• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권2호
• /
• pp.520-541
• /
• 2023

In CRNs, SS is of utmost significance. Every CR user generates a sensing report during the training phase beneath various circumstances, and depending on a collective process, either communicates or remains silent. In the training stage, the fusion centre combines the local judgments made by CR users by a majority vote, and then returns a final conclusion to every CR user. Enough data regarding the environment, including the activity of PU and every CR's response to that activity, is acquired and sensing classes are created during the training stage. Every CR user compares their most recent sensing report to the previous sensing classes during the classification stage, and distance vectors are generated. The posterior probability of every sensing class is derived on the basis of quantitative data, and the sensing report is then classified as either signifying the presence or absence of PU. The ISVM technique is utilized to compute the quantitative variables necessary to compute the posterior probability. Here, the iterations of SVM are tuned by novel GO-PSA by combining GOA and PSO. Novel GO-PSA is developed since it overcomes the problem of computational complexity, returns minimum error, and also saves time when compared with various state-of-the-art algorithms. The dependability of every CR user is taken into consideration as these local choices are then integrated at the fusion centre utilizing an innovative decision combination technique. Depending on the collective choice, the CR users will then communicate or remain silent.

• Smart Structures and Systems
• /
• 제21권1호
• /
• pp.27-35
• /
• 2018

In the water-filling and preloading test, the sensing cables were installed on the surface of steel spiral case and in the surrounding concrete to monitor the strain distribution of several cross-sections by using Brillouin Optical Time Domain Analysis (BOTDA), a kind of distributed optical fiber sensing (DOFS) technology. The average hoop strain of the spiral case was about $330{\mu}{\varepsilon}$ and $590{\mu}{\varepsilon}$ when the water-filling pressure in the spiral case was 2.6 MPa and 4.1 MPa. The difference between the measured and the calculated strain was only about $50{\mu}{\varepsilon}$. It was the first time that the stress adjustment of the spiral case was monitored by the sensing cable when the pressure was increased to 1 MPa and the residual strain of $20{\mu}{\varepsilon}$ was obtained after preloading. Meanwhile, the shrinkage of $70{\sim}100{\mu}{\varepsilon}$ of the surrounding concrete was effectively monitored during the depressurization. It is estimated that the width of the gap between the steel spiral case and the surrounding concrete was 0.51 ~ 0.75 mm. BOTDA based distributed optical fiber sensing technology can obtain continuous strain of the structure and it is more reliable than traditional point sensor. The strain distribution obtained by BOTDA provides strong support for the design and optimization of the spiral case structure.

• 대한전자공학회논문지TC
• /
• 제48권3호
• /
• pp.28-35
• /
• 2011

고용량의 멀티미디어 데이터 전송이 비약적으로 늘어나는 차세대 이동통신 시스템에서 cooperative ARQ 기법은 단말의 QoS를 만족시키기 위한 효과적인 방법이다. 그러나 기존의 cooperative ARQ 기법은 수신노드의 feedback을 받아서 재전송을 하기 때문에 채널 변화가 극심한 MANET 환경에서는 실시간 전송을 보장하기 어렵다는 단점이 있다. 본 논문에서는 ad-hoc OFDMA 통신 네트워크에서 cognitive relay를 이용한 협력통신 기반 cooperative ARQ 재전송 기법을 제안한다. 제안된 기법에서는 송신노드가 전송한 신호의 SINR을 relay가 사전에 sensing함으로써, 수신노드가 feedback 신호를 전송하기 전에 협력 통신을 능동적으로 제안한다. 이를 통하여, 무선 채널의 변화에 따른 지연 분산 특성을 극소화함으로써 실시간 통신을 원활하게 한다. 또한, relay에서 협력 통신을 제안할 때, 잘못된 제안을 최소화하기 위하여 최적의 sensing threshold를 유지할 수 있도록 하는 적응적 sensing threshold 최적화 알고리듬을 제안한다. 모의실험을 통하여, 실시간 멀티미디어 데이터 전송 시스템에서 제안된 cooperative ARQ 재전송 기법이 기존의 알고리듬에 비하여 프레임 전달시간 및 프레임 손실률 측면에서 우수한 성능을 가짐을 확인하였다.

• 대한원격탐사학회지
• /
• 제25권6호
• /
• pp.547-557
• /
• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• 대한원격탐사학회지
• /
• 제36권4호
• /
• pp.515-525
• /
• 2020

This study investigates the potential of bidirectional long short-term memory (Bi-LSTM) for efficient modeling of temporal information in crop classification using multitemporal remote sensing images. Unlike unidirectional LSTM models that consider only either forward or backward states, Bi-LSTM could account for temporal dependency of time-series images in both forward and backward directions. This property of Bi-LSTM can be effectively applied to crop classification when it is difficult to obtain full time-series images covering the entire growth cycle of crops. The classification performance of the Bi-LSTM is compared with that of two unidirectional LSTM architectures (forward and backward) with respect to different input image combinations via a case study of crop classification in Anbadegi, Korea. When full time-series images were used as inputs for classification, the Bi-LSTM outperformed the other unidirectional LSTM architectures; however, the difference in classification accuracy from unidirectional LSTM was not substantial. On the contrary, when using multitemporal images that did not include useful information for the discrimination of crops, the Bi-LSTM could compensate for the information deficiency by including temporal information from both forward and backward states, thereby achieving the best classification accuracy, compared with the unidirectional LSTM. These case study results indicate the efficiency of the Bi-LSTM for crop classification, particularly when limited input images are available.

• 한국컴퓨터정보학회논문지
• /
• 제15권5호
• /
• pp.57-65
• /
• 2010

본 논문에서는 감시 카메라를 통해 입력된 영상 정보로 연기와 화염을 실시간 검출하는 알고리즘을 제안한다. 산불은 막대한 인명, 재산피해를 불러오기 때문에 조기 감지에 따른 초기 진화가 매우 중요하다. 제안하는 산불 감시 알고리즘은 화염 감지와 연기 감지로 나뉘는데, 화염 감지는 단일 프레임에서 YCbCr 컬러 모델에서의 조건 검사를 통하여 화염을 검출한다. 연기 감지를 위해서는 먼저 현재 영상과 인접한 프레임들의 평균 영상사이의 차를 가중치로 이용하여 배경 범위를 설정하고, 이 범위를 벗어나면서 회색조를 갖는 픽셀만을 연기영역으로 검출한다. 제안하는 화염 감지 알고리즘은 기존의 알고리즘보다 일조량에 따른 조도의 변화에 강건하고, 연기 검출 알고리즘은 단위 시간동안의 변화량을 고려하여 회색조의 픽셀만을 연기로 감지하기 때문에 효과적인 조기 산불 탐지가 가능하다. 실험 결과는 제안하는 산불 감시 알고리즘이 기존의 알고리즘보다 우수한 성능을 나타냄을 보여준다.

• 대한원격탐사학회지
• /
• 제18권2호
• /
• pp.91-96
• /
• 2002

고정 검출 시간(Integration Time)을 갖고 Time Delay and Integration(TDI) Charge Coupled Device (CCD) 검출기를 사용하는 위성 영상 기기에서 위성의 고도 및 촬영각의 변화에 대한 영상 기기의 기하 성능 특성을 TDI 불일치와 관련하여 분석하였다. 본 분석을 통하여 고도 저하에 따른 기하 성능 저하를 보완할 수 있는 방법으로서 경사 촬영을 통한 TDI 불일치 제거를 제안하였고 저하된 고도에서 TDI 일치로 최적 성능을 줄 수 있는 최적 경사 촬영각을 구하였다. 본 결과는 임의의 범위의 가변 검출 시간을 갖는 TDI CCD 위성 영상 기기에도 적용 가능하다.

• 대한원격탐사학회지
• /
• 제26권6호
• /
• pp.629-644
• /
• 2010

A real-time image georeferencing system requires all inputs to be determined in real-time. The intrinsic camera parameters can be identified in advance from a camera calibration process while other control information can be derived instantaneously from real-time GPS/INS data. The bottleneck process is tie point acquisition since manual operations will be definitely obstacles for real-time system while the existing extraction methods are not fast enough. In this paper, we present a fast-and-automated image matching technique based on the KLT tracker to obtain a set of tie-points in real-time. The proposed work accelerates the KLT tracker by supplying the initial guessed tie-points computed using the GPS/INS data. Originally, the KLT only works effectively when the displacement between tie-points is small. To drive an automated solution, this paper suggests an appropriate number of depth levels for multi-resolution tracking under large displacement using the knowledge of uncertainties the GPS/INS data measurements. The experimental results show that our suggested depth levels is promising and the proposed work can obtain tie-points faster than the ordinary KLT by 13% with no less accuracy. This promising result suggests that our proposed algorithm can be effectively integrated into the real-time image georeferencing for further developing a real-time surveillance application.

• 인터넷정보학회논문지
• /
• 제12권4호
• /
• pp.35-43
• /
• 2011

최근 들어 무선인지 애드 혹 네트워크(CRAHN)는 임시적으로 활용되지 않은 라이선스 스펙트럼을 기회주의적 방법으로 사용하여 통신하는 차세대 애드 혹 네트워크로 각광받고 있다. 여타 무선인지 시스템에서와 같이, 정확한 스펙트럼 센싱은 무선인지 애드 혹 네트워크 구현을 위한 필수 요소 기술이다. 중앙 제어국 중심의 협력 스펙트럼 센싱 기법은 센싱 성능을 향상 시킬 수 있으나, 무선인지 애드 혹 네트워크와 같은 비인프라망에서는 중앙 제어국이 없어 협력 센싱 구현이 어렵다. 본 논문에서는 무선인지 애드 혹 네트워크를 위한 새로운 순차적 협력 스펙트럼 센싱 기법을 제안한다. 제안된 기법에서는 Dempster Shafer 이론 기반으로 국부 스펙트럼 센싱 데이터의 신뢰도가 가장 높은 인지 노드가 임시 중앙국이 되어 주변 센서 노드로부터 스펙트럼 센싱값을 수집하여 스펙트럼 사용 유무에 대한 최종 결정을 만들고 그 최종 결정을 이웃 노드들에게 전송한다. 또한 본 논문에서는 분산 방법으로 개별 인지 노드들이 자신의 센싱 데이터를 효율적으로 교환하기 위한, 센싱데이터 신뢰도 순서 기반의 전송 메커니즘을 제안하였다. 시뮬레이션을 통해 제안된 방식은 기존 중앙 제어국 중심의 협력 스펙트럼 센싱 기법과 유사한 스펙트럼 센싱 성능을 제공하는 동시에, 최종 스펙트럼 결정까지 소요되는 센싱 데이터 수집시간 및 교환되는 센싱 데이터 량을 현저히 줄일 수 있음을 보였다.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.1400-1402
• /
• 2003

The objective of this paper is to determine the suitable spectral bands for monitoring growth status change during a long period. The long-term ground-level reflectance spectra as well as LAI and biomass were obtained in xiaotangshan area, Beijing, 2001. The narrow-band NDVI type spectral indices by all possible two bands were calculated their correlation coefficients R$^2$ with biomass and LAI. The best NDVIs must have higher R$^2$ with both biomass and LAI. The reasonable band centers and band widths were determined by a systematically increasing bandwidth centered over a wavelength. In addition, the first 19 bands of MODIS were simulated and investigated. Each developed spectral indices was then validated by the biomass and LAI time series using the generalized vector angle. It turned out that six new NDVI type indices within 750-1400nm were developed. NDVI(811_10,957_10) and NDVI(962_10,802_10) performed best. No satisfactory conventional NDVI formed by red and NIR bands were found effective. MODIS_NDVI(band19, band17) and MODIS_NDVI(band19, band2) were much better than MODIS_NDVI(band2,band1) for growth monitoring.