• Korean Journal of Cognitive Science
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• v.25 no.4
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• pp.417-433
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• 2014

This research examined whether Korean-learners of French were sensitive to discourse structure in anaphoric pronoun resolution. In the experiments, participants read three-sentenced stories and made judgements about how the last sentence of each story makes sense in relation to previous two sentences on a 7-point Likert scale. The stories differed in whether the subject of the last sentence continued the subject of the preceding sentence, and whether the subject of the last sentence was mentioned with a pronoun or a proper noun. The results from French participants replicated the patterns shown in previous studies. In contrast, Koreans exhibited greater difficulty in interpreting pronoun-subject sentences than noun-subject sentences regardless of subject continuity. These findings are discussed within the context of developmental perspective, which suggests the processing of co-referential interpretation may interact with language proficiency.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.713-725
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• 2016

Ambidextrous innovation is defined as the innovation capacity to pursue simultaneously both exploration and exploitation. Based on the organization learning and innovation management literature, the ambidexterity hypothesis predicts that ambidextrous innovation would enhance firm performance. This study attempts to verify the ambidexterity hypothesis in the context of TV drama production industry. TV drama producers' ambidextrous innovation is conceptualized as the simultaneous pursuit of exploratory and exploitative approaches in selecting genres of dramas. Data collected from 57 drama producers in 714 Korean TV drama projects between 1994 and 2009 support the ambidextrous hypothesis. The interaction between exploratory and exploitative approaches in genre selection is indeed positively related to the drama performance in terms of the viewing rate. Such results suggest that managers ought to manage high levels of both exploratory and exploitative innovation simultaneously in order to cope with increasing uncertainty, especially in highly uncertain cultural industry.

• Journal of Korean Academy of Nursing Administration
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• v.19 no.1
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• pp.95-107
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• 2013

Purpose: The purpose of this study was to examine the effectiveness of Action Research (AR) approach in nursing. Methods: Participants were 64 perioperative nurses recruited from C hospital in Gwangju, Korea. The nurses were engaged in the project through 2 cycles of planning, acting, observing, and reflecting. A mixed-methods design was used to examine changes in participants and their knowledge management practice. Quantitative data were analyzed using SPSS 20.0 program and qualitative reflection data underwent content analysis. Results: During the project, participants developed standardized pre-operative checklists and opened an Internet Cafe to better manage their perioperative nursing information. At the end of the project, there was a significant increase in nurses' knowledge management (p=.015) and the rate of surgical material prescription errors decreased from 8.0% to 2.9%. Core AR project team members' teamwork skills and organizational commitment increased significantly (p=.040, p=.301, respectively). The main themes that emerged from the qualitative data were learning how to solve problems in practice, facilitating team activities through motivation, barriers of large participation, and rewarded efforts and inflated expectations. Conclusion: The AR project contributed to empowering participants to solve local problems. AR is a useful methodology to promote changes in practices and research participants.

• School Mathematics
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• v.12 no.4
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• pp.605-617
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• 2010

This study explores the characteristics and roles of non-textual elements in secondary mathematics textbooks in the United States and South Korea, using a conceptual framework that I have developed: variety, contextuality, and connectivity. Analyzing five U.S. standards-based textbooks and 13 Korean textbooks, this study shows that although non-textual elements in mathematics textbooks are free of literal language, they exhibit different emphases and reflect assumptions about what is important in learning mathematics and how it can be taught and learned in a particular societal context (Mishra, 1999; Zazkis & Gadowsky, 2001). While there are similar patterns in the use of different types of non-textual elements in textbooks from both countries, different opportunities are provided for students to learn mathematics between the two countries.

• Journal of The Korean Association For Science Education
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• v.36 no.4
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• pp.551-561
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• 2016

The purpose of this study is to investigate both theoretically and empirically the roles of models in abductive reasoning for scientific problem solving. The context of the study is design-based research the goal of which is to develop inquiry learning programs in the domain of earth science, and the current article dealt with an early process of redesigning an abductive inquiry activity in geology. In the theoretical study, an extensive review was conducted with the literature addressing abduction and modeling together as research methods characterizing earth science. The result led to a tentative scheme for modeling-based abductive inference, which represented relationships among evidence, resource models, and explanatory models. This scheme was improved by the empirical study in which experts' reasoning for solving a geological problem was analyzed. The new scheme included the roles of critical evidence, critical resource models, and a scientifically sound explanatory model. Pedagogical implications for the support of student reasoning in modeling-based abductive inquiry in earth science was discussed.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.1-11
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• 2021

Document page segmentation is an important step in building a quality optical character recognition module. The study examined already existing work on the topic of page segmentation and focused on the development of a segmentation model that has greater functional significance for application in an organization, as well as broad capabilities for managing the quality of the model. The main problems of document segmentation were highlighted, which include a complex background of intersecting objects. As classes for detection, not only classic text, table and figure were selected, but also additional types, such as signature, logo and table without borders (or with partially missing borders). This made it possible to pose a non-trivial task of detecting non-standard document elements. The authors compared existing neural network architectures for object detection based on published research data. The most suitable architecture was RetinaNet. To ensure the possibility of quality control of the model, a method based on neural network modeling using the RetinaNet architecture is proposed. During the study, several models were built, the quality of which was assessed on the test sample using the Mean average Precision metric. The best result among the constructed algorithms was shown by a model that includes four neural networks: the focus of the first neural network on detecting tables and tables without borders, the second - seals and signatures, the third - pictures and logos, and the fourth - text. As a result of the analysis, it was revealed that the approach based on four neural networks showed the best results in accordance with the objectives of the study on the test sample in the context of most classes of detection. The method proposed in the article can be used to recognize other objects. A promising direction in which the analysis can be continued is the segmentation of tables; the areas of the table that differ in function will act as classes: heading, cell with a name, cell with data, empty cell.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.37-45
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• 2021

Since the Syrian Civil War in 2011, the number of refugees has been on the rise in Korea as well as worldwide. In addition to recognition of legal status for refugees, employment and education support, and qualification recognition are emerging as social issues. In this context, this study aims to compare the cases of Netherlands and Norway in terms of evaluation and recognition of refugees' qualifications. The findings of the study show that although there were concerns about the lack of official documents to verify the qualifications of refugees, the two countries have developed a special process for the evaluation and recognition for refugees respectively according to the Lisbon Recognition Convention. In addition, both countries have developed a recognition of prior learning system which has made the qualification recognition process flexible from a point of refugees. These experiences could be used as benchmarks for the Korean government which has a responsibility to develop its own qualification recognition system for refugees in the near future.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.185-196
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• 2022

The Internet of Things (IoT) has become more and more widespread in recent years, thus attackers are placing greater emphasis on IoT environments. The IoT connects a large number of smart devices via wired and wireless networks that incorporate sensors or actuators in order to produce and share meaningful information. Attackers employed IoT devices as bots to assault the target server; however, because of their resource limitations, these devices are easily infected with IoT malware. The Distributed Denial of Service (DDoS) is one of the many security problems that might arise in an IoT context. DDOS attempt involves flooding a target server with irrelevant requests in an effort to disrupt it fully or partially. This worst practice blocks the legitimate user requests from being processed. We explored an intelligent intrusion detection system (IIDS) using a particular sort of machine learning, such as Artificial Neural Networks, (ANN) in order to handle and mitigate this type of cyber-attacks. In this research paper Feed-Forward Neural Network (FNN) is tested for detecting the DDOS attacks using a modified version of the KDD Cup 99 dataset. The aim of this paper is to determine the performance of the most effective and efficient Back-propagation algorithms among several algorithms and check the potential capability of ANN- based network model as a classifier to counteract the cyber-attacks in IoT environments. We have found that except Gradient Descent with Momentum Algorithm, the success rate obtained by the other three optimized and effective Back- Propagation algorithms is above 99.00%. The experimental findings showed that the accuracy rate of the proposed method using ANN is satisfactory.

• Journal of the Korean earth science society
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• v.35 no.3
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• pp.203-212
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• 2014

It is important to explore ways that reinforce teachers' curricular expertise at the school level as the school curriculum autonomy expands. This study investigated teachers' curricular expertise that is required for teachers' professionalism, autonomy, and accountability to cope with the increasing school curriculum autonomy. Teachers in the future school are expected to explore and develop school level curriculum within a given school context. Through literature reviews, domestic and foreign case studies, and survey of teachers, this study examined difficulties in science teachers' exercise of their professionalism on curriculum organization and implementation at the school level. Difficulties in exercising teachers' curricular expertise include lack of actual autonomy in curriculum operation at the school level, inadequate infrastructures, demanding accountability based on students' achievement results, lack of time for reflection, and lack of recognition for teachers as independent curriculum designers. In the conclusion section, a couple of ways to solve these difficulties are suggested including expansion of actual autonomy, activation of teachers' participation in policy decision making, reinforcement of qualitative components in school assessment, diversification of the teacher's career ladder, and activation of teachers' participation in professional learning communities.

• Communications of Mathematical Education
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• v.31 no.1
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• pp.103-123
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• 2017

Mathematical tasks in general introduce and deal with real-life situations, and they derive to students' thinking fluently in solving the given tasks. The tasks might be considered as an important and significant factor to lead a successful mathematical teaching and learning situation. MiC Textbook is a representative one showing such good examples and tasks. This study explores concretely and in detail the cognitive demand level of mathematical tasks, by the subject of MiC Textbook. To accomplish this, this study is to reconstruct more elaborately the analysis framework developed by Hwang and Park in 2013. The framework basically was set up utilizing 'the cognitive demand level' suggested by Stein, et, al. The cognitive demand level is divided into two levels such as low level and high level. The low level is comprized of two elements such as Memorization Tasks(MT), Procedures Without Connections Tasks(PNCT), and high level is Procedures With Connections Tasks(PWCT), and Doing Mathematics Tasks(DMT). This study deals with the tasks on the area of 'data analysis and statistics' in MiC 1, 2, 3 level Textbook. As a result, mathematical tasks of MiC Textbook led learners to deal with and understand mathematical content for themselves, and furthermore to do leading roles for checking and reinforcing the content. Also, mathematical tasks of MiC Textbook are comprized of the tasks suitable to enhance mathematical thinking ability through communication. In addition, mathematical tasks of MiC Textbook tend to offer more learning opportunity to learners' themselves while the level of MiC Textbook is going up.