• Journal of the Semiconductor & Display Technology
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• v.7 no.1
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• pp.23-27
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• 2008

Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

• 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.

• Journal of Communications and Networks
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• v.12 no.1
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• pp.74-85
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• 2010

For the purpose of compromising hosts, attackers including infected hosts initially perform a portscan using IP addresses in order to find vulnerable hosts. Considerable research related to portscan detection has been done and many algorithms have been proposed and implemented in the network intrusion detection system (NIDS). In order to distinguish portscanners from remote hosts, most portscan detection algorithms use a fixed threshold that is manually managed by the network manager. Because the threshold is a constant, even though the network environment or the characteristics of traffic can change, many false positives and false negatives are generated by NIDS. This reduces the efficiency of NIDS and imposes a high processing burden on a network management system (NMS). In this paper, in order to address this problem, we propose an automatic portscan detection system using an fast increase slow decrease (FISD) scheme, that will automatically and adaptively set the threshold based on statistical data for traffic during prior time periods. In particular, we focus on reducing false positives rather than false negatives, while the threshold is adaptively set within a range between minimum and maximum values. We also propose a new portscan detection algorithm, rate of increase in the number of failed connection request (RINF), which is much more suitable for our system and shows better performance than other existing algorithms. In terms of the implementation, we compare our scheme with other two simple threshold estimation methods for an adaptive threshold setting scheme. Also, we compare our detection algorithm with other three existing approaches for portscan detection using a real traffic trace. In summary, we show that FISD results in less false positives than other schemes and RINF can fast and accurately detect portscanners. We also show that the proposed system, including our scheme and algorithm, provides good performance in terms of the rate of false positives.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2331-2334
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• 2003

Generally, skin color information has been widely used at the face region extraction step of the face region recognition process. But many experimental results show that they are very sensitive to the given threshold range which is used to extract the face regions at the input image. In this paper, we propose a face region extraction algorithm based on an adaptive range decision for skin color. First we extract the pixels which are regarded as the candidate skin color pixels by using the given range for skin color extraction. Then, the ratio between the total pixels and the extracted pixels is calculated. According to the ratio, we adaptively decide the range of the skin color and extract face region. From the experiment results for the various images, the proposed algorithm shows more accurate results than the conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.767-783
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• 2013

This paper aims at designing a selective demodulation scheme based on Log-likelihood Ratio threshold (SDLT) instead of the conventional adaptive demodulation (ADM) scheme, by using rateless codes. The major difference is that the Log-likelihood ratio (LLR) threshold is identified as a key factor to control the demodulation rate, while the ADM uses decision region set (DRS) to adjust the bit rate. In the 16-QAM SDLT scheme, we deduce the decision regions over an additive white Gaussian channel, corresponding to the variation of LLR threshold and channel states. We also derived the equations to calculate demodulation rate and bit error rate (BER), which could be proven by simulation results. We present an adaptation strategy for SDLT, and compare it with ADM and adaptive modulation (AM). The simulation results show that our scheme not only significantly outperforms the ADM in terms of BER, but also achieves a performance as good as the AM scheme. Moreover, the proposed scheme can support much more rate patterns over a wide range of channel states.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.205-211
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• 2012

By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.12
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• pp.24-30
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• 2003

In this paper, we proposed an adaptive ATC(Automatic Threshold Control) circuit with more decreased settling time by improving the structure of the peak detector. We showed that it could reduce a good deal of the settling time because it showed less than half the error voltage ratio that the ATC circuit with conventional structure showed in analysis. We also designed a burst-mode ATC circuit for the 1.25Gbps EPON system using a commercial foundry. It produced the reference levels in very short time, 6㎱ in 40 ㏈ input dynamic range.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.350-357
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• 2010

In this paper, we present an auto-range fast bilateral filter (FBF) for high-dynamic-range (HDR) images, which increases computation speed by using adaptive standard deviations for range filter (RF) of FBF in iCAM06. Many images that cover the entire dynamic range of the scene with different exposure times are fused into one High Dynamic Range (HDR) image. The representative algorithm for HDR image rendering is iCAM06, which is based on the iCAM framework, such as the local white point adaptation, chromatic adaptation, and the image processing transform (IPT) uniform color space. FBF in iCAM06 uses constant standard deviation in RF. So, it causes unnecessary FBF computation in high stimulus range with broad and low distribution. To solve this problem, the low stimulus image and high stimulus image of CIE tri-stimulus values (XYZ) divided by the threshold are respectively processed by adaptive standard deviation based on its histogram distribution. Experiment results show that the proposed method reduces computation time than the previous FBF.

• Progress in Superconductivity
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• v.5 no.1
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• pp.26-30
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• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.939-948
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• 2005

In EBCOT, the context extraction process takes excessive calculation time and this paper proposed a method to reduce this calculation time. That is, if a coefficient is less than a pre-defined threshold value the coefficient and its descendents skip the context extraction process. There is a trade-off relationship between the calculation time and the image quality or the amount of output data such that as this threshold value increases, the calculation time and the amount of output data decreases, but the image degradation increases. Therefore, by deciding this threshold value according to the network environments or conditions, it is possible to establish a network-adaptive context extraction method. The experimental results showed that the range of the threshold values for acceptable image quality(better than 30dB) is from 0 to 4. The experimental results showed that in this range the Resulting reduction rate in calculation time was from $3\%\;to\;64\%$ in average, the reduction rate in output data was from $32\%$ to $73\%$ in average, which means that large reduction in calculation time and output data can be obtained with a cost of an acceptable image quality degradation. Therefore, the proposed method is expected to be used efficiently in the application area such as the real-time image/video data communication in wireless environments, etc.