• Journal of the Korean Society of Propulsion Engineers
• /
• v.22 no.6
• /
• pp.28-36
• /
• 2018

A study was conducted to apply open-loop control to the combustion instability in a dump combustor using gaseous hydrocarbon fuels. Control power and frequency were varied by employing a loudspeaker under combustion conditions with similar characteristic chemistry times of the fuels. In the case of open-loop control where the frequency was identical to the combustion instability frequency, the open-loop control power affected the control performance. Results obtained from conducted open-loop control tests, where the frequency was different from the combustion instability frequency, show that setting the open-loop control frequency similar to the combustion instability frequency is effective.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2019.01a
• /
• pp.465-467
• /
• 2019

본 논문에서는 영상생성이 가능한 딥러닝 네트워크를 이용하여 조영증강 CT 영상을 획득하는 연구를 수행하였다. CT는 고해상도 영상을 바탕으로 환자의 질병 및 암 세포 진단에 사용되는 의료영상 기법 중 하나이다. 특히, 조영제를 투여한 다음 CT 영상을 획득되는 영상을 조영증강 CT 영상이라 한다. 조영증강된 CT 영상은 물질의 구성 성분의 영상대비를 강조하여 임상의로 하여금 진단 및 치료반응 평가의 정확성을 향상시켜준다. 하지많은 수의 환자들이 조영제 부작용을 갖기 때문에 이에 해당되는 환자의 경우 조영증강 CT 영상 획득이 불가능해진다. 따라서 본 연구에서는 조영증강 영상을 얻지 못하는 환자 및 일반 환자의 불필요한 방사선의 노출을 최소화 하기 위하여 영상생성 딥러닝 기법을 이용하여 CT 영상에서 조영증강 CT 영상을 생성하는 연구를 진행하였다. 영상생성 딥러닝 네트워크는 generative adversarial network (GAN) 모델을 사용하였다. 연구결과 아무런 전처리도 거치지 않은 CT 영상을 이용하여 영상을 생성하는 것 보다 히스토그램 균일화 과정을 거친 영상이 더 좋은 결과를 나타냈으며 생성영상이 기존의 실제 영상과 영상의 구조적 유사도가 높음을 확인할 수 있다. 본 연구결과 딥러닝 영상생성 모델을 이용하여 조영증강 CT 영상을 생성할 수 있었으며, 이를 통하여 환자의 불필요한 방사선 피폭을 최소하며, 생성된 조영증강 CT 영상을 바탕으로 정확한 진단 및 치료반응 평가에 기여할 수 있을거라 기대된다.

• Journal of Preventive Veterinary Medicine
• /
• v.41 no.3
• /
• pp.121-123
• /
• 2017

The hepatitis E virus (HEV) is a leading causative agent of acute hepatitis in humans. Zoonotic HEV strains have been isolated from several animal species, including pigs. New HEV variants have been recently isolated from camels in the Middle East. In the present study, fecal samples from fallow deer, formosan deer, alpaca, and guanaco were analyzed for the detection of HEV. One HEV strain was detected from guanaco, a species of camelids. The nucleotide sequence of guanaco HEV was identical to those of deer HEV-3 strains, which implied the cross-species transmission of HEV-3 from deer to guanaco.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.1
• /
• pp.49-54
• /
• 2019

Since the underwater communication environment, which is used mainly in acoustic channel, is different from terestrial communication, it needs to analyze the appropriate transmission performance in underwater environment to implement the communication services. Appropriate traffic process method for a communication service is required through transmission performance of object traffic for the communication service. In this paper, transmission performance of video traffic on underwater MANET(Mobile Ad-hoc Network) is analyzed and video traffic configuration scheme on underwater MANET with results of performance analysis is suggested, This study is done with computer simulation based on NS(Network Simulator)-3. throughput, transmission delay, packet loss rate is used for transmission performance.

• Journal of Broadcast Engineering
• /
• v.23 no.6
• /
• pp.896-913
• /
• 2018

Seam finding algorithm is one of the most important techniques to construct the high quality 360 VR image. We found that some degradations, such as ghost effect, are generated when the conventional seam finding algorithms (for examples, Voronoi algorithm, Dynamic Programming algorithm, Graph Cut algorithm) are applied, because those make the inefficient masks which cross the body of main objects. In this paper, we proposed an advanced seam finding algorithm providing the efficient masks which go through background region, instead of the body of objects. Simulation results show that the proposed algorithm outperforms the conventional techniques in the viewpoint of the quality of the stitched image.

• The Journal of the Acoustical Society of Korea
• /
• v.37 no.6
• /
• pp.518-524
• /
• 2018

The cover song refers to live recordings or reproduced albums. This paper studies two-dimensional Fourier transform as a feature-dimension reduction method to search cover song fast. The two-dimensional Fourier transform is conducive in feature-dimension reduction for cover song search due to musical-key invariance. This paper extends the previous work, which only utilize the magnitude of the Fourier transform, by introducing an invariant from phase based on the assumption that adjacent frames have the same musical-key change. We compare the cover song retrieval accuracy of the Fourier-transform based methods over two datasets. The experimental results show that the addition of the invariant from phase improves the cover song retrieval accuracy over the previous magnitude-only method.

• Journal of the Semiconductor & Display Technology
• /
• v.17 no.1
• /
• pp.40-44
• /
• 2018

In this paper, the efficiency of the solar system is lowered due to the partial shading such as the environmental factors of the solar panel. In order to solve this problem, a DC OPTIMIZER is proposed for a maximum power generation system of a photovoltaic panel. The proposed DC OPTIMIZER is composed of a buck structure that performs the maximum power point tracking (MPPT) control of each module of the solar panel, thus maximizing the efficiency. In order to verify the proposed DC Optimizer, the efficiency was measured by varying the irradiance using a solar simulator instead of the solar panel. As a result, it showed high efficiency characteristics as the maximum energy conversion efficiency was 99.3% at $800w/m^2$, $900w/m^2$, and the average efficiency was 99.06% excluding $100w/m^2$. The maximum efficiency of MPPT was 99.97% at $200w/m^2$, efficiency showed excellent performance.

• Transactions of Materials Processing
• /
• v.27 no.6
• /
• pp.331-338
• /
• 2018

Electrohydraulic forming (EHF) process is a high speed forming process that utilizes the electric energy discharge in fluid-filled chamber to deform a sheet material. This process is completed in a very short time of less than 1ms. Therefore, finite element analysis is essential to observe the deformation mechanism of the material in detail. In addition, to perform the numerical simulation of EHF, the material properties obtained from the high-speed status, not quasi static conditions, should be applied. In this study, to obtain the parameters in the constitutive equation of Al 6061-T6 at high strain rate condition, a surrogate model using an artificial neural network (ANN) technique was employed. Using the results of the numerical simulation with free-bulging die in LS-DYNA, the surrogate model was constructed by ANN technique. By comparing the z-displacement with respect to the x-axis position in the experiment with the z-displacement in the ANN model, the parameters for the smallest error are obtained. Finally, the acquired parameters were validated by comparing the results of the finite element analysis, the ANN model and the experiment.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.234-241
• /
• 2019

The side effects of using drugs can greatly threaten the health of the public. The reality is that there are very few reports of current side effects. This can be activated by linking adverse drug reactions reporting to the Drug Utilization Review (DUR) currently used by pharmacies. A study of the U.S. medication management system, where drug use assessment is activated, can find ways to activate adverse drug reactions reporting. In 'Pharm IT 3000', which is used as a medication management program in pharmacies, we examined how to enable reporting of adverse drug reactions. The literature study and research on actual program operation have found a convenient way to report side effects by linking the Pharm IT 3000 prescription preparation assessment to the item.

• Journal of Korea Society of Industrial Information Systems
• /
• v.24 no.1
• /
• pp.23-30
• /
• 2019

As deep learning with the network-based algorithms evolve, artificial intelligence is rapidly growing around the world. Among them, finance is expected to be the field where artificial intelligence is most used, and many studies have been done recently. The existing financial strategy using deep-run is vulnerable to volatility because it focuses on stock price forecasts for a single stock. Therefore, this study proposes to construct ETF products constructed through portfolio methods by calculating the stocks constituting funds by using deep learning. We analyze the performance of the proposed model in the KOSPI 100 index. Experimental results showed that the proposed model showed improved results in terms of returns or volatility.