• Smart Structures and Systems
• /
• v.6 no.3
• /
• pp.309-333
• /
• 2010

Civil infrastructure, in both its construction and maintenance, represents the largest societal investment in this country, outside of the health care industry. Despite being the lifeline of US commerce, civil infrastructure has scarcely benefited from the latest sensor technological advances. Our future should focus on harnessing these technologies to enhance the robustness, longevity and economic viability of this vast, societal investment, in light of inherent uncertainties and their exposure to service and even extreme loadings. One of the principal means of insuring the robustness and longevity of infrastructure is to strategically deploy smart sensors in them. Therefore, the objective is to develop novel, durable, smart sensors that are especially applicable to major infrastructure and the facilities to validate their reliability and long-term functionality. In some cases, this implies the development of new sensing elements themselves, while in other cases involves innovative packaging and use of existing sensor technologies. In either case, a parallel focus will be the integration and networking of these smart sensing elements for reliable data acquisition, transmission, and fusion, within a decision-making framework targeting efficient management and maintenance of infrastructure systems. In this paper, prudent and viable sensor and health monitoring technologies have been developed and used in several large structural systems. Discussion will also include several practical bridge health monitoring applications including their design, construction, and operation of the systems.

• Nuclear Engineering and Technology
• /
• v.46 no.6
• /
• pp.737-752
• /
• 2014

As condition-based maintenance (CBM) has risen as a new trend, there has been an active movement to apply information technology for effective implementation of CBM in power plants. This motivation is widespread in operations and maintenance, including monitoring, diagnosis, prognosis, and decision-making on asset management. Thermal efficiency analysis in nuclear power plants (NPPs) is a longstanding concern being updated with new methodologies in an advanced IT environment. It is also a prominent way to differentiate competitiveness in terms of operations and maintenance costs. Although thermal performance tests implemented using industrial codes and standards can provide officially trustworthy results, they are essentially resource-consuming and maybe even a hind-sighted technique rather than a foresighted one, considering their periodicity. Therefore, if more accurate performance monitoring can be achieved using advanced data analysis techniques, we can expect more optimized operations and maintenance. This paper proposes a framework and describes associated methodologies for in-situ thermal performance analysis, which differs from conventional performance monitoring. The methodologies are effective for monitoring, diagnosis, and prognosis in pursuit of CBM. Our enabling techniques cover the intelligent removal of random and systematic errors, deviation detection between a best condition and a currently measured condition, degradation diagnosis using a structured knowledge base, and prognosis for decision-making about maintenance tasks. We also discuss how our new methods can be incorporated with existing performance tests. We provide guidance and directions for developers and end-users interested in in-situ thermal performance management, particularly in NPPs with large steam turbines.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1998.05a
• /
• pp.264-270
• /
• 1998

This research broadens the prime concern of nuclear power plant operations from safe performance to both economic and safe performance. First emergency diesel generator is identified as one of main contributors for the lost plant availability through the review of plants forced outage records. The framework of an integrated architecture for performing modern on-line condition for operational availability improvement is configured in this work. For the development of the comprehensive sensor networks for complex target systems, an integrated methodology incorporating a structural hierarchy, a functional hierarchy, and a fault-system matrix is formulated. The second part of our research is development of intelligent diagnosis and maintenance advisory system, which employs Bayesian Belief networks (BBNs) as a high level reasoning tool incorporating inherent uncertainty use in probabilistic inference. Our prototype diagnosis algorithms are represented explicitly through topological symbols and links between them in a causal direction. As new evidence from sensor network development is entered into the model especially, our advisory of system provides operational advice concerning both availability and safety, so that the operator is able to determine the likely modes, diagnose the system state, locate root causes, and take the most advantageous action. Thereby, this advice improves operational availability

• Asia pacific journal of information systems
• /
• v.8 no.1
• /
• pp.43-64
• /
• 1998

Cooperative query answering is a research effort to develop a fault-tolerant and intelligent database system using the semantic knowledge base constructed from the underlying database. Such knowledge base has two aspects of usage. One is supporting the cooperative query answering process for providing both an exact answer and neighborhood information relevant to a query. The other is supporting ongoing maintenance of the knowledge base for accommodating the changes in the knowledge content and database usage purpose. Existing studies have mostly focused on the cooperative query answering process but paid little attention to the dynamic knowledge base maintenance. This paper proposes a multi-level knowledge representation framework called Knowledge Abstraction Hierarchy(KAH) that can not only support cooperative query answering but also permit dynamic knowledge maintenance, On the basis of the KAH, a knowledge abstraction database is constructed on the relational data model and accommodates diverse knowledge maintenance needs and flexibly facilitates cooperative query answering. In terms of the knowledge maintenance, database operations are discussed for the cases where either the internal contents for a given KAH change or the structures of the KAH itself change. In terms of cooperative query answering, four types of vague queries are discussed, including approximate selection, approximate join, conceptual selection, and conceptual join. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database application systems.

• 한국IT서비스학회:학술대회논문집
• /
• 2008.11a
• /
• pp.486-489
• /
• 2008

재난방재시스템은 재난에 대하여 예방, 대비, 대응, 복구 단계별 활동을 지원하기 위한 정보시스템이다. 재난방재시스템은 여러 형태의 재난에 대하여 여러 수준의 다양한 정보자원을 이용해야 하고 여러 임무를 맡고 있는 다양한 인적자원과 다양한 물적 자원을 활용하여 준비하고 빠르게 대응해야 한다. 기존의 재난방재시스템은 통합적인 상황분석이 부족하고, 지역재난상황에 따라 표준행동에 의한 자동적 실시간 임무부여와 실시간 보고의 처리, 재난관리자의 경험적 지식을 활용될 수 있는 정보시스템화는 미흡한 실정이다. 본 연구에서는 주로 국방, 경찰, 보안 분야에 적용되어온 정보융합(Information fusion)기술과 비즈니스 룰(BRMS)의 규칙기반 지능형 기술을 활용하여 여러 수준의 다양한 정보를 종합 분석하여 통합적인 상황정보를 제공하고, 표준행동 요령과 지역 재난관리자의 지식을 활용하여 인적자원과 물적 자원에 대한 대응계획을 제시하여 대응조치를 선택할 수 있도록 하며, 현장 상황에 따른 실시간 임무 부여와 상황 보고를 처리할 수 있는 정보융합기반 지능형 재난방재 프레임워크를 제안한다. 본 연구의 프레임워크는 지역단위 재난방재에 적용을 고려하고 있으며 오픈소스 소프트웨어를 같이 활용하는 프로토타입 구현을 계획하고 있다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.11a
• /
• pp.310-313
• /
• 2017

범죄수사 과정에서 많은 양의 데이터를 시간 내에 분석하는 것은 성공적인 포렌식의 필수 요소이다. 컴퓨터와 사람 모두에게 있어, 시간과 자원의 제한은 수사 결과에 부정적인 영향을 가져온다. 그러므로 현재 사용되고 있는 다양한 포렌식 도구에는 시간과 자원의 효율적인 사용이 필요하다. 사례기반추론 및 멀티에이전트 시스템과 같은 인공지능 기반의 도구를 통해 디지털 포렌식 수사를 효과적으로 도울 수 있다. 본 논문에서는 인공지능을 활용한 지능형 포렌식 도구 및 프레임워크를 분석하고, 오늘날의 프레임워크의 한계점과 미래에 관해 논의한다. 인공지능 기반 시스템의 목적은 수사에서의 증거를 포함한 데이터를 분석하고 연관성을 밝힘으로서 포렌식 전문가에게 중요한 단서를 제공하고 직접 분석해야하는 데이터의 양을 줄이는 것에 있다. 이러한 인공지능의 활용은 많은 양의 데이터를 수사할 때 사람이 간과할 수 있는 증거들을 연결시켜주는 데에 큰 도움이 된다.

• Journal of Information Technology Applications and Management
• /
• v.21 no.3
• /
• pp.65-77
• /
• 2014

Ubiquitous learning has aroused great interest and is becoming a new way for foreign language education in today's society. However, how to increase the learners' initiative and their community cohesion is still an issue that deserves more profound research and studies. Emotional intelligence can help to detect the learner's emotional reactions online, and therefore stimulate his interest and the willingness to participate by adjusting teaching skills and creating fun experiences in learning. This is, actually the new concept of smart education. Based on the previous research, this paper concluded a neural mechanism model for analyzing the learners' emotional characteristics in ubiquitous environment, and discussed the intelligent monitoring and automatic recognition of emotions from the learners' speech signals as well as their behavior data by multi-agent system. Finally, a framework of emotional intelligence system was proposed concerning the smart foreign language education in ubiquitous learning.

• Journal of Korean Institute of Industrial Engineers
• /
• v.28 no.3
• /
• pp.302-318
• /
• 2002

As facing the challenges from many competitors, the Office of Korea Postal Service has issued the fundamental plan of business renovation which includes the master plan of the information systems. In this paper we discuss the design of a to-be information system for postal service, which will be provided for the completion of the master plan. After briefly discussing the issues on developing information system and the current situation, we provide the design concept and the framework of the to-be system based on the bench marking and gap analysis with advanced systems. The to-be system consists of eight subsystems which can be grouped into three categories; intelligent systems, operational systems, and platforms. We develop detailed specification of each subsystem and provide an operational scenario. We also explain how the to-be system compatibly fits into an integrated information system, which will include the postal, banking, and management functions, to perform its ultimate role for the efficient postal service.

• ETRI Journal
• /
• v.37 no.3
• /
• pp.606-616
• /
• 2015

In this paper, we propose a novel method for road recognition using 3D point clouds based on a Markov random field (MRF) framework in unstructured and complex road environments. The proposed method is focused on finding a solution for an analysis of traversable regions in challenging environments without considering an assumption that has been applied in many past studies; that is, that the surface of a road is ideally flat. The main contributions of this research are as follows: (a) guidelines for the best selection of the gradient value, the average height, the normal vectors, and the intensity value and (b) how to mathematically transform a road recognition problem into a classification problem that is based on MRF modeling in spatial and visual contexts. In our experiments, we used numerous scans acquired by an HDL-64E sensor mounted on an experimental vehicle. The results show that the proposed method is more robust and reliable than a conventional approach based on a quantity evaluation with ground truth data for a variety of challenging environments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.6 no.1
• /
• pp.104-111
• /
• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.