• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.426-429
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• 2017

In this study, we investigated the effect of BN (boron nitride) on the thermal and the electrical conductivity of composites. In case of epoxy/BN composites, the thermal conductivity was increased as the BN contents were increased. Epoxy/AgNP (Ag nanoparticle) nanocomposites exhibited a slight change of thermal conductivity and showed a electrical percolation threshold at 20 vol% of Ag nanoparticles. At the fixed Ag nanoparticle content below the electrical percolation threshold, increasing the amount of BN enhanced the electrical conductivity as well as thermal conductivity for the epoxy/AgNP/BN composites.

• Journal of the Optical Society of Korea
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• v.14 no.4
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• pp.388-394
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• 2010

In this paper the object recognition performance of a photon counting integral imaging system is quantitatively compared with that of a conventional gray scale imaging system. For 3D imaging of objects with a small number of photons, the elemental image set of a 3D scene is obtained using the integral imaging set up. We assume that the elemental image detection follows a Poisson distribution. Computational geometrical ray back propagation algorithm and parametric maximum likelihood estimator are applied to the photon counting elemental image set in order to reconstruct the original 3D scene. To evaluate the photon counting object recognition performance, the normalized correlation peaks between the reconstructed 3D scenes are calculated for the varied and fixed total number of photons in the reconstructed sectional image changing the total number of image channels in the integral imaging system. It is quantitatively illustrated that the recognition performance of the photon counting integral imaging system can be similar to that of a conventional gray scale imaging system as the number of image viewing channels in the photon counting integral imaging (PCII) system is increased up to the threshold point. Also, we present experiments to find the threshold point on the total number of image channels in the PCII system which can guarantee a comparable recognition performance with a gray scale imaging system. To the best of our knowledge, this is the first report on comparisons of object recognition performance with 3D photon counting & gray scale images.

• Journal of Biomedical Engineering Research
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• v.23 no.6
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• pp.477-484
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• 2002

A pacemaker autosense algorithm with dual thresholds. one for noise or tachyarrhythmia detection (noise threshold, NT) and the other for intrinsic beat detection (sensing threshold. ST), was developed to improve the sensing performance in single pass VDD electrograms. unipolar electrograms, or atrial fibrillation detection. When a deflection in an electrogram exceeds the NT (defined as 50% of 57), the autosense algorithm with dual thresholds checks if the deflection also exceeds the ST. If it does, the autosense algorithm calculates the signal to noise ratio (SNR) of the deflection to the highest deflection detected by NT but lower than ST during the last cardiac cycle. If the SNR 2, the autosense algorithm declares an intrinsic beat detection and calculates the next ST based on the three most recent intrinsic peaks. If the SNR $\geq$2, the autosense algorithm checks the number of deflections detected by NT during the last cardiac cycle in order to determine if it is a noise detection or tachyarrhythmia detection. Usually the autosense algorithm tries to set the 57 at 37.5% of the average of the three intrinsic beats, although it changes the percentage according to event classifications. The autosense algorithm was tested through computer simulation of atrial electrograms from 5 patients obtained during EP study, to simulate a worst sensing situation. The result showed that the ST levels for autosense algorithm tracked the electrogram amplitudes properly, providing more noise immunity whenever necessary. Also, the autosense algorithm with dual thresholds achieved sensing performance as good as the conventional fixed sensitivity method that was optimized retrospectively.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.283-283
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• 2010

The liquid metal ion sources(LMIS) in FIB system have many advantages of high current density, high brightness and low ion energy spread. Most FIB systems use LMIS because the ion beam spot size of LMIS is smaller than other ion sources. LMIS is basically emitted by an extractor but the new electrode called the suppressor is able to control the emission current. We investigated characteristics LMIS with a suppressor, the function of the suppressor in LMIS, the change of the electric field by the suppressor and the advantages of using the suppressor. The characteristics of the threshold voltage and current-voltage (I-V) were observed under the varying extracting voltage with floated suppressor voltage, and under the varying suppressor voltages with fixed extractor voltage. We also simulated LMIS with the suppressor through CST(Computer Simulation Technology). The emission current increases as the suppressor voltage decreases because the suppressor voltage which restrains the electric field goes down, The threshold voltage increases as the suppressor voltage increases. We can explain characteristics and functions of LMIS with a suppressor using the electric field.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.66.2-66.2
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• 2013

In this study, we present a pore-selection technique to estimate the size of pore. The estimation of the size of pore is important to examine the temporal evolution of size itself and corresponding intensity. The size of pore is typically estimated by applying the intensity threshold technique to the fixed box which contains the entire pore. The typical method has disadvantages in the following circumstances; there are small features near the pore or the image has low spatial resolution. In the former, it is difficult to define a box containing the pore only, excluding the small features near the pore. In the latter, the background and threshold intensity are insignificant due to the insufficient number of pixel in the box. To avoid these difficulties, we use a pore-selection technique which is simply based on the measurement of distances from the pore center. In addition, we will discuss the advantage of the technique for the imaging spectrograph data like the NST FISS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.532-540
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• 2005

In this paper, a sequential detection scheme is proposed as a combination of a novel weak-signal and a locally optimum(LO) detection schemes. In Part 1, we propose a novel sequential detection scheme for weak signals and show some interesting threshold properties and examples. In Part 2, the performance of the proposed sequential detection scheme is compared with that of the fixed sample size(FSS) test, sequential probability ratio test (SPRT), and truncated sequential probability ratio test(TSPRT).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.53-58
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• 1998

Traffic nonuniformity degrades the performance of DCMA cellular systems. This paper presents a new algorithm called the Soft Handoff with Dynamic Thresholds (SHDT) which reduces the performance degeradation due traffic nonuniformity on CDMA systems. Unlike the conventional fixed handoff thresholds, algorithm allows the handoff thresholds (T_ADD and T_DROP) to vary dynamically according to the traffic density of each cell. This algerian has been implemented by means of computer simulation and the results show that SHDT improves the overall CDMA system performance in terms of outage probability. The SHDT algorithm can easily be applied to CDMA cellular systems without my modification.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.860-865
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• 2021

A data-based model, such as an AAKR model is widely used for monitoring the drifts of sensors in nuclear power plants. However, since a training dataset and a test dataset for a data-based model cannot be constructed with the data from all the possible states, the model uncertainty cannot be good enough to represent the uncertainty of estimations. In fact, the errors of estimation grow much bigger if the incoming data come from inexperienced states. To overcome this limitation of the model uncertainty, a new measure of uncertainty for a data-based model is developed and the predicted uncertainty is introduced. The predicted uncertainty is defined in every estimation according to the incoming data. In this paper, the AAKR model is used as a data-based model. The predicted uncertainty is similar in magnitude to the model uncertainty when the estimation is made for the incoming data from the experienced states but it goes bigger otherwise. The characteristics of the predicted model uncertainty are studied and the usefulness is demonstrated with the pressure signals measured in the flow-loop system. It is expected that the predicted uncertainty can quite reduce the false alarm by using the variable threshold instead of the fixed threshold.

• The Korean Journal of Pain
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• v.35 no.1
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• pp.59-65
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• 2022

Background: There is still unmet need in treating neuropathic pain and increasing awareness regarding the use of drug combinations to increase the effectiveness of treatment and reduce adverse effects in patients with neuropathic pain. Methods: This study was performed to determine the individual and combined effects of pregabalin, tianeptine, and clopidogrel in a rat model of neuropathic pain. The model was created by ligation of the L5-L6 spinal nerve in male Sprague-Dawley rats; mechanical allodynia was confirmed using von Frey filaments. Drugs were administered to the intrathecal space and mechanical allodynia was assessed; drug interactions were estimated by isobolographic or fixed-dose analyses. Results: Intrathecal pregabalin and tianeptine increased the mechanical withdrawal threshold in a dose-dependent manner, but intrathecal clopidogrel had little effect on the mechanical withdrawal threshold. An additive effect was noted between pregabalin and tianeptine, but not between pregabalin and clopidogrel. Conclusions: These findings suggest that intrathecal coadministration of pregabalin and tianeptine effectively attenuated mechanical allodynia in the rat model of neuropathic pain. Thus, pregabalin plus tianeptine may be a valid option to enhance the efficacy of neuropathic pain treatment.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.7
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• pp.258-266
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• 2013

We propose adaptive detection algorithm to reduce a false alarm by considering the characteristics of the random noise on the detection system based on a seismic sensor. The proposed algorithm consists of the first step detection using kernel function and the second step detection using detection classes. Kernel function of the first step detection is obtained from the threshold of the Neyman-Pearon decision criterion using the probability density functions varied along the noise from the measured signal. The second step detector consists of 4 step detection class by calculating the occupancy time of the footstep using the first detected samples. In order to verify performance of the proposed algorithm, the detection of the footsteps using measured signal of targets (walking and running) are performed experimentally. The detection results are compared with a fixed threshold detector. The first step detection result has the high detection performance of 95% up to 10m area. Also, the false alarm probability is decreased from 40% to 20% when it is compared with the fixed threshold detector. By applying the detection class(second step detector), it is greatly reduced to less than 4%.