0.27-dB/km attenuation achieved by MSP preform process [opticalfibers]

Mechanically shaped preforms (MSP) have been demonstrated to combine economic non-CVD (chemical vapor deposition) processing and low loss, with a published value of 0.63 dB/km and a size of 30 fkm/preform. Improved processing is proposed which results in a minimum loss of 0.27 dB/km at 1550 nm. Preforms capable of yielding 150 fkm have been produced. Reboiling during preform stretching and fiber pulling is identified as the last remaining problem of the process     

A multiple-switch high-voltage DC-DC converter

Series connection of power devices has evolved into a mature technique and is widely applied in HV DC power systems. Static and dynamic voltage balance is ensured by shunting individual devices with dissipative snubbers. The snubber losses become pronounced for increased operating frequencies and adversely affect power density. Capacitive snubbers do not exhibit these disadvantages, but they require a zero-voltage switching mode. Super-resonant power converters facilitate the principle of zero-voltage switching. A high-voltage DC-DC power converter with multiple series-connected devices is proposed. It allows the application of nondissipating snubbers to assist the voltage sharing between the multiple series-connected devices and lowers turnoff losses. Simulation results obtained with a circuit simulator are validated in an experimental power converter operating with two series-connected devices. The behavior of the series connection is examined for MOSFETs and IGBTs by both experimental work with a 2 kW prototype and computer simulation. Applications can be found in traction and heavy industry, where the soft-switching power converter is directly powered from a high-voltage source     

An improved formalism for quantum computation based on geometric algebra—case study: Grover’s search algorithm

The Grover search algorithm is one of the two key algorithms in the field of quantum computing, and hence it is desirable to represent it in the simplest and most intuitive formalism possible. We show firstly, that Clifford’s geometric algebra, provides a significantly simpler representation than the conventional bra-ket notation, and secondly, that the basis defined by the states of maximum and minimum weight in the Grover search space, allows a simple visualization of the Grover search analogous to the precession of a spin- ${\frac{1}{2}}$ particle. Using this formalism we efficiently solve the exact search problem, as well as easily representing more general search situations. We do not claim the development of an improved algorithm, but show in a tutorial paper that geometric algebra provides extremely compact and elegant expressions with improved clarity for the Grover search algorithm. Being a key algorithm in quantum computing and one of the most studied, it forms an ideal basis for a tutorial on how to elucidate quantum operations in terms of geometric algebra—this is then of interest in extending the applicability of geometric algebra to more complicated problems in fields of quantum computing, quantum decision theory, and quantum information.     

Figure-ground separation by cue integration

This letter presents an improved cue integration approach to reliably separate coherent moving objects from their background scene in video sequences. The proposed method uses a probabilistic framework to unify bottom-up and top-down cues in a parallel, "democratic" fashion. The algorithm makes use of a modified Bayes rule where each pixel's posterior probabilities of figure or ground layer assignment are derived from likelihood models of three bottom-up cues and a prior model provided by a top-down cue. Each cue is treated as independent evidence for figure-ground separation. They compete with and complement each other dynamically by adjusting relative weights from frame to frame according to cue quality measured against the overall integration. At the same time, the likelihood or prior models of individual cues adapt toward the integrated result. These mechanisms enable the system to organize under the influence of visual scene structure without manual intervention. A novel contribution here is the incorporation of a top-down cue. It improves the system's robustness and accuracy and helps handle difficult and ambiguous situations, such as abrupt lighting changes or occlusion among multiple objects. Results on various video sequences are demonstrated and discussed. (Video demos are available at http://organic.usc.edu:8376/ approximately tangx/neco/index.html .).     

Microbiological survey of a South African poultry processing plant

Bacterial populations associated with poultry processing were determined on neck skin samples, equipment surfaces and environmental samples by replicate surveys. Aerobic plate counts, Enterobacteriaceae counts, Enterobacteriaceae counts and Pseudomonas counts were performed by standard procedures and the prevalence of Listeria, presumptive Salmonella and Staphylococcus aureus determined. Statistically significant (P < 0.05) increases in counts of all types of bacteria were obtained on product samples as a result of processing. Although bacterial counts on neck skin samples decreased by 0.3 to 0.4 log CFU g-1 after spray washing of carcasses, subsequent spinchilling and packaging of whole carcasses resulted in 0.7 to 1.2 log CFU g-1 increases. Bacterial numbers on equipment surfaces, however, decreased significantly from the "dirty" to the "clean" areas of the abattoir. Transport cages, "rubber fingers", defeathering curtains, shackles and conveyor belts repeatedly showed aerobic plate counts in excess of 5.0 log CFU 25 cm-2. Aerobic plate counts of scald tank and spinchiller water were 2 log CFU ml-1 higher than those of potable water samples. Bacterial numbers of the air in the "dirty" area were higher than those of the "clean" area. Listeria, presumptive Salmonella and Staphylococcus aureus were isolated from 27.6, 51.7 and 24.1% of all product samples, respectively, and Listeria and Staphylococcus aureus were also isolated from selected equipment surfaces.     

Learning a color distance metric for region-based image segmentation

In this paper we describe an experiment where we studied empirically the application of a learned distance metric to be used as discrimination function for an established color image segmentation algorithm. For this purpose we chose the Mumford–Shah energy functional and the Mahalanobis distance metric. The objective was to test our approach in an objective and quantifiable way on this specific algorithm employing this particular distance model, without making generalization claims. The empirical validation of the results was performed in two experiments: one applying the resulting segmentation method on a subset of the Berkeley Image Database, an exemplar image set possessing ground-truths and validating the results against the ground-truths using two well-known inter-cluster validation methods, namely, the Rand and BGM indexes, and another experiment using images of the same context divided into training and testing set, where the distance metric is learned from the training set and then applied to segment all the images. The obtained results suggest that the use of the specified learned distance metric provides better and more robust segmentations, even if no other modification of the segmentation algorithm is performed.