• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1207-1216
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• 2018

Discharge or water level predictions at tidally affected river reaches are currently still a great challenge in hydrological practices. This research aims to predict water level of the tide dominated site, Jamsu bridge in the Han River downstream. Physics-based hydrodynamic approaches are sometimes not applicable for water level prediction in such a tidal river due to uncertainty sources like rainfall forecasting data. In this study, TensorFlow deep learning framework was used to build a deep neural network based LSTM model and its applications. The LSTM model was trained based on 3 data sets having 10-min temporal resolution: Paldang dam release, Jamsu bridge water level, predicted tidal level for 6 years (2011~2016) and then predict the water level time series given the six lead times: 1, 3, 6, 9, 12, 24 hours. The optimal hyper-parameters of LSTM model were set up as follows: 6 hidden layers number, 0.01 learning rate, 3000 iterations. In addition, we changed the key parameter of LSTM model, sequence length, ranging from 1 to 6 hours to test its affect to prediction results. The LSTM model with the 1 hr sequence length led to the best performing prediction results for the all cases. In particular, it resulted in very accurate prediction: RMSE (0.065 cm) and NSE (0.99) for the 1 hr lead time prediction case. However, as the lead time became longer, the RMSE increased from 0.08 m (1 hr lead time) to 0.28 m (24 hrs lead time) and the NSE decreased from 0.99 (1 hr lead time) to 0.74 (24 hrs lead time), respectively.

• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.275-286
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• 2019

In order to prevent local extinction of organisms and to preserve biodiversity, it is important to ensure connectivity between habitats. Even if the habitat is exposed to various disturbance factors, it is possible to avoid or respond to disturbances if they are linked to other habitats. Habitat connectivity can be assessed from a variety of perspectives, but the importance of functional connectivity based on species movement has been emphasized in recent years due to the development of computational capabilities and related software. Among them, Circuitscape, which is a connectivity evaluation tool, has an advantage it can provide detailed reference data for the city planning because it maps ecological flows on individual grid based on circuit theory. Therefore, in this study, the functional connectivity of Suwon was evaluated by applying Circuitscape and then, the ecological corridor to be conserved and supplemented was suggested based on it. The results of this study are expected to effectively complement the methodology related ecological corridor/axis, which was previously provided only in the form of a diagram, and to be effective in management of development project and urban planning.

• The Journal of Korean Association of Computer Education
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• v.22 no.1
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• pp.21-30
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• 2019

In this research, there is a purpose to develop an informatics education curriculum of the general level that the preliminary teacher at elementary school prepares for information education. First of all, in order to achieve the purpose, we compare and analyze the standard CS 2013 of the educational curriculum of elementary school teacher training university, University-Level Program cooperation deepening course, higher education course, and prepared content and level. Secondly, subjects were structured in consideration of standard J07-GE analysis of higher education curriculum and cooperation with secondary education course. Third, subject names were determined by examination by experts, taking into consideration the scope of subjects, content system composition, etc. Computer Science II, Computer Science II, Data Management in the domain to understand the basic principles of Computer Science I, Computing System, in order to approach expert opinions, analysis results, problems arising in information society from the viewpoint of computer science We proposed data management and analysis to grasp the patterns and relationships involved. In this research, not only improving ability to solve problems based on the basic capacity strengthening of teachers but also presenting subjects of general level, considering continuity star of high school information subjects it makes sense.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.535-546
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• 2018

This study conducted a meta-analysis to examine syntagmatically on the variables related with recovery among persons with mental illness in Korea. In order to do a meta-analysis, theses and dissertations published between 1999 and 2018 in Korea were reviewed systematically and a total of 24 including studies were selected. Using Comprehensive Meta Analysis (CMA) 3.0 software, this study calculated average effect size and moderator variables related with recovery among persons with mental illness. Results were as follows. First, this study identified a total of 16 variables related with recovery among persons with mental illness. Second, the results indicated that variables which showed large effect sizes included social support(r=.575), empowerment(r=.555), self-efficacy(r=.544), social skill(r=.500), relationship with social worker(r=.482), stigma(r=-.446), family support(r=.418). Third, variables with medium effect sizes included interpersonal relationship capacity (r=.391), agency service satisfaction(r=.366), insight(r=.373) and symptom(r=-.239). Fourth, variables with small effect sizes included work experience(r=.188). Fifth, moderator analyses were conducted utilizing characteristics of residence state (community or mental hospital). Moderator effects were identified in the social support and family support. Based on the findings, theoretical and clinical implications for the recovery among persons with mental illness in Korea were discussed.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Convergence Security Journal
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• v.18 no.1
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• pp.117-128
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• 2018

The purpose of this paper is to analyze the behavior of North Korea's cyber attack against South Korea since 2009 based on major international security theories and suggest South Korea's policy option. For this purpose, this paper applied the behavioral domain and characteristics of 'cyber power' and 'coercion dynamics' model, which are attracting attention in international security studies. The types of cyber attacks from North Korea are classified into the following categories: power-based incarceration, leadership attacks and intrusions, military operations interference, and social anxiety and confusion. In terms of types and means of cyber power, North Korean GPS disturbance, the Ministry of Defense server hacking and EMP are hard power with high retaliation and threat and cyber money cashing and ransomware are analyzed by force in the act of persuasion and incentive in the point of robbing or asking for a large amount of money with software pawns. North Korea 's cyber attack has the character of escape from realistic sanctions based on the second nuclear test. It is important for South Korea to clearly recognize that the aggressive cyberpower of North Korea is changing in its methods and capabilities, and to ensure that North Korea's actions result in far greater losses than can be achieved. To do this, it is necessary to strengthen the cyber security and competence to simultaneously attack and defend through institutional supplement and new establishment such as cyber psychological warfare, EMP attack preparation, and enhancement of security expertise against hacking.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.199-208
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• 2021

In this paper, the effect of artificial intelligence convergence education program that provides STEAM education using machine learning platform on elementary school students' STEAM literacy and learning flow was analyzed. A homogeneous group of 44 elementary school 6th graders was divided into an experimental group and a control group. The control group received 10 lessons of general subject convergence class, and the experimental group received 10 lessons of STEAM-based artificial intelligence convergence education using Machine learning for Kids. To develop the artificial intelligence convergence education program, the goals, achievement standards, and content elements of the 2015 revised curriculum to select subjects and class contents is analyzed. As a result of the STEAM literacy test and the learning flow test, there was a significant difference between the experimental group and the control group. In particular, it can be confirmed that the coding environment in which the artificial intelligence function is expanded has a positive effect on learners' learning flow and STEAM literacy. Among the sub-elements of convergence talent literacy, significant differences were found in the areas of personal competence such as convergence and creativity. Among the sub-elements of learning flow, significant differences were found in the areas such as harmony of challenge and ability, clear goals, focus on tasks, and self-purposed experiences. If further expanded research is conducted in the future, it will be a basic research for more effective education for the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.19-26
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• 2021

The lattice structure is attracting attention from industry because of its excellent strength and stiffness, ultra-lightweight, and energy absorption capability. Despite these advantages, widespread commercialization is limited by the difficult manufacturing processes for complex shapes. Additive manufacturing is attracting attention as an optimal technology for manufacturing lattice structures as a technology capable of fabricating complex geometric shapes. In this study, a unit cell was formed using a three-dimensional coordinate method. The relative density relational equation according to the boundary box size and strut radius of the unit cell was derived. Simple cubic (SC), body-centered cubic (BCC), and face-centered cubic (FCC) with a controlled relative density were designed using modeling software. The accuracy of the equations for calculating the relative density proposed in this study secured 98.3%, 98.6%, and 96.2% reliability in SC, BCC, and FCC, respectively. A simulation of the lattice structure revealed an increase in compressive yield load with increasing relative density under the same cell arrangement condition. The compressive yield load decreased in the order of SC, BCC, and FCC under the same arrangement conditions. Finally, structural optimization for the compressive load of a 20 mm × 20 mm × 20 mm structure was possible by configuring the SC unit cells in a 3 × 3 × 3 array.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.583-590
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• 2021

This paper is a study on the digitization of an analog 3D pen. The term digital implies features such as homeostasis, transformability, combinability, reproducibility, and convenience of storage. One device that produces a combination of these digital characteristics is a 3D printer, but its industrial use is limited due to low productivity and limitations with materials and physical characteristics. In particular, improvements are required to use 3D printers, such as better user accessibility owing to expertise and skills in modeling software and printers. Complementing this fact is the 3D pen, which is excellent in portability and ease of use, but has a limitation in that it cannot be digitized. Therefore, in order to secure a digitalization capability and ease of use, and to secure the safety of printing materials that pose controversial hazards during the printing process, research problems and alternatives have been derived by combining food, and digitization was demonstrated with a newly developed 3D pen. In order to digitize the 3D pen, a sensor in a structured device detects the motion of an analog 3D pen, and this motion is converted into 3D data (X-Y-Z coordinate values) through a spatial analysis algorithm. To prove this method, the similarity was confirmed by visualization using MeshLab version 1.3.4. It is expected that this food pen can be used in youth education and senior healthcare programs in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.134-145
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• 2021

It is common to optimize the propulsion control system through a so-called tuning process that modifies the parameter values of the propulsion control software during a ship commissioning. However, during this process, if the error of the initial setting value is large, the tuning time may take too long, or the propulsion equipment can be seriously damaged. Therefore, we conducted research on the design of a propulsion controller that applied a Processor lever controller even for inexperienced people with relatively little experience in tuning propulsion control software to be able to reduce the tuning time while protecting the propulsion system. Through simulation, by comparing the execution result of propulsion control lever commands through the PI controller without applying the Processor lever controller. We analyzed the improvement of the Overshoot and propulsion performance. The simulation results showed that the safety of the propulsion system increased because Overshoot of approximately 9.74%, which occurred when the Processor lever function was not applied.