• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.142-147
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• 2021

In this paper, we propose an intelligent research fund management system that applies artificial intelligence technology to an integrated research fund management system. By defining research fund management rules as work rules, a detection model learned using deep learning is designed, through which the disapproval status is presented for each research fund usage history. The disapproval detection system of the RCMS implemented in this study predicts whether the newly registered usage details are recognized or disapproved using an artificial intelligence model designed based on the use of an 8.87 million research fund registered in the RCMS. In addition, the item-detail recommendation system described herein presents the usage details according to the usage history item newly registered by the artificial intelligence model through a correlation between the research cost usage details and the item itself. The accuracy of the recommendation was shown to be 97.21%.

• Journal of Information Technology Applications and Management
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• 제22권2호
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• pp.113-122
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• 2015

Collective intelligence can be an influential factor of decision-making based on collaboration and information exchange between individuals. Our study explores whether collective intelligence can mitigate the loss aversion effect, bias and error in human judgment, and collective intelligence in online communities can reduce the loss aversion effect. Our community settings display both individual-level and group-level loss aversion effect, investigate effective collective intelligence characteristics like investment commitment, participant experience. Using a multi-method approach our research comprises a web-based experiment with 100 participants investing 3 situations from a real-world community, data from a survey measuring loss aversion behavior of participants. The results suggest the loss aversion effect mitigates under the online-circumstance. Overall, our results suggest that, while collective intelligence mitigates the loss aversion effect, participants do not transfer these results to other settings.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.421-426
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• 2004

Analyzing adaptive possibilities of agents in multi-agents system, we have discovered new aspects of ambient intelligence in distributed modular systems using intelligent building blocks (I-BLOCKS) [1]. This paper describes early scientific researches related to technical design, applicable experiments and evaluation of adaptive processing and information interaction among I-BLOCKS allowing users to easily develop ambient intelligence applications. The processing technology presented in this paper is embedded inside each DUPLO1 brick by microprocessor as well as selected sensors and actuators in addition. Behaviors of an I-BLOCKS modular structure are defined by the internal processing functionality of each I-Blocks in such structure and communication capacities between I-BLOCKS. Users of the I-BLOCKS system can do 'programming by building' and thereby create specific functionalities of a modular structure of intelligent artefacts without the need to learn and use traditional programming language. From investigating different effects of modem artificial intelligence, I-BLOCKS we have developed might possibly contain potential possibilities for developing applications in ambient intelligence (AmI) environments. To illustrate these possibilities, the paper presents a range of different experimental scenarios in which I-BLOCKS have been used to set-up reconfigurable modular systems. The paper also reports briefly about earlier experiments of I-BLOCKS in different research fields, allowing users to construct AmI applications by a just defined concept of modular artefacts [3].

• Journal of Information Science Theory and Practice
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• 제12권3호
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• pp.49-62
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• 2024

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.229-230
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• 2022

With the development of digital technology, construction companies at home and abroad are in the process of computerizing work and site information for the purpose of improving work efficiency. To this end, various technologies such as BIM, digital twin, and AI-based safety management have been developed, but the accuracy and completeness of the related technologies are insufficient to be applied to the field. In this paper, the learning data that has undergone a pre-processing process optimized for recognition of construction information based on structural members is trained on an existing artificial intelligence model to improve recognition accuracy and evaluate its effectiveness. The artificial intelligence model optimized for the structural member created through this study will be used as a base technology for the technology that needs to confirm the safety of the structure in the future.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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• pp.57-60
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• 2021

본 논문에서는 기지 설비 중 주요 회전기기인 펌프의 이상탐지 알고리즘을 제안한다. 현재 인공지능을 활용하여 생산현장을 혁신하고자 하는 시도가 진행되고 있으나 외산 솔루션에 대한 의존도가 높은 것에 비해 국내 실정에 맞지 않는 경우가 많다. 이에 따라, 선행 연구를 통해 국내 실정에 맞는 인공지능 기술 도입이 필요하다. 본 연구에서는 VAE(Variational Auto Encoder) 알고리즘을 활용해 회전기기의 고장을 진단하는 알고리즘을 개발하였다. 본 연구 수행을 통한 회전기기의 고장 예지·진단 시스템 개발로 설비의 이상 징후 포착, 부품의 교환 시기 등 보수 일정을 예측하고 최종적으로 이를 통한 설비 가동의 효율 증대와 에너지 비용 감소의 효과를 기대한다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2023년도 제68차 하계학술대회논문집 31권2호
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• pp.13-14
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• 2023

집중 안전 점검의 대상인 노후 건축물에서 균열은 건물의 안전도를 점검할 수 있는 지표이다. 안전 점검에 드론을 활용하면서 고해상도의 드론 기반 균열 이미지 수집이 가능해졌고, 육안이 아닌 AI기반으로 균열을 탐지, 구획화할 수 있다. 본 연구에서는 주변 사물과 배경에 구애받지 않고 안전 점검이 가능한 구획화 알고리즘을 제안한다. METU와 POC데이터셋을 가공하여 데이터셋을 구축하고, 이를 바탕으로 ResNet50을 통해 균열과 유사한 배경을 분류하였으며, 균열 구획화 모델을 선정하여 DesneNet201-UNet++으로 mIoU 82.27%를 달성하였다. 본 연구는 노후 건축물 안전 점검에 필요한 균열 폭 추정에 도움이 될 것으로 기대된다.

• 시큐리티연구
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• 제34호
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• pp.259-278
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• 2013

21세기 정보통신기술의 발달과 급격한 인터넷의 확산으로 비밀 출처정보에서만 수집이 가능했던 정보(Information)가 인터넷을 통해 쉽게 검색이 가능하게 되었다. 공개정보(Open Source)가 폭발적으로 증가하면서 정보수집활동에 큰 변화가 일어나고 있으며, 이러한 변화는 국가정보기관에서의 정보수집활동에도 영향을 미치고 있다. 공개출처정보(Open Source Intelligence: OSINT)는 이렇게 넘쳐나는 정보를 효과적으로 처리하고 분석하기위해 등장하였다. OSINT는 주로 9.11테러 이후에 빠르게 적용되었으며, 국가정보기관에서는 이와 관련된 연구와 기술개발에도 적극 참여하고 있다. 이렇게 서구국가에서는 OSINT의 중요성을 인지하고 공개정보(Open Source)를 분석하는 일이 최우선 순위로 떠오르고 있다. 하지만 국내에서는 공개정보(Open Source)의 중요성에 대한 인식이 미흡한 실정이다. 본 연구에서는 OSINT를 소개하고 중요성을 제고하는 것을 목적으로 하였다. 감당하기 힘들 정도로 늘어나는 많은 양의 공개정보(Open Source)를 효과적으로 이용하기 위하여 OSINT의 운용사례와 방법을 소개하고 중요성을 논의하였다. 이는 국가안보를 위협하는 테러뿐만 아니라 각종 범죄를 효과적으로 대응하기위한 방안이기도 하다.

• 디지털산업정보학회논문지
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• 제15권3호
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• pp.55-67
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• 2019

In this study, I researched whether consumers would adopt artificial intelligence speakers. A study was conducted on the motivations that arise when consumers want to use artificial intelligence speakers. Key motivational factors include needs and wants, and emotion is also included in the hypothesis as influencing the intended use. These factors have modeled the motivational process in which consumers want to use artificial intelligence speakers. In the empirical study, the survey was conducted and the survey data was analyzed by applying the method of analysis of the structural equation model. As a result of empirical research, consumers' expectations to meet their general needs for artificial intelligence speakers affected their expectations to meet their wants and their favorable perceptions. And consumers' expectations of meeting their quasi-desire for artificial intelligence speakers have affected their expectations of meeting the wants and affected their perception of favorability. Finally, consumers' expectations for satisfying their wants and their perception of favorability affected their intention to use artificial intelligence speakers. The implications of this study is that it helps to formulate strategies for information technology products with combined functionality. The specific components of motivation can play an important role in increasing consumers' intention to use artificial intelligence speakers.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.204-212
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• 2022

In this paper, a contribution is presented covering the data set in improving and developing electronic services provided to citizens through e-government services based on business intelligence in government agencies in the Republic of Sudan. The Business Intelligence Concept Survey was conducted from the perceptions of information department employees in government agencies. The survey was conducted from April to June 2021 using questionnaires. The dataset contains responses about the factors that influence the use of business intelligence and the barriers and limitations to the use of business intelligence. A five-point Likert scale was used to analyze the quantitative data. The opportunities and challenges associated with it were also discussed and explored. As evidenced by the results, the information department employees agree that business intelligence improves the government decision-making process, which helps decision makers and decision-makers to find alternatives and opportunities that contribute to making more accurate and timely decisions. The results also indicate that creating the infrastructure for applying business intelligence in the e-government work model contributes to the successful implementation of business intelligence in Sudan.