• Journal of Science Education
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• v.46 no.1
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• pp.53-65
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• 2022

In the application and composition of learning content, the field trip learning of scientific inquiry could provide a positive effect. Also, it can arouse an experience of various inquiry activities through open thinking. In addition, it could take a positive effect by providing the diversity and specificity of wildlife experience for the living organism. The biology inquiry program of the field trip is a necessary process to acquire ecological experiences in the learning context. However, there is some problem to solve before the performance of field trip learning as professional knowledge of the outdoors inquiry. Therefore, this study developed a field trip inquiry program for the plant in a coastal dune using artificial intelligence to assist professional knowledge. The researcher carried out literature reviews and analysis related to studies and programs to investigate learning steps, content, and strategy. Also, this study investigated the effects of the program on the affective domain of gifted elementary science students. According to the results of this study, the program can provide a positive effect on motivation, task commitment, and attitude level. Consequently, the field trip learning program for plant in the coastal dune using artificial intelligence developed in this study can arouse a positive effect on the affective domain. Therefore, additional study is necessary related to inquiry programs of the field trip for various students and sites.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.44-51
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• 2022

In this study, TOPSIS(Techniques for Order Performance by Similarity to Ieal Solution) was used to evaluate the installation points of water quality monitoring networks in 34 streams of the Nakdong River watershed. The Nakdong River System has been measuring water quality and flow in 195 local streams since 2011. In particular, the 34 key management points are areas with many pollutants and poor water quality, requiring continuous water quality management. For the selection of points requiring management, 10 indicators were selected for evaluation, and the selected indicators were standardized and weighted using the entropy method. As a result of weight calculation, the presence or absence of a nearby measuring network received the greatest weight, and the average water quality and presence of an industrial complex obtained the highest weight. The evaluated data are judged to be the research results necessary for the establishment of a new water quality measurement network in the Nakdong River system and continuous water quality management in tributaries.

• Journal of Industrial Convergence
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• v.20 no.9
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• pp.25-38
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• 2022

The purpose of this paper is to verify the cost behavior of non-listed companies in Mongolia from 2013 to 2018. And we investigate the relationship between cost behavior and earnings management. Earnings management was measured using the Big-Bath and avoiding loss incentives. Big-Bath suspected firms report a very large loss and avoiding loss suspected firms have a bite profit. The results of this study are as follows. First, non-listed firms in Mongolia, operating costs(oc) and selling, general and administrative(sga) costs show the cost stickiness. Second, cost stickiness was different depending on the earnings management. The suspected avoiding loss firms have upward earnings management incentives, operating costs and sga costs all present anti-cost stickiness. The suspected big bath firms strengthen the cost stickiness of operating costs and sga costs. This study is meaningful in that it first analyzed the relationship between earnings management and cost stickiness of non-listed firms in Mongolia using empirical data. It will be meaningful in that it provides relevant information to those interested in research and investment.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.17-28
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• 2022

This study is to develop the direction of the development of the next-generation mapping of marine information required to develop a base of the utilization localization of maritime production tools. The GIS data-processing products and technologies currently used in the Korea's marine sector depend on external applications which is renewal costs, technical updates, and unreflected characteristics. Meanwhile, the S-100 standard, the next generation hydrographic data model that complements S-57's problems in marine GIS data processing, was adopted as a new marine data standard. This study aims to present the current status and problems of marine GIS technology in Korea and to suggest the development direction of GIS software based on the next generation hydrogrphic data model S-100 standard of IHO(International Hydrographic Organization). S-100-based marine GIS localization technology development and industrial ecosystem development research is expected to scientific decision-making on policy issues that occur with other countries such as marine territory management and development and use of marine resources.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.59-73
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• 2022

Currently, the conflict between use and conservation of the ocean is intensifying in the ocean, so it is essential to introduce an effective method to define and manage it in advance for each core value of ocean. Accordingly, although the ocean is divided into nine marine use zone and managed through marine spatial planning, the analysis of the sea areas where mutually exclusive activities overlap in the ocean is insufficient. In this study, an automated model was developed to derive a sea areas where the core values of the ocean conflict. In order to analyze marine activities, available data on marine activity were collected, and data necessity for the analysis of mutually exclusive marine activities were derived. After classifying the derived data into legal and characteristic data, a conflict matrix was prepared through pairwise comparison between data to designate priorities when overlapping occurs. Based on the designated priorities, an automation model was developed, and sea areas where marine activities conflicted were derived, visualized, and area calculated. Using this, it is judged that the efficiency of decision-making can be improved by clearly deriving the sea areas where major issues occur in establishing the marine spatial planning.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.373-395
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• 2022

This study aimed to examine how prospective mathematics teachers (PMTs) perceive collaborative problem-posing (CPP) as a method to cultivate students' creativity and character in mathematics education. This is to propose the introduction of CPP at the stage of preparatory math teacher education as one of the ways to reinforce the creativity and character education capacity of PMT), and to attempt to be an opportunity to actively utilize CPP in math teaching-learning in the school field for the education of students' creativity and character. To achieve this objective, I designed PMTs taking the 'Educational Theories for Teaching Mathematics' course, required in the second year of university, to experience CPP tasks. Data were collected through questionnaires or interviews over three years on how PMTs recognized the CPP tasks as a tool to cultivate students' creativity and character in secondary schools. The results of the study are as follows. First, PMTs recognized regardless of their CPP experience that CPP might have a positive impact on improving students' ability to devise various ideas and that it positively influences students' attitudes toward building interpersonal relationships, including teamwork, respect, and consideration. Second, the experience of PMTs participating in the CPP made them more positively aware that CPP is effective in improving students' ability to elaborate on ideas. Third, the PMTs' experience of participating in CPP led to a more positive perception of the impact of CPP on the students' abilities and attitudes, namely, the students' ability to elaborate on ideas and their inner attitudes toward individuals, including honesty, fairness, and responsibility, and the attitude of students regarding logically presenting their opinions and making rational decisions. Finally, if there are downsides to the offline environment, an online environment may be more beneficial.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.954-966
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• 2021

With regards to the marine spatial plannings of the world, the spaces are being managed through the integration of various uses and the establishment of systems and laws in the perspective of the utilization of spaces. In the perspective of policy establishment, the policy readiness level is applied to analyze the trends in the studies on South Korea's marine spatial plans. The scope of the study included analyzing marine spatial plan as a keyword in articles published over the period from 2010 to 2020. The methods of analysis included the analyses of the frequency of word appearance, word clouds, and appearance intensity, which were used to identify key issues. Five keywords that were related to the topics were identified, and were again used to identify the key themes. The core themes were changing in all phases, such as the principles development phase, institutionalization phase, policy verification phase. For future benefit, this requires more research in South Korean public organizations and universities.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.175-183
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• 2022

The collision between a ship and bridge across a waterway may result in extremely serious consequences that may endanger the safety of life and property. Therefore, factors affecting ship bridge collision must be investigated, and the impact force should be discussed based on various collision conditions. In this study, a finite element model of ship bridge collision is established, and the peak impact force of a ship bridge collision based on 50 operating conditions combined with three input parameters, i.e., ship loading condition, ship speed, and ship bridge collision angle, is calculated via numerical simulation. Using neural network models trained with the numerical simulation results, the prediction model of the peak impact force of ship bridge collision involving an extremely short calculation time on the order of milliseconds is established. The neural network models used in this study are the basic backpropagation neural network model and Elman neural network model, which can manage temporal information. The accuracy of the neural network models is verified using 10 test samples based on the operating conditions. Results of a verification test show that the Elman neural network model performs better than the backpropagation neural network model, with a mean relative error of 4.566% and relative errors of less than 5% in 8 among 10 test cases. The trained neural network can yield a reliable ship bridge collision force instantaneously only when the required parameters are specified and a nonlinear finite element solution process is not required. The proposed model can be used to predict whether a catastrophic collision will occur during ship navigation, and thus hence the safety of crew operating the ship.