• Journal of Convergence for Information Technology
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• v.9 no.5
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• pp.14-20
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• 2019

Energy saving is becoming more and more important issue due to lack of resources and limited nature. However, There is a lack of learning status on energy saving in the school field. In particular, in elementary education on energy saving was not linked to practice, and the educational effect was insufficient. Although various kinds of learning tools are utilized, many successful cases of energy saving game strategy are introduced in overseas industry field, and game design is proposed so that energy related education can be played through games. Because energy conservation can not be effective without practice, learning using games as a tool is expected to be more effective than learning based on knowledge transfer in the classroom. We propose a defense game for energy conservation education by using the mission elements, score acquisition element, time limit element, and character element which are the interesting elements of the game designed in the previous research.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.89-94
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• 2021

Recently, the boundaries between people who produce and consume digital contents disappears due to the massive developments in information and communications technology (ICT) and the rapidly increasing spread of smartphones unlike in the traditional mass media (e.g., newspapers, radios, and TVs). Through the open service platform, the problem perception for each individual remains the same, but the problem solving methods varies as the service types have been diversified. The creation of added value through the growth of the new media platform industry is expected to enrich our lives, but it can also cause severe social side effects. For example, communication problems between social classes due to the information gap have led to generational conflict, and if such problems persist, it can cause national and social losses. Therefore, this paper analyzes the policy efforts to resolve the information gap and the necessity of the legalization of multimedia literary education to maximize the synergy effect through psychological model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.663-673
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• 2021

Normally, allowable mean overtopping discharge is used as a design parameter for coastal structures. The crest elevation of a structure must ensure wave overtopping discharge within acceptable limits for structural safety and the safety of pedestrians, vehicles, operations, and so on. Some researchers have alternatively proposed using the maximum individual wave overtopping volumes as design criteria during a design storm, since these can provide a better design measure than the mean overtopping rate. This study contributes to the knowledge on maximum individual overtopping volumes in Rayleigh-distributed wave conditions. Two-dimensional physical model tests on typical rubble mound structure geometries were performed, and the new measurement method for individual overtopping was adopted. An empirical formula was proposed to predict the maximum individual overtopping volumes based on the mean overtopping rate, and the reduction effects by the armor crest width on the mean wave overtopping discharge were assessed.

• Journal of Internet of Things and Convergence
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• v.8 no.1
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• pp.31-36
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• 2022

As the society progresses to a knowledge economy, global demand is rapidly increasing in many fields of society. In line with this, interest in globalization is also increasing in universities. Accordingly, students who have graduated from universities are making efforts to find employment in Korea, but the barriers to entry for employment are high due to the high specifications and qualifications of domestic companies, so the government, local governments, and universities are putting a lot of effort into global overseas employment. This study is a training course design for the K-MOVE project aimed at employment in Japanese IT companies. To design this curriculum, we conduct a demand survey of recruiting companies and students, and draw a curriculum based on the results. Then, the effective link between regular subjects and K-MOVE education will be described. This study can be a useful resource for education experts planning overseas employment in the Japanese IT field.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.399-408
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• 2022

ERC-20, the standard API for Ethereum token smart contracts, was introduced to ensure compatibility among applications such as wallets and decentralized exchanges. However, many compatibility vulnerability problems have existed because there is no rigorous functional specifications for each API nor conformance review tools for the standard. In this paper, we proposed a new review procedure and a tool to perform the procedure to review if ERC-20 token smart contract programs for the Ethereum blockchain conform to the de facto standards. Based on the knowledge from an analysis on the ERC-20 API functional behavior of the top 100 token smart contract programs in the existing Ethereum blockchain, a new specification for the de facto standard for ERC-20 API was explicitly defined. The new specification enabled us to design a systematic review method for Ethereum smart contract programs. We developed a tool to support this review method and we evaluated a few benchmark programs with the tool.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.1-9
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• 2023

In this paper, we identify the factors that hinder the application of quantum computing technology to solve meaningful real-world problems, and suggest related research trends and directions. To this end, we summarize the basic knowledge of quantum mechanics from the perspective of computer science, which is necessary to understand the difficulties in applying quantum computing technology, and analyze the currently commercialized quantum computers and quantum programming layers from the literature. Through an analysis of the current status and utilization of cloud-based commercial quantum computing services, we identify four factors that currently hinder the practical application of quantum computing: high barriers to entry for quantum computer programming, constraints on noisy intermediate-scale quantum computers, a still-growing open source ecosystem, and difficulties in simulating realistic problem sizes, and suggest trends and directions for related research. In doing so, it is expected to contribute to laying the groundwork for practical applications of quantum computing technology.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.3 no.2
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• pp.67-72
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• 2022

Ecological research relies on the interpretation of large amounts of visual data obtained from extensive wildlife surveys, but such large-scale image interpretation is costly and time-consuming. Using an artificial intelligence (AI) machine learning model, especially convolution neural networks (CNN), it is possible to streamline these manual tasks on image information and to protect wildlife and record and predict behavior. Ecological research using deep-learning-based object recognition technology includes various research purposes such as identifying, detecting, and identifying species of wild animals, and identification of the location of poachers in real-time. These advances in the application of AI technology can enable efficient management of endangered wildlife, animal detection in various environments, and real-time analysis of image information collected by unmanned aerial vehicles. Furthermore, the need for school education and social use on biodiversity and environmental issues using AI is raised. School education and citizen science related to ecological activities using AI technology can enhance environmental awareness, and strengthen more knowledge and problem-solving skills in science and research processes. Under these prospects, in this paper, we compare the results of our early 2013 study, which automatically identified African cichlid fish species using photographic data of them, with the results of reanalysis by CNN deep learning method. By using PyTorch and PyTorch Lightning frameworks, we achieve an accuracy of 82.54% and an F1-score of 0.77 with minimal programming and data preprocessing effort. This is a significant improvement over the previous our machine learning methods, which required heavy feature engineering costs and had 78% accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.37-48
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• 2009

Household service robots should be able to provide their users with a variety of temporal reasoning services. In this paper, we propose an effective way of developing such temporal reasoning services using a domain-independent AI planner. Developing temporal reasoning services with a domain-independent AI planner, we have to address both the knowledge engineering problem of how to represent various real-world temporal constraints in a planning domain definition language, and the system design problem of how to realize the interface between the AI planner and the service consumer. In this paper, we introduce an example scenario and a set of typical temporal constraints for a household service robot, and then present how to represent them in the standard planning domain definition language. We also explain how to implement a service agent based on an AI planner in order to develop and provide new services efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.240-243
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• 2021

Recently, there have been research results of applying Big data and AI technologies to the evaluation and individual learning for education. It is information technology innovations that collect dynamic and complex data, including student personal records, physiological data, learning logs and activities, learning outcomes and outcomes from social media, MOOCs, intelligent tutoring systems, LMSs, sensors, and mobile devices. In addition, e-learning was generated a large amount of learning data in the COVID-19 environment. It is expected that learning analysis and AI technology will be applied to extract meaningful patterns and discover knowledge from this data. On the learner's perspective, it is necessary to identify student learning and emotional behavior patterns and profiles, improve evaluation and evaluation methods, predict individual student learning outcomes or dropout, and research on adaptive systems for personalized support. This study aims to contribute to research in the field of education by researching and classifying machine learning technologies used in anomaly detection and recommendation systems for educational data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.391-397
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• 2009

This research introduces the implementation for cash flow forecasting system in construction company through a case study. The implemented system shows how to develop overall corporate-level and project-level cash flow forecasting model based on a real business process in construction company. It takes 1 year to implement system. The study proposes the way of system design, process of system design, and considerations of implementation in step by step. Moreover, it shows main screen, limitation and reliability of the system. The proposed model is validated accurate, flexible and simple as a result of comparing actual data to forecasting data for 2 years. This system is easy to approach the employee who don't have any financial knowledge. This research is expected to assist to implement system of cash flow forecasting in construction company.