• Title/Summary/Keyword: independent object

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Challenging a Single-Factor Analysis of Case Drop in Korean

  • Chung, Eun Seon
    • Language and Information
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    • v.19 no.1
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    • pp.1-18
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    • 2015
  • Korean marks case for subjects and objects, but it is well known that case-markers can be dropped in certain contexts. Kwon and Zribi-Hertz (2008) establishes the phenomenon of Korean case drop on a single factor of f(ocus)-structure visibility and claims that both subject and object case drop can fall under a single linguistic generalization of information structure. However, the supporting data is not empirically substantiated and the tenability of the f-structure analysis is still under question. In this paper, an experiment was conducted to show that the specific claims of Kwon and Zribi-Hertz's analysis that places exclusive importance on information structure cannot be adequately supported by empirical evidence. In addition, the present study examines H. Lee's (2006a, 2006c) multi-factor analysis of object case drop and investigates whether this approach can subsume both subject and object case drop under a unified analysis. The present findings indicate that the multi-factor analysis that involves the interaction of independent factors (Focus, Animacy, and Definiteness) is also compatible with subject case drop, and that judgments on case drop are not categorical but form gradient statistical preferences.

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A PC-Based Open Robot Control System : PC-ORC (PC에 기반을 둔 개방형 로봇제어시스템 : PC-ORC)

  • 김점구;최경현;홍금식
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.5
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    • pp.415-425
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    • 2000
  • An open architecture manufacturing strategy intends to integrate manufacturing components on a single platform so that a particular component can be easily added and/or replaced. Therefore, the control scheme based upon the open architecture concept is hardware-independent. In this paper, a modular and object oriented approach for a PC-based open robot control system is investigated. A standard reference model for robot systems, which consists of three modules; hardware module, operating system module, and application software module, is first proposed. Then, a PC-based Open Robot Controller(PC-ORC), which can reconfigure robot control systems in various production environments, is developed. The PC-ORC is built upon the object-oriented method, and allows an easy implementation and modification of various modules. The PC-ORC consists of basic softwares, application objects, and additional hardware device on the PC Platform. The application objects are: sequencer, computation unit, servo control, ancillary equipment, external sensor control, and so on. In order to demonstrate the applicability of the PC-ORC, the proposed PC-ORC configuration is applied to an industrial SCARA robot system.

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Object-Based Fault Diagnosis Expert System (객체 기반 고장 진단 전문가 시스템)

  • Kwon, Kyung-Bong;Kim, Jung-Nyun;Baek, Young-Sik
    • Proceedings of the KIEE Conference
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    • 1997.11a
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    • pp.190-192
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    • 1997
  • In this paper we developed an object-based expert system for electric power system fault diagnosis. The object corresponds to a hardware or event in real world and they are independent each other. The expert system is designed to estimate the fault sections and identify the false operation, nonoperation of protective devices. The expert system was developed using C++ language in pentium PC. We applied the expert system in various sample systems and showed that making up a knowledge base is easier and diagnosis was done in a approximately real time.

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Formal Specification Methods for Distributed Object-Oriented Systems (분산 객체지향 시스템을 위한 정형 명세 방법에 관한 연구)

  • Lee, Sang-Beom
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.5
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    • pp.1426-1433
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    • 2000
  • As distributed computing systems become popular, many modeling techniques and methods have been developed in specify the specification formally and verify the distributed/concurrent sytems. In spite of importance of communication in distributed object-oriented systems, specifying of communication method generally has not been emphasized in the design phase. One reason is due to the system designer misunderstanding, that is, a specification needs to be independent on the implementation. However, since defining communication pattern indistributed object-oriented systems is more serious than the required message passing method in the design phase. specifying the communication pattern is necessary instead of postponing until the implementation. In this paper, two formal specification techniques, temporal logic method and Petri nets method, for the communication in distributed systems are discussed. One is based on the temporal logic, which specifies the different patterns of primitive predicates. This method enable to define the underlying mechanism which can be interpreted as constraints. The Petri net method helps to specify the dynamic behavior of communicational patterns using the properties of Petri nets.

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Extended Kalman Filter Approach to Dynamic Electrical Impedance Tomography with Internal Electrodes

  • S.I. Kang;Kim, K.Y.;Kim, H.C.;Kim, M.C.;Kim, S.;Lee, H.J.;Lee, Y.J.;W.C. Cho
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.39.1-39
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    • 2001
  • Impedance tomography (EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents through the electrodes and induced voltages on the surface of the object. We describe a dynamic EIT imaging technique for the case where the resistivity distribution inside the object changes rapidly within the time taken to acquire a full set of independent measurement data, In doing so, the inverse problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. In particular, additional electrodes are attached to the known internal structure of the object ...

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Expert system for segmentation of 2.5-D image

  • Ahn, Hongyoung
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.376-381
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    • 1992
  • This paper presents an expert system for the segmentation of a 2.5-D image. The results of two segmentation approaches, edge-based and region-based, are combined to produce a consistent and reliable segmentation. Rich information embedded in the 2.5-D image is utilized to obtain a view independent surface patch description of the image, which can facilitate object recognition considerably.

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Feature Extraction of Concepts by Independent Component Analysis

  • Chagnaa, Altangerel;Ock, Cheol-Young;Lee, Chang-Beom;Jaimai, Purev
    • Journal of Information Processing Systems
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    • v.3 no.1
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    • pp.33-37
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    • 2007
  • Semantic clustering is important to various fields in the modem information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a hierarchical clustering in latent semantic space for finding out invisible information from the data.

Overlapped Subband-Based Independent Vector Analysis

  • Jang, Gil-Jin;Lee, Te-Won
    • The Journal of the Acoustical Society of Korea
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    • v.27 no.1E
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    • pp.30-34
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    • 2008
  • An improvement to the existing blind signal separation (BSS) method has been made in this paper. The proposed method models the inherent signal dependency observed in acoustic object to separate the real-world convolutive sound mixtures. The frequency domain approach requires solving the well known permutation problem, and the problem had been successfully solved by a vector representation of the sources whose multidimensional joint densities have a certain amount of dependency expressed by non-spherical distributions. Especially for speech signals, we observe strong dependencies across neighboring frequency bins and the decrease of those dependencies as the bins become far apart. The non-spherical joint density model proposed in this paper reflects this property of real-world speech signals. Experimental results show the improved performances over the spherical joint density representations.

A Study on the Automatic Mesh Generation of the Two Dimensional Structure using Object Oriented Modeling Concept (객체 지향 모델링 개념을 이용한 이차원 구조물의 유한요소 자동 생성에 관한 연구)

  • 장창두;심우승
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1996.04a
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    • pp.70-77
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    • 1996
  • Recently many efforts have been made to improve the efficiency of design and production of the structures using the automation system. But, this work has been progressed as independent or partial system. And, the study on the integrated system is not sufficient in application for practical problems yet. This paper deals with the fundamental concept of modeling system and application method on structural modeling. At first, the core of the integrated system is a shape modeling system that can represent the geometric and topological information. This system must be designed as an open system to be combined with each independent automation system. The appropriate concept to realize this system on structural modeling is object oriented modeling and this enables to integrate each automation system successfully, This concept was applied to automatic mesh generation. For shape modeling system, half-edge data structure that is being used in solid modeling was modified to handle the plate structure in the plane. And, to generate the triangular meshes, direct node connection method was used. And, as a result, the integrated system that generate the meshes of two dimensional structure automatically was realized. And, programmed by C++, these systems can be combined with other systems easily and have good reusability.

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Design of the 3D Object Recognition System with Hierarchical Feature Learning (계층적 특징 학습을 이용한 3차원 물체 인식 시스템의 설계)

  • Kim, Joohee;Kim, Dongha;Kim, Incheol
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.1
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    • pp.13-20
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    • 2016
  • In this paper, we propose an object recognition system that can effectively find out its category, its instance name, and several attributes from the color and depth images of an object with hierarchical feature learning. In the preprocessing stage, our system transforms the depth images of the object into the surface normal vectors, which can represent the shape information of the object more precisely. In the feature learning stage, it extracts a set of patch features and image features from a pair of the color image and the surface normal vector through two-layered learning. And then the system trains a set of independent classification models with a set of labeled feature vectors and the SVM learning algorithm. Through experiments with UW RGB-D Object Dataset, we verify the performance of the proposed object recognition system.