• 한국실내디자인학회논문집
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• 제24권1호
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• pp.207-215
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• 2015

It seems obvious that the spatial information of existing architectural heritage will be re-structured utilizing BIM technology. In the future to be able to implement such task, a new system of classification of spatial information, which fit to the structural nature of architectural heritage is necessary. This paper intend to suggest the conceptual model that can be the base of establishing new classification system for architectural heritage. For this study we reviewed researches related to classification system of architectural heritage (CS-AH) and BIM based architectural heritage (BIM-AH), first. As a result, we found that CS-AH is focused on building elevation and type, and BIM-AH is biased on the Library and Parametric Modeling. Second, we figured out a relationship between the CS-AH and BIM-AH. From this analysis, we found that BIM-AH is biased on Library and Parametric since the building elevation and type was focused on CS-AH. This review suggests a potential of the 3D CS-AH to expand the range of research for BIM-AH. At last, we suggest the three concept of classification are: 1)horizontality-accumulation relationship, 2)structure-infill relationship, 3)segment-member relationship. These three concept, together as one system of classification, could provide useful framework of new classification system of spatial information for architectural heritage.

• 말소리와 음성과학
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• 제7권1호
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• pp.57-65
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• 2015

This study aimed to identify the development pattern of final stop consonant perception using the gating task. Sixty-four subjects participated in the study: 16 children aged 4 years, 16 children aged 5 years, 17 children aged 6 years, and 15 adults. One-syllable words with consonant-vowel-consonant(CVC) structure, mokㄱ-motㄱ and papㄱ-patㄱ were used as stimuli in order to remove the redundancy of acoustic cues in stimulus words, 40ms-length (-40ms) and 60ms-length (-60ms) from the entire duration of the final consonant were deleted. Three conditions (the whole word segment, -40ms, -60ms) were used for this speech perception experiment. 48 tokens (4 stimuli ${\times}3$ conditions ${\times}4$ trials) in total were provided for participants. The results indicated that 5 and 6 year olds showed final consonant perception similar to adults in stimuli, papㄱ-patㄱ and only the 6-year-old children showed perception similar to adults in stimuli, 'mokㄱ-motㄱ. The results suggested that younger typically developing children require more acoustic information to accurately perceive final consonants than older children and adults. Final consonant perception ability may become adult-like around 6 years old. The study provides fundamental data on the development pattern of speech perception in normal developing children, which can be used to compare to those of children with communication disorders.

• 한국전자통신학회논문지
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• 제3권4호
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• pp.276-281
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• 2008

배전계통은 여러 가지 이유로 잦은 고장을 경험하기 때문에 고장위치 추정은 전력공급 신뢰도 측면에서 매우 중요하다. 그렇지만 배전계통은 주 선로에서 분기되는 3상 및 단상 분기선을 가지는 수지상 구조로 설계되며 각 구간 상에 수개의 로드 탭을 가지기 때문에 고장점 표정이 어렵다. 따라서 본 연구에서는 기존의 전력계통 고장점 표정기법에 대해서 조사, 분석하여 배전자동화시스템의 중앙제어장치에서 효과적으로 실행할 수 있는 고장거리 계산 기법을 결정한다. 그리고 EMTP 모의 결과를 통해 결정된 방법의 유효성을 검증한다.

• 말소리와 음성과학
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• 제3권1호
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• pp.51-65
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• 2011

This study attempts to investigate the interlanguage speech intelligibility benefit for listeners (ISIB-L), examining Chinese talkers' production of English liquids and its perception of native listeners and non-native Chinese and Korean listeners. An Accent Judgment Task was conducted to measure non-native talkers' and listeners' phonological proficiency, and two levels of proficiency groups (high and low) participated in the experiment. The English liquids /l/ and /r/ produced by Chinese talkers were considered in terms of positions (syllable initial and final), contexts (segment, word and sentence) and lexical density (minimal vs. nonminimal pair) to see if these factors play a role in ISIIB-L. Results showed that both matched and mismatched interlanguage speech intelligibility benefit for listeners occurred except for the initial /l/. Non-native Chinese and Korean listeners, though only with high proficiency, were more accurate at identifying initial /r/, final /l/ and final /r/, but initial /l/ was significantly more intelligible to native listeners than non-native listeners. There was evidence of contextual and lexical density effects on ISIB-L. No ISIB-L was demonstrated in sentence context, but both matched and mismatched ISIB-L was observed in word context; this finding held true for only high proficiency listeners. Listeners recognized the targets better in the non-minimal pair (sparse density) environment than the minimal pair (higher density) environment. These findings suggest that ISIB-L for English liquids is influenced by talkers' and listeners' proficiency, syllable position in association with L1 and L2 phonological structure, context, and word neighborhood density.

• 산업공학
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• 제22권2호
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• pp.126-134
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• 2009

As product quality and yield are essential factors in semiconductor manufacturing, monitoring the main manufacturing steps is a critical task. For the purpose, FDC(Fault detection and classification) is used for diagnosing fault states in the processes by monitoring data stream collected by equipment sensors. This paper proposes an FDC model based on decision tree which provides if-then classification rules for causal analysis of the processing results. Unlike previous decision tree approaches, we reflect the structural aspect of the data stream to FDC. For this, we segment the data stream into multiple subregions, define structural features for each subregion, and select the features which have high relevance to results of the process and low redundancy to other features. As the result, we can construct simple, but highly accurate FDC model. Experiments using the data stream collected from etching process show that the proposed method is able to classify normal/abnormal states with high accuracy.

• 한국IT서비스학회지
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• 제15권4호
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• pp.153-174
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• 2016

On account of multiple causes, including prolonged global economic crisis, addressing environmental pollution and the advent of hyper-connected society, a new paradigm called 'sharing economy' has rapidly emerged. Many startups have attempted to build promising business model based on the sharing economy concept. Nevertheless, successful cases are still very rare in the global level, except for Uber and Airbnb cases. Therefore, this study analyzes necessary causes and sufficient causes for successful settlements in the market through a comparative case analysis on digital matching firms in the sharing economy businesses. For the case study, we compare five successful cases (Uber, Airbnb, Kickstarter, TaskRabbit and DogVacay), three failure cases (Homejoy, Ridejoy and Tuterspree) and a platform cooperativism case (Juno) in accordance with six value attributes of business model including value proposition, market segment, value chain, cost structure and profit potential, value network and competitive strategy. We apply Boolean method to support controlled comparison and eliminate unnecessary attributes. The Boolean analysis result shows that value proposition, cost structure and profit potential, value network and competitive strategy are the essential attributes. Furthermore, the result indicates that each attribute is a necessary condition, where all four conditions should be met simultaneously in order to be successful. With this result, we discuss essential consideration for those who are planning startup based on the sharing economy business model.

• Journal of Information Processing Systems
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• 제10권4호
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• pp.503-522
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• 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

• 대한원격탐사학회지
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• 제17권4호
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• pp.319-334
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• 2001

Extracting primitives from imagery plays an important task in visual information processing since the primitives provide useful information about characteristics of the objects and patterns. The human visual system utilizes features without difficulty for image interpretation, scene analysis and object recognition. However, to extract and to analyze feature are difficult processing. The ultimate goal of digital image processing is to extract information and reconstruct objects automatically. The objective of this study is to develop robust method to achieve the goal of the image processing. In this study, an adaptive strategy was developed by implementing Gabor filters in order to extract feature information and to segment images. The Gabor filters are conceived as hypothetical structures of the retinal receptive fields in human vision system. Therefore, to develop a method which resembles the performance of human visual perception is possible using the Gabor filters. A method to compute appropriate parameters of the Gabor filters without human visual inspection is proposed. The entire framework is based on the theory of human visual perception. Digital images were used to evaluate the performance of the proposed strategy. The results show that the proposed adaptive approach improves performance of the Gabor filters for feature extraction and segmentation.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1000-1011
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• 2021

In recent years, using Deep Learning methods to apply for medical and biomedical image analysis has seen many advancements. In clinical, using Deep Learning-based approaches for cancer image analysis is one of the key applications for cancer detection and treatment. However, the scarcity and shortage of labeling images make the task of cancer detection and analysis difficult to reach high accuracy. In 2015, the Unet model was introduced and gained much attention from researchers in the field. The success of Unet model is the ability to produce high accuracy with very few input images. Since the development of Unet, there are many variants and modifications of Unet related architecture. This paper proposes a new approach of using Unet++ with pretrained EfficientNet as backbone architecture for breast tumor cell nuclei segmentation and uses the multi-organ transfer learning approach to segment nuclei of breast tumor cells. We attempt to experiment and evaluate the performance of the network on the MonuSeg training dataset and Triple Negative Breast Cancer (TNBC) testing dataset, both are Hematoxylin and Eosin (H & E)-stained images. The results have shown that EfficientUnet++ architecture and the multi-organ transfer learning approach had outperformed other techniques and produced notable accuracy for breast tumor cell nuclei segmentation.

• 방송공학회논문지
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• 제27권1호
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• pp.13-19
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• 2022

동영상 객체 분할(VOS) 기술은 연속된 레이블링 데이터를 필요로 하며, 현재 공개된 데이터셋으로 훈련된 VOS방법은 그 성능이 제한된다. 이 문제를 해결하기 위해 본 논문에서는 간단하면서도 효과적인 동영상 데이터 증강 기술들을 제안한다. 첫번째 증강 기술은 영상 내에서 객체를 제외한 배경을 다른 영상의 배경으로 대체하는 기법이고, 두번째 기술은 학습될 동영상 데이터의 순서를 무작위 확률로 뒤집어 역 재생되는 영상을 학습시키는 기법이다. 두 증강 기술은 객체 분할 시 배경 정보에 강인한 추정을 가능하게 하였고, 추가 데이터 없이 기존 모델의 성능을 향상시킬 수 있음을 보였다.