• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.123-126
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• 2011

본 논문에서는 한국형 스마트 앱 저작도구로 미국, 일본, 한국에서 세계특허를 획득한 원더풀소프트의 M-Bizmaker를 이용하여 식품영양학과와 비서행정과 등 비전공자 회사원과 학생이 협력하는 관계에서도 중급수준의 비즈니스 앱 개발이 단기간에 가능하며 최고의 효율성을 검증할 수 있음을 확인하였다. 즉 저작도구인 M-Bizmaker를 이용하면 초중고, 대학, 일반인까지 모든 계층에서 초단기 1일 교육을 통하여 개인의 아이디어와 개성을 살린 앱을 제작할 수 있다는 결론을 도출하였다. 비전공자들이 제작한 스마트 앱의 수준은 본문에서 설명한 것 같이 단체의 일반홍보, 식단관리, 그래프를 이용한 취업현황, 구글맵 연계 주소 관리, 자동전화걸기, 사진 등의 이미지 관리, 친구 찾기와 같이 구성원을 등록하여 용이하게 관리할 수 있고, 설문조사도 쉽게 할 수 있다. 현재 세계 모바일 시장은 애플, 구글 등 미국시장이 세계시장을 선도하고 있는 상황으로 구글의 앱인벤터, 애플의 앱쿠커 등의 저작도구가 베타버젼으로 존재하지만 세계특허 수준의 한국형 저작도구인 비즈니스용 전문개발인 M-Bizmaker와는 기술수준에서 많은 격차가 존재하므로 국가적 차원에서 앱 저작도구 기술개발 인력 양성에 투자한다면 다가오는 미래에는 우리나라가 세계시장을 선도할 수 있을 것이라 사려 된다.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.105-113
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• 2019

The purpose of this study is to analyze cyber security risk modeling of critical infrastructure, draw out limitations and improvement measures. This paper analyzed cyber security risk modeling of national critical infrastructure like as electricity sector, nuclear power plant, SCADA. This paper analyzed the 26 precedent research cases of risk modeling in electricity sector, nuclear power plant, SCADA. The latest Critical Infrastructure is digitalized and has a windows operating system. Critical Infrastructure should be operated at all times, it is not possible to patch a vulnerability even though find vulnerability. This paper suggest the advanced cyber security modeling characteristic during the life cycle of the critical infrastructure and can be prevented.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.673-681
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• 2021

This study is a case study of artificial intelligence education subjects in the graduate school of education. The main educational contents consisted of understanding and practice of machine learning, data analysis, actual artificial intelligence using Entries, artificial intelligence and physical computing. As a result of the survey on the educational effect after the application of the curriculum, it was found that the students preferred the use of the Entry AI block and the use of the Blacksmith board as a physical computing tool as the priority applied to the elementary education field. In addition, the data analysis area is effective in linking math data and graph education. As a physical computing tool, Husky Lens is useful for scalability by using image processing functions for self-driving car maker education. Suggestions for desirable AI education include training courses by level and reinforcement of data collection and analysis education.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.201-210
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• 2021

This paper introduces the futsal video analysis system consisting of an analysis program using object tracking technology and a web server that visualizes and provides analyzed data. In this paper, small and medium-sized organizations and amateur players are unable to provide game analysis services, so they propose a system that can solve this problem through this paper. Existing analytical systems use special devices or high-cost cameras, making them difficult for users to use. Thus, in this paper, a system is designed and developed to analyze the competitors' competitions and visualize the data using flat images only. Track an object and calculate the accumulated values to obtain the distance per pixel of the object and extract speed-related data and distance-based data based on it. Converts extracted data to graphs and images through a visualization library, making it convenient to use through web pages. Through this analysis system, we improve the problems of the existing analysis system and make data-based scientific and efficient analysis available.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.293-297
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• 2021

This paper applies the natural history contents of the Science Museum and combines the Gestalt theory to develop the butterfly arrangement structure of the butterfly sample box and the butterfly sample information necessary for the sample box as AR (Augmented Reality). Existing analog sample information is expressed as digital information by combining place, butterfly information, and graph to maximize the effect of digital diorama exhibition. Digital natural history information is increased or decreased, and an environment optimized for real samples and suitability is constructed, and natural history contents are arranged in the principles of collectiveness, closure, simplicity, and continuity using the Gestalt visual perception principle to increase attention and increase the attention of butterfly collection information. Was applied as an application plan of AR.

• Journal of Convergence for Information Technology
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• v.11 no.7
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• pp.31-38
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• 2021

In this paper, in order to obtain the optimization of the RNN model used for sentiment analysis, the correlation of each model was studied by observing the trend of loss and accuracy according to hyperparameter tuning. As a research method, after configuring the hidden layer with LSTM and the embedding layer that are most optimized to process sequential data, the loss and accuracy of each model were measured by tuning the unit, batch-size, and embedding size of the LSTM. As a result of the measurement, the loss was 41.9% and the accuracy was 11.4%, and the trend of the optimization model showed a consistently stable graph, confirming that the tuning of the hyperparameter had a profound effect on the model. In addition, it was confirmed that the decision of the embedding size among the three hyperparameters had the greatest influence on the model. In the future, this research will be continued, and research on an algorithm that allows the model to directly find the optimal hyperparameter will continue.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.135-144
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• 2020

In graph theory, the least-cost path is discovered by searching the shortest path between a start node and destination node. The least cost is calculated as a one-dimensional value that represents the difference in distance or price between two nodes, and the nodes and edges that comprise the lowest sum of costs between the linked nodes is the shortest path. However, it is difficult to determine the shortest path if each node has multiple attributes because the number of cost types that can appear is equal to the number of attributes. In this paper, a shortest path search scheme is proposed that considers multiple attributes using the Euclidean distance to satisfy various user requirements. In simulation, we discovered that the shortest path calculated using one-dimensional values differs from that calculated using the Euclidean distance for two-dimensional attributes. The user's preferences are reflected in multi attributes and it was different from one-dimensional attribute. Consequently, user requirements could be satisfied simultaneously by considering multiple attributes.

• Journal of the Korean Chemical Society
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• v.66 no.3
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• pp.243-250
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• 2022

The purpose of this study was to investigate the inscription of North Korean Higher-Level Middle School 1 chemistry textbooks in the era of North Korean leader Kim Jong-un to understand North Korean chemistry education. The types and functions of inscription for each unit of the North Korean Higher-Level Middle School 1 Chemistry textbook were analyzed and compared with the inscription of the 'Chemistry I' textbook in South Korea. Inscriptions were analyzed by constructing an analysis frame based on previous studies. The analysis results were as follows. First, as for the types of inscription used in North Korean textbooks, photographs and illustrations were used the most, and graphs were used the least. Second, the functions of inscription used in North Korean textbooks had many exploratory and exemplary functions, and decorative functions were used the least. Third, there was no significant difference in type and function of textbook inscriptions from North and South Korea. The results of this study may be helpful in understanding North Korean chemistry education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.51-58
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• 2021

Microservices are not only developed independently, but can also be run and deployed independently, ensuring more flexible scaling and efficient collaboration in a cloud computing environment. This impact has led to a surge in migrating to microservices-oriented application environments in recent years. In order to introduce microservices, the problem of identifying microservice units in a single application built with a single architecture must first be solved. In this paper, we propose an algorithm-based approach to identify microservices from legacy systems. A graph is generated using the meta-information of the legacy code, and a microservice candidate is extracted by applying a clustering algorithm. Modularization quality is evaluated using metrics for the extracted microservice candidates. In addition, in order to validate the proposed method, candidate services are derived using codes of open software that are widely used for benchmarking, and the level of modularity is evaluated using metrics. It can be identified as a smaller unit of microservice, and as a result, the module quality has improved.