• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• Atmosphere
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• v.29 no.1
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• pp.87-103
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• 2019

This study introduces the overall characteristics of LOVECLIM version 1.3, the earth system model of intermediate complexity (EMIC), including the installation and operation processes by conducting two kinds of past climate simulation. First climate simulation is the equilibrium experiment during the mid-Holocene (6,000 BP), when orbital parameters were different compared to those at present. The overall accuracy of simulated global atmospheric fields by LOVECLIM is relatively lower than that in Coupled Model Intercomparison Project phase 5 (CMIP5) and Paleoclimate modelling Intercomparison Project phase 3 (PMIP3) simulations. However, surface temperature over the globe, the 800 hPa meridional wind over the mid-latitude coastal region, and the 200 hPa zonal wind from LOVECLIM show similar spatial distribution to those multi-model mean of CMIP5/PMIP3 climate models. Second one is the transient climate experiment from mid-Holocene to present. LOVECLIM well captures the major differences in surface temperature between preindustrial and mid-Holocene simulations by CMIP5/PMIP3 multi-model mean, even though it was performed with short integration time (i.e., about four days in a single CPU environment). In this way, although the earth system model of intermediate complexity has a limit due to its relatively low accuracy, it can be a very useful tool in the specific research area such as paleoclimate.

• Food Engineering Progress
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• v.22 no.4
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• pp.386-391
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• 2018

Effects of a commercial scale intervention system combining ultraviolet (UV)-C and plasma treatments on the microbial decontamination of black pepper powder were investigated. The process parameters include treatment time, time for plasma accumulation before treatment, and water activity of black pepper powder. A significant reduction in the number of indigenous aerobic mesophilic bacteria in black pepper powder was observed after treatments lasted for ${\geq}20min$ (p<0.05) and the reduction was differed by powder manufacturer. The microbial reduction rates obtained by individual UV-C treatment, individual plasma treatment, and UV-C/plasma-combined treatment were 0.2, 0.5, and 1.0 log CFU/g, respectively, suggesting that the efficacy of the microbial inactivation was enhanced by treatment combination. Nonetheless, neither plasma accumulation time nor powder water activity affected the microbial inactivation efficacy of the combined treatment. The UV-C/plasma-combined treatment, however, decreased lightness of black pepper powder, and the decrease generally increased as operation time increased. The plasma accumulation time of 20 min resulted in significant reduction in both lightness and brown color. The results indicate that the commercial-scale intervention system combining treatments of UV-C and plasma has the potential to be applied in the food industry for decontaminating black pepper powder.

• Clean Technology
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• v.27 no.1
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• pp.61-68
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• 2021

Selective catalytic reduction (SCR) is widely used as a method of removing nitrogen oxide in large-capacity thermal power generation systems. Uniform mixing of the injected ammonia and the inlet flue gas is very important to the performance of the denitrification reduction process in the catalyst bed. In the present study, a computational analysis technique was applied to the ammonia injection system design process of a denitrification facility. The applied model is the denitrification facility of an 800 MW class coal-fired power plant currently in operation. The flow field to be solved ranges from the inlet of the ammonia injection system to the end of the catalyst bed. The flow was analyzed in the two-dimensional domain assuming incompressible. The steady-state turbulent flow was solved with the commercial software named ANSYS-Fluent. The nozzle arrangement gap and injection flow rate in the ammonia injection system were chosen as the design parameters. A total of four (4) cases were simulated and compared. The root mean square of the NH3/NO molar ratio at the inlet of the catalyst layer was chosen as the optimization parameter and the design of the experiment was used as the base of the optimization algorithm. The case where the nozzle pitch and flow rate were adjusted at the same time was the best in terms of flow uniformity.

• Journal of Mushroom
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• v.20 no.3
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• pp.127-137
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• 2022

Effects of substrate bed interior environments on mushroom qualities were investigated in oyster mushroom cultivation facilities in which either Reversible Air-Circulation Fans (RACF) blowing air in two directions (upwards and downwards) or customary Convection Fans (CF) with air blowing only upwards were operated throughout the cultivation period. Two days before harvest, the deviation ranges of the bed interior temperature and relative humidity in the facility using RACF were in the ranges of 1.0-1.3℃ and 7.8-9.0% in the first growing cycle, and within 0.7-1.1℃ and 10.0-11.4% in the second cycle. In the facility using CF, the ranges of variation in the indoor environment parameters (5.8-6.4℃ and 21.3-23.1% in the first growing cycle, and 3.4-5.7℃ and 14.6-18.3% in the second growing cycle) were much enlarged compared to those associated with RACF. These results strongly indicate that RACF significantly enhances air uniformity. Some mushroom qualities differed between growing cycles. For instance RACF in the first cycle gave somewhat better qualities than CF, but some qualities, like pileus diameter and stipe length, were slightly lower than those described for CF in the second cycle when the cultivation substrate weakened. The observation that some qualities worsened under RACF conditions, despite better air uniformity during the growing cycle, revealed the possibility that downward wind may exert a non-negligible negative effect on mushroom growth. Therefore in the future, making wind measurements on the interior and exterior of substrate beds is necessary to obtain insights into their influences on mushroom qualities. The RACF operation manual needs to be edited to convey this necessity.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.115-127
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• 2021

With the development of science and technology around the world, the realm of cyberspace, following land, sea, air, and space, is also recognized as a battlefield area. Accordingly, it is necessary to design and establish various elements such as definitions, systems, procedures, and plans for not only physical operations in land, sea, air, and space but also cyber operations in cyberspace. In this research, the importance of cyber targets that can be considered when prioritizing the list of cyber targets selected through intermediate target development in the target development and prioritization stage of targeting processing of cyber operations was selected as a factor to be considered. We propose a method to calculate the score for the cyber target and use it as a part of the cyber target prioritization score. Accordingly, in the cyber target prioritization process, the cyber target importance category is set, and the cyber target importance concept and reference item are derived. We propose a TIR (Target Importance Rank) algorithm that synthesizes parameters such as Event Prioritization Framework based on PageRank algorithm for score calculation and synthesis for each derived standard item. And, by constructing the Stuxnet case-based network topology and scenario data, a cyber target importance score is derived with the proposed algorithm, and the cyber target is prioritized to verify the proposed algorithm.

• Journal of Platform Technology
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• v.10 no.4
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• pp.3-10
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• 2022

In this study, damage resulting from internal flaws was investigated by finite element analysis for the safety evaluation of a non-destructive testing platform for hydrogen pressure vessels. A specimen was modeled and calculated using finite element analysis to determine material properties in accordance with the parameters of the composite material in order to assess the safety of the Type 4 hydrogen pressure vessel. Through this, flaws in the hydrogen pressure vessel were modeled, and test conditions were provided in accordance with rules to look into whether there was safety. Delamination, foreign object, and vertical cracks were modeled for internal flaws, and damage was examined in accordance with failure criteria. As the delamination defect approached the interior of the hydrogen pressure tank, it became more likely to cause damage. Additionally, as the crack depth grew in the case of vertical cracks, the likelihood of crack propagation rose. On the other hand, it was anticipated that the foreign item defect would suffer more damage from the outside in. A non-destructive testing platform will be used to assess the safety of fuel cell vehicles that are already in operation in future research.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.371-380
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• 2023

Relation extraction is to extract relationships between named entities from text. Traditionally, relation extraction methods only extract relations between predetermined subject and object entities. However, in end-to-end relation extraction, all possible relations must be extracted by considering the positions of the subject and object for each pair of entities, and so this method uses time and resources inefficiently. To alleviate this problem, this paper proposes a method that sets directions based on the positions of the subject and object, and extracts relations according to the directions. The proposed method utilizes existing relation extraction data to generate direction labels indicating the direction in which the subject points to the object in the sentence, adds entity position tokens and entity type to sentences to predict the directions using a pre-trained language model (KLUE-RoBERTa-base, RoBERTa-base), and generates representations of subject and object entities through probabilistic crossover operation. Then, we make use of these representations to extract relations. Experimental results show that the proposed model performs about 3 ~ 4%p better than a method for predicting integrated labels. In addition, when learning Korean and English data using the proposed model, the performance was 1.7%p higher in English than in Korean due to the number of data and language disorder and the values of the parameters that produce the best performance were different. By excluding the number of directional cases, the proposed model can reduce the waste of resources in end-to-end relation extraction.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4571-4584
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• 2022

The analysis of rapid flow transients in Reactor Coolant Pumps (RCP) is essential for a reactor safety study. An accurate and precise analysis of the RCP coastdown is necessary for the reactor design. The coastdown of RCP affects the coolant temperature and the colloidal crud in the primary coolant. A realistic and kinetic model has been used to investigate the behavior of activated colloidal crud in the primary coolant and steam generator that solves the pump speed analytically. The analytic solution of the non-dimensional flow rate has been determined by the energy ratio β. The kinetic energy of the coolant fluid and the kinetic energy stored in the rotating parts of a pump are two essential parameters in the form of β. Under normal operation, the pump's speed and moment of inertia are constant. However, in a coastdown situation, kinetic damping in the interval has been implemented. A dynamic model ACCP-SMART has been developed for System Integrated Modular and Advanced Reactor (SMART) to investigate the corrosion due to activated colloidal crud. The Fickian diffusion model has been implemented as the reference corrosion model for the constituent component of the primary loop of the SMART reactor. The activated colloidal crud activity in the primary coolant and steam generator of the SMART reactor has been studied for different equilibrium corrosion rates, linear increase in corrosion rate, and dynamic RCP coastdown situation energy ratio b. The coolant specific activity of SMART reactor equilibrium corrosion (4.0 mg s^-1) has been found 9.63×10^-3 µCi cm^-3, 3.53×10^-3 µC cm^-3, 2.39×10^-2 µC cm^-3, 8.10×10^-3 µC cm^-3, 6.77× 10^-3 µC cm^-3, 4.95×10^-4 µC cm^-3, 1.19×10^-3 µC cm^-3, and 7.87×10^-4 µC cm^-3 for ²⁴Na, ⁵⁴Mn, ⁵⁶Mn, ⁵⁹Fe, ⁵⁸Co, ⁶⁰Co, ⁹⁹Mo, and ⁵¹Cr which are 14.95%, 5.48%, 37.08%, 12.57%, 10.51%, 0.77%, 18.50%, and 0.12% respectively. For linear and exponential coastdown with a constant corrosion rate, the total coolant and steam generator activity approaches a higher saturation value than the normal values. The coolant and steam generator activity changes considerably with kinetic corrosion rate, equilibrium corrosion, growth of corrosion rate (ΔC/Δt), and RCP coastdown situations. The effect of the RCP coastdown on the specific activity of the steam generators is smeared by linearly rising corrosion rates, equilibrium corrosion, and rapid coasting down of the RCP. However, the time taken to reach the saturation activity is also influenced by the slope of corrosion rate, coastdown situation, equilibrium corrosion rate, and energy ratio β.