• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.233-238
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• 2007

An approach to identify Chinese event types is proposed in this paper which combines a good feature selection policy and a Maximum Entropy (ME) model. The approach not only effectively alleviates the problem that classifier performs poorly on the small and difficult types, but improve overall performance. Experiments on the ACE2005 corpus show that performance is satisfying with the 83.5% macro - average F measure. The main characters and ideas of the approach are: (1) Optimal feature set is built for each type according to local feature selection, which fully ensures the performance of each type. (2) Positive and negative features are explicitly discriminated and combined by using one - sided metrics, which makes use of both features' advantages. (3) Wrapper methods are used to search new features and evaluate the various feature subsets to obtain the optimal feature subset.

• Corrosion Science and Technology
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• v.21 no.1
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• pp.9-20
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• 2022

The aim of this paper is to study corrosion inhibition of Aluminum with Capparis decidua extract. The study was performed in a 1.0 M solution of hydrochloric acid (HCl) and was monitored both by measuring mass loss and by using electrochemical and polarization methods. A scanning electron microscopy (SEM) technique was also applied for surface morphology analysis. The results revealed high inhibition efficiency of Capparis decidua extract. Our data also determined that efficiency is governed by temperature and concentration of extract. Optimum (88.2%) inhibitor efficiency was found with maximum extract concentration at 45 o C. The results also showed a slight diminution of aluminum dissolution when the temperature is low. Based on the Langmuir adsorption model, Capparis decidua adsorption on the aluminum surface shows a high regression coefficient value. From the results, the activation enthalpy (∆H#) and activation entropy (∆S#) were estimated and discussed. In conclusion, the study clearly shows that Capparis decidua extract acted against aluminum corrosion in acidic media by forming a protective film on top of the aluminum surface.

• Journal of Forest and Environmental Science
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• v.31 no.3
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• pp.207-213
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• 2015

It is estimated that there is a total of approximately 100,000 species in Korea. However, the number is currently about 30,000 and only 16,027 species are listed in the 'Species Korea' (as of December, 2014). Of the listed species, 51 species are designated as the Endangered Species Class I while 195 species are in the Class II, totaling 246 endangered species including 20 mammals. Under the circumstances that development (e.g., roads) is increasingly threatening the persistence of endangered mammals, it is significant to identify and preserve suitable habitats for them. In this context, evaluating the values of the suitable habitat environment would serve as essential information for development decision making. This study estimated the values of endangered mammals' forest habitats through spatialization of habitat services. In doing so, a species distribution model, Maximum Entropy Model (MaxEnt) was utilized for a group of endangered mammals including, mountain goat, wildcat, marten cat, and flying squirrel. To calculate the values per unit area, a benefit transfer method was used based on the point-estimate technique with the best available values estimated previously. The range of discount rate of 3.0 to 5.5 percent was applied taking the notion of social discount rate into account. As a result, the province with the highest values for endangered mammal habitats appeared to be Gangwon, followed by Gyeongbuk and Gyeongnam. The monetary values of the endangered mammal habitats were estimated to be 330 billion to 421 billion won per year.

• Membrane and Water Treatment
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• v.11 no.1
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• pp.69-77
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• 2020

Former studies revealed that sepiolite thermally treated at high temperature have high adsorption capacity for phosphate. However, its micron size (75 ㎛) limits its application to water treatment. In this study, we synthesized sepiolite impregnated polysulfone (PSf) beads to separate it easily from an aqueous solution. PSf beads with different sepiolite ratios were synthesized and their efficiencies were compared. The PSf beads with 30% impregnated sepiolite (30SPL-PSf bead) possessed the optimum sepiolite ratio for phosphate removal. Kinetic, equilibrium, and thermodynamic adsorption experiments were performed using the 30SPL-PSf bead. Equilibrium adsorption was achieved in 24 h, and the pseudo-first-order model was suitable for describing the phosphate adsorption at different reaction times. The Langmuir model was appropriate for describing the phosphate adsorption onto the 30SPL-PSf bead, and the maximum adsorption capacity of the 30SPL-PSf bead obtained from the model was 24.48 mg-PO₄/g. Enthalpy and entropy increased during the phosphate adsorption onto the 30SPL-PSf bead, and Gibb's free energy at 35 ℃ was negative. An increase in the solution pH from 3 to 11 induced a decrease in the phosphate adsorption amount from 27.30 mg-PO₄/g to 21.54 mg-PO₄/g. The competitive anion influenced the phosphate adsorption onto the 30SPL-PSf bead was in the order of NO₃^- > SO₄^2- > HCO_3^-. The phosphate breakthrough from the column packed with the 30SPL-PSf bead began after ~2000 min, reaching the influent concentration after ~8000 min. The adsorption amounts per unit mass of 30SPL-PSf and removal efficiency were 0.775 mg-PO₄/g and 61.6%, respectively. This study demonstrates the adequate performance of 30SPL-PSf beads as a filter for phosphate removal from aqueous solutions.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.427-437
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• 2019

Background: Climate change is believed to be continuously affecting ticks by influencing their habitat suitability. However, we attempted to model the climate change-induced impacts on future genus Rhipicephalus distribution considering the major environmental factors that would influence the tick. Therefore, 50 tick occuance points were taken to model the potential distribution using maximum entropy (MaxEnt) software and 19 climatic variables, taking into account the ability for future climatic change under representative concentration pathways (RCPs) 4.5 and 8.5, were used. Results: MaxEnt model performance was tested and found with the AUC value of 0.99 which indicates excellent goodness-of-fit and predictive accuracy. Current models predict increased temperatures, both in the mid and end terms together with possible changes of other climatic factors like precipitation which may lead to higher tick-borne disease risks associated with expansion of the range of the targeted tick distribution. Distribution maps were constructed for the current, 2050, and 2070 for the two greenhouse gas scenarios and the most dramatic scenario; RCP 8.5 produced the highest increase probable distribution range. Conclusions: The future potential distribution of the genus Rhipicephalus show potential expansion to the new areas due to the future climatic suitability increase. These results indicate that the genus population of the targeted tick could emerge in areas in which they are currently lacking; increased incidence of tick-borne diseases poses further risk which can affect cattle production and productivity, thereby affecting the livelihood of smallholding farmers. Therefore, it is recommended to implement climate change adaptation practices to minimize the impacts.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.145-161
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• 2014

Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.6
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• pp.161-172
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• 2010

As the interest on biodiversity has increased around the world, researches about evaluating potential for habitat are also increasing to find and comprehend the valuable habitats. This study focus on comprehending the significance of stream in evaluating habitat's potential. The purpose of this study is to evaluate habitat potential with applying stream as a main variable, and to comprehend the relationship between the variables and habitat potential. Basin is a unit that has hydrological properties and dynamic interaction with ecosystem. Especially, biodiversity and suitability of habitat in basin area has direct correlation with stream. Existing studies also are proposing for habitat potential evaluation in basin unit, they applied forest, slope and road as main variables. Despite stream is considered the most important factor in basin area, researchers haven't applied stream as a main variable. Therefore, in this study, three variables that can demonstrate hydrological properties are selected, which are, riparian distance, stream order and land use disturbance, and evaluate habitat potential. Habitat potential is analyzed by using Maxent (Maximum entropy model), and vertebrate's presence data is used as dependent variables and stream order map and land cover map is used as base data of independent variables. As a result of analysis, habitat potential is higher at riparian and upstream area, and lower at frequently disturbed area. Result indicates that adjacent to stream, upstream, and less disturbed area is the habitat that vertebrate prefer. In particular, mammals prefer adjacent area of stream and forest and reptiles prefer upriver area. Birds prefer adjacent area of stream and midstream and amphibians prefer adjacent area of stream and upriver. The result of this research could help to establish habitat conservation strategy around basin unit in the future.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.1
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• pp.54-65
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• 2022

Species distribution models are a useful tool for predicting future distribution and establishing a preemptive response of invasive species. However, few studies considered the possibility of habitat for the aquatic organism and the number of target sites was relatively small compared to the area. Environmental DNA (eDNA) is the emerging tool as the methodology obtaining the bulk of species presence data with high detectability. Thus, this study applied eDNA survey results of Micropterus salmoides and Lepomis macrochirus to species distribution modeling by seasons in the Anyang stream network. Maximum Entropy (MaxEnt) model evaluated that both species extended potential distribution area in October compared to July from 89.1% (12,110,675 m²) to 99.3% (13,625,525 m²) for M. salmoides and 76.6% (10,407,350 m²) to 100% (13,724,225 m²) for L. macrochirus. The prediction value by streams was varied according to species and seasons. Also, models elucidate the significant environmental variables which affect the distribution by seasons and species. Our results identified the potential of eDNA methodology as a way to retrieve species data effectively and use data for building a model.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.324-333
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• 2001

In this paper we present a novel color image segmentation algorithm based on a Gaussian Mixture Model(GMM). It is introduced a Deterministic Annealing Expectation Maximization(DAEM) algorithm which is developed using the principle of maximum entropy to overcome the local maxima problem associated with the standard EM algorithm. In our approach, the GMM is used to represent the multi-colored objects statistically and its parameters are estimated by DAEM algorithm. We also develop the automatic determination method of the number of components in Gaussian mixtures models. The segmentation of image is based on the maximum posterior probability distribution which is calculated by using the GMM. The experimental results show that the proposed DAEM can estimate the parameters more accurately than the standard EM and the determination method of the number of mixture models is very efficient. When tested on two natural images, the proposed algorithm performs much better than the traditional algorithm in segmenting the image fields.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.541-547
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• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.