• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.201-217
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• 2022

The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

• Journal of Mushroom
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• v.20 no.4
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• pp.218-226
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• 2022

Flammulina velutipes, known as winter mushroom in the family of Physalacriaceae, is the main edible and export mushroom with the third highest production after oyster and king oyster mushroom in Korea. However, as normal consumers regard F. velutipes as a simple subsidiary material, there is a limitation to increasing mushroom demand. In order to overcome the consumption limit and increase the differentiation of new varieties, it is necessary to breed varieties with enhanced functionality in consideration of consumer preferences. Therefore, the study was performed to analyze nutrient components and several useful functional substances with 26 genetic resources of F. velutipes. Analyses of inorganic compound(Ca, K, Mg) and 15 amino acids revealed that Strain 4148 had the highest content among the 26 strains. Beta-glucan, which increases immune activity and polyphenol, which exert antioxidant effects were higher in non-white strains than in white strains with a small number of exceptions. Among the five fatty acids, linoleic acid(an omega-6 fatty acid) and α-linolenic acid(an omega-3 fatty acid), were detected in six mushroom strains. α-linolenic acid, which was not found in five major mushrooms including oyster mushrooms, was identified in F. velutipes. The results of HPLC analysis showed that 'Auram' (Strain 4232) and 'Baekseung'(Strain 4230) had the highest content of the stabilizing neurotransmitter GABA(15.38 ㎍/ml and 20.56 ㎍/ml, respectively) among non-white and white strains, respectively. Our findings provide useful information for breeding F. velutipes to obtain strains with enhanced functionality.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.25-43
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• 2022

The ultimate record management's purpose is preservation and utilization. However, the National Archives of Korea (NAK)s Portal has problems such as search system aging and search tools dualization. As a result, the users' search satisfaction is not satisfied, and the improvement demand increases. This study aimed to evaluate the NAK's search quality as a preliminary study for NAK search system advancement. To this end, we analyzed the current status of CAMS and NAK's Portal. Then, we established the test sets and evaluated the NAK's Portal quality from the user's point of view. Evaluation results were analyzed using Precision, Recall, F-score, and MRR. The analysis results showed that the overall search performance was low, particularly in the "advanced subject search," which showed low performance in Precision, Recall, and MRR. Thus, improvement is urgently needed. The test sets established for this study are expected to be used as a basis for objectively measuring the improvement of the search performance after the NAK search system advancement.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.398-406
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• 2022

The outer membrane of Gram-negative bacteria is the outermost layer of cellular environment in which numerous biophysical and biochemical processes are in action sustaining viability. Advances in cell engineering enable modification of bacterial genetic information that subsequently alters membrane physiology to adapt bacteria to specific purposes. Surface display of a functional molecule on the outer membranes is one of strategies that directs host cells to respond to a specific extracellular matter or stimulus. While intracellular expression of a functional peptide or protein fused to a membrane-anchoring motif is commonly practiced for surface display, the method is not readily applicable to exogenous or large proteins inexpressible in bacteria. Chemical conjugation at reactive groups naturally occurring on the membrane might be an alternative, but often compromises fitness due to non-specific modification of essential components. Herein, we demonstrated two distinct approaches that enable site-specific decoration of the outer membrane with a fluorescent agent in Escherichia coli. An unnatural amino acid genetically incorporated in a surface-exposed peptide could act as a chemoselective handle for bioorthogonal dye labeling. A surface-displayed α-helical domain originating from a part of a selected heterodimeric coiled-coil complex could recruit and anchor a green fluorescent protein tagged with a complementary α-helical domain to the membrane surface in a site- and hetero-specific manner. These methods hold a promise as on-demand tools to confer new functionalities on the bacterial membranes.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.675-681
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• 2021

With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1098-1105
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• 2021

The International Maritime Organization has steadily strengthened environmental regulations on nitrogen oxides and carbon dioxide emitted from marine vessels. Consequently, the demand for electric propulsion vessels based on eco-friendly elements has increased. To this end, research and development has been steadily conducted for various vessels. In electric propulsion systems, a redundancy configuration is typically adopted to increase reliability and facilitate the onboard arrangement. Furthermore, studies have been actively conducted to ensure the safety of electric propulsion systems through the combination with digital twin technology. A digital twin can be used to predict outcomes in advance by implementing real-world equipment or space in a virtual world like twins, integrating real-world information and data with the virtual world, and performing computer simulations of situations that can occur in a real environment. In this study, we perform failure modes and effects analysis (FMEA) to validate the electric power management system (PMS) redundancy scheme for the digital twin technology development of electric propulsion vessels. Then, we propose the role and algorithm of PMS as a compensation function for preventing primary and secondary damages caused by a single equipment failure of the PMS and preventing additional damages by analyzing the impact on the entire system under real vessel operating conditions based on the redundancy FMEA suggested for the ship classification and certification. We verified the improvement in propulsion conservation through tests.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.211-221
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• 2022

Recently, the demand for the cultivation of upland soil has been increasing, and the rate of conversion of paddy soil into upland soil is also increasing. Theincrease in uneven precipitation due to climate change has resulted in dramatic effects of waterlogging stress on upland crops. Therefore, the present study was conducted to investigate the changes in growth characteristics and the expression patterns of proteins at the two-leaf stage of adzuki beans. The domestic cultivar, Arari (Miryang No. 8), was used to test waterlogging stress. At the two-leaf stage of adzuki beans, plant height slightly decreased androot fresh weight showed significant changes after 3 days of waterlogging treatment. Chlorophyll content was also significantly different after 3 days of waterlogging treatment compared to its content in control plants. Using two-dimensional gel electrophoresis, more than 400 protein spots were identified. Twenty-one differentially expressed proteins from the two-leaf stage were analyzed using linear trap quadrupole-Fourier transform-ion cyclotron resonance mass spectrometry. Of these 21 proteins, 9 were up-regulated and 12 were down-regulated under waterlogging treatment. Protein information resource (https://pir.georgetown.edu/) categories were assigned to all 49 proteins according to their molecular function, cellular component localization, and biological processes. Most of the proteins were found to be involved in the biological process, carbohydrate metabolism and were localized in chloroplasts.

• Korean journal of applied entomology
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• v.61 no.4
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• pp.539-548
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• 2022

In recent decades, the world has entered a new era in terms of the number and variety of biological invasions, due to economic progress and transportation efficiency. Biological invasion is becoming more likely as demand for foreign fresh foods and decorative goods grows. Alien species continue to infiltrate Korea in a variety of ways, and disturb on the insect fauna of Korea. The goal of plant quarantine is to decrease the economic impact of alien pests on the agriculture and forestry industries. In this study, we focused on insects found in imported cut flowers from 1996 to 2020 using pest information system. Overall, 147,160 cut flowers (159 items) were imported into Korea from 69 countries during this time period. Throughout this time, 467 species of insects were found in all imported cut flowers to Korea, total 13,757 detections. They were classified as provisional regulated pests in 273 species, quarantine managed pests in 78 species, and non-quarantine pests in 118 species. Thysanoptera and Hemiptera had the largest number of alien insect detections (more than 80% of the alien insects) among the nine orders. The outcomes of this study have highlighted the need for ongoing inspection activities targeted at preventing quarantine alien pests from entering or incursion in Korea.

• Journal of Powder Materials
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• v.30 no.4
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• pp.324-331
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• 2023

Lithium (Li) is a key resource driving the rapid growth of the electric vehicle industry globally, with demand and prices continually on the rise. To address the limited reserves of major lithium sources such as rock and brine, research is underway on seawater Li extraction using electrodialysis and Li-ion selective membranes. Lithium lanthanum titanate (LLTO), an oxide solid electrolyte for all-solid-state batteries, is a promising Li-ion selective membrane. An important factor in enhancing its performance is employing the powder synthesis process. In this study, the LLTO powder is prepared using two synthesis methods: sol-gel reaction (SGR) and solid-state reaction (SSR). Additionally, the powder size and uniformity are compared, which are indices related to membrane performance. X-ray diffraction and scanning electron microscopy are employed for determining characterization, with crystallite size analysis through the full width at half maximum parameter for the powders prepared using the two synthetic methods. The findings reveal that the powder SGR-synthesized powder exhibits smaller and more uniform characteristics (0.68 times smaller crystal size) than its SSR counterpart. This discovery lays the groundwork for optimizing the powder manufacturing process of LLTO membranes, making them more suitable for various applications, including manufacturing high-performance membranes or mass production of membranes.