• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.133-153
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• 2023

In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

• Journal of Marine Life Science
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• v.8 no.2
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• pp.115-120
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• 2023

This study aims to find out a suitable extender and cryoprotective agent (CPA) for cryopreservation and its optimum concentration in order to conduct planned artificial seed production of Korean bullhead Pseudobagrus fulvidraco and to preserve superior sperm. Experiments were designed to investigate the effects of the different combinations of three extenders (I: 300 mM glycose, II: Kurokura extender, III: Li extender), four cryoprotectants (dimethyl sulfoxide, ethylene glycol, methanol and glycerol) and four concentrations (5, 10, 15, 20%) on the cryopreservation of Korean bullhead sperm. Postthawed sperm survival rate and sperm activity index (SAI) were detected to evaluate the effects of sperm cryopreservation. The optimal combination of extender and CPA for cryopreservation of Korean bullhead sperm was extender III + 10 and 15% methanol, resulting in a survival rate and SAI of 66.9 ± 8.7, 67.3 ± 13.1% and 2.6 ± 0.4, 2.6 ± 0.5 respectively, which was higher than had been achieved with other extenders and CPAs.

• The Journal of Engineering Geology
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• v.33 no.4
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• pp.673-687
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• 2023

Exploratory data analysis is the process of observing and understanding data collected from various sources to identify their distributions and correlations through their structures and characterization. This process can be used to identify correlations among conditioning factors and select the most effective factors for analysis. This can help the assessment of landslide susceptibility, because landslides are usually triggered by multiple factors, and the impacts of these factors vary by region. This study compared two stages of exploratory data analysis to examine the impact of the data exploration procedure on the landslide prediction model's performance with respect to factor selection. Deep-learning-based landslide susceptibility analysis used either a combinations of selected factors or all 23 factors. During the data exploration phase, we used a Pearson correlation coefficient heat map and a histogram of random forest feature importance. We then assessed the accuracy of our deep-learning-based analysis of landslide susceptibility using a confusion matrix. Finally, a landslide susceptibility map was generated using the landslide susceptibility index derived from the proposed analysis. The analysis revealed that using all 23 factors resulted in low accuracy (55.90%), but using the 13 factors selected in one step of exploration improved the accuracy to 81.25%. This was further improved to 92.80% using only the nine conditioning factors selected during both steps of the data exploration. Therefore, exploratory data analysis selected the conditioning factors most suitable for landslide susceptibility analysis and thereby improving the performance of the analysis.

• Land and Housing Review
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• v.14 no.4
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• pp.111-120
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• 2023

Indoor air quality has become increasingly important with the increase in time spent in residential environments, impact of external fine dust, yellow dust, and the post-COVID 19 pandemic. Residential mechanical ventilation plays a key role in addressing indoor air quality. The legal standard for residential air changes per hour in Korea is 0.5 ACH. However, there are no standards for the location of supply and return vents. This study atempts to analyze the impact of ventilation performance based on the location of supply and return vents. An experiment was conducted using the CO₂ tracer gas concentration decay method in a mock-up house set inside a large chamber to minimize external influences. The experimental results indicated that the commonly used combination of 2 supply and 2 return vents in living room spaces had a lower mean age of air than the combination of 1 supply and 2 return vents. Using multiple supply and return vents had lower mean age of air than using just 1 supply and 1 return vent.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.883-896
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• 2023

As human activities in Korea are spread throughout the mountains, forest fires often affect residential areas, infrastructure, and other facilities. Hence, it is necessary to detect fire-damaged areas quickly to enable support and recovery. Remote sensing is the most efficient tool for this purpose. Fire damage detection experiments were conducted on the east coast of Korea. Because this area comprises a mixture of forest and artificial land cover, data with low resolution are not suitable. We used Sentinel-2 multispectral instrument (MSI) data, which provide adequate temporal and spatial resolution, and the k-nearest neighbor (kNN) algorithm in this study. Six bands of Sentinel-2 MSI and two indices of normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as features for kNN classification. The kNN classifier was trained using 2,000 randomly selected samples in the fire-damaged and undamaged areas. Outliers were removed and a forest type map was used to improve classification performance. Numerous experiments for various neighbors for kNN and feature combinations have been conducted using bi-temporal and uni-temporal approaches. The bi-temporal classification performed better than the uni-temporal classification. However, the uni-temporal classification was able to detect severely damaged areas.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.688-696
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• 2023

In the present study, free roll decay and resistance performances of fishing vessels were evaluated with the combinations and variations of in the parameters of appendages which are attached to improve motion performance of fishing vessels. Computational Ffluid Ddynamics was used to perform free roll decay and resistance analysis. The roll period and decay coefficient were derived by the variations in the combination and dimensions of the primary appendages of the bilge keel and the under keel. It was observed thatThe variations of in the length of the under keel did not significantly impact to the roll damping coefficient. Conversely, for the bilge keel, an increase in the length and angle resulted in an increase in the roll damping coefficient. Comparison of resistance performance was additionally assessed among the selected hulls with the appendages and bare hull. The resistance of the hull with the appendages was higher than that of the bare hull due owing to the changes of in the pressure on the surface of the hull and trim angle. Throughout the present study, the impact of appendage parameter and arrangement on the free roll decay and resistance performance of fishing vessels were was assessed,. which This will be beneficial for the application of appendages to fishing vessels.

• Animal Bioscience
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• v.36 no.12
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• pp.1831-1841
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• 2023

Objective: This study was realized to evaluate the effects of supplementation with blends of water and fat-soluble vitamins on animal performance and carcass traits of young Nellore bulls. Methods: Forty-three Nellore bulls, with an initial weight of 261±27.3 kg and a mean age of 8±1.0 months, were used. Five animals were slaughtered at the beginning of the experiment (reference group), to determine the initial empty body weight of the bulls that remained in the experiment. The remaining 38 bulls were fed ad libitum and distributed in a completely randomized design in a 2×2 factorial scheme, with or without supplementation of water-soluble (B-blend+ or B-blend-) and fat-soluble (ADE+ or ADE-) vitamin blends. Diets were isonitrogenous (120 g of crude protein/kg dry matter [DM] of total mixed ration) and consisted of a roughage:concentrate rate of 30:70 based on total DM of diet. The experiment lasted 170 days, with 30 days of adaptation and 140 days for data collection. At the beginning and end of the experimental period, the bulls were weighed to determine the average daily gain. To estimate the apparent digestibility of nutrients and microbial efficiency, spot collections of feces and urine were performed for five consecutive days. Results: DM, ashes, organic matter, crude protein, ethereal extract, neutral detergent fiber corrected for residual ash and residual nitrogenous, and N intake and apparent digestibility were not influenced by vitamin supplementation, but total digestible nutrients intake and non-fibrous carbohydrates digestibility were influenced by B complex vitamin supplementation. Nitrogen balance, microbial efficiency, and performance data were not influenced (p>0.05) by vitamin supplementation. Conclusion: Vitamin supplementation (a blend of water-soluble and fat-soluble vitamins or their combinations) does not influence the animal performance and carcass traits of young Nellore bulls.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.169-189
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• 2023

The study aims to synthesize the discussion of the innovation district and suggest an alternative to the governance system of the innovation district. Cluster policies that focus on industrial specialization, networking, value chains, and industrial ecosystems have shown some problems and limits in advanced industrial economies. The innovation district, suitable for the era of urban innovation, convergence of industry, housing, leisure, and related variety, emphasizes cooperation through the convergence of various innovations, workshops and industries, and communities. It is important to build a quintuple helix based on cooperative governance through public-private partnerships, integrate the physical and cultural atmosphere, and service industries that strengthen the place prestige. Beyond the industrial aspect, innovation districts can facilitate changes in urban amenities and lifestyles and creative atmosphere, such as diversity, lifestyle, charms, and openness, and promote social vitality and economic interactions. The governance of innovative districts can promote inter-organizational exchanges, and combinations. When knowledge is created through exchanges between companies, it also affects changes in the governance system, evolving from a rigid and centralized system to an open, dynamic, and organic system. Through the innovation policy, the existing Central Business Districts (CBD) can be able to be transformed into a Central Lifestyle Districts (CLD).

• Korean Journal of Culture and Social Issue
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• v.12 no.4
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• pp.55-75
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• 2006

Most previous research on impression formation has been examined the effects of various informations exclusively within a category, either social category or individual characteristic. The present research examined and compared the priming effects of social category information (we and other) versus personality information (warm and cold) on impression formation. In Study 1, participants primed subliminally with combinations of social category and personality information (we/warm, we/cold, other/warm, and other/cold) were asked to rate faceial pictures on the good-bad and likable-dislikable dimensions. The analysis revealed only the significant main effects of social category information but not any effects of personality information on both the impression dimensions. In Study 2 in which participants were primed with either social category or personality information exclusively, priming of social category information influenced the judgments of likable-dislikable dimension and that of personality information influenced the judgments of good-bad dimension. These results suggest that personality information influences impression in general even though its impacts may be overwritten by social categorical information. The findings were discussed with its implication of everyday's impression formation and the cultural psychological perspectives.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1007-1014
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• 2023

Two-dimensional flow analysis, a fundamental component of hydrodynamics, plays a pivotal role in numerically simulating fluid behavior in rivers and waterways. This modeling approach heavily relies on parameters such as eddy viscosity and roughness coefficient to accurately represent flow characteristics. Therefore, combination of appropriate parameters is very important to accurately simulate flow characteristics. In this study, an automation algorithm was developed and applied to find the optimal combination of parameters. Previously, when applying a two-dimensional flow analysis model, former researchers usually depend on the empirical approach, which causes many difficulties in finding optimal variable values. Using the experimental data, we tracked errors according to the combination of various parameters and applied the algorithm that can determine the optimal combination of parameters with the Python language. The automation algorithm can easily determine the most accurate combination by comparing the flow velocity error values among the two-dimensional flow analysis results among the combinations of 121 (11×11) parameters. In the perspective of utilizing automation algorithm, there is an expected high utility in promptly and straightforwardly determining the optimal combination of parameters with the smallest error.