• Spatial Information Research
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• v.8 no.2
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• pp.233-241
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• 2000

The objective of this study were to develop landscape scale ecosystem assessment model, and apply the model for the assessment of the state and change of ecosystem of the study area, Yongin, Korea. Since natural ecosystem of the site has been deteriorated significantly during recent extensive residential development, it is essential to correctly assess ecosystem of the study site. Traditional ecosystem assessment mainly utilizing intensive field survey requires high cost, but the outcome rarely represents spatial pattern of the regional ecosystems. Ecosystem assesment of landscape scale based on landscape ecology can resolve most of the shortfalls of the traditional approach. The research method can be summarized as follows. First, extensive literature review on such topics as spatial pattern of ecosystem, ecosystem assessment of landscape scale, ecological analysis was carried out. Second, a model for the ecosystem assessment of landscape scale emphasizing spatial pattern of ecosystem was developed. This model evaluates three indicators; ecological integrity and biological diversity, watershed integrity, and landscape resilience of 11 watersheds in the study area. Finally, ecological assessment utilizing two sets of indicators, enhancement of and disturbance of ecosystem stability, was carried out. This assessment method is based on Environmental Monitoring and Assessment Program´s Landscape component(EMAP-L) of EPA(1994). The results of this study are as follows. First, the ecosystem assessment of landscape scale of the study area of Yongin, Korea, showed that escosystems of Tanchun01 and Chungmichun01 watersheds had the worst state in the study site in 1991. On the other hand, the ecosystems of Jinwechun01, Kyunganchun02, and Bokhachun01 watersheds had the most stable ecosystem in 1991. Second, ecosystems of Tanchun01, Shingal reservoir, and Kyunganchun01 watersheds were evaluated to be the worst state in the study site in 1996. And, ecosystems of Jinwechun01 and Gosam reservoir watersheds had the most stable ecosystem. Third, ecosystem of Tanchun01 watershed which incudes Suji residential development project site changed the most drastically between 1991 and 1996. The ecosystem of the watershed the most drastically deteriorated due to it´s proximity to Seoul and Bundang new town.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3656-3671
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• 2016

Most of the research in the area of wireless communications exclusively relies on simulations. Further, it is essential that the mobility management strategies and routing protocols should be validated under realistic conditions. Most appropriate mobility models play a pivotal role to determine, whether there is any subtle error or flaw in a proposed model. Simulators are the standard tool to evaluate the performance of mobility models however sometimes they suffer from numerous documented problems. To accomplish the widely acknowledged lack of formalization in this domain, a Coloured Petri nets (CPNs) based random direction mobility model for specification, analysis and validation is presented in this paper for wireless communications. The proposed model does not suffer from any border effect or speed decay issues. It is important to mention that capturing the mobility patterns through CPN is challenging task in this type of the research. Further, an appropriate formalism of CPNs supported to analyze the future system dynamic status. Finally the formal model is evaluated with the state space analysis to show how predefined behavioral properties can be applied. In addition, proposed model is evaluated based on generated simulations to track origins of errors during debugging.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.4
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• pp.397-414
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• 2003

The performance of one-particle stochastic Lagrangian models for passive tracer dispersion are evaluated against measurements in horizontally-homogeneous neutrally-stratified atmospheric surface layer. State-of-the-technology models as well as classical Langevin models, all in class of well mixed models are numerically implemented for inter-model comparison study. Model results (far-downstream asymptotic behavior and vertical profiles of the time averaged concentrations, concentration fluxes, and concentration fluctuations) are compared with the reported measurements. The results are: 1) the far-downstream asymptotic trends of all models except Reynolds model agree well with Garger and Zhukov's measurements. 2) profiles of the average concentrations and vertical concentration fluxes by all models except Reynolds model show good agreement with Raupach and Legg's experimental data. Reynolds model produces horizontal concentration flux profiles most close to measurements, yet all other models fail severely. 3) With temporally correlated emissions, one-particle models seems to simulate fairly the concentration fluctuations induced by plume meandering, when the statistical random noises are removed from the calculated concentration fluctuations. Analytical expression for the statistical random noise of one-particle model is presented. This study finds no indication that recent models of most delicate theoretical background are superior to the simple Langevin model in accuracy and numerical performance at well.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.47-63
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• 2019

The volatility of major crypto currencies was examined and they are diagnosed whether they have a systematic risk or not, by estimating market beta representing systematic risk using GARCH( Generalized Auto Regressive Conditional Heteroskedastieity) model. First, the empirical results showed that their prices are very volatile over time because of the existence of ARCH and GARCH effects. Second, in terms of efficiency, asymmetric GJR model was estimated to be the most appropriate model because the standard error of a market beta was less than that of the OLS model and GARCH model. Third, the estimated market beta of Bitcoin using GJR model was less than 1 at 0.8791, showing that there is no systematic risk. However, unlike OLS model, the market beta of Ethereum and Ripple was estimated at 1.0581 and 1.1222, showing that there is systematic risk. This result shows that bitcoin is less dangerous than Ripple and Ethereum, and ripple is the most dangerous of all three crypto currencies. Finally, the major cryptocurrency found that the negative impact caused greater variability than the positive impact, causing bad news to fluctuate more than good news, and therefore good news and bad news had a different effect on the variability.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.71-78
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• 2023

Employee turnover is one of the most important challenges facing modern organizations. It causes job experiences and skills such as distinguished faculty members in universities, rare-specialized doctors, innovative engineers, and senior administrators. HR analytics has enhanced the area of data analytics to an extent that institutions can figure out their employees' characteristics; where inaccuracy leads to incorrect decision making. This paper aims to develop a novel model that can help decision-makers to classify the problem of Employee Turnover. By using feature selection methods: Information Gain and Chi-Square, the most important four features have been extracted from the dataset. These features are over time, job level, salary, and years in the organization. As one of the important results of this research, these features should be planned carefully to keep organizations their employees as valuable assets. The proposed model based on machine learning algorithms. Classification algorithms were used to implement the model such as Decision Tree, SVM, Random Frost, Neuronal Network, and Naive Bayes. The model was trained and tested by using a dataset that consists of 1470 records and 25 features. To develop the research model, many experiments had been conducted to find the best one. Based on implementation results, the Neural Network algorithm is selected as the best one with an Accuracy of 84 percents and AUC (ROC) 74 percents. By validation mechanism, the model is acceptable and reliable to help origination decision-makers to manage their employees in a good manner.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.68-74
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• 2014

This study analyzes structural stress and fatigue about three types of automotive wheels. As maximum equivalent stresses at 1, 2 and 3 types become lower than the yield stress of material and deformations become minute, theses types are thought be safe on durability. Type 2 model has the most fatigue life among three kinds of types and the rest of models with fatigue lives are shown in the order of type 1 and 3. As the most fatigue frequency of type 2 model happens at the state of average stress and amplitude stress on the stress range narrower than type 1 or 3, type 2 model becomes most stable. In case of type 2 with the state near the average stress of 0 MPa and the amplitude stress of 300MPa, the possibility of maximum damage becomes 30%. This stress state can be shown as the most damage possibility. These study results can be effectively utilized with the design on automotive wheel by anticipating and investigating prevention and durability against its damage.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.8 no.1
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• pp.197-227
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• 1997

The main purpose of this study is ① to settle and to analyze the classification of the Internet Search Engine comparitively, and ② to build the compatible model of Internet Search Engine classification in order to seek information on the Internet resources. specially in the branch of the Computers and Internet areas. For this study, four Internet Search Engine (Excite, 1-Detect, Simmany, Yahoo Korea!), Inspec Classification and two distionaries were used. The major findings and result of analysis are summarized as follows : 1. The basis of the classification is the scope of topics, the system logic, the clearness, the efficiency. 2. The scope of topics is analyzed comparitively by the number of items from each Search Engine. In the result, Excite is the most superior of the four 3. The system logic is analyzed comparitively by the casuality balance and consistency of the items from each Search Engine. In the result, Excite is the most superior of the four 4. The clearness is analyzed comparitively by the clearness and accuracy of items, the recognition of the searchers. In the result, Excite is the most superior of the four. 5 The efficiency is analyzed comparitively by the exactness of indexing and decreasing the effort of the searchers. In the result, Yahoo Korea！ is the most superior of the four. 6 The compatible model of Internet Search Engine classification is estavlished to uplift the scope of topics, the system logic, the clearness, and the efficiency. The model divides the area mainly based upon the topics and resources using‘bookmark’and‘shadow’concept.

• Journal of Veterinary Clinics
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• v.40 no.3
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• pp.197-202
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• 2023

Canine lymphoma (cL) is the most common hematopoietic cancer in dogs. Various determinants have been evaluated to find the predisposing factors in both human and canine lymphoma. Due to common risk factors and similar pathways, cL is considered a potential model for non-Hodgkin lymphoma (NHL) in humans. In this case-series study, major hospitals in Tehran consented to take part in this study and between the years of 2020-2022, provided us with 52 cL cases which were approved by the attended pathologist. We designed a questionnaire and collected information about the dogs and their owners. Most of the owners were women, young (younger than 50 years old), had at least diplomas and interestingly were housewives or househusbands. Male dogs with middle to old age (more than 6 years) were mostly referred. The most common characteristics were neutered, normal BCS, purebred, urban but not industrial residence, previous tobacco smoke exposure but no history of previous fungicide or pesticide exposure. Also, most of them did not have any previous autoimmune or immunosuppressive diseases. Presented characteristics should be considered risk determinants but to approve their validity, they should be further evaluated in epidemiological studies.

• Journal of the Korean Society of Clothing and Textiles
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• v.34 no.10
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• pp.1658-1670
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• 2010

This study investigates the differences in advertisement attitude, brand attitude, and purchase intention based on advertising model and consumer product involvement. A total of 100 respondents in high involvement and 100 respondents in low involvement categories were exposed to the advertisements of a cosmetic brand using 4 different model types: celebrity endorser, expertise endorser, ordinary person as an endorser, and no endorser. The experiment was planned as $2{\times}4$ types including high/low involvement and 4 different model types (25 respondents each). After looking at an advertisement for 1 minute, respondents were asked to answer a survey measuring advertisement attitude, brand attitude, and purchase intension. The results of this study showed that 6 hypotheses were supported and there was a significant difference between the high involvement and low involvement group depending on the advertising models used as well as the advertisement that influence advertisement attitude, brand attitude, and purchase intension. High involvement consumers showed the most favorable advertisement attitude on an advertisement with an expertise endorser, but low involvement consumers showed the most favorable advertisement attitude on an advertisement with a celebrity endorser. High involvement consumers showed the most favorable brand attitude on an advertisement with an expertise endorser whereas low involvement consumers showed the most favorable brand attitude on an advertisement with a celebrity endorser. High involvement consumers showed the highest purchase intention on an advertisement with an expertise endorser whereas low involvement consumers showed no difference in purchase intention depending on advertisement models. This study shows that marketers should differentiate advertising strategies based on consumer involvement.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.11-26
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• 2022

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.