• Trans-
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• v.12
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• pp.81-106
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• 2022

The possibility of metaverse system to be a catalyst for hyper-connected society will be dependent on the speed of connected technological development and its social utilization in the same manner as AI technology. Putting these technical realization processes in brackets, this paper focus on some philosophical-political issues in connection with cognitive-ecological changes in the future cinema which will be influenced by the complexive techno-socio couples of accelerated development of metaverse system. Generally speaking, essence of metaverse system seems to be the degree of immersion by technical accuracy, but is not true. In perspective of cognitive-ecology, flow degree of a picture or photograph is relied not on 'accuracy of representation' but on its message's contextual link-up. In this aspect, real potentiality of metaverse system shall be understood in the context of cognitive-ecological changes of human brain's multi-intelligence networking abilities(intersection of augmentation-simulation and outside-inside) which will be activated in the new structure of natural-social-technological coupling of metaverse system. These cognitive-ecological potentialities have been partially actualized in the cinematic process of tripod mimesis for the longest time, [real contradiction/conflicts (Mimesis-1) -->fictional solutions of cinema (Mimesis-2) --> selective interpretation of spectator's wish fulfillment (Mimesis-3) --> real change (Mimesis-1')]. Therefore metaverse's real potentiality must be considered to be dependent on the possibility of deepening and extending of cinematic circulation between real seperation/problems and ideal connection/solutions. In this context, advanced metaverse system can be compared as a modern technical version of ideal circulation of physics and metaphysics

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.57-65
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• 2021

A hyper-connected intelligence information society is emerging that creates new value by converging IoT, AI, and Bigdata, which are new technologies of the fourth industrial revolution, in all industrial fields. Everything is connected to the network and data is exploding, and artificial intelligence can learn on its own and even intellectual judgment functions are possible. In particular, the Internet of Things provides a new communication environment that can be connected to anything, anytime, anywhere, enabling super-connections where everything is connected. Artificial intelligence technology is implemented so that computers can execute human perceptions, learning, reasoning, and natural language processing. Artificial intelligence is developing advanced technologies such as machine learning, deep learning, natural language processing, voice recognition, and visual recognition, and includes software, machine learning, and cloud technologies specialized in various applications such as safety, medical, defense, finance, and welfare. Through this, it is utilized in various fields throughout the industry to provide human convenience and new values. However, on the contrary, it is time to respond as intelligent and sophisticated cyber threats are increasing and accompanied by potential adverse functions such as securing the technical safety of new technologies. In this paper, we propose a new data modeling method to enable IoT integrated security control by utilizing artificial intelligence technology as a way to solve these adverse functions.

• Korean Journal of Plant Resources
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• v.35 no.5
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• pp.659-666
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• 2022

The effect of rye B chromosome (rye B) on chromosome association was investigated in meiosis of wheat addition line. The wheat addition line was with one Leymus mollis chromosome and one L. racemosus chromosome which are under homoeologous relationship. Chromosome behavior of the two Leymus chromosomes in wheat genetic background was revealed by genomic in situ hybridization. In the first metaphase, most of the two Leymus chromosomes showed univalent in the wheat addition line without rye B (98.1 ± 0.5%). On the other hand, the wheat addition line with rye B showed higher frequency of bivalent (10.3 ± 0.2%) than wheat addition line without rye B (1.9 ± 0.5%). The wheat addition line without rye B showed abnormal bivalents with abnormal structure while the wheat addition line with rye B showed normal bivalent in low frequency. By rye B, some bivalent was composed of wheat and L. racemosus, and some trivalent was composed of wheat bivalents with L. mollis chromosome. Also, some wheat bivalents showed hyper-crossover, so those wheat bivalents showed abnormal structure compared to other wheat bivalents with normal structure such as ring, rod, and pan.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.502-517
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• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.

• Journal of the Korean Geotechnical Society
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• v.38 no.12
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• pp.19-28
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• 2022

Cavities behind concrete walls can adversely affect the stability of structures. Thus study aims to detect cavities behind concrete structures using a microphone in a laboratory model test. A small-scale concrete wall is constructed in a chamber, which is composed of a reinforced concrete plate and dry soil. A plastic bowl is then placed between the plate and soil to simulate a cavity behind the concrete structure. Leaky surface acoustic waves are generated by impacting the concrete plate using a hammer and are measured using a microphone. The measured signals are analyzed using natural frequencies, and cavity-free sections are evaluated. The test results show that the first natural frequency decreases at the cavity section due to the flexural vibration behavior of the plate. In addition, the amplitude corresponding to the first natural frequency decreases as the measurement location becomes farther from the cavity center and significantly decreases at the measurement locations near the rebars. This study demonstrates that a microphone may be useful to detect cavities behind concrete walls.

• The Korea Journal of Herbology
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• v.28 no.5
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• pp.87-93
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• 2013

Objectives : We recently have reported that constituents of OMC-2010 have an immuno-modulatory effects via inhibiting tumor necrosis factor (TNF)-alpha and interleukin (IL)-5. In this study, based on previous data, we investigated the effects of combinations with each OMC constituents on splenocyte cytotoxicity, cytokine productions, and ovalbumin (OVA) induced experimental allergic asthma. Methods : Mouse splenocytes were pre-treated with ethanol extract of constituents of Rehmannia glutinosa (RG), Pinellia ternata (PT), Schisandra chinensis (SC). We made 4 combinations using RG, PT, and SC (A;1:1:1, B;2:1:1, C;1:2:1, D;1:1:2). The cells were pretreated with A, B, C, or D for 1 h, then stimulated with lipopolysaccharide (LPS, $1{\mu}g/ml$) for 48 h. Then the cells were harvested for real-time reverse transcription polymerase chain reaction to detect cytokine productions. Then using effective combination from RG, PR and SC, we administrated the combination orally, then challenged with OVA to induce asthma. Then we analyzed the airway hyper-reactivity (AHR), lung histology and lung TNF-${\alpha}$ and IL-5 mRNA. Results : A. B. C. and D did not showed significant cytotoxicity on splenocytes. Pre-treatment of A inhibited the expression of TNF-${\alpha}$ and IL-5 significantly, but not B, C, and D. In experimental asthma, administration of A significantly inhibited the increase of AHR, lung damage, TNF-${\alpha}$ and IL-5 expression. Conclusions : Theses results could suggest that inhibitory effects of the ideal combination with RG, PT and SC (1:1:1) could be applied to treatment of asthma and study of asthma mechanisms.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.1
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• pp.11-24
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• 2022

It has been reported that the ethanolic extract of the root of Piper methysticum (P. methysticum) inhibits melanogenesis in melanocyte stimulating hormone (MSH)-activated B16 melanoma cells. Flavokawain B (FKB) and Flavokawain C (FKC) isolated from this extract have been found to inhibit melanin production based on anti-melanogenesis activity. This study was designed to find out the inhibition and its process of FKB and FKC on melanin synthesis in melan-a melanocytes. FKB and FKC inhibited melanogenesis at 10 μM, 5 μM respectively in melan-a melanocytes. However, they did not inhibit extracellular tyrosinase activity from melan-a melanocytes. FKB reduced the protein level of tyrosinase (Tyr), tyrosinase-related protein 1 (TRP-1), tyrosinase-related protein 2 (TRP-2), microphthalmia-associated transcription factor (MITF) and the mRNA level of Tyr and TRP-1. FKC reduced the protein level of TRP-2 and MITF and the mRNA level of TRP-1 and Tyr. The reduced expression of Tyr and TRP-1 might be resulted from the decreased MITF which regulates major melanogenic proteins. However, since the mRNA expression of MITF did not change by FKB and FKC treatment, the effects of FKB and FKC on extracellular signal regulating kinase (ERK)/AKT phosphorylation, known to regulate the degradation of MITF, were confirmed. FKB and FKC significantly increased the phosphorylation of ERK1/2, not in AKT. These results suggest that FKB and FKC may be helpful as a potential depigmenting agent for various hyper-pigmentary disorders.

• 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.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.180-193
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• 2021

The complex resistivity method is an exploration technique that can obtain various characteristic information of underground media by measuring resistivity and phase in the frequency domain, and its utilization has recently increased. In this paper, a three-dimensional inversion algorithm for the CR data was developed to increase the utilization of this method. The Poisson equation, which can be applied when the electromagnetic coupling effect is ignored, was applied to the modeling, and the inversion algorithm was developed by modifying the existing algorithm by adopting comlex variables. In order to increase the stability of the inversion, a technique was introduced to automatically adjust the Lagrangian multiplier according to the ratio of the error vector and the model update vector. Furthermore, to compensate for the loss of data due to noisy phase data, a two-step inversion method that conducts inversion iterations using only resistivity data in the beginning and both of resistivity and phase data in the second half was developed. As a result of the experiment for the synthetic data, stable inversion results were obtained, and the validity to real data was also confirmed by applying the developed 3D inversion algorithm to the analysis of field data acquired near a hydrothermal mine.