• 제목/요약/키워드: 하이브리드 방법

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Impact of Ensemble Member Size on Confidence-based Selection in Bankruptcy Prediction (부도예측을 위한 확신 기반의 선택 접근법에서 앙상블 멤버 사이즈의 영향에 관한 연구)

  • Kim, Na-Ra;Shin, Kyung-Shik;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.55-71
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    • 2013
  • The prediction model is the main factor affecting the performance of a knowledge-based system for bankruptcy prediction. Earlier studies on prediction modeling have focused on the building of a single best model using statistical and artificial intelligence techniques. However, since the mid-1980s, integration of multiple techniques (hybrid techniques) and, by extension, combinations of the outputs of several models (ensemble techniques) have, according to the experimental results, generally outperformed individual models. An ensemble is a technique that constructs a set of multiple models, combines their outputs, and produces one final prediction. The way in which the outputs of ensemble members are combined is one of the important issues affecting prediction accuracy. A variety of combination schemes have been proposed in order to improve prediction performance in ensembles. Each combination scheme has advantages and limitations, and can be influenced by domain and circumstance. Accordingly, decisions on the most appropriate combination scheme in a given domain and contingency are very difficult. This paper proposes a confidence-based selection approach as part of an ensemble bankruptcy-prediction scheme that can measure unified confidence, even if ensemble members produce different types of continuous-valued outputs. The present experimental results show that when varying the number of models to combine, according to the creation type of ensemble members, the proposed combination method offers the best performance in the ensemble having the largest number of models, even when compared with the methods most often employed in bankruptcy prediction.

The emergence and ensuing typology of global ebook platform -The case study on Google eBook, Amazon Kindle, Apple iBooks Store (글로벌 전자책 플랫폼의 부상 과정과 유형에 관한 연구 -구글 이북, 아마존 킨들, 애플 아이북스 스토어에 대한 사례연구)

  • Chang, Yong-Ho;Kong, Byoung-Hun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.13 no.8
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    • pp.3389-3404
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    • 2012
  • Based on the case study methods, the study analyzes emergence and ensuing typology of global ebook platforms such as Google eBook, Amazon Kindle, iBooks Store. Global ebook platforms show adaptation process responding to rapidly changing digital technological envirment and it's fitness landscape. The critical elements in its emerging process are the distinct selection criteria, the degree of resource abundance and the search process based on open innovation. Based on these critical elements, the global platforms show speciation process, so called niche creation and are evolving into a variety of the typology based on the initial condition of key resource which makes the platform emerge and grow. Each global ebook platforms is evolving into open platform, hybrid platform, closed platform. Google eBook has openness and extensibility due to a variety of devices based on Android and a direct involvement of actors. Amazon Kindle has developed from a online bookstore and into the hybrid platform which have not only closed quality but also openness with ebook devices and mobile network. iBooks Store has developed into the closed platform through the agency model based on competitive hardwares and closed quality with iphone and ipad.

Preparation and Characterization of PLGA Scaffold Impregnated Keratin for Tissue Engineering Application (케라틴이 함유된 조직공학적 PLGA 지지체의 제조 및 특성 분석)

  • Oh, A-Young;Kim, Soon-Hee;Lee, Sang-Jin;Yoo, James J.;Dyke, Mark van;Rhee, John M.;Khang, Gil-Son
    • Polymer(Korea)
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    • v.32 no.5
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    • pp.403-408
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    • 2008
  • Keratin is the major structural fibrous protein providing outer covering such as wool, hair, and nail. Keratin is useful as natural protein. We developed the keratin loaded poly(L-lactide-co-glycolide) (PLGA) scaffolds (keratin/PLGA) for the possibility of the application of the tissue engineering using bone marrow mesenchymal (BMSCs). Keratin/PLGA (contents 0%, 10%, 20% and 50% of PLGA weight) scaffolds were prepared by solvent casting/salt leaching method. We characterized porosity, wettability, and water uptake ability, DSC of keratin/PLGA scaffold. We seeded BMSCs isolated from the femurs of rat into the inner core of the hybrid scaffold. Celluar viability were assayed by 3- (4,5-dimethylthiazol-2-yl) -2,5-diphenyl-tetrazolium bromide (MTT) test. We confirmed that keratin/PLGA scaffold is hydrophilic by wettability, and water uptake ability measurement results. In MTT assay results, cell viability in scaffolds impregnated 10 and 20 wt% of keratin were higher than other scaffolds. In conclusion, we suggest that keratin/PLGA scaffold may be useful to tissue engineering using BMSCs.

CRNN-Based Korean Phoneme Recognition Model with CTC Algorithm (CTC를 적용한 CRNN 기반 한국어 음소인식 모델 연구)

  • Hong, Yoonseok;Ki, Kyungseo;Gweon, Gahgene
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.3
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    • pp.115-122
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    • 2019
  • For Korean phoneme recognition, Hidden Markov-Gaussian Mixture model(HMM-GMM) or hybrid models which combine artificial neural network with HMM have been mainly used. However, current approach has limitations in that such models require force-aligned corpus training data that is manually annotated by experts. Recently, researchers used neural network based phoneme recognition model which combines recurrent neural network(RNN)-based structure with connectionist temporal classification(CTC) algorithm to overcome the problem of obtaining manually annotated training data. Yet, in terms of implementation, these RNN-based models have another difficulty in that the amount of data gets larger as the structure gets more sophisticated. This problem of large data size is particularly problematic in the Korean language, which lacks refined corpora. In this study, we introduce CTC algorithm that does not require force-alignment to create a Korean phoneme recognition model. Specifically, the phoneme recognition model is based on convolutional neural network(CNN) which requires relatively small amount of data and can be trained faster when compared to RNN based models. We present the results from two different experiments and a resulting best performing phoneme recognition model which distinguishes 49 Korean phonemes. The best performing phoneme recognition model combines CNN with 3hop Bidirectional LSTM with the final Phoneme Error Rate(PER) at 3.26. The PER is a considerable improvement compared to existing Korean phoneme recognition models that report PER ranging from 10 to 12.

Properties of Perovskite Materials and Devices Fabricated Using the Solvent Engineered One-Step Spin Coating Method (단일 스텝 스핀 코팅 방법에서 증발 제어 공정 변경에 따른 페로브스카이트 박막 물성 및 태양 전지 소자 특성 변화에 관한 연구)

  • Oh, Jungseock;Kwon, Namhee;Cha, DeokJoon;Yang, JungYup
    • New Physics: Sae Mulli
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    • v.68 no.11
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    • pp.1208-1214
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    • 2018
  • The one-step spin coating method is reported as an excellent thin film process because it can be easily used to fabricate high-quality methyl-ammonium lead tri-iodide ($MAPbI_3$) perovskite layers. One of the important things in the one-step spin coating method towards obtaining high-quality $MAPbI_3$ layers is the anti-solvent (AS) engineering, which consists of an one-step deposition of the $MAPbI_3$ film and dripping of the AS. The properties of the $MAPbI_3$ layer were found to be strongly influenced by the amount, dispensing speed, and spraying time of the AS solution. The $MAPbI_3$ solution was prepared by dissolving lead iodide and methyl-ammonium iodide in N,N-dimethylformamide and adding N,N-dimethyl sulfoxide. Diethyl ether (DE) was used for the AS solution. The results indicate that a $MAPbI_3$ layer appropriately sprayed with DE is beneficial for improving film quality and device efficiency because nucleation of $MAPbI_3$ layer is affected by the characteristics of DE, which affect the film's crystallinity, density, and surface morphology. The $MAPbI_3$ layer, which was optimized by using 0.7 mL of DE, a 3.03 mL/sec dispensing speed, and a 7 second time to spray after spinning showed the best efficiency of 13.74%, which was reproducible.

Implementation of Prosumer Management System for Small MicroGrid (소규모 마이크로그리드에서 프로슈머관리시스템의 구현)

  • Lim, Su-Youn;Lee, Tae-Won
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.6
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    • pp.590-596
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    • 2020
  • In the island areas where system connection with the commercial power grid is difficult, it is quite important to find a method to efficiently manage energy produced with independent microgrids. In this paper, a prosumer management system for P2P power transaction was realized through the testing the power meter and the response rate of the collected data for the power produced in the small-scale microgrids in which hybrid models of solar power and wind power were implemented. The power network of the microgrid prosumer was composed of mesh structure and the P2P power transaction was tested through the power meter and DC power transmitter in the off-grid sites which were independently constructed in three places. The measurement values of the power meter showed significant results of voltage (average): 380V + 0.9V, current (average): + 0.01A, power: 1000W (-1W) with an error range within ±1%. Stabilization of the server was also confirmed with the response rate of 0.32 sec. for the main screen, 2.61 sec. for the cumulative power generation, and 0.11 sec for the power transaction through the transmission of 50 data in real time. Therefore, the proposed system was validated as a P2P power transaction system that can be used as an independent network without transmitted by Korea Electric Power Corporation (KEPCO).

A Study on Optimization of Perovskite Solar Cell Light Absorption Layer Thin Film Based on Machine Learning (머신러닝 기반 페로브스카이트 태양전지 광흡수층 박막 최적화를 위한 연구)

  • Ha, Jae-jun;Lee, Jun-hyuk;Oh, Ju-young;Lee, Dong-geun
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.55-62
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    • 2022
  • The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

Fine-image Registration between Multi-sensor Satellite Images for Global Fusion Application of KOMPSAT-3·3A Imagery (KOMPSAT-3·3A 위성영상 글로벌 융합활용을 위한 다중센서 위성영상과의 정밀영상정합)

  • Kim, Taeheon;Yun, Yerin;Lee, Changhui;Han, Youkyung
    • Korean Journal of Remote Sensing
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    • v.38 no.6_4
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    • pp.1901-1910
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    • 2022
  • Arriving in the new space age, securing technology for fusion application of KOMPSAT-3·3A and global satellite images is becoming more important. In general, multi-sensor satellite images have relative geometric errors due to various external factors at the time of acquisition, degrading the quality of the satellite image outputs. Therefore, we propose a fine-image registration methodology to minimize the relative geometric error between KOMPSAT-3·3A and global satellite images. After selecting the overlapping area between the KOMPSAT-3·3A and foreign satellite images, the spatial resolution between the two images is unified. Subsequently, tie-points are extracted using a hybrid matching method in which feature- and area-based matching methods are combined. Then, fine-image registration is performed through iterative registration based on pyramid images. To evaluate the performance and accuracy of the proposed method, we used KOMPSAT-3·3A, Sentinel-2A, and PlanetScope satellite images acquired over Daejeon city, South Korea. As a result, the average RMSE of the accuracy of the proposed method was derived as 1.2 and 3.59 pixels in Sentinel-2A and PlanetScope images, respectively. Consequently, it is considered that fine-image registration between multi-sensor satellite images can be effectively performed using the proposed method.

Quantitative precipitation estimation of X-band radar using empirical relationship (경험적 관계식을 이용한 X밴드 레이더의 정량적 강우 추정)

  • Song, Jae In;Lim, Sanghun;Cho, Yo Han;Jeong, Hyeon Gyo
    • Journal of Korea Water Resources Association
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    • v.55 no.9
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    • pp.679-686
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    • 2022
  • As the occurrences of flash floods have increased due to climate change, faster and more accurate precipitation observation using X-band radar has become important. Therefore, the Ministry of Environment installed two dual-pol X-band radars at Samcheok and Uljin. The radar data used in this study were obtained from two different elevation angles and composed to reduce the shielding effect. To obtain quantitative rainfall, quality control (QC), KDP retrieval, and Hybrid Surface Rainfall (HSR) methods were sequentially applied. To improve the accuracy of the quantitative precipitation estimation (QPE) of the X-band radar, we retrieved parameters for the relationship between rainfall rate and specific differential phase, which is commonly called the R-KDP relationship; hence, an empirical approach was developed using multiple rain gauges for those two radars. The newly suggested relationship, R = 27.4K0.81DP, slightly increased the correlation coefficient by 1% more than the relationship suggested by the previous study. The root mean square error significantly decreased from 3.88 mm/hr to 3.68 mm/hr, and the bias of the estimated precipitation also decreased from -1.72 mm/hr to -0.92 mm/hr for overall cases, showing the improvement of the new method.

Development of crop harvest prediction system architecture using IoT Sensing (IoT Sensing을 이용한 농작물 수확 시기 예측 시스템 아키텍처 개발)

  • Oh, Jung Won;Kim, Hangkon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.6
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    • pp.719-729
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    • 2017
  • Recently, the field of agriculture has been gaining a new leap with the integration of ICT technology in agriculture. In particular, smart farms, which incorporate the Internet of Things (IoT) technology in agriculture, are in the spotlight. Smart farm technology collects and analyzes information such as temperature and humidity of the environment where crops are cultivated in real time using sensors to automatically control the devices necessary for harvesting crops in the control device, Environment. Although smart farm technology is paying attention as if it can solve everything, most of the research focuses only on increasing crop yields. This paper focuses on the development of a system architecture that can harvest high quality crops at the optimum stage rather than increase crop yields. In this paper, we have developed an architecture using apple trees as a sample and used the color information and weight information to predict the harvest time of apple trees. The simple board that collects color information and weight information and transmits it to the server side uses Arduino and adopts model-driven development (MDD) as development methodology. We have developed an architecture to provide services to PC users in the form of Web and to provide Smart Phone users with services in the form of hybrid apps. We also developed an architecture that uses beacon technology to provide orchestration information to users in real time.