• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권12호
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• pp.3061-3080
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• 2012

To improve the sensing performance, cooperation among secondary users can be utilized to collect space diversity. In this paper, we focus on the optimization of cooperative spectrum sensing in which multiple cognitive users efficiently cooperate to achieve superior detection accuracy with minimum sensing error probability in multiple cross-over cognitive radio networks. The analysis focuses on two fusion strategies: soft information fusion and hard information fusion. Under soft information fusion, the optimal threshold of the energy detector is derived in both noncooperative single-user and cooperative multiuser sensing scenarios. Under hard information fusion, the optimal randomized rule and the optimal decision threshold are derived according to the rule of minimum sensing error (MSE). MSE rule shows better performance on improving the final false alarm and detection probability simultaneously. By simulations, our proposed strategy optimizes the sensing performance for each cognitive user which is randomly distributed in the multiple cross-over cognitive radio networks.

• 한국위성정보통신학회논문지
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• 제10권2호
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• pp.1-9
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• 2015

최근 제한된 주파수 자원의 효율적인 사용을 위한 인지 무선 기술(CR)이 많은 관심을 받고 있다. CR 기술에서 가장 중요한 부분은 인가 사용자의 통신을 보호 하는 것이다. 따라서 비인가 사용자는 자신이 현재 사용 중인 주파수 대역은 물론 인가 사용자가 나타났을 시에 스위칭 해야 할 후보 채널의 주기적인 센싱도 필요하다. 본 논문에서는 CR 환경에서 인가 사용자를 보호하기 위한 방법으로 비인가 사용자로 하여금 각 노드의 남은 에너지와 센싱 존 이웃이라는 개념을 이용하여 협력적인 채널 센싱을 하도록 제안한다. 채널 센싱은 현재 사용하고 있는 채널을 센싱하는 인밴드센싱과 인가 사용자가 나타났을 경우 스위칭 해야할 후보 채널을 센싱하는 아웃밴드 센싱으로 수행된다. 모의 실험을 통해 제안된 방법이 센싱을 수행하는 노드의 수를 줄임으로 인해 센싱에 필요한 많은 에너지가 절약되고, 남은 노드들의 에너지가 균일해 짐으로써 네트워크의 수명이 길어지는 것을 확인할 수 있다.

• Ecology and Resilient Infrastructure
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• 제6권2호
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• pp.120-127
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• 2019

본 연구에서는 광섬유 온도 분포 센싱을 통한 제체의 침투 및 붕괴와 같은 물리적 변화 현상을 모니터링하기 위해 중규모 제방 수리실험을 수행하였다. 본 실험의 중규모 실험 제방은 바이오폴리머 흙을 제방 전면에 도포하여 강도를 증진시킨 것으로 월류에 의한 침투 및 붕괴 현상이 일반 제방과는 다르게 나타날 수 있으며, 이러한 현상은 광섬유 온도 분포 센싱을 통해 획득한 온도 변화 정보를 통해 분석할 수 있었다. 제체의 위치별 시간에 따른 온도 변화 자료를 통해 제체 내부의 물리적 변화 및 침투가 발생하는 위치와 시간을 판단할 수 있었다. 본 실험에서는 급격한 온도 변화 시점이 제외지 사면보다 제내지 사면에서 먼저 발생하였으며, 이는 실험에서 제내지 사면이 붕괴된 후에 제외지 사면이 붕괴된 순서와 일치하였다.

• ETRI Journal
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• 제42권3호
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• pp.376-387
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• 2020

Massive computation of the reconstruction algorithm for compressive sensing (CS) has been a major concern for its real-time application. In this paper, we propose a novel high-speed architecture for the orthogonal matching pursuit (OMP) algorithm, which is the most frequently used to reconstruct compressively sensed signals. The proposed design offers a very high throughput and includes an innovative pipeline architecture and scheduling algorithm. Least-squares problem solving, which requires a huge amount of computations in the OMP, is implemented by using systolic arrays with four new processing elements. In addition, a distributed-arithmetic-based circuit for matrix multiplication is proposed to counterbalance the area overhead caused by the multi-stage pipelining. The results of logic synthesis show that the proposed design reconstructs signals nearly 19 times faster while occupying an only 1.06 times larger area than the existing designs for N = 256, M = 64, and m = 16, where N is the number of the original samples, M is the length of the measurement vector, and m is the sparsity level of the signal.

• Smart Structures and Systems
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• 제5권2호
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• pp.119-137
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• 2009

Smart sensors densely distributed over structures can use their computational and wireless communication capabilities to provide rich information for structural health monitoring (SHM). Though smart sensor technology has seen substantial advances during recent years, implementation of smart sensors on full-scale structures has been limited. Hardware resources available on smart sensors restrict data acquisition capabilities; intrinsic to these wireless systems are packet loss, data synchronization errors, and relatively slow communication speeds. This paper addresses these issues under the hardware limitation by developing corresponding middleware services. The reliable communication service requires only a few acknowledgement packets to compensate for packet loss. The synchronized sensing service employs a resampling approach leaving the need for strict control of sensing timing. The data aggregation service makes use of application specific knowledge and distributed computing to suppress data transfer requirements. These middleware services are implemented on the Imote2 smart sensor platform, and their efficacy demonstrated experimentally.

• 대한원격탐사학회지
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• 제33권1호
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• pp.15-24
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• 2017

Jellyfish (cnidarian) are conspicuous in many marine ecosystems when in bloom. Despite their importance for the ecosystem structure and function, very few sampling programs are dedicated to sample jellyfish because they are patchily distributed and easily clogged plankton net. Although satellite remote sensing is an excellent observing tool for many phenomena in the ocean, their uses for monitoring jellyfish are not possible due to the coarse spatial resolutions. Hence, we developed the low altitude remote sensing platform to detect jellyfish in high resolutions, which allow us to monitor not only horizontal, but also vertical migration of them. Using low altitude remote sensing platform,we measured the jellyfish from the pier at the Chesapeake Biological Laboratory in Chesapeake Bay. The patterns observed included discrete patches, in rows that were aligned with waves that propagated from deeper regions, and aggregation around physical objects. The corresponding areas of exposed jellyfish on the sea surface were $0.1{\times}10^4pixel^2$, $0.3{\times}10^4pixel^2$, and $2.75{\times}10^4pixel^2$, respectively. Thus, the research result suggested that the migration of the jellyfish was related to the physical forcing in the sea surface.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2006년도 전기학술대회논문집
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• pp.275-276
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• 2006

선박 및 해양기자재의 안전 진단을 위한 기존의 기술은 접 센서(point sensor)를 이용한 변형률 측정 기술이 대부분이라 할 수 있다. 본 논문은 기존의 기술보다 효율적으로 응용될 수 있는 광섬유 센서를 이용한 분포 개념의 온도 및 변형률 측정(DTSS: Distributed Temperature & Strain Sensing) 기술에 대해 소개하고 있다. 이 기술은 선체 응력 모니터링, 해양 구조물 안전진단, subsea flowline 모니터링, platform의 riser 안정성, umbilical 모니터링 등에 활용될 수 있다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1371-1373
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• 2003

The importance of Fundamental Geographical Information Framework for Digital City (FGFDC) is analysed, it provides all city agencies and units with uniform geographic references. Six kind of data are chosen as the core data sets of a FGDC, a web-based distributed mechanism is constructed to promote data sharing among different agencies. Elementary functional requirements of FGDC are analyzed, so that it can serve as a common distributed urban GIS. A practical FGFDC is developed for Yangzhou Development Administrative Region, and an 3D visualization system is developed within this framework.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.648-650
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• 2003

Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

• Current Optics and Photonics
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• 제7권5호
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• pp.511-517
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• 2023

Pipelines play an important role in urban water supply and drainage, oil and gas transmission, etc. This paper presents a technique for pattern recognition of fiber optic vibration signals collected by a distributed vibration sensing (DVS) system using a deep learning residual network (ResNet). The optical fiber is laid on the pipeline, and the signal is collected by the DVS system and converted into a 64 × 64 single-channel grayscale image. The grayscale image is input into the ResNet to extract features, and finally the K-nearest-neighbors (KNN) algorithm is used to achieve the classification and recognition of pipeline damage.