Active structural health monitoring of composite plates and sandwiches

The aim of presented work is to design, assemble and test a functional system, that is able to reveal damage from impact loading. This is done by monitoring of change of spectral characteristics on a damaged structure that is caused by change of mechanical properties of material or by change of structure’s geometry. Excitation and monitoring of structures was done using piezoelectric patches. Unidirectional composite plate was tested for eigenfrequencies using chirp signal. The eigenfrequencies were compared to results from experiments with an impact hammer and consequently with results from finite element method. Same method of finding eigenfrequencies was used on a different unidirectional composite specimen. Series of impacts were performed. Spectrum of eigenfrequencies was measured on undamaged plate and then after each impact. Measurements of the plate with different level of damage were compared. Following experiments were performed on sandwich materials where more different failures may happen. Set of sandwich beams (cut out from one plate made of two outer composite layers and a foam core) was investigated and subjected to several impacts. Several samples were impacted in the same manner to get comparable results. The impacts were performed with growing impact energy

Mimicking POV-Ray Photorealistic Rendering with Accelerated OpenGL Pipeline

Traditional ray tracing algorithms tend to provide photorealistic results but at high computing costs. Rendering times of minutes or days are not exceptional. On the other side, hardware accelerated OpenGL rendering can provide real-time interaction with virtual environment with unnoticeable rendering times. This paper attempts to bring these two together and attempts to give an answer on the difficulty of implementing real-time photorealistic rendering. The paper presents case study on mimicking of POV-Ray photorealistic rendering with accelerated OpenGL pipeline. The study shows the opportunity to accelerate some photorealistic algorithms by real-time approaches while, on the other side, it locates the parts that are difficult to replace by traditional real-time rendering paradigms. Particularly, it is shown how to implement primary and shadow rays and POV-Ray-like material model using accelerated OpenGL pipeline using modern shader technology. On the other side, the difficulties of reflected and refracted rays implementation using real-time rendering approaches is discussed

A Motion-aware Data Transfers Scheduling for Distributed Virtual Walkthrough Applications

Data transfers scheduling is an important part of almost all distributed virtual walkthrough (DVW) applications. Its main purpose is to preserve data transfer efficiency and render quality during scene exploration. The most limiting factors here are network restrictions such as low bandwidth and high latency. Current scheduling algorithms use multi-resolution data representation, priority determination and data prefetching algorithms to minimize these restrictions. Advanced priority determination and data prefetching methods for DVW applications use mathematic description of motion to predict next position of each individual user. These methods depend on the recent motion of a user so that they can accurately predict only near locations. In the case of sudden but regular changes in user motion direction (road networks) or fast moving user, these algorithms are not sufficient to predict future position with required accuracy and at required distances. In this paper we propose a systematic solution to scheduling of data transfer for DVW applications which uses next location prediction methods to compute download priority or additionally prefetch rendered data in advance. Experiments show that compared to motion functions the proposed scheduling scheme can increase data transfer efficiency and rendered image quality during scene exploration

Big data analysis for media production

A typical high-end film production generates several terabytes of data per day, either as footage from multiple cameras or as background information regarding the set (laser scans, spherical captures, etc). This paper presents solutions to improve the integration of the multiple data sources, and understand their quality and content, which are useful both to support creative decisions on-set (or near it) and enhance the postproduction process. The main cinema specific contributions, tested on a multisource production dataset made publicly available for research purposes, are the monitoring and quality assurance of multicamera set-ups, multisource registration and acceleration of 3-D reconstruction, anthropocentric visual analysis techniques for semantic content annotation, and integrated 2-D-3-D web visualization tools. We discuss as well improvements carried out in basic techniques for acceleration, clustering and visualization, which were necessary to deal with the very large multisource data, and can be applied to other big data problems in diverse application fields. © 1963-2012 IEEE

Improving HOG with image segmentation: application to human detection

In this paper we improve the histogram of oriented gradients (HOG), a core descriptor of state-of-the-art object detection, by the use of higher-level information coming from image segmentation. The idea is to re-weight the descriptor while computing it without increasing its size. The benefits of the proposal are two-fold: (i) to improve the performance of the detector by enriching the descriptor information and (ii) take advantage of the information of image segmentation, which in fact is likely to be used in other stages of the detection system such as candidate generation or refinement. We test our technique in the INRIA person dataset, which was originally developed to test HOG, embedding it in a human detection system. The well-known segmentation method, mean-shift (from smaller to larger super-pixels), and different methods to re-weight the original descriptor (constant, region-luminance, color or texture-dependent) has been evaluated. We achieve performance improvements of 4.47% in detection rate through the use of differences of color between contour pixel neighborhoods as re-weighting function

Fetal head size and effect of manual perineal protection

Cílem studie je vyhodnotit zda dříve identifikovaná modifikace Vídeňské metody manuální perineální protekce je také nejefektivnější pro redukci perineálního napětí v případech s výrazně menší nebo větší hlavičkou plodu.The aim of this study was to evaluate whether a previously identified modification of Viennese method of perineal protection remains most effective for reduction of perineal tension in cases with substantially smaller or larger fetal heads

Housing Price Dynamics and Bubble Risk: The Case of Turkey

Housing prices have increased substantially in some emerging markets in recent years. Turkish housing market has also experienced a boom over the last decade with rapid house price appreciations. This study is the first to employ two different house price indexes to analyze housing bubble in Turkey in two different time periods, 2010:M1–2014:M12 and 2007:M6–2014:M12. We first capture the determinants of housing price by employing Bounds test and then examine whether rising house prices have been justified by fundamentals by employing OLS/FMOLS/DOLS, Kalman filter and ARIMA models. The Bounds test results suggest that there is a long-term cointegration among house price indexes and housing rent, construction cost and real mortgage interest rate. The results imply that the Turkish housing market has experienced some cases of overvaluation, but not bubble formation. This evidence has several implications for house price dynamics and risks in the Turkish housing market. Based on Turkish experience, the study also draws policy implications for emerging housing markets