• Food Science and Preservation
• /
• v.31 no.4
• /
• pp.633-644
• /
• 2024

This study investigated the fermentation characteristics and quality attributes of ale beer brewed with MBA grapes to enhance the diversity of Korean domestic ale beers. The grapes were added to the wort in two forms: must and juice, at ratios of 10% and 20%. The results showed that while ale beer with 20% grape addition began fermentation a day later, all samples completed fermentation well on the sixth day. Increasing MBA grape content lowered the pH and increased total acidity and malic acid content without significantly affecting the sour taste. Higher grape addition also decreased the beer's IBU and bitterness scores in sensory evaluation. The addition of must addition enhanced redness due to anthocyanins, significantly increasing color intensity and EBC value of ale beer. Ale beer with the addition of must exhibited higher antioxidant capacities in total phenolic compound content, DPPH radical scavenging, and FRAP activities compared to that with the addition of juice. Sensory evaluation indicated that ale beer with 20% juice addition was preferred for its color, aroma, sweetness, body, and overall preference. The addition of MBA must improved antioxidant capacity, but ale beer with 20% juice had superior sensory qualities.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.44 no.2
• /
• pp.173-182
• /
• 2024

In recent, there has been a trend toward primarily utilizing data-driven models employing artificial intelligence technologies, such as machine learning, for flood prediction. These data-driven models offer the advantage of utilizing pre-training results, significantly reducing the required simulation time. However, it remains that a considerable amount of flood data is necessary for the pre-training in data-driven models, while the available observed data for application is often insufficient. As an alternative, validated simulation results from physically-based models are being employed as pre-training data alongside observed data. In this context, we developed a flood mapping accelerator to generate flood maps for pre-training. The proposed accelerator automates the entire process of flood mapping, i.e., estimating flood discharge using HEC-1, calculating water surface levels using HEC-RAS, simulating channel overflow and generating flood maps using RAS Mapper. With the accelerator, users can easily prepare a database for pre-training of data-driven models from hundreds to tens of thousands of rainfall scenarios. It includes various convenient menus containing a Graphic User Interface(GUI), and its practical applicability has been validated across 26 test-beds.

• Journal of the Korea Organic Resources Recycling Association
• /
• v.18 no.4
• /
• pp.69-76
• /
• 2010

After feeding mixed samples, VS ranged from 60 to 80% of total costs in 15 days. EC ranged from1.21 to 2.45, 1.25 to 2.1 and 1.2 to 1.88mS/cm when worms were fed with a mixture of by-products of tidal current and sewage sludge, a mixture of by-products of algae producy, and food wastes and a mixture of by-products of algae producy, sewage sludge and food wastes. That means the kinds of mixture don't have any negative impacts on worms survival. With the feed with a mixture of by-products of algae producy and food wastes and a mixture of by-products of algae producy, sewage sludge and food wastes, pH shows stable 5.4 to 6.7, and 6.2 to 7.4 where is suitable for worms. But a mixture of by-products of algae producy and sewage sludge is out of proper scope for raising worms, in other words, extra care will be necessary. In case of Eh, a mixture of by-products of algae producy and sewage sludge make eh negative (-) in early stage so also when feeding worms, also extra care will be needed. NaCl ranged from 0.32 to 0.82% or form 0.23 to 0.61% when a mixture of by-products of algae producy and food wastes and a mixture of by-products of algae producy, sewage sludge and food wastes were fed. So taking care of salts will be essential whenever feeding.

• Journal of the Society of Disaster Information
• /
• v.20 no.3
• /
• pp.484-499
• /
• 2024

Purpose: Recently, due to the aging of safety facilities in national industrial complexes, there has been an increase in the frequency and scale of safety accidents, highlighting the need for a shift toward a prevention-centered disaster management paradigm and the establishment of a digital safety network. In response, this study aims to provide an information system that supports more rapid and precise decision-making during disasters by utilizing digital twin-based integrated control technology to predict the spread of hazardous substances, trace the origin of accidents, and offer safe evacuation routes. Method: We considered various simulation results, such as surface diffusion, upper-level diffusion, and combined diffusion, based on the actual characteristics of hazardous substances and weather conditions, addressing the limitations of previous studies. Additionally, we designed an integrated management system to minimize the limitations of spatiotemporal monitoring by utilizing an IoT sensor-based backtracking model to predict leakage points of hazardous substances in spatiotemporal blind spots. Results: We selected two pilot companies in the Gumi Industrial Complex and installed IoT sensors. Then, we operated a living lab by establishing an integrated management system that provides services such as prediction of hazardous substance dispersion, traceback, AI-based leakage prediction, and evacuation information guidance, all based on digital twin technology within the industrial complex. Conclusion: Taking into account the limitations of previous research, we used digital twin-based AI analysis to predict hazardous chemical leaks, detect leakage accidents, and forecast three-dimensional compound dispersion and traceback diffusion.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.37 no.4
• /
• pp.267-274
• /
• 2024

Hydrogen embrittlement fracture poses a challenge in ensuring the structural integrity of materials exposed to hydrogen-rich environments. This study advances our comprehension of hydrogen-induced fracture through an integrated numerical modeling approach. In addition, it employs a ductile fracture model named the Gurson-cohesive model (GCM) and hydrogen diffusion analysis. GCM is employed as a fracture model that combines the Gurson model to illustrate the continuum damage evolution and the cohesive zone model to describe crack surface discontinuity and softening behavior. Moreover, porosity and stress triaxiality are considered as crack initiation criteria . A hydrogen diffusion analysis is also integrated with the GCM to account for hydrogen enhanced decohesion (HEDE) mechanisms and their subsequent impacts on crack initiation and propagation. This framework considers the influence of hydrogen on the softening behavior of the traction-separation relationship on the discontinuous crack surface. Parametric studies explore the sensitivity to diffusion properties and hydrogen-induced fracture properties. By combining numerical models of hydrogen diffusion and the ductile fracture model, this study provides an understanding of hydrogen-induced fracture and thereby contributes significantly to the ongoing efforts to design materials that are resilient to hydrogen embrittlement in practical engineering applications.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.4
• /
• pp.69-79
• /
• 2024

Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

• Journal of Korean Society of Archives and Records Management
• /
• v.24 no.3
• /
• pp.85-104
• /
• 2024

While there have been ongoing discussions and attempts to utilize archives for marketing purposes in various organizations, including businesses, there has been a lack of clarity regarding what should be archived and what should be considered as marketing targets within an organization's history. Consequently, historical marketing has often been past-oriented, with results varying significantly based on the capabilities of those in charge. To introduce and effectively utilize archives in organizational settings, it is crucial to demonstrate that archives can positively impact organizational performance. The Heritage Archives is a utilization plan that offers an approach to digitizing and preserving the valuable heritage and assets of a business, explaining them to various stakeholders through records, serving as a foundation for building trust in the business, and linking them to marketing, branding, and other applications. This study focuses on fundamental concepts for constructing and utilizing heritage archives by defining and interpreting key concepts such as the affordance of records, organizational heritage, and heritage assets. To this end, the study incorporates Geoffrey Yeo's affordance and John M.T. Balmer's concept of heritage. In addition, it compares definitions of assets in KS Q ISO 55000:2021, KS X ISO 15489-1:2016, and KS X ISO 30300:2020. Through the study's findings, insights can be obtained for organizations seeking to implement heritage archives and leverage them for marketing, branding, and related purposes.

• Information Systems Review
• /
• v.26 no.1
• /
• pp.73-91
• /
• 2024

Recently, e-learning platforms are rapidly growing by innovating the education industry by applying various IT technologies. Because student participation in the online environment is considered a prerequisite for learning, low participation rates are considered one of the most important issues determining the performance of e-learning platforms. Gamification has grown rapidly over the past decades and is highly valued for its applicability in education because it is expected to enhance learning motivation. However, despite the interest of researchers, previous studies have reported conflicting results on the effect of gamification on participation rates in the context of e-learning platforms, and have mainly studied structural gamification, but have not sufficiently addressed the effects of content gamification. In this context, this study aims to analyze the effect of content gamification on e-learning platform engagement and to explore the boundary conditions moderating this effect. For empirical analysis, 5,017 data registered from February 11, 2022 to May 31, 2022 were analyzed for the education platform entry (https://playentry.org). The propensity score matching method and Poisson multilevel regression model were applied as analysis methods. As a result of the analysis, content gamification had a statistically significant effect on engagement, and the interaction effects of interaction and content difficulty were statistically significant.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.19 no.4
• /
• pp.215-229
• /
• 2024

The purpose of this study was to explore various factors that affect the organizational commitment of health teachers' behavioral characteristics and explain the causal relationship between each factor. As an exploratory study, the subjects were about 500 people working as health teachers. A survey was conducted, and 190 responses were collected. Descriptive statistics were analyzed using SPSS, and the measurement model and hypotheses were tested using structural equation modeling. As a result of the analysis, the behavioral characteristics of health teachers were found to have a positive effect on their self-efficacy, and the behavioral characteristics and self-efficacy were found to have a positive effect on emotional commitment. In addition, health teachers' self-efficacy has a positive effect on emotional commitment, which means that rather than their behavioral characteristics having a direct effect on emotional commitment, their behavioral characteristics indirectly affect emotional commitment through a mediator called self-efficacy. It shows that it has an impact. In particular, it was confirmed that the school nurse's level of awareness of the importance of the task affected self-efficacy and emotional commitment. The implication of this study is that it explained the phenomenon of transfer of their behavioral characteristics to organizational commitment by empirically revealing that the competency, or behavioral characteristics, of health teachers are a factor affecting organizational commitment through self-efficacy. The goal is to empirically demonstrate that awareness of task importance, a job characteristic, affects self-efficacy and organizational commitment. The results of the study are expected to be able to suggest directions for capacity building and operation of health teachers.

• Culinary science and hospitality research
• /
• v.9 no.4
• /
• pp.163-178
• /
• 2003

The purpose of this study is to find the effect of restaurant brand image upon service quality, price acceptability, and revisit intention, and to propose the importance of brand image to operators and managers who manage restaurants. To accomplish the purpose of this study, sampling was taken among customers who visit six deluxe hotels and six family restaurants in Seoul. Six hundreds questionnaires were distributed to each hotel and restaurant and 487 valid samples were selected for statistical analysis. The questionnaire consists of 77 items about demographical characteristics, brand image, service quality, revisit intention, price acceptability, and spending patterns. SPSS WIN 10.0 was used for statistical analysis. A research model was built up and three null hypotheses were established. Based on theses research model and three null hypotheses, the test was conducted, and the results are as follows. Brand image has an effect upon service quality, and furthermore this can be preceding variable of service quality. Also Service quality has an effect upon price acceptability and revisit intention.