388 research outputs found
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High-speed multi-dimensional relative navigation for uncooperative space objects
This work proposes a high-speed Light Detection and Ranging (LIDAR) based navigation architecture that is appropriate for uncooperative relative space navigation applications. In contrast to current solutions that exploit 3D LIDAR data, our architecture transforms the odometry problem from the 3D space into multiple 2.5D ones and completes the odometry problem by utilizing a recursive filtering scheme. Trials evaluate several current state-of-the-art 2D keypoint detection and local feature description methods as well as recursive filtering techniques on a number of simulated but credible scenarios that involve a satellite model developed by Thales Alenia Space (France). Most appealing performance is attained by the 2D keypoint detector Good Features to Track (GFFT) combined with the feature descriptor KAZE, that are further combined with either the H∞ or the Kalman recursive filter. Experimental results demonstrate that compared to current algorithms, the GFTT/KAZE combination is highly appealing affording one order of magnitude more accurate odometry and a very low processing burden, which depending on the competitor method, may exceed one order of magnitude faster computation
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A New Passive 3-D Automatic Target Recognition Architecture for Aerial Platforms
The 3-D automatic target recognition (ATR) has many advantages over its 2-D counterpart, but there are several constraints in the context of small low-cost unmanned aerial vehicles (UAVs). These limitations include the requirement for active rather than passive monitoring, high equipment costs, sensor packaging size, and processing burden. We, therefore, propose a new structure from motion (SfM) 3-D ATR architecture that exploits the UAV's onboard sensors, i.e., the visual band camera, gyroscope, and accelerometer, and meets the requirements of a small UAV system. We tested the proposed 3-D SfM ATR using simulated UAV reconnaissance scenarios and found that the performance was better than classic 3-D light detection and ranging (LIDAR) ATR, combining the advantages of 3-D LIDAR ATR and passive 2-D ATR. The main advantages of the proposed architecture include the rapid processing, target pose invariance, small template size, passive scene sensing, and inexpensive equipment. We implemented the SfM module under two keypoint detection, description and matching schemes, with the 3-D ATR module exploiting several current techniques. By comparing SfM 3-D ATR, 3-D LIDAR ATR, and 2-D ATR, we confirmed the superior performance of our new architecture
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Fusing Deep Learning and Sparse Coding for SAR ATR
We propose a multimodal and multidiscipline data fusion strategy appropriate for automatic target recognition (ATR) on synthetic aperture radar imagery. Our architecture fuses a proposed clustered version of the AlexNet convolutional neural network with sparse coding theory that is extended to facilitate an adaptive elastic net optimization concept. Evaluation on the MSTAR dataset yields the highest ATR performance reported yet, which is 99.33% and 99.86% for the three- and ten-class problems, respectively
Atrial fibrillation following major noncardiac thoracic surgery: significance and impact on morbidity
Communication and Collaboration between School and Family for Addressing Bullying
School and family are the main socializing agents for children. Therefore, effective communication and collaboration between these contexts is essential, although sometimes there are barriers to school-family partnership, particularly when they try to play a more active role in the educational process. It is widely recognized that parent involvement in school has successful contributions to student school outcomes. Moreover, It is crucial for addressing effectively bullying, as it is a problem student behaviour in Greek society as well.In this context, the present research aims to explore teachers' views about family-school communication and collaboration regarding the extent to which they address effectively bullying. 150 primary education teachers from public schools in Rhodes participated in this research, which conducted in 2015. Results show that teachers endorse the importance of school-family collaboration for addressing bullying. In addition, they consider this collaboration important, as it has an important influence on children's attitudes to school, and their behaviour in school environment. Furthermore, they suggest that school-family collaboration may improve students' social skills, which can enhance their emotional development and reduce their social isolation from the peer group. Finally, they assert that school-family collaboration can empower children's relationship with their parents and teachers, and in the long term it can contribute in enhancing their school achievement
Ecological evaluation of transitional and coastal waters: A marine benthic macrophytes-based model
A model to estimate the ecological status and identify restoration targets of transitional and coastal waters was developed. Marine benthic macrophytic species (seaweeds, seagrasses) were used to indicate shifts in the aquatic ecosystem from the pristine state with late-successional species (Ecological State Group I) to the degraded state with opportunistic (ESG II) species. The first group comprises species with a thick or calcareous thallus, low growth rates and long life cycles (perennials), whereas the second group includes sheet-like and filamentous species with high growth rates and short life cycles (annuals). Seagrasses were included in the first group, whereas Cyanophyceae and species with a coarsely branched thallus were included in the second group.The evaluation of ecological status into five categories from high to bad includes a cross comparison in a matrix of the ESGs and a numerical scoring system (Ecological Evaluation Index). The model could allow comparisons, ranking and setting of priorities at regional and national levels fulfilling the requirements of the EU Water Frame Directive. A successful application of the model was realized in selected lagoons of the Macedonian and Thrace region (North Greece) and in the Saronic Gulf coastal ecosystems (Central Greece)
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3D Automatic Target Recognition for Future LIDAR Missiles
We present a real-time three-dimensional automatic target recognition approach appropriate for future light detection and ranging-based missiles. Our technique extends the speeded-up robust features method into the third dimension by solving multiple two-dimensional problems and performs template matching based on the extreme case of a single pose per target. Evaluation on military targets shows higher recognition rates under various transformations and perturbations at lower processing time compared to state-of-the-art approaches
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B-HoD: A Lightweight and Fast Binary Descriptor for 3D Object Recognition and Registration
3D object recognition and registration in computer vision applications has lately drawn much attention as it is capable of superior performance compared to its 2D counterpart. Although a number of high performing solutions do exist, it is still challenging to further reduce processing time and memory requirements to meet the needs of time critical applications. In this paper we propose an extension of the 3D descriptor Histogram of Distances (HoD) into the binary domain named the Binary-HoD (B-HoD). Our binary quantization procedure along with the proposed preprocessing step reduce an order of magnitude both processing time and memory requirements compared to current state of the art 3D descriptors. Evaluation on two popular low quality datasets shows its promising performance
Eutrophication patterns in an eastern Mediterranean coastal lagoon: Vassova, Delta Nestos, Macedonia, Greece
The results of an intensive monitoring study of main eutrophication parameters in relation to fish farming management, climate and hydrography in the Vassova coastal lagoon (Nestos Delta) are presented. The overall aim is to produce basic knowledge in order to contribute to the management of eutrophication of coastal lagoons at local and national levels. Due to extensive spatiotemporal variability of the measured parameters correlation and regression polynomial analysis was used to identify patterns (p<0.05). Freshwater was the main source of nitrate and phosphate in the lagoon. This finding has justified the reduction of freshwater inflow in the past, which, however, has increased mean salinity to 30 PSU and reduced spatial salinity gradients. Maximum nitrate values in winter coincided with adverse climatic and hydrographic conditions (high precipitation, strong NE to E winds and low tide) and fish farming management that hinder water circulation. Dissolved phosphorus variability indicated the combination of the external (freshwaters) and internal (sediment) P-sources. N/P water values indicated nitrogen being the most important nutrient for primary producers throughout the year, except in winter, when phosphorus was the most important nutrient. Practical measures for improving fish farming practices to decrease “eutrophication risk” during winter are suggested. Existing nutrient data from the Vassova and from other Greek lagoons in comparison were also presented and discussed
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