• The Journal of Bigdata
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• v.2 no.2
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• pp.9-16
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• 2017

Global Platform Solution Company (aka Amazon, Google, MS, IBM) who has cloud platform, are driving AI and Big Data service on their cloud platform. It will dramatically change Enterprise business value chain and infrastructures in Supply Chain Management, Enterprise Resource Planning in Customer relationship Management. Enterprise are focusing the channel with customers and Business Partners and also changing their infrastructures to platform by integrating data. It will be Digital Transformation for decision support. AI and Deep learning technology are rapidly combined to their data driven platform, which supports mobile, social and big data. The collaboration of platform service with business partner and the customer will generate new ecosystem market and it will be the new way of enterprise revolution as a part of the 4th industrial revolution.

• Journal of Environmental Science International
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• v.12 no.2
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• pp.185-193
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• 2003

The purpose of this study was attempted to establish concepts of environmental-friendly applications of flood plain and to suggest the application plans. The results of this study can be summarized as follows; 1. Roles of flood plain as biotop (restoration, preservation, and creation of stream corridor ecosystem) should be considered. 2. Application methods considering environmental and scenic values should be reviewed. 3. Application methods reflecting values as regional ecological resources should be planned. 4. Preservation and application should be considered together, and obtaining a means of living for regional residents and creation of economic profits should be considered together. 5. Land application and approach method by usages (integrated management model) should be applied to utilize and manage flood plain efficiently. 6. Flood plain application programs should be designed reflecting opinions of regional residents. 7. With respect to space planning of flood plain, introduction of facilities focused on ecosystem preservation/ecosystem restoration/experiences/observation/learning/culture/ recreation/water purification could be reviewed positively.

• Journal of the Korean Society of Visualization
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• v.19 no.2
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• pp.41-47
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• 2021

River and stream are the important water supply source in our lives. Eutrophication causes excessive green algae growth including microcystis, which makes harmful to ecosystem and human health. Therefore, the water purification process to remove green algae is essential. In Korea, green algae alarm system exists depending on the concentration of green algae cells in river or stream. To maintain the growth amount under control, green algae monitoring system is being used. However, the unmanned, small and automatic monitoring system would be preferable. In this study, we developed the 3D printed device to measure the concentration of green algae cell using microfluidic droplet generator and deep learning. Deep learning network was trained by using transfer learning through pre-trained deep learning network. This newly developed microfluidic cell counter has sufficient accuracy to be possibly applicable to green algae alarm system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.841-854
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• 2020

The paper explains the method to process, analyze and predict traffic patterns in Los Angeles county using Big Data and Machine Learning. The dataset is used from a popular navigating platform in the USA, which tracks information on the road using connected users' devices and also collects reports shared by the users through the app. The dataset mainly consists of information about traffic jams and traffic incidents reported by users, such as road closure, hazards, accidents. The major contribution of this paper is to give a clear view of how the large-scale road traffic data can be stored and processed using the Big Data system - Hadoop and its ecosystem (Hive). In addition, analysis is explained with the help of visuals using Business Intelligence and prediction with classification machine learning model on the sampled traffic data is presented using Azure ML. The process of modeling, as well as results, are interpreted using metrics: accuracy, precision and recall.

• The Korean Journal of Ecology
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• v.28 no.6
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• pp.405-415
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• 2005

This paper considers the advantage of Machine Learning (ML) implemented to freshwater ecosystem research. Currently, many studies have been carried out to find the patterns of environmental impact on dynamics of communities in aquatic ecosystems. Ecological models popularly adapted by many researchers have been a means of information processing in dealing with dynamics in various ecosystems. The up-to-date trend in ecological modelling partially turns to the application of ML to explain specific ecological events in complex ecosystems and to overcome the necessity of complicated data manipulation. This paper briefly introduces ML techniques applied to freshwater ecosystems in Korea. The manuscript provides promising information for the ecologists who utilize ML for elucidating complex ecological patterns and undertaking modelling of spatial and temporal dynamics of communities.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.35-44
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• 2013

This article is exploring on the concept and realization conditions of 'Smart Education' including the propulsion environment and problems about 'Smart Education'. Based on the concept and realization conditions of 'Smart Education', this paper will review various aspects, such as the technology, infrastructure, school teachers' preparation situation, ecosystem and distribution system, and propose further policy alternatives of 'Smart Education'.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.464-465
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• 2018

Bass and Bluegill, which are representative ecosystem disturbance species, are reported to be the most important factor in the reduction of domestic native fish populations in Korea. Therefore, it is necessary to develop system and field application technology for the extermination of these foreign species. Recently, the CNN(Convolutional Neural Network), one of the deep learning systems for the recognition, classification, and learning, has shown excellent performance. However, CNN data used for object recognition and classification were mainly applied to recognition and classification of other objects with distinct characteristics. This study proposes a system that applies CNN to the classification of fish species with similar characteristics.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.45-52
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• 2023

With the advent of deep learning, Artificial Intelligence (AI) technology has experienced rapid advancements, extending its application across various industrial sectors. However, the focus has shifted from the independent use of AI technology to its dispersion and proliferation through the open AI ecosystem. This shift signifies the transition from a phase of research and development to an era where AI technology is becoming widely accessible to the general public. However, as this dispersion continues, there is an increasing demand for the verification of outcomes derived from AI technologies. Causal AI applies the traditional concept of causal inference to AI, allowing not only the analysis of data correlations but also the derivation of the causes of the results, thereby obtaining the optimal output values. Causal AI technology addresses these limitations by applying the theory of causal inference to machine learning and deep learning to derive the basis of the analysis results. This paper analyzes recent cases of causal AI technology and presents the major tasks and directions of causal AI, extracting patterns between data using the correlation between them and presenting the results of the analysis.

• Journal of The Korean Association For Science Education
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• v.36 no.1
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• pp.29-43
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• 2016

There have been much efforts to reconstruct the science curriculum focusing on Disciplinary Core Ideas(DCI) in many countries such as America and Europe, the most practical effort has been to design a curriculum with learning progressions(LPs). LPs describe stepwise how students can systematically move toward the understanding of more sophisticated ideas or scientific activities and explain in succession the process of understanding the ideas while the students learn. In this study, a LP for ecosystems has been developed, and the developed LP is then evaluated accordingly. The Ecosystem is one of the DCI of the life science in Next Generation Science Standards(NGSS). The development process of the LP was set at step 4(Development, Assessment, Analysis, and Amendment), and developed through an iterative process of sequences. As a result of analyzing the developed LP, an assessment based on the LP provides reliable information to identifying student ability. This study proposes the development process of the LP and its methodological aspects to use Core Achievement Standards, Ordered Multiple-Choice items and the Rasch model. In addition, using the empirically proven LP suggests a way of strengthening curriculum linked to educational content, teaching methods and assessment. Utilizing the proposed development process in this study will be to present the standard into the direction of becoming part of the curriculum. Currently, the state of domestic research for the LP is still lacking. This study determined the development process of the LP and the need to conduct future research on the LPs.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.603-611
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• 2016

Educational games offer an opportunity to engage and inspire students to take an interest in every subject material in school. The "fun" obtain when playing games become a trigger for the use of games in learning. However, there are doubts whether the players actually learn while they are having fun. Vidyanusa is an Online Mathematics Education Game being developed by Crayonpedia Education Ecosystem in Indonesia. The learning goal of Vidyanusa is to engage junior high school students in learning mathematics. In this paper, we design the Vidyanusa game material Functions and Relations by using Balanced Design Approach. This approach has three models in succession; the Content Model outlines the purpose of the game, the Task Model maps out the mission, and the Evidence Model outlines student measurement. This paper will then discusses the quality of games produced in term of Usability factor for effective results and objective. The measurement of the game was carried out based on International Standard ISO/IEC 9126-1 FDIS about Software Quality Product.