Relevance feedback for CBIR: a new approach based on probabilistic feature weighting with positive and negative examples.

In content-based image retrieval, understanding the user's needs is a challenging task that requires integrating him in the process of retrieval. Relevance feedback (RF) has proven to be an effective tool for taking the user's judgement into account. In this paper, we present a new RF framework based on a feature selection algorithm that nicely combines the advantages of a probabilistic formulation with those of using both the positive example (PE) and the negative example (NE). Through interaction with the user, our algorithm learns the importance he assigns to image features, and then applies the results obtained to define similarity measures that correspond better to his judgement. The use of the NE allows images undesired by the user to be discarded, thereby improving retrieval accuracy. As for the probabilistic formulation of the problem, it presents a multitude of advantages and opens the door to more modeling possibilities that achieve a good feature selection. It makes it possible to cluster the query data into classes, choose the probability law that best models each class, model missing data, and support queries with multiple PE and/or NE classes. The basic principle of our algorithm is to assign more importance to features with a high likelihood and those which distinguish well between PE classes and NE classes. The proposed algorithm was validated separately and in image retrieval context, and the experiments show that it performs a good feature selection and contributes to improving retrieval effectiveness.     

Catalyst surface at a fractal of cost—a quest for optimal catalyst loading

Intuition tells us that any decrease in the catalytically active surface area should result in an equivalent decrease in the reaction yield and efficiency. Our findings counter this by showing that the active surface and hence the catalyst loading can be reduced drastically in the diffusion-limited heterogeneous reaction systems, while the conversion rate remains essentially unchanged by using fractals for spatial distribution of the catalyst load. The results of this study provide an unusual circumstance for optimal design of chemically active surfaces and can be used to drastically reduce cost of heterogeneous chemical and biological reactors, sensors, and electrodes of fuel cells. The proposed approach can be exploited to its fullest extent in chemical microsystems by utilizing the latest advances in our abilities to manipulate matter on the micro/nano scale.     

Reducing aliasing in images: a PDE-based diffusion revisited

In this paper, we introduce a new diffusion algorithm that can be used for reducing aliasing on both step edges and lines. It derives from the diffusion model of Perona and Malik, and works as an adaptive level-curve method in which diffusion is carried out in the normal direction of the gradient for step edges, while the eigenvalues of the Hessian matrix are used for lines. To get sharp images, we use high-pass filters to preserve as much as possible the high frequency content while diffusing. Experimental tests using grayscale and colour images show that our algorithm efficiently reduces aliasing.     

Predictive control of Timed Event Graphs with specifications defined by P-time Event Graphs

The aim of this paper is the predictive control of Timed Event Graphs with specifications defined by P-time Event Graphs. We propose a fixed-point approach which leads to a pseudo-polynomial algorithm. As the performance of the algorithm is crucial in on-line control, we highlight an important case where the resolution of this first algorithm is efficient. The second technique is a space controller on a horizon leading to a strongly polynomial algorithm.     

Increasing image compression rate using steganography

The goal of image compression is to remove the redundancies for minimizing the number of bits required to represent an image while steganography works by embedding the secret data in redundancies of the image in invisibility manner. Our focus in this paper is the improvement of image compression through steganography. Even if the purposes of digital steganography and data compression are by definition contradictory, we use these techniques jointly to compress an image. Hence, two schemes exploring this idea are suggested. The first scheme combines a steganographic algorithm with the baseline DCT-based JPEG, while the second one uses this steganographic algorithm with the DWT-based JPEG. In this study data compression is performed twice. First, we take advantage of energy compaction using JPEG to reduce redundant data. Second, we embed some bit blocks within its subsequent blocks of the same image with steganography. The embedded bits not only increase file size of the compressed image, but also decrease the file size further more. Experimental results show for this promising technique to have wide potential in image coding.     

Tunable TiO2 (anatase and rutile) materials manufactured by mechanical means

Anatase and rutile are two naturally found titanium dioxide phases with attractive dielectric, catalytic, and photo-catalytic characteristics. Anatase and rutile are photo-catalytically active in the UV region, since their band gaps are 3.2 eV and 3.75 eV, respectively. In this work is proposed a cost-effective, easy to launch methodology for modification of the TiO₂ bandgap. Such modifications will make the oxides photo-catalytically active in a wider optical range from the visible wavelengths to an extended UV spectrum. The proposed methodology is based on mechanical means such as mixing and milling. Various ratios of anatase:rutile were investigated and milled from 0 (mixing only) to 50 h using high energy mills. The results on mixing and milling show that it is possible to modify the bandgap of the TiO₂ from 2.53 eV to 4.04 eV. The characterization was conducted by means of X-ray diffraction, Raman spectroscopy, Scanning electron microscopy, and optical spectroscopy.     

Mechanisms of Shear Resistance of Concrete Beams Strengthened in Shear with Externally Bonded FRP

In recent years, numerous investigations have addressed the shear strengthening of reinforced concrete (RC) beams with externally bonded fiber-reinforced polymer (FRP) composites. Despite this research effort, the mechanisms of shear resistance that are developed in such a strengthening system have not yet been fully documented and explained. This clearly inhibits the development of rational and reliable code specifications. This paper aims to contribute to the understanding of the shear resistance mechanisms involved in RC beams strengthened in shear with externally bonded FRP. It is based on results obtained from an experimental program, involving 17 tests, performed on full size T beams, and using a comprehensive and carefully optimized measuring device. The resistance mechanisms are studied by observing the evolution of the behavior of the strengthened beams as the applied loads are increased. The local behavior of the FRP and the transverse steel, in particular in the failure zones, are thoroughly examined. The operative resistance mechanisms are also studied through the load sharing among the concrete, the FRP, and the transverse steel, at increasing levels of applied load.     

Theoretical Study of the Doping Effects of n-type and p-type Silicon on the Surface Plasmon Resonance Using a 2D Grating

Silicon - A theoretical study on the excitation of surface plasmon (SP) through a 2D doping silicon gratingis present. Both n- and p-type doping silicon were used. The doping effects of n -type and...