• Food Engineering Progress
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• v.14 no.2
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• pp.92-98
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• 2010

In this study, various active functional components in Chinese Quince were extracted by solvent extraction method. A central composit design for optimization was applied to investigate the effects of independent variables such as solvent to sample ratio ($X_{1}$), extraction temperature ($X_{2}$), and extraction time ($X_{3}$) on the soluble solid contents ($Y_{1}$), total phenols ($Y_{2}$), electron donating ability ($Y_{3}$), browning color ($Y_{4}$) and reducing sugar contents ($Y_{5}$). It was found that extraction temperature and extraction time were the main effective factors in this extraction process. The maximum soluble solid contents of 35.77% was obtained at 26.38 mL/g ($X_{1}$), 72.82$^{\circ}C$ ($X_{2}$) and 74.86 min ($X_{3}$) in saddle point. Total phenols were rarely affected by solvent ratio and extraction time, but it was affected by extraction temperature. The maximum total phenols of 20.70% was obtained at 22.61 mL/g ($X_{1}$), 84.49$^{\circ}C$ ($X_{2}$), 77.25 min ($X_{3}$) in saddle point. The electron donating ability was affected by extraction time. The maximum electron donating ability of 94.12% was obtained at 10.65 mL/g ($X_{1}$), 67.78$^{\circ}C$ ($X_{2}$), 96.75 min ($X_{3}$) in saddle point. The maximum browning color of 0.32% was obtained at 23.77 mL/g ($X_{1}$), 87.27$^{\circ}C$ ($X_{2}$), 96.68 min ($X_{3}$) in saddle point. The maximum value of reducing sugar content of 10.55% was obtained at 26.83 mL/g ($X_{1}$), 82.167$^{\circ}C$ ($X_{2}$), 81.94 min ($X_{3}$). Reducing sugar content was affected by extraction time.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.265-276
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• 2023

The purpose of this study was to develop a plan to ensure that students lacking basic science skills acquire the minimum needed science learning ability while completing the common curriculum. We surveyed 27 elementary and secondary science teachers with experience in research and teaching related to basic skills support to investigate their perceptions of the criteria for minimum achievement standards using Consensual Qualitative Research (CQR) and Analytic Hierarchy Process (AHP). The results indicated that the science teachers tended to describe low achievers as lacking science learning competency, accumulating a science learning deficit, and lacking prerequisite knowledge. However, there were some differences in the characteristics that the elementary and secondary teachers paid attention to in students with insufficient science and basic academic skills. Specifically, the secondary teachers demonstrated greater sensitivity towards low learning motivation and difficulties in using scientific symbols, whereas the elementary teachers were more sensitive towards students' attitudes towards science or lack of experience. Furthermore, it has been observed that the prioritization of items, categorized by school level, differs in terms of setting minimum achievement standards to ensure basic skill support. This implies the need to develop minimum achievement standards considering various variables based on the school level. As there are diverse opinions among science teachers, depending on their expertise, regarding the factors to be considered when developing these standards to guarantee science and basic skill support. Based on the findings of the study, policy support is required to enhance teachers' professionalism in developing students' basic skills while considering the individual context and diversity of low achievers. Additionally, it is crucial to establish a shared vision for students lacking basic skills to reduce the gap between national policy and the practices of science teachers in ensuring support for basic skills.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.275-291
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• 2023

Global warming has made the polar regions more accessible, leading to increased demand for the construction of new resource-development plants in oil-rich permafrost regions. The selection of locations of resource-development plants in permafrost regions should consider the surface displacement resulting from thawing and freezing of the active layer of permafrost. However, few studies have considered surface displacement in the selection of optimal locations of resource-development plants in permafrost region. In this study, Analytic Hierarchy Process (AHP) analysis using a range of geospatial information variables was performed to select optimal locations for the construction of oil-sands development plants in the permafrost region of southern Athabasca, Alberta, Canada, including consideration of surface displacement. The surface displacement velocity was estimated by applying the Small BAseline Subset Interferometric Synthetic Aperture Radar technique to time-series Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar images acquired from February 2007 to March 2011. ERA5 reanalysis data were used to generate geospatial data for air temperature, surface temperature, and soil temperature averaged for the period 2000~2010. Geospatial data for roads and railways provided by Statistics Canada and land cover maps distributed by the North American Commission for Environmental Cooperation were also used in the AHP analysis. The suitability of sites analyzed using land cover, surface displacement, and road accessibility as the three most important geospatial factors was validated using the locations of oil-sand plants built since 2010. The sensitivity of surface displacement to the determination of location suitability was found to be very high. We confirm that surface displacement should be considered in the selection of optimal locations for the construction of new resource-development plants in permafrost regions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.45-60
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• 2023

In this study, we analyzed the influence of middle-aged office workers' entrepreneurial competency and entrepreneurial opportunity recognition on entrepreneurial intention by mediating entrepreneurial opportunity evaluation. Sub-variables of entrepreneurial competency were classified into prior knowledge, positive attitude, and social network. For the empirical analysis of this study, an online survey using Naver Office was conducted for about 15 days (February 6, 2023 - February 20, 2023) targeting office workers across the country who are interested in starting a business, and a total of 262 copies were collected and missing values. For 250 copies excluding 12 copies, SPSS Ver.24.0 and PROCESS MACRO Model 4.0 were used for empirical analysis. The results of the analysis are as follows: First, the higher the prior knowledge of the founder's individual competency, social network, and entrepreneurial opportunity recognition, the higher the entrepreneurial opportunity evaluation and entrepreneurial intention. On the other hand, it was found that the positive attitude among entrepreneurs' individual competencies did not affect entrepreneurship opportunity evaluation and entrepreneurial intention. In addition, the magnitude of the influence on entrepreneurial opportunity evaluation and entrepreneurial intention was in the order of entrepreneurial opportunity recognition, prior knowledge, and social network. This is because the positive attitude of middle-aged office workers towards start-up has a negative image of start-up due to the shrinking start-up environment due to COVID-19, fear of failure due to lack of preparation for start-up, and successive cases of start-up failure due to cognitive bias errors due to overconfidence. implying that there is Second, it was found that the evaluation of entrepreneurship opportunities had a significant positive (+) effect on entrepreneurial intention in a situation where the entrepreneur's individual competency and entrepreneurial opportunity recognition were controlled. Third, the startup opportunity evaluation was shown to mediate between the prior knowledge of the entrepreneur's individual competency, social network and entrepreneurial opportunity recognition, and entrepreneurial intention, but it did not mediate between positive attitude and entrepreneurial intention. Fourth, among the factors influencing entrepreneurial opportunity evaluation and entrepreneurial intention, entrepreneurial opportunity recognition was found to be larger than founder's individual competency, confirming the importance of entrepreneurial opportunity recognition. Fifth, it was found that prior knowledge and network, which are individual capabilities of the founder, affect the evaluation of entrepreneurial opportunities and entrepreneurial intention, so that strengthening entrepreneurship education to recognize the importance of cultivating prior entrepreneurial knowledge and experience can revitalize middle-aged office workers' entrepreneurship. confirmed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.157-175
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• 2022

At this moment, a paradigm shift is taking place across all sectors of society for the transition movements to the digital economy. Various movements are taking place in the global agricultural industry to achieve innovative growth using big data which is a key resource of the 4th industrial revolution. Although the government is making various attempts to promote the use of big data, the movement of the agricultural industry as a key player in the use of big data, is still insufficient. Therefore, in this study, effects of performance expectations, effort expectations, social impact, facilitation conditions, based on the Unified Theory of Acceptance and Use of Technology(UTAUT), and innovation tendencies on the acceptance intention of big data were analyzed using the economic and practical benefits that can be obtained from the use of big data for agricultural-related companies as moderating variables. 333 questionnaires collected from agricultural-related companies were used for empirical analysis. The analysis results using SPSS v22.0 and Process macro v3.4 were found to have a significant positive (+) effect on the intention to accept big data by effort expectations, social impact, facilitation conditions, and innovation tendencies. However, it was found that the effect of performance expectations on acceptance intention was insignificant, with social impact having the greatest influence on acceptance intention and innovation tendency the least. Moderating effects of economic benefit and practical benefit between effort expectation and acceptance intention, moderating effect of practical benefit between social impact and acceptance intention, and moderating effect of economic benefit and practical benefit between facilitation condition and acceptance intention were found to be significant. On the other hand, it was found that economic benefits and practical benefits did not moderate the magnitude of the influence of performance expectations and innovation tendency on acceptance intention. These results suggest the following implications. First, in order to promote the use of big data by companies, the government needs to establish a policy to support the use of big data tailored to companies. Significant results can only be achieved when corporate members form a correct understanding and consensus on the use of big data. Second, it is necessary to establish and implement a platform specialized for agricultural data which can support standardized linkage between diverse agricultural big data, and support for a unified path for data access. Building such a platform will be able to advance the industry by forming an independent cooperative relationship between companies. Finally, the limitations of this study and follow-up tasks are presented.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.219-232
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• 2022

Empirical studies on entrepreneurial intentions have been conducted from various perspectives over the past few decades. The unemployment rate has increased as the global economy stagnates in the aftermath of the COVID-19 pandemic, and entrepreneurship is emerging as an alternative to job creation. Although numerous antecedent variables have positive effects on entrepreneurial intention, this study focuses on entrepreneurial self-efficacy as an individual factor and the entrepreneur's family background as an environmental factor. This study analyzed the survey results of 300 global respondents through the online survey platform Prolific. The respondents were screened by asking a question about having had entrepreneurial education. Since the effects of entrepreneurial self-efficacy on entrepreneurial intention have been proved in numerous domestic studies, this study aims to generalize these results by investigating global samples. The moderated mediation analysis was performed using PROCESS to verify the research hypotheses. This research investigated the effect of entrepreneurial knowledge acquisition on entrepreneurial intention via entrepreneurial self-efficacy and the moderated mediation effect of the family background of entrepreneurs. The results of this study are summarized as follows. First, acquisition of entrepreneurial knowledge had a positive effect on entrepreneurial intention. Second, entrepreneurial self-efficacy mediated the relationship between entrepreneurship knowledge acquisition and entrepreneurial intention. Third, the entrepreneurship family background moderated this relationship. Specifically, when the family entrepreneurship background is strong (vs. weak), the positive effect of entrepreneurial knowledge acquisition on entrepreneurial intention via entrepreneurial self-efficacy significantly increased. The implications of this study are as follows. First, in the process of preparing for a own business, entrepreneurial education is a necessary condition to improve the entrepreneurial intention. Second, the higher the level of acquisition of entrepreneurial knowledge, the more positive attitudes toward entrepreneurial intention can be induced. Third, strong family background of entrepreneurship further promotes entrepreneurship intention by increasing entrepreneurial self-efficacy. In conclusion, in order to revitalize entrepreneurship, it is important to provide various entrepreneurial education programs. These educational programs will be able to improve entrepreneurial self-efficacy by providing more opportunities for students to acquire entrepreneurial knowledge, and thereby promote entrepreneurial intention. In addition, it is important to develop and provide advanced educational curriculum for those who have start-up business experiences in their families.

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.51-63
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• 2024

While the government policy to fully adopt BIM in the construction sector is being implemented, the construction and utilization of landscape BIM models are facing challenges due to problems such as limitations in BIM authoring tools, difficulties in modeling natural materials, and a shortage in BIM content including libraries. In particular, plants, fundamental design elements in the field of landscape architecture, must be included in BIM models, yet they are often omitted during the modeling process, or necessary information is not included, which further compromises the quality of the BIM data. This study aimed to contribute to the construction and utilization of landscape BIM models by developing a plant library that complies with BIM standards and is applicable to the landscape industry. The plant library of trees and shrubs was developed in Revit by modeling 3D shapes and collecting attribute items. The geometric information is simplified to express the unique characteristics of each plant species at LOD200, LOD300, and LOD350 levels. The attribute information includes properties on plant species identification, such as species name, specifications, and quantity estimation, as well as ecological attributes and environmental performance information, totaling 24 items. The names of the files were given so that the hierarchy of an object in the landscape field could be revealed and the object name could classify the plant itself. Its usability was examined by building a landscape BIM model of an apartment complex. The result showed that the plant library facilitated the construction process of the landscape BIM model. It was also confirmed that the library was properly operated in the basic utilization of the BIM model, such as 2D documentation, quantity takeoff, and design review. However, the library lacked ground cover, and had limitations in those variables such as the environmental performance of plants because various databases for some materials have not yet been established. Further efforts are needed to develop BIM modeling tools, techniques, and various databases for natural materials. Moreover, entities and systems responsible for creating, managing, distributing, and disseminating BIM libraries must be established.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.9
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• pp.955-960
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• 2008

We investigated and estimated at the characteristics of decomposition and mineralization of benomyl using a design of experiment(DOE) based on the general factorial design in an E-beam process, and also the main factors(variables) with benomyl concentration(X$_1$) and E-beam irradiation(X$_2$) which consisted of 5 levels in each factor was set up to estimate the prediction model and the optimization conditions. At frist, the benomyl in all treatment combinations except 17 and 18 trials was almost degraded and the difference in the decomposition of benomyl in the 3 blocks was not significant(p > 0.05, one-way ANOVA). However, the % of benomyl mineralization was 46%(block 1), 36.7%(block 2) and 22%(block 3) and showed the significant difference of the % that between each block(p < 0.05). The linear regression equations of benomyl mineralization in each block were also estimated as followed; block 1(Y$_1$ = 0.024X$_1$ + 34.1(R$^2$ = 0.929)), block 2(Y$_2$ = 0.026X$_2$ + 23.1(R$^2$ = 0.976)) and block 3(Y$_3$ = 0.034X$_3$ + 6.2(R$^2$ = 0.98)). The normality of benomyl mineralization obtained from Anderson-Darling test in all treatment conditions was satisfied(p > 0.05). The results of prediction model and optimization point using the canonical analysis in order to obtain the optimal operation conditions were Y = 39.96 - 9.36X$_1$ + 0.03X$_2$ - 10.67X$_1{^2}$ - 0.001X$_2{^2}$ + 0.011X$_1$X$_2$(R$^2$ = 96.3%, Adjusted R$^2$ = 94.8%) and 57.3% at 0.55 mg/L and 950 Gy, respectively. A Microtox test using V. fischeri showed that the toxicity, expressed as the inhibition(%), was reduced almost completely after an E-beam irradiation, whereas the inhibition(%) for 0.5 mg/L, 1 mg/L and 1.5 mg/L was 10.25%, 20.14% and 26.2% in the initial reactions in the absence of an E-beam illumination.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.55-79
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• 2013

In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.