• Title/Summary/Keyword: Layer Selection

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Isolation of S-627(A) and (B) as Candidates of Anticandiosis Agent (생리활성물질 S-627(A)와 S-627(B)의 분리)

  • Lee, Sang-Han;Lee, Dong-Sun;Seu, Young-Bae;Kim, Jong-Guk;Hong, Soon-Duck
    • Journal of Life Science
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    • v.7 no.3
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    • pp.186-191
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    • 1997
  • In order to select new anticandiosis agent-producing candidates, we used a modified selection method. Two active fractions designated as S-6279A) and (B) were isolated from the fermentation broth of Streptomycetes sp. S627 which was screened by methanol extraction, diaion HP-20 and silica gel column chromatography (chloroform-me-thanol, and benzene-ethyl acetate), and preparative thin layer chromatography.

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A Scheme of Channel Diversity Load Balancing Consideration for Path Selection in WMNs

  • Gao, Hui;Kwag, Young-wan;Lee, Hyung-ok;Nam, Ji-seung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.249-251
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    • 2014
  • This paper proposes a channel diversity based load-balancing cross-layer routing scheme for Wireless Mesh Networks (WMNs). The proposed scheme deals with channel diversity phase and load balancing phase in WMNs. Channel diversity factor $metric_{ch-d}$ and load balancing factor $f_{load}$ are defined and employed cooperatively as a combined path selection policy.

Time Trends in Estimates of Genetic Parameters in a Population of Layer Breeders (난용종계 집단에서의 선발에 의한 유전모수 변화 양상)

  • 최연호;오봉국
    • Korean Journal of Poultry Science
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    • v.17 no.4
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    • pp.255-268
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    • 1990
  • This study was carried out to investigate the time-trends of genetic parameters of the dosed flock population which selected for improving egg production. Data for two layer pure lines, Line-W (Single Comb White Leghorn) and Line-B (brown layer) which have been maintained at the Mani Breeding Farm were collected from 1980 to 1985 during 5 generations. The effective number of parents per generation ranged from 148 to 366 in Line-W and 85 to 355 in Line-B, and the cumulative expected inbreeding coefficients during 5 generations of selection were 15% and 1.6%. So inbreeding could not be considered a critical factor on estimating the genetic parameters, heritabilities and genetic correlations Heritabilities of EN 300 and EN 400, primary two selected traits were significantly decreased during 5 generations but the estimates of the other 03its not showed the consistent decreasing pattern significantly. No time trends of probable consequence were evident in the genetic correlation coefficients of the traits studied. The reason for that situation was attributed to the fact that selection was conducted for multiple objectives and the relative importance of selection for the studied traits were not consistent by generations.

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Movie Box-office Prediction using Deep Learning and Feature Selection : Focusing on Multivariate Time Series

  • Byun, Jun-Hyung;Kim, Ji-Ho;Choi, Young-Jin;Lee, Hong-Chul
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.6
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    • pp.35-47
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    • 2020
  • Box-office prediction is important to movie stakeholders. It is necessary to accurately predict box-office and select important variables. In this paper, we propose a multivariate time series classification and important variable selection method to improve accuracy of predicting the box-office. As a research method, we collected daily data from KOBIS and NAVER for South Korean movies, selected important variables using Random Forest and predicted multivariate time series using Deep Learning. Based on the Korean screen quota system, Deep Learning was used to compare the accuracy of box-office predictions on the 73rd day from movie release with the important variables and entire variables, and the results was tested whether they are statistically significant. As a Deep Learning model, Multi-Layer Perceptron, Fully Convolutional Neural Networks, and Residual Network were used. Among the Deep Learning models, the model using important variables and Residual Network had the highest prediction accuracy at 93%.

Restoration Model of Quercus mongolica Community in the Case of Korean National Capital Region (수도권지역의 신갈나무군집 복원모형)

  • 강현경;방광자
    • Journal of the Korean Institute of Landscape Architecture
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    • v.28 no.6
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    • pp.1-15
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    • 2001
  • The purpose of this study is to figure out the structural characteristics of urban plant community and suggest restoration model of Quercus mongolica in the case of Korean national Capital Region. The investigation areas were selected from urban area of Mt. Nam at Chung-Gu, suburban areas of Mt. Bong at Eunpyoung-GU, Mt. Sungju at Buchon City and non-urban areas of Mt. Suri at Kunpu City and Mt. Chonma t namyangju-City. After the main study field had been classified into the evaluation of the ecological characteristics and the modeling of the vegetation. We analyzed to evaluate the ecological characteristics of the forest structure -- successional stage, naturalness, multi-layer structure of the forest and species diversity, and the plant community structures. We have proposed vegetation restoration model based on the selection of proper plants, the number of individuals, diameter short area of breast height, the shortest distance between plants in non-urban area. As for successional stage, It was judged that the ecological succession may not be followed like the present stage of the surveyed areas in urban, suburban and non-ruban areas. As for the retention of naturalness and multi-layer structures of vegetation, In Quercus mongolica community, Robinia pseudo-acacia and Ailanthus altissima occurred in each layers at Mt. Nam, Mt. Bong and Mt. Sungju, and Eupatorium rugosum occurred in herbaceous layer at Mt. Nam. Consequently, the ecological restoration plan following the structure of the vegetation in Mt. Chonma seemed to be advisable in Q. mongolica community, there were less number of species and individuals in urban areas than those of non-urban areas. Planting of trees following the simulated native plant community of non-urban areas seemed to be required to promote the plants in urban areas. Considering the number of individuals up to three layers in each 400$m^2$ area, it was composed of twenty nine in canopy layer, forth nine in understory layer, 367 in shrub layer and 33.7% herbaceous ground cover in the Q.mongolica community. The suggested restoration model in this study is nan applicable model for the introduction in the cities, and this study shows that continuous experiments and field investigation on this model should be performed in the future.

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Selection of Scalable Video Coding Layer Considering the Required Peak Signal to Noise Ratio and Amount of Received Video Data in Wireless Networks (무선 네트워크에서 요구되는 평균 최대 신호 대 잡음비와 수신 비디오 데이터양을 고려하는 스케일러블 비디오 코딩 계층 선택)

  • Lee, Hyun-No;Kim, Dong-Hoi
    • Journal of Digital Contents Society
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    • v.17 no.2
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    • pp.89-96
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    • 2016
  • SVC(Scalable Video Coding), which is one form among video encoding technologies, makes video streaming with the various frame rate, resolution, and video quality by combining three different scalability dimensions: temporal, spatial, and video quality scalability. As the above SVC-encoded video streaming consists of one base layer and several enhancement layers, and a wireless AP(Access Point) chooses and sends a suitable layer according to the received power from the receiving terminals in the changeable wireless network environment, the receiving terminals supporting SVC are able to receive video streaming with the appropriate resolution and quality according to their received powers. In this paper, after the performance analysis for the received power, packet loss rate, PSNR(Required Peak Signal to Noise Ratio), video quality level and amount of received video data based on the number of SVC layers was performed, an efficient method for selecting the number of SVC layer satisfying the RSNR and minimizing the amount of received video data is proposed.

Comparison of Artificial Neural Network Model Capability for Runoff Estimation about Activation Functions (활성화 함수에 따른 유출량 산정 인공신경망 모형의 성능 비교)

  • Kim, Maga;Choi, Jin-Yong;Bang, Jehong;Yoon, Pureun;Kim, Kwihoon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.63 no.1
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    • pp.103-116
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    • 2021
  • Analysis of runoff is substantial for effective water management in the watershed. Runoff occurs by reaction of a watershed to the rainfall and has non-linearity and uncertainty due to the complex relation of weather and watershed factors. ANN (Artificial Neural Network), which learns from the data, is one of the machine learning technique known as a proper model to interpret non-linear data. The performance of ANN is affected by the ANN's structure, the number of hidden layer nodes, learning rate, and activation function. Especially, the activation function has a role to deliver the information entered and decides the way of making output. Therefore, It is important to apply appropriate activation functions according to the problem to solve. In this paper, ANN models were constructed to estimate runoff with different activation functions and each model was compared and evaluated. Sigmoid, Hyperbolic tangent, ReLU (Rectified Linear Unit), ELU (Exponential Linear Unit) functions were applied to the hidden layer, and Identity, ReLU, Softplus functions applied to the output layer. The statistical parameters including coefficient of determination, NSE (Nash and Sutcliffe Efficiency), NSEln (modified NSE), and PBIAS (Percent BIAS) were utilized to evaluate the ANN models. From the result, applications of Hyperbolic tangent function and ELU function to the hidden layer and Identity function to the output layer show competent performance rather than other functions which demonstrated the function selection in the ANN structure can affect the performance of ANN.

TWO-LAYER MUTI-PARAMETERIZED SCHWARZ ALTERNATING METHOD FOR TWO-DIMENSIONAL PROBLEMS

  • Kim, Sang-Bae
    • Journal of applied mathematics & informatics
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    • v.30 no.3_4
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    • pp.477-488
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    • 2012
  • The convergence rate of a numerical procedure based on Schwarz Alternating Method(SAM) for solving elliptic boundary value problems depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It has been observed that the mixed interface condition, controlled by a parameter, can optimize SAM's convergence rate. In [8], one introduced the two-layer multi-parameterized SAM and determined the optimal values of the multi-parameters to produce the best convergence rate for one-dimensional elliptic boundary value problems. In this paper, we present a method which utilizes the one-dimensional result to get the optimal convergence rate for the two-dimensional problem.

Merging of Two Artificial Neural Networks

  • Kim, Mun-Hyuk;Park, Jin-Young
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.258-261
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    • 2002
  • This paper addresses the problem of merging two feedforward neural networks into one network. Merging is accomplished at the level of hidden layer. A new network selects its hidden layer's units from the two networks to be merged We uses information theoretic criterion (quadratic mutual information) in the selection process. The hidden unit's output and the target patterns are considers as random variables and the mutual information between them is calculated. The mutual information between hidden units are also considered to prevent the statistically dependent units from being selected. Because mutual information is invariant under linear transformation of the variables, it shows the property of the robust estimation.

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Analysis of Sperm Chemoattractant in Follicular Fluid (난포액내 정자유인물질의 분석)

  • 박영식
    • Journal of Embryo Transfer
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    • v.14 no.1
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    • pp.47-57
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    • 1999
  • Among proteins separated from methanol extract of follicular fluid with superose column, the components inducing sperm swim-up separation through sucrose layer were analysed with superose column in Smart system and SDS-PAGE. And the results obtained were as follows; The fractions of retention volume (RV) 0.83ml and RV 1.36ml separated with superose column should stimulate sperm migration and movement. However, RV 0.83 fraction was consisted of complex materials containing RV 1.36 component. RV 1.36 fraction contained a BSA analogue of 67 kilodaltons (Kd) and showed identical peak pattern with BSA fraction V. In conclusion, the protein of 67 Kd in follicular fluid should stimulate sperm migration and movement.

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