Uniaxial tensile response of microfibre reinforced cement composites

Microfibre reinforced cement composites reinforced with high volume fractions of carbon, steel and polypropylene fibres were tested in uniaxial tension. Composites investigated included those with only one type of fibre (mono-fibre composites) and those with two or more types of fibres (hybrid-fibre composites) in the same mix. Considerable strengthening, toughening and stiffening of the host matrix due to microfibre reinforcement were observed. In the hybrid-fibre composites, different fibres appear to act as additive phases; i.e., they maintain their individual reinforcing capabilities. The composites were also impact tested in uniaxial tension using a newly designed instrumented impact machine. When compared with static test results, considerable sensitivity to stress rate was noted; composites were found to be stronger and tougher under impact and the improvements were more pronounced at higher fibre volume fractions. The potential of these composites for use in thin sheet products and other similar applications is recognized, and the need for continued research is stressed.     

Developmental variations in plasma leptin,leptin soluble receptor and their molar ratio in healthy infants

Background  

Leptin and its soluble receptor (sOB-R) are important to regulation of body composition but there are no data on the developmental variations in these plasma variables and their relationship with body composition measurements,     

Adaptive moving shadow detection and removal by new semi-supervised learning technique

The efficient application of current methods of shadow detection in video is hindered by the difficulty in defining their parameters or models and/or their application domain dependence. This paper presents a new shadow detection and removal method that aims to overcome these inefficiencies. It proposes a semi-supervised learning rule using a new variant of co-training technique for shadow detection and removal in uncontrolled scenes. The new variant both reduces the run-time through a periodical execution of a co-training process according to a novel temporal framework, and generates a more generic prediction model for an accurate classification. The efficiency of the proposed method is shown experimentally on a testbed of videos that were recorded by a static camera and that included several constraints, e.g., dynamic changes in the natural scene and various visual shadow features. The conducted experimental study produced quantitative and qualitative results that highlighted the robustness of our shadow detection method and its accuracy in removing cast shadows. In addition, the practical usefulness of the proposed method was evaluated by integrating it in a Highway Control and Management System software called RoadGuard.     

On line background modeling for moving object segmentation in dynamic scenes

Fast and accurate moving object segmentation in dynamic scenes is the first step in many computer vision applications. In this paper, we propose a new background modeling method for moving object segmentation based on dynamic matrix and spatio-temporal analyses of scenes. Our method copes with some challenges related to this field. A new algorithm is proposed to detect and remove cast shadow. A comparative study by quantitative evaluations shows that the proposed approach can detect foreground robustly and accurately from videos recorded by a static camera and which include several constraints. A Highway Control and Management System called RoadGuard is proposed to show the robustness of our method. In fact, our system has the ability to control highway by detecting strange events that can happen like vehicles suddenly stopped in roads, parked vehicles in emergency zones or even illegal conduct such as going out from the road. Moreover, RoadGuard is capable of managing highways by saving information about the date and time of overloaded roads.     

A dynamic video watermarking algorithm in fast motion areas in the wavelet domain

In this paper, we propose a video watermarking algorithm which embeds different parts of a single watermark into different shots of a video under the wavelet domain. Based on a Motion Activity Analysis, different regions of the original video are separated into perceptually distinct categories according to motion information and region complexity. Thus, the localizations of the watermark are adjusted adaptively in accordance with the human visual system and signal characteristics, which makes them perceptually invisible and less vulnerable to automated removal. In addition, contrary to traditional methods where the watermark remains at a fixed position on the screen, the watermark moves along with moving objects and thus motion artefacts can be avoid. The multi-frame based extraction strategy ensures that the watermark can be correctly recovered from a very short segment of video. Individual frames extracted from the video also contain watermark information. Experimental results show that the inserted watermark is not only less perceptible but also robust against common video processing attacks.     

Improved Interface Conditions for 2<Emphasis Type="Italic">D</Emphasis> Domain Decomposition with Corners: Numerical Applications

This article deals with a local improvement of domain decomposition methods for 2-dimensional elliptic problems for which either the geometry or the domain decomposition presents conical singularities. After explaining the main results of the theoretical analysis carried out in Chniti et al. (Calcolo 45, 2008), the numerical experiments presented in this article confirm the optimality properties of the new interface conditions.     

Prediction of visual attention with deep CNN on artificially degraded videos for studies of attention of patients with Dementia

Multimedia Tools and Applications - Studies of visual attention of patients with Dementia such as Parkinson’s Disease Dementia and Alzheimer Disease is a promising way for non-invasive...     

Fusion of thermal infrared and visible spectra for robust moving object detection

The detection of moving objects is a crucial step for many video surveillance applications whether using a visible camera (VIS) or an infrared (IR) one. In order to profit from both types, several fusion methods were proposed in the literature: low-level fusion, medium-level fusion and high-level fusion. The first one is the most used for moving objects’ detection in IR and VIS spectra. In this paper, we present an overview of the different moving object detection methods in IR and VIS spectra and a state of the art of the low-level fusion techniques. Moreover, we propose a new method for moving object detection using low-level fusion of IR and VIS spectra. In order to evaluate quantitatively and qualitatively our proposed method, three series of experiments were carried out using two well-known datasets namely “OSU Color-Thermal Database” and “INO-Database”; the results of these evaluations show promising results and demonstrate the effectiveness of the proposed method.     

Compositional characteristics and aromatic profile of date palm seeds from seven varieties grown in Tunisia

This paper reports a discrimination study based on the physico‐chemical characteristics, fatty acids and profile of volatile compounds of the seeds from seven date palm varieties (Phoenix dactylifera L.) grown in Tunisia. Date seeds contained 10.49–14.76% moisture; 6.28–11.2% fat (on a dry weight basis); 2.67–12.85% protein; 0.91–6.06% reducing sugar; 0.61–2.98% sucrose and 0.97–1.17% ash. Gas liquid chromatography revealed that the oil fraction of the date palm seeds contained eighteen fatty acids, with oleic acid (30.77–42.50%) and lauric acid (18.51–27.48%) as the main unsaturated and saturated ones. Volatile profile showed differences among varieties. In total, forty‐five compounds were identified, mainly alcohols, aldehydes and unsaturated hydrocarbons ones. This study provides evidence that the seeds of date may be a potential source of valuable nutrients with interesting functionality.