• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.701-702
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• 2013

전국 50여개의 AI(Artificial Insemination)센터는 국내 양돈산업 인공수정 기술을 개발하고 보급하는 중추적인 역할을 수행하고 있다. 이에 반해 AI센터의 숫자 규모는 전국적으로 매우 제한되어 있어, AI센터의 운영 및 AI 기술에 대한 정보관리는 각 센터별 독자적인 운영시스템으로 관리되어 상호 정보융합을 통한 양돈산업 발전에 활용되는 사례가 매우 적다. 또한 개별 AI센터에서 관리하고 있는 소비자들의 지역분포도가 매우 폭넓어 실시간으로 수요자에 대한 판매 관리정보를 제공함에 있어 그 한계를 가지고 있다. 이에 본 논문에서는 전국의 AI센터 관리운영에 통합적이고 효율성을 지원할 수 있는 모바일 웹기반 개선된 AI PigMoS(Pig Monitoring System, PigMoS) 시스템을 제안하고 구현하였다. 본 논문에서 제안한 모바일 웹기반 개선된 AI PigMoS 시스템은 이동성, 실시간 정보서비스 등에 해당되는 시스템 모듈을 모바일 웹을 기반으로 구현하여 개별 AI센터에서 운영할 수 있게 하였다. 이에 본 논문에서는 기존의 AI PigMoS 시스템을 개선하여 재구축하였으며, 이동성, 실시간 정보서비스 등이 필요한 모듈을 중심으로 모바일 기능을 설계하고 구현하여, 원거리 소비자들에게 실시간으로 생성된 AI정보를 제공하여 AI센터의 정보관리 효율성과 경쟁력 향상을 높일 것으로 기대한다.

• Journal of Information Technology Services
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• v.22 no.6
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• pp.17-35
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• 2023

This study investigated how helpful the use of generative AI such as ChatGPT is in conducting engaged learning at each university. In this study, based on the experiences of users using generative AI technology, we analyzed the relationship between usability and ease in consideration of the characteristics of learners, and examined whether there is an intention to continue using generative AI technology in the future. In this study, in order to verify the factors affecting the intention to use ChatGPT technology in order to solve the problems given in the participating classes, we examined previous papers based on the Technology Acceptance Model (TAM) and the Information System Success Model (IS), extracted the factors affecting the intention of ChatGPT technology, and presented the research model and hypothesis. Empirical research on the continuous use of generative AI in participatory learning using ChatGPT was conducted to determine whether it is suitable for long-term and continuous use in the educational environment, and whether it is sustainable by examining the intention of learners to continue using it. First, user satisfaction was positively related to the intention to continue using generative AI technology. Second, if the user experience has a great influence on the intention to continue using ChatGPT technology, and users gain experiences such as usefulness, interest, and effective response in the process of using the technology, the evaluation of the technology is positively formed and the intention to continue using it is high. Third, the ease of use of the technology also showed that it was intended to be used continuously when an environment was provided in which users could easily and conveniently utilize generative AI technology.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.21-29
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• 2024

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the "drone" keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI's power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.428-434
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• 2020

Recently, due to the development of ICT technology, changes to the convergence service platform of information systems are accelerating. Convergence services expanded to cyber systems with 5G communication, IoT, AI, and cloud are being reflected in the real world. However, the field of cybersecurity audit for responding to cyber attacks and security threats and strengthening security technology is insufficient. In this paper, we analyze the international standard analysis of information security management system, security audit analysis and security of related systems according to the expansion of 5G communication, IoT, AI, Cloud based information system security. In addition, we design and study cybersecurity audit checklists and contents for expanding security according to cyber attack and security threat of information system. This study will be used as the basic data for audit methods and audit contents for coping with cyber attacks and security threats by expanding convergence services of 5G, IoT, AI, and Cloud based systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.639-641
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• 2022

With the increasing of aging population, a lot of researches on monitoring systems for solitary senior citizens are under study. In general, a monitoring system provides a monitoring service by computing the information of vision, sensors, and measurement values on a server. Design considering data security is essential because a risk of data leakage exists in the structure of the system employing the server. In this paper, we propose a intelligent monitoring system for solitary senior citizens with vision-based security architecture. The proposed system protects privacy by ensuring high security through an architecture that blocks communication between a camera module and a server by employing an edge AI module. The edge AI module was designed with Verilog HDL and verified by implementing on a Field Programmable Gate Array (FPGA). We tested our proposed system on 5,144 frame data and demonstrated that a dangerous detection signal is generated correctly when human motion is not detected for a certain period.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.2
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• pp.1-9
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• 2023

The purpose of this study is to derive the need to improve the test and evaluation(T&E) performance system of the weapon systems to which advanced science and technology is applied, evaluate priorities, and present development plans. T&E of Al-based weapon systems through a literature research and case analysis on changes in the T&E environment for weapon system, 11 detailed evaluation items were derived from the in terms of the T&E system, structure, and technology. Al-based weapon system test evaluation should be performed in parallel with data-based performance evaluation and actual T&E, and performance measurement using a separate T&E data set is required for AI models performance evaluation. As a result of analyzing the importance of T&E through AHP analysis, the order of T&E system-technology-structure was evaluated, and the priority of detailed evaluation items was evaluated in the order of T&E result judgment-T&E organization and expert training-scientific T&E. For evaluation items with high priority, measures to improve the T&E performance system were presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.951-952
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• 2013

국내 양돈분야에서의 AI(Artificial Insemination)센터는 인공수정 기술의 개발과 보급과 관하여서는 중추적인 역할을 수행하고 있다. 그러나 현재 전국AI센터에서 사용하고 있는 정보관리 시스템은 독립적이고 운영체제에 의존적인 형태로 운영되고 있다. 따라서 현재 전국AI센터 정보관리 체계는 실시간으로 정보관리 시스템의 접근제한과 모바일 서비스 등의 분야에서 그 분명한 한계를 가진다. 이에 본 논문에서는 유무선 통합(FMC) AI PigMoS(Pig Monitoring System, PigMoS) 시스템을 제안하고 구현하였다. 본 논문에서 제안한 FMC AI PigMoS 시스템은 이동성, 실시간 정보관리 등을 지원할 수 있도록 인터넷과 모바일에서 운영할 수 있도록 구현 하였다. 구현된 FMC AI PigMoS 시스템은 이동성과 실시간 정보관리 등에 필요한 모듈 중심으로 설계하고 구현하였다. 이는 원거리 소비자들에게 각 AI센터에서 생성된 AI정보를 실시간으로 제공하여 개별AI센터의 경쟁력 향상을 높일 것으로 기대한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.4
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• pp.372-380
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• 2022

This study proposes a distributed parallel processing system, called the Fast Analysis System for remote sensing daTa(FAST), for large-scale satellite image processing and analysis. FAST is a system that designs jobs in vertices and sequences, and distributes and processes them simultaneously. FAST manages data based on the Hadoop Distributed File System, controls entire jobs based on Apache Spark, and performs tasks in parallel in multiple slave nodes based on a docker container design. FAST enables the high-performance processing of progressively accumulated large-volume satellite images. Because the unit task is performed based on Docker, it is possible to reuse existing source codes for designing and implementing unit tasks. Additionally, the system is robust against software/hardware faults. To prove the capability of the proposed system, we performed an experiment to generate the original satellite images as ortho-images, which is a pre-processing step for all image analyses. In the experiment, when FAST was configured with eight slave nodes, it was found that the processing of a satellite image took less than 30 sec. Through these results, we proved the suitability and practical applicability of the FAST design.

• The Journal of Korean Institute of Information Technology
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• v.17 no.12
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• pp.125-134
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• 2019

As the limitations of the passive recognition domain, which is not guaranteed transparency of the operation process, AI technology has a vulnerability that depends on the data. Human error is inherent because raw data for artificial intelligence learning must be processed and inspected manually to secure data quality for the advancement of AI learning. In this study, we examine the necessity of learning data management before machine learning by analyzing inaccurate cases of AI learning data and cyber security attack method through the approach from cyber security perspective. In order to verify the learning data integrity, this paper presents the direction of data-preserving artificial intelligence system, a blockchain-based learning data environment model. The proposed method is expected to prevent the threats such as cyber attack and data corruption in providing and using data in the open network for data processing and raw data collection.

• Journal of Advanced Navigation Technology
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• v.28 no.5
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• pp.650-656
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• 2024

This study proposes an AI-based image restoration technique to reduce image distortion caused by lighting and noise in nighttime environments and improve the performance of infrared detection systems. A synthetic image dataset was constructed using visible light images under various lighting conditions and ISO settings, and deep learning models (AutoEncoder and U-Net) were trained to assess image restoration performance. Experimental results show that the Multi-ISO model (9-channel) outperforms the Single-ISO model (3-channel), especially when utilizing input data with multiple ISO values. This study demonstrates that AI models can be effectively trained using synthetic data, even when real data collection is challenging, and can be applied to image restoration tasks. These findings are expected to contribute to enhancing the performance of optical detection systems through AI-based technology.