• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.5
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• pp.430-442
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• 2013

This paper presents a fast multi-reference frame integer motion estimator for H.264/AVC. The proposed system uses the previously proposed fast multi-reference frame algorithm. The previously proposed algorithm executes a full search area motion estimation in reference frames 0 and 1. After that, the search areas of motion estimation in reference frames 2, 3 and 4 are minimized by a linear relationship between the motion vector and the distances from the current frame to the reference frames. For hardware implementation, the modified algorithm optimizes the search area, reduces the overlapping search area and modifies a division equation. Because the search area is reduced, the amount of computation is reduced by 58.7%. In experimental results, the modified algorithm shows an increase of bit-rate in 0.36% when compared with the five reference frame standard. The pipeline structure and the memory controller are also adopted for real-time video encoding. The proposed system is implemented using 0.13 um CMOS technology, and the gate count is 1089K with 6.50 KB of internal SRAM. It can encode a Full HD video ($1920{\times}1080P@30Hz$) in real-time at a 135 MHz clock speed with 5 reference frames.

• The Journal of the Acoustical Society of Korea
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• v.24 no.4
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• pp.202-209
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• 2005

The rapid development of digital media and communication network urgently brings about the need of data certification technology to protect IPR (Intellectual property right). This paper proposed a new watermarking method for embedding owner's audio signal. Because this method uses an audio signal as a watermark to be embedded, it is very useful to claim the ownership aurally. And it has the advantage of restoring audio signal modified and especially removed by image removing attacks by applying our LBX(Linear Bit-expansion) interleaving. Three basic stages of our watermarking include: 1) Encode . analogue owner's audio signal by PCM and create new digital audio watermark, 2) Interleave an audio watermark by our LBX; and 3) Embed the interleaved audio watermark in the low frequency band on DTn (Discrete Haar Wavelet Transform) of image. The experimental results prove that this method is resistant to lossy JPEG compression as standard image compression and especially to cropping and rotation which remove a part of Image.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.235-242
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• 2008

To improve video quality and coding efficiency, H.264/AVC adopted an adaptive rate control. But this method has a problem as it cannot predict an accurate quantization parameter(QP) for the first frame. The first QP is decided among four constant values by using encoder input parameters. It does not consider encoding bits, results in significant fluctuation of the image quality and decreases the average quality of the whole coded sequence. In this paper, we propose a new algorithm for the first frame QP decision in the H.264/AVC encoder. The QP is decided by the existing algorithm and the first frame is encoded. According to the encoded bits, the new initial QP is decided. We can predict optimal value because there is a linear relationship between encoded bits and the new initial QP. Next, we re-encode the first frame using the new initial QP. Experimental results show that the proposed algorithm not only achieves better quality than the state of the art algorithm, but also adopts a rate control forthe sequence that was impossible with the existing algorithm. By reducing fluctuation, subjective quality also improved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.83-87
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• 1995

The implementation of the voice dodec is imjplemented by using TMS320C30, which is the floating point DSP chip from Texas Instrument. QCELP (Qualcomm Code Excited Linear Prediction) is used to encode and decode the voice. The QCELP code is implemented by the TMS320C30 C-dode. The DSP board is controlled by the PC. The PC program tranfors the voice file from and to the DSP board, which is also implemented by C-code. The voice is encoded by the DSP board and the encoded data is transferred to PC to be stored as a file. To hear the voice. the voice data file is sent to DSP board and decoded to synthesize audible voice. Two flags are used by both programs to notify the status of the operation. By checking the flags, DSP and PC decides when the voice data is transferred between them.

• Journal of Microbiology and Biotechnology
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• v.29 no.1
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• pp.37-43
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• 2019

The gene encoding an ${\alpha}-{\text\tiny{L}}-arabinofuranosidase$ (BvAF) GH51 from Bacillus velezensis FZB42 was cloned and expressed in Escherichia coli. The corresponding open reading frame consists of 1,491 nucleotides which encode 496 amino acids with the molecular mass of 56.9 kDa. BvAF showed the highest activity against sugar beet (branched) arabinan in 50 mM sodium acetate buffer (pH 6.0) at $45^{\circ}C$. However, it could hardly hydrolyze debranched arabinan and arabinoxylans. The time-course hydrolyses of branched arabinan and arabinooligosaccharides (AOS) revealed that BvAF is a unique exo-hydrolase producing exclusively ${\text\tiny{L}}-arabinose$. BvAF could cleave ${\alpha}-(1,2)-$ and/or ${\alpha}-(1,3)-{\text\tiny{L}}-arabinofuranosidic$ linkages of the branched substrates to produce the debranched forms of arabinan and AOS. Although the excessive amount of BvAF could liberate ${\text\tiny{L}}-arabinose$ from linear AOS, it was extremely lower than that on branched AOS. In conclusion, BvAF is the arabinan-specific exo-acting ${\alpha}-{\text\tiny{L}}-arabinofuranosidase$ possessing high debranching activity towards ${\alpha}-(1,2)-$ and/or ${\alpha}-(1,3)-linked$ branches of arabinan, which can facilitate the successive degradation of arabinan by $endo-{\alpha}-(1,5)-{\text\tiny{L}}-arabinanase$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Investigative Magnetic Resonance Imaging
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• v.23 no.3
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• pp.179-201
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• 2019

Portable low-cost magnetic resonance imaging (MRI) systems have the potential to enable "point-of-care" and timely MRI diagnosis, and to make this imaging modality available to routine scans and to people in underdeveloped countries and areas. With simplicity, no maintenance, no power consumption, and low cost, permanent magnets/magnet arrays/magnet assemblies are attractive to be used as a source of static magnetic field to realize the portability and to lower the cost for an MRI scanner. However, when taking the canonical Fourier imaging approach and using linear gradient fields, homogeneous fields are required in a scanner, resulting in the facts that either a bulky magnet/magnet array is needed, or the imaging volume is too small to image an organ if the magnet/magnet array is scaled down to a portable size. Recently, with the progress on image reconstruction based on non-linear gradient field, static field patterns without spatial linearity can be used as spatial encoding magnetic fields (SEMs) to encode MRI signals for imaging. As a result, the requirements for the homogeneity of the static field can be relaxed, which allows permanent magnets/magnet arrays with reduced sizes, reduced weight to image a bigger volume covering organs such as a head. It offers opportunities of constructing a truly portable low-cost MRI scanner. For this exciting potential application, permanent magnets/magnet arrays have attracted increased attention recently. A magnet/magnet array is strongly associated with the imaging volume of an MRI scanner, image reconstruction methods, and RF excitation and RF coils, etc. through field patterns and field homogeneity. This paper offers a review of permanent magnets and magnet arrays of different kinds, especially those that can be used for spatial encoding towards the development of a portable and low-cost MRI system. It is aimed to familiarize the readers with relevant knowledge, literature, and the latest updates of the development on permanent magnets and magnet arrays for MRI. Perspectives on and challenges of using a permanent magnet/magnet array to supply a patterned static magnetic field, which does not have spatial linearity nor high field homogeneity, for image reconstruction in a portable setup are discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.703-710
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• 2016

In robotics research, accurate estimation of current robot position is important to achieve motion control of a robot. In this research, we focus on a sensor fusion method to provide improved position estimation for a wheeled mobile robot, considering two different sensor measurements. In this case, we fuse camera-based vision and encode-based odometry data using Kalman filter techniques to improve the position estimation of the robot. An external camera-based vision system provides global position coordinates (x, y) for the mobile robot in an indoor environment. An internal encoder-based odometry provides linear and angular velocities of the robot. We then use the position data estimated by the Kalman filter as inputs to the motion controller, which significantly improves performance of the motion controller. Finally, we experimentally verify the performance of the proposed sensor fused position estimation and motion controller using an actual mobile robot system. In our experiments, we also compare the Kalman filter-based sensor fused estimation with two different single sensor-based estimations (vision-based and odometry-based).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1908-1924
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• 2001

Interoperability and inter-working in the various network and media environment with different technology background is very important to enlarge the opportunity of service access and to increase the competitive power of service. The ITU-T and advanced counties are planning ahead for provision of GII enabling user to access advanced global communication services supporting multimedia communication applications, embracing all modes of information. In this paper, we especially forced the heterogeneity of end user applications for multimedia networking. The heterogeneity has several technical aspects, like different medium access methods, heterogeneous coding algorithms for audio-visual data and so on. Among these elements, we have been itemized bit rate shaping algorithm on the compressed moving video. Previous manipulations of video has been done on the uncompressed signal domain. That is, compressed video should be converted to linear PCM signal. To do such a procedures, we should decode, manipulate and then encode the video to compressed signal once again. The traditional approach for processing the video signa1 has several critical weak points, requiring complexity to implement, degradation of image quality and large processing delay. The bit rate shaping algorithm proposed in this paper process the manipulation of moving video on the completely compressed domain to cope with above deficit. With this algorithms. we could realized efficient video bit rate shaping and the result of software simulation shows that this method has significant advantage than that of pixel oriented algorithms.