• 제목/요약/키워드: Intelligence and Information Technology

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Ambient Intelligence in Distributed Modular Systems

  • Ngo Trung Dung;Lund Henrik Hautop
    • 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].

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The MapDS-Onto Framework for Matching Formula Factors of KPIs and Database Schema: A Case Study of the Prince of Songkla University

  • Kittisak Kaewninprasert;Supaporn Chai-Arayalert;Narueban Yamaqupta
    • 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.

Disapproval Judgment System of Research Fund Execution Details Based on Artificial Intelligence

  • Kim, Yongkuk;Juan, Tan;Jung, Hoekyung
    • 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%.

Automatic Parameter Tuning for Simulated Annealing based on Threading Technique and its Application to Traveling Salesman Problem

  • Fangyan Dong;Iyoda, Eduardo-Masato;Kewei Chen;Hajime Nobuhara;Kaoru Hirota
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.439-442
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    • 2003
  • In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5% decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

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구조부재 인식을 위한 인공지능 학습데이터 생성방법 연구 (A Study on Artificial Intelligence Learning Data Generation Method for Structural Member Recognition)

  • 윤정현;김시욱;김치경
    • 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.

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인터넷 시대의 정보활동: OSINT의 이해와 적용사례분석 (Intelligence in the Internet Era: Understanding OSINT and Case Analysis)

  • 이완희;윤민우;박준석
    • 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.

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인공지능 스피커 사용 동기 형성에 관한 연구 (A Study on the Motivation of Artificial Intelligence Speaker)

  • 임양환
    • 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.

Adopting e-Government Services in Less Developed Countries According to the Characteristics of Business Intelligence: (Sudan as a model)

  • Adrees, Mohmmed S.
    • 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.

레이더와 전자정보 장비의 정보융합 특성 분석 (An Analysis of Information Fusion Characteristics between Radar and Electronic Intelligence System)

  • 임중수
    • 한국산학기술학회논문지
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    • 제7권5호
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    • pp.847-851
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    • 2006
  • 본 논문에서는 레이더와 전자정보 장비를 사용해서 획득한 각각의 정보를 종합해서 레이더에서 획득한 표적신호와 전자정보에서 획득한 전자파 정보를 융합하는 기술을 제시한다. 레이더와 전자정보 장비를 융합하면 표적을 정확하게 확인할 수 있기 때문에 레이더의 탐지 오차율이 줄어들고 표적에 대한 상세 정보를 확보할 수 있으며, 정보융합 모듈에서 융합한 내용을 종합표시기에서 통합된 정보를 표시할 때 장비의 성능을 향상시킬 수 있으며 표적식별이나 목표물 선정에 사용할 수 있다.

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Cyber-attack group analysis method based on association of cyber-attack information

  • Son, Kyung-ho;Kim, Byung-ik;Lee, Tae-jin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권1호
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    • pp.260-280
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    • 2020
  • Cyber-attacks emerge in a more intelligent way, and various security technologies are applied to respond to such attacks. Still, more and more people agree that individual response to each intelligent infringement attack has a fundamental limit. Accordingly, the cyber threat intelligence analysis technology is drawing attention in analyzing the attacker group, interpreting the attack trend, and obtaining decision making information by collecting a large quantity of cyber-attack information and performing relation analysis. In this study, we proposed relation analysis factors and developed a system for establishing cyber threat intelligence, based on malicious code as a key means of cyber-attacks. As a result of collecting more than 36 million kinds of infringement information and conducting relation analysis, various implications that cannot be obtained by simple searches were derived. We expect actionable intelligence to be established in the true sense of the word if relation analysis logic is developed later.