• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.436-439
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• 2010

최근 USN(Ubiquitous Sensor Network) 기술은 시범사업 수준의 테스트 환경을 벗어나 산업 현장 전반에 적용이 시도되고 있다. 현재의 USN 기술은 신뢰성 및 보안성이 취학하여 대규모 플랜트와 같은 난환경 산업 현장에의 적용이 어려운 현실이다. 또한 표준화된 기술의 부재로 인해 사용되는 USN 관련 장치들의 상호호환이 어려우며 기존 설비와의 호환이 어려워 산업 현장에 설치 규제가 심한 상태이. 다이러한 현실에도 불구하고 에너지 플랜트와 같은 고위험 시설물의 경우 설비에 대한 지속적인 감시 및 관리가 필요하며, 이를 위한 관련 기술의 개발이 필요하다. 본 논문에서는 USN 기술을 기반으로 에너지플랜트와 같은 고위험 시설물을 위한 고도화되고 지능화된 안전 인프라를 구축하여, 다양한 사고위험으로부터 안전성을 확보할 수 있는 스마트 플랜트안전 프레임워크를 제안한다. 제안하는 프레임워크에서는 플랜트를 위한 고위험 시설물의 감시에 필수적인 요소기술을 소개하고, 이를 통합하기 위한 프래임워크 구조를 제시하여 향후 관련 기술에 대한 기준점을 제시한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.41-48
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• 2007

Latest advances in network sensor technology and state of the art of mobile robot, and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. In this study, as the preliminary step for developing a multi-purpose "Intelligent Space" platform to implement advanced technologies easily to realize smart services to human. We will give an explanation for the ISpace system architecture designed and implemented in this study and a short review of existing techniques, since there exist several recent thorough books and review paper on this paper. Instead we will focus on the main results with relevance to the DIND data fusion with CI of Intelligent Space. We will conclude by discussing some possible future extensions of ISpace. It is first dealt with the general principle of the navigation and guidance architecture, then the detailed functions tracking multiple objects, human detection and motion assessment, with the results from the simulations run.

• Smart Structures and Systems
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• v.5 no.2
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• pp.139-152
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• 2009

Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

• Journal of the Korean Solar Energy Society
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• v.27 no.4
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• pp.147-155
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• 2007

It is essential to investigate the structure and the main characteristic of Home USN (Ubiquitous Sensor Network) technologies in built ubiquitous environment while designing future residential space. For this study, three different housing types have been selected to implement ubiquitous technologies for residential space; those are regular, elderly, and single residence units. It is certain that efficiency of ubiquitous home design is improved if main components of each specific housing type are analyzed precisely in digital way and design models are prepared accordingly. Ubiquitous technology, in conclusion, has to be applied not on)r with systematical mechanism or electronic setting but in human-centered atmosphere as well, keeping with deep consideration for bio-housing service factors in eco-friendly surrounding; we call this Ubiquitous Humanism.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.11
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• pp.1128-1133
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• 2008

Cellulose based electroactive paper(EAPap) has been developed as a new smart material due to its advantages of piezoelectricity, large displacement, low power consumption, low cost and flexibility. EAPap can be used for a surface acoustic wave (SAW) device using the piezoelectric property of EAPap, resulting in the cost effective and flexible SAW device. In this paper, inter digit transducer(IDT) structure using lift-off technique with a finger gap of 10mm was used for micro fabrication of the cellulose EAPap SAW devices. The performance of IDT patterned SAW device was characterized by a Network Analyzer. The feasibility of cellulose EAPap as a potential acoustic device was presented and explained.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.979-982
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• 2013

위치정보를 이용한 서비스가 요구가 증가함에 따라, 실외를 중심으로 이뤄지던 위치정보서비스는 실내를 중심으로 요구되고 있다. 더불어 좀더 정확한 실내측위 시스템에 대한 필요성도 증가되고 있다. 최근의 위치 정보 서비스는 스마트폰의 보급과 함께 모바일 기기의 환경이 이용되고 있다. 본 논문은 스마트 디바이스 기반으로 WLAN(Wireless Local Area Network)과 DATABASE 를 이용한 Fingerprinting 방식을 제안한다. 또한 기존의 Fingerprinting 방식에 스마트 디바이스에 내장된 Gyroscope sensor 를 이용하여 모바일 환경에서 일부 영역에서 발생할 수 있는 신호의 오차를 보정하는 새로운 방법도 제시한다. 실제 테스트 환경을 구축하여 실험한 결과도 제시하였다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.24-30
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• 2014

In this paper, a new remote terminal unit(hereafter RTU) is proposed to manage a wide range of applications and a variety of sensors (eg, pressure, water quality, temperature and humidity sensors, the amount of pollutants, $CO_2$, etc.) to monitor and control the facility such as water treatment plant, intake and effluent pumping station, water tank and distribution network. Fault status of local sensor devices and network are alerted by using the embedded fault handling capabilities of the RTU in the system and also sent to the fault handling server, by which fault can be easily monitored to users. The developed system was applied to one of K-water branch offices in Geoje city and improved its reliability and stability for controlling and monitoring water facility.

• Smart Structures and Systems
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• v.2 no.3
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• pp.253-274
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• 2006

The structural monitoring of multi-wire strands is of importance to prestressed concrete structures and cable-stayed or suspension bridges. This paper addresses the monitoring of strands by ultrasonic guided waves with emphasis on the signal processing and automatic defect classification. The detection of notch-like defects in the strands is based on the reflections of guided waves that are excited and detected by magnetostrictive ultrasonic transducers. The Discrete Wavelet Transform was used to extract damage-sensitive features from the detected signals and to construct a multi-dimensional Damage Index vector. The Damage Index vector was then fed to an Artificial Neural Network to provide the automatic classification of (a) the size of the notch and (b) the location of the notch from the receiving sensor. Following an optimization study of the network, it was determined that five damage-sensitive features provided the best defect classification performance with an overall success rate of 90.8%. It was thus demonstrated that the wavelet-based multidimensional analysis can provide excellent classification performance for notch-type defects in strands.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.132-135
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• 2022

Recently, with the development of IoT communication technology, products and services that detect and inform the surrounding environment under the name of smart plugs are being developed. In particular, in order to prepare for fire or gas leakage accidents, products that automatically close and warn when abnormal symptoms occur are used. Most of them use methods of collecting, analyzing, and processing information through networks. However, there is a disadvantage that it cannot be used when the network is temporarily in a failed state. In this paper, sensor information was analyzed using deep learning, and a model that can predict abnormal symptoms was learned in advance and applied to MCU. The performance of each model was evaluated by developing firmware that can judge and process on its own regardless of network and applying a predictive model to the MCU after 3 to 120 seconds.