• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.1-7
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• 2011

Recently, various researches have been proposed to accelerate GPU-based volume ray-casting. However, those researches may cause several problems such as bottleneck of data transmission between CPU and GPU, requirement of additional video memory for hierarchical structure and increase of processing time whenever opacity transfer function changes. In this paper, we propose an efficient GPU-based empty space skipping technique to solve these problems. We store maximum density in a brick of volume dataset on a vertex element. Then we delete vertices regarded as transparent one by opacity transfer function in geometry shader. Remaining vertices are used to generate bounding boxes of non-transparent area that helps the ray to traverse efficiently. Although these vertices are independent on viewing condition they need to be reproduced when opacity transfer function changes. Our technique provides fast generation of opaque vertices for interactive processing since the generation stage of the opaque vertices is running in GPU pipeline. The rendering results of our algorithm are identical to the that of general GPU ray-casting, but the performance can be up to more than 10 times faster.

• Journal of Nutrition and Health
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• v.38 no.3
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• pp.251-258
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• 2005

The purposes of this study were to conceptualize the Home Meal Replacement (HMR) in Korea and to gather professionals' opinions of prospect and task for HMR industry in Korea. A total of 67 experts participated in a three round survey by Delphi technique, which was used to integrate and share the each expert's professional idea. According to the result, HMR was translated into 'Gajeongsiksa daeyongsik' in Korean and given definition to 'a meal taken directly or through brief cooking process at home by purchasing ready to eat or ready to end-cook type of food'. As the result of categorizing HMR products of Korean food, 'I. Ready to eat' such as side dishes, kimchi, salad, sandwich, kimbab, and so on and 'II. Ready to heat' such as rice, porridge, retort food (soup, broth, curry, spaghetti, etc.), frozen pizza, grilled food, jabchae, instant soup, and so on were construed in a limited sense of the HMR. In addition, 'III. Ready to end-cook' such as frozen dumpling, frozen pork cutlet, seasoned meat, powder-type soup, and so on as well as these two kinds were interpreted in a broad sense of the HMR. In the prospect of HMR industry in Korea, the Korean HMR industry would develop continuously accompanied by increasing of consumers using HMR products. Introduction and generalization of HMRs would serve the convenience for meal preparation and then influence the change of home meal pattern. Nevertheless, it was concerned about that using HMRs might have limitation on solving the problems of dietary life including irregular meal, skipping a meal, and so on and influence the nutrition imbalance. For the development of HMRs, developing various menu and the packaging materials for HMR products, constructing the thorough sanitary management, and strengthening R & D for the HMR of Korean food were the future tasks in Korean HMR industry.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.369-379
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• 2016

This paper deals with an efficient method for skipping inter-channel phase differences (IPD) in the MPEG surround of the unified speech and audio coding (USAC). Based on the psycho-acoustic sensitivity on the IPD, we estimate a threshold on IPD, below which we can not notice degradation in spatial cue. We propose an IPD skip method, in which any IPDs within the threshold are set to zero and are not transmitted. The proposed IPD skip method gives about 38% savings in terms of bit amount for IPD. Nevertheless, in the MUSHRA test, the proposed method does not show any noticeable degradation in the decoded audio quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2C
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• pp.193-202
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• 2010

In this paper, we propose a fast algorithm that can reduce the complexity for inter mode decision of the H.264 encoder. The main idea consists of two techniques. The first one is the technique early terminating mode decision process. We focused on the skip and $16{\times}16$ mode because these modes occupies the largest portion in most of sequences. The second one is the technique skipping unnecessary $8{\times}8$ modes. The time consumption caused by the $8{\times}8$ mode is very considerable. Therefore if we can extract the unnecessary $8{\times}8$ mode calculation well, a large amount of time can be saved in total encoding process. The experimental results show that the proposed algorithm can achieve up to 43% speed up ratio with insignificant PSNR loss. The increase of total bits encoded is also not noticeable.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.327-336
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• 2004

For visual inspection system in real industrial environment, it is one of most important tasks to design fast and stable pattern matching algorithm. This paper presents an edge-based point correlation algorithm avoiding full search in visual inspection system. Conventional algorithms based on NGC(normalized gray-level correlation) have to overcome some difficulties for applying to automated inspection system in factory environment. First of all, NGC algorithms need high time complexity and thus high performance hardware to satisfy real-time process. In addition, lighting condition in realistic factory environments if not stable and therefore intensity variation from uncontrolled lights gives many roubles for applying directly NGC as pattern matching algorithm in this paper, we propose an algorithm to solve these problems from using thinned and binarized edge data and skipping full point search with edge-map analysis. A point correlation algorithm with the thinned edges is introduced with image pyramid technique to reduce the time complexity. Matching edges instead of using original gray-level pixel data overcomes NGC problems and pyramid of edges also provides fast and stable processing. All proposed methods are preyed from experiments using real images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.431-435
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• 2011

This paper presents optimized searching technique to improve the performance of H.264/AVC. The proposed CAVLC encoder uses forward and backward searching algorithm to compute the parameters. By zero-block skipping technique and pipelined scheduling, the proposed CAVLC encoder can obtain better performance. The experimental result shows that the proposed architecture needs only 66.6 cycles on average for each $16{\times}16$ macroblock encoding. The proposed architecture improves the performance by 13.8% than that of previous designs. The proposed CAVLC encoder was implemented using VerilogHDL and synthesized with Megnachip $0.18{\mu}m$ standard cell library. The synthesis result shows that the gate count is about 15.6K with 125Mhz clock frequency.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.682-692
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• 2006

Searching for gene products which have similar biological functions are crucial for bioinformatics. Modern day biological databases provide the functional description of gene products using Gene Ontology(GO). In this paper, we propose a technique for semantic similarity search for gene products using the GO annotation information. For this purpose, an information-theoretic measure for semantic similarity between gene products is defined. And an algorithm for semantic similarity search using this measure is proposed. We adapt Fagin's Threshold Algorithm to process the semantic similarity query as follows. First, we redefine the threshold for our measure. This is because our similarity function is not monotonic. Then cluster-skipping and the access ordering of the inverted index lists are proposed to reduce the number of disk accesses. Experiments with real GO and annotation data show that GORank is efficient and scalable.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.160-168
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• 2011

A Frequency domain beamforming technique is widely used in sonar systems with a large number of beams and sensors. In the battlefield environment requiring real-time signal processing, it is needed to optimize the computational complexity of the spectrum computation to implement an efficient and fast frequency domain beamformer. So, in this paper, we proposed the pruned-GSFFT (pruned generalized sliding fast Fourier transform) as a new spectrum computation method. The proposed method help to reduce the computational complexity of the real-time partial spectrum computation by eliminating the redundancy between consecutive input samples and skipping the regardless frequency bands. Also the characteristics of the proposed pruned-GSFFT method and its computational complexity are compared to those of previous FFT algorithms.

• Journal of Internet of Things and Convergence
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• v.8 no.4
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• pp.1-7
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• 2022

As the number of IoT devices increases, power management of the cluster head, which acts as a gateway between the cluster and sink nodes in the IoT network, becomes crucial. Particularly when the cluster head is a mobile wireless terminal, the power consumption of the IoT network must be minimized over its lifetime. In addition, the delay of information transmission in the IoT network is one of the primary metrics for rapid information collecting in the IoT network. In this paper, we propose a low-power buffer management algorithm that takes into account the information transmission delay in an IoT network. By forwarding or skipping received packets utilizing deep Q learning employed in deep reinforcement learning methods, the suggested method is able to reduce power consumption while decreasing transmission delay level. The proposed approach is demonstrated to reduce power consumption and to improve delay relative to the existing buffer management technique used as a comparison in slotted ALOHA protocol.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.650-652
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• 2022

Frame rate up-conversion (FRUC) algorithm is an image interpolation technology that improves the frame rate of moving pictures. This solves problems such as screen shake or blurry motion caused by low frame rate video in high-definition digital video systems, and provides viewers with a more free and smooth visual experience. In this paper, we propose a video compression technique using deep learning-based FRUC algorithm. The proposed method compresses and transmits after excluding some images from the original video, and uses a deep learning-based interpolation method in the decoding process to restore the excluded images, thereby compressing them with high efficiency. In the experiment, the compression performance was evaluated using the decoded image and the image restored by the FRUC algorithm after encoding the video by skipping 1 or 3 pages. When 1 and 3 sheets were excluded, the average BD-rate decreased by 81.22% and 27.80%. The reason that excluding three images has lower encoding efficiency than excluding one is because the PSNR of the image reconstructed by the FRUC method is low.