• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.95-103
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• 2017

Horizon correction is a crucial stage for image composition enhancement. In this paper, we propose a deep learning based method for estimating the slanted angle of a photograph and correcting it. To estimate and correct the horizon direction, existing methods use hand-crafted low-level features such as lines, planes, and gradient distributions. However, these methods may not work well on the images that contain no lines or planes. To tackle this limitation and robustly estimate the slanted angle, we propose a convolutional neural network (CNN) based method to estimate the slanted angle by learning more generic features using a huge dataset. In addition, we utilize multiple adaptive spatial pooling layers to extract multi-scale image features for better performance. In the experimental results, we show our CNN-based approach robustly and accurately estimates the slanted angle of an image regardless of the image content, even if the image contains no lines or planes at all.

• Journal of Internet of Things and Convergence
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• v.6 no.3
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• pp.1-6
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• 2020

This paper aims to integrate the previous models about mean object transfer latency in one framework and analyze the result through the computational experience. The analytical object transfer latency model assumes the multiple packet losses and the Internet of Things(IoT) environment including multi-hop wireless network, where fast re-transmission is not possible due to small window. The model also considers the initial congestion window size and the multiple packet loss in one congestion window. Performance evaluation shows that the lower and upper bounds of the mean object transfer latency are almost the same when both transfer object size and packet loss rate are small. However, as packet loss rate increases, the size of the initial congestion window and the round-trip time affect the upper and lower bounds of the mean object transfer latency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1337-1344
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• 2004

This paper deals with analysis and real-time Implementation of a wide band adaptive multirate speech codec (AMR-WB) using a fixed-point DSP of TI's TMS320C6201. In the AMR-WB codec, input speech is divided into two frequency bands, lower and upper bands, and processed independently. The lower band signal is encoded based on the ACELP algorithm and the upper band signal is processed using the random excitation with a linear prediction synthesis filter. The implemented AMR-WB system used 218 kbytes of program memory and 92 kbytes of data memory. And its proper operation was confirmed by comparing a decoded speech signal sample-by-sample with that of PC-based simulation. Maximum required time of 5 75 ms for processing a frame of 20 ms of speech validates real-time operation of the Implemented system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.4_1
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• pp.335-341
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• 2014

The main goal of this study is on developing a proper brand-new data of national base map and Data Based(DB) model for new information technology environments. To achieve this goal, we generated a brand-new Hybrid spatial information model which is specialized in the spatio-temporal map structure, the framework map for information integration, and the multiple-layered topology structure. The DB structure was designed to reflect the change of objections by adding a new dimension of 'time' in the spartial information, while the infrastructure was able to connect/converge with other information by giving the unique ID and multi-scale fusion map structure. Furthermore, the topology and multi visualization structure, including indoor and basement information, were designed to overcome limitations of expressing in 2 dimension map. The result from the performance test, which was based on the Hybrid spatial information model, confirms the possibility in advanced national base map and conducted DB model through implementing various information and spatiotemporal connections.

• KIISE Transactions on Computing Practices
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• v.21 no.5
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• pp.387-392
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• 2015

MapReduce is a framework used to process large data sets in parallel on a large cluster. A group-by query is a query that partitions the input data into groups based on the values of the specified attributes, and then evaluates the value of the specified aggregate function for each group. In this paper, we propose an efficient method for processing multiple group-by queries using MapReduce. Instead of computing each group-by query independently, the proposed method computes multiple group-by queries in stages with one or more MapReduce jobs in order to reduce the total execution cost. We compared the performance of this method with the performance of a less sophisticated method that computes each group-by query independently. This comparison showed that the proposed method offers better performance in terms of execution time.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.557-564
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• 2013

An important research challenge about the traditional Internet environment is to enable open networking architecture on which end users are able to innovate the Internet based on the technologies of network programmability, virtualization, and federation. The SDN (Software Defined Network) technology that includes OpenFlow protocol specifications, is suggested as a major driver for the open networking architecture, and is closely coupled with the classical Internet (non-SDN). Therefore, it is very important to keep the integrated SDN and non-SDN network infrastructure reliable from the view point of network operators and engineers. Under this background, this paper proposes an operations and management framework for the combined software defined network environment across not only a single-domain network, but also multi-domain networks. The suggested framework is designed to allow SDN controllers and DvNOC systems to interact with each other to achieve sustainable end-to-end user-oriented SDN and non-SDN integrated network environment. Plus, the proposed scheme is designed to apply enhanced functionalities on DvNOC to support four major network failure scenarios over the combined network infrastructure, mainly derived from SDN controllers, SDN devices, and the connected network paths.

• Journal of the Korea Computer Graphics Society
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• v.24 no.1
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• pp.9-16
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• 2018

In this paper, we introduce a visualization framework for cell image data obtained from optical diffraction tomography (ODT), including a method for representing cell morphology in 3D virtual environment and a color mapping protocol. Unlike commonly known volume data sets, such as CT images of human organ or industrial machinery, that have solid structural information, the cell image data have rather vague information with much morphological variations on the boundaries. Therefore, it is difficult to come up with consistent representation of cell structure for visualization results. To obtain desired visual representation of cellular structures, we propose an interactive visualization technique for the ODT data. In visualization of 3D shape of the cell, we adopt a volume rendering technique which is generally applied to volume data visualization and improve the quality of volume rendering result by using empty space jittering method. Furthermore, we provide a layer-based independent rendering method for multiple transfer functions to represent two or more cellular structures in unified render window. In the experiment, we examined effectiveness of proposed method by visualizing various type of the cell obtained from the microscope which can capture ODT image and fluorescence image together.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.2 s.302
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• pp.27-36
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• 2005

This thesis proposed an effective encryption method for the DCT-based image/video contents and made it possible to operate in a high speed by implementing it as an optimized hardware. By considering the increase in the amount of the calculation in the image/video compression, reconstruction and encryption, an partial encryption was performed, in which only the important information (DC and DPCM coefficients) were selected as the data to be encrypted. As the result, the encryption cost decreased when all the original image was encrypted. As the encryption algorithm one of the multi-mode AES, DES, or SEED can be used. The proposed encryption method was implemented in software to be experimented with TM-5 for about 1,000 test images. From the result, it was verified that to induce the original image from the encrypted one is not possible. At that situation, the decrease in compression ratio was only $1.6\%$. The hardware encryption system implemented in Verilog-HDL was synthesized to find the gate-level circuit in the SynopsysTM design compiler with the Hynix $0.25{\mu}m$ CMOS Phantom-cell library. Timing simulation was performed by Verilog-XL from CadenceTM, which resulted in the stable operation in the frequency above 100MHz. Accordingly, the proposed encryption method and the implemented hardware are expected to be effectively used as a good solution for the end-to-end security which is considered as one of the important problems.

• Journal of the Korean Orthopaedic Association
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• v.55 no.6
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• pp.527-533
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• 2020

Purpose: This study compared the effects of a buprenorphine transdermal patch (BTDP) on the chest and knee for pain control after total knee arthroplasty (TKA). Materials and Methods: A retrospective case-control study was conducted from August 2018 to August 2019 on 231 patients who underwent TKA. Two hundred cases were selected considering age, sex, and body mass index. Before and after applying the BTDP, the Numeric Rating Scale (NRS), adverse effects and compliance were measured. All measurements in the chest application group (group A=100) and knee application group (group B=100) were compared. Results: NRS was similar in rest between the groups treated with BTDP, but at two days and three days afternoon, five, six, and seven days postoperatively in group B, the NRS was significantly lower than that of group A. The adverse effects of the central nervous system and gastrointestinal system after applying BTDP were significantly lower in group B than in group A. No significant differences in adverse effects of the cardiovascular system and skin were observed between the two groups. Regarding the maintenance of BTDP, group B was significantly higher than group A. Conclusion: The direct application of BTDP after TKA to painful knee joints showed excellent results in early postoperative pain control and can be a useful method for increasing patient compliance by reducing the frequency of adverse effects.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.415-418
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• 2007

가까운 미래에 인간생활에 활용될 지능형 로봇은 인간과 공존하면서도 효과적으로 인간을 도와줄 수 있는 인간친화형 로봇이라 할 수 있다. 이러한 것을 실현하기 위해서 로봇은 미지의 환경 내에서 자신의 위치 및 방향을 인식해야 할 필요가 있다. 더욱이, 이것은 일상생활에서 자연스럽게 이뤄지는 것이 당연하다. 로봇을 제어하는 가장 중요한 문제중의 하나로서 이동로봇의 주행에서의 위치불확실성을 해결함으로서 로봇의 위치를 추정하는 것이 바람직하다 할 수 있다. 본 논문에서는 실내외 공간에서 인간을 포한함 이동물체의 영상정보를 이용하여 이동로봇의 자기위치를 인식하기 위한 방법을 제시하고 있다. 제시한 방법은 로봇자체의 DR센서 정보와 카메라에서 얻은 영상정보로부터 로봇의 위치추정방법을 결합 한 것이다. 그리고 이동물체의 이전 위치정보와 관측 카메라의 모델을 사용하여 이동물체에 대한 영상프레임 좌표와 추정된 로봇위치 간의 관계를 표현할 수 있는 식을 제시하고 있다. 또한 이동하는 인간과 로봇의 위치와 방향을 추정하기 위한 제어방법을 제시하고 이동로봇의 위치를 추정하기위해서 칼만필터 방법을 적용하였다. 그리고 시뮬레이션 및 실험을 통하여 제시한 방법을 검증하였다.