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Train Crowdedness Analysis Model for the Seoul Metropolitan Subway : Considering Train Scheduling (열차운행계획을 반영한 수도권 도시철도 열차 혼잡도 분석모형 연구)

  • Lee, Sangjun;Yun, Seongjin;Shin, Seongil
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.21 no.3
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    • pp.1-17
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    • 2022
  • Accurate analysis of the causes of metro rail traffic congestion provides a means of addressing issues arising from metro rail traffic congestion in metropolitan areas. Currently, congestion analysis based on counting, weight detection, CCTVs, and mobile Wi-Fi is limited by poor accuracies or because studies have been restricted to single routes and trains. In this study, a train congestion analysis model was used that includes the transfer and multi-path behavior of metro passengers and train operation plans for metropolitan urban railroads. Analysis accuracy was improved by considering traffic patterns in which passengers must wait for next trains due to overcrowding. The model updates train crowding levels every 10 minutes, provides information to potential passengers, and thus, is expected to increase the social benefits provided by the Seoul metropolitan subway

Variable Block-size Motion Estimation based on Merging Procedure (병합 방법에 의한 가변 블록 움직임 예측)

  • Lee, Kyu-Ho;Son, Nam-Rye;Lee, Guee-Sang
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.11a
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    • pp.65-68
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    • 2003
  • 본 논문에서는 가장 최근의 동영상 표준인 H.264에서 가변 블록 움직임 예측 시 인접한 블록과의 상관성을 분석하여 병합 절차를 추가함으로써 매크로블록의 최종 모드를 결정하는 시간을 줄이기 위한 알고리즘을 제안한다. H.264에서는 매크로블록의 모드를 결정하기 위하여 총 7가지 모드를 사용하여 움직임 예측은 실시함으로써 부호화 효율을 극대화시킨 반면 이러한 움직임 예측이 부호화기의 복잡도를 높이는 주요 요인으로 현재 커다란 단점으로 지적되고 있다. 본 논문에서는 $8{\times}8$ 움직임 예측이 끝난 후 인접한 두 블록 사이의 거리론 임계값(Threshold)과 비교하여 다음 모드의 움직임 예측의 실시 여부를 먼저 절정함으로써 필요한 움직임 예측에 소비되는 시간을 단축시켰다. 여기서 실험 조건으로 명시하고 있는 것은 대표적인 단일모드 중에서 수행 성능이 가장 좋은 $8{\times}8$ 모드를 기본모드로 사용하고 병합 시 $16{\times}16$ 모드 쪽으로 상향식(bottom-up) 방법의 병합을 수행해 나아간다 모의실험을 통해 수행 성능과 전체 부호화 시간 측면을 본 논문에서 제안한 방법과 4가지 모드인 $16{\times}16,\;16{\times}8,\;8{\times}16,\;8{\times}8$ 모드를 모두 사용한 경우, $8{\times}8$ 단일모드를 사용한 경우를 비교하였다. 실험 결과 $8{\times}8$ 단일모드보다 수행 성능이 향상되었으며, 시간 단축 면에서 제안한 방법이 4가지 모드인 $16{\times}16,\;16{\times}8,\;8{\times}16,\;8{\times}8$ 모드를 모두 사용한 경우와 $8{\times}8$ 단일모드를 사용한 경우보다 계산 시간이 감소하였음을 확인하였다.행중인 MoIM-Messge서버의 네트워크 모듈로 다중 쓰레드 소켓폴링 모델을 적용하였다.n rate compared with conventional face recognition algorithms. 아니라 실내에서도 발생하고 있었다. 정량한 8개 화합물 각각과 총 휘발성 유기화합물의 스피어만 상관계수는 벤젠을 제외하고는 모두 유의하였다. 이중 톨루엔과 크실렌은 총 휘발성 유기화합물과 좋은 상관성 (톨루엔 0.76, 크실렌, 0.87)을 나타내었다. 이 연구는 톨루엔과 크실렌이 총 휘발성 유기화합물의 좋은 지표를 사용될 있고, 톨루엔, 에틸벤젠, 크실렌 등 많은 휘발성 유기화합물의 발생원은 실외뿐 아니라 실내에도 있음을 나타내고 있다.>10)의 $[^{18}F]F_2$를 얻었다. 결론: $^{18}O(p,n)^{18}F$ 핵반응을 이용하여 친전자성 방사성동위원소 $[^{18}F]F_2$를 생산하였다. 표적 챔버는 알루미늄으로 제작하였으며 본 연구에서 연구된 $[^{18}F]F_2$가스는 친핵성 치환반응으로 방사성동위원소를 도입하기 어려운 다양한 방사성의 약품개발에 유용하게 이용될 수 있을 것이다.었으나 움직임 보정 후 영상을 이용하여 비교한 경우, 결합능 변화가 선조체 영역에서 국한되어 나타나며 그 유의성이 움직임 보정 전에 비하여 낮음을 알 수 있었다. 결론: 뇌활성화 과제 수행시에 동반되는 피험자의 머리 움직임에 의하여 도파민 유리가 과대평가되었으며 이는 이 연구에서 제안한 영상정합을 이용한 움직임 보정기법에 의해서 개선되었다. 답이 없는 문제, 문제 만들기, 일반화가 가능한 문제 등으로 보고, 수학적 창의성 중 특히 확산적 사고에 초점을 맞추어 개방형 문제가 확산적 사고의 요소인 유창성, 독창성, 유연성 등에 각각 어떤 영향을 미치는지 20주의 프로그램을 개발, 진행하여 그 효과를 검증하고자 한다. 개방형 문

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Measuring Effects of Senior Programs in Art Muiseums (미술관 시니어 프로그램의 효과 측정 방법 연구)

  • Kwon, Eun Yong
    • Trans-
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    • v.7
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    • pp.49-80
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    • 2019
  • As ageing society rapidly unfolds, it is becoming an even more important issue to secure wellbeing and happiness of senior citizens and the society as a whole. Growing talks on how culture and art positively affect the elderly led to more demands from the public on culture and art institutions to increase their social participations. Art museums too, as an art and cultural institution and a social education entity, are requested to play a bigger role in the effort to tackle the concerns derived from the ageing society. Korean art museums came up with senior programs since 2000, which makes it a relatively recent phenomenon. The consensus on the importance and needs of such programs has been around for a while in our society. However, effect measurement of these programs needs further research and discussion. This thesis examined the effect of senior programs using the Museum Wellbeing Measures Toolkit published in 2013. With the service quality research model, correlations were analyzed among program components, wellbeing effect, participant satisfaction and their willingness to re-enroll in order to produce a practical guidance on how to plan and operate the programs. To measure effect of senior programs and to analyze influencing factors would provide us with important data to prove the social responsibility and benefit art museums offer in our society. At the same time, such researches would contribute to enhancing the quality of current programs run by museums and give methodological suggestions on how to assess and improve senior programs.

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The Application of a Multiple Service Paradigm Assessment Format for Disability Program Proposals Submitted to the Korean Community Chest (공동모금 재정지원을 통해 본 장애인복지 분야의 서비스 패러다임 동향 분석)

  • Kim, Jung-Woo;Park, Kyung-Su
    • Korean Journal of Social Welfare
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    • v.57 no.1
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    • pp.147-167
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    • 2005
  • In the West, the model for provision of services to the disabled has shifted from a focus on the individual to that of a social model. This shift reflects a movement away from a materialist approach to one that is grounded in idealism. In the context of themultiple service paradigm movement this paper explores trends in the provision of social services to the disabled in Korea. In order to accomplish this task the writer conducted an analysis of Korean Community Chest proposals, existing legislation and legislative systems as well as the disability movement in Korea. Data was collected from the 2003 program proposals submitted to the Korea Community Chest. This data was classified using Priestly's Multiple Service Paradigm of Disability. The results suggest that the Korean Community Chest favored an individual idealist approach. There was only limited support given to proposals that reflect the social model approach and thus issues of accessibility, independent living and inclusion are given short shrift. This paper argues the need for a reversal of this trend through the Korean Community Chest supporting issues mentioned above and that the social model should be given greater attention by this funding body. Implications for practice using the multiple paradigm model are discussed.

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Developing the Design Guideline of Auditory User Interface for Digital Appliances (가전제품의 청각 사용자 인터페이스(AUI) 디자인을 위한 가이드라인 개발 사례)

  • Lee, Ju-Hwan;Jeon, Myoung-Hoon;Han, Kwang-Hee
    • Science of Emotion and Sensibility
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    • v.10 no.3
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    • pp.307-320
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    • 2007
  • In this study, we attempted to provide a distinctive cognitive, emotional 'Auditory User Interface (AUI) Design Guideline' according to home appliance groups and their functions. It is an effort to apply a new design method to practical affairs to overcome the limit of GUI centered appliance design and reflect user multimodal properties by presenting a guideline possible to generate auditory signals intuitively associable with the operational functions. The reason why this study is required is because of frequent instances given rise to annoyance as not systematic application of AUI, but arbitrary mapping. This study tried to provide a useful guideline of AUI in home appliances by extracting the relations with cognitive, emotional properties of a certain device or function induced by several properties of auditory signal and showing the empirical data on the basic mechanism of such relations.

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The Relationship between Local Fiscal Indices and Standardized Mortality rate (지역 재정지표와 표준화 사망률의 관련성)

  • Han, Ji-Yeon;Na, Bak-Ju;Lee, Moo-Sik;Hong, Jee-Young;Lim, Nam-Gu
    • Proceedings of the KAIS Fall Conference
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    • 2010.05b
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    • pp.1072-1076
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    • 2010
  • 본 지역 재정지표와 표준화사망률간의 관계에 대한 것으로, 연구대상지역은 1998년부터 2007년까지의 전국 232개 시 군 구이며 이를 5개 광역권과 4개 도시 종류에 따라 분류하였다. 지역 재정지표는 1인당 지방세부담액과 재정자립도, 재정자주도, 의존재원비율을 활용하였고, 지역 총사망률은1998년에서 2007년까지의 통계청 사망 원자료 상의 사망자수를 분자로, 주민등록인구를 분모로 직접 표준화법을 사용하여 연구대상 지역의 성 연령표준화사망률을 산출하였다. 자료의 분석은 SPSS 12.0K를 이용하여 상관분석, 일원배치분산분석(Tukey b 사후검정) 및 회귀분석을 실시하였다. 주요 결과로는 첫째, 재정지표와 표준화사망률간의 상관분석을 실시하여 연도별로 계수 값을 구한 결과 1인당 지방세부담액을 제외하고 재정자립도, 재정자주도, 의존재원비율 모두 남자, 여자, 전체 모두가 전 연도에 걸쳐 상관계수 값이 통계적으로 유의하였으며, 남자가 여자보다 높은 상관관계를 보였다. 둘째, 재정자립도, 재정자주도 각각을 표준화사망률과 단순 회귀분석을 실시한 결과, 표준화사망률 남자, 여자, 전체가 전 연도에서 통계적으로 유의하였고, 재정자립도와 재정자주도가 낮을수록 사망률이 높은 것으로 나타났다. 셋째, 광역권역, 도시 종류까지 고려한 재정지표의 다중회귀분석을 실시한 결과, 1인당 지방세부담액과 의존재원비율, 광역권역과 도시 종류에 따른 지역을 고려하고도 재정자주도의 효과는 전체사망과 남자, 여자, 전 연도에 걸쳐 모두 통계적으로 매우 유의하여 재정자주도가 높을수록 사망률이 낮은 것으로 나타났고 이런 경향은 여자보다 남자에서 더욱 강하게 나타났다. 넷째, 광역권별 분석의 경우, 충청권은 수도권에 비해서 표준화사망률에서 유의한 차이는 없었으며 호남권과 영남권은 전체 표준화사망률의 경우 전체 연도의 절반 이상에서 수도권에 비해서 통계적으로 유의하게 높았고, 남자와 여자에서는 이런 경향이 약해졌다. 강원 제주권은 전체 사망에서 수도권에 비해 전체 연도의 절반 이상이 유의하게 사망률이 낮았으며, 여자도 이와 비슷한 양상을 보여주었다. 다섯째, 도시 종류에 따른 분석에서 대도시에 비해 중소도시는 통계적으로 유의한 차이는 없었으나, 전 연도에 걸쳐 도농통합도시와 군지역은 대도시에 비해 통계적으로 사망률이 높았다. 여섯째, 전 연도에 걸쳐 의존재원비율이 높아질수록 사망률이 유의하게 높아졌다. 이는 남자, 여자 모두에서 유사하게 나타났다. 마지막으로 연도별 분석 이후 1998년에서 2007년 전체 다중 회귀분석을 실시한 결과 전체 사망과 여자의 경우 1인당 지방세부담액을 제외한 모든 변수에서 통계적으로 유의하였다. 지역의 재정력이 성 연령 표준화사망률에 영향을 미치는 것으로 파악되었는데 이를 단서로 지역의 건강 격차가 발생하는 원인과 기전을 밝히기 위해 향후 보다 면밀한 후속 연구가 이뤄져야 하겠고 지역 간 건강 격차를 완화하기 위한 여러 방법론적 고찰 안에 지역간 재정력의 격차를 완화하려는 정책적인 접근도 필요할 것으로 사료된다.

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Design and Implementation of Co-Verification Environments based-on SystemVerilog & SystemC (SystemVerilog와 SystemC 기반의 통합검증환경 설계 및 구현)

  • You, Myoung-Keun;Song, Gi-Yong
    • Journal of the Institute of Convergence Signal Processing
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    • v.10 no.4
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    • pp.274-279
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    • 2009
  • The flow of a universal system-level design methodology consists of system specification, system-level hardware/software partitioning, co-design, co-verification using virtual or physical prototype, and system integration. In this paper, verification environments based-on SystemVerilog and SystemC, one is native-code co-verification environment which makes prompt functional verification possible and another is SystemVerilog layered testbench which makes clock-level verification possible, are implemented. In native-code co-verification, HW and SW parts of SoC are respectively designed with SystemVerilog and SystemC after HW/SW partitioning using SystemC, then the functional interaction between HW and SW parts is carried out as one simulation process. SystemVerilog layered testbench is a verification environment including corner case test of DUT through the randomly generated test-vector. We adopt SystemC to design a component of verification environment which has multiple inheritance, and we combine SystemC design unit with the SystemVerilog layered testbench using SystemVerilog DPI and ModelSim macro. As multiple inheritance is useful for creating class types that combine the properties of two or more class types, the design of verification environment adopting SystemC in this paper can increase the code reusability.

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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.

A Comparative Research on End-to-End Clinical Entity and Relation Extraction using Deep Neural Networks: Pipeline vs. Joint Models (심층 신경망을 활용한 진료 기록 문헌에서의 종단형 개체명 및 관계 추출 비교 연구 - 파이프라인 모델과 결합 모델을 중심으로 -)

  • Sung-Pil Choi
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.1
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    • pp.93-114
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    • 2023
  • Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

Online news-based stock price forecasting considering homogeneity in the industrial sector (산업군 내 동질성을 고려한 온라인 뉴스 기반 주가예측)

  • Seong, Nohyoon;Nam, Kihwan
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.1-19
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    • 2018
  • Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.