• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.43-50
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• 2019

Block-chain enjoys technical advantages such as "robust security," owing to the structural characteristic that forgery is impossible, decentralization through sharing the ledger between participants, and the hyper-connectivity connecting Internet of Things, robots, and Artificial Intelligence. As a result, public organizations have highly positive attitudes toward the adoption of technology using block-chain, and the design of university information services is no exception. Universities are also considering the application of block-chain technology to foundations that implement various information services within a university. Through case studies of block-chain applications across various industries, this study designs an empirical model of an integrated information service platform that integrates information systems in a university. A basic road map of university information services is constructed based on block-chain technology, from planning to the actual service design stage. Furthermore, an actual empirical model of an integrated information service in a university is designed based on block-chain by applying this framework.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1749-1760
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• 2022

In modern society, human and social damages caused by natural disasters and frequent disaster accidents have been increased year by year. Prompt access to dangerous disaster sites that are inaccessible or inaccessible using state-of-the-art Earth observation equipment such as satellites, drones, and survey robots, and timely collection and analysis of meaningful disaster information. It can play an important role in protecting people's property and life throughout the entire disaster management cycle, such as responding to disaster sites and establishing mid-to long-term recovery plans. This special issue introduces the National Disaster Management Research Institute (NDMI)'s disaster management technology that utilizes various Earth observation platforms, such as mobile survey vehicles equipped with close-range disaster site survey sensors, drones, and survey robots, as well as satellite technology, which is a tool of remote earth observation. Major research achievements include detection of damage from water disasters using Google Earth Engine, mid- and long-term time series observation, detection of reservoir water bodies using Sentinel-1 Synthetic Aperture Radar (SAR) images and artificial intelligence, analysis of resident movement patterns in case of forest fire disasters, and data analysis of disaster safety research. Efficient integrated management and utilization plan research results are summarized. In addition, research results on scientific investigation activities on the causes of disasters using drones and survey robots during the investigation of inaccessible and dangerous disaster sites were described.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.857-862
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• 2021

Recently, rapid climate change has had a significant impact on the bee ecosystem. The decrease in the number of bees and the change in the flowering period have a huge impact on the harvesting of beekeepers. Accordingly, attention is focused on smart beekeeping, which introduces IoT technology to beekeeping. According to the characteristics of beekeeping, it is impossible to continuously observe the beehive in the hive with the naked eye, and the condition of the hive is mostly dependent on knowledge from experience. Although a system that can measure partly through sensors such as temperature/humidity change inside the hive and measurement of the amount of CO2 is applied, there is no research on measuring the movement path and amount of movement of bees inside the beehive. Part of the migration of honeybees inside the hive can provide basic information to predict the most important cleavage time in beekeeping. In this study, we propose a device that detects the movement path of bees and measures and records data entering and exiting the hive in real time. The device proposed in this study was developed according to the honeycomb standard of the existing beehive so that beekeeping farms could use it. The development method used a photodetector that can detect the movement of bees to configure 16 movement paths and to detect the movement of bees in real time. If the measured honeybee movement status is utilized, the problem of directly observing the colony with the naked eye in order not to miss the swarming time can be solved.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1074-1081
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• 2021

Nitrous oxide (N₂O) is one of the six major greenhouse gases and is known to produce a greenhouse ef ect by absorbing infrared radiation in the atmosphere. In particular, its global warming potential (GWP) is 310 times higher than that of CO₂, making N₂O a global concern. Accordingly, strong environmental regulations are being proposed. N₂O reduction technology can be classified into concentration recovery, catalytic decomposition, and pyrolysis according to physical methods. This study intends to provide information on temperature conditions and reaction time required to reduce nitrogen oxides with cost. The high-temperature ranges selected for pyrolysis conditions were calculated at intervals of 100 K from 1073 K to 1373 K. Under temperatures of 1073 K and 1173 K, the N₂O reduction rate and nitrogen monoxide concentration were observed to be proportional to the residence time, and for 1273 K, the N₂O reduction rate decreased due to generation of the reverse reaction as the residence time increased. Particularly for 1373 K, the positive and reverse reactions for all residence times reached chemical equilibrium, resulting in a rather reduced reaction progression to N₂O reduction.

• The Mathematical Education
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• v.62 no.2
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• pp.289-302
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• 2023

In today's digital information society, student knowledge and skills to analyze big data and make informed decisions have become an important goal of school mathematics. Integrating big data statistical projects with digital technologies in high school <Artificial Intelligence> mathematics courses has the potential to provide students with a learning experience of high impact that can develop these essential skills. This paper proposes a set of guidelines for designing effective big data statistical project-based tasks and evaluates the tasks in the artificial intelligence mathematics textbook against these criteria. The proposed guidelines recommend that projects should: (1) align knowledge and skills with the national school mathematics curriculum; (2) use preprocessed massive datasets; (3) employ data scientists' problem-solving methods; (4) encourage decision-making; (5) leverage technological tools; and (6) promote collaborative learning. The findings indicate that few textbooks fully align with these guidelines, with most failing to incorporate elements corresponding to Guideline 2 in their project tasks. In addition, most tasks in the textbooks overlook or omit data preprocessing, either by using smaller datasets or by using big data without any form of preprocessing. This can potentially result in misconceptions among students regarding the nature of big data. Furthermore, this paper discusses the relevant mathematical knowledge and skills necessary for artificial intelligence, as well as the potential benefits and pedagogical considerations associated with integrating technology into big data tasks. This research sheds light on teaching mathematical concepts with machine learning algorithms and the effective use of technology tools in big data education.

• Land and Housing Review
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• v.14 no.3
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• pp.125-135
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• 2023

In South Korea, it has been increased the necessity of supplying housing services to meet the needs and desires of various residents by reflecting various demographic and social changes. In particular, various smart device has been widely utilized in South Korea and the smart technologies, such as artificial intelligence and the Internet of Things has been developed rapidly. These smart technologies could support smart housing that allows residents to easily and comfortably employ residential services. However, it is necessary to improve the awareness of users in order to spread the smart housing residential services connected to smart technologies. For this reason, this study observed changes in users' perceptions of smart housing residential service technology using Living Lab. As a result, after experiencing the Living Lab, users' awareness of smart housing housing service increased, and it was observed that the preferred housing service technology was more detailed than before the Living Lab experience. This study shows that it is important to raise users' awareness for the dissemination of smart housing residential service technology, and that Living Lab can be an effective means for this purpose.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Convergence Security Journal
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• v.22 no.2
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• pp.131-141
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• 2022

Future battlefield domains are expanding to ground, sea, air, space, and cyber, so future military operations are expected to be carried out simultaneously and complexly in various battlefield domains. In addition, the application of convergence technologies that create innovations in all fields of economy, society, and defense, such as artificial intelligence, IoT, and big data, is being promoted. However, since the current Korean military C4I system manages warfighting function DBs in one DB server, the efficiency of combat performance is reduced utilization and distribution speed of data and operation response time. To solve this problem, research is needed on how to apply the 4th industrial revolution technologies such as AI, IoT, 5G, big data, and cloud to the Korean military C4I system, but research on this is insufficient. Therefore, this paper analyzes the problems of the current Korean military C4I system and proposes to apply the 4th industrial revolution technology in terms of operational mission, network and data link, computing environment, cyber operation, interoperability and interlocking capabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.505-508
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• 2022

Artificial intelligence itself has the value of advancing technology, and it is used in various industrial fields to enhance the added value of products and services produced in various industries. Therefore, regulations and policies related to artificial intelligence should be considered from a broader perspective. However, researchers have different understandings, and there is no agreement on how to regulate artificial intelligence. Therefore, we will examine the direction of government regulation on artificial intelligence technology in an exploratory manner. First, accountability, transparency, stability, and fairness are derived as the goals of artificial intelligence regulation, and the system itself, development process, and utilization process are set as the scope of regulation, and users and developers are subject to regulation. The academic significance of this study can be seen as analyzing the current level of artificial intelligence technology and laying the foundation for consistent discussions on artificial intelligence regulations in the future. Considering the life cycle from AI development to application, what is important is the balance of promotion policies to promote the artificial intelligence industry and regulatory policies to respond to the resulting risks. The goal of law related to artificial intelligence is to establish a system in which artificial intelligence can be accommodated in a positive direction to all participants, including developers, companies, and users.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.5
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• pp.44-56
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• 2023

This research explores the enhancement of park operation and management by analyzing the changing demands of park users. While traditional methods depended on surveys, there has been a recent shift towards utilizing social media data to understand park usage trends. Notably, most research has focused on text data from social media, overlooking the valuable insights from image data. Addressing this gap, our study introduces a novel method of assessing park usage using social media image data and then applies it to actual city park evaluations. A unique image analysis tool, built on Visual Question Answering (VQA) deep learning technology, was developed. This tool revealed specific city park details such as user demographics, behaviors, and locations. Our findings highlight three main points: (1) The VQA-based image analysis tool's validity was proven by matching its results with traditional text analysis outcomes. (2) VQA deep learning technology offers insights like gender, age, and usage time, which aren't accessible from text analysis alone. (3) Using VQA, we derived operational and management strategies for city parks. In conclusion, our VQA-based method offers significant methodological advancements for future park usage studies.