Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework

This correspondence presents a novel hybrid wrapper and filter feature selection algorithm for a classification problem using a memetic framework. It incorporates a filter ranking method in the traditional genetic algorithm to improve classification performance and accelerate the search in identifying the core feature subsets. Particularly, the method adds or deletes a feature from a candidate feature subset based on the univariate feature ranking information. This empirical study on commonly used data sets from the University of California, Irvine repository and microarray data sets shows that the proposed method outperforms existing methods in terms of classification accuracy, number of selected features, and computational efficiency. Furthermore, we investigate several major issues of memetic algorithm (MA) to identify a good balance between local search and genetic search so as to maximize search quality and efficiency in the hybrid filter and wrapper MA     

Probe recording technology using novel MEMS devices

In this paper, we present novel micro-electro-mechanical systems (MEMS) devices for unique probe recording technology, where the 1-D cantilever probe array approach requires a small number of cantilever probe tips for a large media platform and hence has higher reliability. The probe storage system is composed of three key MEMS devices: MEMS XY-stage, linear motor and 1-D cantilever probe array with integrated heater. The design and fabrication process of three MEMS devices are given with prototypes. Their performances are discussed with the experimental results. The compact MEMS XY-stage device can be driven with ±20 μm movement, in X- and Y-directions. The miniature linear motor is smoothly driven to move back and forth at the speed of 20 mm/s and step of 150 μm by 150 mA pulse driving current. The indented (writing) bit size of 100 nm on polymer media is achieved by the prototyped cantilever probe tip with integrated heater.     

Automatic learners with feedback queries

Automatic classes are classes of languages for which a finite automaton can decide whether a given element is in a set given by its index. The present work studies the learnability of automatic families by automatic learners which, in each round, output a hypothesis and update a long-term memory, depending on the input datum, via an automatic function. Many variants of automatic learners are investigated: where the long-term memory is restricted to be the current hypothesis whenever this exists, cannot be of length larger than the length of the longest datum seen, or has to consist of a constant number of examples seen so far. Learnability is also studied with respect to queries which reveal information about past data or past computation history; the number of queries per round is bounded by a constant.     

An Internet-enabled image- and model-based virtual machining system

Virtual reality (VR) can be described as a four-dimensional (4-D) simulation of the real world, including the 3-D geometry space, 1-D time and the immersive or semi-immersive interaction interface. VR applications in mechanical-related research areas are becoming popular, e.g. virtual layout design, virtual prototyping, Internet-based virtual manufacturing, etc. However, research in VR applications is facing conflicting requirements for high rendering quality and near real-time interactivity. This paper represents an Internet-based virtual machining system that builds an integrated VR scene, which combines images and models, to overcome the above conflicts. This research is divided into three parts: first, image mosaics techniques are used to implement an Internet-based virtual workshop, which is an image-based virtual scene. The method of obtaining original sequential images, the principle of image mosaics to realize automatic seamless stitching, and projection transformation matrices to reconstruct a closed inward-facing space are presented. Secondly, a model-based virtual milling machine has been constructed with three detailed approaches: a category-based dynamic graph structure to support collision detection, a relation-oriented collision detection method to improve the efficiency of collision detection, and a dynamic modelling method to model a dynamic workpiece object. Finally, an Internet-based virtual milling system, which is the integration of the image-based virtual workshop and the model-based virtual CNC machine, is constructed using the reposition method to achieve visual consistency of the virtual objects and images. This system, which includes an integrated scene, combines the advantages of image-based VR and model-based VR. Consequently, this system has both high rendering quality and good real-time interactivity.     

Halogen-induced charge transfer polymerization of pyrrole in aqueous media

Simultaneous polymerization and doping of pyrrole have been carried out in the presence of a halogenic electron acceptor, bromine (Br₂) or iodine (I₂), in aqueous dispersion or in a two-phase solvent system. The morphology of the polypyrrole (PPY) so produced is granular and porous. The electrical conductivity of the PPY-I₂ charge transfer (CT) complex is of the order of 10¹ ohm⁻¹ cm⁻¹ while that of the PPY-Br₂ complex is about one order of magnitude less. Both complexes are stable in the atmosphere. The physicochemical properties of the PPY-I₂ and PPY-Br₂ CT complexes prepared under various experimental conditions are examined in detail.     

Analytical evaluation of aircraft operational risks from runway rutting

Runway surface distortions such as rutting allow water to accumulate on the runway surface which may cause aircraft operational risks related to hydroplaning and loss of friction. This may increase the runway excursion risk during wet weather conditions. Several standards relating to airfield pavement maintenance have documented that rutting can cause safety hazards to aircrafts due to hydroplaning risk. This paper proposes an analytical approach to evaluate the hydroplaning potential for aircrafts due to the flooded ruts of a runway pavement and evaluate the operational risk. A finite element model is developed to simulate aircraft tyre hydroplaning under given set of operating conditions. By performing this evaluation for different rut depths, an assessment of the relative severity levels of different rut depths with respect to hydroplaning can be made. A numerical example is presented to illustrate the application of the procedure to evaluate operational risks to aircraft from runway rutting.     

DynaMICs: Comprehensive Support for Run-Time Monitoring

Software engineering strives to enable the economic construction of software systems that behave reliably, predictably, and safely. In other engineering disciplines, safety is assured in part by detailed monitoring of processes. In software, we may achieve some level of confidence in the operation of programs by monitoring their execution. DynaMICs is a software tool that facilitates the collection and use of constraints for software systems. In addition, it supports traceability by mapping constraints to system artifacts. Constraint specifications are stored separately from code; constraint-monitoring code is automatically generated from the specifications and inserted into the program at appropriate places; and constraints are verified at execution time. These constraint checks are triggered by changes made to variable values. We describe the architecture of DynaMICs, discuss alternative verification techniques, and outline research directions for the DynaMICs project.     

Mastering Surface Reconstruction of Metastable Spinel Oxides for Better Water Oxidation

Developing highly active electrocatalysts for oxygen evolution reaction (OER) is critical for the effectiveness of water splitting. Low‐cost spinel oxides have attracted increasing interest as alternatives to noble metal–based OER catalysts. A rational design of spinel catalysts can be guided by studying the structural/elemental properties that determine the reaction mechanism and activity. Here, using density functional theory (DFT) calculations, it is found that the relative position of O p‐band and M_Oh (Co and Ni in octahedron) d‐band center in ZnCo_2?xNi_xO₄ (x = 0–2) correlates with its stability as well as the possibility for lattice oxygen to participate in OER. Therefore, it is testified by synthesizing ZnCo_2?xNi_xO₄ spinel oxides, investigating their OER performance and surface evolution. Stable ZnCo_2?xNi_xO₄ (x = 0–0.4) follows adsorbate evolving mechanism under OER conditions. Lattice oxygen participates in the OER of metastable ZnCo_2?xNi_xO₄ (x = 0.6, 0.8) which gives rise to continuously formed oxyhydroxide as surface‐active species and consequently enhances activity. ZnCo_1.2Ni_0.8O₄ exhibits performance superior to the benchmarked IrO₂. This work illuminates the design of highly active metastable spinel electrocatalysts through the prediction of the reaction mechanism and OER activity by determining the relative positions of the O p‐band and the M_Oh d‐band center.     

Prenatal development of intrafetal and maternal-fetal synchrony.

Fetal and maternal data were monitored serially at 6 gestational ages from 20 to 38 weeks in 195 Peruvian fetuses. Digitized data included fetal heart rate and motor activity, as well as maternal heart rate and electrodermal conductance. Time series analysis evaluated the development of synchrony in 2 streams of fetal functioning and between mothers and fetuses. Intrafetal synchrony between heart rate and motor activity developed in an orderly fashion, with peak cross-correlation approaching an asymptote at 5 s at 28 weeks. Synchrony was not observed between fetal heart rate and maternal measures. Fetal motor activity exhibited synchrony with both maternal electrodermal and heart rate activity. Implications for revealing fundamental properties of neural development prior to birth are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prefrontal cortical projections to the hypothalamus in macaque monkeys

The organization of projections from the macaque orbital and medial prefrontal cortex (OMPFC) to the hypothalamus and related regions of the diencephalon and midbrain was studied with retrograde and anterograde tracing techniques. Almost all of the prefrontal cortical projections to the hypothalamus arise from areas within the "medial prefrontal network," as defined previously by Carmichael and Price ([1996] J. Comp. Neurol. 371:179-207). Outside of the OMPFC, only a few neurons in the temporal pole, anterior cingulate and insular cortex project to the hypothalamus. Axons from the OMPFC also innervate the basal forebrain, zona incerta, and ventral midbrain. Within the medial prefrontal network, different regions project to distinct parts of the hypothalamus. The medial wall areas 25 and 32 send the heaviest projections to the hypothalamus; axons from these areas are especially concentrated in the anterior hypothalamic area and the ventromedial hypothalamic nucleus. Orbital areas 13a, 12o, and Iai, which are related to the medial prefrontal network, selectively innervate the lateral hypothalamic area, especially its posterior part. The cellular regions of the paraventricular, supraoptic, suprachiasmatic, arcuate, and mammillary nuclei are conspicuously devoid of cortical axons, but many axons abut the borders of these nuclei and may contact dendrites that extend from them. Areas within the orbital prefrontal network on the posterior orbital surface and agranular insula send only weak projections to the posterior lateral hypothalamic area. The rostral orbital surface does not contribute to the cortico-hypothalamic projection.