• Title/Summary/Keyword: Vector Architecture

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Architecture Exploration of Optimal Many-Core Processors for a Vector-based Rasterization Algorithm (래스터화 알고리즘을 위한 최적의 매니코어 프로세서 구조 탐색)

  • Son, Dong-Koo;Kim, Cheol-Hong;Kim, Jong-Myon
    • IEMEK Journal of Embedded Systems and Applications
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    • v.9 no.1
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    • pp.17-24
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    • 2014
  • In this paper, we implement and evaluate the performance of a vector-based rasterization algorithm for 3D graphics by using a SIMD (single instruction multiple data) many-core processor architecture. In addition, we evaluate the impact of a data-per-processing elements (DPE) ratio that is defined as the amount of data directly mapped to each processing element (PE) within many-core in terms of performance, energy efficiency, and area efficiency. For the experiment, we utilize seven different PE configurations by varying the DPE ratio (or the number PEs), which are implemented in the same 130 nm CMOS technology with a 500 MHz clock frequency. Experimental results indicate that the optimal PE configuration is achieved as the DPE ratio is in the range from 16,384 to 256 (or the number of PEs is in the range from 16 and 1,024), which meets the requirements of mobile devices in terms of the optimal performance and efficiency.

Small-Size Induction Machine Equivalent Circuit Including Variable Stray Load and Iron Losses

  • Basic, Mateo;Vukadinovic, Dinko
    • Journal of Electrical Engineering and Technology
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    • v.13 no.4
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    • pp.1604-1613
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    • 2018
  • The paper presents the equivalent circuit of an induction machine (IM) model which includes fundamental stray load and iron losses. The corresponding equivalent resistances are introduced and modeled as variable with respect to the stator frequency and flux. Their computation does not require any tests apart from those imposed by international standards, nor does it involve IM constructional details. In addition, by the convenient positioning of these resistances within the proposed equivalent circuit, the order of the conventional IM model is preserved, thus restraining the inevitable increase of the computational complexity. In this way, a compromise is achieved between the complexity of the analyzed phenomena on the one hand and the model's practicability on the other. The proposed model has been experimentally verified using four IMs of different efficiency class and rotor cage material, all rated 1.5 kW. Besides enabling a quantitative insight into the impact of the stray load and iron losses on the operation of mains-supplied and vector-controlled IMs, the proposed model offers an opportunity to develop advanced vector control algorithms since vector control is based on the fundamental harmonic component of IM variables.

Classification method for failure modes of RC columns based on key characteristic parameters

  • Yu, Bo;Yu, Zecheng;Li, Qiming;Li, Bing
    • Structural Engineering and Mechanics
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    • v.84 no.1
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    • pp.1-16
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    • 2022
  • An efficient and accurate classification method for failure modes of reinforced concrete (RC) columns was proposed based on key characteristic parameters. The weight coefficients of seven characteristic parameters for failure modes of RC columns were determined first based on the support vector machine-recursive feature elimination. Then key characteristic parameters for classifying flexure, flexure-shear and shear failure modes of RC columns were selected respectively. Subsequently, a support vector machine with key characteristic parameters (SVM-K) was proposed to classify three types of failure modes of RC columns. The optimal parameters of SVM-K were determined by using the ten-fold cross-validation and the grid-search algorithm based on 270 sets of available experimental data. Results indicate that the proposed SVM-K has high overall accuracy, recall and precision (e.g., accuracy>95%, recall>90%, precision>90%), which means that the proposed SVM-K has superior performance for classification of failure modes of RC columns. Based on the selected key characteristic parameters for different types of failure modes of RC columns, the accuracy of SVM-K is improved and the decision function of SVM-K is simplified by reducing the dimensions and number of support vectors.

Estimating Hydrodynamic Coefficients of Real Ships Using AIS Data and Support Vector Regression

  • Hoang Thien Vu;Jongyeol Park;Hyeon Kyu Yoon
    • Journal of Ocean Engineering and Technology
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    • v.37 no.5
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    • pp.198-204
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    • 2023
  • In response to the complexity and time demands of conventional methods for estimating the hydrodynamic coefficients, this study aims to revolutionize ship maneuvering analysis by utilizing automatic identification system (AIS) data and the Support Vector Regression (SVR) algorithm. The AIS data were collected and processed to remove outliers and impute missing values. The rate of turn (ROT), speed over ground (SOG), course over ground (COG) and heading (HDG) in AIS data were used to calculate the rudder angle and ship velocity components, which were then used as training data for a regression model. The accuracy and efficiency of the algorithm were validated by comparing SVR-based estimated hydrodynamic coefficients and the original hydrodynamic coefficients of the Mariner class vessel. The validated SVR algorithm was then applied to estimate the hydrodynamic coefficients for real ships using AIS data. The turning circle test wassimulated from calculated hydrodynamic coefficients and compared with the AIS data. The research results demonstrate the effectiveness of the SVR model in accurately estimating the hydrodynamic coefficients from the AIS data. In conclusion, this study proposes the viability of employing SVR model and AIS data for accurately estimating the hydrodynamic coefficients. It offers a practical approach to ship maneuvering prediction and control in the maritime industry.

Comparison and Evaluation of Vector and Raster Methods for Mobile Map Services (모바일 맵 서비스를 위한 벡터와 래스터 기법의 비교 평가)

  • Choi Jin-Oh
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.8
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    • pp.1459-1464
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    • 2006
  • There are two approaches to construct mobile GIS, Vector and Raster methods, according to the map data transformation format from server to mobile client. Each method requires a different implementation architecture of server and client modules for mobile map services. And each have advantages and disadvantages at the different aspects. This thesis implements these two approaches, thus, compares the each merits, by experiments. They include the transmission performance, map quality, and so on.

Comparison and Evaluation of Vector and Raster Methods in Mobile Map Services (모바일 지도 서비스에서 벡터와 래스터 기법의 비교 평가)

  • 최진오
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.10a
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    • pp.464-467
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    • 2003
  • There are two approaches to construct mobile GIS, Vector and Raster methods, according to the map data transformation format from server to mobile client. Each method requires a different implementation architecture of server and client modules for mobile map services. And each have advantages and disadvantages at the different aspects. This thesis implements these two approaches, thus, compares the each merits, by experiments. They include the transmission performance, map quality, and so on.

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Multi-stage Speech Recognition Using Confidence Vector (신뢰도 벡터 기반의 다단계 음성인식)

  • Jeon, Hyung-Bae;Hwang, Kyu-Woong;Chung, Hoon;Kim, Seung-Hi;Park, Jun;Lee, Yun-Keun
    • MALSORI
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    • no.63
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    • pp.113-124
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    • 2007
  • In this paper, we propose a use of confidence vector as an intermediate input feature for multi-stage based speech recognition architecture to improve recognition accuracy. A multi-stage speech recognition structure is introduced as a method to reduce the computational complexity of the decoding procedure and then accomplish faster speech recognition. Conventional multi-stage speech recognition is usually composed of three stages, acoustic search, lexical search, and acoustic re-scoring. In this paper, we focus on improving the accuracy of the lexical decoding by introducing a confidence vector as an input feature instead of phoneme which was used typically. We take experimental results on 220K Korean Point-of-Interest (POI) domain and the experimental results show that the proposed method contributes on improving accuracy.

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A Adaptive Motion Estimation Using Spatial correlation and Slope of Motion vector for Real Time Processing and Its Architecture (실시간 적응형 Motion Estimation 알고리듬 및 구조 설계)

  • 이준환;김재석
    • Proceedings of the IEEK Conference
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    • 2000.11d
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    • pp.57-60
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    • 2000
  • This paper presents a new adaptive fast motion estimation algorithm along with its architecture. The conventional algorithm such as full - search algorithm, three step algorithm have some disadvantages which are related to the amount of computation, the quality of image and the implementation of hardware, the proposed algorithm uses spatial correlation and a slope of motion vector in order to reduce the amount of computation and preserve good image quality, The proposed algorithm is better than the conventional Block Matching Algorithm(BMA) with regard to the amount of computation and image quality. Also, we propose an efficient at chitecture to implement the proposed algorithm. It is suitable for real time processing application.

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High-Performance and Low-Complexity Image Pre-Processing Method Based on Gradient-Vector Characteristics and Hardware-Block Sharing

  • Kim, Woo Suk;Lee, Juseong;An, Ho-Myoung;Kim, Jooyeon
    • Transactions on Electrical and Electronic Materials
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    • v.18 no.6
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    • pp.320-322
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    • 2017
  • In this paper, a high-performance, low-area gradient-magnitude calculator architecture is proposed, based on approximate image processing. To reduce the computational complexity of the gradient-magnitude calculation, vector properties, the symmetry axis, and common terms were applied in a hardware-resource-shared architec-ture. The proposed gradient-magnitude calculator was implemented using an Altera Cyclone IV FPGA (EP4CE115F29) and the Quartus II v.16 device software. It satisfied the output-data quality while reducing the logic elements by 23% and the embedded multipliers by 76%, compared with previous work.

A Self Creating and Organizing Neural Network (자기 분열 및 구조화 신경회로망)

  • 최두일;박상희
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.5
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    • pp.533-540
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    • 1992
  • The Self Creating and Organizing (SCO) is a new architecture and one of the unsupervized learning algorithm for the artificial neural network. SCO begins with only one output node which has a sufficiently wide response range, and the response ranges of all the nodes decrease automatically whether adapting the weights of existing node or creating a new node. It is compared to the Kohonen's Self Organizing Feature Map (SOFM). The results show that SCONN has lots of advantages over other competitive learning architecture.

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