• Korean Journal of Optics and Photonics
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• v.13 no.4
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• pp.295-300
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• 2002

We developed an optical transmitter and receiver for an electrical time division multiplexed (ETDM) 20 Gb/s optical transmission system, and experimentally investigated their characteristics. Especially, the clock extraction circuit, which is a key component in realizing broadband optical transmission receivers, was realized by using an NRZ-to-PRZ converter implemented with a half-period delay line and an EX-OR, a high-Q bandpass filter using a cylindrical dielectric resonator, and a microstrip coupled-line bandpass filter. Finally, the bit-error-rate of demultiplexed 10 Gb/s electrical signal after back to-back transmission was measured, and a high receiver sensitivity [-26.2 dBm for NRZ ($2^{7}-1$) pseudorandom binary sequence (PRBS)] was obtained

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2003.10a
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• pp.59-59
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• 2003

ADAM은 metalloprotease/disintegrin domain을 가진 transmembrane glycoprotein으로서 지금까지 30종류 이상의 ADAM 및 10종류 이상의 ADAM-TS 단백질이 알려져 있다. 이들의 기능은 포유동물의 수정 시 sperm-egg binding과 fusion, myoblast fusion, integrin과의 결합 등에 직접 관여하거나, TNF-alpha 등의 생체신호전달물질이 세포로부터 분비될 때에 이들의 구조를 변화시켜 활성화시키는 효소로서의 작용, 그리고 dendritic cell differentiation 등에 관여하는 것으로 알려져 있다. 본 연구에서는 난소가 제거된 생쥐를 이용하여 자궁조직의 ADAM-8, -9, -10, -12, -15, -17 그리고 -TS1의 gene의 발현이 $17 \beta $-estradiol에 의하여 조절되는 지를 알아보았다. 생후 6 - 8주 된 암컷 생쥐의 난소를 제거하고, 2 주 후에 $17 \beta $-estradiol ($E_2$), progesterone ($P_4$) 혹은 이 둘 혼합액 ($E_2 + P_4$)을 sesame oil에 녹여 근육주사하였다. 2, 6, 12 시간 후 각각 자궁 조직을 얻고 유전자의 발현 양상을 알아보기 위하여 시료로부터 total RNA을 추출하여 역전사 중합효소반응 (RT-PCR)을 실시하였다. Densitometry를 이용, rpL7에 대한 ADAMS의 mRNA 발현 양을 상대적으로 분석하였다. 그 결과 ADAM-8과 -15는 6시간째에서, ADAM-10과 -TS1은 2시간째에서 sesame oil을 주사하거나 $P_4$만을 주사한 군보다 E$_2$를 주사한 군에서 mRNA의 양이 현저하게 증가하였고 ADAM-12는 2시간째에서 ADAM-17은 12시간째에서 sesame oil을 주사하거나 $P_$만을 주사한 군보다 E$_2$를 주사한 군에서 mRNA의 양이 현저하게 증가하였다. 이러한 결과로 미루어 ADAM-8, -10, -15 그리고 TS1은 progesterone에 의하여, ADAM-12와 17은 $17 \beta $-estradiol에 의하여 유전자의 발현이 upregulation 되는 것으로 생각되어진다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.217-222
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• 2015

Clustering is one of important data mining techniques known as exploratory data analysis and is being applied in various engineering and scientific fields such as pattern recognition, remote sensing, and so on. The method organizes data by abstracting underlying structure either as a grouping of individuals or as a hierarchy of groups. Weather radar observes atmospheric objects by utilizing reflected signals and stores observed data in corresponding coordinate. To analyze the radar data, it is needed to be separately organized precipitation and non-precipitation echo based on similarities. Thus, this paper studies to apply clustering method to radar data. In addition, in order to solve the problem when precipitation echo locates close to non-precipitation echo, fuzzy logic based clustering method which can consider both distance and other properties such as reflectivity and Doppler velocity is suggested in this paper. By using actual cases, the suggested clustering method derives better results than previous method in near-located precipitation and non-precipitation echo case.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.62-68
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• 2016

The fingerprint, which is one of the methods of indoor localization using WiFi, has been frequently studied because of its ability to be implemented via wireless access points. This method has low positioning resolution and high computational complexity compared to other methods, caused by its dependence of reference points in the radio map. In order to compensate for these problems, this paper presents a radio map designed algorithm based on the log-distance path loss model fusing a WiFi and BLE fingerprint. The proposed algorithm designs a radio map with variable values using the log-distance path loss model and reduces distance errors using a median filter. The experimental results of the proposed algorithm, compared with existing fingerprinting methods, show that the accuracy of positioning improved by from 2.747 m to 2.112 m, and the computational complexity reduced by a minimum of 33% according to the access points.

• Analytical Science and Technology
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• v.9 no.3
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• pp.253-261
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• 1996

Analytical method for the determination of trace germanium in inorganic matrices by differential pulse polarography(DPP) was studied. The reduction peak of germanium(IV) in perchloric acid solution containing 1, 2, 3-trihydroxy benzene appeared at -0.45V(vs. Ag/AgCl) and the peak current for germanium complex varied linearly with concentration variation. Factors affecting sensitivity and precision for germanium quantification were studied and detection limit under the investigated parameters was 1ng/ml. Inorganic samples were decomposed by fusion with potassium pyrosulfate. Serious interferences of Se(IV), Pb(II), As(III) for the determination of germanium were discussed. Interferences of these elements could be avoided by extraction of germanium from decomposed matrices by $CCl_4$ in 10M HCl solution. The germanium contents of inorganic samples(Pb bf. dust, Cu bf. dust, gneiss, Cu anode slime) were determined by the above method.

• Analytical Science and Technology
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• v.25 no.6
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• pp.467-475
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• 2012

A gas chromatography-mass spectrometric (GC-MS) method was developed for determining 17 hazard compounds containing phenols, polycyclic aromatic hydrocarbons and pesticides in surface water. A 1.0 L surface water sample was placed in a separatory funnel and saturated with NaCl, and the solution was extracted with 40 mL of methylene chloride. Under the established condition, the lowest quantification limit was 1.0-10 ng/L and the relative standard deviations were less than 22%. The method was used to analyze 70 surface water samples collected from 35 regions in Gum-River. The samples revealed the compounds concentrations in the range of 1.1-26,604 ng/L. Maximum concentrations of compounds detected were not exceeded guidelines established in other countries. The developed method may be valuable for monitoring hazards in water.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.2-7
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• 2004

In this paper, we proposed the content-based music information retrieval technique using some MPEG-7 low-level descriptors. Especially, pitch information and timbral features can be applied in music genre classification, music retrieval, or QBH(Query By Humming) because these can be modeling the stochasticpattern or timbral information of music signal. In this work, we restricted the music domain as O.S.T of movie or soap opera to apply broadcasting system. That is, the user can retrievalthe information of the unknown music using only an audio clip with a few seconds extracted from video content when background music sound greeted user's ear. We proposed the audio feature set organized by MPEG-7 descriptors and distance function by vector distance or ratio computation. Thus, we observed that the feature set organized by pitch information is superior to timbral spectral feature set and IFCR(Intra-Feature Component Ratio) is better than ED(Euclidean Distance) as a vector distance function. To evaluate music recognition, k-NN is used as a classifier

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.693-701
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• 2017

In this paper, we propose a new method for music genre classification using spikegram and deep neural network. The human auditory system encodes the input sound in the time and frequency domain in order to maximize the amount of sound information delivered to the brain using minimum energy and resource. Spikegram is a method of analyzing waveform based on the encoding function of auditory system. In the proposed method, we analyze the signal using spikegram and extract a feature vector composed of key information for the genre classification, which is to be used as the input to the neural network. We measure the performance of music genre classification using the GTZAN dataset consisting of 10 music genres, and confirm that the proposed method provides good performance using a low-dimensional feature vector, compared to the current state-of-the-art methods.

• The Korean Journal of Food And Nutrition
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• v.30 no.2
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• pp.371-377
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• 2017

Muscle atrophy is characterized by a decrease in the mass of the muscle. With an increase in life expectancy and chronic illnesses, the incidence of muscle atrophy is increasing and the quality of life of patients is decreasing. Thus, reducing muscle atrophy is of high clinical and socio-economic importance. Mistletoe is a semi-parasitic plant that has been used as a traditional medicine in many countries to treat various human illnesses. It has been reported that Korean mistletoe extract (KME) has diverse biological functions including anti-tumor, anti-oxidant, anti-diabetic, anti-obesity properties, and extension of lifespan. Especially, we have recently reported that KME improves exercise endurance in mice, indicating its beneficial roles in enhancing the capacity of skeletal muscle. In this study, we investigated whether KME could activate the signaling pathway related to protein synthesis in a mouse model of muscle atrophy. Interestingly, KME efficiently activated the Akt/mTOR pathway, and Akt and mTOR are important signaling hub molecules for the acceleration of protein synthesis in muscle cells. In addition, KME also increased the activity of S6 kinase which is involved in the regulation of muscle cell size. Moreover, the ERK activity, required for transcription of ribosomal RNA for protein synthesis, was also enhanced in KME-treated mouse muscle. These data support the idea that KME increases muscle mass via increased protein synthesis. Our findings also suggest that Korean mistletoe might be a promising candidate for the development of functional foods that are beneficial for preventing muscle atrophy.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.511-526
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• 2020

Single-cell RNA-sequencing (scRNA-seq) data consists of each cell's RNA expression extracted from large populations of cells. One main purpose of using scRNA-seq data is to identify inter-cellular heterogeneity. However, scRNA-seq data pose statistical challenges when applying traditional clustering methods because they have many missing values and high level of noise due to technical and sampling issues. In this paper, motivated by analyzing scRNA-seq data, we propose a novel spectral-based clustering method by imposing different weights on genes when computing a similarity between cells. Assigning weights on genes and clustering cells are performed simultaneously in the proposed clustering framework. We solve the proposed non-convex optimization using an iterative algorithm. Both real data application and simulation study suggest that the proposed clustering method better identifies underlying clusters compared with existing clustering methods.