• Title/Summary/Keyword: 벡터공간모델

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Determination and Performance Evaluation of a Codebook for MIMO Systems Utilizing Statistical Properties of The Spatial Channel Model (공간 채널 모델의 통계적 특성을 활용하는 MIMO 시스템의 코드북 결정 및 성능 평가)

  • Suh, Junyeub;Kang, Hosik;Sung, Wonjin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.7
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    • pp.22-30
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    • 2015
  • For long-term evolution (LTE) MIMO transmission, codebooks are used to utilize the estimated channel information under the limited feedeback environment, and related study has been actively performed. Existing codebooks include codevectos constructed based on vector quantization (VQ) and discrete Fourier transform (DFT), and the LTE standard specifies codebooks modified from these examples to support up to 8 transmit antennas. As the number of antennas increases and as the spatial channel model is used as a standard environment to evaluate the LTE transmission performance, new beamforming methods as well as codebook designs are needed. In this paper, we implement the 3-dimensional spatial channel model (3D-SCM) to analyze the key statistical characteristics of the generated channel, and present efficient ways of determining corresponding codebooks. In particular, we propose a nonuniform-phase DFT-based codebook to improve the existing uniform-phase DFT-based codebook, and evaluate its performance under the given SCM transmission environment. There exists a strong tendancy in statistical distributions of the phase difference between adjacent antenna elements for the SCM, which can be appropriately exploited in codebook design to produce a performance gain over the existing design.

(A Question Type Classifier based on a Support Vector Machine for a Korean Question-Answering System) (한국어 질의응답시스템을 위한 지지 벡터기계 기반의 질의유형분류기)

  • 김학수;안영훈;서정연
    • Journal of KIISE:Software and Applications
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    • v.30 no.5_6
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    • pp.466-475
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    • 2003
  • To build an efficient Question-Answering (QA) system, a question type classifier is needed. It can classify user's queries into predefined categories regardless of the surface form of a question. In this paper, we propose a question type classifier using a Support Vector Machine (SVM). The question type classifier first extracts features like lexical forms, part of speech and semantic markers from a user's question. The system uses $X^2$ statistic to select important features. Selected features are represented as a vector. Finally, a SVM categorizes questions into predefined categories according to the extracted features. In the experiment, the proposed system accomplished 86.4% accuracy The system precisely classifies question type without using any rules like lexico-syntactic patterns. Therefore, the system is robust and easily portable to other domains.

The Method of the Evaluation of Verbal Lexical-Semantic Network Using the Automatic Word Clustering System (단어클러스터링 시스템을 이용한 어휘의미망의 활용평가 방안)

  • Kim, Hae-Gyung;Song, Mi-Young
    • Korean Journal of Oriental Medicine
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    • v.12 no.3 s.18
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    • pp.1-15
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    • 2006
  • For the recent several years, there has been much interest in lexical semantic network. However, it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic word clustering systems, which are called system A and system B respectively. 68,455,856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3,656 '-ha' verbs. The target data is the 'multilingual Word Net-CoreNet'.When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A, 45.3%.

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The Simulator Design for the Analysis of Aircraft Longitudinal Dynamic Characteristics (항공기 세로 동특성 해석을 위한 시뮬레이터 설계)

  • Yoon, Sun-Ju
    • Journal of the Korea Computer Industry Society
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    • v.7 no.4
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    • pp.427-436
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    • 2006
  • State-space method for the analysis of the dynamic characteristics of a body motion is set up as mathematical tool for the solution of differential equation by computer. Representation of a system is described as a simple form of matrix calculation and unique form of model is available for the linear or nonlinear, time variant or time invariant, mono variable or multi variable system etc. For the analysis of state-space method a complicated vector calculation is required, but this analysis can be simplified with the specific functions of a software package. Recently as the Graphical User Interface softwares are well-developed, then it is very simplified to execute the simulation of the dynamic characteristics for the state-space model with the interactive graphics treatment. The purpose of this study is to developed the simulator for the educational analysis of the dynamic characteristics of body motion, and for the analysis of the longitudinal dynamic characteristics of an aircraft that is primarily to design the simulator for the analysis of the transient response of an aircraft longitudinal stability.

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A Study on the Analysis of the Error in Photometric Stereo Method Caused by the General-purpose Lighting Environment (測光立體視法에서 범용조명원에 기인한 오차 해석에 관한 연구)

  • Kim, Tae-Eun;Chang, Tae-Gyu;Choi, Jong-Soo
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.31B no.11
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    • pp.53-62
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    • 1994
  • This paper presents a new approach of analyzing errors resulting from nonideal general-purpose lighting environment when the Photometric Stereo Method (PSM) is applied to estimate the surface-orientation of a three-dimensional object. The approach introduces the explicit modeling of the lighting environment including a circular-disk type irradiance object plane and the direct simulation of the error distribution with the model. The light source is modeled as a point source that has a certain amount of beam angle, and the luminance distribution on the irradiance plane is modeled as a Gaussian function with different deviation values. A simulation algorithm is devised to estimate the light source orientation computing the average luminance intensities obtained from the irradiance object planes positioned in three different orientations. The effect of the nonideal lighting model is directly reflected in such simulation, because of the analogy between the PSM and the proposed algorithm. With an instrumental tool designed to provide arbitrary orientations of the object plane at the origin of the coordinate system, experiment can be performed in a systematic way for the error analysis and compensation. Simulations are performed to find out the error distribution by widely varying the light model and the orientation set of the object plane. The simulation results are compared with those of the experiment performed in the same way as the simulation. It is confirmed from the experiment that a fair amount of errors is due to the erroneous effect of the general-purpose lighting environment.

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An Electric Load Forecasting Scheme for University Campus Buildings Using Artificial Neural Network and Support Vector Regression (인공 신경망과 지지 벡터 회귀분석을 이용한 대학 캠퍼스 건물의 전력 사용량 예측 기법)

  • Moon, Jihoon;Jun, Sanghoon;Park, Jinwoong;Choi, Young-Hwan;Hwang, Eenjun
    • KIPS Transactions on Computer and Communication Systems
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    • v.5 no.10
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    • pp.293-302
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    • 2016
  • Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.

A Study on the Speed Sensorless Vector Control for Induction Motor Adaptive Control Method using a High Frequency Boost Chopper of Hybrid Type Piezoelectric Transformer (하이브리드형 압전 변압기의 고주파 승압 초퍼를 이용한 적응제어기법 유도전동기 속도 센서리스 벡터제어에 관한 연구)

  • Hwang, Lark-Hoon;Na, Seung-Kwon;Kim, Yeong-Wook;Choi, Song-Shik
    • Journal of Advanced Navigation Technology
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    • v.17 no.3
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    • pp.332-345
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    • 2013
  • In this paper, recently, it is described to the piezoelectric transformer technology develops, because it was have to favorable characteristics such as electromagnetic-noise free, compact size, higher efficiency, and superior power density, flux linkage, noiseless, etc. its resonance frequency was used to output waveform of a sine wave. A rotor speed identification method of induction motor based on the theory of flux model reference adaptive system(FMRAS). The estimator execute the rotor speed identification so that the vector control of the induction motor may be achieved. The improved auxiliary variable of the model are introduced to perform accurate rotor speed estimation. The control system is composed of the PI controller for speed control and the current controller using space voltage vector PWM techniuqe and DC-DC converter. High speed calculation and processing for vector control is carried out by digital signal one chip microprocessor. Validity of the proposed control method is verified through simulation and experimental results.

Real-Time Image-Based Relighting for Tangible Video Teleconference (실감화상통신을 위한 실시간 재조명 기술)

  • Ryu, Sae-Woon;Parka, Jong-Il
    • Journal of Broadcast Engineering
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    • v.14 no.6
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    • pp.807-810
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    • 2009
  • This paper deals with a real-time image based relighting system for tangible video teleconference. The proposed image based relighting system renders the extracted human object using the virtual environmental images. The proposed system can homogenize virtually the lighting environments of remote users on the video teleconference, or render the humans like they are in the virtual places. To realize the video teleconference, the paper obtains the 3D object models of users in real-time using the controlled lighting system. In this paper, we use single color camera and synchronized two directional flash lights. Proposed system generates pure shading images using on and off flash images subtraction. One pure shading reflectance map generates a directional normal map from multiplication of each reflectance map and basic normal vector map. Each directional basic normal map is generated by inner vector calculation of incident light vector and camera viewing vector. And the basic normal vector means a basis component of real surface normal vector. The proposed system enables the users to immerse video teleconference just as they are in the virtual environments.

A Study on Fuzzy Wavelet LDA Mixed Model for an effective Face Expression Recognition (효과적인 얼굴 표정 인식을 위한 퍼지 웨이브렛 LDA융합 모델 연구)

  • Rho, Jong-Heun;Baek, Young-Hyun;Moon, Sung-Ryong
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.6
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    • pp.759-765
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    • 2006
  • In this paper, it is proposed an effective face expression recognition LDA mixed mode using a triangularity membership fuzzy function and wavelet basis. The proposal algorithm gets performs the optimal image, fuzzy wavelet algorithm and Expression recognition is consisted of face characteristic detection step and face Expression recognition step. This paper could applied to the PCA and LDA in using some simple strategies and also compares and analyzes the performance of the LDA mixed model which is combined and the facial expression recognition based on PCA and LDA. The LDA mixed model is represented by the PCA and the LDA approaches. And then we calculate the distance of vectors dPCA, dLDA from all fates in the database. Last, the two vectors are combined according to a given combination rule and the final decision is made by NNPC. In a result, we could showed the superior the LDA mixed model can be than the conventional algorithm.

A Study on Research Trends of Graph-Based Text Representations for Text Mining (텍스트 마이닝을 위한 그래프 기반 텍스트 표현 모델의 연구 동향)

  • Chang, Jae-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.5
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    • pp.37-47
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    • 2013
  • Text Mining is a research area of retrieving high quality hidden information such as patterns, trends, or distributions through analyzing unformatted text. Basically, since text mining assumes an unstructured text, it needs to be represented as a simple text model for analyzing it. So far, most frequently used model is VSM(Vector Space Model), in which a text is represented as a bag of words. However, recently much researches tried to apply a graph-based text model for representing semantic relationships between words. In this paper, we survey research trends of graph-based text representation models for text mining. Additionally, we also discuss about future models of graph-based text mining.