• Title/Summary/Keyword: f-vector

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SIZE OF DOT PRODUCT SETS DETERMINED BY PAIRS OF SUBSETS OF VECTOR SPACES OVER FINITE FIELDS

  • Koh, Doowon;Pi, Youngjin
    • Journal of the Chungcheong Mathematical Society
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    • v.26 no.4
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    • pp.853-867
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    • 2013
  • In this paper we study the cardinality of the dot product set generated by two subsets of vector spaces over finite fields. We notice that the results on the dot product problems for one set can be simply extended to two sets. Let E and F be subsets of the d-dimensional vector space $\mathbb{F}^d_q$ over a finite field $\mathbb{F}_q$ with q elements. As a new result, we prove that if E and F are subsets of the paraboloid and ${\mid}E{\parallel}F{\mid}{\geq}Cq^d$ for some large C > 1, then ${\mid}{\Pi}(E,F){\mid}{\geq}cq$ for some 0 < c < 1. In particular, we find a connection between the size of the dot product set and the number of lines through both the origin and a nonzero point in the given set E. As an application of this observation, we obtain more sharpened results on the generalized dot product set problems. The discrete Fourier analysis and geometrical observation play a crucial role in proving our results.

Lq-ESTIMATES OF MAXIMAL OPERATORS ON THE p-ADIC VECTOR SPACE

  • Kim, Yong-Cheol
    • Communications of the Korean Mathematical Society
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    • v.24 no.3
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    • pp.367-379
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    • 2009
  • For a prime number p, let $\mathbb{Q}_p$ denote the p-adic field and let $\mathbb{Q}_p^d$ denote a vector space over $\mathbb{Q}_p$ which consists of all d-tuples of $\mathbb{Q}_p$. For a function f ${\in}L_{loc}^1(\mathbb{Q}_p^d)$, we define the Hardy-Littlewood maximal function of f on $\mathbb{Q}_p^d$ by $$M_pf(x)=sup\frac{1}{\gamma{\in}\mathbb{Z}|B_{\gamma}(x)|H}{\int}_{B\gamma(x)}|f(y)|dy$$, where |E|$_H$ denotes the Haar measure of a measurable subset E of $\mathbb{Q}_p^d$ and $B_\gamma(x)$ denotes the p-adic ball with center x ${\in}\;\mathbb{Q}_p^d$ and radius $p^\gamma$. If 1 < q $\leq\;\infty$, then we prove that $M_p$ is a bounded operator of $L^q(\mathbb{Q}_p^d)$ into $L^q(\mathbb{Q}_p^d)$; moreover, $M_p$ is of weak type (1, 1) on $L^1(\mathbb{Q}_p^d)$, that is to say, |{$x{\in}\mathbb{Q}_p^d:|M_pf(x)|$>$\lambda$}|$_H{\leq}\frac{p^d}{\lambda}||f||_{L^1(\mathbb{Q}_p^d)},\;\lambda$ > 0 for any f ${\in}L^1(\mathbb{Q}_p^d)$.

Determination of Fall Direction Before Impact Using Support Vector Machine (서포트벡터머신을 이용한 충격전 낙상방향 판별)

  • Lee, Jung Keun
    • Journal of Sensor Science and Technology
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    • v.24 no.1
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    • pp.47-53
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    • 2015
  • Fall-related injuries in elderly people are a major health care problem. This paper introduces determination of fall direction before impact using support vector machine (SVM). Once a falling phase is detected, dynamic characteristic parameters measured by the accelerometer and gyroscope and then processed by a Kalman filter are used in the SVM to determine the fall directions, i.e., forward (F), backward (B), rightward (R), and leftward (L). This paper compares the determination sensitivities according to the selected parameters for the SVM (velocities, tilt angles, vs. accelerations) and sensor attachment locations (waist vs. chest) with regards to the binary classification (i.e., F vs. B and R vs. L) and the multi-class classification (i.e., F, B, R, vs. L). Based on the velocity of waist which was superior to other parameters, the SVM in the binary case achieved 100% sensitivities for both F vs. B and R vs. L, while the SVM in the multi-class case achieved the sensitivities of F 93.8%, B 91.3%, R 62.3%, and L 63.6%.

Machine learning-based Predictive Model of Suicidal Thoughts among Korean Adolescents. (머신러닝 기반 한국 청소년의 자살 생각 예측 모델)

  • YeaJu JIN;HyunKi KIM
    • Journal of Korea Artificial Intelligence Association
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    • v.1 no.1
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    • pp.1-6
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    • 2023
  • This study developed models using decision forest, support vector machine, and logistic regression methods to predict and prevent suicidal ideation among Korean adolescents. The study sample consisted of 51,407 individuals after removing missing data from the raw data of the 18th (2022) Youth Health Behavior Survey conducted by the Korea Centers for Disease Control and Prevention. Analysis was performed using the MS Azure program with Two-Class Decision Forest, Two-Class Support Vector Machine, and Two-Class Logistic Regression. The results of the study showed that the decision forest model achieved an accuracy of 84.8% and an F1-score of 36.7%. The support vector machine model achieved an accuracy of 86.3% and an F1-score of 24.5%. The logistic regression model achieved an accuracy of 87.2% and an F1-score of 40.1%. Applying the logistic regression model with SMOTE to address data imbalance resulted in an accuracy of 81.7% and an F1-score of 57.7%. Although the accuracy slightly decreased, the recall, precision, and F1-score improved, demonstrating excellent performance. These findings have significant implications for the development of prediction models for suicidal ideation among Korean adolescents and can contribute to the prevention and improvement of youth suicide.

A Stator Flux Oriented V/f Control of Induction Motor in Low Speed Range

  • Kim Young-Real
    • Proceedings of the KIPE Conference
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    • 2001.10a
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    • pp.466-469
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    • 2001
  • In this paper, closed loop V/f control of induction motor has been implemented by the estimated speed. Closed loop V/f control improve the performance of induction motor drive system at low speed compared to open loop V/f control. However, closed loop V/f control need speed sensor. By using the estimated speed, closed loop V/f control is possible without speed sensor. Rotor speed is calculated from the difference between synchronous frequency and slip angular frequency. 3-phase voltage reference is obtained from synchronous frequency. And the PWM technique using space vector PWM is applied in this scheme. In the space vector PWM, effective time of 3-phase voltage reference is used to simplify the calculation of effective voltage time. This scheme is simple to implement and one chip microprocessor was used in experimental system.

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A Video Stream Retrieval System based on Trend Vectors (경향 벡터 기반 비디오 스트림 검색 시스템)

  • Lee, Seok-Lyong;Chun, Seok-Ju
    • Journal of Korea Multimedia Society
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    • v.10 no.8
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    • pp.1017-1028
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    • 2007
  • In this paper we propose an effective method to represent, store, and retrieve video streams efficiently from a video database. We extract features from each video frame, normalize the feature values, and represent them as values in the range [0,1]. In this way a video frame with f features can be represented by a point in the f-dimensional space $[0,1]^f$, and thus the video stream is represented by a trail of points in the multidimensional space. The video stream is partitioned into video segments based on camera shots, each of which is represented by a trend vector which encapsulates the moving trend of points in a segment. The video stream query is processed depending on the comparison of those trend vectors. We examine our method using a collection of video streams that are composed of sports, news, documentary, and educational videos. Experimental results show that our trend vector representation reduces a reconstruction error remarkably (average 37%) and the retrieval using a trend vector achieves the high precision (average 2.1 times) while maintaining the similar response time and recall rate as existing methods.

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Fraud detection support vector machines with a functional predictor: application to defective wafer detection problem (불량 웨이퍼 탐지를 위한 함수형 부정 탐지 지지 벡터기계)

  • Park, Minhyoung;Shin, Seung Jun
    • The Korean Journal of Applied Statistics
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    • v.35 no.5
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    • pp.593-601
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    • 2022
  • We call "fruad" the cases that are not frequently occurring but cause significant losses. Fraud detection is commonly encountered in various applications, including wafer production in the semiconductor industry. It is not trivial to directly extend the standard binary classification methods to the fraud detection context because the misclassification cost is much higher than the normal class. In this article, we propose the functional fraud detection support vector machine (F2DSVM) that extends the fraud detection support vector machine (FDSVM) to handle functional covariates. The proposed method seeks a classifier for a function predictor that achieves optimal performance while achieving the desired sensitivity level. F2DSVM, like the conventional SVM, has piece-wise linear solution paths, allowing us to develop an efficient algorithm to recover entire solution paths, resulting in significantly improved computational efficiency. Finally, we apply the proposed F2DSVM to the defective wafer detection problem and assess its potential applicability.

Implementation of Compact Vector Control System for Induction Motor Using TMS320F2812 DSP and Smart Power Module (TMS320F2812 DSP와 스마트 파워모듈을 사용한 유도전동기 소형 벡터제어 시스템의 구현)

  • Lim Jeong-Gyu;Kim Seok-Hwan;Chung Se-Kyo
    • Proceedings of the KIPE Conference
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    • 2004.07a
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    • pp.11-14
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    • 2004
  • This paper presents an implementation of compact vector control system for induction motor using a digital signal processor (DSP) and a smart power module (SPM). The DSP TMS320F2812 has most necessary functions for ac motor control in a single chip and SPM provides a compact power stage. The indirect vector control algorithm is implemented in the drive system using these devices. The developed system is applied by 0.8kW induction servo motor and the all functions are verified through the experiments.

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The Convergence Characteristics of The Time- Averaged Distortion in Vector Quantization: Part I. Theory Based on The Law of Large Numbers (벡터 양자화에서 시간 평균 왜곡치의 수렴 특성 I. 대수 법칙에 근거한 이론)

  • 김동식
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.7
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    • pp.107-115
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    • 1996
  • The average distortio of the vector quantizer is calcualted using a probability function F of the input source for a given codebook. But, since the input source is unknown in geneal, using the sample vectors that is realized from a random vector having probability function F, a time-average opeation is employed so as to obtain an approximation of the average distortion. In this case the size of the smple set should be large so that the sample vectors represent true F reliably. The theoretical inspection about the approximation, however, is not perfomed rigorously. Thus one might use the time-average distortion without any verification of the approximation. In this paper, the convergence characteristics of the time-average distortions are theoretically investigated when the size of sample vectors or the size of codebook gets large. It has been revealed that if codebook size is large enough, then small sample set is enough to obtain the average distortion by approximatio of the calculated tiem-averaged distortion. Experimental results on synthetic data, which are supporting the analysis, are also provided and discussed.

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Vector control of AC servo motor using TMX320F2812 (TMX320F2812를 이용한 AC서보 모터의 벡터제어)

  • Choi, Chi-Young;Hong, Sun-Ki;Han, Sang-Bok
    • Proceedings of the KIEE Conference
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    • 2003.07b
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    • pp.1132-1134
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    • 2003
  • This paper presents the realization of the vector control for AC servo motor using a high performance DSP, TMX320F2812. This DSP has some special peripheral circuits to drive a AC Servo motor as AD converter, QEP and so on. It makes us reduce the time of developing a control system and also can be simple size controller. The vector control algorithm for instantaneous torque control and SVPWM algorithm by offset voltage methods is adopted and we got the satisfactory results.

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