• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 춘계학술대회논문집
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• pp.559-564
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• 2002

Cross-talk cancellation, inverse filter design or deconvolution in a generic term, is a vital process for a virtual sound realization in the stereo sound reproduction system. Most, if not all, of the design algorithms available for the inverse filter are based on a linearized model of the real physical plant. The result of such a plant-based design method, which may be referred to here as the indirect method, is biased due to both modelling and inversion errors. This paper presents a novel direct cross-talk cancellation method that may be free from the inversion error. The direct method can directly models the inverse filter by a suitable rearrangement of the input and output ports of the original plant so that no inversion is required here. Advantages are discussed with various experiments in an anechoic chamber using a PC soundcard. Binaural reproduction tests conducted showed that the conventional indirect method yields about 8 % reproduction performance error on both ear positions, whereas the direct method offers about 3 %.

• 한국측량학회지
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• 제34권4호
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• 한국측량학회지
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• 제28권3호
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• pp.337-345
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• 2010

일반적으로 비용이 많이 들고 복잡한 처리과정을 거치는 디지털 항공사진측량은 독립형 워크스테이션 시스템을 기반으로 사용되어 왔다. 본 연구에서는 Open Geospatial Consortium에서 제안한 국제 GIS 표준인 Web Processing Service을 통해 항공사진측량 처리 과정에 대한 새로운 접근 방안을 제시하고자 한다. 실험을 위해 항공사진측량 업무를 기본단위로 정의하는 WPS 프로파일링 과정을 거쳐 여러 개의 제네릭 프로세스로 정의하였고, 정의된 프로세스는 WPS 표준에 따라 각각 서버 S/W와 클라이언트 S/W 모듈을 구현하였다. 본 연구를 통해 WPS의 기본 단위 항공사진측량 프로세스를 다수의 사용자가 웹을 사용하여 공유, 재활용 측면의 접근을 기대할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Smart Structures and Systems
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• 제6권3호
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• pp.239-262
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• 2010

Tube Lines has carried out a "knowledge and investigation programme" on the deep tube tunnels comprising the Jubilee, Northern and Piccadilly lines, as required by the PPP contract with London Underground. Many of the tunnels have been in use for over 100 years, so this assessment was considered essential to the future safe functioning of the system. This programme has involved a number of generic investigations which guide the assessment methodology and the analysis of some 5,000 individual structures. A significant amount of investigation has been carried out, including ultrasonic thickness measurement, detection of brickwork laminations using radar, stress measurement using magnetic techniques, determination of soil parameters using CPT, pressuremeter and laboratory testing, installation of piezometers, material and tunnel segment testing, and trialling of remote photographic techniques for inspection of large tunnels and shafts. Vibrating wire, potentiometer, electro level, optical and fibre-optic monitoring has been used, and laser measurement and laser scanning has been employed to measure tunnel circularity. It is considered that there is scope for considerable improvements in non-destructive testing technology for structural assessment in particular, and some ideas are offered as a "wish-list". Assessment reports have now been produced for all assets forming Tube Lines' deep tube tunnel network. For assets which are non-compliant with London Underground standards, the risk to the operating railway has to be maintained as low as reasonably practicable (ALARP) using enhanced inspection and monitoring, or repair where required. Monitoring techniques have developed greatly during recent years and further advances will continue to support the economic whole life asset management of infrastructure networks.

• 정보과학회 논문지
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• 제42권12호
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• pp.1590-1599
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• 2015

다양한 개인 의료 장비들이 등장함에 따라 개인 의료 컨텍스트가 풍부하게 수집되고 있다. 이렇게 수집된 의료 컨텍스트를 분석함으로써 소프트웨어적으로 질병을 진단하기 위한 노력이 이어지고 있다. 본 논문에서는 의료 전문가들이 사용하는 의료 분석 기법을 정형화하고, 각 의료 기법을 실현화하기 위한 추론 기법을 식별하며, 추론기법의 적용 지침을 제시한다. 또한, 의료 기법을 제공하는 추론 시스템을 PoC 수준에서 개발하고, 실제 의료 컨텍스트를 분석하여 질병 진단 실험을 수행함으로써 제시하는 의료 분석 기법 및 추론 기법 적용 지침의 실효성과 그 효과를 검증한다.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.379-386
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• 2012

A symptom-based procedure with a critical safety function monitoring system has been established to reduce the operator's diagnosis and cognitive burden since the Three-Mile Island (TMI) accident. However, it has been reported that a symptom-based procedure also requires an operator's cognitive efforts to cope with off-normal events. This can be caused by mismatches between a static model, an emergency operating procedure (EOP), and a dynamic process, the nature of an ongoing situation. The purpose of this study is to share the evidence of mismatches that may result in an excessive cognitive burden in conducting EOPs. For this purpose, we analyzed simulated emergency operation records and observed some operator behaviors during the EOP operation: continuous steps, improper description, parameter check at a fixed time, decision by information previously obtained, execution complexity, operation by the operator's knowledge, notes and cautions, and a foldout page. Since observations in this study are comparable to the results of an existing study, it is expected that the operational behaviors observed in this study are generic features of operators who have to cope with a dynamic situation using a static procedure.

• 중소기업융합학회논문지
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• 제5권1호
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• pp.13-18
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• 2015

악성코드란 해커가 악의적인 목적을 위하여 작성이 되어있는 실행 가능한 코드의 통칭으로써 자기복제 능력과 감염 대상 유무에 따라 바이러스, 웜, 트로이목마 등으로 분류된다. 주로 웹페이지 검색이나 P2P사용, 셰어웨어를 사용 할 때 등, 이런 상황에서 침투가 많이 발생이 되고 있다. 악성코드로 공격을 당하게 되면 이메일이 자동으로 발송이 된다거나, 시스템 성능 저하, 개인 정보 유출 등의 피해를 입게 된다. 이번에 악성코드를 소개 하면서 악성코드에 관련된 내용들을 설명하고 대응책을 알아본다. 그리고 향후 연구방향에 대해서도 생각해본다.

• ETRI Journal
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• 제28권5호
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• pp.593-606
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• 2006

Thanks to the great possibilities of providing different types of telecommunication traffic to a large geographical area, satellite networks are expected to be an essential component of the next-generation internet. As a result, issues concerning the designing and testing of efficient connection-admission-control (CAC) strategies in order to increase the quality of service (QoS) for multimedia traffic sources, are attractive and at the cutting edge of research. This paper investigates the potential strengths of a generic digital-video-broadcasting return-channel-via-satellite (DVB-RCS) system architecture, proposing a new CAC algorithm with the aim of efficiently managing real-time multimedia video sources, both with constant and high variable data rate transmission; moreover, the proposed admission strategy is compared with a well-known iterative CAC mainly designed for the managing of real-time bursty traffic sources in order to demonstrate that the new algorithm is also well suited for those traffic sources. Performance analysis shows that, both algorithms guarantee the agreed QoS to real-time bursty connections that are more sensitive to delay jitter; however, our proposed algorithm can also manage interactive real-time multimedia traffic sources in high load and mixed traffic conditions.

• 전력전자학회논문지
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• 제20권6호
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• pp.498-508
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• 2015

In the simulation of photovoltaic (PV) power conditioning systems, PSIM is a widely accepted circuit simulation platform because of its fast speed and C-code support. PSIM provides two kinds of generic PV panel models: functional model and physical model. Whereas the functional model simulates PV in the standard test condition (STC) only, the physical model can emulate changing PV characteristics under varying temperatures and irradiation conditions and is thus more suitable for system simulation. However, the physical model requires complicated parameters from users, and thus it is prone to errors and is difficult to use. In this study, a new PSIM model for PV is presented to solve these problems. The proposed model utilizes manufacturers' datasheet values specified under STC only and excludes user-defined information from input parameters. To achieve good accuracy even in varying environmental conditions, single-diode model parameters are successively tuned to a time-varying virtual datasheet. Comparison with a conventional physical model shows that the proposed model provides more accurate simulation according to error analysis based on the EN50530 standard.