• Journal of Korean Society of Environmental Engineers
• /
• v.36 no.4
• /
• pp.231-236
• /
• 2014

Sawdust, produced as an wood by-product, is usable biomass as liquid fuels if decomposed to monomer unit, because the chemical structure are similar to high octane materials found in gasoline. In this study, parameters of thermochemical degradation by acetone-solvolysis reaction of sawdust such as the effect of reaction temperature, reaction time and type of solvent on conversion yield and degradation products were investigated. The liquid products by acetone-solvolysis from sawdust produced various kind of ketone, phenol and furan compounds. The optimum sawdust conversion was observed to be 88.7% at $350^{\circ}C$, 40min. Combustion heating value of liquid products from thermochemical conversion processes was as high as 7,824 cal/g. The energy yield and mass yield in acetone-solvolysis of sawdust was 60.8% and 36.4 g-oil/100g-sawdust after 40 min of reaction at $350^{\circ}C$, respectively. The major components of the acetone-solvolysis products, that could be used as liquid fuel, were 4-methyl-3-pentene-2-one, 1,3,5-trimethylbezene, 2,6-dimethyl-2,5-heptadiene-4-one, 3-methyl-2-cyclopenten-1-one as ketone compounds.

• Journal of the Korean GEO-environmental Society
• /
• v.25 no.4
• /
• pp.21-28
• /
• 2024

In this study, a polyhedral domain decomposition method for Smoothed Particle Hydrodynamics (SPH) analysis is introduced. SPH which is one of meshless methods is a numerical analysis method for fluid flow simulation. It can be useful for analyzing fluidic soil or fluid-structure interaction problems. SPH is a particle-based method, where increased particle count generally improves accuracy but diminishes numerical efficiency. To enhance numerical efficiency, parallel processing algorithms are commonly employed with the Cartesian coordinate-based domain decomposition method. However, for parallel analysis of complex geometric shapes or fluidic problems under dynamic boundary conditions, the Cartesian coordinate-based domain decomposition method may not be suitable. The introduced polyhedral domain decomposition technique offers advantages in enhancing parallel efficiency in such problems. It allows partitioning into various forms of 3D polyhedral elements to better fit the problem. Physical properties of SPH particles are calculated using information from neighboring particles within the smoothing length. Methods for sharing particle information physically separable at partitioning and sharing information at cross-points where parallel efficiency might diminish are presented. Through numerical analysis examples, the proposed method's parallel efficiency approached 95% for up to 12 cores. However, as the number of cores is increased, parallel efficiency is decreased due to increased information sharing among cores.

• Journal of the Korean GEO-environmental Society
• /
• v.25 no.4
• /
• pp.13-20
• /
• 2024

In this paper, a parallel analysis algorithm for Smoothed Particle Hydrodynamics (SPH), one of the numerical methods for fluidic materials, is introduced. SPH, which is a meshless method, can represent the behavior of a continuum using a particle-based approach, but it demands substantial computational resources. Therefore, parallel analysis algorithms are essential for SPH simulations. The domain decomposition algorithm, which divides the computational domain into partitions to be independently analyzed, is the most representative method among parallel analysis algorithms. In Discrete Element Method (DEM) and Molecular Dynamics (MD), the Cartesian coordinate-based domain decomposition method is popularly used because it offers advantages in quickly and conveniently accessing particle positions. However, in SPH, it is important to share particle information among partitioned domains because SPH particles are defined based on information from nearby particles within the smoothing length. Additionally, maintaining CPU load balance is crucial. In this study, a highly parallel efficient algorithm is proposed to dynamically minimize the size of orthogonal domain partitions to prevent excess CPU utilization. The efficiency of the proposed method was validated through numerical analysis models. The parallel efficiency of the proposed method is evaluated for up to 30 CPUs for fluidic models, achieving 90% parallel efficiency for up to 28 physical cores.

• 대한공업교육학회지
• /
• v.36 no.2
• /
• pp.181-199
• /
• 2011

The purpose of this study is to determine the level of key competencies and teacher efficacy of pre-service industrial teachers as related to their personal backgrounds, and to analyze the correlation between personal variables, key competencies and teaching efficacy. This will be provided as basic resources for pre-service teacher training program to improve the understanding of key competencies and teaching efficacy of pre-service industrial teachers. The results of this study are as follows. First, the teacher efficacy of pre-service industrial teachers was found to be above average (M=3.0), and teaching efficacy (M=3.41) was found to be a bit higher than personal teacher efficacy (M=3.28). Upon analyzing the significant differences of teacher efficacy resulting from background variables, it was found that gender and major had no difference while the effect of school year on teaching efficacy of teacher efficacy showed statistically significant differences. Second, the lower regions of key competencies of pre-service industrial teachers all were above the average 3.0. Gender and school year were exhibited no significant difference, and only the global competence of key competencies showed significant difference. Third, it was found that the gender and major of pre-service industrial teachers had no correlation with teacher efficacy and key competencies. On the other hand, school year variable showed significant positive correlation with teacher efficacy (r=.274) and key competencies (r=.168). Lastly, it was found that key competencies and teacher efficacy had positive correlation of r=.475.

• Journal of Korea Water Resources Association
• /
• v.51 no.spc
• /
• pp.1079-1089
• /
• 2018

The majority of existing studies for quantifying uncertainties in climate change impact assessments suggest only the uncertainties of each stage, and not the total uncertainty and its propagation in the whole procedure. Therefore, this study has proposed a new method, the Uncertainty Delta Method (UDM), which can quantify uncertainties using the variances of projections (as the UDM is derived from the first-order Taylor series expansion), to allow for a comprehensive quantification of uncertainty at each stage and also to provide the levels of uncertainty propagation, as follows: total uncertainty, the level of uncertainty increase at each stage, and the percentage of uncertainty at each stage. For quantifying uncertainties at each stage as well as the total uncertainty, all the stages - two emission scenarios (ES), three Global Climate Models (GCMs), two downscaling techniques, and two hydrological models - of the climate change assessment for water resources are conducted. The total uncertainty took 5.45, and the ESs had the largest uncertainty (4.45). Additionally, uncertainties are propagated stage by stage because of their gradual increase: 5.45 in total uncertainty consisted of 4.45 in emission scenarios, 0.45 in climate models, 0.27 in downscaling techniques, and 0.28 in hydrological models. These results indicate the projection of future water resources can be very different depending on which emission scenarios are selected. Moreover, using Fractional Uncertainty Method (FUM) by Hawkins and Sutton (2009), the major uncertainty contributor (emission scenario: FUM uncertainty 0.52) matched with the results of UDM. Therefore, the UDM proposed by this study can support comprehension and appropriate analysis of the uncertainty surrounding the climate change impact assessment, and make possible a better understanding of the water resources projection for future climate change.

• Korean small business review
• /
• v.43 no.1
• /
• pp.165-186
• /
• 2021

Startups are undergoing a change throughout the growth process of startups that appear in existing studies as they move away from the existing B2B or B2C frame and expand their target customer groups to O2O, C2C. In this regard, a new type of startup known as unicorns, a unicorn which has grown rapidly in a short period of time, is being created by successfully attracting government support and external investment in recognition of the potential value of the startup. This study examined the relationship between investment attraction and growth after founding for five representative unicorns in the U.S. and Korea. As a result, it was found that private investment in Korea is passive and defensive, and is attracted after the Series A stage, compared to the U.S., where the growth potential of the startup ecosystem is positively evaluated. In addition, it found that government's support policy throughout the startup's growth process is an abstract and comprehensive policy focusing on initial funding for startups. Therefore, it was suggested that the scope of government policies should be expanded to forster startups as unicorns, and that it is necessary to establish and implement differentiated support policies for each growth of the scale-up of startups. This study is significant in that it presented the criteria for the growth stage and support of startups as well as policy support for scale-up through practical case analysis of unicorns.

• Journal of Service Research and Studies
• /
• v.10 no.4
• /
• pp.57-70
• /
• 2020

Globally, cloud service is a core infrastructure that improves industrial productivity and accelerates innovation through convergence and integration with various industries, and it is expected to continuously expand the market size and spread to all industries. In particular, due to the global pandemic caused by COVID-19, the introduction of cloud services was an opportunity to be recognized as a core infrastructure to cope with the untact era. However, it is still at the preliminary stage for market expansion of cloud service in Korea. This paper aims to empirically analyze how cloud services can be accepted by users by each industry through extended Technology Acceptance Model(TAM), and what factors influence the acceptance and avoidance of cloud services to users. For this purpose, the impact and factors on the acceptance intention of cloud services were analyzed through the hypothesis test through the proposed extended technology acceptance model. The industrial sector selected four industrial sectors of education, finance, manufacturing and health care and derived factors by examining the parameters of TAM, key characteristics of the cloud and other factors. As a result of the empirical analysis, differences were found in the factors that influence the intention to accept cloud services for each of the four industry sectors, which means that there is a difference in perception of the introduction or use of cloud services by industry sector. Eventually it is expected that this study will not only help to understand the intention of using cloud services by industry, but also help cloud service providers expand and provide cloud services to each industry.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.203-213
• /
• 2022

To understand an underlying geological structure via seismic imaging, the velocity information of the subsurface medium is crucial. Although the full-waveform inversion (FWI) method is considered useful for estimating subsurface velocity models, 3D FWI needs a lot-of computing power and time. Herein, we compare the calculation efficiency and accuracy of frequency-domain 2D and 3D acoustic FWIs. Thereafter, we demonstrate that the artifacts from 2D approximation can be partially suppressed via frequency-domain 2D FWI by employing diffraction angle filtering (DAF). By applying DAF, which employs only big reflection angle components, the impact of noise and out-of-plane reflections can be reduced. Additionally, it is anticipated that the DAF can create long-wavelength velocity structures for 3D FWI and migration.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.3
• /
• pp.141-156
• /
• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Journal of Technology Innovation
• /
• v.11 no.1
• /
• pp.147-176
• /
• 2003

This Paper Presents a new measurement technique to derive the level of BSRC (Basic Science and Research Capacity) index by use of the factor analysis which is extended with the assumption of the standard normal probability distribution of the selected explanatory variables. The new measurement method is used to forecast the gap of Korea's BSRC level compared with those of major OECD countries in terms of time lag and to make their international comparison during the time period of 1981∼1999, based on the assumption that the BSRC progress function of each country takes the form of the logistic curve. The US BSRC index is estimated to be 0.9878 in 1981, 0.9996 in 1990 and 0.99991 in 1999, taking the 1st place. The US BSRC level has been consistently the top among the 16 selected variables, followed by Japan, Germany, France and the United Kingdom, in order. Korea's BSRC is estimated to be 0.2293 in 1981, taking the lowest place among the 16 OECD countries. However, Korea's BSRC indices are estimated to have been increased to 0.3216 (in 1990) and 0.44652 (in 1999) respectively, taking 10th place. Meanwhile, Korea's BSRC level in 1999 (0.44652) is estimated to reach those of the US and Japan in 2233 and 2101, respectively. This means that Korea falls 234 years behind USA and 102 years behind Japan, respectively. Korea is also estimated to lag 34 years behind Germany, 16 years behind France and the UK, 15 years behind Sweden, 11 years behind Canada, 7 years behind Finland, and 5 years behind the Netherlands. For the period of 1981∼1999, the BSRC development speed of the US is estimated to be 0.29700. Its rank is the top among the selected OECD countries, followed by Japan (0.12800), Korea (0.04443), and Germany (0.04029). the US BSRC development speed (0.2970) is estimated to be 2.3 times higher than that of Japan (0.1280), and 6.7 times higher than that of Korea. German BSRC development speed (0.04029) is estimated to be fastest in Europe, but it is 7.4 times slower than that of the US. The estimated BSRC development speeds of Belgium, Finland, Italy, Denmark and the UK stand between 0.01 and 0.02, which are very slow. Particularly, the BSRC development speed of Spain is estimated to be minus 0.0065, staying at the almost same level of BSRC over time (1981 ∼ 1999). Since Korea shows BSRC development speed much slower than those of the US and Japan but relative]y faster than those of other countries, the gaps in BSRC level between Korea and the other countries may get considerably narrower or even Korea will surpass possibly several countries in BSRC level, as time goes by. Korea's BSRC level had taken 10th place till 1993. However, it is estimated to be 6th place in 2010 by catching up the UK, Sweden, Finland and Holland, and 4th place in 2020 by catching up France and Canada. The empirical results are consistent with OECD (2001a)'s computation that Korea had the highest R&D expenditures growth during 1991∼1999 among all OECD countries ; and the value-added of ICT industries in total business sectors value added is 12% in Korea, but only 8% in Japan. And OECD (2001b) observed that Korea, together with the US, Sweden, and Finland, are already the four most knowledge-based countries. Hence, the rank of the knowledge-based country was measured by investment in knowledge which is defined as public and private spending on higher education, expenditures on R&D and investment in software.