• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.11a
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• pp.119-119
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• 2007

• Journal of the Korean Institute of Navigation
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• v.25 no.2
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• pp.159-172
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• 2001

The information technology(IT) development of telecommunication, along with the information analyzation over the world, enables the firms to process their inner and outer operations through Electronic Data Interchange (EDI) system. And the concept of logistics has become more important to the enterprises in strategic sense because it had aggrandized itself to more comprehensive and integrative concept. Also the world shipping market is more competitive than any other market. In these environment, to maintain competitive power, shipping firms process operations by Logistics Information system(LIS), And then, reduce the working processes, working time and its costs. So the LIS has become more important in developing our national logistics system and industry. Therefore, this study purposes on empirically analyzing the activation factors of shipping LIS and the relationship these, factors with logistic performances in the shipping industry. Considering environments of Shipping logistics information system, this study sets up the research model and hypothesis to examine the activation factors of shipping LIS and the relationship these factors with logistic performances. We used the field data on the 163 numbers of firms(29 overseas shipping companies and 133 forwarding Agency) to get the empirical evidence. According to the study results, The shipping LIS activation factors which the sample firms recognized as important: were top managers support, well structured communication channel, strategic plans connection and inner information analyzation level. And IS organization & human resources, IS discipline & training, software development, IS organizational alignment, database management system, information standardization, competitive advantage, financial support and government support represent partially significant. Also, the current shipping LISs main problems are expensive system cost, standardization of working processs, institutions imperfection and systems interaction defect. So these problems must be improved to activate shipping LIS.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.406-415
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• 2013

The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.179-184
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• 2012

Dipterocarps (Dipterocarpaceae) is a dominant tree family of tropical rainforest in Southeast Asia. Dipterocarps have been exploited for its timber and disappearing fast in East Kalimantan. In this study, we predicted the distribution of dipterocarpus, one of the main dipterocarps genera, by evaluating its habitat suitability using logistic regression analysis with specimen collection points and environmental factors from GIS data. Current distribution of dipterocarpus was generated by combining the habitat suitability classes with an updated forest cover map. Rainfall, soil type, followed by elevation was the main factors that influence the distribution of dipterocarpus in East Kalimantan. Dipterocarpus can be found in a quarter of the current forest cover, which is highly suitable as habitat of Dipterocarpus.

• Journal of Agricultural Extension & Community Development
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• v.16 no.4
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• pp.939-965
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• 2009

The Machine Learning has been identified as a promising approach to knowledge-based system development. This study aims to examine the ability of machine learning techniques for farmer's decision making and to develop the reference model for using pig farm data. We compared five machine learning techniques: logistic regression, decision tree, artificial neural network, k-nearest neighbor, and ensemble. All models are well performed to predict the sow's productivity in all parity, showing over 87.6% predictability. The model predictability of total litter size are highest at 91.3% in third parity and decreasing as parity increases. The ensemble is well performed to predict the sow's productivity. The neural network and logistic regression is excellent classifier for all parity. The decision tree and the k-nearest neighbor was not good classifier for all parity. Performance of models varies over models used, showing up to 104% difference in lift values. Artificial Neural network and ensemble models have resulted in highest lift values implying best performance among models.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.7-14
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• 2000

The purpose of this study is to improvement strategies for transportation systems of container cargo in Busan port. Therefore, it was forecasted the future container cargo demand using logistic curve formula. In 2011, container cargo demand was forecasted 8.791 million TEU(T/S including 12.559 million TEU). In order to improvement transportation systems of container cargo, this study presented following; $\circled1$ port facilities expansion, $\circled2$ diversity of container transport modes. $\circled3$ make up ICD and exclusive container roads, $\circled4$ the second Seoul-Busan Expressway.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.579-587
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• 2015

Landslides are major natural geological hazards that result in a large amount of property damage each year, with both direct and indirect costs. Many researchers have produced landslide susceptibility maps using various techniques over the last few decades. This paper presents the landslide susceptibility results from the geographically weighted regression model using remote sensing and geographic information system data for landslide susceptibility in the Inje area of South Korea. Landslide locations were identified from aerial photographs. The eleven landslide-related factors were calculated and extracted from the spatial database and used to analyze landslide susceptibility. Compared with the global logistic regression model, the Akaike Information Criteria was improved by 109.12, the adjusted R-squared was improved from 0.165 to 0.304, and the Moran’s I index of this analysis was improved from 0.4258 to 0.0553. The comparisons of susceptibility obtained from the models show that geographically weighted regression has higher predictive performance.

• Journal of Navigation and Port Research
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• v.32 no.9
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• pp.729-736
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• 2008

Very often has it happened that Korean flag ships were detained due to the defect of the ship itself at the port they are entering into by the system of Port State Control(PSC). It does matter because the high detention ratio of Korean ships causes to increase the survey ratio of Korean ships by PSC countries, which increases overall operating costs of Korean shipping companies. Therefore Korean government should take tougher action on the detention of Korean ships. The study uses 946 inspections to formulate the model of identifying PSC-weak ships by logistic regression analysis.

• Journal of Korean Society of Forest Science
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• v.95 no.2
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• pp.160-167
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• 2006

Most of the forest fires that occur in South Korea are caused by human. We partitioned South Korea into nine districts and used observed weather data and daily fire occurrence records for the 1994 to 2003 period to develop a human-caused fire occurrence model of South Korea. Logistic regression analysis techniques were used to relate the probability of a fire day to Fine Fuel Moisture Code (FFMC) component of the Canadian Forest Fire Danger Rating System. The probability of the number of fire day was increased as FFMC increased in the nine districts of South Korea.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.5
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• pp.521-529
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• 2015

Owing to a reliance on imported products from Europe and Japan, the use of logistics equipment with poor energy efficiency coupled with high maintenance costs can lead to high operating costs for some domestic logistic centers. To lower their operating costs, the logistic centers use motorized roller conveyors. In order to commercialize this process, it is necessary to establish the test criteria and assess the reliability of the process. Currently, there exists no standard verification method to test the reliability of motorized roller conveyors. In this study, we propose reliability assessment criteria for a: i) reliability test, ii) environmental test, iii) safety test, and iv) lifetime test.