Watermark detection with zero-knowledge disclosure

Watermarking schemes embed information imperceptibly in digital objects and are proposed as primitives in various copyright protection applications, such as proofs of authorship, dispute resolving protocols or fingerprinting. In many applications, the presence of watermarks must be provable to any possibly dishonest party. Traditionally, watermark detection requires knowledge of sensitive information like the watermark or the embedding key. This is a major security risk, since this information is in most cases sufficient to remove the watermark and to defeat the goal of copyright protection. Zero-knowledge watermark detection is a promising approach to overcome security issues during the process of watermark detection: cryptographic techniques are used to prove that a watermark is detectable in certain data, without jeopardizing the watermark. This paper presents a formal definition of zero-knowledge watermark detection, discusses zero-knowledge watermark detection protocols and compares their properties.     

A fast wavelet-based moment method for solving thin-wire EFIE

Solving the thin-wire electric field integral equation (EFIE) by the multiresolution wavelet expansion method involves a time-consuming double numerical integration for each nonzero element of the moment matrix which in turn can outweigh the advantages of achieving a sparse matrix. To speed up the matrix fill process in wavelet-based moment method codes, first, the triangular scaling functions of a nonorthogonal piecewise liner wavelet at the finest spatial resolution are appropriately replaced by sinusoidal dipoles for which mutual impedances are available in closed-form analytical expressions. The fast wavelet bases transform is then exploited to effectively transfer the resultant matrix equation to multiresolution wavelet domain. Numerical results obtained by the compactly supported semi-orthogonal linear B-spline wavelet demonstrate dramatic reduction of the overall solution time without any degradation in the accuracy of the final solution.     

Model Selection by Predictive Validation

: Gaussian mixture modelling is used to provide a semi-parametric density estimate for a given data set. The fundamental problem with this approach is that the number of mixtures required to adequately describe the data is not known in advance. In our previous work , we described an algorithm, termed Predictive Validation, which attempted to automatically select the number of components. The aim of this paper is to investigate the influence of the various parameters in our model selection method in order to develop it into an operational tool. In this paper, we demonstrate the successful application of model validation to three applications in which the selected models are used for supervised classification, unsupervised classification and outlier detection tasks. Received: 23 Novenber 2000, Received in revised form: 24 April 2001, Accepted: 21 May 2001     

Study on novel poly (vinyl pyrrolidone) doped MWCNTs/polyrhodanine nanocomposites: Synthesis,characterization, and thermal performance

In this paper, poly (vinyl pyrrolidone) (PVP) doped multiwall carbon nanotubes (MWCNTs/polyrhodanine), were synthesized through one-step chemical oxidative polymerization of rhodanine monomers on the surface-modified carbon nanotubes. Characterization of MWCNTs/polyrhodanine was conducted by using scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transforms infrared spectroscopy (FT-IR), X-ray diffraction (XRD), and EDX spectrum analyses in which the results confirmed the successful formation of MWCNTs/polyrhodanine. In addition, to investigate the thermal properties of samples, thermogravimetric analysis (TGA) was employed, and results exhibited significant improvement in the nanocomposite thermal stability due to the addition of MWCNTs with reinforcement effect in polymer matrix.     

Organometallic Bonding in an Ullmann‐Type On‐Surface Chemical Reaction Studied by High‐Resolution Atomic Force Microscopy

The on‐surface Ullmann‐type chemical reaction synthesizes polymers by linking carbons of adjacent molecules on solid surfaces. Although an organometallic compound is recently identified as the reaction intermediate, little is known about the detailed structure of the bonded organometallic species and its influence on the molecule and the reaction. Herein atomic force microscopy at low temperature is used to study the reaction with 3,9‐diiododinaphtho[2,3‐b:2′,3′‐d]thiophene (I‐DNT‐VW), which is polymerized on Ag(111) in vacuum. Thermally sublimated I‐DNT‐VW picks up a Ag surface atom, forming a C? Ag bond at one end after removing an iodine. The C? Ag bond is usually short‐lived, and a C? Ag? C organometallic bond immediately forms with an adjacent molecule. The existence of the bonded Ag atoms strongly affects the bending angle and adsorption height of the molecular unit. Density functional theory calculations reveal the bending mechanism, which reveals that charge from the terminus of the molecule is transferred via the Ag atom into the organometallic bond and strengths the local adsorption to the substrate. Such deformations vanish when the Ag atoms are removed by annealing and C? C bonds are established.     

ARO: A new model free optimization algorithm for real time applications inspired by the asexual reproduction

This paper presents a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as asexual reproduction optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem; this leads to the fitter individual. ARO adaptive search ability along with its strength and weakness points are fully described in the paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of an improved genetic algorithm (GA). Results of simulation illustrate that ARO remarkably outperforms GA.     

Development of degradation model for urban asphalt pavement

There is a lack of a profound understanding of urban pavement deterioration pattern. This is due to the complexity of traffic conditions and the variety of pavement structures in urban roads. The lack of a suitable deterioration model for the urban pavements limits the possibility of making any scientific and cost-effective repair and maintenance strategy. There is a need for a better understanding of the long-term behaviour of urban pavements by which predictive pavement condition models can be derived and consequently a suitable maintenance management system can be built. In response to this need, a comprehensive field study was performed in three Iranian cosmopolitan cities. Pervasive pavement damages were defined and an urban pavement condition index was established. A deterioration model was developed by monitoring and analysing the conditions of road pavements in a period of four years. This model varies as the structural and loading conditions of the pavement change. The efficiency and practicability of the model in predicting the conditions of the pavements were illustrated.     

Photoconductive optically driven deformable membrane for spatial light modulator applications utilizing GaAs substrates

The fabrication and characterization of an optically addressable deformable mirror for a spatial light modulator is described. Device operation utilizes an electrostatically driven pixellated aluminized polymeric membrane mirror supported above an optically controlled photoconductive GaAs substrate. A 5 microm thick grid of patterned photoresist supports the 2 microm thick aluminized Mylar membrane. A conductive ZnO layer is placed on the back side of the GaAs wafer. A standard Michelson interferometer is used to measure mirror deformation data as a function of illumination, applied voltage, and frequency. A simplified analysis of device operation is also presented.     

A 0.2-W Heterostructure Barrier Varactor Frequency Tripler at 113 GHz

We present a high-power InAlAs/InGaAs/InP heterostructure barrier varactor (HBV) frequency tripler. The HBV device topology was designed for efficient thermal dissipation and high efficiency. To verify simulations, the device was flip-chip soldered onto embedding microstrip circuitry on an aluminum nitride substrate. This hybrid circuit was then mounted in a waveguide block without any movable tuners. From the resulting RF measurements, the maximum output power was 195 mW at 113 GHz, with a conversion efficiency of 15%. The measured 3-dB bandwidth was 1.5%     

Triiodide PVC membrane electrodes based on charge-transfer complexes

Three new electrodes were prepared by incorporating two different charge-transfer complexes and amino crown ether into plasticized PVC membranes. The electrodes showed Nernstian response to triiodide ion over the activity range from 1.0 x 10(-5) to 1.0 x 10(-1) mol x L(-1) with detection limits at approximately 1.0 x 10(-6) mol x L(-1). The resulting electrodes have fast response times (20-30 s) and good stabilities (4 months) and can be used over a wide pH range of 2.5-9.0. The proposed electrodes exhibit anti-Hofmeister behavior with excellent selectivity toward triiodide ion against a wide range of common interferences. Comparative study suggests that amino (aza) crown ether alone or in the form of a charge-transfer complex with iodine, as an ionophore in a PVC liquid membrane, is sensitive to triiodide ion. The electrodes were used as indicator electrodes in potentiometric titration of triiodide ion against thiosulfate ion.