Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

Smoothing: A natural way to detect contour features

This work presents a dominant point detector. The angles of the contour are characterized through local entropy produced by a rotationally symmetric smoothing. The proposed scheme uses a punctual multi-scale approach in which only the candidates are analyzed in higher scales. To preserve the angle-entropy relationship in higher scales, we propose a smoothing kernel which presents special features that ensure its steepness in every scale. It is built from the sum of two Gaussians with different openings resembling center-surround receptive fields. The outputs of the proposed method are confronted to a ground-truth found in the literature, and to popular boundary based corner detectors that used the same set of images. Results reveal that the proposed detector performs extremely well.     

Binary and m-ary encoding in applications of tree-based genetic algorithms for QoS routing

Ubiquitous and Pervasive Computing (UPC) applications often have Quality of Service (QoS) requirements. These become constraints for the UPC network infrastructure. In this paper, we refer to Mobile ad Hoc Networks, one of the most important technologies supporting UPC, and investigate on Genetic Algorithms (GAs) for QoS routing. GAs are part of the soft computing paradigm and can solve the NP search of QoS routes with multiple constraints. We elaborate on tree-based GAs, which represent the set of paths from source to destination as a tree and encode them through the crossed junctions. While their most well-known applications use m-ary encoding representing single paths in the chromosomes, in this paper we discuss a binary encoding with the objective of improving the convergence speed. The binary encoding represents classes of paths in the chromosomes and allows local search on classes of paths. These classes are both collectively exhaustive and mutually exclusive. Simulation results compare convergence speed and scalability of GA applications with binary and m-ary encoding in networks with an increasing number of nodes and links per node. As the per-class processing is reason of additional computational cost, an hybrid GA application that uses both binary and m-ary encoding is introduced.     

On Efficiency of Multi-job Grid Allocation Based on Statistical Trace Data

The ever growing number of computation-intensive applications calls for utilizing large-scale, potentially interoperable distributed infrastructures. Nowadays, such distributed systems enable the management of heterogeneous scientific workflows of considerable sizes, where job scheduling and resource management is a crucial issue. In this paper we focus on the challenges of scheduling parameter sweep applications, a specific and commonly used type of workflows where ordering of job executions is irrelevant. A parameter sweep has a large set of independent job instances, called a multi-job, submitted for execution in a single step. In order to cope with the high uncertainty and unpredictable load of resources, and the simultaneous submissions of multi-job instances, we propose a statistics-based brokering approach for allocating jobs to resources so that the makespan is minimised. Earlier studies claim that users’ predictions on job runtime are inaccurate and unusable for scheduling. Our aim is to examine, whether statistical trace data for the same purpose is efficient compared to randomized allocation.     

Chaotic fluid mixing by alternating microparticle topologies to enhance biochemical reactions

We report experimental results on chaotic mass transport induced by alternating topological changes of magnetic particle chains actuated by a rotating magnetic field. Results on the induced fluid flows, through particle tracing experiments and mixing experiments, are obtained for (1) the regime of rigid chain rotation and (2) the regime wherein chains periodically fragment and reform. In the case of rigid rotating chains, the overall tracer particle trajectories are steady, slightly modulated circles around the center of the microparticle chains. In the regime of periodic chain breaking and reformation, the tracer particle trajectories become chaotic. The level of mixing is measured by using a mixing index (M) in a water–dye system, i.e., in a perfectly mixed system M = 0, while in an unmixed system M = 1. When particle chains periodically break and reform, we observe that the mixing index M decreases from 1 to 0.1 within 15 rotational cycles. For rigid rotating chains, M reaches a minimum of only 0.5. We also report the effect of the different actuation regimes on a biological binding reaction in the solution and indeed found that the reaction product (at equal actuation time) is significantly enhanced (3 times) by the dynamic chain regime as compared to the rigid chain regime. We conclude that the alternating topological change of microparticle chains—with repetitive chain breakup and chain reformation—is an effective mechanism to achieve chaotic mixing and thereby promote and homogenize reactions in lab-on-a-chip systems.     

A review of the unique features of HDL apoproteins

The human plasma high density lipoproteins (HDL) are a heterogeneous ensemble of five proteins associated with both neutral and polar lipids. The sequences of all five proteins are known. ApoA-I and apoA-II are the major protein components; apoC-I, apoC-II and apoC-III are the minor protein components. All these apoproteins spontaneously recombine with phospholipids to give stable lipid-protein complexes and freely exchange between the two major HDL subclasses, HDL₂ and HDL₃. In addition, ApoC-I, apoC-II, and apoC-III exchange between HDL and very low density lipoproteins. Furthermore, certain HDL apoproteins are activators for plasma enzymes that are important in lipid metabolism. ApoA-I and apoC-I activate lecithin/cholesterol acyltransferase; apoC-II is an activator of lipoprotein lipase. The regions of apoC-I and apoC-II that are involved in the activation of these enzymes have been localized with synthetic peptides. Studies of synthetic and native fragments of apoA-II, apoC-I, apoC-II, and apoC-III as well as model lipid-binding peptides have identified specific regions with structural features common to lipid-binding proteins. These special properties, which include helical potential, sequences with a critical amphipathic length, and high hydrophobicity of the nonpolar side of the amphipathic helix, are the determinants of HDL structure and metabolism.     

Twin-image suppression in digital in-line holography based on wave-front filtering

Pattern Analysis and Applications - Digital holography is an imaging process able to recreate three-dimensional representations of objects from recording pattern interference among distinct waves....     

Recommending multimedia visiting paths in cultural heritage applications

The valorization and promotion of worldwide Cultural Heritage by the adoption of Information and Communication Technologies represent nowadays some of the most important research issues with a large variety of potential applications. This challenge is particularly perceived in the Italian scenario, where the artistic patrimony is one of the most diverse and rich of the world, able to attract millions of visitors every year to monuments, archaeological sites and museums. In this paper, we present a general recommendation framework able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context-aware recommendation techniques supporting intelligent multimedia services for the users—i.e. dynamic visiting paths for a given environment. Specific applications of our system within the cultural heritage domain are proposed by means of real case studies in the mobile environment related both to an outdoor and indoor scenario, together with some results on user’s satisfaction and system accuracy.