• Journal of Information Technology Services
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• v.11 no.sup
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• pp.177-189
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• 2012

We developed the ocean disaster detection system(OD2S) which copes with the occurrences of ocean disasters (e. g. the red and green tide, the oil spill, the typhoon, and the sea ice) by converging and integrating the ocean color remote sensing using the satellite and the information technology exploiting the mass data processing and the pattern recognitions. This system which is based on the cosine similarity detects the ocean disasters in real time. The existing ocean color sensors which are operated in the polar orbit platforms cannot conduct the real time observation of ocean environments because they support the low temporal resolutions of one observation a day. However, geostationary ocean color imager(GOCI), the first geostationary ocean color sensor in the world, produces the ocean color images(e. g. the chlorophyll, the colored dissolved organic matter(CDOM), and the total suspended solid(TSS)), with high temporal resolutions of hourly intervals up to eight observations a day. The evaluation demonstrated that the OD2S can detect the excessive concentration of chlorophyll, CDOM, and TSS. Based on these results, it is expected that OD2S detects the ocean disasters in real time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.11A
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• pp.1035-1046
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• 2005

This paper analyzes the channel assignment techniques and their performance in the On Board Processing (OBP) satellite communication system. It suggests the new Continuous Rate Assignment (CRA) and Dynamic Rare Assignment (DRA) for improving the efficiency of channel assignment at the OBP switch. Mathematical analysis and simulation are given to evaluate the system performance. Aggregate real-time and non-real-time services are considered as different classes. Higher priority is given to voice and video real-time services to avoid delay variation. Onboard scheduler uses CRA and DRA ways to arrange the capacity allocation dynamically. An improved algorithm is given to make the channel more efficient by doing some evaluation of the switching matrix.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1144-1155
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• 2006

Digital communication networks have become a core technology in advanced building automation systems. BACnet(Building Automation and Control networks) is a standard data communication protocol designed specifically for building automation and control systems. BACnet adopts Master-Slave/Token-Passing(MS/TP) protocol as one of its field level networks. In this study, we introduce a method of implementing a bandwidth allocation scheme in the MS/TP protocol. The bandwidth allocation scheme improves the capability of real-time communication of the original MS/TP protocol. The bandwidth allocation scheme introduced in this paper can be easily implemented in the existing MS/TP protocol with a slight modification. In this study, we actually developed the hardware and firmware of the modified MS/TP communication module in which the bandwidth allocation scheme is implemented. Using the modified MS/TP communication module, we developed an experimental model in order to examine the validity of the bandwidth allocation scheme in the MS/TP protocol. Experimental results show that the modified MS/TP protocol satisfies the requirements of real time communication for periodic and urgent messages of BACnet communication services.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5936-5954
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• 2018

Eight out of the top ten the largest technology companies in the world are involved in some way with the coming mobile VR revolution since Facebook acquired Oculus. This trend has allowed the technology related with mobile VR to achieve remarkable growth in both academic and industry. Therefore, the importance of reproducing the acoustic expression for users to experience more realistic is increasing because auditory cues can enhance the perception of the complicated surrounding environment without the visual system in VR. This paper presents a audio downmixing system for auralization based on hardware, a stage of sound rendering pipelines that can reproduce realiy-like sound but requires high computation costs. The proposed system is verified through an FPGA platform with the special focus on hardware architectural designs for low power and real-time. The results show that the proposed system on an FPGA can downmix maximum 5 sources in real-time rate (52 FPS), with 382 mW low power consumptions. Furthermore, the generated 3D sound with the proposed system was verified with satisfactory results of sound quality via the user evaluation.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.75-81
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• 2023

In this study, we design an optimized Graphics Processing Unit (GPU)-based GNSS signal processing technique with the goal of designing and implementing a GNSS Software Defined Receiver (SDR) that can operate in real time all-in-view mode under multi-constellation and multi-frequency signal environment. In the proposed structure the correlators of the existing GNSS SDR are processed by the GPU. We designed a memory structure and processing method that can minimize memory access bottlenecks and optimize the GPU memory resource distribution. The designed GNSS SDR can select and operate only the desired GNSS or desired satellite signals by user input. Also, parameters such as the number of quantization bits, sampling rate, and number of signal tracking arms can be selected. The computing capability of the designed GPU-based GNSS SDR was evaluated and it was confirmed that up to 2400 channels can be processed in real time. As a result, the GPU-based GNSS SDR has sufficient performance to operate in real-time all-in-view mode. In future studies, it will be used for more diverse GNSS signal processing and will be applied to multipath effect analysis using more tracking arms.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.17-22
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• 2023

In this paper, we propose a black ice detection system using Convolutional Neural Networks (CNNs). Black ice poses a serious threat to road safety, particularly during winter conditions. To overcome this problem, we introduce a CNN-based architecture for real-time black ice detection with an encoder-decoder network, specifically designed for real-time black ice detection using thermal images. To train the network, we establish a specialized experimental platform to capture thermal images of various black ice formations on diverse road surfaces, including cement and asphalt. This enables us to curate a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Additionally, in order to enhance the accuracy of black ice detection, we propose a multi-scale dilation convolution feature fusion (MsDC-FF) technique. This proposed technique dynamically adjusts the dilation ratios based on the input image's resolution, improving the network's ability to capture fine-grained details. Experimental results demonstrate the superior performance of our proposed network model compared to conventional image segmentation models. Our model achieved an mIoU of 95.93%, while LinkNet achieved an mIoU of 95.39%. Therefore, it is concluded that the proposed model in this paper could offer a promising solution for real-time black ice detection, thereby enhancing road safety during winter conditions.

• Smart Structures and Systems
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• v.31 no.5
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• pp.501-516
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• 2023

Dynamic irregularity and acceleration of bridges subjected to high-speed trains provide crucial information for comprehensive evaluation of the health state of under-track structures. This paper proposes a novel approach for real-time estimation of vertical track dynamic irregularity and bridge acceleration using deep generative adversarial network (GAN) and vibration data from in-service train. The vehicle-body and bogie acceleration responses are correlated with the two target variables by modeling train-bridge interaction (TBI) through least squares generative adversarial network (LSGAN). To realize supervised learning required in the present task, the conventional LSGAN is modified by implementing new loss function and linear activation function. The proposed approach can offer pointwise and accurate estimates of track dynamic irregularity and bridge acceleration, allowing frequent inspection of high-speed railway (HSR) bridges in an economical way. Thanks to its applicability in scenarios of high noise level and critical resonance condition, the proposed approach has a promising prospect in engineering applications.

• Journal of IKEEE
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• v.28 no.1
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• pp.26-32
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• 2024

Recently, various video resolution formats have emerged, and digital devices have built in dedicated scaler chips to support them by enlarging or reducing the resolution of input videos. Therefore, the performance and hardware size of scaler chips are important. In this paper, the combinatorial interpolation scaler algorithm proposed by Han is used to design the hardware using the line memory structure with dual-clock proposed by Han and Jung. The proposed hardware is capable of real-time processing in QHD environments, designed using Verilog, and validated using Xilinx's Vivado 2023.1. We also verify the performance of Han's proposed algorithm with a quantitative numerical evaluation of the proposed hardware.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.143-149
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• 2024

The production and procurement of shipbuilding and offshore equipment is an important competitive factor in the shipbuilding and offshore industry. Recently, ICT-based digital technology has been rapidly applied to the manufacturing industry following the Fourth Industrial Revolution. Under the digital transformation, real-time data interface technology based on SCM (Supply Chain Management) is emerging as an important tool to improve the efficiency of the equipment manufacturing process. In this study, the characteristics and advantages and disadvantages of interface technologies of web-based data interface technologies were compared and analyzed. The performance was compared between theoretical evaluation based on technical features and practical application cases. As a result, it was confirmed that GraphQL is useful for selective data processing, but there is a problem with optimization, and REST API has a problem with receiving data due to a fixed data structure. Therefore, this study aims to suggest ways to utilize and optimize these data interface technologies.

• ETRI Journal
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• v.38 no.3
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• pp.425-434
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• 2016

A novel average magnitude difference function (AMDF)-based pitch detection scheme (PDS) is proposed to achieve better performance in speech quality. A performance evaluation of the proposed PDS is carried out through both a simulation and a real-time implementation of a speech analysis-synthesis system. The parameters used to compare the performance of the proposed PDS with that of PDSs that are based on either a cepstrum, an autocorrelation function (ACF), an AMDF, or circular AMDF (CAMDF) methods are as follows: percentage gross pitch error (%GPE); a subjective listening test; an objective speech quality assessment; a speech intelligibility test; a synthesized speech waveform; computation time; and memory consumption. The proposed PDS results in lower %GPE and better synthesized speech quality and intelligibility for different speech signals as compared to the cepstrum-, ACF-, AMDF-, and CAMDF-based PDSs. The computational time of the proposed PDS is also less than that for the cepstrum-, ACF-, and CAMDF-based PDSs. Moreover, the total memory consumed by the proposed PDS is less than that for the ACF- and cepstrum-based PDSs.