• Asian Pacific Journal of Cancer Prevention
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• v.15 no.4
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• pp.1863-1869
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• 2014

The amplification of telomerase component (TERC) gene could play an important role in generation and treatment of haematological malignancies. This present study was aimed to investigate copy number amplification status of TERC gene in chronic myeloid leukaemia (CML) patients who were being treated with imatinib mesylate (IM). Genomic DNA was extracted from peripheral blood of CML-IM Resistant (n=63), CML-IM Respond (n=63) and healthy individuals (n=30). TERC gene copy number predicted (CNP) and copy number calculated (CNC) were determined based on $Taqman^{(R)}$ Copy Number Assay. Fluorescence in situ hybridization (FISH) analysis was performed to confirm the normal signal pattern in C4 (calibrator) for TERC gene. Nine of CML patients showed TERC gene amplification (CNP=3), others had 2 CNP. A total of 17 CML patients expressed CNC>2.31 and the rest had 2.31>CNC>1.5. TERC gene CNP value in healthy individuals was 2 and their CNC value showed in range 1.59-2.31. The average CNC TERC gene copy number was 2.07, 1.99 and 1.94 in CML-IM Resistant patients, CML-IM Respond and healthy groups, respectively. No significant difference of TERC gene amplification observed between CML-IM Resistant and CML-IM Respond patients. Low levels of TERC gene amplification might not have a huge impact in haematological disorders especially in terms of resistance towards IM treatment.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.50-59
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• 1997

In this paper, we implement an automatic speech segmentation and labeling system which marks phone boundaries automatically for constructing the Korean speech database. We specify and implement the system based on conventional speech segmentation and labeling techniques, and also develop the graphic user interface(GUI) on Hangul $Motif^{TM}$ environment for the users to examine the automatic alignment boundaries and to refine them easily. The developed system is applied to 16kHz sampled speech, and the labeling unit is composed of 46 phoneme-like units(PLUs) and silence. The system uses both of the phonetic and orthographic transcription as input methods of linguistic information. For pattern-matching method, hidden Markov models(HMM) is employed. Each phoneme model is trained using the manually segmented 445 phonetically balanced word (PBW) database. In order to evaluate the performance of the system, we test it using another database consisting of sentence-type speech. According to our experiment, 74.7% of phoneme boundaries are within 20ms of the true boundary and 92.8% are within 40ms.

• Journal of the Microelectronics and Packaging Society
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• v.23 no.4
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• pp.107-112
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• 2016

In this paper, the hydrophobic rough surfaces were prepared by employing a conventional nano-imprint lithography technique, and the effects of surface parameter, ratio of the top surface to the flat unit cell, on the impingement behaviors of liquid droplet were investigated to improve robustness of hydrophobic functionality. The critical height defined for the transition from rebound to fragmentation is measured by droplet impingement test in order to study dynamic behavior of an impinged droplet. It showed the critical height decreased with high surface parameter while it increased with low surface parameter. However, the critical height decreased again as surface parameter decreased further. Observed results suggest that the optimized surface pattern should be designed for the increased critical height.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.125-133
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So intuitive fuzzy c-means(IFCM) clustering algorithm is applied to improve KNN, which is the KNN/IFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of IFCM based on signal to noise ratio(SNR). Then, the k RPs are classified into different clusters through IFCM based on SNR. Experimental results indicate that the proposed KNN/IFCM hybrid algorithm generally outperforms KNN, KNN/FCM, KNN/PFCM algorithm when the locations error is less than 2m.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.109-115
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• 2011

As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So artificial neural network(ANN) clustering algorithm is applied to improve KNN, which is the KNN/ANN hybrid algorithm presented in this paper. For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of ANN based on SNR. Then, the k RPs are classified into different clusters through ANN based on SNR. Experimental results indicate that the proposed KNN/ANN hybrid algorithm generally outperforms KNN algorithm when the locations error is less than 2m.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.10
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• pp.83-98
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• 2007

The handover between different radio access networks, especially where their coverage overlaps, suffers various complications since the different access networks provide different service characteristics. One way to reduce service interruptions and QoS (i.e., bandwidth, throughput, delay) degradations during the inter-technology handover is to reserve the required resource in advance. The resource reservation algorithm should minimize the handover latency and maximize the resource utilization based on the accurate estimation on mobile's location, velocity, movement pattern and service requirements. In this paper, we propose a resource reservation algorithm based on the mobile terminal velocity and the cell selection probability, which maximizes resource utilization ana reduces network overhead. We compare the proposed algorithm with PMS(Predictive Mobility Support) and VCDS(Velocity and Call Duration Support scheme) based on 3-layer network model under various scenarios.

• Korean Journal of Plant Resources
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• v.10 no.2
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• pp.188-193
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• 1997

Panax ginseng C.A.Meyer,1 to 5 years old were electrophored and were stained for SOD activity. The result indicated a total of 13 distinct form of the enzyme and the pattern of achromatic bands were not different according to ages. Nine of the enzyme activities were eliminated with cyanide or peroxide treatment and were resistant to treatment of chloroform plus ethanol. It suggested that they may be cupro-zinc containing SOD, whereas four were cyanide or peroxide resistant and were eliminated with cholroform plus ethanol treatment. They may be manganese containing SOD. Ginseng roos. 1 to 5 years old were analyzed for their SOD measurement of SOD activities of all extracts, the significant difference of SOD activities were not shown according to ages. All ginseng extracts had the total SOD activities of all extracts, the significant difference of SOD activities were not shown according to ages. All ginseng extracts had the total SOD activities of about 700-800 unit/g of fresh weight. Therefore, the SOD activities from SOD-mimic compounds were higher than one from SOD. The ratio between the SOD activity from SOD-mimic compounds and one from true SOD was approximately 2:1 to 3:1.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Nuclear Engineering and Technology
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• v.20 no.1
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• pp.19-26
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• 1988

The low leakage leading pattern has features as the placement of some fresh fuel assemblies in the core interior to reduce the neutron fluence on the pressure vessel and to enhance the neutron economics. But as fresh fuel assemblies are loaded in the core interior, the local power tends to exceed safety limit due to the high reactivity of the fresh assemblies. Therefore, a large number of burnable poisons must be utilized in a low leakage scheme to suppress the high assembly power as well as the excess reactivity. In this study the effects of burnable poisons are treated as a perturbation on the power distribution, and the 'Power Sensitivity Coefficient' concept is adopted. An application study is performed for cycle 1 of the Korea Nuclear Unit-7 (KNU-7) to justify the usefulness of the reverse depletion method coupled with the above concept. To obtain the optimal burnable poision distribution at the given burnup step, the linear programming technique is adopted. The result shows maximum 4.5% error in the amount of burnable poisons between the calculated and the reference values. It is concluded that the design methodology which consists of the reverse depletion, the power sensitivity coefficient concept, and the linear programming technique can be used to find the optimal turnable poison distribution.

• Applied Chemistry for Engineering
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• v.31 no.4
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• pp.347-351
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• 2020

A material changes its physical and chemical properties through the interaction with radiation and also the neutrons, which is electronically neutral so that the penetration depth is relatively deeper than that of other radioactive way including alpha or beta ray. Therefore, the radiation damage by neutron irradiation has been intensively investigated for a long time with respect to the safety of nuclear power plants. The damage induced by neutron irradiation begins with the creation of point defects in atomic scale in the unit of picoseconds, and their progress pattern can be characterized by microstructural defects, such as dislocation loops and voids. Their morphological characteristics affect the properties of neutron-irradiated materials, therefore, it is very important to predict the microstructure at a given neutron irradiation condition. This paper briefly reviews the evolution of radiation damage induced by neutron irradiation and introduces a phase-field model that can be widely used in predicting the microstructure evolution of irradiated materials.