• 한국사회정책
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• v.20 no.2
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• pp.261-304
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• 2013

This article is aiming intensively to analyze the polarizing tendency of labour market and social integration. The polarization of labour market is being regarded as one of the hottest issues not less important than those problems of economic growth, employment, income distribution and national security etc. in the national policy. In this article, we will first follow up the important phenomena of labour market polarization and the background as well as its consequence. Especially, it asks if the present labour policy in the new government which is now being concentrated on the improvement of employment rate(from the present 63% to the 70% in the future) could deserve to diminish the polarization of labour market in korea. At one side, this article makes the special attention on the diversifying tendency of labour market and the various phenomena of fragmentation and segmentation in the labour market according to the forms and types of employment and according to the employee's status as much as the company's size. At the other side, it emphasizes that to overcome the polarization of labour market should require the wide reform from the legal measure to the improvement of the wage system, and the qualification system and the social investment as well as the human resource development. Furthermore, this article stresses the importance of integrative approach between the active market policy and the social policy instead of choosing each policy option, seperatively.

• The Journal of Korean Philosophical History
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• no.58
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• pp.279-305
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• 2018

Confucius stressed both 'study (學)' and 'thinking (思)' but the two notions are complementary. To precisely measure the importance of the two, however, 'study' outweighs 'thinking.' Yet Confucius primarily states three steps on Analects of Confucius. In other words, Confucius mentioned two steps on 'Haksajang (學思章)' on the surface but it is actually composed of three steps. Then what is the step three? It is a critical issue to grasp the core of Confucius' idea. The ultimate goal of Confucius' idea is, as stressed by Cheng Yi (程伊川), to 'reach the realm of saint by learning,' which refers to a saint as an ideal human character. This paper is to examine three steps of 'oneness of study and thinking (學思合一)' as a way of Confucius' academic methodology to be the saint along with its structure. Saint, in a word, is characterized as 'communication (通).' It means communication through learning and thinking, which are the three steps of study(學)-thinking (思)-communication(通). Confucius emphasizes that this step also is a process itself (知) but it can be truly completed (dual structure) only by practice (行). Eventually, Confucius' academic methodology is of learning scriptures (學), thinking based on this learning (思) and practicing (行) based on this entire procedure (通). In other words, it is of a dual structure with three steps of 知 (study(學)-thinking(思)-communication(通))-practice(行).

• Journal of Wetlands Research
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• v.23 no.2
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• pp.122-132
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• 2021

We reviewed the methods employed in Korean tidal flat surveys to measure the local abundance of the endangered wildlife and marine protected species, the fiddler crab, Austruca lactea. A complete census for infinite population is impossible even in a limited habitat within a tidal flat, and density estimates from samples strongly vary due to diverse biological and ecological factors. The habitat boundaries and areas shift with periodicities or rhythmic activities of organisms as well as measurement errors. Hence the local abundance calculated from density and habitat areas should be regarded as transient. This conjecture was valid based on the spatio-temporal variations of the density averages, standard error ranges, and spatial distribution of the crab, A. lactea observed for 3 years (2015-2017) in Songdo tidal flat in Incheon. We proposed the potential habitat areas using the occurrence probability of 50% from logistic regression model, reflecting the importance of habitat conservation value as an alternative to local abundance. The spatial shape of potential habitat predicted from a generalized model would remain constant over time unless the species' critical environmental conditions change rapidly. The species-specific model is expected to be used for the introduction of desired species in future habitat restoration/creation projects.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.307-332
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• 2022

One of the most intensively conducted research areas in business application study is a bankruptcy prediction model, a representative classification problem related to loan lending, investment decision making, and profitability to financial institutions. Many research demonstrated outstanding performance for bankruptcy prediction models using artificial intelligence techniques. However, since most machine learning algorithms are "black-box," AI has been identified as a prominent research topic for providing users with an explanation. Although there are many different approaches for explanations, this study focuses on explaining a bankruptcy prediction model using a counterfactual example. Users can obtain desired output from the model by using a counterfactual-based explanation, which provides an alternative case. This study introduces a counterfactual generation technique based on a genetic algorithm (GA) that leverages both domain knowledge (i.e., causal feasibility) and feature importance from a black-box model along with other critical counterfactual variables, including proximity, distribution, and sparsity. The proposed method was evaluated quantitatively and qualitatively to measure the quality and the validity.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.6
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• pp.35-50
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• 2022

As the water shortage has become a noticeable issue due to climate change, forests play an importance role as the provider of water supply service. There is, however, little information about the relationships between the factors used in the estimation of water supply service and coarse pore fraction of forest soil which determines the potential of water supply. To find out whether there would be an amelioration in the scoring system of water supply service estimation, we examined all factors except meteorological one and additionally, analyzed 4 extra factors that might be related with coarse pore fraction of soil. A total of 2,214 soil samples were collected throughout South Korea to measure coarse pore fractions from 2015 to 2020. First, the result of average coarse pore fraction of all samples showed 32.98±6.59% which was consistent with previous studies. And the results of non-parametric analysis of variance indicated that only two of eleven factors that was used in the scoring system matched the results of coarse pore fraction of forest soils. Tree canopy coverage showed no difference among categories, and slope also showed no significance at level of 0.05 in the linear regression analysis. Additionally, the applicability of 4 extra factors were confirmed, as the result of coarse pore fractions of soil samples were different for various categories of each factor. Therefore, the scoring system of water supply service of forest should be revised to improve accuracy.

• Journal of the Korea Institute of Building Construction
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• v.22 no.4
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• pp.391-402
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• 2022

With the number of social overhead capital(SOC) projects that introduce private capital on the rise, overseas construction global companies today need to establish and advance their overseas order strategies. In this context, the purpose of this study is to develop the public private partnership(PPP) capacity evaluation model for developing countries and use it for domestic overseas construction companies to establish strategies for overseas expansion. The PPP competency evaluation model analyzes the importance of PPP competency evaluation items and infrastructure environment competency evaluation items through a review of previous studies and an interview survey with overseas construction experts. Through the above analysis results and expert surveys, problems that may occur when overseas construction companies enter the PPP market were derived, and improvement measures were proposed. Countries with a high probability of overseas construction companies entering the PPP market were determined to be those that have a mature PPP system, low risk in construction, and a good entry environment with a high infrastructure market size and growth rate. In addition, a lack of PPP investment experience, the absence of information on the infrastructure environment, and a shortage of PPP experts were identified as problems when entering the overseas construction PPP market. As an improvement measure, it was suggested to enter in cooperation with domestic and foreign companies. In addition, a plan was proposed to develop a curriculum to secure experts in areas such as PPP finance and contracts and to provide PPP information for each country. These findings are expected to contribute to overseas construction companies proposing strategies for entering the overseas construction market and using them for overseas expansion strategies and policy establishment.

• The Mathematical Education
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• v.62 no.2
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• pp.175-194
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• 2023

Despite the importance of pattern learning for elementary school students, few studies have investigated in detail the understanding of patterns of lower-grade students. This study aimed to analyze the understanding of patterns of second-grade elementary school students. Since the patterns in the second grade are taught through the unit called Finding Rules, students' understanding of patterns was compared and contrasted before and after they learned the unit. To this end, a written instrument to measure students' understanding of patterns was developed on the basis of previous studies on pattern learning for lower-grade students. A total of 189 students were analyzed. As a result of the study, the overall correct answer rates in the post-test were higher in most items than those in the pre-test, illustrating the positive effect of the specific unit. However, students found it difficult to find rules in which two components would change simultaneously either in geometric or numeric patterns, find patterns that would be similar in structure, represent geometric patterns into numeric patterns, find empty terms in increasing patterns, and reason the specific terms in patterns that can be differently interpreted. Based on these research results, this study sheds light on students' understanding of patterns and suggests implications to improve their understanding.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.497-504
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• 2023

In this study, Selective catalytic reduction (SCR) + Diesel particulate filter (DPF) system was installed on a ship with a low-speed engine to conduct the on-board test. The target ship (2,881 gross tons, rated power 1,470 kW@240 rpm ×1) is a general cargo ship sailing in the coastal area. Drawing development, approvals and temporary survey of the ship were performed for the installation of the after-treatment system. For performance evaluation, the gaseous emission analyzer was used according to the NOx technical code and ISO-8178 method of measurement. The particulate matter analyzer used a smoke meter to measure black carbon, as discussed by the International Maritime Organization (IMO). Tests were conducted using MGO (0.043%) and LSFO (0.42%) fuels according to the sulfur content. The test conditions were selected by considering the engine rpm (130, 160 and 180). Gaseous emission and particulate matter (smoke) were measured according to the test conditions to confirm the reduction efficiency of the after treatment system. The results of NOx emission and particulate matter (smoke) revealed that reduction efficiency was more than 90%. The exhaust pressure met the allowable back pressure (less than 50 mbar). This study confirms the importance of the on-board test and the potential of SCR + DPF systems as a response technology for reducing nitrogen oxides and particulate matter.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.125-132
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• 2022

Sentence compression is a natural language processing task that generates concise sentences that preserves the important meaning of the original sentence. For grammatically appropriate sentence compression, early studies utilized human-defined linguistic rules. Furthermore, while the sequence-to-sequence models perform well on various natural language processing tasks, such as machine translation, there have been studies that utilize it for sentence compression. However, for the linguistic rule-based studies, all rules have to be defined by human, and for the sequence-to-sequence model based studies require a large amount of parallel data for model training. In order to address these challenges, Deleter, a sentence compression model that leverages a pre-trained language model BERT, is proposed. Because the Deleter utilizes perplexity based score computed over BERT to compress sentences, any linguistic rules and parallel dataset is not required for sentence compression. However, because Deleter compresses sentences only considering perplexity, it does not compress sentences by reflecting the linguistic information of the words in the sentences. Furthermore, since the dataset used for pre-learning BERT are far from compressed sentences, there is a problem that this can lad to incorrect sentence compression. In order to address these problems, this paper proposes a method to quantify the importance of linguistic information and reflect it in perplexity-based sentence scoring. Furthermore, by fine-tuning BERT with a corpus of news articles that often contain proper nouns and often omit the unnecessary modifiers, we allow BERT to measure the perplexity appropriate for sentence compression. The evaluations on the English and Korean dataset confirm that the sentence compression performance of sentence-scoring based models can be improved by utilizing the proposed method.