• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.695-700
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• 2018

This paper presents the development of compact and lightweight broadband power amplifier module using HMIC (Hybrid Microwave Integrated Circuit) technology that could be high-density integration for many non-packaged microwave components into the small area of a high dielectric constant printed circuit board, such as a ceramic substrate, also using the special design and fabrication schemes for the structure of minimized electromagnetic interference to obtain the homogeneous electrical performance at the wideband frequency. The results confirmed that the small signal gain has a gain flatness of ${\pm}1.5dB$ within the range of 32 to 36 dB. In addition, the output power satisfied more than 30 dBm. The noise figure was measured within 7 dB, and OIP3 (Output Third Order Intercept Point) was more than 39 dBm. The fabricated broadband power amplifier satisfied the target specification required to electrically drive the high power amplifiers of jamming generators for electronic warfare, so the actual applicability to the system was verified. Future studies will be aimed at designing other similar microwave power amplifiers in the future.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.6 s.348
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• pp.30-38
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• 2006

In this paper, an algerian that provisions absolute and proportional differentiation of packet delays is proposed with an objective for enhancing quality of service (QoS) in future packet networks. It features a scheme that compensates the deviation for prediction on the traffic to be arrived continuously It predicts the traffic to be arrived at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot and derives the difference between them. The deviation is utilized to the delay control operation for the next time slot to offset it. As it compensates the prediction error continuously, it shows superior adaptability to the bursty traffic as well as the exponential traffic. It is demonstrated through simulation that the algorithm meets the quantitative delay bounds and shows superiority to the traffic fluctuation in comparison with the conventional non-adaptive mechanism.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.4
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• pp.403-413
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• 2017

In this paper, to increase the use of industrial byproducts for $CO_2$ reduction and to improve construction performance, it was manufactured that $CO_2$ reduction type quaternary component high fluidity concrete (QC-HFC) with Reduced cement usage by more than 80% and its quality and hydration characteristics were evaluated. QC-HFC was found to satisfy the target performance, and the flow and mechanical properties were similar to those of conventional concrete. The drying shrinkage of QC-HFC decreased about twice compared with the conventional blend, and the hydration heat decreased about 36%. As a result, it can be concluded that the amount of cracks can be reduced by reducing temperature stress due to hydration heat reduction effect and reducing deformation due to relatively small temperature difference between inside and outside. Also, As a result of the simulation of the mass structure, the temperature cracking index of QC-HFC is 1.1 or more, and the cracking probability is reduced by about 35%, so that the crack due to temperature can be reduced.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.267-267
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• 2021

제주도는 화산섬의 지질특성상 강수의 지표침투성이 높아 지표수의 개발이용여건이 취약한 관계로 용수의 대부분을 지하수에 의존하고 있다. 따라서 지하수의 보전관리는 매우 중요한 사항이며 특히 지하수의 안정적인 이용을 위해서는 지하수 취수가 주변지역 지하수위에 미치는 영향 분석이 반드시 필요하다. 본 연구는 딥러닝 알고리즘인 Long Short-Term Memory(LSTM)를 활용하여 제주도 남동쪽 표선유역 중산간지역에 위치한 2개 지하수위 관측정을 대상으로 지하수 취수영향을 분석하였다. 입력자료로써 인근 2개 강우관측소의 일단위 강수량자료와 인근 6개 취수정의 지하수 취수량자료 및 연구대상 관측정의 지하수위 자료(2001. 2. 11. ~ 2019. 10. 31.)를 사용하였다. 지하수위 변동특성을 최대한 반영하기 위해 LSTM의 예측일수를 1일로 설정하였다. 보정 및 검증 기간을 사용하여 매개변수의 과적합을 방지하였으며, 테스트 기간을 사용하여 LSTM의 예측성능을 평가하였다. 평가지수로써 Nash-Sutcliffe Efficiency(NSE)와 평균제곱근오차(RMSE)를 사용하였다. 그리고 지하수 취수가 주변 지하수위 변동에 미치는 영향을 분석하기 위해 취수량을 최대취수량인 2,300 m³/일, 최대취수량의 2/3인 1,533 m³/일 및 0 m³/일로 설정하여 모의하였다. 모의결과, 2개 감시정의 보정, 검증 및 예측기간에 대한 NSE는 최대 0.999, 최소 0.976의 범위를 보였으며, RMSE는 최대 0.494 m, 최소 0.084 m를 보여 LSTM은 우수한 예측성능을 나타내었다. 이것은 LSTM이 지하수위 변동특성을 적절히 학습하였다는 것을 의미하며 따라서 추정된 매개변수를 활용하여 지하수 취수영향을 모의 및 분석하였다. 그 결과, 지하수위 하강량은 최대 0.38 m 였으며 이것은 대상지점에 대한 취수량은 지하수위 하강에 거의 영향을 주지 않는다는 것을 의미한다. 또한 취수량과 지하수위 하강량과의 관계는 한 개 관측정에 대해 선형적인 관계를 보인 반면 나머지 한 개 관측정에 대해서는 비선형적인 관계를 나타내는 것을 확인하였다. 따라서 LSTM 알고리즘을 활용하여 제주도 표선유역 중산간지역의 지하수위 변동특성을 분석할 수 있다.

• Journal of the Korean Society of Radiology
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• v.14 no.3
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• pp.211-220
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• 2020

High-quality computed tomography (CT) images enable precise lesion detection and accurate diagnosis. A lot of studies have been performed to improve CT image quality while reducing radiation dose. Recently, deep learning-based techniques for improving CT image quality have been developed and show superior performance compared to conventional techniques. In this study, a super-resolution convolutional neural network (SRCNN) model was used to improve the spatial resolution of CT images, and image quality according to the hyperparameters, which determine the performance of the SRCNN model, was evaluated in order to verify the effect of hyperparameters on the SRCNN model. Profile, structural similarity (SSIM), peak signal-to-noise ratio (PSNR), and full-width at half-maximum (FWHM) were measured to evaluate the performance of the SRCNN model. The results showed that the performance of the SRCNN model was improved with an increase of the numbers of epochs and training sets, and the learning rate needed to be optimized for obtaining acceptable image quality. Therefore, the SRCNN model with optimal hyperparameters is able to improve CT image quality.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.208-217
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• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• Journal of Advanced Navigation Technology
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• v.6 no.3
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• pp.188-194
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• 2002

DBS is utilized as very useful media in information-oriented society because it covers wide service area and provide high quality services. But DBS needs skill that can receive DBS signal at move. In this paper, it is considered a development of a device to receive DBS and design of a low noise downconverter that use tracking antenna to receive DBS at mobiles unit and ships which navigate in Korea peninsula coast. The structure of dual phase LNB is composed of LNA, BPF, oscillator, mixer, and IF amplifier. And for the position tracking, two input-output phase performed in phase. Measured results showed good performance that with respect to input signal 11.7 GHz~12.2 GHz, noise figure is 0.87 dBmax and conversion gain 62 dB, temperature characterization ${\pm}400$ kHz in respect to - 30 to $60^{\circ}C$, and phase noise -101 dBc/Hz in respect to offset 100 kHz.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.503-510
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• 2003

In CDMA cellular system, because all users share the frequency resource the signals of other user becomes interference which influences the communication quality. The system capacity defined the number of connected users within a cell is determined by the amount of interference, therefore the exact estimation of interference is important to system performance evaluation. In this paper, we propose an approximated function which calculates other cell interference in terms of Riemann-Zeta function in CDMA cellular systems, and compare with simulation results in other to verify its usefulness. The upper and lower bounds of system capacity calculated with the proposed approximated function gives almost alike result with the simulation. The proposed interference bounds are useful to calculate system capacity and to evaluate some algorithm in a hierarchical cellular systems where various propagation environments are mixed.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.487-501
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• 2017

A machine vision system (MVS) is a computer system that utilizes one or more image-capturing devices to provide image data for analysis and interpretation. Recently there have been a number of industrial- and medical-device applications where control charts have been proposed for use with image data. The use of image-based control charting is somewhat different from traditional control charting applications, and these differences can be attributed to several factors, such as the type of data monitored and how the control charts are applied. In this paper, we investigate the adjustment effect of image size and region of interest (ROI) size, when we use control charts to monitor grayscale image data in industry.

• Proceedings of the Korea Concrete Institute Conference
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• 2008.11a
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• pp.785-788
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• 2008

This study is focused on applying heavyweight concrete to ballast used to have stability of a ship. Generally, heavyweight concrete is made from a high density aggregate like magnetite or limonite. However, these materials are hard to obtain them from relevant companies and so expensive. Therefore, this study plans to product heavyweight ballast concrete which is easy to obtain by recycled iron slag. Heavyweight ballast concrete isn't required to meet some compressive strength in use, but it is required to have high flowable and 2.7t/m3 of bulk density to fill the ballast tank densely. The designed field mix proportion of concrete based on the results of pre-experiment shows it can control the temperature crack and has superior chloride corrosion resistance after conducting chloride corrosion experiment. Also, it is prefer that before airtightness voltile corrosion inhibiter(VCI) is added in airtight space of shipyard.