Both Korea and Japan's thermal thresholds are considered for a plant's optimal climatic niche. By considering the thermal thresholds of these two regions for the same species, the different responses observed will reflect the plant's 'hardening' process in a rising climate. The model illustrated that the subpolar plants Taxus cuspidata and Ulmus davidiana var. japonica are predicted to have low suitability in Seoul. The temperate plants Zelkova serrata and Pinus densiflora, which have a broad climatic niche, exhibited the highest present probability in the future. The subtropical plants Camellia japonica and Castanopsis cuspidata var. sieboldii may exhibit a modest growth pattern in the late 21C's future climatic period when an appropriate frost management scheme is offered. The model can be used to hypothesize how urban ecosystems could change over time. Moreover, the developed model can be used to establish selection guidelines for urban plants with high levels of climatic adaptability.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.100-104
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• 2013

In this paper, we present an optimal threshold setting method for flame detection of infrared thermal image. Conventional infrared flame detection methods used fixed intensity threshold to segment candidate flame regions and further processing is performed to decide correct flame detection. So flame region segmentation step using the threshold is important processing for fire detection algorithm. The threshold should be change in input image depends on camera types and operation conditions. We have analyzed the conventional thresholds composed of fixed-intensity, average, standard deviation, maximum value. Finally, we extracted that the optimal threshold value is more than summation of average and standard deviation, and less than maximum value. it will be enhance flame detection rate than conventional fixed-threshold method.