Effect of Powder Processing and Sintering Conditions on the Microstructural,Thermal, and Mechanical Properties of Reticulated Zinc Oxide Ceramic Foams

Ceramic foams are made of zinc oxide using different amounts of Sb₂O₃ and Bi₂O₃ as sintering aids. The effect of a ball milling processing of the starting powders and the sintering temperature on the microstructure and the properties of the ZnO foams is investigated. The focus is set on the evolution of the secondary phases formed within the microstructure of ZnO. A determining effect is identified in the amount of an Al₂O₃ impurity which is introduced by abrasion of the milling vessels during ball milling. Alumina is partially dissolved in a spinel α–Zn₇Sb₂O₁₂ secondary phase which is stabilized by a reduction of the unit cell volume. Remaining Al₂O₃ is incorporated into zinc oxide under formation of a defect wurtzite phase. The phase evolution is a complex function of the content of sintering aids, the Al₂O₃ impurity level and the sintering temperature. The shrinkage during sintering and the porosity evolution are correlated to the phase composition within the ZnO material. The thermal conductivity and the compressive strength of the foams are determined, normalized with respect to their porosity, and correlated to the microstructure and phase composition of the ZnO strut material.     

Making scanned Arabic documents machine accessible using an ensemble of SVM classifiers

International Journal on Document Analysis and Recognition (IJDAR) - Raster-image PDF files originating from scanning or photographing paper documents are inaccessible to both text search engines...     

Salient Object Subitizing

We study the problem of salient object subitizing, i.e. predicting the existence and the number of salient objects in an image using holistic cues. This task is inspired by the ability of people to quickly and accurately identify the number of items within the subitizing range (1–4). To this end, we present a salient object subitizing image dataset of about 14 K everyday images which are annotated using an online crowdsourcing marketplace. We show that using an end-to-end trained convolutional neural network (CNN) model, we achieve prediction accuracy comparable to human performance in identifying images with zero or one salient object. For images with multiple salient objects, our model also provides significantly better than chance performance without requiring any localization process. Moreover, we propose a method to improve the training of the CNN subitizing model by leveraging synthetic images. In experiments, we demonstrate the accuracy and generalizability of our CNN subitizing model and its applications in salient object detection and image retrieval.     

Biocatalytic Synthesis of Nitriles through Dehydration of Aldoximes: The Substrate Scope of Aldoxime Dehydratases

Nitriles, which are mostly needed and produced by the chemical industry, play a major role in various industry segments, ranging from high‐volume, low‐price sectors, such as polymers, to low‐volume, high‐price sectors, such as chiral pharma drugs. A common industrial technology for nitrile production is ammoxidation as a gas‐phase reaction at high temperature. Further popular approaches are substitution or addition reactions with hydrogen cyanide or derivatives thereof. A major drawback, however, is the very high toxicity of cyanide. Recently, as a synthetic alternative, a novel enzymatic approach towards nitriles has been developed with aldoxime dehydratases, which are capable of converting an aldoxime in one step through dehydration into nitriles. Because the aldoxime substrates are easily accessible, this route is of high interest for synthetic purposes. However, whenever a novel method is developed for organic synthesis, it raises the question of substrate scope as one of the key criteria for application as a “synthetic platform technology”. Thus, the scope of this review is to give an overview of the current state of the substrate scope of this enzymatic method for synthesizing nitriles with aldoxime dehydratases. As a recently emerging enzyme class, a range of substrates has already been studied so far, comprising nonchiral and chiral aldoximes. This enzyme class of aldoxime dehydratases shows a broad substrate tolerance and accepts aliphatic and aromatic aldoximes, as well as arylaliphatic aldoximes. Furthermore, aldoximes with a stereogenic center are also recognized and high enantioselectivities are found for 2‐arylpropylaldoximes, in particular. It is further noteworthy that the enantiopreference depends on the E and Z isomers. Thus, opposite enantiomers are accessible from the same racemic aldehyde and the same enzyme.     

Piecemeal Learning of an Unknown Environment

We introduce a new learning problem: learning a graph bypiecemeal search, in which the learner must return every so often to its starting point (for refueling, say). We present two linear-time piecemeal-search algorithms for learningcity-block graphs: grid graphs with rectangular obstacles.     

Special-Purpose AC Converter Systems for Constant Horsepower Applications

The ac converter system discussed involves a design concept that results in a total cost that is competitive with dc converter systems when applied to specific application requirements. The particular application used as a reference is the limited speed range, constant horsepower grinder. This application may be satisfied by a constant voltage, adjustable frequency converter, and motor combination. First, the application requirements are presented. Next, the discussion covers satisfaction of these requirements by means of specific design as to minimize cost. Finally, other unusual aspects of the system are presented, such as the method of modifying the motor voltage during acceleration, the requirement for high voltage output, and a unique packaging design to satisfy the severe ambient conditions of the application.     

Using kernels for a video-based mouse-replacement interface

Some people cannot use their hands to control a computer mouse due to conditions such as cerebral palsy or multiple sclerosis. For these individuals, there are various mouse-replacement solutions. One approach is to enable them to control the mouse pointer using head motions captured with a web camera. One such system, the Camera Mouse, uses an optical flow approach to track a manually-selected small patch of the subject’s face, such as the nostril or the edge of the eyebrow. The optical flow tracker may lose the facial feature when the tracked image patch drifts away from the initially-selected feature or when a user makes a rapid head movement. To address the problem of feature loss, we developed and incorporated the Kernel-Subset-Tracker into the Camera Mouse. The Kernel-Subset-Tracker is an exemplar-based method that uses a training set of representative images to produce online templates for positional tracking. We designed the augmented Camera Mouse so that it can compute these templates in real time, employing kernel techniques traditionally used for classification. We propose three versions of the Kernel-Subset-Tracker, each using a different kernel, and compared their performance to the optical-flow tracker under five different experimental conditions. Our experiments with test subjects show that augmenting the Camera Mouse with the Kernel-Subset-Tracker improves communication bandwidth statistically significantly. Tracking of facial features was accurate, without feature drift, even during rapid head movements and extreme head orientations. We conclude by describing how the Camera Mouse augmented with the Kernel-Subset-Tracker enabled a stroke-victim with severe motion impairments to communicate via an on-screen keyboard.