• Title/Summary/Keyword: State representation

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Neural Model for Named Entity Recognition Considering Aligned Representation

  • Sun, Hongyang;Kim, Taewhan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.613-616
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    • 2018
  • Sequence tagging is an important task in Natural Language Processing (NLP), in which the Named Entity Recognition (NER) is the key issue. So far the most widely adopted model for NER in NLP is that of combining the neural network of bidirectional long short-term memory (BiLSTM) and the statistical sequence prediction method of Conditional Random Field (CRF). In this work, we improve the prediction accuracy of the BiLSTM by supporting an aligned word representation mechanism. We have performed experiments on multilingual (English, Spanish and Dutch) datasets and confirmed that our proposed model outperformed the existing state-of-the-art models.

WEIGHTED BLOCH SPACES IN $C^n$

  • Kyong Taik Hahn;Ki Seong Choi
    • Journal of the Korean Mathematical Society
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    • v.35 no.1
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    • pp.177-189
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    • 1998
  • In this paper, weighted Bloch spaces $B_q (q > 0)$ are considered on the open unit ball in $C^n$. These spaces extend the notion of Bloch spaces to wider classes of holomorphic functions. It is proved that the functions in a weighted Bloch space admit certain integral representation. This representation formula is then used to determine the degree of growth of the functions in the space $B_q$. It is also proved that weighted Bloch space is a Banach space for each weight q > 0, and the little Bloch space $B_q,0$ associated with $B_q$ is a separable subspace of $B_q$ which is the closure of the polynomials for each $q \geq 1$.

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Performance Analysis of Local Network PPP-RTK using GPS Measurements in Korea

  • Jeon, TaeHyeong;Park, Sang Hyun;Park, Sul Gee
    • Journal of Positioning, Navigation, and Timing
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    • v.11 no.4
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    • pp.263-268
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    • 2022
  • Precise Point Positioning-Real Time Kinematic (PPP-RTK) is a high accuracy positioning method that combines RTK and PPP to overcome the limitations on service coverage of RTK and convergence time of PPP. PPP-RTK provides correction data in the form of State Space Representation (SSR), unlike RTK, which provides measurement-based Observation Space Representation (OSR). Due to this, PPP-RTK has an advantage that it can transmit less data than RTK. So, recently, several techniques for PPP-RTK have been proposed. However, in order to utilize PPP-RTK techniques, performance analysis of these in a real environment is essential. In this paper, we implement the local network PPP-RTK and analyze the positioning performance according to the distance within 100 km from the reference station in Korea. As results of experiment, the horizontal and vertical 95% errors of local network PPP-RTK were 6.25 cm and 5.86 cm or less, respectively.

The Performance Verification of Optimal State Feedback Controllers via The Inverted Pendulum (도립진자 시스템을 통한 최적 상태 되먹임 제어기의 성능 검증)

  • Lee, Jong-Yeon;Lee, Bo-Ra;Hyun, Chang-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.6
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    • pp.768-773
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    • 2010
  • This paper presents the performance verification of the optimal state feedback controller via inverted pendulum systems. The proposed method generates the optimal control inputs satisfying both the constrained input and the performance specification. In addition, it reduces the steady-state error by adopting the integral control technique. In order to verify the performance of the proposed method, we apply both the proposed method and the general state feedback control to an inverted pendulum, CEM-IP-01 in the experiment.

A Framework of Building Knowledge Representation for Sustainability Rating in BIM

  • Shahaboddin Hashemi Toroghi;Tang-Hung. Nguyen;Jin-Lee. Kim
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.437-443
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    • 2013
  • Recently, sustainable building design, a growing field within architectural design, has been emerged in the construction industry as the practice of designing, constructing, and operating facilities in such a manner that their environmental impact, which has become a great concern of construction professionals, can be minimized. A number of different green rating systems have been developed to help assess that a building project is designed and built using strategies intended to minimize or eliminate its impact on the environment. In the United States, the widely accepted national standards for sustainable building design are known as the LEED (Leadership in Energy and Environmental Design) Green Building Rating System. The assessment of sustainability using the LEED green rating system is a challenging and time-consuming work due to its complicated process. In effect, the LEED green rating system awards points for satisfying specified green building criteria into five major categories: sustainable sites, water efficiency, energy and atmosphere, materials and resources, and indoor environmental quality; and sustainability of a project is rated by accumulating scores (100 points maximum) from these five major categories. The sustainability rating process could be accelerated and facilitated by using computer technology such as BIM (Building Information Modeling), an innovative new approach to building design, engineering, and construction management that has been widely used in the construction industry. BIM is defined as a model-based technology linked with a database of project information, which can be accessed, manipulated, and retrieved for construction estimating, scheduling, project management, as well as sustainability rating. This paper will present a framework representing the building knowledge contained in the LEED green building criteria. The proposed building knowledge framework will be implemented into a BIM platform (e.g. Autodesk Revit Architecture) in which sustainability rating of a building design can be automatically performed. The development of the automated sustainability rating system and the results of its implementation will be discussed.

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Sensorless Control of Induction Motor using Adaptive FNN Controller (적응 FNN에 의한 유도전동기의 센서리스 제어)

  • Lee, Young-Sil;Lee, Jung-Chul;Lee, Hong-Gyun;Nam, Su-Myeong;Chung, Dong-Hwa
    • Proceedings of the KIEE Conference
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    • 2004.10a
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    • pp.179-181
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    • 2004
  • This paper is proposed an adaptive fuzzy-neural network(A-FNN) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using A closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.

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Dynamic Incidence Matrix Representation of Timed Petri Nets and Its Applications for Performance Analysis

  • Shon, J.G.;Hwang, C.S.;Baik, D.K.
    • Journal of the Korean Operations Research and Management Science Society
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    • v.16 no.2
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    • pp.128-147
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    • 1991
  • We propose a dynamic incidence matrix (DIM) for reflecting states and time conditions of a timed Petri net (TPN) explicitly. Since a DIM consists of a conventional incidence matrix, two time-related vectors and two state-related vectors, we can get the advantages inherent in the conventional incidence matrix of describing a static structure of a system as well as another advantage of expressing time dependent state transitions. We introduce an algorithm providing the DIM with a state transition mechanism. Because the algorithm is, in fact, an algorithmic model for discrete event simulation of TPN models, we provide a theoretical basis of model transformation of a TPN model into a DEVS(Discrete Event system Specification) model. By executing the algorithm we can carry out performance analysis of computer communication protocols which are represented TPN models.

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Fundamental Condition for the Realization of Maximal Contrast and Brightness in Liquid Crystal Display Devices: I. Monochromatic Case (액정표지소자에서 화면의 명암대비와 밝기를 극대화하는 기본조건: I. 단색광의 경우)

  • 노봉규;김규석;김진승
    • Korean Journal of Optics and Photonics
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    • v.5 no.3
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    • pp.404-410
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    • 1994
  • The contrast and the brightness of a liquid crystal display panel are expressed in terms of the characteristic parameters of the rotational transformation on the Poincare sphere of the liquid crystal (LC) cell, which is the geometric representation of the electro-optic polarization transmission characteristics of the cell. From these, we show that the contrast and the brightness of the displayed images can be maximized when the rotation angle becomes $180^{\circ}$ for the rotational transformation corresponding to the change of the state of the LC cell from non-select to select state. state.

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Variance Analysis for State Estimation In Communication Channel with Finite Bandwidth (유한한 대역폭을 가지는 통신 채널에서의 상태 추정값에 대한 분산 해석)

  • Fang, Tae-Hyun;Choi, Jae-Weon
    • Proceedings of the KSME Conference
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    • 2000.11a
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    • pp.693-698
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    • 2000
  • Aspects of classical information theory, such as rate distortion theory, investigate how to encode and decode information from an independently identically distributed source so that the asymptotic distortion rate between the source and its quantized representation is minimized. However, in most natural dynamics, the source state is highly corrupted by disturbances, and the measurement contains the noise. In recent coder-estimator sequence is developed for state estimation problem based on observations transmitted with finite communication capacity constraints. Unlike classical estimation problems where the observation is a continuous process corrupted by additive noises, the condition is that the observations must be coded and transmitted over a digital communication channel with finite capacity. However, coder-estimator sequence does not provide such a quantitative analysis as a variance for estimation error. In this paper, under the assumption that the estimation error is Gaussian distribution, a variance for coder-estimation sequence is proposed and its fitness is evaluated through simulations with a simple example.

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Sensorless Vector Control of Induction Motor with HAI Controller (HAI 제어기에 의한 유도전동기의 센서리스 벡터제어)

  • Lee, Jung-Chul;Lee, Hong-Gyun;Chung, Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.54 no.2
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    • pp.73-79
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    • 2005
  • This paper is proposed hybrid artificial intelligent (HAI) controller based on the vector controlled induction motor drive system. The hybrid combination of fuzzy control and neural network will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed estimation of induction motor using a closed-loop state observer. The rotor position is calculated through the stator flux position and an estimated flux value of rotation reference frame. A closed-loop state observer is implemented to compute the speed feedback signal. The results of analysis prove that the proposed control system has strong robustness to rotor parameter variation, and has good steady-state accuracy and transitory response.