• Title/Summary/Keyword: Vector method

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Investigation on the Effect of Multi-Vector Document Embedding for Interdisciplinary Knowledge Representation

  • Park, Jongin;Kim, Namgyu
    • Knowledge Management Research
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    • v.21 no.1
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    • pp.99-116
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    • 2020
  • Text is the most widely used means of exchanging or expressing knowledge and information in the real world. Recently, researches on structuring unstructured text data for text analysis have been actively performed. One of the most representative document embedding method (i.e. doc2Vec) generates a single vector for each document using the whole corpus included in the document. This causes a limitation that the document vector is affected by not only core words but also other miscellaneous words. Additionally, the traditional document embedding algorithms map each document into only one vector. Therefore, it is not easy to represent a complex document with interdisciplinary subjects into a single vector properly by the traditional approach. In this paper, we introduce a multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. After introducing the previous study on multi-vector document embedding, we visually analyze the effects of the multi-vector document embedding method. Firstly, the new method vectorizes the document using only predefined keywords instead of the entire words. Secondly, the new method decomposes various subjects included in the document and generates multiple vectors for each document. The experiments for about three thousands of academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the multi-vector based method, we ascertained that the information and knowledge in complex documents can be represented more accurately by eliminating the interference among subjects.

A METHOD FOR ADJUSTING ADAPTIVELY THE WEIGHT OF FEATURE IN MULTI-DIMENSIONAL FEATURE VECTOR MATCHING

  • Ye, Chul-Soo
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.772-775
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    • 2006
  • Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

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Sequential Fault Detection and Isolation for Redundant Inertial Sensor Systems with Uncertain Factors

  • Kim, Jeong-Yong;Yang, Cheol-Kwan;Shim, Duk-Sun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2594-2599
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    • 2003
  • We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

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A causal ordering algorithm using a new compression method (새로운 압축 방식을 이용한 인과관계 순서화 알고리즘)

  • 권봉경;정광수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.6
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    • pp.1127-1136
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    • 1997
  • A vector timestamp is used to satisfy message ordering in a group communications. In this paper, we propose a new vector timestamp compression method which is applicable to a single process group environment where one process belongs to only one precess group. An existing compression method compares the fields of the previously sent vector timestamp with thouse of the currently updated vector timestamp, then sends only the modified fields of the vector timestamp. Unlike the previous one, a proposed compression method performs individual compression for each process using the locally maintained vector timestamp information on other processes. Also, we logicallyproved the causal ordering algorithm using the new compression method and compared the performance of the proposed method with one of the previous compression method by computer simulation. Using the proposed compression method, the message overhead required for causal ordering can be reduced.

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A Study on the Performance Enhancement of Radar Target Classification Using the Two-Level Feature Vector Fusion Method

  • Kim, In-Ha;Choi, In-Sik;Chae, Dae-Young
    • Journal of electromagnetic engineering and science
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    • v.18 no.3
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    • pp.206-211
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    • 2018
  • In this paper, we proposed a two-level feature vector fusion technique to improve the performance of target classification. The proposed method combines feature vectors of the early-time region and late-time region in the first-level fusion. In the second-level fusion, we combine the monostatic and bistatic features obtained in the first level. The radar cross section (RCS) of the 3D full-scale model is obtained using the electromagnetic analysis tool FEKO, and then, the feature vector of the target is extracted from it. The feature vector based on the waveform structure is used as the feature vector of the early-time region, while the resonance frequency extracted using the evolutionary programming-based CLEAN algorithm is used as the feature vector of the late-time region. The study results show that the two-level fusion method is better than the one-level fusion method.

Three dimensional vector control of airconditioner inverter (에어컨 인버터의 3차원 Vector제어)

  • 장재석;이장명
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.500-503
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    • 1997
  • In this paper, we investigate the control methodology of inverter Airconditioner, using the three dimensional vector scheme. The method of three dimensional vector aims at the determination of optimal switching patterns for PWM to reduce switching loss and to improve the performance supplied voltage. The induction motors are widely used for home Airconditioners. These motors can be classified into two types: on or off control of Airconditioner and the speed control of motor. For speed control of motors, generally PWM methods are used. The PWM method based upon the modulation of triangular wave can not afford to supply line voltage to the motor sufficiently because of the capacity of processing speed of micro processors. Therefore airconditioner can not be operated efficiently. This problem can be solved with the method of three dimensional vector since it can increase the supplied voltage and maximum operating frequency of motor to 173V and 96Hz, respectively. As the result, this method shows 10 - 15% increase of voltage and 10% increase of operating frequency over the modulation of triangular wave. According to a theoretical study, the number of switching in the method of three dimensional vector is smaller than that of the modulation of triangular wave. The power consumption can be reduced and the supplied voltage can be increased. In other words, the efficiency of Airconditioner can be improved. We show that the method of three dimensional vector can supply higher voltage than the modulation of triangular method through the experiments and verify the degree of improvement of efficiency theoretically.

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A vector control method for multiple induction motors (다중모터 구동에서의 벡터제어)

  • Byun, Yeun-Sub;Kim, Young-Chol
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.649-652
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    • 2003
  • In this paper, we presents a vector control method for the parallel-connected motor drive system. The new estimation scheme of rotor flux position is presented to reduce sensitivity due to load difference between the motors. To confirm the validity of the proposed control method. we compare a simulation result of the proposed control method with that of the conventional indirect vector control method. The simulation results show that the proposed control method is more effective for change in load torque and motor parameters.

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Vectorization of an Explicit Finite Element Method on Memory-to-Memory Type Vector Computer (Memory-to-Memory방식 벡터컴퓨터에서의 외연적 유한요소법의 벡터화)

  • 이지호;이재석
    • Computational Structural Engineering
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    • v.4 no.1
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    • pp.95-108
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    • 1991
  • An explicit finite element method can be executed more rapidly and effectively on vector computer than on the scalar computer because it has suitable structures for vector processing. In this paper, an efficient vectorization method of the explicit finite element program on the memory-to-memory type vector computer is proposed. First, the general vectorization method which can be applied regardless of the vector architecture is investigated, then the method which is suitable for the memory-to-memory type vector computer is proposed. To illustrate the usefulness of the proposed vectorization method, DYNA3D, the existing explicit finite element program, is migrated on HDS AS/XL V50 which is the memory-to-memory type vector computer. Performance results on actual test show a vector/scalar speedup is above 2.4.

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Design of Two Mount Systems by Vector Synthesis Method (백터합성법에 의한 2마운트계 설계)

  • 차현주;이시복;이상훈
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1997.04a
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    • pp.491-495
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    • 1997
  • In this paper, an effective mount design method using vector synthesis is presented for two mount systems. For designing mount stiffnesses effectively, we perform a sensitivity analysis, i.e, identify the contribution rate of an input component vector to the total output vector. Especially, we show that it is necessary to takea phase sensitivity into consideration in case of two mount systems, such as the excavator mount systems having engine mounts and cabin mounts. THe proposed method is testified is testified through an test bed.

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The Identification of Generation Mechanism of Noise and Vibrtaion and Transmission Characteristics for Engine System - The Source Identification and Noise Reduction of Compartment by Multidimensional Spectral Analysis and Vector Synthesis Method - (엔진의 소음.진동발생기구 및 전달특성 규명 -다차원해석법과 벡터합성법에 의한 차실소음원 규명 및 소음저감 -)

  • O, Jae-Eung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.7
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    • pp.1127-1140
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    • 1997
  • With the study for identifying the transmission characteristics of vibration and noise generated by operating engine system of a vehicle, recently many engineers have studied actively the reduction of vibration and noise inducing uncomfortableness to the passenger. In this study, output noise was analyzed by multi-dimensional spectral analysis and vector synthesis method. The multi-dimensional analysis method is very effective in case of identification of primary source, but this method has little effect on suggestion for interior noised reduction. For compensation of this, vector synthesis method was used to obtain effective method for interior noise reduction, after identifying primary source for output noise. In this paper, partial coherence function of each input was calculated to know which input was most coherent to output noise, then with simulation of changes for input magnitude and phase by vector synthesis diagram, the trends of synthesized output vector was obtained. As a result, the change of synthesized output vector could be estimated.