Effect of Homophily on Network Evolution

Kibae Kim,Jorn Altmann 한국경영과학회 2016 한국경영과학회 학술대회논문집 Vol.2016 No.10

Exploration of the anti-diabetic potential of hydro-ethanolic leaf extract of Koenigia polystachya L.: an edible wild plant from Northeastern India

Alokali Kiba,Dipankar Saha,Bhrigu Kumar Das 한국실험동물학회 2023 Laboratory Animal Research Vol.39 No.3

Background: Globally, medicinal plants are used to treat diseases like diabetes. The present study evaluates the possible antioxidant, acute oral toxicity, the in-vitro and in-vivo antidiabetic potential of the hydro-ethanolic leaf extract of Koenigia polystachya (HELeKP) against beta-cell damage in experimentally induced diabetes mellitus. The DPPH (2,2-diphenyl-1-picrylhydrazine), ABTS [2,2′-azino bis-(3-ethylbenzothiazoline-6-sulfonic acid)], H2O2 (Hydrogen peroxide), superoxide radical scavenging activity and NO (Nitric oxide) assay estimated the in-vitro antioxidant assay of HELeKP. The acute oral toxicity study was evaluated per the OECD (Organization for Economic Cooperation and Development) test guidelines 425. Diabetes was stimulated in rats with a single dose of Streptozotocin (STZ), and after confirmation of diabetes, HELeKP was given orally for 21 days. Blood/serum samples were gathered and examined for biochemical changes, while tissue samples were evaluated for histopathological alterations. Results: The IC50 value of the HELeKP for all the anti-oxidant assays confirms the free radical scavenging activity. The data on acute oral toxicity revealed that the HELeKP used in the study was comparatively very safe. The outcomes of the in-vivo study suggested that the extract significantly reduced (p < 0.001) the fasting glucose level in STZ-induced diabetic rats. Furthermore, the lipid profile level was significantly normalized (p < 0.01, p < 0.001) in diabetic rats. The histopathological observation of the pancreas in HELeKP-treated rats showed significant beta-cell restoration. Conclusions: Based on the outcomes of this study, the HELeKP-treated rats have significant free radical scavenging and anti-diabetic potential. Therefore, it can be recommended as a beneficial functional vegetable for consumption.

주파수 영역 수동소나 표적신호 분리 및 잡음 제거 알고리즘

이기배(Kibae Lee),김주호(Juho Kim),정명준(Myoung Jun Cheong),류영우(Young Woo Ryu),배진호(Jinho Bae),이종현(Chong Hyun Lee) 대한전자공학회 2018 전자공학회논문지 Vol.55 No.3

본 논문에서는 다중 표적환경에서 수동소나 표적신호 분리를 위한 주파수 영역 신호분리 및 잡음 제거 알고리즘을 제안한다. 수동소나는 주로 선박 및 항만의 안전을 위해 수중 이동체의 탐지 및 식별에 사용된다. 그러나 여러 수중 잡음 환경과 다중 표적환경에서 다수의 표적신호가 혼재하는 상황에 의해 개별 표적신호의 탐지 및 식별에 어려움을 가진다. 이러한 이유로 주파수 영역에서의 JADE(Joint Approximate Diagonalization of Eigen-matrices)와 심층 신경망(deep neural network) 기반의 SDAE(Stacked Denoising Auto-Encoder)를 이용한 표적신호 분리 및 잡음 제거 알고리즘을 제안한다. 모의실험 결과, 주파수 영역에서 JADE를 사용함이 시간 영역에서 적용함과 비교하여 우수한 분리 성능을 보였다. 또한 SDAE를 함께 수행함으로써 2.64-4.01dB의 신호 대 잡음비(SNR) 향상을 가졌으며, JADE 수행 과정에서 분리되지 않은 신호성분을 제거함으로써 신호분리 성능을 향상시켰다. In this paper, we propose frequency domain signal separation and noise reduction algorithm for separation of passive sonar target signals in multi-target environment. Passive sonar is mainly used for the detection and identification of underwater vehicles for the safety of ships and harbors. However, it is difficult to detect and identify individual target signals due to underwater noise environment and the mixed situation of multiple target signals in multiple target environment. For this reason, we propose a target signal separation and noise reduction algorithm using JADE (Joint Approximation Diagonalization of Eigen-matrices) in frequency domain and SDAE (Stacked Denoising Auto-Encoder) based on deep neural network. Simulation results show that the use of JADE in the frequency domain is superior to that applied in the time domain. In addition, the signal to noise ratio (SNR) improvement of 2.64-4.01dB was achieved by performing SDAE and signal separation performance was improved by eliminating non-separated signal components during JADE performance.

주행로봇제어를 위한 DWT와 SVM기반의 EEG신호 분류 알고리즘

이기배(Kibae Lee),이종현(Chong Hyun Lee),배진호(Jinho Bae),이재일(Jaeil Lee) 대한전자공학회 2015 전자공학회논문지 Vol.52 No.8

본 논문은 ‘좌’, ‘우’방향 제어를 위해 취득된 EEG(Electroencephalogram) 신호 기반 분류 알고리즘과 EEG 센서, Labview, DAQ, Matlab, 주행로봇으로 구성된 방향 제어 시스템을 제안한다. 제안된 알고리즘은 DWT(Discrete Wavelet Transform) 로 추출된 주파수대역 정보를 특징으로 이용하며, Fishers core 를 이용하여 변별력이 높은 주파수 대역의 특징을 선별한다. 또한, SVM (Support Vector Machine) 을 이용하여 분류 성능이 최고가 되는 특징벡터의 조합을 제안하고, 잘못된 판정에 의한 오동작을 방지하기 위한 MLD (Maximum Likelihood Decision) 기반의 판정보류 알고리즘도 제안한다. 제안된 알고리즘에 의해 선택된 4개의 특징벡터는 국제 표준 전극 배치법에 따른 P8 채널의 d2(16-32Hz), d5(2-4Hz) 주파수 대역의 전압의 절대 값 평균과 표준편차이다. SVM 분류기로 실험한 결과 98.75%의 정확도와 1.25%의 오류율 성능을 보였다. 또한, 오류 확률 70%를 판정 보류로 규정할 경우, 제안된 알고리즘은 인식률 95.63%의 정확도와 오류율 0%을 보였다. In this paper, we propose a classification algorithm based on the obtained EEG(Electroencephalogram) signal for the control of "left‘ and ’right‘ turnings of which a driving system composed of EEG sensor, Labview, DAQ, Matlab and driving robot. The proposed algorithm uses features extracted from frequency band information obtained by DWT (Discrete Wavelet Transform) and selects features of high discrimination by using Fisher score. We, also propose the number of feature vectors for the best classification performance by using SVM(Support Vector Machine) classifier and propose a decision pending algorithm based on MLD (Maximum Likelihood Decision) to prevent malfunction due to misclassification. The selected four feature vectors for the proposed algorithm are the mean of absolute value of voltage and the standard deviation of d5(2-4Hz) and d2(16-32Hz) frequency bands of P8 channel according to the international standard electrode placement method. By using the SVM classifier, we obtained 98.75% accuracy and 1.25% error rate. Also, when we specify error probability of 70% for decision pending, we obtained 95.63% accuracy and 0% error rate by using the proposed decision pending algorithm.

Seabed Sediment Classification Algorithm using Continuous Wavelet Transform

Lee, Kibae,Bae, Jinho,Lee, Chong Hyun,Kim, Juho,Lee, Jaeil,Cho, Jung Hong Korean Society of Ocean Engineers 2016 Journal of advanced research in ocean engineering Vol.2 No.4

In this paper, we propose novel seabed sediment classification algorithm using feature obtained by continuous wavelet transform (CWT). Contrast to previous researches using direct reflection coefficient of seabed which is function of frequency and is highly influenced by sediment types, we develop an algorithm using both direct reflection signal and backscattering signal. In order to obtain feature vector, we employ CWT of the signal and obtain histograms extracted from local binary patterns of the scalogram. The proposed algorithm also adopts principal component analysis (PCA) to reduce dimension of the feature vector so that it requires low computational cost to classify seabed sediment. For training and classification, we adopts K-means clustering algorithm which can be done with low computational cost and does not require prior information of the sediment. To verify the proposed algorithm, we obtain field data measured at near Jeju island and show that the proposed classification algorithm has reliable discrimination performance by comparing the classification results with actual physical properties of the sediments.

SDAE를 이용한 수동소나 표적신호 분리 알고리즘

이기배(Kibae Lee),이지현(Jeehyun Lee),배진호(Jinho Bae),정명준(Myoung Jun Cheong),이종현(Chong Hyun Lee) 대한전자공학회 2017 대한전자공학회 학술대회 Vol.2017 No.6

In this paper, we propose passive sonar target signal separation algorithm using SDAE(Stacked Denoising Auto-Encoder). By using the proposed algorithm based on SDAE along with Fast ICA(Independent Component Analysis) algorithm, we obtained 4~5dB improved SNR of target signal. Also, we proposed separation algorithm using SDAE and filter bank designed by harmonic relation, which showed superior performance to existing BSS algorithms.

주파수에 따른 감쇠계수 변화량을 이용한 해저 퇴적물 특징 추출 알고리즘

이기배(Kibae Lee),김주호(Juho Kim),이종현(Chong Hyun Lee),배진호(Jinho Bae),이재일(Jaeil Lee),조정홍(Jung Hong Cho) 대한전자공학회 2017 전자공학회논문지 Vol.54 No.1

본 논문에서는 해저 퇴적물 분류를 위한 특징 추출 기법을 제안하고 검증한다. 기존 연구에서는 주파수의 영향이 없는 반사계수를 이용하여 퇴적물을 분류해 왔다. 그러나 해저 퇴적물의 음향 감쇠계수는 주파수의 함수이며 퇴적 성분에 따라 서로 다른 특성을 나타낸다. 따라서 주파수에 따른 감쇠계수 변화량을 이용하여 특징벡터를 생성하였다. 감쇠계수 변화량은 Chirp 신호에 의해 생성된 두 번째 층 반사신호를 이용하여 추정한다. Chirp 신호의 다중대역 특징이 다차원 벡터를 형성하기 때문에 기존의 방법에 비해 우수한 특성을 갖는다. 반사계수에 의한 분류 성능과 비교하기 위해 선형 판별 분석법 (LDA, Linear Discriminant Analysis)를 이용하여 차원을 축소하였다. Biot 모델을 이용하여 모의실험 환경을 구축하고 Fisher score와 MLD (Maximum Likelihood Decision)를 기반의 분류 정확도를 이용해 제안된 특징을 평가하였다. 그 결과, 제안된 특징은 반사계수에 비해 높은 변별력을 보이며, 측정 및 깊이 추정오차에도 강인한 특성을 보였다. In this paper, we propose novel feature extraction algorithm for classification of seabed sediment. In previous researches, acoustic reflection coefficient has been used to classify seabed sediments, which is constant in terms of frequency. However, attenuation of seabed sediment is a function of frequency and is highly influenced by sediment types in general. Hence, we developed a feature vector by using attenuation variation with respect to frequency. The attenuation variation is obtained by using reflected signal from the second sediment layer, which is generated by broadband chirp. The proposed feature vector has advantage in number of dimensions to classify the seabed sediment over the classical scalar feature (reflection coefficient). To compare the proposed feature with the classical scalar feature, dimension of proposed feature vector is reduced by using linear discriminant analysis (LDA). Synthesised acoustic amplitudes reflected by seabed sediments are generated by using Biot model and the performance of proposed feature is evaluated by using Fisher scoring and classification accuracy computed by maximum likelihood decision (MLD). As a result, the proposed feature shows higher discrimination performance and more robustness against measurement errors than that of classical feature.

천연기능성 식품소재의 산업화

이기배(Kibae Lee) 한국식품영양과학회 2015 식품산업과 영양 Vol.20 No.1

파라메트릭 배열을 이용한 은폐 물체 탐지 시스템

이기배(Kibae Lee),이재일(Jaeil Lee),배진호(Jinho Bae),이종현(Chong Hyun Lee),조정홍(Jung Hong Cho) 대한전자공학회 2017 전자공학회논문지 Vol.54 No.3

본 논문에서는 은폐 물체 탐지를 위해 인체에 무해한 음향신호 중 파라메트릭 배열을 이용한 음향 탐지 시스템을 제안한다. 제안된 탐지 시스템은 파라메트릭 배열 현상으로부터 생성되는 고 지향성 Chirp 신호를 송신신호로 사용하고, Dechirp 처리과정을 통해 수신신호의 신호 대 잡음비를 개선하여 거리 분해능을 향상시키는 기법을 사용한다. 제안된 파라메트릭 배열 시스템의 송신센서는 8 × 2 배열로 구축하였으며, 센서 배열의 빔 폭은 수평방향 약 7°와 수직방향 약 26°를 형성한다. 제안된 시스템을 검증하기 위해 물체 탐지 및 가시화를 위한 2축 구동 제어 선형 스테이지를 구축하였으며, 이를 이용하여 은폐된 물체에 대한 A-scan, B-scan 및 C-scan 실험을 진행하였다. 실험 결과, 천에 은폐된 동판과 파이프를 탐지하고 형상을 확인하였으며, 가시화된 형상에서 동판은 0.015 ㎡, 파이프는 0.046㎡ 의 오차를 보여주었다. In this paper, we propose hidden object detection system using parametric array based on acoustic signal that is harmless to human body. A transmit signal of the proposed detection system uses a high directive chirp signal generated from parametric array phenomenon, which uses technique to improve a signal to noise (SNR) of a received signal and a distance resolution trough the dechirp processing. The transmit sensor array is constructed as 8 × 2 and has a horizontal beam width of 7° and vertical beam width of 26°. To verify the detection and visualization of the proposed system, a 2-axis driving control system based on linear stage was constructed, and A-scan, B-scan, and C-scan experiments was addressed for hidden object. From experimental results, we detected and visualized the hidden bronze plate and pipe by cloth and the visualized shapes was confirmed. Especially, the obtained errors was 0.015 ㎡ for bronze plate, and 0.046㎡ for pipe.

SAR 기반 디지털 보조 자동 오프셋 저감 루프를 이용한 저잡음 다중경로 증폭기

남기배(Kibae Nam),유무경(Mookyoung Yoo),강상균(Sanggyun Kang),진병관(Byeongkwan Jin),손혁태(Hyeoktae Son),김경환(Kyounghwan Kim),위지향(Jihyang Wi),안승민(Seungmin Ahn),고형호(Hyoungho Ko) 대한전자공학회 2023 대한전자공학회 학술대회 Vol.2023 No.6