A New Forgery Image Dataset and its Subjective Evaluation

The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing plat- form with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data

Chromospheric Evershed flow

We studied the chromospheric Evershed flow from filtergrams obtained at nine wavelengths along the Hα profile. We computed line-of-sight velocities based on Becker's cloud model and we determined the components of the flow velocity vector as a function of distance from the center of the sunspot, assuming an axial symmetry of both the spot and the flow. We found that the flow velocity decreases with decreasing height and that the maximum of the velocity shifts towards the inner penumbral boundary. The flow related to some fibrils deviates significantly from the average Evershed flow. The profile of the magnitude of the flow velocity as a function of distance from the spot center, indicates that the velocity attains its maximum value in the downstream part of the flow channels (assumed to have the form of a loop). This behavior can be understood in terms of a critical flow that pass from subsonic to supersonic near the apex of the loop, attains its higher velocity at the downstream part of the loop and finally relaxes to subsonic through a tube shock. We computed the average flow vector from segmented line-of-sight velocity maps, excluding bright or dark fibrils alternatively. We found that the radial component of the velocity does not show a significant difference, but the magnitude of the vertical component of the velocity related to dark fibrils is higher than that related to bright fibrils.

Computational Approaches and Models for Ovarian Ageing: From 2D to 4D

The theme of the work presented in this multi-disciplinary PhD is the development of new computational tools and techniques to study and understand spatio-temporal follicle growth in neonatal mouse ovaries. The female ovary is endowed at birth with a finite, non-renewable supply of oocytes, each enclosed in a layer of supporting somatic (granulosa) cells to form a quiescent follicle. From birth, a steady trickle of follicles initiate growth to maintain a supply of mature oocytes for regular ovulation. Disruption in the regulation of initiation of follicle growth can result in various pathologies, such as premature ovarian failure and polycystic ovary syndrome. The mechanism of regulation of the initiation of follicle growth remains unclear, but may involve inter-follicle signaling via paracrine growth factors. To investigate this hypothesis, a new technique for quantifying and analyzing spatial distributions of quiescent and growing follicles in the adult human has been developed, as an extension of a novel technique previously developed in neonatal mice in our laboratory. As in the mouse study, we have found evidence that in the human ovary neighbouring quiescent follicles inhibit follicle growth, at a small range. This approach has been further extended to cultured neonatal mouse ovaries, which in vitro lack a systemic blood supply, to investigate the relative contributions of inter-follicle paracrine signaling and endocrine growth factor/nutrient signaling to the regulation of initiation of follicle growth. Accurate counts of the numbers of follicles in ovaries are important for a wide variety of studies of ovarian physiology, including investigating the effects of age, toxins, chemotherapeutics, endocrine disruptors and specific genes (knock out/transgenic studies) on follicle formation, endowment and development. Many published studies use frequent sampling of a small number of ovaries (often as few as three) to obtain estimates of the number of follicles. We have tested the validity of this approach by generating 3D spherical simulated ovaries which contain realistic numbers of follicles at different stages and which are realistically positioned within these ovaries. The number and position of follicles is based on real biological data. This model enables us to rapidly ‘virtually’ section the ovary in silico and obtain computer-generated counts of the numbers of follicles in sections at different frequencies, such as one every fifth section (1/5), 1/20 or 1/50. As we know precisely how many follicles each simulated ovary contains, we can compare the accuracy using different sampling frequencies of varying numbers of ovaries. This has enabled us to demonstrate that the error is smaller when infrequent sampling of a large number of ovaries (≥8) is carried out, and that this actually involves analyzing fewer sections overall. We have gone on to generate simulated ovaries from knockout mice, with more or fewer follicles, and can predict how many ovaries are required to make robust comparisons between knockout and control animals. This has shown that biological variability contributes more to counting error than the method of sampling. These simulated ovaries provide a unique resource to model large studies. Currently follicle counts are obtained by fixing and serially sectioning ovaries, and manually counting the follicles in sections. This is laborious and time-consuming. Faster methods of obtaining follicle estimates are required. With the use of confocal microscopy and immunohistochemistry for an oocyte-specific protein, we were able to establish a protocol that allows us to image and computationally reconstruct a whole neonatal mouse ovary in 3D. Follicle number can be estimated rapidly using a stereologic method. The stereologic technique error was estimated using the simulated ovary model, leading to the conclusion that the method can be safely used to obtain rapid estimates of follicle number. The time required can be further reduced by using image processing to detect the stained follicles on the sections. We have developed an algorithmic technique that can instantaneously identify stained oocytes, count them, and calculate their spatial distribution. A fundamental unanswered question is whether follicles move in the ovary, particularly as they grow. This question has arisen from the observation that small follicles tend to be situated close to the ovarian surface, while large ones are closer to the medulla. This question has implications for interfollicle signaling. We have developed a protocol to image the ovary while in culture using timelapse confocal and live lipid stains to visualize the follicles. Results show that small follicles are not moving significantly over a period of 12h. This project can be extended in the future with the use of transgenic mice for GFP tagging, to accurately monitor changes in structures of interest within cultured ovaries

Autopilot spatially-adaptive active contour parameterization for medical image segmentation

In this work, a novel framework for automated, spatially-adaptive adjustment of active contour regularization and data fidelity parameters is proposed and applied for medical image segmentation. The proposed framework is tailored upon the isomorphism observed between these parameters and the eigenvalues of diffusion tensors. Since such eigenvalues reflect the diffusivity of edge regions, we embed this information in regularization and data fidelity parameters by means of entropy-based, spatially-adaptive `heatmaps'. The latter are able to repel an active contour from randomly directed edge regions and guide it towards structured ones. Experiments are conducted on endoscopic as well as mammographic images. The segmentation results demonstrate that the proposed framework bypasses iterations dedicated to false local minima associated with noise, artifacts and inhomogeneities, speeding up contour convergence, whereas it maintains a high segmentation quality

A stochastic approach for dynamic soil-pile interaction under enviromental effects.

The paper deals with a computational stochastic approach for the unilateral contact problem of dynamic soil-pile interaction. Unilateral contact effects due to tensionless soil capacity, soil elastoplastic-fracturing behaviour and gapping are strictly taken into account, as well as environmental effects under uncertainty decreasing the soil resistance. The proposed methodology concerns the treatment of both, the deterministic and the probabilistic problem. The numerical approach concerning the deterministic problem is based on a double discretization, in space by the Finite Element Method combined with Boundary Element Method, and in time, and on nonconvex optimization. Uncertainties concerning the input parameter values are treated by the Monte Carlo method in the probabilistic problem section. Finally, the proposed methodology is applied for a practical case of dynamic soil-pile interaction

Chromospheric Evershed flow

We studied the chromospheric Evershed flow from filtergrams obtained at nine wavelengths along the Hα profile. We computed line-of-sight velocities based on Becker's cloud model and we determined the components of the flow velocity vector as a function of distance from the center of the sunspot, assuming an axial symmetry of both the spot and the flow. We found that the flow velocity decreases with decreasing height and that the maximum of the velocity shifts towards the inner penumbral boundary. The flow related to some fibrils deviates significantly from the average Evershed flow. The profile of the magnitude of the flow velocity as a function of distance from the spot center, indicates that the velocity attains its maximum value in the downstream part of the flow channels (assumed to have the form of a loop). This behavior can be understood in terms of a critical flow that pass from subsonic to supersonic near the apex of the loop, attains its higher velocity at the downstream part of the loop and finally relaxes to subsonic through a tube shock. We computed the average flow vector from segmented line-of-sight velocity maps, excluding bright or dark fibrils alternatively. We found that the radial component of the velocity does not show a significant difference, but the magnitude of the vertical component of the velocity related to dark fibrils is higher than that related to bright fibrils.

Computer-Generated Ovaries to Assist Follicle Counting Experiments

Precise estimation of the number of follicles in ovaries is of key importance in the field of reproductive biology, both from a developmental point of view, where follicle numbers are determined at specific time points, as well as from a therapeutic perspective, determining the adverse effects of environmental toxins and cancer chemotherapeutics on the reproductive system. The two main factors affecting follicle number estimates are the sampling method and the variation in follicle numbers within animals of the same strain, due to biological variability. This study aims at assessing the effect of these two factors, when estimating ovarian follicle numbers of neonatal mice. We developed computer algorithms, which generate models of neonatal mouse ovaries (simulated ovaries), with characteristics derived from experimental measurements already available in the published literature. The simulated ovaries are used to reproduce in-silico counting experiments based on unbiased stereological techniques; the proposed approach provides the necessary number of ovaries and sampling frequency to be used in the experiments given a specific biological variability and a desirable degree of accuracy. The simulated ovary is a novel, versatile tool which can be used in the planning phase of experiments to estimate the expected number of animals and workload, ensuring appropriate statistical power of the resulting measurements. Moreover, the idea of the simulated ovary can be applied to other organs made up of large numbers of individual functional units

Progressive Collapse of Existing RС Structures due to Environmental Effects: A Numerical Approach for Strengthening by Ties

Existing old reinforced concrete (RC) buildings are sometimes subjected to obligatory removal of some structural element‐members, e.g. columns, and so to the risk of a progressive collapse. This happens due to various reasons, which can concern changes of serviceability and requirements, or environmental effects which cause strength degradation etc. In order to avoid such a progressive collapse, a modification of the structural response and a redistribution of internal actions can result to a requirement for strengthening the remaining structure after the removal of the degraded elements. The present study deals with such a case, which concerns the computational analysis of framed RC structures under the removal of some columns and the so‐induced requirement of a strengthening by ties (tension only elements). The unilateral behaviour of these cable‐ties, which can undertake only tension, is strictly considered, and the response of the remaining historic structure strengthened by ties is computed. Finally, in a practical case of a framed RC structure, the effectiveness of the proposed methodology is shown.ABSTRACTS ХІХ МЕЖДУНАРОДНА НАУЧНА КОНФЕРЕНЦИЯ ПО СТРОИТЕЛСТВО И АРХИТЕКТУРА ВСУ'2019 се организира със съдействието на Фонд "Научни изследвания" с договор за съфинансиране № КП‐06‐МНФ/34. Editors: Vanyo Georgiev, Assoc. Prof. PhD Aleksandra Ivanova, Assoc. Prof. PhD artist Ventsislav Stoyanov, Assoc. Prof. PhD Eng. Yulia Ilieva, Assoc. Prof. PhD Architec

A new multistage lattice vector quantization with adaptive subband thresholding for image compression

Lattice vector quantization (LVQ) reduces coding complexity and computation due to its regular structure. A new multistage LVQ (MLVQ) using an adaptive subband thresholding technique is presented and applied to image compression. The technique concentrates on reducing the quantization error of the quantized vectors by "blowing out" the residual quantization errors with an LVQ scale factor. The significant coefficients of each subband are identified using an optimum adaptive thresholding scheme for each subband. A variable length coding procedure using Golomb codes is used to compress the codebook index which produces a very efficient and fast technique for entropy coding. Experimental results using the MLVQ are shown to be significantly better than JPEG 2000 and the recent VQ techniques for various test images