• Structural Engineering and Mechanics
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• v.81 no.5
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• pp.565-574
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• 2022

The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (𝚫K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (𝚫K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (ρ) and Variance Account Factor (VAF).

• Human Ecology Research
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• v.60 no.4
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• pp.549-564
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• 2022

This study aimed to develop an e-mentoring youth financial education program and verify its effectiveness for promoting financial empowerment and establishing financial capabilities among independent consumers. A four-session, eight-hour "Youth Financial Empowerment Mentoring Program" was developed. This program dealt with financial literacy and financial psychology factors in an integrated fashion. We used the nonequivalent control group pretest-posttest design to evaluate the program's effectiveness. Specifically, by using Zoom, a virtual conference platform, four mentors of college students were trained for four sessions over two weeks. Meanwhile, four groups were formed with four mentors and 18 high school mentees to implement a four-week e-mentoring program. As a result of the analysis of covariance, significant differences were found between the two groups in all financial psychology factors and financial literacy variables. In addition, the score of the experimental group was higher than that of the control group. As a result of qualitative evaluation through FGI for mentees and mentors, mentees experienced positive changes in financial behavior, beliefs, attitudes, and personal relationships, as well as increased financial knowledge. Meanwhile, mentors experienced positive changes in their introspection into financial behavior and consumption. Considering these results, we can conclude that this program effectively induces participants to learn and reflect on their initiative, which is in line with the original goal of "improving financial empowerment".

• Advances in nano research
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• v.14 no.4
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• pp.363-373
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• 2023

A novel type of steel fiber with a rounded-end shape is presented to improve the bonding behavior of fibers with Carbon Nanotubes (CNT)-reinforced Ultra-High Performance Concrete (UHPC) matrix. For this purpose, by performing a parametric study and using the nonlinear finite element method, the impact of geometric characteristics of the fiber end on its bonding behavior with UHPC has been studied. The cohesive zone model investigates the interface between the fibers and the cement matrix. The mechanical properties of the cohesive zone model are determined by calibrating the finite element results and the experimental fiber pull-out test. Also, the results are evaluated with the straight steel fibers outcomes. Using the novel presented fibers, the bond strength has significantly improved compared to the straight steel fibers. The new proposed fibers increase bond strength by 1.1 times for the same diameter of fibers. By creating fillet at the contact area between the rounded end and the fiber, bond strength is significantly improved, the maximum fiber capacity is reachable, and the pull-out occurs in the form of fracture and tearing of the fibers, which is the most desirable bonding mode for fibers. This also improves the energy absorbed by the fibers and is 4.4 times more than the corresponding straight fibers.

• Applied Chemistry for Engineering
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• v.34 no.3
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• pp.291-298
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• 2023

This research evaluates the sustainability of gasifying livestock manure to produce fuel gas from an economic and carbon emission perspective. The entire process, including gasification, fuel gas purification, and pipeline installation to transport the produced fuel gas to the demanding industrial complex, is analyzed for realistic feasibility. The study is conducted using an ASPEN PLUS simulation with experimental data. The results of the economic and CO₂ life cycle assessments confirm that the fuel gas produced from livestock manure is competitive with natural gas despite having a lower calorific value. When used as a fuel with a high hydrogen content, the fuel gas emits less CO₂ per calorific value, making it more environmentally friendly. A scenario analysis is also performed to determine the expected economics, with price competitiveness being influenced by several factors. Although a significant decrease in natural gas prices could reduce the price competitiveness of the proposed process, it can still be supported by government policies. The cash flow analysis also confirms the economic viability of the process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1530-1544
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• 2023

Data monitoring is an important foundation of modern science. In most cases, the monitoring data is time-series data, which has high application value. The deep learning algorithm has a strong nonlinear fitting capability, which enables the recognition of time series by capturing anomalous information in time series. At present, the research of time series recognition based on deep learning is especially important for data monitoring. Deep learning algorithms require a large amount of data for training. However, abnormal sample is a small sample in time series, which means the number of abnormal time series can seriously affect the accuracy of recognition algorithm because of class imbalance. In order to increase the number of abnormal sample, a data augmentation method called GANBATS (GAN-based Bi-LSTM and Attention for Time Series) is proposed. In GANBATS, Bi-LSTM is introduced to extract the timing features and then transfer features to the generator network of GANBATS.GANBATS also modifies the discriminator network by adding an attention mechanism to achieve global attention for time series. At the end of discriminator, GANBATS is adding averagepooling layer, which merges temporal features to boost the operational efficiency. In this paper, four time series datasets and five data augmentation algorithms are used for comparison experiments. The generated data are measured by PRD(Percent Root Mean Square Difference) and DTW(Dynamic Time Warping). The experimental results show that GANBATS reduces up to 26.22 in PRD metric and 9.45 in DTW metric. In addition, this paper uses different algorithms to reconstruct the datasets and compare them by classification accuracy. The classification accuracy is improved by 6.44%-12.96% on four time series datasets.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.4
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• pp.387-398
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• 2023

Conventional aquaculture faces declining productivity, shifting to recirculating aquaculture system (RAS), known for minimizing water usage and maintaining consistent water temperatures for year-round fish growth. Rainbow trout (Oncorhynchus mykiss), a globally important cold-water species and the third most farmed fish in inland waters of Korea, valued for its fecundity and rapid growth. Dissolved oxygen, an important environmental factor affecting fish production and economics, highlights the need for smart aquaculture practices. Since 2018, the rise of intelligent aquaculture platforms, incorporating information and communications technology (ICT), emphasizes the essential role of RAS implementation. This eight-week study aimed to determine the optimal dissolved oxygen concentration for rainbow trout in RAS, utilizing a device for continuous monitoring, control and record. Dissolved oxygen concentrations were set at 5-6 mg/L, 9-10 mg/L, 14-15 mg/L and 17-18 mg/L. The growth rate significantly decreased at 5-6 mg/L, with no significant differences in other experimental groups. In hematological analysis, growth hormone (GH) was significantly highest at 5-6 mg/L, followed by 9-10 mg/L while Insulin-like growth factor-1 (IGF-1) was significantly lowest at 5-6 mg/L. In conclusion, the optimal dissolved oxygen concentration for rainbow trout in RAS is approximately 9-10 mg/L. Higher concentrations do not contribute to further growth or profitability.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.4
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• pp.98-106
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• 2008

The strengthening in terms of efficiency, easy, economics is very popular method when it is applied to a damaged structures. The purpose of this study develops anchorage system that supports enough strengthening effect without any damage. In addition it is checked whether the method can be conveniently applied to structures. To verify strengthening effect a flexural experiments were performed. Four concrete beams were constructed and tested. Deflections, strains and modes of failure were recorded to examine strengthen of beams. Comparing crack load of each experimental data, yielding load, ultimate load, ductility index, and tendon stress were analyzed.

• Information Systems Review
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• v.17 no.2
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• pp.77-100
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• 2015

This study examined the factors that influence the smartphone user's decision to accept the personalized mobile advertisement. As a theoretical basis, we applied the privacy calculus model (PCM) that illustrates how consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. In particular, we investigated how smartphone users make a risk-benefit assessment under which personalized service as benefit-side factor and information privacy risks as a risk-side factor accompanying their acceptance of advertisements. Further, we extend the current PCM by considering advertisement fatigue as a new factor that may influence the user's acceptance. The research model with five (5) hypotheses was tested using data gathered from 215 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a mobile advertisement service was provided. The results showed that three (3) out of five (5) hypotheses were supported. First, we found that the intention to accept advertisements is positively and significantly influenced by the perceived value of personalization. Second, perceived advertisement fatigue was also found to be a strong predictor of the intention to accept advertisements. However, we did not find any evidence of direct influence of privacy risks. Finally, we found that the significant moderating effect between the perceived value of personalization and advertisement fatigue. This suggests that the firms should provide effective tailored advertisement that can increase the perceived value of personalization to mitigate the negative impacts of advertisement fatigue.

• Journal of Korean Home Economics Education Association
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• v.15 no.4
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• pp.115-132
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• 2003

The purpose of this study is aimed at giving proof that helps the elementary practical arts education system accomplish as the effects are turned out experimentally. Two classes of the sixth grade of J elementary school in Dae-gu have been selected in order to be experimented. One was chosen as an experimental group, the other was done as a comparative group. The creative-problem-solving learning-model was applied to the experimental group, and the traditional way of teaching was applied to the comparative group. For four classes of the sixth grades, ‘chapter 8: Making with recycled materials’ was proceeded as the content. Then. tests about the way of environmental awareness and creativity were carried out twice. After that, the results of pre and after-test in the comparative and experiment groups were compared using the t-test method. Following the analysis of the data collected in this study. the following major observations were obtained: First, children who were educated the creative problem-solving in a practical arts education achieved higher scores than before. Therefore, it turns out that the CPS method is an effective way to improve the environmental awareness in children. It showed that it included lots of daily habits connected with daily life and it made the intention to carry out the environment-preservation stronger and children´s attitude towards the environment improved. Moreover, making with recycled materials was used to solve an environmental problem, affecting in a positive way in our life. It also made the positive recognition about the environment. Second. the application of the creative problem-solving class of the practical arts education can make positive results to children. It helped children to have more interest in the environment around them. Children´s fluency, flexibility and originality in their ideas were improved as much as possible while they were solving problems. Consequently, the application of the creative problem-solving class model of elementary practical arts environmental education lets children expand environment consciousness and creativity.

• Journal of the Korean Society of Food Science and Nutrition
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• v.13 no.2
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• pp.169-174
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• 1984

For the purpose of investigating whether the administration of sunflower pollen load has any influence upon liver cholesterol metabolism in mouse, lipids were isolated from sunflower pollen load, identified and quantitated by thin-layer and gas liquid chromatographies. We also studied changes in liver cholesterol level in mouse according to the amount and the period of pollen load administration. Lipids of sunflower pollen load were constituted 84.10f of neutral lipid, 10.50% of glycolipid and 5.40% of phospholipid. The main fatty acid contents of neutral lipid, glycolipid and phospholipid were ranged 28.48 to 33.70% of linoleic acid, 12.90 to 47.50% of palmitic acid ana 11.20 to 12.20% of oleic acid, however, phospholipid contained more palmitic acid than the other lipids. The body weight of the Pollen fed mouse significantly increased during experimental Period in comparison with control group. From the fact tat the ratio of liver weight to body weight of pollen fed mouse was smaller than that of control group, it was proved that liver lipid metabolism of pollen fed mouse was more active than that of control group. During early experimental period, liver cholesterol level had been increased according to pollen load administration(P.O), and then the level decreased rapidly to the similar level to that of control group at the end of the period.