• Industrial Engineering and Management Systems
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• 제15권4호
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• pp.403-431
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• 2016

The objective of this study is to integrate the business, maintenance and production processes of a manufacturing system by incorporating errors. First, the required functions are estimated according to the historical data. The system activities are simulated by Visual SLAM software and the required outputs are obtained. Several outputs including lead times in different dimensions, total cost and production rates are computed through simulation. Finally, data envelopment analysis (DEA) is utilized in order to select the best option between the defined scenarios due to the multi-criteria feature of the problem. This is the first study in which the lead times, cost and production rates are simultaneously considered in the integrated system imposed of business, maintenance and production processes by incorporating errors. In the current study, the major bottlenecks of the system being studied are identified and suggested different strategies to improve the system and make the best decision.

• 말소리와 음성과학
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• 제11권2호
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• pp.57-64
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• 2019

본 논문에서는 음성 합성을 위한 오픈소스 시스템인 Merlin 툴킷을 이용하여 한국어 TTS 시스템을 구성한다. TTS 시스템에서 HMM 기반의 통계적 음성 합성 방식이 널리 사용되고 있는데, 이 방식에서 문맥 요인을 포함시키는 음향 모델링 구성의 한계로 합성 음성의 품질이 저하된다고 알려져 있다. 본 논문에서는 여러 분야에서 우수한 성능을 보여 주는 심층 신경망 기법을 적용하는 음향 모델링 아키텍처를 제안한다. 이 구조에는 전연결 심층 피드포워드 신경망, 순환 신경망, 게이트 순환 신경망, 단방향 장단기 기억 신경망, 양방향 장단기 기억 신경망 등이 포함되어 있다. 실험 결과, 문맥을 고려하는 시퀀스 모델을 아키텍처에 포함하는 것이 성능 개선에 유리하다는 것을 알 수 있고, 장단기 기억 신경망을 적용한 아키텍처가 가장 좋은 성능을 보여주었다. 그리고 음향 특징 파라미터에 델타와 델타-델타 성분을 포함하는 것이 성능 개선에 유리하다는 결과가 도출되었다.

• Asia pacific journal of information systems
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• 제1권1호
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• pp.63-86
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• 1991

In this paper, our concern is the artificial neural network-based patten classification, when can resolve the difficulties in the Autoregressive Moving Average(ARMA) model identification problem To effectively classify a time series into an approriate ARMA model, we adopt the Multi-layered Backpropagation Network (MLBPN) as a pattern classifier, and Extended Sample Autocorrelation Function (ESACF) as a feature extractor. To improve the classification power of MLBPN's we suggest an integrated neural network system which consists of an AR Network and many small-sized MA Networks. The output of AR Network which will gives the MA order. A step-by-step training strategy is also suggested so that the learned MLBPN's can effectively ESACF patterns contaminated by the high level of noises. The experiment with the artificially generated test data and real world data showed the promising results. Our approach, combined with a statistical parameter estimation method, will provide a way to the automation of ARMA modeling.

• 한국CDE학회논문집
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• 제17권1호
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• pp.7-16
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• 2012

One distinguishing feature of BIM(Building Information Modeling) is the objectification of spatial elements independently, which makes it easy to represent spatial network. From this perspective, this study aimed to develop the spatial network analysis tool based on open BIM technologies. From the literature review, an object model of spatial network with nodes and links and a process model from construction to visualization were established. A prototype system implementing the proposed models, named SNAT(Spatial Network Analysis Tool), was developed in Java platform with using its open source packages. SNAT can create a spatial network from IFC-BIM model, calculate the indices of spatial network analysis, and visualize it with the representing types(map, graph, matrix and table).

• ETRI Journal
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• 제34권4호
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• pp.583-590
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• 2012

In this paper, we present a new approach for speaker diarization. First, we use the prosodic information calculated on the original speech to resynthesize the new speech data utilizing the spectrum modeling technique. The resynthesized data is modeled with sinusoids based on pitch, vibration amplitude, and phase bias. Then, we use the resynthesized speech data to extract cepstral features and integrate them with the cepstral features from original speech for speaker diarization. At last, we show how the two streams of cepstral features can be combined to improve the robustness of speaker diarization. Experiments carried out on the standardized datasets (the US National Institute of Standards and Technology Rich Transcription 04-S multiple distant microphone conditions) show a significant improvement in diarization error rate compared to the system based on only the feature stream from original speech.

• 한국정보통신학회논문지
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• 제14권12호
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• pp.2737-2746
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• 2010

최근 물류 산업에 USN/RFID 기술을 접목한 새로운 u-물류 패러다임이 등장하고 있다. 본 논문에서는 u-물류 패러다임을 토대로 GPS와 RFID를 이용한 웹 기반 물류차량 이력관리 시스템을 제안한다. 본 시스템의 설계시 모든 이벤트 처리 과정을 하나의 리사이클 형태의 상태로 간주하고 전체 시스템을 객체지향의 UML을 이용하여 모델링한다. 또한 RFID를 기반으로 물류차량을 식별하고 식별된 물류차량이 어떤 처리 과정을 거치고 있는 지를 확인하게 되며, GPS를 활용하여 차량의 위치 정보를 확인한다. 구현 방식은 C/S 방식으로 관리자가 사용하는 웹 기반의 인터페이스를 설계하고, 시스템 사용자의 이동성을 고려하여 PDA 기반의 사용자 GUI를 구현한다. 아울러 본 논문에서는 수요가, 생산처, 물류처, 관리자, 운전자를 각각 구분하고 각 기능을 별도로 구현하여 시스템 재사용성을 높이는데 초점을 둔다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2004년도 추계학술대회 및 정기총회
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• pp.139-142
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• 2004

Business Activities usually comprises various types of business processes. However, most companies don't standardize the constituent processes and accumulate them in formal models, so that they have their limitations for efficient process management and continuous process improvement. Recently, in order to overcome the obstacles, the companies increasingly tend to introduce a BPM (Business Process Management) system. The BPM system functions as modeling dispersed processes over the companies definitely, running the processes and improving them. In addition, the BPM plays a role as a platform in which diverse business applications can be developed. Generally, it is prerequisite to define business processes clearly to run them in the BPM. Unfortunately, companies don't arrange the processes systematically, so that they have difficulty in the introduction and implementation of the system. In this paper, we introduce a new type of a business application to support the clarification of business structure and processes in the companies and facilitate the introduction of the BPM system. The new system is a 'job manual system' developed on the BPM platform. A process model modeled in the job manual system can be transported directly to the BPM system in which the model becomes an executable status. The new system's properties including this feature enable to manage business processes efficiently and help users of the both system perform relevant tasks conveniently.

• 정보처리학회논문지D
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• 제12D권4호
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• pp.589-600
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• 2005

다양하고 빠르게 변화하는 사용자의 요구사항을 만족시키기 위하여 재사용을 고려한 애플리케이션의 개발이 요구되어지고 있다. 이를 통해 대두된 것이 프로덕트 라인이다. 프로덕트 라인은 다양하게 빠르게 변화하는 시장의 요구사항과 특정 도메인 영역에 속하는 애플리케이션 간의 재사용 가능한 아키텍처 및 컴포넌트의 구성으로부터 연관된 시스템 구축 시 생산성과 품질의 향상을 제공함으로써 현재 많은 관심의 초점이 되고 있다. 또한, 이들 프로덕트 라인에서는 프로덕트들 사이의 공통성과 변화성에 초점을 두고 이들 분류 방법으로 휘처 모델링 이라는 개념을 주로 사용하여 분석하고 있다. 또한 재사용 가능한 아키텍처는 많은 변화 계획들과 메커니즘을 포함하고 있다. 그러나 지금까지 이러한 변화들이 일어나는 상황을 이해하는 것과 특별한 상황에서도 가능하게 하는 옵션들을 기록하는 것은 명확히 이루어지지 못하였다. 아키텍처가 오랜 기간 동안 많은 프로덕트 버전에서 사용되어 진다거나, 다른 프로덕트들의 설계를 위해 사용되어지는 아키텍처에서의 프로덕트 라인 문맥에서라면, 매우 중요하게 다루어진다. 즉, 명백한 변화성의 표현과, 아키텍처에서 변경이 되는 적절한 위치를 식별하는 것이 중요하다. 하지만, 아키텍처를 설계하기 위한 아키텍처에서의 변화성 관리에 대한 명확한 방법이 미흡하다. 따라서 본 논문에서는 재사용 가능한 아키텍처를 설계하기 위해 변화성의 명확한 표현과 아키텍처에서의 적절한 위치를 식별하기 위해, 다양한 변화성 타입을 정의하고, 휘처 모델을 기반으로 한 아키텍처의 변화성과 아키텍처의 컴포넌트 관련성에서의 변화성 표현 방법을 기술하고, 제시한 이론을 기반으로 웹 학습 시스템의 설계과정을 거쳐 구현하고자 한다.

• 산업경영시스템학회지
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• 제32권1호
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• pp.102-110
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• 2009

Concurrent Engineering(CE) has presented new possibilities for successful product development by incorporating various product life-cycle functions from the earlier stage of design. In the product design, geometric representation is vital not only in its traditional role as a means of communicating design information but also in its role as a means of externalizing designer's thought process by visualizing the design product. During the last dozens of years, there has been extraordinary development of computer-aided tools intended to generate, present or communicate 3D models. However, there has not been comparable progress in the development of 3D-CAD systems intended to represent and manipulate a variety of product life-cycle information in a consistent manner. This paper proposes a novel concept, Minus Volume (MV), to incorporate various design information relevant to product lift-cycle functions. MV is a functional shape that is extracted from a design object within a bounding box. A prototype 3D-CAD system is implemented based on the MV concept and illustrated with the successful implementation of concurrent design and manufacturing.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.