• Title/Summary/Keyword: In-hand modeling

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Parametric Analysis and Design Engine for Tall Building Structures

  • Ho, Goman;Liu, Peng;Liu, Michael
    • International Journal of High-Rise Buildings
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    • v.1 no.1
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    • pp.53-59
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    • 2012
  • With the rise in CPU power and the generalization and popularity of computers, engineering practice also changed from hand calculations to 3D computer models, from elastic linear analysis to 3D nonlinear static analysis and 3D nonlinear transient dynamic analysis. Thanks to holistic design approach and current trends in freeform and contemporary architecture, BIM concept is no longer a dream but also a reality. BIM is not just providing a media for better co-ordination but also to shorten the round-the-clock time in updating models to match with other professional disciplines. With the parametric modeling tools, structural information is also linked with BIM system and quickly produces analysis and design results from checking to fabrication. This paper presents a new framework which not just linked the BIM system by means of parametric mean but also create and produce connection FE model and fabrication drawings etc. This framework will facilitate structural engineers to produce well co-ordinate, optimized and safe structures.

Comparison of Alternative knowledge Acquisition Methods for Allergic Rhinitis

  • Chae, Young-Moon;Chung, Seung-Kyu;Suh, Jae-Gwon;Ho, Seung-Hee;Park, In-Yong
    • Journal of Intelligence and Information Systems
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    • v.1 no.1
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    • pp.91-109
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    • 1995
  • This paper compared four knowledge acquisition methods (namely, neural network, case-based reasoning, discriminant analysis, and covariance structure modeling) for allergic rhinitis. The data were collected from 444 patients with suspected allergic rhinitis who visited the Otorlaryngology Deduring 1991-1993. Among four knowledge acquisition methods, the discriminant model had the best overall diagnostic capability (78%) and the neural network had slightly lower rate(76%). This may be explained by the fact that neural network is essentially non-linear discriminant model. The discriminant model was also most accurate in predicting allergic rhinitis (88%). On the other hand, the CSM had the lowest overall accuracy rate (44%) perhaps due to smaller input data set. However, it was most accuate in predicting non-allergic rhinitis (82%).

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Empirical Analysis on the Influence of Service Quality of Leisure Food E-Commerce in China on Consumer Satisfaction Degree (중국 레저푸드 전자상거래의 서비스 품질이 소비자 만족도에 미치는 영향에 관한 실증분석)

  • Liu, Zi-Yang;Meng, Jia
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2019.07a
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    • pp.407-408
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    • 2019
  • This thesis determines the research framework and scale design of leisure food E-Commerce consumer satisfaction degree by referring to previous theoretical model of customer satisfaction degree, the universal satisfaction evaluation index system, and the characteristics of leisure food E-Commerce in China. In this research, consumers who have bought leisure food online are taken as the research object, data are collected by questionnaires, and exploratory factor method is used to screen valid sample data. Through the Empirical Analysis which includes Descriptive Statistical Analysis, Reliability and Validity Analysis and Structural Equation Modeling, it is concluded that website design, logistics delivery service, commodity quality, and after-sales service are the main service quality on which the Leisure food E-Commerce enterprises should take focus. The service quality has significant positive influences on satisfaction degree. On the other hand consumer satisfaction has a significant positive influence on customer loyalty, which will create more earnings for the Leisure food E-Commerce enterprises.

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Virtual Space Calibration for Laser Vision Sensor Using Circular Jig (원형 지그를 이용한 레이저-비젼 센서의 가상 공간 교정에 관한 연구)

  • 김진대;조영식;이재원
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.12
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    • pp.73-79
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    • 2003
  • Recently, the tole-robot operations to an unstructured environment have been widely researched. The human's interaction with the tole-robot system can be used to improve robot operation and performance for an unknown environment. The exact modeling based on real environment is fundamental and important process for this interaction. In this paper, we propose an extrinsic parameter calibration and data augmentation method that only uses a circular jig in the hand-eye laser virtual environment. Compared to other methods, easier estimation and overlay can be done by this algorithm. Experimental results using synthetic graphic demonstrate the usefulness of the proposed algorithm.

Application of Object Modeling and AR for Forest Field Investigation (산림 현장조사를 위한 객체 모델링과 AR의 활용)

  • Park, Joon-Kyu;Oh, Myoung-Kwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.411-416
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    • 2020
  • Field investigations of forests are carried out by writing measured data by hand, and it is a hassle to reorganize the results after a field survey. In this study, a method using object modeling and augmented reality (AR) was applied in a test forest to increase the efficiency of a field investigations. Using a 3D laser scanner, data on were acquired 387 trees within an area of 1 ha at the study site. The coordinates, height, and diameter were calculated through object extraction and modeling of a tree. The proposed can reduce the time required to acquire data in the field and can be used as basic data for building related systems. In addition, the modeling results of trees and a survey using GNSS and AR techniques can be used check coordinates, labor, and attribute information, such as the chest height diameter of the trees being surveyed in the field. The shortcomings of the survey method could be improved. In the future, the method could greatly improve the efficiency of tree surveys and monitoring by reducing the manpower and time required for field surveys.

Dynamic Bayesian Network based Two-Hand Gesture Recognition (동적 베이스망 기반의 양손 제스처 인식)

  • Suk, Heung-Il;Sin, Bong-Kee
    • Journal of KIISE:Software and Applications
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    • v.35 no.4
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    • pp.265-279
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    • 2008
  • The idea of using hand gestures for human-computer interaction is not new and has been studied intensively during the last dorado with a significant amount of qualitative progress that, however, has been short of our expectations. This paper describes a dynamic Bayesian network or DBN based approach to both two-hand gestures and one-hand gestures. Unlike wired glove-based approaches, the success of camera-based methods depends greatly on the image processing and feature extraction results. So the proposed method of DBN-based inference is preceded by fail-safe steps of skin extraction and modeling, and motion tracking. Then a new gesture recognition model for a set of both one-hand and two-hand gestures is proposed based on the dynamic Bayesian network framework which makes it easy to represent the relationship among features and incorporate new information to a model. In an experiment with ten isolated gestures, we obtained the recognition rate upwards of 99.59% with cross validation. The proposed model and the related approach are believed to have a strong potential for successful applications to other related problems such as sign languages.

A study on development dispatcher's training simulator in the operation of power system (훈련용시뮤레이터 현황과 향후계획)

  • Kim, Mun-Gi;Jeong, Chang-Deok
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.515-517
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    • 1993
  • Dispatcher's Training simulation function are network analysis, power system modeling, supervisory control, and system security assessment. This function provides hand-on training for power dispatchers for operation of the nation control center in the future, it needs interface between simulator and expert system. This paper introduces DTS function which is adopted in the Central Load Dispatching Office.

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Prediction of Prosodic Boundary Strength by means of Three POS(Part of Speech) sets (품사셋에 의한 운율경계강도의 예측)

  • Eom Ki-Wan;Kim Jin-Yeong;Kim Seon-Mi;Lee Hyeon-Bok
    • MALSORI
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    • no.35_36
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    • pp.145-155
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    • 1998
  • This study intended to determine the most appropriate POS(Part of Speech) sets for predicting prosodic boundary strength efficiently. We used 3-level POB bets which Kim(1997), one of the authors, has devised. Three POS sets differ from each other according to how much grammatical information they have: the first set has maximal syntactic and morphological information which possibly affects prosodic phrasing, and the third set has minimal one. We hand-labelled 150 sentences using each of three POS sets and conducted perception test. Based on the results of the test, stochastic language modeling method was used to predict prosodic boundary strength. The results showed that the use of each POS set led to not too much different efficiency in the prediction, but the second set was a little more efficient than the other two. As far as the complexity in stochastic language modeling is concerned, however, the third set may be also preferable.

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Application Software Modeling and Integration Methodology using AUTOSAR-ready Light Software Architecture (AUTOSAR 대응 경량화 소프트웨어 아키텍처를 이용한 어플리케이션 소프트웨어 모델링 및 통합 방법)

  • Park, In-Seok;Lee, Woo-Taik;SunWoo, Myoung-Ho
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.6
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    • pp.117-125
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    • 2012
  • This paper describes a model-based software development methodology for AUTOSAR-ready light software architecture(AUTOSAR-Lite). The proposed methodology briefly represents an application software modeling technique using Matlab/Simulink. Using the proposed technique, application software architecture elements (e.g. software components, runnables, and interfaces) and functional behaviors can be designed in a single modeling environment. From the designed model, the codes of application software is automatically generated using Real-Time Workshop Embedded Coder. The generated application software is easily integrated with hand-coded basic software using the proposed method. In order to evaluate the proposed methodology, a diesel engine management system for a passenger car was employed as a case study. Based on the methodology, 8 atomic software components and 52 runnables are successfully developed, and they are evaluated by engine experiments. From this case study, AUTOSAR compatible model-based application software was successfully developed, and the effectiveness of the proposed methodology was evaluated.

Changes in air pollutant emissions from road vehicles due to autonomous driving technology: A conceptual modeling approach

  • Hwang, Ha;Song, Chang-Keun
    • Environmental Engineering Research
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    • v.25 no.3
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    • pp.366-373
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    • 2020
  • The autonomous vehicles (AVs) could make a positive or negative impact on reducing mobile emissions. This study investigated the changes of mobile emissions that could be caused by large-scale adoption of AVs. The factors of road capacity increase and speed limit increase impacts were simulated using a conceptual modeling approach that combines a hypothetical speed-emission function and a traffic demand model using a virtual transportation network. The simulation results show that road capacity increase impact is significant in decreasing mobile emissions until the market share of AVs is less than 80%. If the road capacity increases by 100%, the mobile emissions will decrease by about 30%. On the other hand, driving speed limit increase impact is significant in increasing mobile emissions, and the environmentally desirable speed limit was found at around 95 km/h. If the speed limit increases to 140 km/h, the mobile emissions will increase by about 25%. This is because some vehicles begin to bypass the congested routes at high speeds as speed limit increases. Based on the simulation results, it is clear that the vehicle platooning technology implemented at reasonable speed limit is one of the AV technologies that are encouraging from the environmental point of view.