• Title/Summary/Keyword: World model approach

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Visual Tracking Using Monte Carlo Sampling and Background Subtraction (확률적 표본화와 배경 차분을 이용한 비디오 객체 추적)

  • Kim, Hyun-Cheol;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.5
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    • pp.16-22
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    • 2011
  • This paper presents the multi-object tracking approach using the background difference and particle filtering by monte carlo sampling. We apply particle filters based on probabilistic importance sampling to multi-object independently. We formulate the object observation model by the histogram distribution using color information and the object dynaminc model for the object motion information. Our approach does not increase computational complexity and derive stable performance. We implement the whole Bayesian maximum likelihood framework and describes robust methods coping with the real-world object tracking situation by the observation and transition model.

Mixed Integer Linear Programming Model to Determine the Optimal Levels of Technical Attributes in QFD under Multi-Segment Market (다수의 마켓 세그먼트 하에서 품질기능전개 시(時) 기술특성들의 최적 값을 결정하기 위한 혼합정수계획모형)

  • Yang, Jae Young;Yoo, Jaewook
    • Korean Management Science Review
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    • v.33 no.2
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    • pp.75-87
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    • 2016
  • Quality function deployment (QFD) is a widely adopted customer-oriented product development methodology by analyzing customer requirements. It is a main activity in QFD planning process to determine the optimal values of the technical attributes (TAs) so as to achieve the customer requirements (CRs) from the House of Quality (HoQ). In most of the previous research, all the TAs in QFD are assumed to have either continuous or discrete values. In the real world applications, the continuous TAs and the discrete TAs are often mixed in QFD. In this paper, a mixed integer linear programming model is formulated to obtain the optimal values for the continuous TAs and the discrete TAs in QFD planning as well as Branch and Bound (B and B) algorithm is proposed as the solution approach. Finally, the proposed model and solution approach are illustrated with an office chair under multi-segment market, and the sensitivity analysis is performed to study how the proposed model and its solutions respond to the variation for the two elements which are budget and CRs' weights.

Transformation Approach to Model Online Gaming Traffic

  • Shin, Kwang-Sik;Kim, Jin-Hyuk;Sohn, Kang-Min;Park, Chang-Joon;Choi, Sang-Bang
    • ETRI Journal
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    • v.33 no.2
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    • pp.219-229
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    • 2011
  • In this paper, we propose a transformation scheme used to analyze online gaming traffic properties and develop a traffic model. We analyze the packet size and the inter departure time distributions of a popular first-person shooter game (Left 4 Dead) and a massively multiplayer online role-playing game (World of Warcraft) in order to compare them to the existing scheme. Recent online gaming traffic is erratically distributed, so it is very difficult to analyze. Therefore, our research focuses on a transformation scheme to obtain new smooth patterns from a messy dataset. It extracts relatively heavy-weighted density data and then transforms them into a corresponding dataset domain to obtain a simplified graph. We compare the analytical model histogram, the chi-square statistic, and the quantile-quantile plot of the proposed scheme to an existing scheme. The results show that the proposed scheme demonstrates a good fit in all parts. The chi-square statistic of our scheme for the Left 4 Dead packet size distribution is less than one ninth of the existing one when dealing with erratic traffic.

A Prototype Implementation for 3D Animated Anaglyph Rendering of Multi-typed Urban Features using Standard OpenGL API

  • Lee, Ki-Won
    • Korean Journal of Remote Sensing
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    • v.23 no.5
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    • pp.401-408
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    • 2007
  • Animated anaglyph is the most cost-effective method for 3D stereo visualization of virtual or actual 3D geo-based data model. Unlike 3D anaglyph scene generation using paired epipolar images, the main data sets of this study is the multi-typed 3D feature model containing 3D shaped objects, DEM and satellite imagery. For this purpose, a prototype implementation for 3D animated anaglyph using OpenGL API is carried out, and virtual 3D feature modeling is performed to demonstrate the applicability of this anaglyph approach. Although 3D features are not real objects in this stage, these can be substituted with actual 3D feature model with full texture images along all facades. Currently, it is regarded as the special viewing effect within 3D GIS application domains, because just stereo 3D viewing is a part of lots of GIS functionalities or remote sensing image processing modules. Animated anaglyph process can be linked with real-time manipulation process of 3D feature model and its database attributes in real world problem. As well, this approach of feature-based 3D animated anaglyph scheme is a bridging technology to further image-based 3D animated anaglyph rendering system, portable mobile 3D stereo viewing system or auto-stereo viewing system without glasses for multi-viewers.

Predicting Session Conversion on E-commerce: A Deep Learning-based Multimodal Fusion Approach

  • Minsu Kim;Woosik Shin;SeongBeom Kim;Hee-Woong Kim
    • Asia pacific journal of information systems
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    • v.33 no.3
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    • pp.737-767
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    • 2023
  • With the availability of big customer data and advances in machine learning techniques, the prediction of customer behavior at the session-level has attracted considerable attention from marketing practitioners and scholars. This study aims to predict customer purchase conversion at the session-level by employing customer profile, transaction, and clickstream data. For this purpose, we develop a multimodal deep learning fusion model with dynamic and static features (i.e., DS-fusion). Specifically, we base page views within focal visist and recency, frequency, monetary value, and clumpiness (RFMC) for dynamic and static features, respectively, to comprehensively capture customer characteristics for buying behaviors. Our model with deep learning architectures combines these features for conversion prediction. We validate the proposed model using real-world e-commerce data. The experimental results reveal that our model outperforms unimodal classifiers with each feature and the classical machine learning models with dynamic and static features, including random forest and logistic regression. In this regard, this study sheds light on the promise of the machine learning approach with the complementary method for different modalities in predicting customer behaviors.

A Logical Design Methodology for Relational Databases Using the MAO (Multiple Aspects-based Object) Model (MAO 모델을 사용한 관계 데이타베이스의 논리적 설계방법론)

  • Cho, Dong-Young;Baik, Doo-Kwon;Hwang, Chong-Sun
    • Journal of the Korean Operations Research and Management Science Society
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    • v.16 no.2
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    • pp.49-64
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    • 1991
  • In this paper, we present a stepwise design methodology for relational databases using a new conceptual data model, the MAO(Multiple Aspects-based Object) model. Our methodology consists two steps : first, data requirements are conceptualized using the MAO model with concepts such as objects types and aspect types : second, the MAO model is transformed into the third normal form inn the relational model supported by commercial DBMs. A top-down approach is used for the MAO modelling in the first, step, and the transformation process in the second step can be automated. Our methodology supports easier and more database design of real world than other methodologies using existing data models.

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Causal model analysis between quantity and quality for deriving ranking model of Online reviews (온라인리뷰의 랭킹모델링을 위한 양과 질의 인과모형 분석)

  • Lee, Changyong;Kim, Keunhyung
    • The Journal of Information Systems
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    • v.28 no.1
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    • pp.1-16
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    • 2019
  • Purpose The purpose of this study is to analyze causal relationship between quantity and quality for deriving ranking model of Online reviews. Thus, we propose implications for deriving the ranking model for retrieving Online reviews more effectively. Design/methodology/approach We collected Online review from Tripadvisor web sites which might be a kind of world-famous tourism web sites. We transformed the natural text reviews to quantified data which consists of quantified positive opinions, quantified negative opinions, quantified modification opinions, reviews lengths and grade scores by using opinion mining technologies in R package. We executed corelation and regression analysis about the data. Findings According to the empirical analysis result, this study confirmed that the review length influenced positive opinion, negative opinion and modification opinion. We also confirmed that negative opinion and modification opinion influenced the grade score.

Application of An Ecological Engineering Approach in Evaluating Protected Area at Local Scales (생태계 보호지역 평가에서 생태공학 도입과 활용)

  • Koo, Kyung Ah
    • Journal of Environmental Impact Assessment
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    • v.29 no.2
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    • pp.144-155
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    • 2020
  • This research developed an approach to identify ecologically important areas at local scales and explained how the results of this approach could contribute to extend the protected areas in the Republic of Korea (ROK). While most developed countries have considered various biotic and abiotic factors, ecological processes, migration routes, habitat connectivity, ecosystem services, and etc. to determine the protected areas, ROK has considered a few factors focusing on biodiversity, landscape, and the habitats of endangered organisms. However, for sustainable management of our nature, we need comprehensive understanding of various ecosystem factors and interactions among them at local scales in designating protected areas. Forthis, we developed a conceptual model based on the ecological engineering approach and then explained how the results of this approach could contribute to extend the protected areas. In particular, we considered future land-use and climate change in determining the priority areas for novel protected areas. Our research suggested an effective methodology 1) to include various ecosystem factors and 2) to consider future environmental changes as well as current environmental conditions in finding the ecologically important areas and prioritizing these areas. However, our approach has limitations on the real-world applications due to the lack of fundamental information and data on our ecosystems. To improve the effectiveness of our approach in the real-world applications, we need various long-term ecological research results, environmental and ecological monitoring data, and both current and future spatial environmental data.

Design Evaluation of Portable Electronic Products Using AR-Based Interaction and Simulation (증강현실 기반 상호작용과 시뮬레이션을 이용한 휴대용 전자제품의 설계품평)

  • Park, Hyung-Jun;Moon, Hee-Cheol
    • Korean Journal of Computational Design and Engineering
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    • v.13 no.3
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    • pp.209-216
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    • 2008
  • This paper presents a novel approach to design evaluation of portable consumer electronic (PCE) products using augmented reality (AR) based tangible interaction and functional behavior simulation. In the approach, the realistic visualization is acquired by overlaying the rendered image of a PCE product on the real world environment in real-time using computer vision based augmented reality. For tangible user interaction in an AR environment, the user creates input events by touching specified regions of the product-type tangible object with the pointer-type tangible object. For functional behavior simulation, we adopt state transition methodology to capture the functional behavior of the product into a markup language-based information model, and build a finite state machine (FSM) to controls the transition between states of the product based on the information model. The FSM is combined with AR-based tangible objects whose operation in the AR environment facilitates the realistic visualization and functional simulation of the product, and thus realizes faster product design and development. Based on the proposed approach, a product design evaluation system has been developed and applied for the design evaluation of various PCE products with highly encouraging feedbacks from users.

A Study of the Factors Influencing on the Intention to Use Fintech (핀테크 사용의도에 영향을 미치는 요인에 관한 연구)

  • Kim, Eun Jung;Kim, Joo Hyun;Kim, Jong Weon
    • The Journal of Information Systems
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    • v.26 no.1
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    • pp.75-91
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    • 2017
  • Purpose Fintech has been recently drawing extensive attention all over the world as the innovative trend that will change the future of the global financial industry. However, fintech has been mostly focusing on the payment service in the embryonic stage in Korea. This paper will investigate the approach to increase the intention to use for those who do not use fintech at present. Design/methodology/approach This paper empirically analyzes the impact of innovation of users and the perceived ease-of-use and security on the intention to use through the perceived usefulness and confidence. The 255 survey responses were used to verify research hypotheses through covariate structural equation model. Findings According to the analysis results, it was found that innovation had a significant impact on the perceived usefulness, but had no significant impact on confidence. The perceived usefulness had a significant impact on perceived usefulness and confidence. Moreover, the perceived usefulness and confidence had a significant impact on the intention to use. Meanwhile, it was identified that the security perceived by those who do not use fintech had a negative impact on perceived usefulness, confidence, and intention to use related to fintech. Accordingly, fintech service providers need to determine an approach to help customers to have a positive perception on the security of fintech.