• 제목/요약/키워드: the Combination Data

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다중 인식기의 다단계 결합을 통한 무제약 필기숫자 인식 (Unconstrained Handwritten Numeral Recognition using Multistage Combination of Multiple Recognizers)

  • 이관용;백종현;변혜란;이일병
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제26권1호
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    • pp.93-93
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    • 1999
  • Researches on digit recognition have been conducted actively for a long time because the classes to recognize are much fewer than other character sets and because it is very likely thatthe digit recognition can be applied to many problems in real world, The recent studies on designingrecognition system with high performance are in progress with two different aspects. One is toconstruct a recognizer using several features at the same time, and the other is to use severalrecognizers. In this paper, we propose a multistage combination method to recognize the unconstrainedhandwritten numerals. The method is a two-stage combination method which uses multiplecombination methods at the same time unlike the existing methods with only one combination method.The recognizers are first combined by several combination methods of different classes simultaneously,and then the results of them are combined by another combination method to generate a final result.Five recognizers and eight combination methods are used in the proposed system. The experimentalresults showed that the recognition rates on CENPARMI and CEDAR data were 97.75% and 98.6%,respectively and the recognition performance could be improved as the process passed through stages,We could get the best performance by combining the combination methods of different classes, whichmeans there are a complementary relation among them, The proposed method can be considered asan extended version of the existing combination methods.

The Optimal Combination of Neural Networks for Next Day Electric Peak Load Forecasting

  • Konishi, Hiroyasu;Izumida, Masanori;Murakami, Kenji
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -2
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    • pp.1037-1040
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    • 2000
  • We introduce the forecasting method for a next day electric peak load that uses the optimal combination of two types of neural networks. First network uses learning data that are past 10days of the target day. We name the neural network Short Term Neural Network (STNN). Second network uses those of last year. We name the neural network Long Term Neural Network (LTNN). Then we get the forecasting results that are the linear combination of the forecasting results by STNN and the forecasting results by LTNN. We name the method Combination Forecasting Method (CFM). Then we discuss the optimal combination of STNN and LTNN. Using CFM of the optimal combination of STNN and LTNN, we can reduce the forecasting error.

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Evaluation of the Effects of a Combination of Silicate Minerals in Duck Diets on Growth Performance and Litter Quality

  • Chung, Tae-Ho
    • 한국환경과학회지
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    • 제27권10호
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    • pp.933-936
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    • 2018
  • An experiment was conducted to evaluate the efficacy of a mixture of bentonite and illite as feed additives on the growth performance and litter quality of 90 Pekin ducks. The ducks were individually weighed and randomly divided into two treatments (control and 1% combination of silicate minerals), with three replicate pens per treatment, and 15 ducks per pen. Growth performance was not significantly affected (p>0.05) by the combination of bentonite and illite, but a trend of increased growth performance was observed in the control groups. Total nitrogen content and pH in the litter decreased following supplementation with the combination of bentonite and illite (p<0.05) when compared with the control group. This data indicates that the dietary supplementation with the combination of bentonite and illite (1% level) has no positive effect on the growth performance and litter quality of Pekin ducks.

Soft Combination Schemes for Cooperative Spectrum Sensing in Cognitive Radio Networks

  • Shen, Bin;Kwak, Kyung-Sup
    • ETRI Journal
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    • 제31권3호
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    • pp.263-270
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    • 2009
  • This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.

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캐주얼 셔츠의 체크패턴 변인에 따른 이미지 평가 -톤 인 톤 배색을 중심으로- (The Image Evaluation according to Checked Pattern Variable of Casual Shirts -Focus on Tone-in-Tone Coloration-)

  • 최수경
    • 한국의류학회지
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    • 제35권8호
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    • pp.867-876
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    • 2011
  • This study investigates the image of casual shirts according to color combination, tone, and interval of checked pattern in tone-in-tone coloration. The experimental materials developed for this study were a set of stimulus and response scales. The stimuli were 24 color pictures, in which color combination (RY: Red+Yellow, BP: Blue+Purple), tone (light, dull, dark), and interval (0.5cm, 1.5cm, 3.5cm, and 5.5cm) were manipulated. The 7-point scale was used for evaluation of image. Data were obtained from 240 female college students living in Seoul, Gwangju, Jinju, and Changwon in April 2010. For data analysis, ANOVA and Duncan-test were used by using SPSS program. The results of this study are as follows. Image according to color combination, tone, and interval of checked pattern consisted of five dimensions of attractiveness, youth- activity, appeal, modesty, and freshness. The cover combination showed an independent effect on freshness. Tone showed an independent effect on attractiveness, youth-activity, appeal, and modesty. Interval showed an independent effect on appeal, modesty, and freshness. Interaction effects of color combination and tone on youth-activity and appeal were found. In addition, interaction effects of tone and interval on attractiveness, youth-activity, and freshness were also found.

Metformin Synergistically Potentiates the Antitumor Effects of Imatinib in Colorectal Cancer Cells

  • Lee, Jaeryun;Park, Deokbae;Lee, Youngki
    • 한국발생생물학회지:발생과생식
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    • 제21권2호
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    • pp.139-150
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    • 2017
  • Metformin is the most commonly prescribed anti-diabetic drug with relatively minor side effect. Substantial evidence has suggested that metformin is associated with decreased cancer risk and anticancer activity against diverse cancer cells. The tyrosine kinase inhibitor imatinib has shown powerful activity for treatment of chronic myeloid leukemia and also induces growth arrest and apoptosis in colorectal cancer cells. In this study, we tested the combination of imatinib and metformin against HCT15 colorectal cancer cells for effects on cell viability, cell cycle and autophagy. Our data show that metformin synergistically enhances the imatinib cytotoxicity in HCT15 cells as indicated by combination and drug reduction indices. We also demonstrate that the combination causes synergistic down-regulation of pERK, cell cycle arrest in S and $G_2/M$ phases via reduction of cyclin B1 level. Moreover, the combination resulted in autophagy induction as revealed by increased acidic vesicular organelles and cleaved form of LC3-II. Inhibition of autophagic process by chloroquine led to decreased cell viability, suggesting that induction of autophagy seems to play a cell protective role that may act against anticancer effects. In conclusion, our present data suggest that metformin in combination with imatinib might be a promising therapeutic option in colorectal cancer.

냉간 조합압축과 상압소결에 의한 세라믹 분말의 정밀정형과 유한요소해석 (Near-Net-Shape Forming and Finite Element Analysis for Ceramic Powder Under Cold Combination Pressing and Pressureless Sintering)

  • 김홍기;이형만;김기태
    • 대한기계학회논문집A
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    • 제24권2호
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    • pp.526-534
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    • 2000
  • Near-net-shape forming of zirconia powder was investigated under the combination of cold die and isostatic pressing and pressureless sintering. A novel combination pressing technique, i.e., die com paction under cold isostatic pressing, allowed to produce a complex shaped ceramic powder compact with the controlled dimensions and relatively uniform density distributions. The constitutive models proposed by Kim and co-workers for densification of ceramic powder under cold compaction and high temperature were implemented into a finite element program (ABAQUS). Experimental data for relative density distributions and deformations of zirconia powder compacts produced by cold combination pressing and pressureless sintering were compared with finite element results. Finite element results agreed well with experimental data.

퍼지 가중 평균을 이용한 다중 센서 데이타 융합 (Multisensor Data Combination Using Fuzzy Weighted Average)

  • 김완주;고중협;정명진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1993년도 하계학술대회 논문집 A
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    • pp.383-386
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    • 1993
  • In this paper, we propose a sensory data combination method by a fuzzy number approach for multisensor data fusion. Generally, the weighting of one sensory data with respect to another is derived from measures of the relative reliabilities of the two sensory modules. But the relative weight of two sensory data can be approximately determined through human experiences or insufficient experimental data without difficulty. We represent these relative weight using appropriate fuzzy numbers as well as sensory data itself. Using the relative weight, which is subjective valuation, and a fuzzy-numbered sensor data, the fuzzy weighted average method is used for a representative sensory data. The manipulation and calculation of fuzzy numbers can be carried out using the Zadeh's extension principle which can be approximately implemented by the $\alpha$-cut representation of fuzzy numbers and interval analysis.

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수집한 GPS데이터의 상호방향성을 이용한 경로데이터 조합방법 (A Combination Method of Trajectory Data using Correlated Direction of Collected GPS Data)

  • 구광민;박희민
    • 한국멀티미디어학회논문지
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    • 제19권8호
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    • pp.1636-1645
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    • 2016
  • In navigation systems that use collected trajectory for routing, the number and diversity of trajectory data are crucial despite the infeasible limitation which is that all routes should be collected in person. This paper suggests an algorithm combining trajectories only by collected GPS data and generating new routes for solving this problem. Using distance between two trajectories, the algorithm estimates road intersection, in which it also predicts the correlated direction of them with geographical coordinates and makes a decision to combine them by the correlated direction. With combined and generated trajectory data, this combination way allows trajectory-based navigation to guide more and better routes. In our study, this solution has been introduced. However, the ways in which correlated direction is decided and post-process works have been revised to use the sequential pattern of triangles' area GPS information between two trajectories makes in road intersection and intersection among sets comprised of GPS points. This, as a result, reduces unnecessary combinations resulting redundant outputs and enhances the accuracy of estimating correlated direction than before.

상호작용 중요도 행렬을 이용한 단백질-단백질 상호작용 예측 (Protein-Protein Interaction Prediction using Interaction Significance Matrix)

  • 장우혁;정석훈;정휘성;현보라;한동수
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제36권10호
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    • pp.851-860
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    • 2009
  • 최근 계산을 통한 단백질 상호작용 예측 기법 중, 단백질 쌍이 포함하고 있는 도메인들 사이의 관계에 중점을 둔 도메인 정보 기반 예측 기법들이 다양하게 제안되고 있다. 하지만, 다수의 도메인 쌍들이 상호작용에 기여하는 정도를 정밀하게 반영하는 계산 기법은 드문 실정이다. 본 논문에서는 단백질 상호작용에 있어 도메인 조합 쌍의 상호작용 영향력을 수치화하여 반영한 상호작용 중요도 행렬을 고안하고 이를 기반으로 한 단백질 상호작용 예측 시스템을 구현한다. 일반적인 도메인 조합 기법과 달리, 상호작용 중요도 행렬에서는 상호작용을 위한 도메인간의 협업 확률이 고려된 Weighted 도메인 조합과, 다수의 Weighted 도메인 조합 중 실제 상호작용 주체가 될 확률을 도메인 조합 쌍의 힘(Domain Combination Pair Power, DCPPW)으로 수치화한다. DIP과 IntAct에서 얻어온 S. cerevisiae의 단백질 상호작용 데이터와 Pfam-A 도메인 정보를 사용한 정확도 검증 결과, 평균 63%의 민감도와 94%의 특이도를 확인하였으며, 학습집단의 증가에 따른 안정적인 예측 정확도 향상을 보였다. 본 논문에서 구현한 예측 시스템과 학습 데이터는 웹(http://code.google.com/p/prespi)을 통하여 내려 받을 수 있다.