• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.1-10
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• 2023

Strong Critics of' Moral Hazard, due to plummeting severely their stock price down and damage falling on plain investor, has been skyrocketed against massively and simultaneously exercising stock option right of C-Level members in Stock market listed startups right after IPO regardless of proper and legal process followed. Korean Financial Supervisory Board initiate new act of extending to apply'Lock-up Rule'even to stock option of core interest group after IPO. However, it will cause startups and venture more difficulties to recruit top level of talented staffs. This paper aims to propose RSU(Restricted Stock Unit) as alternative to breakthrough the current deadlock issue with respect to stock option controversy many startups facing. This paper to meet goal, first, including Korean introducing status of RSU, it clarify the concept of RSU by comparing exploration with Restricted Stock and define characteristic of RSU by comparing Stock Option. Second, it bring more effective ways of startups introducing RSU in Korea overcoming its limitations and challenges. Third, it carry out FGI to legal expert deeply involved of introducing RSU in Korea at policy domain. FGI focus on defining core challenging factors and their level of huddles of introducing RSU in Korea with proposing breakthrough policies to landing RSU softly in Korea. Fourth, it suggest valid policies of introducing and stabilizing RSU in Korea completely. This paper expect some contributions Korean startups and venture on finding market friendly right breakthrough out of stock option dilemma currently in.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.205-216
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• 2024

Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.111-118
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• 2024

The concept of social stratification and hierarchy among human dates back to the origin of human race. Presently, the growing reputation of social networks has given us with an opportunity to analyze these well-studied phenomena over different networks at different scales. Generally, a social network could be defined as a collection of actors and their interactions. In this work, we concern ourselves with a particular type of social networks, known as trust networks. In this type of networks, there is an explicit show of trust (positive interaction) or distrust (negative interaction) among the actors. In other words, an actor can designate others as friends or foes. Trust networks are typically modeled as signed networks. A signed network is a directed graph in which the edges carry an edge weight of +1 (indicating trust) or -1 (indicating distrust). Examples of signed networks include the Slashdot Zoo network, the Epinions network and the Wikipedia adminship election network. In a social network, actors tend to connect with each other on the basis of their perceived social hierarchy. The emergence of such a hierarchy within a social community shows the manner in which authority manifests in the community. In the case of signed networks, the concept of social hierarchy can be interpreted as the emergence of a tree-like structure comprising of actors in a top-down fashion in the order of their ranks, describing a specific parent-child relationship, viz. child trusts parent. However, owing to the presence of positive as well as negative interactions in signed networks, deriving such "trust hierarchies" is a non-trivial challenge. We argue that traditional notions (of unsigned networks) are insufficient to derive hierarchies that are latent within signed networks In order to build hierarchies in signed networks, we look at two interpretations of trust namely presence of trust (or "good") and lack of distrust (or "not bad"). In order to develop a hierarchy signifying both trust and distrust effectively, the above interpretations are combined together for calculating the overall trustworthiness (termed as deserve) of actors. The actors are then arranged in a hierarchical fashion based on these aggregate deserve values, according to the following hypothesis: actor v is assigned as a child of actor u if: (i) v trusts u, and (ii) u has a higher deserve value than v. We describe this hypothesis with additional qualifiers in this thesis.

• Journal of Radiation Protection and Research
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• v.41 no.1
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• pp.49-55
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• 2016

Background: For the purpose of baseline data collection and enhancement of environmental monitoring the distribution studies of $^{137}Cs$ and $^{90}Sr$ in the soil of Uljin province was performed and the relation between surface soil activities and soil properties (pH, TOC and median of the surface soil) was analyzed. Materials and Methods: For 14 spots within 10 km from the NPP surface soil samples were collected and soils for depth profile were sampled for 3 spots in April 2011. Using ${\gamma}$-ray spectrometry with HPGe detector, the concentrations of $^{137}Cs$ were determined and the concentrations of $^{90}Sr$ were measured by counting ${\beta}$-activity of $^{90}Y$ (in equilibrium with $^{90}Sr$) in a gas flow proportional counter. Results and Discussion: The concentration ranges of $^{137}Cs$ and $^{90}Sr$ were $<0.479-39.6Bq{\cdot}(kg-dry)^{-1}$ (avg. $7.51Bq{\cdot}(kg-dry)^{-1}$) and $0.209-1.85Bq{\cdot}(kg-dry)^{-1}$ (avg. $0.74Bq{\cdot}(kg-dry)^{-1}$) which were similar to the reported values from other regions in Korea. The activity ratio of $^{137}Cs$ to $^{90}Sr$ in surface soils was around 9.67, which is much bigger than the initial value of 1.75 for worldwide fallouts because of faster downward movement of $^{90}Sr$ after fallout than that of $^{137}Cs$. For depth profile studies soils were collected down to 40 cm depth for the locations of Deokgu, Hujeong and Maehwa. The $^{137}Cs$ concentration distribution of the first two showed maximum values at top soils and decreased rapidly in exponential manner, while $^{90}Sr$ showed two local maximum values for soils near top and about 30 cm depth. Through linear fittings between the $^{137}Cs$ and $^{90}Sr$ concentrations of surface soil and pH, TOC and median of the surface soil, the only probable relationship obtained was between $^{137}Cs$ and TOC (determination coefficient $R^2=0.6$). Conclusion: The concentration ranges of $^{137}Cs$ and $^{90}Sr$ in Uljin were similar to the reported values from other regions in Korea. The only probable relationship obtained between activities and soil properties was between $^{137}Cs$ and TOC.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.5
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• pp.842-847
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• 2012

This study was conducted to estimate the greenhouse gas emissions on local government levels from 1990 to 2010 using 2006 IPCC guideline methodology. To calculate greenhouse gas emissions based on the 16 local governments, emission factor and scaling factor were used with default value and activity data came from the food, agricultural, forestry and fisheries statistical yearbook of MIFAFF (Ministry for Food, Agriculture, Forestry, and Fisheries). The total emissions in crop sector gradually decreased from 1990 to 2010 due to a decline in agricultural land and nitrogen fertilizer usage. The annual average emission of greenhouse gas was the highest in Jeonnam (JN) with 1,698 Gg $CO_2$-eq and following Chungnam (CN), Gyungbuk (GB), Jeonbuk (JB) and Gyunggi (GG). The sum of top-six locals emission had occupied 83.4% of the total emission in cropland sector. The annual average emissions in 1990 by applying 2006 IPCC guideline were approximately 43% less than the national greenhouse gas inventory by 1996 IPCC guideline. Jeonnam (JN) province occupied also the highest results of greenhouse gas emission estimated by gas types (methane, nitrous oxide and carbon dioxide) and emission sources such as rice cultivation, agricultural soil, field burning of crop residue and urea fertilizer.

• Korean Journal of Soil Science and Fertilizer
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• v.13 no.2
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• pp.57-63
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• 1980

The effect of particle size of silicate fertilizer, crushed slag from the steel industry, on the behavior of silicate in soil was investigated through laboratory experiments. The silicate fertilizer was sieved to obtain three fractions of particles, coarser than 10 mesh 20-35 mesh, and finer than 100 mesh. Silicate concentration of the extract obtained by shaking 20 mg of particles, coarser than 10 mesh, 20-35 mesh, and finer than 100 mesh, in 50 ml of distilled water for 4 hours was 0.3, 1.0, and 3.2 ppm respectively. As shaking the mixture of the silicate fertilizer and soil proceeded, silicate concentration of the extract increased, and this increase after 4 hour shaking was attributed mainly to dissolution of soil silicate. When the mixture of soil and the silicate fertilizer was incubated under submerged condition, silicate concentration of the solution decreased for the first 2-4 weeks, thereafter increased with incubation time. During this incubation period, silicate concentration of the solution changed inversely with pH of the solution. After 6-10 weeks, however, both silicate concentration and pH of the solution increased with incubation time. Silicate concentration of the effluent from the 14.5 cm soil column of which top 4.5 cm was packed with the mixture of 30 g of soil and 30 mg of the silicate fertilizer reached maximum at 0.94 pore volumes for the particles of 20-35 mesh and 1.03 pore volumes for the particles finer than 100 mesh, whereas the effluent concentration reached maximum at 0.88 pore volumes for the soil column without the silicate fertilizer treatment. Soil analysis made after water percolation revealed that 1.5 pore volumes of water could leach down large amount of the water soluble silicate but not the sodium acetate extractable silicate, from top 3-6 cm soil layer.

• Journal of the Mineralogical Society of Korea
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• v.32 no.3
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• pp.173-184
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• 2019

Variations in grain size distribution and clay mineral assemblage are closely related to the sedimentary facies that reflect depositional conditions during the glacial and interglacial periods. Gravity cores BS17-GC15 and BS17-GC04 were collected from the continental shelf and rise in the eastern Bellingshausen Sea during a cruise of the ANA07D Cruise Expedition by the Korea Polar Research Institute in 2017. Core sediments in BS17-GC15 consisted of subglacial diamicton, gravelly muddy sand, and bioturbated diatom-bearing mud from the bottom to the top sediments. Core sediments in BS17-GC04 comprised silty mud with turbidites, brownish structureless mud, laminated mud, and brownish silty bioturbated diatom-bearing mud from the bottom to the top sediments. The clay mineral assemblages in the two core sediments mainly consisted of smectite, chlorite, illite, and kaolinite. The clay mineral contents in core GC15 showed a variation in illite from 28.4 % to 44.5 % in down-core changes. Smectite contents varied from 31.1 % in the glacial period to 20 % in the deglacial period and 25.1 % in the interglacial period. Chlorite and kaolinite contents decreased from 40.5 % in the glacial period to 30.3 % in the interglacial period. The high contents of illite and chlorite indicated a terrigenous detritus supply from the bedrocks of the Antarctic Peninsula. Core GC04 from the continental rise showed a decrease in the average smectite content from 47.2 % in the glacial period to 20.6 % in the interglacial period, while the illite contents increased from the 21.3 % to 43.2 % from the glacial to the interglacial period. The high smectite contents in core GC04 during the glacial period may be supplied from Peter I Island, which has a known smectite-rich sediment contributed by Antarctic Circumpolar Currents. Conversely, the decrease in smectite and increase in chlorite and illite contents during the interglacial period was likely caused by a higher supply of chlorite- and illite-enriched sediment from the eastern Bellingshausen Sea shelf by the southwestward flowing contour current.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Environmental Impact Assessment
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• v.24 no.6
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• pp.607-618
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• 2015

Five years have passed since the first set of environmental samples was taken in 2011 to represent various ecosystems which would help future generations lead back to the past environment. Those samples have been preserved cryogenically in the National Environmental Specimen Bank(NESB) at the National Institute of Environmental Research. Even though there is a strict regulation (SOP, standard operating procedure) that rules over the whole sampling procedure to ensure each sample to represent the sampling area, it has not been put to the test for the validation. The question needs to be answered to clear any doubts on the representativeness and the quality of the samples. In order to address the question and ensure the sampling practice set in the SOP, many steps to the measurement of the sample, that is, from sampling in the field and the chemical analysis in the lab are broken down to evaluate the uncertainty at each level. Of the 8 species currently taken for the cryogenic preservation in the NESB, pine tree samples from two different sites were selected for this study. Duplicate samples were taken from each site according to the sampling protocol followed by the duplicate analyses which were carried out for each discrete sample. The uncertainties were evaluated by Robust ANOVA; two levels of uncertainty, one is the uncertainty from the sampling practice, and the other from the analytical process, were then compiled to give the measurement uncertainty on a measured concentration of the measurand. As a result, it was confirmed that it is the sampling practice not the analytical process that accounts for the most of the measurement uncertainty. Based on the top-down approach for the measurement uncertainty, the efficient way to ensure the representativeness of the sample was to increase the quantity of each discrete sample for the making of a composite sample, than to increase the number of the discrete samples across the site. Furthermore, the cost-effective approach to enhance the confidence level on the measurement can be expected from the efforts to lower the sampling uncertainty, not the analytical uncertainty. To test the representativeness of a composite sample of a sampling area, the variance within the site should be less than the difference from duplicate sampling. For that, a criterion, ${i.e.s^2}_{geochem}$(across the site variance) <${s^2}_{samp}$(variance at the sampling location) was proposed. In light of the criterion, the two representative samples for the two study areas passed the requirement. In contrast, whenever the variance of among the sampling locations (i.e. across the site) is larger than the sampling variance, more sampling increments need to be added within the sampling area until the requirement for the representativeness is achieved.

• Korean Journal of Environmental Biology
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• v.27 no.2
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• pp.183-190
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• 2009

Characterization of the analysis of forest vegetation, soil environmental conditions and water quality were performed from March 2003 to March 2007. The two basins were characterized by cultivated area (Kaesim reservoir) and mountain area (Jangchan reservoir), and divided into eleven small basins, where dynamics of pollutants, forest vegetation and soil environmental conditions were surveyed. The vegetation can be divided into 10 types by $Z\ddot{u}rich$-Montpellier school's method. Pearson coefficients between vegetation type and water quality were correlated with dissolved oxygen (DO) in the Quercus variabilis community at the 5% level and total phosphorus (TP) in the Larix leptolepis plantation at the 1% level. Especially total phosphorous and total nitrogen increased in small basins where the proportion of cultivated and residential area increased. The analysis of influences of pollutant discharge on water quality showed that pollutant charge was very low in forest land area ($Y_{T-P}$=-0.0017X+0.2215, r=0.16, $Y_{COD}$=- 0.0395X+8.5051 r=0.47). The soil types of western area were comparatively simple, but those of eastern area were complicated with regosols, red-yellow soils, lithosoles, etc. The pH, total solid (TS) and volatile substance (VS) of the forest and agricultural land soils collected in each site were 5.4~6.9, 75.8~80.2%, and 3.80%~5.80%, respectively. According to the analytical result of soil environmental conditions, heavy metal contents fell short to the mean value of natural conditions. Runoff amount (Y) and depth of topsoil (X) were negatively correlated, $Y_{ron}=-1.0088X_{top}+35.378$ (r=0.68). The correlation was much lower in up-stream but much higher in down-stream, because permeation into soil particle was larger on down-stream due to its more or less gentle slope. Pearson coefficients between soil pH and water pH were statistically significant at 1% level.