• Journal of Power Electronics
• /
• v.17 no.4
• /
• pp.1048-1057
• /
• 2017

An indirect matrix converter (IMC) is a modern power generation system that enables a direct ac/ac conversion without the need for any bulky and limited lifetime electrolytic capacitor. This system also allows four-quadrant operation, generation of sinusoidal output voltage waveforms with variable frequency and amplitude, and control of input power factor. This study proposes a pulse-width modulation-based sliding-mode controller to achieve unity input-power factor operation of the IMC independently of the active power exchanged with the grid, as well as a fast dynamic response. The designed equivalent control law determines, at each sampling period, the appropriate q-axis component of the modulated input current to be injected into the grid through the LC input filter. An integral term of the error is included in the expression of the sliding surface to increase the accuracy of the control method. A double space vector modulation method is used to synthesize the direction of the space vector of the input currents as required by the sliding-mode controller and the space vectors of the target output voltages. Simulation and experimental results are provided to show the effectiveness and evaluate the performance of the proposed control method.

• The KIPS Transactions:PartD
• /
• v.11D no.4
• /
• pp.835-844
• /
• 2004

Recently, the location-based service for moving customers is becoming one of the most important service in mobile communication area. For moving object applications, there are lots of update operations and such update loads are concentrated on some particular area unevenly. Range queries, whose range can be window or circular, are the most essential query types in LBS. We need to distinguish completely contained cells from partially contained cells in those range queries. Also, it is necessary to consider temporal dimension to filter out qualifying objects correctly. In this paper, we adopt two-level index structures with fixed grid file structures in the second level, which are designed to minimize update operations. We propose a spatial ceil filtering method using VP filtering and a combined spatio-temporal filtering method using time gone concepts. Some experimental results are shown for various window queries and circular queries with different filtering combinations to show the performance tradeoffs of the proposed methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.6
• /
• pp.1129-1135
• /
• 2007

Human face detection technique plays an important role in computer vision area. It has lots of applications such as face recognition, video surveillance, human computer interface, face image database management, and querying image databases. In this paper, a fast face detection approach using Principal Component Analysis (PCA) and Support Vector Machines (SVM) is proposed based on the previous study on face detection technique. In the proposed detection system, firstly it filter the face potential area using statistical feature which is generated by analyzing the local histogram distribution the detection process is speeded up by eliminating most of the non-face area in this step. In the next step, PCA feature vectors are generated, and then detect whether there are faces present in the test image using SVM classifier. Finally, store the detection results and output the results on the test image. The test images in this paper are from CMU face database. The face and non-face samples are selected from the MIT data set. The experimental results indicate the proposed method has good performance for face detection.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.10
• /
• pp.1845-1851
• /
• 2007

Background noise and room reverberation are two causes of degradation in speech in listening situations. Many algorithms developed to enhance reverberant speech. In this paper we propose a dereverberation method for enhancement of speech using modified the linear prediction(LP) residual in reverberant room condition. The proposed dereberberation method based on the fact that the signification excitation of the vocal tract system takes place at the instant of glottal closure in voiced speech. Our method used delay information form each sensor, and we need reverberant signals from 3 sensors. We obtain a new LP residual signal using modified IP residual combination which derived form weighting of the LP residual and the Hilbert transform of LP residual. The nature of the coherently added Hilbert envelop has several large amplitude spikes because of the effects of noise and reverberation. This residual of the clean speech is used to excite the time-varying all-pole filter to obtain the enhanced speech. We achieved simulation of proposed algorithm for performance analysis in reverberation environment. The proposed algorithm improves substantially the quality of reverberant speech.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.10
• /
• pp.403-410
• /
• 2019

Image de-snowing aims at eliminating the negative influence by snow particles and improving scene understanding in images. In this paper, a perceptual generative adversarial network based a single image snow removal method is proposed. The residual U-Net is designed as a generator to generate the snow free image. In order to handle various sizes of snow particles, the inception module with different filter kernels is adopted to extract multiple resolution features of the input snow image. Except the adversarial loss, the perceptual loss and total variation loss are employed to improve the quality of the resulted image. Experimental results indicate that our method can obtain excellent performance both on synthetic and realistic snow images in terms of visual observation and commonly used visual quality indices.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.22 no.5
• /
• pp.599-606
• /
• 2019

The Arena Fragmentation Test(AFT) is one of the important tasks for designing a high-explosive warhead. In order to measure the statistics of a warhead in the test, fragments of a warhead that penetrate steel plates are detected by using complex and expensive measuring equipment. In this paper, instead of using specific hardware to measure the statistics of a warhead, we propose to use an image processing based object detection algorithm to detect fragments in AFT. To this end, we use a hard-thresholding method with a brightness feature and apply a morphology filter to remove noise components. We also propose a simple yet effective temporal filtering method to detect only the first penetrating fragments. We show that the performance of the proposed method is comparable to that of a hardware system under the same experimental conditions. Furthermore, the proposed method can produce better results in terms of finding exact positions of fragments.

• Industry Promotion Research
• /
• v.6 no.4
• /
• pp.1-9
• /
• 2021

The purpose of this study is to manufacture lightweight aggregates for recycling water treatment sludge, to identify the physical properties of the aggregates, and present a method of utilizing the manufactured lightweight aggregates. The chemical composition and thermal properties were examined via a raw materials analysis. The aggregate examined here was fired by the rapid sintering method and the single-particle density and water absorption rate were measured. Water treatment sludge has high ignition loss and high fire resistance. When 30wt% of purified sludge was added, the single-particle density of the aggregates was in the range of 0.8~1.2g/cm³ at a temperature of 1,150~1,200℃. At temperatures of 1200℃ or higher, ultra-light aggregates having a single-particle density of 0.8 or less could be produced. When applied to concrete by replacing the general aggregate in the concrete, a specimen having strength values of 200 to 450 kgf/cm² on 28 days was obtained, and when applied as a filter material, the performance was equal to or higher than that of ordinary sand.

• International Journal of Computer Science & Network Security
• /
• v.21 no.12spc
• /
• pp.463-468
• /
• 2021

Single image super-resolution (SISR) is an image processing technique, and its main target is to reconstruct the high-quality or high-resolution (HR) image from the low-quality or low-resolution (LR) image. Currently, deep learning-based convolutional neural network (CNN) image super-resolution approaches achieved remarkable improvement over the previous approaches. Furthermore, earlier approaches used hand designed filter to upscale the LR image into HR image. The design architecture of such approaches is easy, but it introduces the extra unwanted pixels in the reconstructed image. To resolve these issues, we propose novel deep learning-based approach known as Lightweight deep CNN-based approach for Single Image Super-Resolution (LDCSIR). In this paper, we propose a new architecture which is inspired by ResNet with Inception blocks, which significantly drop the computational cost of the model and increase the processing time for reconstructing the HR image. Compared with the other state of the art methods, LDCSIR achieves better performance in terms of quantitively (PSNR/SSIM) and qualitatively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.12 no.3
• /
• pp.186-191
• /
• 2019

In this paper, we propose a implementation approach of the high-speed feature extraction algorithm. The proposed method is based on the block type classification algorithm which reduces the computation time when target macro block is divided to smooth block type that has no image features. It is quantitatively identified that occurs at 29.5% of the total image using 200 standard test images with $64{\times}64$ macro block size. This means that within a standard test image containing various image information, 29.5% can reduce the complexity of the operation. When the proposed approach is applied to the Canny edge detection, the required latency of the edge detection can be completely eliminated, such as 2D derivative filter, gradient magnitude/direction computation, non-maximal suppression, adaptive threshold calculation, hysteresis thresholding. Also, it is expected that operation time of the feature detection can be reduced by applying block type classification algorithm to various feature extraction algorithms in this way.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.18 no.1
• /
• pp.56-73
• /
• 2019

Probe-based systems have been gaining popularity in advanced traveler information systems. However, the high possibility of providing inaccurate travel-time information due to the inherent time-lag phenomenon is still an important issue to be resolved. To mitigate the time-lag problem, different prediction techniques have been applied, but the techniques are generally regarded as less effective for travel times with high variability. For this reason, current 5-min aggregated data have been commonly used for real-time travel-time provision on highways with high travel-time fluctuation. However, the 5-min aggregation interval itself can further increase the time-lags in the real-time travel-time information equivalent to 5 minutes. In this study, a new scheme that uses both individual probe and 5-min aggregated travel times is suggested to provide reliable real-time travel-time information. The scheme utilizes individual probe data under congested conditions and 5-min aggregated data under uncongested conditions, respectively. As a result of an evaluation with field data, the proposed scheme showed the best performance, with a maximum reduction in travel-time error of 18%.