• ETRI Journal
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• v.32 no.1
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• pp.120-128
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• 2010

In this paper, we describe a modified fixed-threshold sequential minimal optimization (FSMO) for 1-slack structural support vector machine (SVM) problems. Because the modified FSMO uses the fact that the formulation of 1-slack structural SVMs has no bias, it breaks down the quadratic programming (QP) problems of 1-slack structural SVMs into a series of smallest QP problems, each involving only one variable. For various test sets, the modified FSMO is as accurate as existing structural SVM implementations (n-slack and 1-slack SVM-struct) but is faster on large data sets.

• ETRI Journal
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• v.31 no.2
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• pp.121-128
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• 2009

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).

• Journal of Acupuncture Research
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• v.29 no.4
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• pp.25-34
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• 2012

Objectives : This study was conducted to investigate the effects of fixed-intensity and varied-intensity electroacupuncture in pain and sensory threshold concerning parameters visual analogue scale(VAS), brief pain inventory(BPI) and quantitative sensory testing(QST), among chronic tension headache patients. Methods : Thirty patients with chronic tension headache were randomly assigned to three groups and received different kinds of electroacupuncture at $ST_{36}$ and $ST_{37}$. Group A received fixed-intensity electroacupuncture(fixed-EA), group B received varied-intensity electroacupuncture (varied-EA), and group C received only acupuncture treatment without electrical stimulation as a control group. The intervention was given three times per week, and continued in two weeks. All the experiments were conducted blindly. Results : Fixed-EA group showed a significant decrease of VAS and BPI compared to the baseline measurement, while both varied-EA and control group did not. Of the parameters of QST, subtraction of heat pain threshold(HPT) and cold pain threshold(CPT) slightly increased in all groups, but this was not significant. Conclusions : These results suggest that fixed-EA reduce pain and improve quality of life in patients with chronic tension headache and that acupuncture may regulate patient's pain sensitivity through changing sensory threshold.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.756-763
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• 2020

Objective: To evaluate the effects of attenuation threshold on CT pulmonary vascular volume ratios in children and young adults with congenital heart disease, and to suggest an optimal attenuation threshold. Materials and Methods: CT percentages of right pulmonary vascular volume were compared and correlated with percentages calculated from nuclear medicine right lung perfusion in 52 patients with congenital heart disease. The selected patients had undergone electrocardiography-synchronized cardiothoracic CT and lung perfusion scintigraphy within a 1-year interval, but not interim surgical or transcatheter intervention. The percentages of CT right pulmonary vascular volumes were calculated with fixed (80-600 Hounsfield units [HU]) and adaptive thresholds (average pulmonary artery enhancement [PA_avg] divided by 2.50, 2.00, 1.75, 1.63, 1.50, and 1.25). The optimal threshold exhibited the smallest mean difference, the lowest p-value in statistically significant paired comparisons, and the highest Pearson correlation coefficient. Results: The PA_avg value was 529.5 ± 164.8 HU (range, 250.1-956.6 HU). Results showed that fixed thresholds in the range of 320-400 HU, and adaptive thresholds of PA_avg/1.75-1.50 were optimal for quantifying CT pulmonary vascular volume ratios. The optimal thresholds demonstrated a small mean difference of ≤ 5%, no significant difference (> 0.2 for fixed thresholds, and > 0.5 for adaptive thresholds), and a high correlation coefficient (0.93 for fixed thresholds, and 0.91 for adaptive thresholds). Conclusion: The optimal fixed and adaptive thresholds for quantifying CT pulmonary vascular volume ratios appeared equally useful. However, when considering a wide range of PAavg, application of optimal adaptive thresholds may be more suitable than fixed thresholds in actual clinical practice.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7B
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• pp.892-896
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• 2011

This paper proposes a two-stage synchronization scheme using a serial search non-coherent correlator appropriate for the IEEE 802.15.4a system. The proposed method improved the synchronization performance by using multi-pulse signals unlike the conventional method using single-pulse signals. It also compensated for the degradation of performance at low SNR resulting from the use of fixed threshold by applying the adaptive threshold technique. The proposed method showed a detection probability that is higher by approximately 0.2-0.3 compared with the conventional method in the IEEE 802.15.4a channel model.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.213-219
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• 2021

The submarine's intercept pulse detection detects pulses radiated from enemy surface ships, submarines, and torpedoes, and performs an important function of providing maneuverability and survivability of submarine. Whether or not the intercept pulse is detected is determined by comparing the size of the received pulse with the threshold value by the operator. In the case of intercept pulses, the intensity of the pulses is frequently reduced under the influence of various environmental factors. In the situation, if detection is performed with a fixed threshold, a non-detection problem occurs and persists until the operator sets a low threshold. In this paper, we proposed method for automatically adjusting threshold to reduce the non-detection problem caused by a fixed threshold. Simulation were preformed on 4 cases with different pulse level fluctuation widths, and it was confirmed that the detection performance was improved by increasing the number of detections when a method for automatically adjusting threshold was applied to all cases. Through the proposed method, it is expected that the intercept pulse detection performance will be improved in the marine environment the large fluctuations in pulse level in the future.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.61-65
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• 2013

In this paper, we propose system model to solve conventional threshold problem of using fixed false alarm for energy spectrum sensing. Spectrum sensing reliability is ensured when Secondary user have high SNR. Thus, it is not reasonable using fixed optional false alarm without considering CR user's SNR. So, we propose adaptive threshold method. adaptive threshold is decided by controling FA according to CR user's SNR.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.91-96
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• 2014

This paper proposed an adaptive threshold method for detecting flame candidate regions in a infrared image and it adapts according to the contrast and intensity changes in the image. Conventional flame detection systems uses fixed threshold method since surveillance environment does not change, once the system installed. But it needs a adaptive threshold method as requirements of surveillance system has changed. The proposed adaptive threshold algorithm uses the dynamic behavior of flame as featured parameter. The test result is analysed by comparing test result of proposed adaptive threshold algorithm and conventional fixed threshold method. The analysed data shows, the proposed method has 91.42% of correct detection rate and false detection is reduced by 20% comparing to the conventional method.

• 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.

• ETRI Journal
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• v.40 no.4
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• pp.531-536
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• 2018

The weighted K-nearest neighbor (WKNN) algorithm is used to reduce positioning accuracy, as it uses a fixed number of neighbors to estimate the position. In this paper, we propose a dynamic threshold location algorithm (DH-KNN) to improve positioning accuracy. The proposed algorithm is designed based on a dynamic threshold to determine the number of neighbors and filter out singular reference points (RPs). We compare its performance with the WKNN and Enhanced K-Nearest Neighbor (EKNN) algorithms in test spaces of networks with dimensions of $20m{\times}20m$, $30m{\times}30m$, $40m{\times}40m$ and $50m{\times}50m$. Simulation results show that the maximum position accuracy of DH-KNN improves by 31.1%, and its maximum position error decreases by 23.5%. The results demonstrate that our proposed method achieves better performance than other well-known algorithms.