LiDAR-assisted Large-scale Privacy Protection in Street-view Cycloramas

Recently, privacy has a growing importance in several domains, especially in street-view images. The conventional way to achieve this is to automatically detect and blur sensitive information from these images. However, the processing cost of blurring increases with the ever-growing resolution of images. We propose a system that is cost-effective even after increasing the resolution by a factor of 2.5. The new system utilizes depth data obtained from LiDAR to significantly reduce the search space for detection, thereby reducing the processing cost. Besides this, we test several detectors after reducing the detection space and provide an alternative solution based on state-of-the-art deep learning detectors to the existing HoG-SVM-Deep system that is faster and has a higher performance.Comment: Accepted at Electronic Imaging 201

6-(4-Fluorophenyl)-8-phenyl-2,3-dihydro-4H-imidazo[5,1-b][1,3]thiazin-4-one: an unusual [6-5] fused-ring system

The title compound, C₁₈H₁₃FN₂OS, is the first structural example of a [6-5] fused ring incorporating the 2,3-dihydro-4H-imidazo[5,1-b][1,3]thiazin-4-one molecular scaffold. The six-membered 2,3-dihydro-1,3-thiazin-4-one ring adopts an envelope conformation, with the S-CH₂ C atom displaced by 0.761 (2) Å from the five-atom plane (all within 0.05 Å of the mean plane). The imidazole ring is planar. The phenyl ring is twisted from coplanarity with the imidazole ring by 23.84 (5)° and the 4-fluorophenyl ring is twisted by 53.36 (6)°, due to a close C(aryl)-H...O=C contact with the thiazin-4-one carbonyl O atom. The primary intermolecular interaction involves a CH₂ group with the F atom [C...F = 3.256 (2) Å and C-H...F = 137°]

Bootstrapped CNNs for Building Segmentation on RGB-D Aerial Imagery

Detection of buildings and other objects from aerial images has various applications in urban planning and map making. Automated building detection from aerial imagery is a challenging task, as it is prone to varying lighting conditions, shadows and occlusions. Convolutional Neural Networks (CNNs) are robust against some of these variations, although they fail to distinguish easy and difficult examples. We train a detection algorithm from RGB-D images to obtain a segmented mask by using the CNN architecture DenseNet.First, we improve the performance of the model by applying a statistical re-sampling technique called Bootstrapping and demonstrate that more informative examples are retained. Second, the proposed method outperforms the non-bootstrapped version by utilizing only one-sixth of the original training data and it obtains a precision-recall break-even of 95.10% on our aerial imagery dataset.Comment: Published at ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Science

Reversible Embedding to Covers Full of Boundaries

In reversible data embedding, to avoid overflow and underflow problem, before data embedding, boundary pixels are recorded as side information, which may be losslessly compressed. The existing algorithms often assume that a natural image has little boundary pixels so that the size of side information is small. Accordingly, a relatively high pure payload could be achieved. However, there actually may exist a lot of boundary pixels in a natural image, implying that, the size of side information could be very large. Therefore, when to directly use the existing algorithms, the pure embedding capacity may be not sufficient. In order to address this problem, in this paper, we present a new and efficient framework to reversible data embedding in images that have lots of boundary pixels. The core idea is to losslessly preprocess boundary pixels so that it can significantly reduce the side information. Experimental results have shown the superiority and applicability of our work

Use of modern educational technologies and standardization of control by the department of general dentistry of OMU IHU in order to improve the quality of training of dentists

In the implementation of the strategy of Ukraine's integration into the European Union, one of the directions of the higher educational establishments in general and higher medical educational institutions in particular is the introduction of a system of integrated licensed examinations with a university-independent assessment of knowledge according to state standards. The results of the licensed exam allow you to get an objective picture of the level of theoretical training of graduate students, and the integral exam Krok-2 is a progressive form in the work of a higher medical school. The authors cover aspects of improving the educational process at the Department of General Dentistry. The implemented methods of teaching allowed to combine theoretical training of students for the practical training of their practical skills; made more interesting and clear independent non-auditing work of students; gave teachers the ability to control the quality of this work. It allows to improve the quality of preparation of students-dentists both for final examinations, and for the further professional activity

Polymer-Encapsulated Halide Perovskite Color Converters

An easy process to fabricate highly luminescent and color-pure polymer-encapsulated halide perovskite color converters is reported. Methylammonium lead bromide (MAPbBr3) with an additive of amantadine hydrochloride is prepared by dry mechanochemical synthesis together with an encapsulating polymer. (In this report, poly(methyl methacrylate), polystyrene, and polyethylene oxide are investigated.) The composite material is heated and pressed into a thin disk exhibiting strong luminescent properties. By adjusting the weight percentage of the perovskite in the polymer, the disk can be opaque or transmissive. The disks are stable in air for over 2 months. By inserting a secondary emitter, white light can be obtained by illuminating it with a blue light source

Optimal Taxation of Risky Human Capital

In a model with ex-ante homogenous households, earnings risk and a general earnings function, we derive the optimal linear labor tax rate and optimal linear education subsidies. The optimal income tax trades off social insurance against incentives to work and to invest in human capital. Education subsidies are not used for social insurance, but are only targeted at off-setting the distortions of the labor tax and internalizing a fiscal externality. Both optimal education subsidies and tax rates increase if labor and education are more complementary, since education subsidies indirectly lower labor tax distortions by stimulating labor supply. Optimal education subsidies (taxes) also correct non-tax distortions arising from missing insurance markets. Education subsidies internalize a positive (negative) fiscal externality if there is underinvestment (overinvestment) in education due to risk. Education policy unambiguously allows for more social insurance if education is a risky activity. However, if education hedges against labor market risk, optimal tax rates could be lower than without education subsidies