Face-Specific Data Augmentation for Unconstrained Face Recognition

International Journal of Computer Vision - We identify two issues as key to developing effective face recognition systems: maximizing the appearance variations of training images and minimizing...     

The effect of atmospheric plasma treatment of recycled carbon fiber at different plasma powers on recycled carbon fiber and its polypropylene composites

To increase the mechanical properties of recycled carbon fiber-reinforced polypropylene (PP) composites, recycled carbon fibers (RCF) were subjected to atmospheric plasma treatment at different plasma powers (100, 200, and 300 W). The changes on surface topography and roughness of RCF were examined by atomic force microscopy. Plasma treatment of RCF increased the roughness value of RCF. The variation of surface elemental compositions and tensile strength of RCF were determined by using X-ray photoelectron spectroscopy and tensile test, respectively. Plasma-treated RCF-reinforced PP composites were fabricated using high speed thermo-kinetic mixer. Plasma treatment of RCF at 100 W increased the tensile and flexural strength values of RCF-reinforced PP composites considerably by 17 and 11%, respectively. However, plasma treatment of RCF at higher plasma powers (200 W and 300 W) decreased tensile and flexural strength values of composites because of the etching of RCF. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47131.     

Microbial profile and bacterial characterisation of naturally debittered Hurma olives compared to non‐debittered Erkence variety during ripening period

Naturally debittered Hurma olive is grown in a specific area in Karaburun peninsula in Turkey. It is characterised by its sweet taste and it differs from other varieties by losing its bitterness caused by phenolic compounds during its maturation period on the tree. Therefore, Hurma olive does not require any further debittering process to be served as table olive. This study was particularly interested in the comparison of the microbial profile of Hurma olive during its 8 weeks of maturation period in two subsequent harvest years and Erkence (not naturally debittered) olive. In addition, main bacterial profile of both Hurma and Erkence olives were isolated and identified. Aerobic mesophilic microorganism (AMM), lactic acid bacteria (LAB), Enterobacteriaceae, Pseudomonadaceae, Staphylococci, Micrococcaceae, yeasts and moulds (Y&Ms) were detected (counted and isolated) in the olive drupes during the maturation period. Isolated bacteria were identified as different spp. of Bacillaceae, Enterobacteriaceae, Micrococcoceae and Pseudomonadaceae.     

Improved prediction methods for scalable predictive animated mesh compression

Animated meshes represented as sequences of static meshes sharing the same connectivity require efficient compression. Among the compression techniques, layered predictive coding methods efficiently encode the animated meshes in a structured way such that the successive reconstruction with an adaptable quality can be performed. The decoding quality heavily depends on how well the prediction is performed in the encoder. Due to this fact, in this paper, three novel prediction structures are proposed and integrated into a state of the art layered predictive coder. The proposed structures are based on weighted spatial prediction with its weighted refinement and angular relations of triangles between current and previous frames. The experimental results show that compared to the state of the art scalable predictive coder, up to 30% bitrate reductions can be achieved with the combination of proposed prediction schemes depending on the content and quantization level.     

Sustainable hydrogen production options from food wastes

In this study, two thermochemical processes, namely steam gasification and supercritical water gasification (SCWG), were comparatively studied to produce hydrogen from food wastes containing about 90% water. The SCWG experiments were performed at 400 and 450 °C in presence of catalyst (Trona, K₂CO₃ and seaweed ash). The maximum hydrogen yield was obtained at 450 °C in presence of K₂CO₃ catalyst. In second process, hydrothermal carbonization was used to convert food wastes into a high-quality solid fuel (hydrochar) that was further gasified in a dual-bed reactor in presence of steam. The steam gasification of hydrochar was carried out with and without catalysts (iron?ceria catalyst and dolomite). The maximum hydrogen yield obtained from steam gasification process was 28.08 mmol/g dry waste, about 7.7 times of that from SCWG. This study proposed a new concept for hydrogen production from wet biomass, combination of hydrothermal carbonization following steam gasification.     

Shape-driven segmentation of the arterial wall in intravascular ultrasound images

Segmentation of arterial wall boundaries from intravascular images is an important problem for many applications in the study of plaque characteristics, mechanical properties of the arterial wall, its 3-D reconstruction, and its measurements such as lumen size, lumen radius, and wall radius. We present a shape-driven approach to segmentation of the arterial wall from intravascular ultrasound images in the rectangular domain. In a properly built shape space using training data, we constrain the lumen and media-adventitia contours to a smooth, closed geometry, which increases the segmentation quality without any tradeoff with a regularizer term. In addition to a shape prior, we utilize an intensity prior through a nonparametric probability-density-based image energy, with global image measurements rather than pointwise measurements used in previous methods. Furthermore, a detection step is included to address the challenges introduced to the segmentation process by side branches and calcifications. All these features greatly enhance our segmentation method. The tests of our algorithm on a large dataset demonstrate the effectiveness of our approach.     

Synthesis and application of phenylcarbamodithioate compound for steel protection

Phenyldithiocarbamate compound has been synthesized and studied as corrosion inhibitor for steel. Dithiocarbamate (DTC) compounds with linear alkyl groups are good inhibitors, but their stability is quite low in acidic solutions. It should be noted that long-term stability is important for practical applications, in order to avoid excess use of chemicals. So, we have synthesized phenyl substituted DTC which offers strong inhibition efficiency and extra stability. This new inhibitor is chemically adsorbed on steel through its DTC group, while the aromatic ring provides extra stability and long-term efficiency. For the assessment of corrosion kinetics, we have utilized potentiodynamic and ac impedance studies; also solution assay analysis was realized with atomic absorption spectroscopy. It was revealed that inhibitor exhibits remarkably high efficiency, even under elevated temperature conditions. At 55 °C temperature conditions, i_corr value decreased from 5050 to 154 μA cm^?2, with the addition of 500 ppm inhibitor. The long-term stability of inhibitor was also tested and 85.93% efficiency was obtained after three days of exposure period for 500 ppm concentration.     

A variational approach to problems in calibration of multiple cameras

This paper addresses the problem of calibrating camera parameters using variational methods. One problem addressed is the severe lens distortion in low-cost cameras. For many computer vision algorithms aiming at reconstructing reliable representations of 3D scenes, the camera distortion effects will lead to inaccurate 3D reconstructions and geometrical measurements if not accounted for. A second problem is the color calibration problem caused by variations in camera responses that result in different color measurements and affects the algorithms that depend on these measurements. We also address the extrinsic camera calibration that estimates relative poses and orientations of multiple cameras in the system and the intrinsic camera calibration that estimates focal lengths and the skew parameters of the cameras. To address these calibration problems, we present multiview stereo techniques based on variational methods that utilize partial and ordinary differential equations. Our approach can also be considered as a coordinated refinement of camera calibration parameters. To reduce computational complexity of such algorithms, we utilize prior knowledge on the calibration object, making a piecewise smooth surface assumption, and evolve the pose, orientation, and scale parameters of such a 3D model object without requiring a 2D feature extraction from camera views. We derive the evolution equations for the distortion coefficients, the color calibration parameters, the extrinsic and intrinsic parameters of the cameras, and present experimental results.     

Magnetically Guided Self‐Assembly and Coding of 3D Living Architectures

In nature, cells self‐assemble at the microscale into complex functional configurations. This mechanism is increasingly exploited to assemble biofidelic biological systems in vitro. However, precise coding of 3D multicellular living materials is challenging due to their architectural complexity and spatiotemporal heterogeneity. Therefore, there is an unmet need for an effective assembly method with deterministic control on the biomanufacturing of functional living systems, which can be used to model physiological and pathological behavior. Here, a universal system is presented for 3D assembly and coding of cells into complex living architectures. In this system, a gadolinium‐based nonionic paramagnetic agent is used in conjunction with magnetic fields to levitate and assemble cells. Thus, living materials are fabricated with controlled geometry and organization and imaged in situ in real time, preserving viability and functional properties. The developed method provides an innovative direction to monitor and guide the reconfigurability of living materials temporally and spatially in 3D, which can enable the study of transient biological mechanisms. This platform offers broad applications in numerous fields, such as 3D bioprinting and bottom‐up tissue engineering, as well as drug discovery, developmental biology, neuroscience, and cancer research.