• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5C
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• pp.454-463
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• 2010

After the efficiency of H.264 video compression has been announced, it replaced MPEG-2 standard in several applications. So transcoding methods of MPEG-2 to H.264 have been studying because there are variety devices and contents followed by MPEG-2. Although H.264 supported various service such as IPTV, DMB, digital broadcasting etc, but users using MPEG-2 devices cannot accessible to them. This paper propose H.264 to MPEG-2 transcoding for users of MPEG-2 devices without displacement H.264. The proposed method predicted a motion vector for MPEG-2 encoder after it extracted from motion vectors of variable blocks in H.264 to improve processing time. Also it predicted a optimal motion vector using modified boundary matching algorithm after grasped a special character for boundary and background of object. The experimental results from proposed method show a considerable reduction in processing time, as much as 68% averagely, with a small objective quality reduction in PSNR.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.61-68
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• 2015

Mobile ad hoc networks (MANETs) are self-organized dynamic networks populated by mobile nodes. This paper presents the improved cross-layer approach to complement the recent works for video transmission services on MANET. We use a statistical design of experiment and analysis in order to investigate interactions between major factors of each layer effectively with minimizing ns-3 simulation run time. The proposed cross-layer approach considers MANET protocol layers (i.e., physical, network and transmission layers) and an application layer (i.e., a video encoder) as factors simultaneously. In addition, the approach defines an objective video quality metric as a response variable. The result of this paper can be applicable as a preliminary research to design an optimized video transmission application which has ability to adjust controllable factors to dynamic uncontrollable factors.

• Journal of the Korea Society of Computer and Information
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• v.15 no.9
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• pp.1-8
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• 2010

The key challenge in HW/SW co-design is how to choose the appropriate HW/SW partitioning from the vast array of possible options in the mapping set. In this paper we present a unique and efficient approach for addressing this problem known as Customized Heuristic Algorithm for Reducing Mapping Sets(CHARMS). CHARMS uses sensitivity to individual task computational complexity as well the computed weighted values of system performance influencing metrics to streamline the mapping sets and extract the most optimal cases. Using H.263 encoder, we show that CHARMS sieves out 95.17% of the sub-optimal mapping sets, leaving the designer with 4.83% of the best cases to select from for run-time implementation.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.367-374
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• 2021

Stock price prediction is a subject of research in various fields such as economy, statistics, computer engineering, etc. In recent years, researches on predicting the movement of stock prices by learning artificial intelligence models from various indicators such as basic indicators and technical indicators have become active. This study proposes a deep learning model that predicts the ups and downs of KOSPI from overseas indices such as S&P500, past KOSPI indices, and trading trends by KOSPI investors. The proposed model extracts a latent variable using a stacked auto-encoder to predict stock price fluctuations, and predicts the fluctuation of the closing price compared to the market price of the day by learning an LSTM suitable for learning time series data from the extracted latent variable to decide to buy or sell based on the value. As a result of comparing the returns and prediction accuracy of the proposed model and the comparative models, the proposed model showed better performance than the comparative models.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.136-144
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• 2021

The purpose of this study was to develop and verify a precision transmission error measurement system for a gear pair. The transmission error measurement system of the gear pair was developed as a measurement unit, signal processing unit, and signal analysis unit. The angular displacement for calculating the transmission error of the gear pair was measured using an encoder. The signal amplification, interpolation, and transmission error calculation of the measured angular displacement were conducted using a field-programmable gate array (FPGA) and a real-time processor. A high-pass filter (HPF) was applied to the calculated transmission error from the real-time processor. The transmission error measurement test was conducted using a gearbox, including the master gear pair. The same test was repeated three times in the clockwise and counterclockwise directions, respectively, according to the load conditions (0 - 200 N·m). The results of the gear transmission error tests showed similar tendencies, thereby confirming the stability of the system. The measured transmission error was verified by comparing it with the transmission error analyzed using commercial software. The verification showed a slight difference in the transmission error between the methods. In a future study, the measurement and analysis method of the developed precision transmission error measurement system in this study may possibly be used for gear design.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.337-346
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• 2021

Detection of abnormal signal generally can be done by using features of normal signals as main information because of data imbalance. This paper propose an efficient method for abnormal signal detection using parallel AutoEncoder (AE) which can use features of abnormal signals as well. The proposed Parallel AE (PAE) is composed of a normal and an abnormal reconstructors having identical AE structure and train features of normal and abnormal signals, respectively. The PAE can effectively solve the imbalanced data problem by sequentially training normal and abnormal data. For further detection performance improvement, additional binary classifier can be added to the PAE. Through experiments using public acoustic data, we obtain that the proposed PAE shows Area Under Curve (AUC) improvement of minimum 22 % at the expenses of training time increased by 1.31 ~ 1.61 times to the single AE. Furthermore, the PAE shows 93 % AUC improvement in detecting abnormal underwater acoustic signal when pre-trained PAE is transferred to train open underwater acoustic data.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.660-669
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• 2019

Recently, with the development of three-dimensional scanning devices and multi-dimensional array cameras, research is continuously conducted on techniques for handling three-dimensional data in application fields such as AR (Augmented Reality) / VR (Virtual Reality) and autonomous traveling. In particular, in the AR / VR field, content that expresses 3D video as point data has appeared, but this requires a larger amount of data than conventional 2D images. Therefore, in order to serve 3D point cloud content to users, various technological developments such as highly efficient encoding / decoding and storage, transfer, etc. are required. In this paper, V-PCC bit stream created using V-PCC encoder proposed in MPEG-I (MPEG-Immersive) V-PCC (Video based Point Cloud Compression) group, It is defined by the MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard, and provides to be composed of segments. Also, in order to provide the user with the information of the 3D coordinate system, the depth information parameter of the signaling message is additionally defined. Then, we design a verification platform to verify the technology proposed in this paper, and confirm it in terms of the algorithm of the proposed technology.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.35-45
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• 2018

Motion Estimation(ME) has been developed to reduce the redundant data in digital video signal. ME is an important part of video encoding system, However, it requires huge computational complexity of the encoder part, and fast motion search methods have been proposed to reduce huge complexity. Multi- view video is obtained by capturing on a three-dimensional scene with many cameras at different positions and its complexity increases in proportion to the number of cameras. In this paper, we proposed an efficient motion method which chooses a search pattern adaptively by using the temporal-spatial correlation of the block and the characteristics of the block. Experiment results show that the computational complexity reduction of the proposed method over TZ search method and FS method can be up to 70~75% and 99% respectively while keeping similar image quality and bit rates.

• Design & Manufacturing
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• v.13 no.1
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• pp.55-60
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• 2019

Smart-phone in the recently released high-end applied to the camera module is equipped with the most features auto focusing camera module. Also, auto focusing camera module is divided into voice coil motor, encoder, and piezo according to type of motion mechanism. Auto focusing camera module is composed of voice coil motor (VCM) as an actuator and leaf spring as a guide and suspension. VCM actuator is made of magnet, yoke as a metal, and coil as a copper wire. Recently, the assembly as yoke and magnet is made by human resources. These process has a long process time and it is difficult to secure quality. Also, These process is not economical in cost, and productivity is reduced. Therefore, an automatic assembly as yoke and magnet is needed in the present process. In this paper, we have developed an automatic assembly device that can automatically assemble yoke and magnet, and performed verifying performance. Therefore, by using the developed automatic assembly device, it is possible to increase the productivity and reduce the production cost.

• Journal of The Korean Astronomical Society
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• v.51 no.6
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• pp.207-214
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• 2018

A coelostat is often used for solar observations, because it corrects the image rotation automatically by guiding sunlight into a fixed telescope with two plane mirrors. For the purposes of education and spectroscopic observation, the solar group at Seoul National University (SNU) plans to develop the SNU coelostat (SNUC) and install it in the SNU Astronomical Observatory (SAO). Requirements of the SNUC are < 1" positioning accuracy with 30 cm beam size on the entrance pupil in the compact dome. To allow for installation in the small dome, we design a compact slope type coelostat with a 45 cm primary plane mirror and a 39 cm secondary plane mirror. The motion of the SNUC is minimized by fixing the position of the slope frame. Numerical simulations of the available observational time of the designed coelostat shows that the sun can be observed ay all times from June to early August and at least three hours in other months. Since the high accuracy driving motors installed in the SNUC can be affected by external environment factors such as humidity and temperature variations, we design a prototype to test the significance of these effects. The prototype consists of a 20 cm primary plane mirror, a 1 m slope rail, a direct drive motor, a ballscrew, a linear motion guide, an AC servo motor, a reduction gear and a linear encoder. We plan to control and test the accuracy of the prototype with varying atmospheric conditions in early 2019. After testing the prototype, the SNUC will be manufactured and installed in SAO by 2020.