• Korean Journal of Food Science and Technology
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• v.31 no.4
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• pp.1011-1016
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• 1999

This study was performed to search a physical method having high yield and quality and minimum environmental pollution for extraction of pectin from apple pomace. Based on the physical solubilization of plant cell wall under the condition of high temperature, pressure and shearing stress, apple pomace was treated by a corotating intermeshing type twin-screw extruder with the diameter-to-length ratio of 1/20. The specific mechanical energy of extruder was introduced as system parameter for extrusion process modeling and the shaft speed, feed rate and moisture content as process variables. The yield, average molecular weight and galacturonic acid content of water-soluble polysaccharides obtained by extrusion were, respectively, modeled with the linear functions of the system parameter which was of the form as a linear function of process variables. The specific mechanical energy increased with increase of shaft speed and with decrease of feed rate and moisture content. Out of process variables, moisture content had the greatest effect on specific mechanical energy. The yield increased with increase of specific mechanical energy while the average molecular weight and galacturonic acid content increased with its decrease. In aspects of yield and quality of pectin, the results from this study showed the possibility to replace a traditional acidic method with the extrusion treatment of this study.

• Journal of the Korean Geographical Society
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• v.39 no.6 s.105
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• pp.907-921
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• 2004

Lots of characteristics such as dwelling, neighborhood, and accessibility characteristics affect to the housevalue. Many researches have been done to identify values of each characteristic using hedonic technique. However, there is a limit to identify interaction of each characteristic and variation of each characteristic among the accessibility context. This paper has implemented the Expansion Method research paradigm to model the housevalue determination process in the city of Seoul. The findings of this paper have revealed the presence of contextual variations in the housevalue determination process. The initial model for housevalue reveals that as $F_1$ increases (i.e., larger the number of rooms/bathrooms, larger parking space) and/or $F_2$ increases (i.e., higher owner occupied housing units, higher apartment housing units) and/or $F_3$ increases, (i.e., higher the ratio of higher than college graduated households, 8 school zone, older housing units) the estimated housevalue increases. However, the above relationships drift across their respective contexts. The houses which have negative $F_1$ value, the housevalue does not fluctuate according to the distance to the city center or subcenters. However, the houses which have positive $F_1$ value, the closer to the subcenters or shorter to the river, the higher the estimated housevalues. On the other hand, in areas far from the subcenters, the estimated housevalues does not fluctuate much according to the corresponding $F_2$ level. In areas close to the subcenters, the estimated housevalues vary tremendously according to the $F_2$ value. In the residual analysis, it is revealed that large apartment which are located in Kangnam, IchongDong, MokDong are underestimated. This paper has contributed to our understanding of the housevalue determination process by providing an alternative conceptualization to the traditional approach.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1183-1193
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• 2021

Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

• Applied Chemistry for Engineering
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• v.34 no.1
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• pp.23-29
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• 2023

Microfluidic reactors have been made to achieve significant development for the generation of new functional materials to apply in a variety of fields. Over the last decade, microfluidic reactors have attracted attention as a user-friendly approach that is enabled to control physicochemical parameters such as size, shape, composition, and surface property. Here, we develop a centrifugal microfluidic reactor that can control the flow of fluid based on centrifugal force and generate multifunctional particles of various sizes and compositions. A centrifugal microfluidic reactor is fabricated by combining microneedles, micro- centrifuge tubes, and conical tubes, which are easily obtained in the laboratory. Depending on the experimental control param- eters, including centrifuge rotation speed, alginate concentration, calcium ion concentration, and distance from the needle to the calcium aqueous solution, this strategy not only enables the generation of size-controlled microparticles in a simple and reproducible manner but also achieves scalable production without the use of complicated skills or advanced equipment. Therefore, we believe that this simple strategy could serve as an on-demand platform for a wide range of industrial and academic applications, particularly for the development of advanced smart materials with new functionalities in biomedical engineering.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.389-399
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• 2023

Recently, there has been a growing focus on the Entrepreneurial Intention of Chinese College Students as a key driver of motivational behavior. However, previous research has provided limited analysis on the actual impact of Social Support on the Entrepreneurial Intention of Chinese College Students. The purpose of this study is to enhance the Entrepreneurial Intention of Chinese College Students and to ascertain the mediating effect of Career Adaptability in the relationship between Social Support and Entrepreneurial Intention. Zhejiang Province, the top-ranked province in private economy in China, possesses a strong economic development momentum and an innovative entrepreneurial atmosphere. Therefore, this study selected 194 third and fourth-year undergraduate students from universities in Zhejiang Province as participants and collected data through a survey utilizing measures of Social Support, Career Adaptability, and Entrepreneurial Intention. The collected data was analyzed for correlations between the measured variables using SPSS 26 and Stata 17 SEM Builder for quantification and validation. The results of the study revealed that, firstly, while Social Support did not have a direct impact on Entrepreneurial Intention, it was found to have an indirect influence on Entrepreneurial Intention through Career Adaptability and its various sub-variables. Secondly, Social Support among College Students was found to have a positive impact on Career Adaptability. Thirdly, Career Adaptability among College Students was found to have a positive impact on Entrepreneurial Intention. Based on these analytical findings, this study provides theoretical and practical implications as well as fundamental information for entrepreneurship education and Career Adaptability at the university level.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.167-187
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• 2020

Currently, Korea is changing into an ultra-aging society, and office workers retire at the age of 49.5 on average from their main jobs, and the national pension is delayed from 62 years old to 65 years old by 2034, so research is needed to prepare for the aging of office workers after retirement. The purpose of this study is to examine the factors affecting the intention to start a business after retirement and the mediating effect of another sense of success expectation on life after retirement, targeting office workers nationwide. Changes in individual attitudes and systematic institutional support are needed to prepare for a sustainable job until the age of 100 after retirement, that is, a start-up utilizing wisdom and experience in work life. As a result of the study, the ability to perform the goal as job performance, economic preparation for retirement preparation, preparation for external relations, and future anxiety have a positive effect on the entrepreneurial will, and the ability to use new technologies as job performance, and physical preparation for retirement. Preparation and preparation for internal relations were found to have no effect. In the influencing relationship between preparation for external relations and the will of start-up, and future anxiety and will of start-up, another sense of success was confirmed to have a partial mediation effect. In the relationship between economic preparation and willingness to start a business, the effect of complete mediation was confirmed. In order to increase the will to start a business after retirement, it was confirmed that another sense of expectation for success was an important variable. Introducing a government-sponsored education system in the company to reduce the government's financial burden due to super-aging and achieve corporate growth through employee training while potential founders, office workers, are employed, and entrepreneurship and goals for the three life goals of office workers By introducing a performance improvement program, we were able to get implications that would be a solution to the growth of individuals and businesses and reducing the government's financial burden.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.6
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• pp.497-504
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• 2012

Finite element analysis is to approximate a geometry model developed in computer-aided design(CAD) to a finite element model, thus the conventional shape design sensitivity analysis and optimization using the finite element method have some difficulties in the parameterization of geometry. However, isogeometric analysis is to build a geometry model and directly use the functions describing the geometry in analysis. Therefore, the geometric properties can be embedded in the NURBS basis functions and control points so that it has potential capability to overcome the aforementioned difficulties. In this study, the isogeometric structural analysis and shape design sensitivity analysis in the generalized curvilinear coordinate(GCC) systems are discussed for the curved geometry. Representing the higher order geometric information, such as normal, tangent and curvature, yields the isogeometric approach to be the best way for generating exact GCC systems from a given CAD geometry. The developed GCC isogeometric structural analysis and shape design sensitivity analysis are verified to show better accuracy and faster convergency by comparing with the results obtained from the conventional isogeometric method.

• Journal of the Korean Geotechnical Society
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• v.15 no.1
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• pp.151-160
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• 1999

A series of laboratory tests for the marine clay sampled under the sea of Kwangyang bay have been conducted. The main types of tests are the general index property tests, the oedometer tests and the triaxial compression tests in both undrained(CIU) and drained(CID) conditions. The clayey samples, classified as CL, CH with natural water content of 38.3~84.6% and liquidity index of 0.71~0.98, are in the normally consolidated state with O.C.R. of 1.0l~l.60. The undrained stress path from CIU tests can be normalized with isotropic consolidation pressure$(p_0)$ and equal shear strain contour is linear passing through the origin in the (q, p) plot. The undrained shear strain is found to be the only function of the stress ratio($\eta$) and linear with intercept in the ($\varepsilon/\eta,\eta$) plot. The built-up pore pressure normalized with pc is also linear with respect to $\eta$. and its slope is defined by ´C´ as a pore pressure parameter. Equations to predict the undrained stress path and the shear strain are proposed. It is proved that the proposed equations give better agreements to the measured values than the Cam-clay theories. The failure points of the stress path are located on the same C.S.L. in (q, p) plot during both CIU and CID tests, which justifies the concept of critical state theory.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.69-78
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• 2017

Shannon of the 5G smartphone and Fourier of the signal processing meet in the sampling theorem (2 times the highest frequency 1). In this paper, the initial Shannon Theorem finds the Shannon capacity at the point-to-point, but the 5G shows on the Relay channel that the technology has evolved into Multi Point MIMO. Fourier transforms are signal processing with fixed parameters. We analyzed the performance by proposing a 2N-1 multivariate Fourier-Jacket transform in the multimedia age. In this study, the authors tackle this signal processing complexity issue by proposing a Jacket-based fast method for reducing the precoding/decoding complexity in terms of time computation. Jacket transforms have shown to find applications in signal processing and coding theory. Jacket transforms are defined to be $n{\times}n$ matrices $A=(a_{jk})$ over a field F with the property $AA^{\dot{+}}=nl_n$, where $A^{\dot{+}}$ is the transpose matrix of the element-wise inverse of A, that is, $A^{\dot{+}}=(a^{-1}_{kj})$, which generalise Hadamard transforms and centre weighted Hadamard transforms. In particular, exploiting the Jacket transform properties, the authors propose a new eigenvalue decomposition (EVD) method with application in precoding and decoding of distributive multi-input multi-output channels in relay-based DF cooperative wireless networks in which the transmission is based on using single-symbol decodable space-time block codes. The authors show that the proposed Jacket-based method of EVD has significant reduction in its computational time as compared to the conventional-based EVD method. Performance in terms of computational time reduction is evaluated quantitatively through mathematical analysis and numerical results.