Strong metal-support interactions (SMSIs) between Pt and Ti3+ on Pt/TiOx nanoparticles for enhanced degradation of organic pollutant

In this work, Pt nanoparticles were deposited onto the surface of Magnéli phase titanium suboxide (TiO_x) nanoparticles using a microwave-assisted deposition method. The effect of different concentrations of Pt nanoparticles was investigated to evaluate the strong metal-support interactions (SMSIs) between Pt and TiO_x based on their performance for the degradation of organic pollutant molecules. The adsorption and catalytic performance of the as-synthesized Pt/TiO_x nanoparticles were evaluated with respect to the degradation of rhodamine B (RhB) molecules without any external energy source. The Pt/TiO_x nanoparticles with Pt loading at 10 wt% (10%Pt/TiO_x) exhibited a remarkable performance. The XPS, CV, and FTIR analyses confirmed the presence of RhB degradation reactions under dark condition. This remarkable performance of the Pt/TiO_x nanoparticles was attributed to the SMSIs between Pt and Ti³⁺ atoms, which improves their performance compared with Pt/TiO₂ nanoparticles, and high density of active sites due to their nanometer size, which results in better performance compared with that of Pt/TiO_x submicron particles.     

Iris quality assessment and bi-orthogonal wavelet based encoding for recognition

Iris recognition has been demonstrated to be an efficient technology for personal identification. In this work, methods to perform iris encoding using bi-orthogonal wavelets and directional bi-orthogonal filters are proposed and compared. All the iris images are enhanced using the wavelet domain in-band de-noising method. This method is shown to improve the iris segmentation results. A framework to assess the iris image quality based on occlusion, contrast, focus and angular deformation is introduced and used as part of a novel adaptive matching technique based on the assessed iris image quality. Adaptive matching presents improved performance when compared against the Hamming distance method. Four different databases are used to analyze the system performance. The first two databases include popular CASIA and high resolution University of Bath databases. Results obtained for these databases compare with results from the literature, in terms of speed as well as accuracy. The other two databases have challenging off-angle (WVU database) and uncontrolled (Clarkson database) iris images and are used to assess the limits of system performance. Best results are achieved for directional bi-orthogonal filter based encoding technique combined with the adaptive matching method with EER values of 0.07%, 0.15%, 0.81% and 1.29% for the four databases, which reflect highly competent performance and high correlation with the quality of the iris images.     

Double preference relations for generalised belief change

Many belief change formalisms employ plausibility orderings over the set of possible worlds to determine how the beliefs of an agent ought to be modified after the receipt of a new epistemic input. While most such possible world semantics rely on a single ordering, we investigate the use of an additional preference ordering—representing, for instance, the epistemic context the agent finds itself in—to guide the process of belief change. We show that the resultant formalism provides a unifying semantics for a wide variety of belief change operators. By varying the conditions placed on the second ordering, different families of known belief change operators can be captured, including AGM belief contraction and revision, Rott and Pagnucco's severe withdrawal, the systematic withdrawal of Meyer et al., as well as the linear liberation and σ-liberation operators of Booth et al. Our approach also identifies novel classes of belief change operators worthy of further investigation.     

Total variation, adaptive total variation and nonconvex smoothly clipped absolute deviation penalty for denoising blocky images

The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty function motivated by the recent progress in the statistical literature on high-dimensional variable selection. Using a particular instantiation of the majorization-minimization algorithm, the optimization problem can be efficiently solved and the computational procedure realized is similar to the spatially adaptive total variation model. Our two-pixel image model shows theoretically that the new penalty function solves the bias problem inherent in the total variation model. The superior performance of the new penalty function is demonstrated through several experiments. Our investigation is limited to “blocky” images which have small total variation.     

Running temperature and mechanical stability of grease as maintenance parameters of railway bearings

Spherical roller bearings in railway car wheels are critical components whose failure may have catastrophic consequences. The present study aims to analyse the mechanical stability of greases and temperature of bearings as indicators for condition-based bearing maintenance. The performed case study includes nine fully-formulated commercial greases examined in the wheel bearings of five ore cars operated in northern Scandinavia. The studied ore cars travelled a distance of about 300000km during a period of three years. Small samples of the greases were taken on eight occasions to test their mechanical stability. In addition, the temperatures of the bearings were continuously recorded. After the test period, the wear, electrical damage, and corrosion of the bearings were examined. One of the findings is that the shear stress of the grease at a certain shear velocity (the certain yieldstress (CEY) value) is a good maintenance indicator and is highly dependent on the grease type. The bearing's wear, electrical damage and corrosion also depend on the grease type. However, no oxidation of the greases was identified. The paper also outlines a systematic methodology to determine an overall maintenance indicator for railway roller bearings which is based on the field measurements.     

A 10 tesla table-top controlled waveform magnet

Controlled waveform magnets (CWMs) are a class of pulsed magnets whose pulse shape with time can be programmed by the user. With a CWM, the user gains control not only over the magnitude of the field but also over its rate of change. In this work we present a table-top CWM, driven by a capacitor bank, capable of producing virtually any user-shaped magnetic field waveform up to 10 tesla. Insulated gate bipolar transistor chips have been paralleled to form the high current switch and paralleled chips of SiC Schottky diodes form the crowbar diode module. Sample controlled waveforms including flat-tops up to 10 tesla and some triangular magnetic field pulses have been successfully generated for 10-20 ms with a ripple <1%.     

Bridging Artifacts and Actors: Expertise Sharing in Organizational Ecosystems

We synthesize findings from longitudinal case studies examining work practices in three different organizations and propose analytical and methodological frameworks to guide the design and implementation of technologies for expertise and knowledge management. We appropriate the concept of ecosystem to argue that we can create active and useful solutions for knowledge management through a focus on interaction between two mutually intertwined elements of an ecosystem—artifacts and actors. We show that in expertise and knowledge sharing systems domain knowledge and technological knowledge are complementary and we present evidence that small solutions can have far reaching effects. Finally, we make a case for full integration of IT developers as an element of expertise sharing ecosystem.     

A Novel Photonic Microwave Filter With Infinite Impulse Response

A novel design of a photonic microwave filter with infinite impulse response is presented and demonstrated experimentally, ft overcomes the problems due to optical coherence. The design exhibits substantial flexibility, permitting easy and continuous tunability of the free spectral range. In particular, when a Mach-Zehnder modulator is used in the filter, the passband of the filter response can be changed to stopband and vice versa. The design also provides scope for cascading more stages. Theoretical analysis and measured results are presented, showing a very good match between them.     

Application of battery energy storage system to load frequency control of an isolated power system

A battery energy storage system (BES) can provide fast active power compensation and hence it also can be used to improve the performance of the load frequency control. In this paper, the study is carried out on a single area model representing the whole power system considering generation rate constraint (GRC). An incremental model of BES is proposed and merged into the load frequency control of the power system. Optimum value of integral gain setting is obtained using integral squared technique (ISE). Dynamic responses of the system are presented with and without considering BES facility. Analysis reveals that BES improves the system performance significantly. Copyright © 1999 John Wiley & Sons, Ltd.     

Interference-aware feedback based iterative Hungarian approach to allocate multiple channels to multiple D2D pairs to maximize underlay D2D network capacity

The spectral efficiency of a cellular network can be increased significantly by allowing spatial reuse of its spectrum by an underlay device-to-device (D2D) network. In an underlay D2D network, devices in close vicinity are allowed to establish low-power direct links with little to no involvement of the base station. In order to increase the spectral efficiency and the number of devices with channel access, multiple D2D pairs may transmit in each cellular channel. Additionally, each pair can be allowed to utilize multiple channels to transmit so as to maximize the D2D network capacity. This multiple-pair multiple-channel (MPMC) strategy is quite appealing but is limited by the resultant additional aggregate interference and the inherent complexity, hence necessitating the need for a fast and reliable channel allocation scheme. This work proposes a polynomial-time iterative Hungarian assignment with feedback (IHAF) algorithm for multiple channel allocations amongst multiple D2D pairs that increases the D2D network capacity manifold while maintaining the desired minimum capacity for each cellular user.