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

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

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

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

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

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)

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

An integrated process of biodiesel production from indigenous microalgae in Northern Greece: first results

For environmental, economic and competence reasons, the fuel industry has pushed for alternative fuels in the past few years. One option that is considered are biofuels, which are renewable fuels and have the characteristic of lower or zero emissions of CO2 in the lifecycle, depending on their origin, their production and use. That is done, because the carbon they contain has been committed in the development of organic matter from the atmosphere, which returns after combustion so the balance of emissions throughout the life cycle of biofuel is "theoretically zero