• Title/Summary/Keyword: Minimal Representation

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A Minimal Power Scheduling Algorithm for Low Power Circuit Design

  • Lin, Chi-Ho
    • Proceedings of the IEEK Conference
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    • 2002.07a
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    • pp.212-215
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    • 2002
  • In this paper, we present an intermediate representation CDFG(Control Data Flow Graph) and an efficient scheduling technique for low power circuit design. The proposed CDFG represents control flow, data dependency and such constraints as resource constraints and timing constraints. In the scheduling technique, the constraints are substituted by subgraphs, and then the number of subgraphs is minimized by using the inclusion and overlap relation efficiently. Also, iterative rescheduling process are performed in a minimum bound estimation, starting with the as soon as possible as scheduling result, so as to reduce the power consumption in low power design. The effectiveness of the proposed algorithm has been proven by the experiment with the benchmark examples.

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A Study on the Interrelation of Material and Space in Modern Interior Design (현대 실내디자인에 있어 재료와 공간의 상호관계성에 관한 연구)

  • 이상협;김문덕
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2003.05a
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    • pp.187-191
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    • 2003
  • Modern interior design is expanding diversely, with the rapid development of technology and change of era. The basic of interior space that is rapidly changing consists of floor, wall and ceiling, and these are formed by materials, materials for structure or finishing materials. In the modern interior space, materials are utilized to present an atmosphere that meets the trend of the dissolution of post-modernism and the trend of minimalism. Accordingly, in this study, designers who take serious view on the relation of space and material, and the relation focusing on completed works, in modern interior design were investigated. The interrelation of the representation of each material, organic space, minimal space, and the space of Oriental fusion style were investigated through the works of modern interior designers, such as Karim Rashid and Ettore Sottsass.

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THE DIMENSION REDUCTION ALGORITHM FOR THE POSITIVE REALIZATION OF DISCRETE PHASE-TYPE DISTRIBUTIONS

  • Kim, Kyung-Sup
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.16 no.1
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    • pp.51-64
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    • 2012
  • This paper provides an efficient dimension reduction algorithm of the positive realization of discrete phase type(DPH) distributions. The relationship between the representation of DPH distributions and the positive realization of the positive system is explained. The dimension of the positive realization of a discrete phase-type realization may be larger than its McMillan degree of probability generating functions. The positive realization with sufficient large dimension bound can be obtained easily but generally, the minimal positive realization problem is not solved yet. We propose an efficient dimension reduction algorithm to make the positive realization with tighter upper bound from a given probability generating functions in terms of convex cone problem and linear programming.

The Improved Velocity-based Models for Pedestrian Dynamics

  • Yang, Xiao;Qin, Zheng;Wan, Binhua;Zhang, Renwei;Wang, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.9
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    • pp.4379-4397
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    • 2017
  • Three different improvements of the Velocity-based model were proposed in a minimal velocity-based pedestrian model. The improvements of the models are based on the different agent forms. The different representations of the agent lead to different results, in this paper, we simulated the pedestrian movements in some typical scenes by using different agent forms, and the agent forms included the circles with different radiuses, the ellipse and the multi-circle stand for one pedestrian. We have proposed a novel model of pedestrian dynamics to optimize the simulation. Our model specifies the pedestrian behavior using a dynamic ellipse, which is parameterized by their velocity and can improve the simulaton accuracy. We found a representation of the pedestrian much closer to the reality. The phenomena of the self-organization can be observable in the improved models.

Basic principle of cone beam computed tomography (Cone beam형 전산화단층영상의 원리)

  • Choi Yong-Suk;Kim Gyu-Tae;Hwang Eui-Hwan
    • Imaging Science in Dentistry
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    • v.36 no.3
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    • pp.123-129
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    • 2006
  • The use of computed tomography for dental procedures has increased recently. Cone beam computed tomography (CBCT) systems have been designed for imaging hard tissues of the dentomaxillofacial region. CBCT is capable of providing high resolution in images of high diagnostic quality. This technology allows for 3-dimensional representation of the dentomaxillofacial skeleton with minimal distortion, but at lower equipment cost, simpler image acquisition and lower patient dose. Because this technology produces images with isotropic sub-millimeter spatial resolution, it is ideally suited for dedicated dentomaxillofacial imaging. In this paper, we provide a brief overview of cone beam scanning technology and compare it with the fan beam scanning used in conventional CT and the basic principles of currently available CBCT systems.

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Linearized Methods for Quantitative Analysis and Parametric Mapping of Brain PET (뇌 PET 영상 정량화 및 파라메터영상 구성을 위한 선형분석기법)

  • Kim, Su-Jin;Lee, Jae-Sung
    • Nuclear Medicine and Molecular Imaging
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    • v.41 no.2
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    • pp.78-84
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    • 2007
  • Quantitative analysis of dynamic brain PET data using a tracer kinetic modeling has played important roles in the investigation of functional and molecular basis of various brain diseases. Parametric imaging of the kinetic parameters (voxel-wise representation of the estimated parameters) has several advantages over the conventional approaches using region of interest (ROI). Therefore, several strategies have been suggested to generate the parametric images with a minimal bias and variability in the parameter estimation. In this paper, we will review the several approaches for parametric imaging with linearized methods which include graphical analysis and mulilinear regression analysis.

Information Structure of Relative Clauses in English: a Flexible and Computationally Tractable Model

  • Song, Sanghoun
    • Language and Information
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    • v.18 no.2
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    • pp.1-29
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    • 2014
  • Relativization is one of the common syntactic operations to merge two different clauses into a single information unit. This operation plays a pivotal role to structuralize multiple clauses cohesively as well as serves to specify the property an individual has within the context. That implies that relativization contributes to information structure of multiclausal sentences. In this context, this paper delves into information structure of relative clauses in English with an eye toward creation of a computational model from a standpoint of machine translation. The current work employs Head-driven Phrase Structure Grammar (HPSG, Pollard and Sag (1994)) as a theory of grammar and Minimal Recursion Semantics (MRS, Copestake et al. (2005) as a meaning representation system. Building upon these formalisms, this paper addresses how information structure of relative clauses can be represented and constrained. The current work makes use of Individual CONStraints (ICONS) for modeling relative clauses with respect to information structure. The current work also investigates which relative clause involves which information structure constraint. The present study argues that non-restrictive relative clauses impose a more specific constraint on information structure than restrictive relative clauses.

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Design of a Pseudo Gaussian Function Network Using Asymmetric Activation Functions

  • Kim, Byung-Man;Cho, Hyung-Suck
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.43.3-43
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    • 2001
  • In conventional RBF network, the activation functions of hidden layers generally are symmetric functions like gaussian function. This has been considered to be one of the limiting factors for the network to speed up learning of actuately describing a given function. To avoid this criticism, we propose a pseudo gaussian function (PGF) whose deviation is changed according to the direction of incoming pattern. This property helps to estimate the given function more effectively with a minimal number of centers because of its flexibility of functional representation. A level set method is used to describe the asymmetric shape of deviation of the pseudo gaussian function. To demonstrate the performance of the proposed network ...

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Efficient Image Retrieval using Minimal Spatial Relationships (최소 공간관계를 이용한 효율적인 이미지 검색)

  • Lee, Soo-Cheol;Hwang, Een-Jun;Byeon, Kwang-Jun
    • Journal of KIISE:Databases
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    • v.32 no.4
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    • pp.383-393
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    • 2005
  • Retrieval of images from image databases by spatial relationship can be effectively performed through visual interface systems. In these systems, the representation of image with 2D strings, which are derived from symbolic projections, provides an efficient and natural way to construct image index and is also an ideal representation for the visual query. With this approach, retrieval is reduced to matching two symbolic strings. However, using 2D-string representations, spatial relationships between the objects in the image might not be exactly specified. Ambiguities arise for the retrieval of images of 3D scenes. In order to remove ambiguous description of object spatial relationships, in this paper, images are referred by considering spatial relationships using the spatial location algebra for the 3D image scene. Also, we remove the repetitive spatial relationships using the several reduction rules. A reduction mechanism using these rules can be used in query processing systems that retrieve images by content. This could give better precision and flexibility in image retrieval.

Robust Radiometric and Geometric Correction Methods for Drone-Based Hyperspectral Imaging in Agricultural Applications

  • Hyoung-Sub Shin;Seung-Hwan Go;Jong-Hwa Park
    • Korean Journal of Remote Sensing
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    • v.40 no.3
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    • pp.257-268
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    • 2024
  • Drone-mounted hyperspectral sensors (DHSs) have revolutionized remote sensing in agriculture by offering a cost-effective and flexible platform for high-resolution spectral data acquisition. Their ability to capture data at low altitudes minimizes atmospheric interference, enhancing their utility in agricultural monitoring and management. This study focused on addressing the challenges of radiometric and geometric distortions in preprocessing drone-acquired hyperspectral data. Radiometric correction, using the empirical line method (ELM) and spectral reference panels, effectively removed sensor noise and variations in solar irradiance, resulting in accurate surface reflectance values. Notably, the ELM correction improved reflectance for measured reference panels by 5-55%, resulting in a more uniform spectral profile across wavelengths, further validated by high correlations (0.97-0.99), despite minor deviations observed at specific wavelengths for some reflectors. Geometric correction, utilizing a rubber sheet transformation with ground control points, successfully rectified distortions caused by sensor orientation and flight path variations, ensuring accurate spatial representation within the image. The effectiveness of geometric correction was assessed using root mean square error(RMSE) analysis, revealing minimal errors in both east-west(0.00 to 0.081 m) and north-south directions(0.00 to 0.076 m).The overall position RMSE of 0.031 meters across 100 points demonstrates high geometric accuracy, exceeding industry standards. Additionally, image mosaicking was performed to create a comprehensive representation of the study area. These results demonstrate the effectiveness of the applied preprocessing techniques and highlight the potential of DHSs for precise crop health monitoring and management in smart agriculture. However, further research is needed to address challenges related to data dimensionality, sensor calibration, and reference data availability, as well as exploring alternative correction methods and evaluating their performance in diverse environmental conditions to enhance the robustness and applicability of hyperspectral data processing in agriculture.