• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.2
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• pp.189-196
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• 2010

Spatial information and smart phone technology have made innovative improvement of daily life. Spatial and geographic information are in practice for various applications. Especially, spatial information along with information and telecommunication technology could create new contents for providing services for convenient daily life. Spatial information technology, recently, is not only for acquiring location and attribute data but also providing tools to extract information and knowledge systematically for decision making. Various indoor applications have emerged in accordance with demands on daily GIS(Geographic information system). This paper aims for applying spatial information technology to support decision-making in shopping. The main contents include product database, optimal path search, shopping time expectation, automatic housekeeping book generation and analysis. Especially for foods, function to analyze information of the nutrition facts could help to improve dietary pattern and well-being. In addition, this system is expected to provide information for preventing overconsumption and impulse purchase could help economical and effective purchase pattern by analyzing propensity to consume.

• Korean Journal of Construction Engineering and Management
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• v.8 no.3
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• pp.142-149
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• 2007

A ubiquitous environment in construction should be developed integrating hardware and software systems. The objective of this paper is to study the feasibility of applying the RFID technology to the concrete pour process, and improve the effectiveness of data exchange A pilot system of u-CPS (Ubiquitous Concrete Pour System) has been developed to test the feasibility. The pilot can automatically generate the data for concrete pour work such as departure time, arrival time, concrete pour time. Construction managers can keep track of the progress of concrete pour work using the information. A case study was done for a building construction using the pilot system, the result of which demonstrated that the RFID-base system can help improve the effectiveness of data communication during the concrete pour process.

• Korean Journal of Food Science and Technology
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• v.35 no.4
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• pp.684-689
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• 2003

In previous paper, we isolated the bacteria, Bacillus subtilis JM-3, with proteolytic and fibrinolytic activity for candidate microorganisms that have rapid fermenting and physiological functions from anchovy sauce. This study was carried out to search physiological functions of Bacillus subtilis JM-3, such as antimicrobial, antioxidative, antimutagenic, angiotensin-converting enzyme inhibition, and anticarcinogenic activity in vitro. The cell free culture of Bacillus subtilis JM-3 showed strong antibacterial activity against Listeria monocytogenes, antioxidative activity with 87% of inhibition rate against linoleic acid, 50% of antimutagenic activity against N-nitrosodimethylamine and N-nitrosomorpholine, and 88.9% of growth inhibition rate against SNU-1 cell line (stomach cancer cell of human). However, Bacillus subtilis JM-3 did not show angiotensin-converting enzyme inhibition activity.

• Membrane Journal
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• v.27 no.6
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• pp.477-486
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• 2017

Hydrogen is one of energy storage systems, which could be transfer from electric energy to chemical energy or from chemical energy to electric energy, and is as an energy carrier. Water electrolysis is being investigating as one of the hydrogen production methods. Recently, water electrolysis receive attention for the element technology in PTG (power to gas) and PTL (power to liquid) system. In this paper, it was explained the principle and type for the water electrolysis, and recent research review for the alkaline water electrolysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.774-779
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• 2012

Brain-computer interface based on motor imagery is a system that transforms a subject's intention into a control signal by classifying EEG signals obtained from the imagination of movement of a subject's limbs. For the new paradigm, we do not know which positions are activated or not. A simple approach is to use as many channels as possible. The problem is that using many channels causes other problems. When applying a common spatial pattern (CSP), which is an EEG extraction method, many channels cause an overfit problem, in addition there is difficulty using this technique for medical analysis. To overcome these problems, we suggest a binary particle swarm optimization with channel impact factor in order to select channels close to the most important channels as channel selection method. This paper examines whether or not channel impact factor can improve accuracy by Support Vector Machine(SVM).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.79-82
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• 2019

This study aims to design and implement automated SEO tools that has applied the artificial intelligence techniques for search engine optimization (SEO; Search Engine Optimization). Traditional Search Engine Optimization (SEO) on-page optimization show limitations that rely only on knowledge of webpage administrators. Thereby, this paper proposes the metadata generation system. It introduces three approaches for recommending metadata; i) Downloading the metadata which is the top of webpage ii) Generating terms which is high relevance by using bi-directional Long Short Term Memory (LSTM) based on attention; iii) Learning through the Generative Adversarial Network (GAN) to enhance overall performance. It is expected to be useful as an optimizing tool that can be evaluated and improve the online marketing processes.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.59-66
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• 2022

In this paper, by applying IoT technology to the Ultimate game, which is one of the games using Flyingdisc, the process of the game is traced based on the players and the flyingdisc, and a comprehensive relationship analysis between players is performed on the results of the game. A WiFi module with built-in GPS is attached in the players and flyingdisc. The player's ID, latitude/longitude values received from GPS and time are stored in the database in realtime during the game. Process informations of the game is also stored in the database at the same time using mobile Ultimate game App. Based on this informations after the game is over, we developed a system that can perform comprehensive analysis of the game contents. By using the informations stored in the database, the player-based game process and the flyingdisc-based scoring process are visualized in the virtual playground. Various game result informations for players are graphically analyzed using Python.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.513-520
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• 2021

Recently, research on edutech, which combines education and technology in the e-learning field called learning, education and training, has been actively conducted, but it is still insufficient to collect and utilize data tailored to individual learners based on learning activity data that can be automatically collected from digital devices. Therefore, this study attempts to detect questions in textbooks or problem papers using artificial intelligence computer vision technology that plays the same role as human eyes. The textbook or questionnaire item detection model proposed in this study can help collect, store, and analyze offline learning activity data in connection with intelligent education services without digital conversion of textbooks or questionnaires to help learners provide personalized learning services even in offline learning.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Journal of the Korea Institute of Building Construction
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• v.17 no.6
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• pp.545-557
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• 2017

The study is about the efficient alternative to concrete surface in the field of visual inspection technology for deteriorated infrastructure. By combining industrial drones and deep learning based image analysis techniques with traditional visual inspection and research, we tried to reduce manpowers, time requirements and costs, and to overcome the height and dome structures. On board device mounted on drones is consisting of a high resolution camera for detecting cracks of more than 0.3 mm, a lidar sensor and a embeded image processor module. It was mounted on an industrial drones, took sample images of damage from the site specimen through automatic flight navigation. In addition, the damege parts of the site specimen was used to measure not only the width and length of cracks but white rust also, and tried up compare them with the final image analysis detected results. Using the image analysis techniques, the damages of 54ea sample images were analyzed by the segmentation - feature extraction - decision making process, and extracted the analysis parameters using supervised mode of the deep learning platform. The image analysis of newly added non-supervised 60ea image samples was performed based on the extracted parameters. The result presented in 90.5 % of the damage detection rate.