• Journal of Digital Convergence
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• v.12 no.6
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• pp.231-236
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• 2014

In this paper, we propose a processing speed improvement by adding a parallel processing based on device(graphic card) into a road region extraction by host(PC) based serial processing. The OpenCV CUDA supports the many functions of parallel processing method by interworking a conventional OpenCV with CUDA. Also, when interworking the OpenCV and CUDA, OpenCV functions completed a configuration are optimized the User's device(Graphic Card) specifications. Thus, OpenCV CUDA usage provides an algorithm verification and easiness of simulation result deduction. The proposed method is verified that the proposed method has a about 3.09 times faster processing speed than a conventional method by using OpenCV CUDA and graphic card of NVIDIA GeForce GTX 560 Ti model through experimentation.

• Smart Media Journal
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• v.12 no.11
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• pp.67-76
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• 2023

We propose a visualization method to respond to civil complaints through an analysis of the impact of blasting. In order to analyze the impact of blasting on tunnel excavation, we propose a simulation visualization method considering the mutual influence of the construction infrastructure by linking measurement data and 3D BIM model. First, the level of BIM modeling required for simulation was defined. In addition, vibration measurement data were collected for the GTX-A construction site, terrain and structure BIM were created, and a method for visualizing measurement data using blast vibration estimation was developed. Next, a spherical blasting influence source library was developed for visualization of the blasting influence source, and a specification table that could be linked with Revit Dynamo automation logic was constructed. Using this result, a method for easily visualizing the impact analysis of blasting vibration in 3D was proposed.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.485-490
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• 2017

In this paper, we propose a technique for high speed removal of sea-fog using a graphic processor. This technique uses a host processor(CPU) and several graphics processors(GPU) capable of parallel processing to remove sea-fog from the input image. In the process of removing sea-fog, the dark channel extraction, the maximum brightness channel extraction, and the calculation of the transmission are performed by the host processor, and the process of refining the transmission by applying the bidirectional filter is performed in parallel through the graphic processor. To verify the proposed parallel processing method, three NVIDIA GTX 1070 GPUs were used to construct the verification environment. As a result, it takes about 140ms when implemented with one graphics processor, and 26ms when implemented using OpenMP and multiple GPGPUs. The proposed a parallel processing algorithm based on the graphics processor unit can be used for safe navigation, port control and monitoring system.

• Journal of KIISE
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• v.45 no.1
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• pp.94-98
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• 2018

We propose Wide Inception ResNet (WIR Net) an optimized neural network architecture as a real-time semantic segmentation method for autonomous driving. The neural network architecture consists of an encoder that extracts features by applying a residual connection and inception module, and a decoder that increases the resolution by using transposed convolution and a low layer feature map. We also improved the performance by applying an ELU activation function and optimized the neural network by reducing the number of layers and increasing the number of filters. The performance evaluations used an NVIDIA Geforce GTX 1080 and TX1 boards to assess the class and category IoU for cityscapes data in the driving environment. The experimental results show that the accuracy of class IoU 53.4, category IoU 81.8 and the execution speed of $640{\times}360$, $720{\times}480$ resolution image processing 17.8fps and 13.0fps on TX1 board.

• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.521-534
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• 2020

Paralytic shellfish poisoning (PSP) occurs when saxitoxin (STX), which is produced by harmful algae (dinoflagellates) and then accumulated in bivalve shellfish by filter-feeding, is consumed by humans. With recent advances in analysis technology, it has been reported that dinoflagellates also produce a variety of analogues such as the gonyautoxin (GTX) group and the N-sulfo-carbamoyl toxin (C toxin) group, in addition to STX. Accordingly, CODEX and the EFSA are stepping forward to manage STX and analogues as STX groups requiring safety management. In Korea, the occurrence of dinoflagellates producing STX analogues has already been reported, and contamination of analogues (GTX group, C toxin group) in live mussels has also been reported. In this study, in order to provide the basis for systematic monitoring and safety management of STX and analogues, their physicochemical characteristics, occurrence of dinoflagellates, toxicity and toxic equivalency factor, analytical method and occurrence were widely reviewed. This review is expected to contribute to strengthening the safety management of STX and its analogues.

• Journal of Cadastre & Land InformatiX
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• v.44 no.1
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• pp.97-111
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• 2014

As urbanization and industrialization develops, the necessity of utilizing scarce land in three dimensions is raising. The issue of utilizing underground space is being actively discussed particularly when Geyeonggi-do announced GTX(Great Train Express) construction plan which aims to relieve traffic congestion in metropolitan areas. The current regulation on compensation of underground space is based on "Regulations on compensation standard complied by using underground space for construction of urban railway" but it is difficult for covering the whole rights to protect a three-dimensional right. In this context, the study is to propose the improvement plans of land right's problem and compensation issues to utilization of underground space for the right complementary. To do this, the study reviews the use situation of the classification surface right and using adjudication which defines the effect scope of underground space extending land ownership. As well as it analyzes issues about compensation standard for utilizing of underground space.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.3
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• pp.23-32
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• 2008

The computing power of graphics processing units(GPU) has already surpassed that of CPU and the gap between their powers is getting wider. Thus, research on GPGPU which applies GPU to general purpose becomes popular and shows great success especially in the field of parallel data processing. Since the implementation of cryptographic algorithm using GPU was started by Cook et at. in 2005, improved results using graphic libraries such as OpenGL and DirectX have been published. In this paper, we present skills and results of implementing block ciphers using CUDA library announced by NVIDIA in 2007. Also, we discuss a general method converting source codes of block ciphers on CPU to those on GPU. On NVIDIA 8800GTX GPU, the resulting speeds of block cipher AES, ARIA, and DES are 4.5Gbps, 7.0Gbps, and 2.8Gbps, respectively which are faster than the those on CPU.

• Journal of Communications and Networks
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• v.17 no.2
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• pp.198-202
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• 2015

This paper presents a computationally efficient implementation of a Hamming code decoder on a graphics processing unit (GPU) to support real-time software-defined radio, which is a software alternative for realizing wireless communication. The Hamming code algorithm is challenging to parallelize effectively on a GPU because it works on sparsely located data items with several conditional statements, leading to non-coalesced, long latency, global memory access, and huge thread divergence. To address these issues, we propose an optimized implementation of the Hamming code on the GPU to exploit the higher parallelism inherent in the algorithm. Experimental results using a compute unified device architecture (CUDA)-enabled NVIDIA GeForce GTX 560, including 335 cores, revealed that the proposed approach achieved a 99x speedup versus the equivalent CPU-based implementation.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.43-45
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• 2012

This paper is based on embedding the biometrics techniques on GPU for better computational efficiency and fast matching process using the parallel nature of the GPU processors to compare thousands of images for fingerprint recognition in a fraction of a second. In this paper we worked on GPU (INVIDIA GeForce GTX 260 with compute capability 1.3 and dual core-2-dou processor) for fingerprint matching and found that the efficiency is better than the results with related work already done on CMOS, CPU, ARM9, MATLAB Neural Networks etc which shows the better performance of our system in terms of computational time. The features matching process proposed for fingerprint recognition and the verification procedure is done on 5,000 images which are available online in the databases FVC2000, 2002, 2004 [1].

• Journal of the Society of Disaster Information
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• v.6 no.1
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• pp.92-119
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• 2010

As the necessity to utilize deep-placed underground spaces is increasing, we have to seriously consider the safety problems arising from the U/G spaces which is a restricted environment. Due to the higher cost of land compensation for above ground area and environmental issues, the plan to utilize deep-placed U/G spaces is currently only being established for the construction of U/G road network and GTX. However it is also expected that the U/G spaces are to be used as a living space because of the growing desires to change the above ground areas into the environmentally green spaces. Accordingly it is necessary to protect the U/G environments which is vulnerable against desasters caused by fire, explosion, flooding, terrorism, electric power failure, etc. properly. We want to introduce the principles of the Quantitative Risk Assessment(QRA) method for preparedness against the desasters arising from U/G environments, and also want to introduce an example of QRA which was implemented for the GOTTHARD tunnel which is the longest one in Europe.