• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.269-275
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• 2013

In this paper, a new modeling method of a magnetic levitation(Maglev) system using extreme learning machine(ELM) is proposed. The linearized methods using Taylor Series expansion has been used for modeling of a Maglev system. However, the numerical method has some drawbacks when dealing with the components with high nonlinearity of a Maglev system. To overcome this problem, we propose a new modeling method of the Maglev system with electro magnetic suspension, which is based on ELM with fast learning time than conventional neural networks. In the proposed method, the initial input weights and hidden biases of the method are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose generalized inverse. matrix Experimental results show that the proposed method can achieve better performance for modeling of Maglev system than the previous numerical method.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.295-304
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• 2022

The purpose of this study is to investigate the influencing factors and mechanism of the characteristics of the live broadcast e-commerce platform and the characteristics of the host on the impulse purchase intention of live broadcast viewers. Based on the ELM model, this study complements existing research content. This study adopts the form of questionnaire survey and conducts empirical analysis using SPSS, AMOS, Mplus and other analysis software for online live broadcast users. The results show that the characteristics of live broadcast platforms have a positive impact on consumers' flow experience and satisfaction; the personal characteristics of anchors have a positive impact on consumers' flow experience and satisfaction; consumers' flow experience and satisfaction have a positive impact on impulse Purchase intention has a positive impact, and flow experience and satisfaction have a mediating effect on the characteristics of the live broadcast platform and the personal characteristics of the host.

• Annual Conference on Human and Language Technology
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• 2017.10a
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• pp.220-224
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• 2017

최근 은행, 보험회사 등 핀테크 관련 업체에서는 챗봇과 같은 인공지능 대화 시스템을 고객상담 업무에 도입하고 있다. 본 논문에서는 금융 도메인을 위한 고객상담 챗봇을 구현하기 위하여, 자연어 이해 기술 중 하나인 고객상담 대화의 도메인 및 화행분류 방법을 제시한다. 이 기술을 통해 자연어로 이루어지는 상담내용을 이해하고 적합한 응답을 해줄 수 있는 기술을 개발할 수 있다. TF-IDF, LDA, 문장 임베딩 등 대화 문장에 대한 자질을 추출하고, 추출된 자질을 Extreme learning machine(ELM)을 통해 도메인 및 화행 분류 모델을 학습한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1324-1330
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• 2007

In this paper, we propose pattern recognition algorithm for activities of daily living by adopting extreme learning machine based on single layer feedforward networks(SLFNs) to the signal from bidirectional accelerometer. For activity classification, 20 persons are participated and we acquire 6, types of signals at standing, walking, running, sitting, lying, and falling. Then, we design input vector using reduced model for ELM input. In ELM classification results, we can find accuracy change by increasing the number of hidden neurons. As a result, we find the accuracy is increased by increasing the number of hidden neuron. ELM is able to classify more than 80 % accuracy for experimental data set when the number of hidden is more than 20.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.220-224
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• 2017

최근 은행, 보험회사 등 핀테크 관련 업체에서는 챗봇과 같은 인공지능 대화 시스템을 고객상담 업무에 도입하고 있다. 본 논문에서는 금융 도메인을 위한 고객상담 챗봇을 구현하기 위하여, 자연어 이해 기술 중 하나인 고객상담 대화의 도메인 및 화행분류 방법을 제시한다. 이 기술을 통해 자연어로 이루어지는 상담내용을 이해하고 적합한 응답을 해줄 수 있는 기술을 개발할 수 있다. TF-IDF, LDA, 문장 임베딩 등 대화 문장에 대한 자질을 추출하고, 추출된 자질을 Extreme learning machine(ELM)을 통해 도메인 및 화행 분류 모델을 학습한다.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.509-521
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• 2016

A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

• Membrane and Water Treatment
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• v.13 no.4
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• pp.201-208
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• 2022

Emulsion Liquid Membrane (ELM) is a prominent technique for the separation of heavy metal ions from wastewater due to the fast extraction and is a single-stage operation of stripping-extraction. The selection of the components (Surfactant and Carrier) of ELM is a very significant step for its preparation. In the ELM technique, the primary water- in-oil (W/O) emulsion is emulsified in water to produce water-in-oil-in-water (W/O/W) emulsion. The water in oil emulsion was prepared by mixing the membrane phase and internal phase. To prepare the membrane phase, the extractant D2EHPA (di-2-ethylhexylphosphoric acid) was used as a mobile carrier, Span-80 as a surfactant, and Paraffin as a diluent. Moreover, the internal (receiving) phase was prepared by dissolving sulphuric acid in water. Di-(2- ethylhexyl) phosphoric acid such as surfactant concentration, carrier concentration, sulphuric acid concentration in the receiving (internal) phase, agitation time (emulsion phase and feed phase), the volume ratio of the membrane phase to the receiving phase, the volume ratio of the external feed phase to the primary water-in-oil emulsion and pH of feed were studied on the percentage extraction of metal ions at 20℃. The results show that it is possible to remove 78% for As(V), 98% for Cd(II), and 99% for Pb(II). Emulsion Liquid Membrane (ELM) is a well-known technique for separating heavy metal ions from wastewater due to the fast extraction and is a single-stage operation of stripping-extraction. The selection of ELM components (Surfactant and Carrier) is a very significant step in its preparation. In the ELM technique, the primary water-in-oil (W/O) emulsion is emulsified to produce water-in-oil-in-water (W/O/W) emulsion. The water in the oil emulsion was prepared by mixing the membrane and internal phases. The extractant D2EHPA (di-2-ethylhexylphosphoric acid) was used as a mobile carrier, Span-80 as a surfactant, and Paraffin as a diluent. Moreover, the internal (receiving) phase was prepared by dissolving sulphuric acid in water. Di-(2-ethylhexyl) phosphoric acid such as surfactant concentration, carrier concentration, sulphuric acid concentration in the receiving (internal) phase, agitation time (emulsion phase and feed phase), the volume ratio of the membrane phase to the receiving phase, the volume ratio of the external feed phase to the primary water-in-oil emulsion and pH of feed were studied on the percentage extraction of metal ions at 20℃. The results show that it is possible to remove 78% for As(V), 98% for Cd(II), and 99% for Pb(II).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.469-472
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• 2002

본 논문에서는 카오스에 기반을 둔 ELM(Expanding Logistic Map) 암호화 알고리즘을 개선하기 위해 CELM(Cascade Expanding Logistic Map)을 제안한다. 제안된 암호화 시스템은 3차 방정식에 기반을 둔 ELM의 차수를 증가시켜 키의 범위를 확대하고, 서로 다른 Key 값과 초기 값의 함수를 Cascade연결하여 안정성을 높일 수 있었다.

• Fashion & Textile Research Journal
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• v.17 no.5
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• pp.838-843
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• 2015

In this study, a cotton knit was dyed with elm bark extract; subsequently, the dyed fabric was measured according to the types of mordants and the preprocessing cationizers used. Additionally, antibiosis against super bacteria was examined. The results follow. First, the color of the dyed cotton knit appeared reddish and yellowish for fabrics treated with non-mordants and mordants. When preprocessing with a cationizer was conducted, the dyeing properties were the best. Second. even when mordants were not used for dyeing, color fastness after washing, sweating, and rubbing was generally good Grade 4 and 5. Color fastness after exposure to sunlight was the best Grade 4 for fabric prepared with ferrous sulfate as the mordant. Third. as for antimicrobial properties, or resistance to super bacteria, the growth of bacteria was suppressed in a meaningful way for fabrics treated with non-mordants and mordants, compared to the control group fabric. The dyeing methods with the most powerful antimicrobial effects were dyeing after preprocessing with a cationizer and preparing fabric with copper sulfate as the mordant. The results stated above show that in case of dyeing with elm bark extract, preprocessing of the cotton knit with a cationizer and dying with copper mordant displayed high levels of antimicrobial properties that were useful for resisting super bacteria. Of these the dyeing properties were the best when preprocessing with a cationizer.

• Journal of the Korean Wood Science and Technology
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• v.28 no.3
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• pp.62-69
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• 2000

The bark of ash(Fraxinus rhynchophylla) and elm(Ulmus davidiana var. japonica) trees were collected, extracted with acetone-$H_2O$(7:3, v/v), fractionated with hexane, chloroform and ethylacetate, and freeze dried to give some dark brown powder. Each fraction of the powder was chromatographed on a Sephadex LH-20 column using a series of aqueous methanol and ethanol-hexane mixture as eluents. The ash bark contained a large amount of coumarin derivatives such as aesculetin and aesculin in addition to trace amount of ligstroside and oleuropein. Most of the elm bark extractive were (+)-catechin and its glycosides such as (+)-catechin-7-O-xylopyranose and (+)-catechin-7-O-apiofuranose in addition to a small amount of procyanidin B-3, a dimeric (+)-catechin. NMR and FAB-MS spectrometric analyses were performed to characterize the structures of isolated phenolic compounds.