• Tunnel and Underground Space
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• v.32 no.6
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• pp.451-463
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• 2022

Whenever a mineshaft accidentally collapses, speedy risk assessment is both required and crucial. But onsite safety diagnosis by humans is reportedly difficult considering the additional risk of collapse of the unstable mineshaft. Generally, drones equipped with high-speed lidar sensors can be used for such inspection. However, the drone technology is restrictively applicable at very shallow depth, failing in mineshafts with depths of hundreds of meters because of the limit of wireless communication and turbulence inside the mineshaft. In previous study, a three-dimensional (3D) scanning system with a single channel lidar was fabricated and operated using towed cable in a mineshaft to a depth of 200 m. The rotation and pendulum movement errors of the measuring unit were compensated for by applying the data of inertial measuring unit and comparing the similarity between the scan data of the adjacent depths (Kim et al., 2020). However, the errors grew with scan depth. In this paper, a multi-channel lidar sensor to obtain a continuous cross-sectional image of the mineshaft from a winch system pulled from bottom upward. In this new approach, within overlapped region viewed by the multi-channel lidar, rotation error was compensated for by comparing the similarity between the scan data at the same depth. The fabricated system was applied to scan 0-165 m depth of the mineshaft with 180 m depth. The reconstructed image was depicted in a 3D graph for interpretation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.543-548
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• 2021

The higher the resolution of the image, the higher the satisfaction of the viewers of the image, and the super-resolution imaging has a considerable increase in research value among the fields of computer vision and image processing. In this study, the main features of low-resolution image LR are extracted mainly using deep learning super-resolution models. It learns and reconstructs the extracted features, and focuses on reconstruction-based algorithms that generate high-resolution image HR. In this paper, we investigate SRCNN and VDSR in a super-resolution algorithm model based on reconstruction. The structure and algorithm process of the SRCNN and VDSR model are briefly introduced, and the multi-channel and special form are also examined in the improved performance evaluation function, and understand the performance of each algorithm through experiments. In the experiment, an experiment was performed to compare the results of the SRCNN and VDSR models with the peak signal-to-noise ratio and image structure similarity, so that the results can be easily judged.

• Archives of design research
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• v.16 no.2
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• pp.365-374
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• 2003

Recently many TV have much interest in Network Design to get an advantage in the competition of the multi channels as part of the channel brand strategy. Since the Network Design was introduced in Korea in 1997, the major cable channels and satellite channels began to display Network Design on their screen competitively. But the production of Network Design has many problems in the field due to the lack of research information. The style guide is considered very important to succeed in Network Design execution as an indispensible process for a consistent planning and concrete production. This paper studied the Network Design Style Guide to establish a theoretical system of Network Design for a TV channel image promotion. First, this paper discussed the concept of Network Design and the necessity of the Network Design Style Guide, Second, this paper systemized the main component through the case study of the Network Design Style Guide and defined the concept of each element.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.245-247
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• 2022

Backscattered x-ray imaging is a technology capable of acquiring an image inside an irradiated object by measuring X-rays scattered from an object. For image acquisition, the system must include an X-ray generator and a detection system for measuring scattered x-rays. The imaging device must acquire a real-time signal at sampling intervals for x-rays generated by passing through a high-speed rotating collimator, and for this purpose, a high-speed signal acquisition device is required. We developed a high-speed multi-channel signal acquisition device for converting and transmitting signals generated by the sensor unit composed of a large-area plastic scintillator and a photomultiplier tube. The developed detector is a system capable of acquiring signals at intervals of at least 15u seconds and converting and transmitting signals of up to 6 channels. And a system includes remote control functions such as high voltage, signal gain, and low level discrimination for individual calibration of each sensor. Currently, we are conducting an application test for image acquisition under various conditions.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.1982-1990
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• 2022

The purpose of this study was to verify the possibility of fuel rod pattern analysis in a fresh fuel assembly using the Yonsei single-photon emission computed tomography (YSECT) system. The YSECT system consisted of three main parts: four trapezoidal-shaped bismuth germanate scintillator-based 64-channel detectors, a semiconductor-based multi-channel data acquisition system, and a rotary stage. In order to assess the performance of the prototype YSECT, tomographic images were obtained for three representative fuel rod patterns in the 6 × 6 array using two representative image-reconstruction algorithms. The fuel-rod patterns were then assessed using an in-house fuel rod pattern analysis algorithm. In the experimental results, the single-directional projection images for those three fuel-rod patterns well discriminated each fuel-rod location, showing a Gaussian-peak-shaped projection for a single 10 mm-diameter fuel rod with 12.1 mm full-width at half maximum. Finally, we successfully verified the possibility of the fuel rod pattern analysis for all three patterns of fresh fuel rods with the tomographic images obtained by the rotational YSECT system.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1605-1613
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• 2020

The tidal channel is a coastal sedimentary terrain that plays the most important role in the formation and development of tidal flats, and is considered a very important index for understanding and distribution of tidal flat sedimentation/erosion terrain. The purpose of this study is to understand the changes in tidal channels by a period after the opening of the floodgate of the seawall in the reclaimed land of Sihwa Lake using KOMPSAT high-resolution multispectral satellite image data and to evaluate the applicability and efficiency of high-resolution satellite images. KOMPSAT 2 and 3 images were used for extraction of the tidal channels' lineaments in 2009, 2014, and 2019 and were applied to supervised classification method based on Principal Component Analysis (PCA), Artificial Neural Net (ANN), Matched Filtering (MF), and Spectral Angle Mapper (SAM) and band ratio techniques using Normalized Difference Water Index (NDWI) and MF/SAM. For verification, a numerical map of the National Geographic Information Service and Landsat 7 ETM+ image data were utilized. As a result, KOMPSAT data showed great agreement with the verification data compared to the Landsat 7 images for detecting a direction and distribution pattern of the tidal channels. However, it has been confirmed that there will be limitations in identifying the distribution of tidal channels' density and providing meaningful information related to the development of the sedimentary process. This research is expected to present the possibility of utilizing KOMPSAT image-based high-resolution remote exploration as a way of responding to domestic intertidal environmental issues, and to be used as basic research for providing multi-platform-image-based convergent thematic maps and topics.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.40-45
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• 2001

In this paper, we implemented a multimodal system combining speech and lip information, and evaluated its performance. We designed speech recognizer using speech information and lip recognizer using image information. Both recognizers were based on HMM recognition engine. As a combining method we adopted the late integration method in which weighting ratio for speech and lip is 8:2. By the way, Our constructed multi-modal recognition system was ported on DARC system. That is, our system was used to control Comdio of DARC. The interrace between DARC and our system was done with TCP/IP socked. The experimental results of controlling Comdio showed that lip recognition can be used for an auxiliary means of speech recognizer by improving the rate of the recognition. Also, we expect that multi-model system will be successfully applied to o traffic information system and CNS (Car Navigation System).

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.53-59
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• 2002

The MSC is a payload on the KOMPSAT-2 satellite to perform the earth remote sensing. The instrument images the earth using a push-broom motion with a swath width of 15 km and a GSD(Ground Sample Distance) of 1 m over the entire FOV(Field Of View) at altitude 685 km. The instrument is designed to haute an on-orbit operation duty cycle of 20% over the mission lifetime of 3 years with the functions of programmable gain/offset and on-board image data compression/storage. The MSC instrument has one channel for panchromatic imaging and four channel for multi-spectral imaging covering the spectral range from 450nm to 900nm using TDI(Time Belayed Integration) CCD(Charge Coupled Device) FPA(Focal Plane Assembly). The MSC hardware consists of three subsystem, EOS(Electro Optic camera Subsystem), PMU(Payload Management Unit) and PDTS(Payload Data Transmission Subsystem) and each subsystems are currently under development and will be integrated and verified through functional and space environment tests. Final verified MSC will be delivered to spacecraft bus for AIT(Assembly, Integration and Test) and then COMSAT-2 satellite will be launched after verification process through IST(Integrated Satellite Test). In this paper, the introduction of MSC, the configuration of MSC electronics including electrical interlace and design of CEU(Camera Electronic Unit) in EOS are described. MSC Operation parameters induced from the operation concept are discussed and analyzed to find the influence of system for on-orbit operation in future.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.8-15
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• 2019

Recently, the importance of pre-shipment quality inspection has been emphasized due to the increase of STB supply. In this paper, we propose a method to support automation of quality inspection through simultaneous multi-channel input of STB video signal. The proposed method extracts a fingerprint using the center scan line of the image after stable video shot boundary detection using CeLDP combining color information and LDP code and performs synchronization between input video channels. The proposed method shows stronger shot boundary detection performance than the conventional shot detection method. Through the experiments applied to the real environment, it is possible to secure reliability and real-time quality check for synchronization between multi-channel inputs required for STB quality inspection. Also, based on the proposed method, we intend to study a large-scale quality inspection method in the future and propose a more effective quality inspection system.