• Korean Journal of Remote Sensing
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• v.15 no.4
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• pp.367-375
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• 1999

This paper describes the development, operations, and applications of ROCSAT-l and its Ocean Color Imager (OCI) remote-sensing payload. It is the first satellite program of NSPO. The satellite was successfully launched by Lockheed Martin's Athena on January 26, 1999 from Cape Canaveral, Florida. ROCSAT-l is a Low Earth Orbit (LEO) experimental satellite. Its circular orbit has an altitude of 600km and an inclination angle of 35 degrees. The satellite is designed to carry out scientific research missions, including ocean color imaging, experiments on ionospheric plasma and electrodynamics, and experiments using Ka-band (20∼30GHz) communication payloads. The OCI payload is utilized to observe the ocean color in 7 bands (including one redundant band) of Visible and Near-Infrared (434nm∼889nm) range with the resolution of 800m at nadir and the swath of 702km. It employs high performance telecentric optics, push-broom scanning method using Charge Coupled Devices (CCD) and large-scale integrated circuit chips. The water leaving radiance is estimated from the total inputs to the OCI, including the atmospheric scattering. The post-process estimates the water leaving radiance and generates different end products. The OCI has taken images since February 1999 after completing the early orbit checkout. Analyses have been performed to evaluate the performances of the instrument in orbit and to compare them with the pre-launch test results. This paper also briefly describes the ROCSAT-l mission operations. The spacecraft operating modes and ROCSAT Ground Segment operations are delineated, and the overall initial operations of ROCSAT-l are summarized.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.77-78
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• 2022

To improve the fire vulnerability of the organic insulation sandwich panel core, which is the main culprit of the large-scale fire disaster, an experiment was conducted to examine the thermal conductivity properties of the core material mixed with the organic insulation material EPS Bead and the inorganic insulation material glass wool. As the Additional ratio of glass wool increased, the thermal conductivity decreased, and it was determined that the replacement of glass wool of 3% or more had little effect on the decrease in thermal conductivity. In addition, it can be seen that the most ideal thermal conductivity is exhibited when 1% Replacement ratio of EPS and 3% glass wool are added. The core material of such organic and inorganic insulation materials is judged to be a core material that can compensate for the fire vulnerability of existing insulation materials. Therefore, in order to determine whether it is used as a core material for sandwich panels, additional studies such as fire resistance experiments and sound absorption experiments are needed in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2470-2491
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• 2018

Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.199-202
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• 2005

High speed milling process is emerging as an important fabrication process benefits include the ability to fabricate micro and meso-scale parts out of a greater range of materials and with more varied geometry. It also enables the creation of micro and meso-scale molds for injection molding. Factors affecting surface roughness have not been studied in depth for this process. A series of experiments has been conducted in order to begin to characterize the factors affecting surface roughness and determine the range of attainable surface roughness values for the high speed milling process. It has previously been shown that run-out creates a greater problem for the dimensional accuracy of parts created by high speed milling process. And run-out also has a more significant effect on the surface quality of milled parts. The surface roughness traces reveal large peak to valley variations. This run-out is generated by spindle dynamics and tool geometry. In order to investigate the relationship between tool setting errors and surface roughness end tilted mills were used to cut aluminum samples. The results indicate that tool setting errors have significant effects on surface roughness and cutting forces.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3723-3728
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• 2011

This study investigated the friction behaviors of rock and grout through the small /large scale laboratory experiments. The small-scale laboratory tests were undertaken using a specially designed and fabricated equipments to simulate the contact surface of rock. In calibration chamber test, a artificial rock mass was prepared in soil container to measure the tensile resistance of grout. Test condition includes the grouting method of pressure involvement. The results of the tests show that the pressure grouting increases the frictional resistance significantly.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.4
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• pp.389-403
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• 2019

Large amounts of concrete waste are likely to arise from the decommissioning of a Kori-1 nuclear power plant. Several studies have been conducted on decommissioning concrete waste in recent decades, however, they have been limited to contaminated concrete issues or were small pilot-scale experiments. This study constructed two industrial-scale models of on-site concrete waste management for clean as well as contaminated concrete. To evaluate the performance of both the models, simulations were conducted using the Flexsim software. The concrete particle size distribution of Kori-1 and concrete processor properties based on widely used construction equipment were used as sources of input data for the simulations. It was observed that it may take over two years to complete the on-site concrete management processes owing to the performance of existing processors. In addition, it was demonstrated that it is essential to identify bottlenecks in the system and enhance the performance of the relevant processors to avoid delays of the decommissioning schedule. Our results suggest that this novel approach can contribute to developing schedules or expediting delayed activities in the Kori-1 decommissioning project.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.627-628
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• 2006

High speed milling process is emerging as an important fabrication process benefits include the ability to fabricate micro and meso-scale parts out of a greater range of materials and with more varied geometry. It also enables the creation of micro and meso-scale molds for injection molding. Factors affecting surface roughness have not been studied in depth for this process. A series of experiments has been conducted in order to begin to characterize the factors affecting surface roughness and determine the range of attainable surface roughness values for the high speed milling process. It has previously been shown that run-out creates a greater problem for the dimensional accuracy of pans created by high speed milling process. And run-out also has a more significant effect on the surface quality of milled parts. The surface roughness traces reveal large peak to valley variations. This run-out is generated by spindle dynamics and tool geometry. In order to investigate the relationship between tool alignment errors and surface roughness the scallop generating mechanism in the ball-end milling with tool alignement errors has been studied and simulated. The results indicate that tool alignment errors have no significant effects ell the dimension of scallops in for flat planes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.5
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• pp.212-217
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• 2014

Recently, the use of renewable energy has been increased due to growing concern on the energy-saving at buildings and the reduction of $CO_2$ emission. In the field of architecture, to reduce the energy consumption of heating, cooling and hot water supply, heat pump systems with renewable energy has been developed and used in various applications. However, there have been many of researches on the large-scale commercial heat pump systems, but the research and the field application of a compact heat pump system is rare. Therefore, in order to develop the compact heat pump for the small-scale residential building, this study conducted the performance test and feasibility study for a hybrid heat pump using the heat source of air, solar and ground. In the results of experiments through a trial product, the average COP of cooling mode with ground heat source was 4.75, and it of heating mode was 4.03. Furthermore, the average COP of cooling mode with air heat source was 2.60, and it of heating mode was 2.92. Finally, payback period of the system was calculated as 9.2 years.

• Transactions of Materials Processing
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• v.23 no.3
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• pp.178-183
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• 2014

Continuous casting is a process where molten metal is solidified into a semi-finished billet on a large scale with either a rectangular or round cross section for subsequent processing. The use of continuous casting provides an opportunity for producing material on a practical industrial scale with lower cost than conventional casting. In the current study, the material was fabricated by continuous casting and subsequent extrusion. Tensile tests were conducted on continuous cast ZK60A after extrusion over a range of strain rates at temperatures from 473K to 623K. The alloy exhibits a quasi-superplastic behavior with a maximum recorded elongation of ~250% at 523K when tested with an initial strain rate of $10^{-5}/s$. The experiments give a strain rate sensitivity exponent of 0.3~0.4 and an activation energy of 108 kJ/mol. From the current investigation, it was found that the high-temperature plastic flow of the ZK60A is controlled by a dislocation viscous glide mechanism.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1310-1319
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• 2016

Face detection is the first step in a wide range of face applications. However, detecting faces in the wild is still a challenging task due to the wide range of variations in pose, scale, and occlusions. Recently, many deep learning methods have been proposed for face detection. However, further improvements are required in the wild. Another important issue to be considered in the face detection is the computational complexity. Current state-of-the-art deep learning methods require a large number of patches to deal with varying scales and the arbitrary image sizes, which result in an increased computational complexity. To reduce the complexity while achieving better detection accuracy, we propose a fully convolutional network-based face detection that can take arbitrarily-sized input and produce feature maps (heat maps) corresponding to the input image size. To deal with the various face scales, a multi-scale network architecture that utilizes the facial components when learning the feature maps is proposed. On top of it, we design multi-task learning technique to improve detection performance. Extensive experiments have been conducted on the FDDB dataset. The experimental results show that the proposed method outperforms state-of-the-art methods with the accuracy of 82.33% at 517 false alarms, while improving computational efficiency significantly.