• Korean Journal of Cognitive Science
• /
• v.23 no.3
• /
• pp.295-322
• /
• 2012

In this paper, we cluster similar word senses applying vector space model and HAL (Hyperspace Analog to Language). HAL measures corelation among words through a certain size of context (Lund and Burgess 1996). The similarity measurement between a word pair is cosine similarity based on the vector space model, which reduces distortion of space between high frequency words and low frequency words (Salton et al. 1975, Widdows 2004). We use PCA (Principal Component Analysis) and SVD (Singular Value Decomposition) to reduce a large amount of dimensions caused by similarity matrix. For sense similarity clustering, we adopt supervised and non-supervised learning methods. For non-supervised method, we use clustering. For supervised method, we use SVM (Support Vector Machine), Naive Bayes Classifier, and Maximum Entropy Method.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.33 no.2
• /
• pp.223-233
• /
• 2023

Gauss Sieve is an algorithm for solving SVP and requires exponential time and space complexity. The terminationcondition of the Sieve is determined by the size of the constructed list and the number of collisions related to space complexity. The term 'collision' refers to the state in which the sampled vector is reduced to the vector that is already inthe list. if collisions occur more than a certain number of times, the algorithm terminates. When executing previous algorithms, we noticed that unnecessary operations continued even after the shortest vector was found. This means that the existing termination condition is set larger than necessary. In this paper, after identifying the point where unnecessary operations are repeated, optimization is performed on the number of operations required. The tests are conducted by adjusting the threshold of the collision that becomes the termination condition and the distribution in whichthe sample vector is generated. According to the experiments, the operation that occupies the largest proportion decreased by62.6%. The space and time complexity also decreased by 4.3 and 1.6%, respectively.

• Journal of Korea Multimedia Society
• /
• v.18 no.10
• /
• pp.1205-1215
• /
• 2015

Efficient multi-view coding techniques are needed to reduce the complexity of multi-view video which increases in proportion to the number of cameras. To reduce the complexity and maintain image quality and bit-rates, an motion estimation method and temporal prediction structure are proposed in this paper. The proposed motion estimation method exploits the characteristic of motion vector distribution and the motion direction and motion size of the block to place search points and decide the search patten adaptively. And the proposed prediction structure divides every GOP to decide the maximum index of hierarchical B layer and the number of pictures of each B layer. Experiment results show that the complexity reduction of the proposed temporal prediction structure and motion estimation method over hierarchical B pictures prediction structure and TZ search method which are used in JMVC(Joint Multi-view Video Coding) reference model can be up to 45∼70% while maintaining similar video quality and bit rates.

• Journal of Power Electronics
• /
• v.17 no.1
• /
• pp.88-95
• /
• 2017

To reduce common-mode voltage (CMV), various reduced CMV pulse width modulation (RCMV-PWM) algorithms have been proposed, including active zero state PWM (AZSPWM) algorithms, remote state PWM (RSPWM) algorithms, and near state PWM (NSPWM) algorithms. Among these algorithms, AZSPWM algorithms can reduce CMV, but they increase the number of switchings compared to the conventional space vector PWM (CSVPWM). This paper presents a new AZSPWM algorithm for reductions in both the CMV and total number of switchings in BLAC motor drives. Since the proposed AZSPWM algorithm uses only active voltage vectors for motor control, it reduces CMV by 1/3 compared to CSVPWM. The proposed AZSPWM algorithm also reduces the total number of switchings compared to existing AZSPWM algorithms by eliminating the switchings required from one sector to the next. The performance of the proposed algorithm is verified by analyses, simulations, and experimental results.

• Journal of Power Electronics
• /
• v.16 no.5
• /
• pp.1851-1860
• /
• 2016

The traction motors in electric multiple unit (EMU) trains are powered by AC-DC-AC converters, and the DC link voltage is generated by single phase PWM converters, with a fluctuation component under twice the frequency of the input catenary AC grid, which causes fluctuations in the motor torque and current. Traditionally, heavy and low-efficiency hardware LC resonant filters parallel in the DC side are adopted to reduce the ripple effect. In this paper, an analytical model of the ripple phenomenon is derived and analyzed in the frequency domain, and a ripple control scheme compensating the slip frequency of rotor vector control systems without a hardware filter is applied to reduce the torque and current ripple amplitude. Then a relatively simple discretization method is chosen to discretize the algorithm with a high discrete accuracy. Simulation and experimental results validate the proposed ripple control strategy.

• Journal of Communications and Networks
• /
• v.12 no.1
• /
• pp.67-73
• /
• 2010

Current on-demand ad-hoc routing protocols are not appropriate for wireless mesh networks (WMNs), because flooding-based route discovery is both redundant and expensive in terms of control message overhead. In this paper, we propose an efficient on-demand routing approach with directional flooding (DF), which is suitable for the WMNs with limited mobility. In the route discovery process to reach a gateway, our DF scheme can reduce the number of route request (RREQ) packets broadcast by using a restricted directional flooding technique. Simulation results show that ad hoc on-demand distance vector (AODV) with DF (AODV-DF) can significantly reduce routing overhead by RREQ packets and enhance overall performance compared with the original AODV.

• Computers and Concrete
• /
• v.16 no.5
• /
• pp.741-757
• /
• 2015

In the last decade, several modeling approaches have been proposed and applied to estimate the high-performance concrete (HPC) slump flow. While HPC is a highly complex material, modeling its behavior is a very difficult issue. Thus, the selection and application of proper modeling methods remain therefore a crucial task. Like many other applications, HPC slump flow prediction suffers from noise which negatively affects the prediction accuracy and increases the variance. In the recent years, ensemble learning methods have introduced to optimize the prediction accuracy and reduce the prediction error. This study investigates the potential usage of bagging (Bag), which is among the most popular ensemble learning methods, in building ensemble models. Four well-known artificial intelligence models (i.e., classification and regression trees CART, support vector machines SVM, multilayer perceptron MLP and radial basis function neural networks RBF) are deployed as base learner. As a result of this study, bagging ensemble models (i.e., Bag-SVM, Bag-RT, Bag-MLP and Bag-RBF) are found superior to their base learners (i.e., SVM, CART, MLP and RBF) and bagging could noticeable optimize prediction accuracy and reduce the prediction error of proposed predictive models.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.10
• /
• pp.1930-1935
• /
• 2009

This paper deals with the torque ripple reduction of permanent magnet synchronous motor using harmonic current injection. Torque ripple of electric motor reduces system stability and performances, therefore efforts to reduce torque ripple are exerted in the design process. Torque ripple can be reduced by appropriate pole/slot combination, skew of rotor or stator, design of magnetic circuit, etc. In addition, torque ripple can be also reduced by input voltage and current, and many researches have been conducted to reduce torque ripple for six-step drive. Torque ripple reduction for current vector controlled permanent magnet synchronous motor also have been conducted and verified by investigating back emf wave form. Torque ripple reduction in this paper started from getting torque profile according to input current and electrical angle calculated by FEA, then instantaneous currents at each electrical angles for constant torque are calculated and applied to experiments. Therefore, 0% of torque ripple can be obtained theoretically with harmonic current injection. In order to maximize the effect of torque ripple reduction, a BLDC motor having high harmonic component of back emf is chosen. With sinusoidal current drive, over 100% of torque ripple is obtained initially, then 0.5 % of torque ripple is obtained by FEA using harmonic current injection. The effect is verified by experiment and the presented method can be effectively applicable to Electric Power Steering(EPS).

• Journal of Power Electronics
• /
• v.17 no.3
• /
• pp.641-652
• /
• 2017

This paper proposes a cost-effective topology to drive a three-phase open-end load based on a five-leg indirect matrix converter (IMC) and a space vector modulation (SVM) method. By sharing an inverter leg with two load terminals, the proposed topology can reduce the number of power switches when compared to topologies based on a direct matrix converter or a six-leg IMC. The new SVM method uses only the active vectors that do not produce common-mode voltage (CMV), which results in zero CMV across the load phase and significantly reduces the peak value of the CMV at the load terminal. Furthermore, the proposed drive system can increase the voltage transfer ratio up to 1.5 and provide a superior performance in terms of an output line-to-line voltage with a three-level pulse-width modulation waveform. Simulation and experimental results are given to verify the effectiveness of the proposed topology and the new SVM method.

• Wind and Structures
• /
• v.29 no.5
• /
• pp.313-321
• /
• 2019

The wind blowing at high velocity in an open storage yard leads to wind erosion and loss of material. Fence structures can be constructed around the periphery of the storage yard to reduce the erosion. The fence will cause turbulence and recirculation behind it which can be utilized to reduce the wind erosion and loss of material. A properly designed fence system will produce lesser turbulence and longer shelter effect. This paper aims to show the applicability of Support Vector Machine (SVM) to predict the recirculation length. A SVM model was built, trained and tested using the experimental data gathered from the literature. The newly developed model is compared with numerical turbulence model, in particular, modified $k-{\varepsilon}$ model along with the experimental results. From the results, it was observed that the SVM model has a better capability in predicting the recirculation length. The SVM model was able to predict the recirculation length at a lesser time as compared to modified $k-{\varepsilon}$ model. All the results are analyzed in terms of statistical measures, such as root mean square error, correlation coefficient, and scatter index. These examinations demonstrate that SVM has a strong potential as a feasible tool for predicting recirculation length.