• Journal of Internet Computing and Services
• /
• v.20 no.5
• /
• pp.105-111
• /
• 2019

Core technologies that lead the Fourth Industrial Revolution era, such as artificial intelligence, big data, and autonomous driving, are implemented and serviced through the rapid development of computing power and hyper-connected networks based on the Internet of Things. In this paper, we implement two different models for drivable area segmentation in various environment, and propose a better model by comparing the results. The models for drivable area segmentation are using DeepLab V3+ and Mask R-CNN, which have great performances in the field of image segmentation and are used in many studies in autonomous driving technology. For driving information in various environment, we use BDD dataset which provides driving videos and images in various weather conditions and day&night time. The result of two different models shows that Mask R-CNN has higher performance with 68.33% IoU than DeepLab V3+ with 48.97% IoU. In addition, the result of visual inspection of drivable area segmentation on driving image, the accuracy of Mask R-CNN is 83% and DeepLab V3+ is 69%. It indicates Mask R-CNN is more efficient than DeepLab V3+ in drivable area segmentation.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.36 no.8
• /
• pp.929-934
• /
• 2012

This study was carried out to analyze the dynamic characteristics of laser tailor-welded blanks (TWBs) made of dissimilar materials. The analysis was performed using Hyper Works 10.0 with Solver LS-DYNA v.971. 2D-Shell was used as the modeling element, and the number of elements and nodes was 35,641 and 36,561, respectively. The impact speed was 10 km/h. To analyze the impact characteristics according to the height of the weld line for the upper and lower parts of the center pillar, the length of the lower part was set as 300 and 400 mm. When the lower part was made of SPFC980 steel with a length of 300 mm, the deformation was the smallest and the absorbed energy of the impact force was the largest. On based the lower part of center pillar, the position of TWB shows the shorter and the better value. In other words, the performance depended on the proportion of the upper part made of high-strength SABC1470 steel. A lower part made of SPFH590 steel showed large deformation. In contrast, a lower part made of SPFC980 steel showed significantly lesser deformation. Therefore, the impact performance of a lower part made of SPFC980 steel with a length of 300 mm showed the best analysis result.

• Journal of Ginseng Research
• /
• v.46 no.3
• /
• pp.337-347
• /
• 2022

Coronavirus disease 2019 (COVID-19) is currently a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 are directly associated with hyper-activation of innate immune response that excessively produce pro-inflammatory cytokines and induce cytokine storm, leading to multi-organ-failure and significant morbidity/mortality. Currently, several antiviral drugs such as Paxlovid (nirmatrelvir and ritonavir) and molnupiravir are authorized to treat mild to moderate COVID-19, however, there are still no drugs that can specifically fight against challenges of SARS-CoV-2 variants. Panax ginseng, a medicinal plant widely used for treating various conditions, might be appropriate for this need due to its anti-inflammatory/cytokine/viral activities, fewer side effects, and cost efficiency. To review Panax ginseng and its pharmacologically active-ingredients as potential phytopharmaceuticals for treating cytokine storm of COVID-19, articles that reporting its positive effects on the cytokine production were searched from academic databases. Experimental/clinical evidences for the effectiveness of Panax ginseng and its active-ingredients in preventing or mitigating cytokine storm, especially for the cascade of cytokine storm, suggest that they might be beneficial as an adjunct treatment for cytokine storm of COVID-19. This review may provide a new approach to discover specific medications using Panax ginseng to control cytokine storm of COVID-19.

• The Bulletin of The Korean Astronomical Society
• /
• v.40 no.1
• /
• pp.49.2-49.2
• /
• 2015

IntraCluster Medium (ICM) located at the galaxy cluster is in the state of very hot, tenuous, magnetized, and highly ionized X-ray emitting plasmas. High temperature and low density make ICM very viscous and conductive. In addition to the high conductivity, fluctuating random plasma motions in ICM, occurring at all evolution stages, generate and amplify the magnetic fields in such viscous ionized gas. The amplified magnetic fields in reverse drive and constrain the plasma motions beyond the viscous scale through the magnetic tension. Moreover, without the influence of resistivity viscous damping effect gets balanced only with the magnetic tension in the extended viscous scale leading to peculiar ICM energy spectra. This overall collisionless magnetohydrodynamic (MHD) turbulence in ICM was simulated using a hyper diffusivity method. The results show the plasma motions and frozen magnetic fields have power law of $E_V^k{\sim}k^{-3}$, $E_M^k{\sim}k^{-1}$. To explain these abnormal power spectra we set up two simultaneous differential equations for the kinetic and magnetic energy using an Eddy Damped Quasi Normal Markovianized (EDQNM) approximation. The solutions and dimensions of leading terms in the coupled equations derive the power spectra and tell us how the spectra are formed. We also derived the same results with a more intuitive balance relation and stationary energy transport rate.

• Journal of electromagnetic engineering and science
• /
• v.10 no.3
• /
• pp.132-137
• /
• 2010

We present results of room-temperature characterization of lithographically manufactured antenna-coupled NbN micro-bolometers. The bolometers are assembled together with a hyper-hemispherical Si lens to couple the incident radiation to the bolometer from the back-side of the substrate. The bolometers are designed to operate at 300~1,000 GHz and they are characterized at 321~782 GHz. Radiation patterns are measured at 321 GHz, 400 GHz, 654 GHz, and at 782 GHz. The frequency dependency of the beamwidth is studied with several azimuthal beam profile measurements at 321~500 GHz.

• Journal of Microbiology and Biotechnology
• /
• v.20 no.4
• /
• pp.718-726
• /
• 2010

A selected fungal strain, for production of the raw-starchdigesting enzyme by solid-state fermentation, was improved by two repeated sequential exposures to ${\gamma}$-irradiation of $Co^{60}$, ultraviolet, and four repeated treatments with Nmethyl-N'-nitrosoguanidine. The mutant strain Aspergillus sp. XN15 was chosen after a rigorous screening process, with its production of the raw-starch-digesting enzyme being twice that of usual wild varieties cultured under preoptimized conditions and in an unsupplemented medium. After 17 successive subculturings, the enzyme production of the mutant was stable. Optimal conditions for the production of the enzyme by solid-state fermentation, using wheat bran as the substrate, were accomplished for the mutant Aspergillus sp. XN15. With the optimal fermentation conditions, and a solid medium supplemented with nitrogen sources of 1% urea and 1% $NH_4NO_3$, 2.5 mM $CoSO_4$, 0.05% (v/w) Tween 80, and 1% glucose, the mutant Aspergillus sp. XN15 produced the raw-starch-digesting enzyme in quantities 19.4 times greater than a typical wild variety. Finally, XN15, through simultaneous saccharification and fermentation of a raw rice corn starch slurry, produced a high level of ethanol with $Y_{p/s}$ of 0.47 g/g.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.11
• /
• pp.1151-1157
• /
• 2009

Ensuring both product quality and reducing material cost are important issue for the design of the piping system of an air conditioner outdoor unit. This paper describes a shape optimization that achieves mass reduction of an air conditioner piping system while satisfying two design constraints on resonance avoidance and the maximum stress in the pipes. In order to obtain optimized design results with various analysis fields considered simultaneously, an automated multidisciplinary analysis system was constructed using PIAnO v.2.4, a commercial process integration and design optimization(PIDO) tool. As the first step of the automated analysis system, a finite element model is automatically generated corresponding to the specified shape of the pipes using a morphing technique included in HyperMesh. Then, the performance indices representing various design requirements (e.g. natural frequency, maximum stress and pipe mass) are obtained from the finite element analyses using appropriate computer-aided engineering(CAE) tools. A sequential approximate optimization(SAO) method was employed to effectively obtain the optimum design. As a result, the pipe mass was reduced by 18 % compared with that of an initial design while all the constraints were satisfied.

• Journal of Advanced Navigation Technology
• /
• v.15 no.2
• /
• pp.313-318
• /
• 2011

Virtualization has recently come under the spotlight as an important emerging technology. The technology was initially focused on services rather than the effective use of the system when it was developed in the 1960s. Now, following with technological advancement, virtualization is used on servers based on x86. The biggest merit by far of this technology is economic. Virtualization enables server integration, which can cut operating expenses (including personnel expenses) since it costs less to purchase, power and maintain multiple servers if they are integrated by the virtualization technology. This study examines the trend of virtualization technology and suggests a roadmap for future server integration.

• Transactions of Materials Processing
• /
• v.29 no.4
• /
• pp.218-228
• /
• 2020

The prediction of final mass and optimized process conditions of injection molded products using Artificial Neural Network (ANN) were demonstrated. The ANN was modeled with 10 input parameters and one output parameter (mass). The input parameters, i.e.; melt temperature, mold temperature, injection speed, packing pressure, packing time, cooling time, back pressure, plastification speed, V/P switchover, and suck back were selected. To generate training data for the ANN model, 77 experiments based on the combination of orthogonal sampling and random sampling were performed. The collected training data were normalized to eliminate scale differences between factors to improve the prediction performance of the ANN model. Grid search and random search method were used to find the optimized hyper-parameter of the ANN model. After the training of ANN model, optimized process conditions that satisfied the target mass of 41.14 g were predicted. The predicted process conditions were verified through actual injection molding experiments. Through the verification, it was found that the average deviation in the optimized conditions was 0.15±0.07 g. This value confirms that our proposed procedure can successfully predict the optimized process conditions for the target mass of injection molded products.

• Structural Monitoring and Maintenance
• /
• v.9 no.3
• /
• pp.289-303
• /
• 2022

In this study, the impact of assigned pixel labels on the accuracy of crack image identification of steel structures is examined by using an atrous separable convolution neural network (ASCNN). Firstly, images containing fatigue cracks collected from steel structures are classified into four datasets by assigning different pixel labels based on image features. Secondly, the DeepLab v3+ algorithm is used to determine optimal parameters of the ASCNN model by maximizing the average mean-intersection-over-union (mIoU) metric of the datasets. Thirdly, the ASCNN model is trained for various image sizes and hyper-parameters, such as the learning rule, learning rate, and epoch. The optimal parameters of the ASCNN model are determined based on the average mIoU metric. Finally, the trained ASCNN model is evaluated by using 10% untrained images. The result shows that the ASCNN model can segment cracks and other objects in the captured images with an average mIoU of 0.716.