• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of Korean Elementary Science Education
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• v.41 no.3
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• pp.501-520
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• 2022

Considering the importance of spatial thinking in the process of learning astronomy, it is necessary to educate pre-service teachers on teaching methods that consider spatial thinking from the teacher training program stage. Accordingly, after providing education on spatial thinking to pre-service science teachers, problems and improvement plans perceived by them were explored for the images and inquiry activities of astronomy textbook units. In this study, spatial thinking in the astronomical domain was defined as the amalgam of the concepts of space, representation tools, and reasoning processes. The juniors attending the University of Education in the metropolitan area were educated on spatial thinking for two weeks in October 2021. They were then asked to voluntarily select one of the astronomy units to analyze problems in the textbooks and present modification plans to address those problems. Finally, 33 cases presented by 22 pre-service science teachers were analyzed, and the results of the study were as follows. Pre-service teachers recognized the problems in textbooks in terms of the concepts of space and reasoning processes, and proposed improvement plans to supplement them. However, in some cases, even if pre-service teachers properly recognized a problem, the improvement plan was not appropriate, or they were not able to analyze the images or inquiry activities in terms of spatial thinking. This study is significant in that it shows that pre-service teachers have the potential to properly reorganize and revise textbooks by participating in teacher training programs on spatial thinking. Furthermore, based on the results of this study, the direction of the teacher training program concerning spatial thinking was discussed.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.97-104
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• 2022

European integration processes have acted as a catalyst for the emergence of a new type of educational environment, which is characterized by competent flexibility of specialists. Therefore, the article focuses on professional training of teachers in the context of European integration processes using information technology and the search for innovative methods of training specialists. One of the educational priorities in Europe is to create a new model of a teacher who has an academic education, knows innovative methods, is able to perform functions and tasks efficiently and professionally, adequately, quickly and correctly respond to changes and innovations. The tasks facing education in the European dimension are formulated. The main trends in the education of teachers in modern Europe are described: the need to deepen and expand subject training programs in pedagogical institutions of Higher Education, which will allow autonomy of activity, awareness of responsibility for independent creative decisions, create favorable conditions for the development of professionalism through the use of Information Technology and the search for innovative methods of training specialists. At the present stage, various models of teacher training are being developed based on the University and practical concept using information technology and searching for innovative methods of training specialists. On this basis, two different theories of perception of teacher education were formed: as preparation of teachers for work throughout their professional career; as preparation for the first years of professional work, which is periodically repeated in the process of continuous professional training and improvement. Among the advantages that the use of Information Technology and the search for innovative methods of training specialists to implement the learning process, it is worth mentioning the following: simultaneous use of several channels of perception of the student or student in the learning process, thanks to which the integration of information processed by different sensory organs is achieved; the ability to simulate complex real experiments; visualization of abstract information by dynamic representation of processes, etc.

• Journal of Korean Library and Information Science Society
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• v.54 no.1
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• pp.191-220
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• 2023

This research attempts to identify how members of an online community collaboratively engaged with particular social information behaviors and accomplished a defined collective action. While responding to the Sewol Ferry tragedy, MissyUSA members quickly communicated and mobilized a collective action, a full-page ad campaign in The New York Times. As a follow up study, this secondary analysis quantitatively analyzes the primary data from a previous study to explore potential relationships or underlying factors among the various identified information behaviors. In this study, nineteen of the previously identified information behaviors were analyzed using exploratory factor analysis, yielding a total of eight factors. The two major factors of shared representation/collective identification and mobilizing resources verified the findings of the previous study and are in line with the findings typical of political science. The three factors of collaborative decision-making, reaction to tension, and brainstorming were factors that maximized communication and mobilization online, without any face-to-face communication or physical organization. Three emergent factors of outburst of dissent, boycott, and planning explained how members used negative emotions of anger, referential information for boycott, and incubated next collective actions. Through exploratory factor analysis, this study verifies and expands on the findings of the previous study by identifying several emergent factors that relate to the collaborative information behaviors of an online community engaged in a collective action.

• Journal of the Korean Chemical Society
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• v.67 no.5
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• pp.353-361
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• 2023

This study analyzed the uses of visual representations of particles in the matter units of the middle school science textbooks developed under the 2015 Revised National Curriculum. The material units in four textbooks were divided into explanation, inquiry, and evaluation sections, and visual representations of particles presented in the science textbooks were analyzed by the use type, the activity type, and the level of activity. In the explanation section, the visual representations of particles were mainly presented in the auxiliary use type, and in the inquiry and evaluation section, they were mainly presented in a direct use type. In terms of the activity types of the direct use of visual representations of particles, the interpreting activity was mainly presented in the explanation and evaluation sections, while the generating activity and completing activity were presented in relatively higher proportion in the inquiry section than the other two sections. In terms of activity level, identifying was the most common activity level in the explanation section, and inferring was the most common activity level in the inquiry and evaluation sections. Based on these results, the implications for the presentation and uses of visual representations of particles in science textbooks are discussed.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.8
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• pp.355-364
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• 2023

As advanced cyber threats continue to increase in recent years, it is difficult to detect new types of cyber attacks with existing pattern or signature-based intrusion detection method. Therefore, research on anomaly detection methods using data learning-based artificial intelligence technology is increasing. In addition, supervised learning-based anomaly detection methods are difficult to use in real environments because they require sufficient labeled data for learning. Research on an unsupervised learning-based method that learns from normal data and detects an anomaly by finding a pattern in the data itself has been actively conducted. Therefore, this study aims to extract a latent vector that preserves useful sequence information from sequence log data and develop an anomaly detection learning model using the extracted latent vector. Word2Vec was used to create a dense vector representation corresponding to the characteristics of each sequence, and an unsupervised autoencoder was developed to extract latent vectors from sequence data expressed as dense vectors. The developed autoencoder model is a recurrent neural network GRU (Gated Recurrent Unit) based denoising autoencoder suitable for sequence data, a one-dimensional convolutional neural network-based autoencoder to solve the limited short-term memory problem that GRU can have, and an autoencoder combining GRU and one-dimensional convolution was used. The data used in the experiment is time-series-based NGIDS (Next Generation IDS Dataset) data, and as a result of the experiment, an autoencoder that combines GRU and one-dimensional convolution is better than a model using a GRU-based autoencoder or a one-dimensional convolution-based autoencoder. It was efficient in terms of learning time for extracting useful latent patterns from training data, and showed stable performance with smaller fluctuations in anomaly detection performance.

• 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.512-519
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• 2023

Noise pollution poses significant challenges to human well-being and marine ecosystems. It is primarily caused by the flow around ships and marine installations, emphasizing the need for accurate noise evaluation of flow noise to ensure environmental safety. Existing flow noise analysis methods for underwater environments typically use a hybrid method combining computational fluid dynamics and Ffowcs Williams-Hawkings acoustic analogy. However, this approach has limitations, neglecting near-field effects such as reflection, scattering, and diffraction of sound waves. In this study, an alternative using direct method flow noise analysis via the lattice Boltzmann method (LBM) is incorporated. The LBM provides a more accurate representation of the underwater structural boundaries and acoustic wave effects. Despite challenges in underwater environments due to numerical instabilities, a novel DM-TS LBM collision operator has been developed for stable implementations for hydroacoustic applications. This expands the LBM's applicability to underwater structures. Validation through flow noise analysis in pipe orifice demonstrates the feasibility of near-field analysis, with experimental comparisons confirming the method's reliability in identifying main pressure peaks from flow noise. This supports the viability of near-field flow noise analysis using the LBM.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.601-610
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• 2023

The comprehension of water-level behavior in rivers is essential for effective flood and river environmental management. The objective of this study is to propose a methodology that can be used by field engineers engaged in actual practice, to readily identify the characteristics of water-level behavior during flood events. To this end, a total of 45 historical water-level records from 2010 to 2022 year, which provide flood information for the flood vulnerable districts of the Han River, were obtained. A Water-level Rise Behavior Curve (WRBC) was developed and suggested to quantify the amount of water-level rise per unit time during flood. As a result, the water-level rises by more than 80% of the total rise within the first 6.2 hours, followed by a gradual rise. The time required to achieve a particular equilibrium varied depending on the area and runoff characteristics of the upstream. Furthermore, the study revealed that the WRBC provides a statistical representation of the water-level rise trend during floods, and can be effectively utilized for flood mitigation measures in waterfront spaces and irrigation facilities.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.123-132
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• 2019

This paper analyzes the performances of actor Song Kang-Ho in the background of interdisciplinary and integrated film acting, using performance rather than acting as a general term. If the act is a concept limited to acting training or acting skills, performance is a broad concept that includes expressions, movements, and emotions. The performance on the screen can be explained in the context of film and can be extended to the social attitude of acting. In addition, I used the term screen in terms of representation rather than film referring to medium. Song Kang-Ho expressed the performances of various characters in more than 30 films. Although his facial expressions, gestures, and voices suitable for individual characters in various genres are represented in various ways, personality inherent in the actor Song Kang-Ho integrates persona with character. What drives it is the social attitude of screen performance. As a sign, acting is an ideological construct and foregrounds a character who describes a certain social and historical moment. Song Gang-Ho as actor, persona and character, who asserts the popularity, speaks to society and makes discourse. His comic performance is always confronting the tragedy of life, his face is the spirit of the times, and it expands into social meaning. The face of the close-up does not laugh at all, the gesture symbolized by the curved rear view is exaggerated disorderedly and disturbingly, and the voice using dialect accent does not follow the standard of the vocal.