Thermal and flammability properties of a silica–poly(methylmethacrylate) nanocomposite

PMMA, poly(metheylmethacrylate), nanocomposites were made by in situ radical polymerization of MMA, methylmethacrylate, with colloidal silica (ca. 12 nm) to study the effects of nanoscale silica particles on the physical properties and flammability properties of PMMA. Transparent samples resulted and the dispersity of the particles was examined by transmission electron microscopy and atomic force microscopy. The addition of nanosilica particles (13% by mass) did not significantly change the thermal stability, but it made a small improvement in modulus, and it reduced the peak heat release rate roughly 50%. Last, the flame‐retardant mechanism provided by the addition of nanosilica particles in PMMA is discussed. Published 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 2072–2078, 2003     

Thermal Response and Oxidation of Tyranno™-Fiber-Reinforced Si-Ti-C-O Matrix Composites for a Thermal Protection System in High-Enthalpy Dissociated Air

The thermal response and oxidation of Tyranno™ Lox-M fiber-reinforced Si-Ti-C-O matrix composites in high-enthalpy dissociated air was investigated in an arc jet facility (an arc wind tunnel). The maximum surface temperature reached 1310–1670°C. Catalytic recombination of oxygen and nitrogen on the composite surface under dissociated air was not significant. Surface recession was insignificant below 1600°C surface temperatures and above 5 kPa of oxygen partial pressure at the stagnation point. Passive-to-active oxidation transition of the composite agreed with Balat's theory for monolithic silicon carbide. A glass sealant prevented active oxidation of the composite for short-time exposures.     

Formation and transformation of cubic 3PbO·2Ta2O5 solid solution

The formation of lead tantalates in the PbO-rich region is studied using the powders prepared by the simultaneous hydrolysis of lead and tantalum alkoxides. Cubic 3PbO · 2Ta₂O₅ solid solutions crystallize at low temperatures from amorphous materials between 60 and 75 mol% PbO. The lattice parameter,a, increases linearly from 1.0545 to 1.0705 nm with increasing PbO. At higher temperatures the solid solutions above 66.67 mol% PbO are transformed into those of rhombohedral 2PbO · Ta₂O₅. Rhombohedral 5PbO · 2Ta₂O₅ is formed at 850 to 900 °C by transformation of 2PbO·Ta₂O₅ solid solution corresponding to 71.43 mol% PbO. The existence of previously reported 3PbO·Ta₂O₅ is not confirmed.     

Transmission of correct gaze direction in video conferencing using screen-embedded cameras

In this paper, we propose a new video conferencing system that presents correct gaze directions of a remote user by switching among images obtained from multiple cameras embedded in a screen according to a local user’s position. Our proposed method reproduces a situation like that in which the remote user is in the same space as the local user. The position of the remote user to be displayed on the screen is determined so that the positional relationship between the users is reproduced. The system selects one of the embedded cameras whose viewing direction towards the remote user is the closest to the local user’s viewing direction to the remote user’s image on the screen. As a result of quantitative evaluation, we confirmed that, in comparison with the case using a single camera, the accuracy of gaze estimation was improved by switching among the cameras according to the position of the local user.

     

Isolation kernel: the X factor in efficient and effective large scale online kernel learning

Large scale online kernel learning aims to build an efficient and scalable kernel-based predictive model incrementally from a sequence of potentially infinite data points. Current state-of-the-art large scale online kernel learning focuses on improving efficiency. Two key approaches to gain efficiency through approximation are (1) limiting the number of support vectors, and (2) using an approximate feature map. They often employ a kernel with a feature map with intractable dimensionality. While these approaches can deal with large scale datasets efficiently, this outcome is achieved by compromising predictive accuracy because of the approximation. We offer an alternative approach that puts the kernel used at the heart of the approach. It focuses on creating a sparse and finite-dimensional feature map of a kernel called Isolation Kernel. Using this new approach, to achieve the above aim of large scale online kernel learning becomes extremely simple—simply use Isolation Kernel instead of a kernel having a feature map with intractable dimensionality. We show that, using Isolation Kernel, large scale online kernel learning can be achieved efficiently without sacrificing accuracy.

     

Morphology study of oriented SmBCO film deposited by MOCVD

c-axis-oriented SmBa_2Cu_3O_7(SmBCO) films have been deposited on(100)- LaA1O_3(LAO)substrate by metal organic chemical vapor deposition(MOCVD) technique.The effects of deposition temperature(T_(dep)) and total pressure(P_(tot)) on the orientation and microstructure of SmBCO films were investigated.The orientation of SmBCO films transformed from α-axis to c-axis with increasing of T_(dep) from 900 to 1 100℃.At T_(dep)=1 050℃,SmBCO films had c-axis orientation and tetragon surface.At P_(tot)~(dep)=400-800 Pa and T_(dep)=1 050 ℃,totally c-axis-oriented SmBCO films were obtained.The R_(dep) of SmBCO films increased firstly and then decreased with increasing P_(tot).The surface of SmBCO films exhibited tetragon morphology at 1 050 ℃ and400 Pa.Maximum thickness of SmBCO film deposited was 1.2μm at P_(tot)= 600 Pa,and the corresponding R_(dep)was 7.2 μm·h~(-1).     

Lab-scale feasibility study on new elastomer comprising chloroprene and acrylonitrile for oil and gas applications

The limited options of suitable elastomers with adequate cost-performance balance drive the necessity to introduce new materials in the oil & gas (O&G) application space. The relevance of a recently developed copolymer of chloroprene and acrylonitrile (referred to as acrylonitrile–chloroprene rubber or NCR) to O&G applications is described in this technical contribution. The new elastomer demonstrates adequate physical properties and reasonably good high and low-temperature capabilities. It offers good resistance to several aqueous and non-aqueous fluids with low volume swelling and retains its physical properties to reasonable extents while exposed to hot test oils. Acrylonitrile–chloroprene rubber has been found to sustain “sour gas” exposure. Good abrasion resistance, high tear strength, and remarkably high flex-fatigue resistance coupled with low heat build-up reflect its durability under dynamic conditions. In addition, acrylonitrile–chloroprene rubber can very well withstand the rapid gas decompression test at 25°C. This unique combination of attributes may allow acrylonitrile–chloroprene rubber to be considered as a candidate material for high-performance O&G applications.     

β-phase transformation and thermoelectric power in FeSi2 and Fe2Si5 based alloys containing small amounts of Cu

The effects of Cu addition on the β phase formation rate and the thermoelectric power in various FeSi₂ and Fe₂Si₅ based alloys was examined. The peritectoid reaction (a+→β) in FeSi₂ alloys was initially enhanced by the addition of Cu but it became slower for longer annealing times. The retained metallic ε was harmful for the thermoelectric power. The inherent thermoelectric properties of (FeSi₂)_99−XMn₁Cu_X (X=0–1.O at.%), (FeSi₂)_99−X Co₁Cu_X (X=0–1.0 at.%) alloys were attained after the elimination of ε. In the case of eutectoid reaction (→β+Si). Differential thermal analysis, X-ray diffraction and microscopic observation clearly confirmed that the eutectoid reaction rate was drastically enhanced by the addition of a small amount of Cu and its rate decreased with decreasing Cu content. The rate also depends on the annealing temperature and reached a maximum at about 1073 K for most alloys. The addition of only 0.1 at.% Cu was still very effective even in Mn or Co doped alloys. The thermoelectric power of these alloys increased very quickly with annealing time. Their final values decreased with Cu content and saturated at 0.2 at.% Cu. The value of the 0.1 at.% Cu added alloy was higher than that of both the conventional p- and a-type FeSi₂ based alloys. These results suggest that the Fe₂Si₅ alloys with a small amount of Cu may be attractive as new thermoelectric materials.     

Predicting viewer-perceived activity/dominance in soccer games with stick-breaking HMM using data from a fixed set of cameras

We attempted to predict activity/dominance for soccer games, where activity is defined as the degree of activity of the game as perceived by the viewer, whereas dominance is the degree at which the viewer perceives a particular team to dominate over the other team. Such activity/dominance information would help a layman viewer understand the game. It would also enable construction of an automatic digest creation system that extracts scenes having high activity/dominance. There are two facets of this study: 1. The main part of the underlying prediction model consists of a Stick-Breaking Hidden Markov Model, where the data automatically estimates the number of states of the Markov process behind the data. 2. The data used in this paper is vector time-series data consisting of player, referee, and ball positions, together with team information, acquired by a set of fixed cameras. The problem was approached with a Bayesian framework where learning and prediction were implemented by three different methods: Markov Chain Monte Carlo, Expectation Maximization, and Variational Bayes. The proposed method was tested using a dataset consisting of 10 professional soccer games and was compared against standard regression methods.     

Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments

We extend an abstract agent-based swarming model based on the evolution of neural network controllers, to explore further the emergence of swarming. Our model is grounded in the ecological situation, in which agents can access some information from the environment about the resource location, but through a noisy channel. Swarming critically improves the efficiency of group foraging, by allowing agents to reach resource areas much more easily by correcting individual mistakes in group dynamics. As high levels of noise may make the emergence of collective behavior depend on a critical mass of agents, it is crucial to reach sufficient computing power to allow for the evolution of the whole set of dynamics in simulation. Since simulating neural controllers and information exchanges between agents are computationally intensive, to scale up simulations to model critical masses of individuals, the implementation requires careful optimization. We apply techniques from astrophysics known as treecodes to compute the signal propagation, and efficiently parallelize for multi-core architectures. Our results open up future research on signal-based emergent collective behavior as a valid collective strategy for uninformed search over a domain space.