Reversible data embedding into images using wavelet techniques and sorting.

The proliferation of digital information in our society has enticed a lot of research into data-embedding techniques that add information to digital content, like images, audio, and video. In this paper, we investigate high-capacity lossless data-embedding methods that allow one to embed large amounts of data into digital images (or video) in such a way that the original image can be reconstructed from the watermarked image. We present two new techniques: one based on least significant bit prediction and Sweldens' lifting scheme and another that is an improvement of Tian's technique of difference expansion. The new techniques are then compared with various existing embedding methods by looking at capacity-distortion behavior and capacity control.     

The combination of CRISPR-MVLST and PFGE provides increased discriminatory power for differentiating human clinical isolates of Salmonella enterica subsp. enterica serovar Enteritidis

Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) is a major cause of foodborne salmonellosis. Rapid, efficient and accurate methods for identification are required to track specific strains of S. Enteritidis during outbreaks of human salmonellosis. By exploiting the hypervariable nature of virulence genes and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs), we previously developed a powerful sequence-based subtyping approach, designated CRISPR-MVLST. To substantiate the applicability of CRISPR-MVLST, we analyzed a broad set of S. Enteritidis isolates collected over a six-year period. Among 141 isolates we defined 22 Enteritidis Sequence Types (ESTs), the majority of which were novel. Notably, strains exhibiting the common PFGE pattern, JEGX01.0004 (characteristic of ∼40% of S. Enteritidis isolates in the United States), were separated into twelve distinct sequence types. Conversely, isolates of EST4, the most predominant EST we observed, comprised eight different PFGE patterns. Importantly, we showed that some genotypes that were previously associated with the food supply chain at the farm level have now been identified in clinical samples.     

Water hammer reduces fouling during natural water ultrafiltration

Today’s ultrafiltration processes use permeate flow reversal to remove fouling deposits on the feed side of ultrafiltration membranes. We report an as effective method: the opening and rapid closing of a valve on the permeate side of an ultrafiltration module. The sudden valve closure generates pressure fluctuations due to fluid inertia and is commonly known as “water hammer”. Surface water was filtrated in hollow fiber ultrafiltration membranes with a small (5%) crossflow. Filtration experiments above sustainable flux levels (>125 l (m²h)⁻¹) show that a periodic closure of a valve on the permeate side improves filtration performance as a consequence of reduced fouling. It was shown that this effect depends on flux and actuation frequency of the valve. The time period that the valve was closed proved to have no effect on filtration performance. The pressure fluctuations generated by the sudden stop in fluid motion due to the valve closure are responsible for the effect of fouling reduction. High frequency recording of the dynamic pressure evolution shows water hammer related pressure fluctuations to occur in the order of 0.1 bar. The pressure fluctuations were higher at higher fluxes (higher velocities) which is in agreement with the theory. They were also more effective at higher fluxes with respect to fouling mitigation.     

Towards a Guideline for Design of a Corporate Entrepreneurship Function for Business Development in Medium‐Sized Technology‐Based Companies

The speed with which global high‐technology markets evolve makes companies recognize that an effective innovation process is the best way to guarantee competitiveness. However, when (medium‐sized) companies then wish to set up a corporate entrepreneurship function to enhance business development processes, they can find little material available in literature to assist in such processes. In this article we have described a guideline and some backgrounds for creating a corporate entrepreneurship function to realize business development in a high‐tech context.     

Computationally efficient analysis of cable-stayed bridge for GA-based optimization

Optimum design of a cable-stayed bridge structure is very complicated because of large number of design variables. Use of genetic algorithms (GAs) in optimizing such structure consumes significant computational time. Due to nonlinearity, structural analysis itself takes considerable computational time and the genetic algorithm has to perform a large number of iterations in order to obtain global minima. A new approach combining GA and support vector machine (SVM) has been adopted. This drastically reduces the computation time of optimization. The genetic algorithm is employed to obtain the minimum cost of the cable-stayed bridge. Constraint evaluation is done using SVM which is trained by a data base generated through FEM analysis. System level optimization is carried out considering configuration and cross-sectional parameters as design variables. In the present study, optimization was carried out for bridge lengths ranging from 100 to 500 m. Final optimum designs were reanalyzed to check the adequacy of the developed approach.     

Support vector machine based aerodynamic analysis of cable stayed bridges

Flutter, a self-excited vibration resulting from the interaction between structural motion and aerodynamic force, is the major aspect in wind resistant design of cable stayed bridges. The critical speed for flutter of a deck section can be evaluated using the flutter derivatives obtained by sectional model testing of the bridge deck in a wind tunnel. Since it is very expensive, time consuming and laborious to conduct wind tunnel tests for all the practical dimensions of deck, the support vector machine (SVM) is applied for predicting the flutter derivatives for any deck size. The wind tunnel experimental data is collected from literature and SVM is trained. Thus predicted flutter derivatives are used for estimation of critical flutter velocity of cable stayed bridges. The effect of each aerodynamic derivative on flutter instability is investigated in this study.     

Nonlinear Discrete Wavelet Transforms over Finite Sets and an Application to Binary Image Compression

The discrete wavelet transform was originally a linear operator that works on signals that are modeled as functions from the integers into the real or complex numbers. However, many signals have discrete function values. This paper builds on two recent developments: the extension of the discrete wavelet transform to finite-valued signals and the research of nonlinear wavelet transforms triggered by the introduction of the lifting scheme by Sweldens. It defines discrete wavelet transforms as bijective, translation-invariant decompositions of signals that are functions from the integers into any finite set. Such transforms are essentially nonlinear, but they can be calculated very time efficiently since only discrete arithmetic is needed. Properties of these generalized discrete wavelet transforms are given along with an elaborate example of such a transform. In addition, the paper presents some ideas to find explicit examples of discrete wavelet transforms over finite sets. These ideas are used to show that, in case the finite set is a ring, there are much more nonlinear transforms than linear transforms. Finally, the paper exploits this increased number of transforms to do lossless compression of binary images.The research is sponsored (grant no. 613.006.570) by the Dutch Science Foundation (NWO).