• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.5
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• pp.67-80
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• 2022

This study was conducted to derive policy measures such as fostering and supporting by examining the actual conditions of domestic startups. The subject of this study was the start-ups located in Seongnam-si, where Pangyo Techno Valley, which is the highest-level innovation cluster in Korea and is evaluated as a start-up mecca. Startups were defined as startups under 7 years old based on new technologies such as IT, BT, and CT, and the subjects of the study were selected. This can be seen as a step forward from previous research in that it embodies the concept of a startup that was previously abstract in a quantitatively measurable way. As a result of the analysis, about 94% of startups are distributed in the so-called "Death Valley" growth stage, and startups above scale-up, which means full-scale growth beyond BEP, account for about 6%. appeared to be occupied. He cited the problem of start-up funds as the biggest difficulty in the early stages of startups, and cited the loan evaluation method that prioritizes sales or collateral in raising funds as the biggest problem. In addition, start-ups rated the access to private investment capital such as VC, AC, and angel investors at a low level compared to policy funds, which are public funds. Most startups showed a lot of interest in overseas expansion, and they chose matching overseas investors such as overseas VCs as the biggest support for overseas expansion. The overall competitiveness in the overseas market was 49.6 points, which is less than 50 points out of 100, indicating that the overall competitiveness was somewhat inferior. It was analyzed that public support and investment in overseas sales channels (sales channels, distribution networks, etc.) should be prioritized along with enhancement of technological competitiveness in order for domestic startups to increase their competitiveness in overseas markets as well as in the domestic market.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Soil and Groundwater Environment
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• v.12 no.4
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• pp.25-31
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• 2007

Characterizing the risk posed by a mixture of chemicals is a challenging task due to the chemical interactions of individual components that may affect their physical behavior and hence alter their exposure to receptors. In this study, cell tests that represent subsurface environment were carried out using benz[a]anthracene (BaA) and p-xylene focusing on phasetransforming interaction to verify increased mobility and risk of highly sorbed pollutants in the presence of less sorbed, mobile liquid pollutants. A transport model was also developed to interpret results and to simulate the same process on a field scale. The experimental results showed that BaA had far greater mobility in the presence of p-xylene than in the absence of that. The main transport mechanisms in the vadose zone were by dissolution to p-xylene or water. The transport model utilizing Defined Time Steps (DTS) was developed and tested with the experimental results. The predicted and observed values showed similar tendency, but the more work is needed in the future study for more precise modeling. The field-scale simulation results showed that transport of BaA to groundwater table was significantly faster in the presence of NAPL, and the oral carcinogenic risk of BaA calculated with the concentration in groundwater was 15${\sim}$87 times larger when mixed with NAPL than when solely contaminated. Since transport rate of PAHs is very slow in the subsurface without NAPL and no degradation of PAHs was considered in this simulation during the transport, the increase of risk in the presence of NAPL is expected to be greater for the actual contaminated site.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.81-94
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• 2006

The water quality impacts of forest fragmentation at the Doam-dam watershed were evaluated in this study. For this ends, the watershed scale model, Soil and Water Assessment Tool (SWAT) model was utilized. To exclude the effects of different magnitude and patterns in weather, the same weather data of 1985 was used because of significant differences in precipitation in year 1985 and 2000. The water quality impacts of forest fragmentation were analyzed temporarily and spatially because of its nature. The flow rates for Winter and Spring has increased with forest fragmentations by $8,366m^3/month$ and $72,763m^3/month$ in the S1 subwatershed, experiencing the most forest fragmentation within the Doam-dam watershed. For Summer and Fall, the flow rate has increased by $149,901m^3/month$ and $107,109m^3/month$, respectively. It is believed that increased flow rates contributed significant amounts of soil erosion and diffused nonpoint source pollutants into the receiving water bodies. With the forest fragmentation in the S1 watershed, the average sediment concentration values for Winter and Spring increased by 5.448mg/L and 13.354mg/L, respectively. It is believed that the agricultural area, which were forest before the forest fragmentation, are responsible for increased soil erosion and sediment yield during the spring thaw and snow melts. For Spring and Fall, the sediment concentration values increased by 20.680mg/L and 24.680mg/L, respectively. Compared with Winter and Spring, the increased precipitation during Summer and Fall contributed more soil erosion and increased sediment concentration value in the stream. Based on the results obtained from the analysis performed in this study, the stream flow and sediment concentration values has increased with forest fragmentation within the S1 subwatershed. These increased flow and soil erosion could contribute the eutrophication in the receiving water bodies. This results show that natural functionalities of the forest, such as flood control, soil erosion protection, and water quality improvement, can be easily lost with on-going forest fragmentation within the watershed. Thus, the minimize the negative impacts of forest fragmentation, comprehensive land use planning at watershed scale needs to be developed and implemented based on the results obtained in this research.

• Korean Journal of Psychosomatic Medicine
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• v.21 no.1
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• pp.18-26
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• 2013

Objectives : Type D personality was originally introduced to study the role of personality in predicting outcomes of heart disease. However, researches showed that other medical conditions are also affected by this personality. The purpose of this study was to evaluate the relationship between type D personality and somatic symptom complaints in depressive patients. Methods : Eighty-two individuals diagnosed with depressive disorder were included. Type D personality was measured with DS14. Patient Health Questionnaire(PHQ) 9 and 15 were used to measure depression severity and somatization tendencies. For alexithymia, TAS-20 was used. Student T-test and linear regression analysis were performed. The best regression model was determined by stepwise variable selection. Results : More than half of the subjects(56%) complained at least medium degree somatic symptoms according to PHQ-15 criteria. Two-thirds of the subjects were classified as Type D personality(63.4%). The mean PHQ-15 score of the Type D individuals was significantly higher than the remaining subjects(PHQ-15 mean=12.7, $p=8.2{\times}10^{-7}$). The best regression model included age, PHQ-9 score and NA subscale score as predictor variables. Among these, only the coefficients of age($p=1.5{\times}10^{-3}$) and NA score($p=1.5{\times}10^{-7}$) were found to be statistically significant. Conclusions : The result showed that Type D personality was one of the strong predictors of somatic complaints among depressive individuals. The finding that negative affectivity rather than social inhibition was more closely associated with somatization tendencies does not fully agree with the traditional explanation that inability to express negative emotion predispose the individuals to somatic symptoms. The finding that alexithymia was not shown to be a significant predictors also substantiated this discrepancy. However, it might be possible that the high correlation between NA and SI subscore(r=0.65) and between NA and TAS-20 score(r=0.44) hid the additional effects of social inhibition and alexithymia. Further research with a larger sample would be needed to investigate the effects of the latter two components over and above the effect of negative affectivity on the somatic complaints in depressive patients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.423-433
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• 2019

In order to predict the seabed topography change due to the construction of offshore wind power structures in the west-southern sea of Korea, field observations for tides, tidal currents, suspended sediment concentrations and seabed sediments were carried out at the same time. These data could be used for numerical simulation. In numerical experiments, the empirical constants for the suspended sediment flux were determined by the trial and error method. When a concentration distribution factor was 0.1 and a proportional constant was 0.05 in the suspended sediment equilibrium concentration formulae, the calculated suspended sediment concentrations were reasonably similar with the observed ones. Also, it was appropriate for the open boundary conditions of the suspended sediment when the south-east boundary corner was 11.0 times, the south-west was 0.5 times, the westnorth 1.0 times, the north-west was 1.0 times and the north-east was 1.0 times, respectively, using the time series of the observed suspended sediment concentrations. In this case, the depth change was smooth and not intermittent around the open boundaries. From these calibrations, the annual water depth change before and after construction of the offshore wind power structures was shown under 1 cm. The reason was that the used numerical model for the large scale grid could not reproduce a local scour phenomenon and they showed almost no significant velocity change over ± 2 cm/s because the jacket structures with small size diameter, about 1 m, were a water-permeable. Therefore, it was natural that there was a slight change on seabed topography in the study area.

• Cartoon and Animation Studies
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• s.28
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• pp.209-233
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• 2012

The animation cluster in Korea has begun as a part of the local cultural cluster in the late 1990s with components of companies, local governments, educational institutions, and human resources, which were necessary to run the cluster. And, the animation cluster was initiated for the purpose of encouraging regional economies, but the basic unit was the local on a small scale. Because of this inherent weakness in the local cluster, it was needed to add some additional strategies that could expand the local animation industry into the formal leading industry. That is why the development policy was set up, and the local promotion agency based on this policy was established. It has been several years to manage the local promotion agency, and it is reported that there have been some visible effects. But, it is found out that analyzing the outcome of small unit cluster on the basis of existing criteria on a large scale is not reliable, which means it is not possible to evaluate the outcome of local cluster in a material way. Some examples of problems are as follows. First, the local cluster was made not autonomously but deliberately. Second, the animation cluster of each province has the same market as its target. Therefore, this research - on the basis of the diamond model - focuses on analyzing the existence and role of local promotion agencies rather than evaluating the outcome itself. Through the cases of two provincial cities, Chuncheon and Bucheon, this research examines if it is possible to evaluate the outcome of local clusters managed by promotion agencies.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.4 no.3_4
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• pp.79-91
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• 1971

A boat seine has been used as a major fishing gear for catching anchovy (Engraulis japonica) in the southern coastal waters of Korea since 1920s. The original seine was operated by two rowing boats as the haul seine. The rowing boats were, in recent, replaced by powered boats. The net size was enlarged by more than three times the original nit as they began to by operated in the deeper waters of approximately sixty meters. However, there are many problems in the efficiency of the fishing gear to be improved. The authors studied on the hydrodynamic resistance and performance of the boat seine net of the 1/10 scale model in tow. The results are summaried as follows. 1. The hydrodynamic resistance converted from model experiment into the full scale is: $$R_1=30,000\;v^{1.2}\;(0.2{\leqq}v{\leqq}1.0)$$ $$R_2=16,000\;v^2\;(0.2{\leqq}v{\leqq}0.6)$$ where $R_1$ and $R_2$ denote the resistance of whole gear and of bag net in kg respectively, and v the speed of flow in m/sec. 2. In the extension wing, approximately seventy percent of the length of the ground rope from the towing end to the inside-wing slopes down from sea level toward the sea bottom, while the thirty percent of the inside of it remains parallel with th: 5:a level. The performance is regarded to b: inefficient for driving fish shoal into the inside-wing, especially for the shoal diving suddenly. 3. At the towing speed higher than 0.2 m/sec, the trailing edge of the inside-wing is blown backward beyond the seaming line connecting the inside-wing and the mouth of the bag net. It is regarded as an unreasonable performance to drive the fish shoal smoothly into the bag net. 4. At the towing speed higher than 0.2 m/sec, the posterior end of the lower bosom is lifted up above the level of the ground rope of the inside-wing. It is considered that the fish shoal diving suddenly can escape through the discrepancy between the lower bosom and the sea bottom, even if the ground rope of the inside-wing sweeps the sea bottom. 5. The angle of inclination of the upper bosom is estimated as $35\~40^{\circ}$. It seems that the inclination is too steep to drive smoothly the fish shoal diving toward the sea bottom into the bag net. 6. In structure, circumference of the posterior section of the bag net is wider by 1.3 times that of the anterior section. Actually in towing at a speed higher than 0.2m/sec, however, the circumference of the posterior section becomes smaller than that of the anterior section. It is recommended to be designed in a long cylindrical form.

• Journal of Microbiology and Biotechnology
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• v.29 no.10
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• pp.1607-1623
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• 2019

Sediment bioelectrochemical systems (SBESs) can be integrated into brackish aquaculture ponds for in-situ bioremediation of the pond water and sediment. Such an in-situ system offers advantages including reduced treatment cost, reusability and simple handling. In order to realize such an application potential of the SBES, in this laboratory-scale study we investigated the effect of several controllable and uncontrollable operational factors on the in-situ bioremediation performance of a tank model of a brackish aquaculture pond, into which a SBES was integrated, in comparison with a natural degradation control model. The performance was evaluated in terms of electricity generation by the SBES, Chemical oxygen demand (COD) removal and nitrogen removal of both the tank water and the tank sediment. Real-life conditions of the operational parameters were also experimented to understand the most close-to-practice responses of the system to their changes. Predictable effects of controllable parameters including external resistance and electrode spacing, similar to those reported previously for the BESs, were shown by the results but exceptions were observed. Accordingly, while increasing the electrode spacing reduced the current densities but generally improved COD and nitrogen removal, increasing the external resistance could result in decreased COD removal but also increased nitrogen removal and decreased current densities. However, maximum electricity generation and COD removal efficiency difference of the SBES (versus the control) could be reached with an external resistance of $100{\Omega}$, not with the lowest one of $10{\Omega}$. The effects of uncontrollable parameters such as ambient temperature, salinity and pH of the pond (tank) water were rather unpredictable. Temperatures higher than $35^{\circ}C$ seemed to have more accelaration effect on natural degradation than on bioelectrochemical processes. Changing salinity seriously changed the electricity generation but did not clearly affect the bioremediation performance of the SBES, although at 2.5% salinity the SBES displayed a significantly more efficient removal of nitrogen in the water, compared to the control. Variation of pH to practically extreme levels (5.5 and 8.8) led to increased electricity generations but poorer performances of the SBES (vs. the control) in removing COD and nitrogen. Altogether, the results suggest some distinct responses of the SBES under brackish conditions and imply that COD removal and nitrogen removal in the system are not completely linked to bioelectrochemical processes but electrochemically enriched bacteria can still perform non-bioelectrochemical COD and nitrogen removals more efficiently than natural ones. The results confirm the application potential of the SBES in brackish aquaculture bioremediation and help propose efficient practices to warrant the success of such application in real-life scenarios.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.