Autonomous aerial cinematography in unstructured environments with learned artistic decision‐making

Aerial cinematography is revolutionizing industries that require live and dynamic camera viewpoints such as entertainment, sports, and security. However, safely piloting a drone while filming a moving target in the presence of obstacles is immensely taxing, often requiring multiple expert human operators. Hence, there is a demand for an autonomous cinematographer that can reason about both geometry and scene context in real‐time. Existing approaches do not address all aspects of this problem; they either require high‐precision motion‐capture systems or global positioning system tags to localize targets, rely on prior maps of the environment, plan for short time horizons, or only follow fixed artistic guidelines specified before the flight. In this study, we address the problem in its entirety and propose a complete system for real‐time aerial cinematography that for the first time combines: (a) vision‐based target estimation; (b) 3D signed‐distance mapping for occlusion estimation; (c) efficient trajectory optimization for long time‐horizon camera motion; and (d) learning‐based artistic shot selection. We extensively evaluate our system both in simulation and in field experiments by filming dynamic targets moving through unstructured environments. Our results indicate that our system can operate reliably in the real world without restrictive assumptions. We also provide in‐depth analysis and discussions for each module, with the hope that our design tradeoffs can generalize to other related applications. Videos of the complete system can be found at https://youtu.be/ookhHnqmlaU .     

Modeling of Trivalent Chromium Sorption onto Commercial Resins by Artificial Neural Network

In this research, artificial neural network (ANN) model having three layers was developed for precise estimation of Cr(III) sorption rate varying from 17% to 99% by commercial resins as a result of obtaining 38 experimental data. ANN was trained by using the data of sorption process obtained at different pH (2–7) values with Amberjet 1200H and Diaion CR11 amount (0.01–0.1 g) dosage, initial metal concentration (4.6–31.7 ppm), contact time (5–240 min), and a temperature of 25°C. A feed-forward back propagation network type with one hidden layer, different algorithm (transcg, trainlm, traingdm, traincgp, and trainrp), different transfer function (logsig, tansig, and purelin) for hidden layer and purelin transfer function for output layer were used, respectively. Each model trained for cross-validation was compared with the data that were not used. The trainlm algorithm and purelin transfer functions with five neurons were well fitted to training data and cross-validation. After the best suitable coefficient of determination and mean squared error values were found in the current network, optimal result was searched by changing the number of neurons range from 1 to 20 in the current network hidden layer.     

Hydrothermal preparation and electrochemical properties of Gd3+ and Bi3+, Sm3+, La3+, and Nd3+ codoped ceria-based electrolytes for intermediate temperature-solid oxide fuel cell

The structure, the thermal expansion coefficient, electrical conductivities of Ce_0.8Gd_0.2?xM_xO_2?δ (for M: Bi, x = 0–0.1, and for M: Sm, La, and Nd, x = 0.02) solid solutions, prepared for the first time hydrothermally, are investigated. The uniformly small particle size (28–59 nm) of the materials allows sintering of the samples into highly dense ceramic pellets at 1300–1400 °C. The maximum conductivity, σ_700 °C around 4.46 × 10^?2 S cm^?1 with E_a = 0.52 eV, is found at x = 0.1 for Bi-co-doping. Among various metal-co-dopings, for x = 0.02, the maximum conductivity, σ_700 °C around 2.88 × 10^?2 S cm^?1 with E_a = 0.67 eV, is found for Sm-co-doping. The electrolytic domain boundary (EDB) of Ce_0.8Gd_0.1Bi_0.1O_2?δ is found to be 1.2 × 10^?19 atm, which is relatively lower than that of the singly doped samples. The thermal expansion coefficients, determined from high-temperature X-ray data are 11.6 × 10^?6 K^?1 for the CeO₂, 12.1 × 10^?6 K^?1 for Ce_0.8Gd_0.2O_2?δ, and increase with co-doping to 14.2 × 10^?6 K^?1 for Ce_0.8Gd_0.18Bi_0.02O_2?δ. The maximum power densities for the single cell based on the codoped samples are higher than that of the singly doped sample. These results suggest that co-doping can further improve the electrical performance of ceria-based electrolytes.     

Biochemical Characterization of Turkish Extra Virgin Olive Oils from Six Different Olive Varieties of Identical Growing Conditions

Extra virgin olive oils were extracted from six different major olive cultivars (Gemlik, Ayvalik, Domat, Akhisar, Memecik, Arbequina) cultivated in the Aegean region of Turkey. Fatty acid, sterol and tocopherol compositions were analyzed and the results were compared by multivariate statistical analysis. Olive samples were collected from the same orchard in order to limit the contribution of parameters such as climate, soil quality and agricultural practices to the total variance of chemical composition of olive oils. Principal component analysis (PCA) showed that cultivars can be clearly distinguished on the basis of fatty acid and sterol composition. It is of interest to note that palmitoleic acid content of Arbequina, a Spanish cultivar, is significantly (p < 0.05) higher than the local Turkish cultivars in question and it is the only olive sample whose palmitoleic acid concentration is higher than that of the stearic acid concentration, exhibiting a divergent composition from the local Turkish cultivars. β‐Sitosterol and Δ5‐avenasterol contents of the oils are significantly correlated (r = ?0.989, p < 0.05) and this results in a discriminative axis on the PCA loading plot. Tocopherol composition was relatively insufficient in discriminating the olive varieties. Regarding tocopherol compositions Gemlik cultivar is distinguished from other cultivars with its γ‐tocopherol content, which is in average two times higher than that of other cultivars. The result of the present compositional study provides important data which can be used for olive oil authenticity studies in Turkey.     

A Comparison on Physical,Structural, and Photocatalytical Properties of TiO2 Nanopowders Produced Using Sol‐Gel and Flame Spray Pyrolysis

In this study, nanoscale photocatalyst TiO₂ powders were synthesized via sol‐gel and flame spray pyrolysis (FSP). Phase structures and ratios were analyzed by X‐ray diffractometer (XRD). Size, specific surface area, and morphologies were determined using particle size analyzer, Brunauer‐Emmett‐Teller theory, and scanning electron microscope, respectively. Anatase phase with some rutile together was obtained in XRD analysis. The degradation rates of aqueous methylene blue (MB) by TiO₂ nanopowders were calculated using UV–vis spectrophotometer. It was found that MB decomposition was successfully achieved with significantly high efficiencies for both sol‐gel and FSP‐derived powders with small differences.     

Effect of boron‐containing materials on the flammability and thermal degradation of polyamide 6 composites containing melamine

Three different boron‐containing substances—zinc borate (ZnB), borophosphate (BPO₄), and a boron‐ and silicon‐containing oligomer (BSi)—were used to improve the flame retardancy of melamine in a polyamide 6 (PA‐6) matrix. The combustion and thermal degradation characteristics of PA‐6 composites were investigated with the limiting oxygen index (LOI), the UL‐94 standard, thermogravimetric analysis (TGA)/Fourier transform infrared (FTIR) spectroscopy, and differential scanning calorimetry (DSC). A slight increase was seen in the LOI values of a sample containing BSi (1 wt %). BPO₄ at high loadings showed a V0 rating (indicating the best flame retardancy) and slightly lower LOI values in comparison with samples with only melamine. For ZnB and BSi, glassy film and char formation decreased the dripping rate and sublimation of melamine, and this led to low LOIs. According to the TGA–FTIR results, the addition of boron compounds did not change the decomposition product distribution of melamine and PA‐6. The addition of boron compounds affected the flame retardancy by physical means. The TGA data showed that boron compounds and melamine reduced the decomposition temperature of PA‐6. According to the DSC data, the inclusion of boron compounds increased the onset temperature of sublimation of melamine and also affected the flame retardancy negatively. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Synthesis and Properties of Boron Doped NaxCo2O4 Nanocrystalline Ceramics

Sodium cobalt oxide (NaCo₂O₄) nanofibers with diameters ranging between 20 and 200?nm were prepared by electrospinning a precursor mixture of PVA/(Na–Co) acetate. This was the first time any such attempt was made. Afterwards, the electrospun nanofibers were subjected to calcination treatment. The characteristics of the fibers were investigated using a Fourier transform infrared spectroscopy, a X-ray diffractometer, and a scanning electron microscopy. The boron doped and undoped NaCo₂O₄ nanofibers calcined at 850?°C were polycrystalline of the γ Na_xCo₂O₄ phase having diameters ranging between 20 and 60?nm with grain sizes of 5–10?nm, and the nanofibers calcined at 800?°C were single crystals having linked particles or crystallites with particle sizes ranging between 60 and 200?nm. The results indicated a significant effect of calcination temperature on the crystalline phase and morphology of the nanofibers. It could be seen in the SEM micrograph of the fibers that when boron was added, this resulted in the formation of cross-linked bright-surfaced fibers. The average fiber diameter for boron doped and undoped fiber mats were 204 and 123?nm, respectively. The grain diameters of boron doped and undoped nanocrystalline sintered powders were measured as 140 and 118?nm, respectively.     

System-on-chip design for ultrasonic target detection using split-spectrum processing and neural networks

Ultrasonic detection and characterization of targets concealed by scattering noise is remarkably challenging. In this study, a neural network (NN) coupled to split-spectrum processing (SSP) is examined for target echo visibility enhancement using experimental measurements with input signal-to-noise ratio around 0 dB. The SSP-NN target detection system is trainable and consequently is capable of improving the target-to-clutter ratio by an average of 40 dB. The proposed system is exceptionally robust and outperforms the conventional techniques such as minimum, median, average, geometric mean, and polarity threshold detectors. For realtime imaging applications, a field-programmable gate array (FPGA)-based hardware platform is designed for system-onchip (SoC) realization of the SSP-NN target detection system. This platform is a hardware/software co-design system using parallel and pipelined multiplications and additions for highspeed operation and high computational throughput.     

Penicillium digitatum immobilized on pumice stone as a new solid phase extractor for preconcentration and/or separation of trace metals in environmental samples

This study presents a column solid phase extraction procedure based on column biosorption of Cu(II), Zn(II) and Pb(II) ions on Penicillium digitatum immobilized on pumice stone. The analytes were determined by flame atomic absorption spectrometry (FAAS). The optimum conditions such as: pH values, amount of solid phase, elution solution and flow rate of sample solution were evaluated for the quantitative recovery of the analytes. The effect of interfering ions on the recovery of the analytes has also been investigated. The recoveries of copper, zinc and lead under the optimum conditions were found to be 97+/-2, 98+/-2 and 98+/-2%, respectively, at 95% confidence level. For the analytes, 50-fold preconcentration was obtained. The analytical detection limits for Cu(II), Zn(II) and Pb(II) were 1.8, 1.3 and 5.8 ng mL(-1), respectively. The proposed procedure was applied for the determination of copper, zinc and lead in dam water, waste water, spring water, parsley and carrot. The accuracy of the procedure was checked by determining copper, zinc and lead in standard reference tea samples (GBW-07605).