• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.26-30
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• 2018

Planetary global localization is necessary for long-range rover missions in which communication with command center operator is throttled due to the long distance. There has been number of researches that address this problem by exploiting and matching rover surroundings with global digital elevation maps (DEM). Using conventional methods for matching, however, is challenging due to artifacts in both DEM rendered images, and/or rover 2D images caused by DEM low resolution, rover image illumination variations and small terrain features. In this work, we use train CNN discriminator to match rover 2D image with DEM rendered images using conditional Generative Adversarial Network architecture (cGAN). We then use this discriminator to search an uncertainty bound given by visual odometry (VO) error bound to estimate rover optimal location and orientation. We demonstrate our network capability to learn to translate rover image into DEM simulated image and match them using Devon Island dataset. The experimental results show that our proposed approach achieves ~74% mean average precision.

• Bulletin of the Korean Chemical Society
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• v.31 no.12
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• pp.3684-3692
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• 2010

A series of azole-containing piperazine derivatives have been designed and synthesized. The obtained compounds were investigated in vitro for their antibacterial, antifungal and cytotoxic activities. The preliminary results showed that most compounds exhibited moderate to significant antibacterial and antifungal activities in vitro. 1-(4-((4-chlorophenyl) (phenyl)methyl)piperazin-1-yl)-2-(1H-imidazol-1-yl)ethanone and 1-(4-((4-Chlorophenyl)(phenyl)methyl)piperazin-1-yl)-2-(2-phenyl-1H-imidazol-1-yl)ethanone gave remarkable and broad-spectrum antimicrobial efficacy against all tested strains with MIC values ranging from 3.1 to $25\;{\mu}g/mL$, and exhibited comparable activities to the standard drugs chloramphenicol and fluconazole in clinic. Moreover, 2-((4-((4-chlorophenyl)(phenyl)methyl)piperazin-1-yl)methyl)-1H-benzo[d]imidazole was found to be the most effective in vitro against the PC-3 cell line, reaching growth inhibition values (36.4, 60.1 and 76.5%) for each tested concentration: $25\;{\mu}g/mL$, $50\;{\mu}g/mL$ and $100\;{\mu}g/mL$ in dose-dependent manner. The results also showed that the azole ring had noticeable effect on their antimicrobial and cytotoxic activities, and imidazole and benzimidazole moiety were much more favourable to biological activity than 1,2,4-triazole.

• Journal of Microbiology and Biotechnology
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• v.21 no.9
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• pp.968-971
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• 2011

Leuconostoc genus, which comprise heterofermentative lactic acid bacteria, reduces fructose to mannitol by recycling intracellular NADH. To evaluate the mannitol productivities of different Leuconostoc species, 5 stock cultures and 4 newly isolated strains were cultivated in MRS and simplified media containing glucose and fructose (1:2 ratio). Among them, L. citreum KACC 91348P, which was isolated from kimchi, showed superior result in cell growth rate, mannitol production rate, and yield in both media. The optimal condition for mannitol production of this strain was pH 6.5 and $30^{\circ}C$. When L. citreum KACC was cultured in simplified medium in a 2 l batch fermenter under optimal conditions, the maximum volumetric productivity was 14.83 $g{\cdot}l^{-1}h^{-1}$ and overall yield was 86.6%. This strain is a novel and efficient mannitol producer originated from foods to be used for fermentation of fructose-containing foods.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.169-182
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• 2014

High-performance research reactors require fuel that operates at high specific power to high fission density, but at relatively low temperatures. Research reactor fuels are designed for efficient heat rejection, and are composed of assemblies of thin-plates clad in aluminum alloy. The development of low-enriched fuels to replace high-enriched fuels for these reactors requires a substantially increased uranium density in the fuel to offset the decrease in enrichment. Very few fuel phases have been identified that have the required combination of very-high uranium density and stable fuel behavior at high burnup. U-Mo alloys represent the best known tradeoff in these properties. Testing of aluminum matrix U-Mo aluminum matrix dispersion fuel revealed a pattern of breakaway swelling behavior at intermediate burnup, related to the formation of a molybdenum stabilized high aluminum intermetallic phase that forms during irradiation. In the case of monolithic fuel, this issue was addressed by eliminating, as much as possible, the interfacial area between U-Mo and aluminum. Based on scoping irradiation test data, a fuel plate system composed of solid U-10Mo fuel meat, a zirconium diffusion barrier, and Al6061 cladding was selected for development. Developmental testing of this fuel system indicates that it meets core criteria for fuel qualification, including stable and predictable swelling behavior, mechanical integrity to high burnup, and geometric stability. In addition, the fuel exhibits robust behavior during power-cooling mismatch events under irradiation at high power.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.11-18
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• 2021

This paper shows the applicability of deep learning algorithm in predicting target position and getting correction value of impact point in order to improve the accuracy of naval gun firing. Predicting target position, the proposed model using LSTM model and RN structure is expected to be more accurate than existing method using kalman filter. Getting correction value of impact point, the another proposed model suggests a reinforcement model that manages factors which is related in ballistic calculation as data set, and learns using the data set. The model is expected to reduce error of naval gun firing. Combining two models, a ballistic calculation model for improving accuracy of naval gun firing based on deep learning algorithm was designed.

• Steel and Composite Structures
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• v.50 no.1
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• pp.89-105
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• 2024

Multichannel analysis of surface waves (MASW) method has exhibited broad application prospects in the nondestructive detection of interfacial debonding in steel-concrete composite structures (SCCS). However, due to the structural diversity of SCCS and the high stealthiness of interfacial debonding defects, the feasibility of MASW method needs to be investigated in depth. In this study, synthetic parametric study on MASW nondestructive debonding detection for SCCSs is performed. The aim is to quantitatively analyze influential factors with respect to structural composition of SCCS and MASW measurement mode. First, stress wave composition and propagation process in SCCS are studied utilizing 2D numerical simulation. For structural composition in SCCS, the thickness variation of steel plate, concrete core, and debonding defects are discussed. To determine the most appropriate sensor arrangement for MASW measurement, the effects of spacing and number of observation points, along with distances between excitation points, nearest boundary, as well as the first observation point, are analyzed individually. The influence of signal type and frequency of transient excitation on dispersion figures from forwarding analysis is studied to determine the most suitable excitation signal. The findings from this study can provide important theoretical guidance for MASW-based interfacial debonding detection for SCCS. Furthermore, they can be instrumental in optimizing both the sensor layout design and signal choice for experimental validation.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.147-158
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• 2014

In order to investigate how the microstructure of fuel/matrix-interaction (FMI) layers change during irradiation, different U-7Mo dispersion fuel plates have been irradiated to high fission density and then characterized using scanning electron microscopy (SEM). Specifially, samples from irradiated U-7Mo dispersion fuel elements with pure Al, Al-2Si and AA4043 (~4.5 wt.%Si) matrices were SEM characterized using polished samples and samples that were prepared with a focused ion beam (FIB). Features not observable for the polished samples could be captured in SEM images taken of the FIB samples. For the Al matrix sample, a relatively large FMI layer develops, with enrichment of Xe at the FMI layer/Al matrix interface and evidence of debonding. Overall, a significant penetration of Si from the FMI layer into the U-7Mo fuel was observed for samples with Si in the Al matrix, which resulted in a change of the size (larger) and shape (round) of the fission gas bubbles. Additionally, solid fission product phases were observed to nucleate and grow within these bubbles. These changes in the localized regions of the microstructure of the U-7Mo may contribute to changes observed in the macroscopic swelling of fuel plates with Al-Si matrices.

• Current Optics and Photonics
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• v.7 no.3
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• pp.237-247
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• 2023

In middle- and long-distance imaging systems, due to the atmospheric turbulence caused by temperature, wind speed, humidity, and so on, light waves propagating in the air are distorted, resulting in image-quality degradation such as geometric deformation and fuzziness. In remote sensing, astronomical observation, and traffic monitoring, image information loss due to degradation causes huge losses, so effective restoration of degraded images is very important. To restore images degraded by atmospheric turbulence, an image-restoration method based on improved compound multibranch feature fusion (CMFNetPro) was proposed. Based on the CMFNet network, an efficient channel-attention mechanism was used to replace the channel-attention mechanism to improve image quality and network efficiency. In the experiment, two-dimensional random distortion vector fields were used to construct two turbulent datasets with different degrees of distortion, based on the Google Landmarks Dataset v2 dataset. The experimental results showed that compared to the CMFNet, DeblurGAN-v2, and MIMO-UNet models, the proposed CMFNetPro network achieves better performance in both quality and training cost of turbulent-image restoration. In the mixed training, CMFNetPro was 1.2391 dB (weak turbulence), 0.8602 dB (strong turbulence) respectively higher in terms of peak signal-to-noise ratio and 0.0015 (weak turbulence), 0.0136 (strong turbulence) respectively higher in terms of structure similarity compared to CMFNet. CMFNetPro was 14.4 hours faster compared to the CMFNet. This provides a feasible scheme for turbulent-image restoration based on deep learning.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.393-400
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• 2001

This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process (NHPP). The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with generalized model by Goel dependent on the constant reflecting the quality of testing. The performance measures and parametric inferences of the new models, Rayleigh and Gumbel distributions, are discussed. The results of the new models are applied to real software failure data and compared with Goel-Okumoto and Yamada, Ohba and Osaki models. Tools of parameter inference was used method of the maximun likelihood estimate and the bisection algorithm for the computing nonlinear root. In this paper, using the sum of the squared errors, model selection was employed. The numerical example by NTDS data was illustrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1392-1413
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• 2022

In order to meet the rapid development of the unmanned aerial vehicle (UAV) communication needs, cooperative spectrum sensing (CSS) helps to identify unused spectrum for the primary users (PU). However, multi-UAV mode (MUM) requires the large communication resource in a cognitive UAV network, resulting in a severe decline of spectrum efficiency (SE) and energy efficiency (EE) and increase of energy consumption (EC). On this account, we extend the traditional 2D spectrum space to 3D spectrum space for the UAV network scenario and enable UAVs to proceed with spectrum sensing behaviors in this paper, and propose a novel multi-slot mode (MSM), in which the sensing slot is divided into multiple mini-slots within a UAV. Then, the CSS process is developed into a composite hypothesis testing problem. Furthermore, to improve SE and EE and reduce EC, we use the sequential detection to make a global decision about the PU channel status. Based on this, we also consider a truncation scenario of the sequential detection under the sensing delay constraint, and further derive a closed-form performance expression, in terms of the CSS performance and cooperative efficiency. At last, the simulation results verify that the performance and cooperative efficiency of MSM outperforms that of the traditional MUM in a low EC.