• Journal of the Korean Data and Information Science Society
• /
• v.26 no.1
• /
• pp.65-75
• /
• 2015

This paper analyzes the determinants of wage for the college and university graduates utilizing both individual-level and industry-level variables. We note that wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and industry-level (level-2) variables. Then, the assumption that individual wage is independent in the classical regression is violated. Therefore, this paper utilizes the hierarchical linear model (HLM). The major results are the followings. First, the multiple correspondence analysis including level-1 and 2 variables reveals that both level 1 and level 2 variables affects individual wages judging from the fact that the values of level 1 and level 2 variables differ across the different level of individual wage groups. Second, the decision tree analysis including level-1 and 2 variables shows that the most influential variable in wage determination is industry-level wage and the next is industry-level working hour, ages and sex in the decling order in. This suggests that the utilization of the HLM is appropriate since the characteristics of industry is important in determining the individual wage. Third, it is shown that the HLM model is the best compared to the other models which do not take level-1 and level-2 variables simultaneously into account.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.3
• /
• pp.259-268
• /
• 2012

This paper aims to estimate the carbon dioxide stocks in forests using airborne LiDAR data with a density of approximate 4.4 points per meter square. To achieve this goal, a processing chain consisting of bare earth Digital Terrain Model(DTM) extraction and individual tree top detection has been developed. As results of this experiment, the reliable DTM with type-II errors of 3.32% and tree positions with overall accuracy of 66.26% were extracted in the study area. The total estimated carbon dioxide stocks in the study area using extracted 3-D forests structures well suited with the traditional method by field measurements upto 7.2% error level. This results showed that LiDAR technology is highly valuable for replacing the existing forest resources inventory.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.13 no.2
• /
• pp.1-11
• /
• 2014

In this paper, travel speed patterns were deducted based on historical DSRC travel speed data using Decision Tree technique to improve availability of the massive amount of historical data. These patterns were designed to reflect spatio-temporal vicissitudes in reality by generating pattern units classified by months, time of day, and highway sections. The study area was from Seoul TG to Ansung IC sections on Gyung-bu highway where high peak time of day frequently occurs in South Korea. Decision Tree technique was applied to categorize travel speed according to day of week. As a result, five different pattern groups were generated: (Mon)(Tue Wed Thu)(Fri)(Sat)(Sun). Statistical verification was conducted to prove the validity of patterns on nine different highway sections, and the accuracy of fitting was found to be 93%. To reduce travel pattern errors against individual travel speed data, inclusion of four additional variables were also tested. Among those variables, 'traffic condition on previous month' variable improved the pattern grouping accuracy by reducing 50% of speed variance in the decision tree model developed.

• The Korean Journal of Ecology
• /
• v.19 no.6
• /
• pp.499-506
• /
• 1996

Forest stand development in Kwangnung Experimental Forest, Korea, was simulated with a forest succession gap model of the JABOWA/FORET type, in order to predict climax species and characterime the trend of community structure along the succession. The model runs for a period or 1, 000 yr and is based on the averaged successional characteristics of 50 forest plote with an individual size or 1/12 ha gap consisted of the 15 major tree species. The total bimass and leafarea index have arrived at a steady state since about 200 yr and these values are smaller than that or field survey. Carpinus cordata, C. laxiflora, Quercus mongolica and Q. serrata were epected to be climax species that represent about 86% or total biomass in later stage and these results coincided with the previous succession studies from field survey in the area.

• Journal of Information Technology Applications and Management
• /
• v.11 no.1
• /
• pp.161-174
• /
• 2004

This study is intended to suggest1 the optimized data mining model for the efficient customer credit evaluation in the capital finance industry. To accomplish the research objective, various data mining models for the customer credit evaluation are compared and analyzed. Furthermore, existing models such as Multi-Layered Perceptrons, Multivariate Discrimination Analysis, Radial Basis Function, Decision Tree, and Logistic Regression are employed for analyzing the customer information in the capital finance market and the detailed data of capital financing transactions. Finally, the data from the integrated model utilizing a genetic algorithm is compared with those of each individual model mentioned above. The results reveals that the integrated model is superior to other existing models.

• The Plant Pathology Journal
• /
• v.15 no.4
• /
• pp.210-216
• /
• 1999

TREGRO, a computer simulation model of individual tree growth, was applied to estimate ozone ($\textrm{O}_3$) effects on aspen(Populus tremuloides) growth under ambient and 1.7 times ambient $\textrm{O}_3$ of Seoul in 1996. The three highest $\textrm{O}_3$ (Kuui-dong, Ssangmun-dong, Sungsoo-dong) and the two lowest $\textrm{O}_3$ sites (Mapo-dong, Namgajwa-dong) were evaluated. The current ambient $\textrm{O}_3$ did not affect aspen growth compared to simulation without $\textrm{O}_3$. The only effect was 6.6 percent of total assimilated carbonloss at Ssangmun-dong where the level of $\textrm{O}_3$ was greatest among the 21 sites examined. Decrease as much as 50 percent of total carbon gain was calculated at 1.7 times ambient $\textrm{O}_3$ of the three highest sites. The carbon loss by $\textrm{O}_3$ came from biomass of tissues and total nonstructural cabron (TNC) such as starch and sugar. The most sensitive fraction was TNC and the next was root biomass. Foliage mass was not affected by $\textrm{O}_3$. Structural biomass loss was at best 1 to 3 percent at 1.7 times ambient $\textrm{O}_3$ at the two lowest sites. The daily carbon simulation was affected by $\textrm{O}_3$ mainly during Growth Period 4 (Jul. 21-Oct. 26). Correlations between site, dose, and the simulated responses of aspen (tissue biomass, TNC, respiration, and senescence) ranged from -0.703 to -0.973 depending on the plant responses. The ozone effects on poplar in Seoul are not severe currently, but are probably measurable at Ssangmun-dong. However, severe $\textrm{O}_3$ effects on biomass would occur if $\textrm{O}_3$ levels increase to 1.7 times ambient $\textrm{O}_3$ in Seoul. In addition, v could weaken the trees thus increasing susceptibility to pathogens or insects.

• Nuclear Engineering and Technology
• /
• v.50 no.5
• /
• pp.745-750
• /
• 2018

New exercise technology such as the virtual reality (VR)-based exercise system is required to meet soaring demand for target participants in exercises and to alleviate the difficulties in personnel mobilization through an alternative approach to the exercise system. In a previous study, event tree methodologies were introduced in setting up an exercise scenario of a VR-based radiological exercise system. In the scenario, the locations at which major events occur are rephrased as nodes, routes as paths, and public response actions as protective actions or contents of an exercise at individual locations. In the study, a model for estimating effective doses to the participants is proposed to evaluate the exercise system, using the effective dose rates at particular times and locations derived from a computer program. The effective dose received by a student when she/he follows a successful route is about a half of the dose received when she/he does not follow the exercise guide directions. In addition, elapsed time to finish an exercise when following a successful route is less than one-third of the time spent to finish an exercise when following the guide's directions.

• International Journal of Computer Science & Network Security
• /
• v.23 no.11
• /
• pp.190-194
• /
• 2023

By looking the importance of communication, data delivery and access in various sectors including governmental, business and individual for any kind of data, it becomes mandatory to identify faults and flaws during cyber communication. To protect personal, governmental and business data from being misused from numerous advanced attacks, there is the need of cyber security. The information security provides massive protection to both the host machine as well as network. The learning methods are used for analyzing as well as preventing various attacks. Machine learning is one of the branch of Artificial Intelligence that plays a potential learning techniques to detect the cyber-attacks. In the proposed methodology, the Decision Tree (DT) which is also a kind of supervised learning model, is combined with the different cross-validation method to determine the accuracy and the execution time to identify the cyber-attacks from a very recent dataset of different network attack activities of network traffic in the UNSW-NB15 dataset. It is a hybrid method in which different types of attributes including Gini Index and Entropy of DT model has been implemented separately to identify the most accurate procedure to detect intrusion with respect to the execution time. The different DT methodologies including DT using Gini Index, DT using train-split method and DT using information entropy along with their respective subdivision such as using K-Fold validation, using Stratified K-Fold validation are implemented.

• Journal of Korean Society of Forest Science
• /
• v.100 no.1
• /
• pp.62-69
• /
• 2011

Six commonly used non-linear growth functions were fitted to individual tree height-dbh data of eight major tree species measured by the $5^{th}$ National Forest Inventory in Chungcheong province. A total of 2,681 trees were collected from permanent sample plots across Chungcheong province. The available data for each species were randomly splitted into two sets: the majority (90%) was used to estimate model parameters and the remaining data (10%) were reserved to validate the models. The performance of the models was compared and evaluated by $R^2$, RMSE, mean difference (MD), absolute mean difference (AMD) and mean difference(MD) for diameter classes. The combined data (100%) were used for final model fitting. The results showed that these six sigmoidal models were able to capture the height-diameter relationships and fit the data equally well, but produced different asymptote estimates. Sigmoidal growth models such as Chapman-Richards, Weibull functions provided the most satisfactory height predictions. The effect of model performance on stem volume estimation was also investigated. Tree volumes of different species were computed by the Forest Resources Evaluation and Prediction Program using observed range of diameter and the predicted tree total height from the six models. For trees with diameter less than 30 cm, the six height-dbh models produced very similar results for all species, while more differentiation among the models was observed for large-sized trees.

• Journal of Korean Society of Forest Science
• /
• v.85 no.3
• /
• pp.539-551
• /
• 1996

In this study, a number of distance-dependent competition indices on tree-level which incorporate the tree sizes and distances to competitors, and traditional stand-level density measures were estimated from the data compiled with position-dependent survey in a Pinus densiflora stand. The performance of the estimated competition indices was examined by comparing the relationship with the diameter growth, and a dbh growth function, in which the competition index is considered as a one of influence factors, are developed. In the searching method of competing trees, the competition index estimated with $30^{\circ}$ competition interrupting angle showed the highest correlation with the annual dbh growth, while the expanding the competing zone distance had no significant effect on the performance of competition index in estimating annual dbh growth. The most of the examined stand-level competition indices, based on distance-dependent single-tree competition indices, were evaluated to describe similarly the stand competition status. As a result of partial correlation analysis in which the effect of age and site index are eliminated, Alemdag's mean competition index and relative spacing index were determined to have the highest correlation with dbh. The relative spacing index, which can be easily measured in field without measuring the position of individual trees, was considered to be a better suited one for estimating mean dbh of a stand. Among distance-dependent competition indices on tree-level, Hegyi's competition index showed the best performance in their correlation with annual dbh growth, if eliminated the effect of site index and dbh. This enabled to derive the following annual dbh growth function of individual trees which incorporate age, dominant height, dbh and Hegyi's competition index as influence factors : $$dbh^{\prime}=3.975362676{\cdot}age^{-1.099274613}{\cdot}ho^{0.199893990}{\cdot}dbh^{0.269430865}{\cdot}HgCI^{-0.353643587}$$ This function is coincided to the growth principle in which site index has a positive effect on the annual dbh growth, while high age or competition causes to reduce the annual dbh growth, and can be used as a function in single tree growth model.