• Title/Summary/Keyword: Intelligent Data Analysis

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A comparison analysis of factors to affect pedestrian volumes by land-use type using Seoul Pedestrian Survey data (토지이용유형별 보행량 영향 요인 비교·분석 - 서울시 유동인구 조사자료를 바탕으로)

  • Jang, Jin-Young;Choi, Sung-Taek;Lee, Hyang-Sook;Kim, Su-Jae;Choo, Sang-Ho
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.14 no.2
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    • pp.39-53
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    • 2015
  • The paper analyzes factors to affect pedestrian volumes by land-use type using 2012 Seoul Pedestrian Survey. First of all, five groups were classified based on land-use types around survey points such as residential, commercial, industrial and green uses, using k-average cluster analysis. Then, differences in average pedestrian volumes by group were compared for a day and time of day. In addition, multiple regression analysis was employed to identify factors to affect pedestrian volumes, considering physical features, land use types, public transportation accessibility, and socio-economic indices as independent variables by spatial hierarchy. Model results show that the walkway width positively influenced on pedestrian volumes for all groups, whereas other variables differently affected by group. Our results can be used as basic data for establishing polices with respect to pedestrian road design and improvement as well as estimating pedestrian demand by land-use type.

Estimation of Drag Factors Between Roadway Surface and Human Body (인체와 노면간의 마찰계수 추정에 관한 연구)

  • Kim, Min-Tae;Lee, Sang-Soo;Lee, Chul-Ki
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.6
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    • pp.54-62
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    • 2010
  • The scientific analysis of car-pedestrian accidents is not an easy task because of the characteristic of the accidents itself. Since the analysis involved human being, there were few experimental data that could be used for the analysis. The coefficient of friction of human body was the one of crucial data for accident analysis, but no field experiment report was available for various roadway conditions. This study intends to measure the coefficient of friction of human body through field studies. Results showed that the coefficient of friction of human body for dry asphalt pavement conditions was 0.59~0.62, and for dry concrete pavement conditions was 0.59~0.61. In addition, the coefficients for wet asphalt pavement and for wet concrete pavement conditions were 0.56~0.59 and 0.51~0.54 respectively, indicating 5.0% and 8.3% reduction compared to the dry conditions. The deduced coefficients were validated using the simulation program. It has been confirmed that the experiment values were close to the simulation results.

A Study on Selected Station Analysis of AFC-Based Integrated Transit Network - Focused on Subway Transfer Stations in Seoul Metropolitan Area - (AFC-기반 통합대중교통 네트워크의 Selected Station Analysis (SSA) 연구 - 수도권 지하철 환승역사를 중심으로 -)

  • Lee, Mee Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.17 no.6
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    • pp.67-83
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    • 2018
  • This research is motivated by the question, "Where, when, and through what mode does an individual passenger moving within a subway station use to travel from starting to final destinations ?" To answer this, the stations passed by the individual passenger, the path taken, and modes used need to be known beforehand. In the metropolitan integrated public transportation fare system, Automated Fare Collection System(AFC) can be a source of information on transit modes, stations, and paths of individual passengers. AFC calculates a fare for the passenger based on travel data such as boarding and alighting stations, time, and mode used. In this research, an Selected Station Analysis(SSA) method, in which AFC data is used to observe passenger movement in the metropolitan public transportation subway station from the perspective of subway transfer stations, is proposed. SSA subdivides individual passenger movement in transfer stations and analyzes initial station/time and final destination station/time information using the trip chain perspective.

A Trend Analysis of Advanced Fusion Technology in the Construction Industry (건설 산업에서의 첨단융합기술 동향 분석에 관한 연구)

  • Son, Hyo-Joo;Kim, Tae-Woo;Kim, Chang-Wan;Kim, Hyoung-Kwan;Han, Seung-H.;Kim, Sang-Bum;Kim, Mun-Kyum
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2007.04a
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    • pp.188-192
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    • 2007
  • This paper presents a current perspective on advanced fusion research trends in the construction industry as reflected in the proceedings of International Symposium on Automation and Robotics in Construction (ISARC) which has focused on advanced fusion technology in last decades. The paper reports the results of a 7-year analysis of papers between 2000 and 2006. The analysis focused on such data as research topics of the proceedings. The paper summarizes the data extracted from the paper and uses it to analyze advanced fusion research trends. The research result shows that the top research topics in advanced fusion research areas are construction robots and automation and intelligent construction management. The research also found that research related to advanced fusion technology is increasing throughout the world and topics are changing as current needs change.

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A Study on Analysis and Design of Metadata Model for Intelligent e-Learning System (지능형 학습 시스템을 위한 메타데이터 모형 분석 및 설계 연구)

  • Jang, Jin-Cheul;Hong, Seong-Yong;Yi, Mun-Yang
    • 한국정보교육학회:학술대회논문집
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    • 2011.01a
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    • pp.211-217
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    • 2011
  • Recent IT (information technology) environmental changes, such as emerging social network services or increasing user participation in multimedia environment, have made it necessary for e-learning systems to undergo changes in various ways. Metadata is an agreement for interoperability between different systems. The standardization of metadata for e-learning system has been driven by some domestic and international organizations, but applying diverse environmental changes into the design of e-learning metadata is in dire need. In this paper, we present a methodology for the analysis and design of modeling e-learning metadata and elicit the design requirements, on the basis of the metadata standard KEM 3.0, about the elements that are expected to be needed in future e-learning systems. Based on the requirements from the analysis, we present the three-layer model for classifying the requirements by the importance of metadata elements per Kana Model. An intelligent e-learning system is to be developed based on the proposed modeling design, which we hope to influence the development of an international standard in the future.

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Global Technical Knowledge Flow Analysis in Intelligent Information Technology : Focusing on South Korea (지능정보기술 분야에서의 글로벌 기술 지식 경쟁력 분석 : 한국을 중심으로)

  • Kwak, Gihyun;Yoon, Jungsub
    • The Journal of the Korea Contents Association
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    • v.21 no.1
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    • pp.24-38
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    • 2021
  • This study aims to measure Korea's global competitiveness in intelligent information technology, which is the core technology of the 4th industrial revolution. For analysis, we collect patents of each field and prior patents cited by them, which are applied at the U.S. Patent Office (USPTO) between 2010 and 2018 from PATSTAT Online. A global knowledge transfer network was established by grouping citing- and cited-relationships at a national level. The in-degree centrality is used to evaluate technology acceptance, which indicates the process of absorbing existing technological knowledge to create new knowledge in each field. Second, to evaluate the impact of existing technological knowledge on the creation of new one, the out-degree centrality is investigated. Third, we apply the PageRank algorithm to qualitatively and quantitatively investigate the importance of the relationships between countries. As a result, it is confirmed through all the indicators that the AI sector is currently the least competitive.

Resonance analysis of cantilever porous graphene platelet reinforced pipe under external load

  • Huang, Qinghua;Yu, Xinping;Lv, Jun;Zhou, Jilie;Elvenia, Marischa Ray
    • Steel and Composite Structures
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    • v.45 no.3
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    • pp.409-423
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    • 2022
  • Nowadays, there is a high demand for great structural implementation and multifunctionality with excellent mechanical properties. The porous structures reinforced by graphene platelets (GPLs) having valuable properties, such as heat resistance, lightweight, and excellent energy absorption, have been considerably used in different engineering implementations. However, stiffness of porous structures reduces significantly, due to the internal cavities, by adding GPLs into porous medium, effective mechanical properties of the porous structure considerably enhance. This paper is relating to vibration analysis of fluidconveying cantilever porous graphene platelet reinforced (GPLR) pipe with fractional viscoelastic model resting on foundations. A dynamical model of cantilever porous GPLR pipes conveying fluid and resting on a foundation is proposed, and the vibration, natural frequencies and primary resonant of such a system are explored. The pipe body is considered to be composed of GPLR viscoelastic polymeric pipe with porosity in which Halpin-Tsai scheme in conjunction with the fractional viscoelastic model is used to govern the construction relation of nanocomposite pipe. Three different porosity distributions through the pipe thickness are introduced. The harmonic concentrated force is also applied to the pipe and the excitation frequency is close to the first natural frequency. The governing equation for transverse motions of the pipe is derived by the Hamilton principle and then discretized by the Galerkin procedure. In order to obtain the frequency-response equation, the differential equation is solved with the assumption of small displacement, damping coefficient, and excitation amplitude by the multiple scale method. A parametric sensitivity analysis is carried out to reveal the influence of different parameters, such as nanocomposite pipe properties, fluid velocity and nonlinear viscoelastic foundation coefficients, on the primary resonance and linear natural frequency. Results indicate that the GPLs weight fraction porosity coefficient, fractional derivative order and the retardation time have substantial influences on the dynamic response of the system.

Financial Forecasting System using Data Editing Technique and Case-based Reasoning (자료편집기법과 사례기반추론을 이용한 재무예측시스템)

  • Kim, Gyeong-Jae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.283-286
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    • 2007
  • This paper proposes a genetic algorithm (GA) approach to instance selection in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in complex problem solving. Nonetheless, compared to other machine learning techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for instance selection in CBR.

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Tracking of Multiple Vehicles Using Occlusion Segmentation Based on Spatio-Temporal Association

  • Lim, Jun-Sik;Kim, Soo-Hyung;Lee, Guee-Sang;Yang, Hyung-Jeong;Na, In-Seop
    • International Journal of Contents
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    • v.7 no.4
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    • pp.19-23
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    • 2011
  • This paper proposes a segmentation method for overlapped vehicles based on analysis of the vehicle location and the spatiotemporal association information. This method can be used in an intelligent transport system. In the proposed method, occlusion is detected by analyzing the association information based on a vehicle's location in continuous images, and occlusion segmentation is carried out by using the vehicle information prior to occlusion. In addition, the size variations of the vehicle to which association tracking is applied can be anticipated by learning the variations according to the overlapped vehicles' movements. To assess the performance of the suggested method, image data collected from CCTVs recording traffic information is used, and average success rate of occlusion segmentation is 96.9%.

EEG Feature Classification Based on Grip Strength for BCI Applications

  • Kim, Dong-Eun;Yu, Je-Hun;Sim, Kwee-Bo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.4
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    • pp.277-282
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    • 2015
  • Braincomputer interface (BCI) technology is making advances in the field of humancomputer interaction (HCI). To improve the BCI technology, we study the changes in the electroencephalogram (EEG) signals for six levels of grip strength: 10%, 20%, 40%, 50%, 70%, and 80% of the maximum voluntary contraction (MVC). The measured EEG data are categorized into three classes: Weak, Medium, and Strong. Features are then extracted using power spectrum analysis and multiclass-common spatial pattern (multiclass-CSP). Feature datasets are classified using a support vector machine (SVM). The accuracy rate is higher for the Strong class than the other classes.