The effects of ordering on the morphology of two-layer alumite—Forming a patterned interface

Two-layer alumite has been synthesized by three-step anodizing such that the 1st layer was formed by commonly known two-step anodizing at a prescribed voltage and the 2nd layer was formed at two-times higher anodizing voltage, in suitable electrolytes. When the 2nd layer is formed at an ordering voltage, alternate pores of the 1st layer continue growing through the 2nd layer, in a regular pattern. The neighboring pores cease their growth, possibly due to upward flow and thickening of barrier oxide at the new cell boundaries. The growing pores in the 2nd layer are equi-distant provided that the 1st layer is also formed under ordering conditions. If the 2nd layer is formed under non-ordering conditions the regular pattern at the interface is completely lost. Employing the two-layer alumite, nanowires by the 1st layer can be grown such that alternate pores remain empty, providing a new superlattice.     

Proposal for Highly Nonlinear Dispersion-Flattened Octagonal Photonic Crystal Fibers

A highly nonlinear photonic crystal fiber (HNL-PCF) based on an octagonal structure with isosceles triangular-latticed cladding is proposed for the telecommunication window. The finite-difference method with anisotropic perfectly matched boundary layer is used to investigate the guiding properties. It is demonstrated that it is possible to design a simple HNL low-loss dispersion-flattened PCF with a nonlinear coefficient of the order 27 W^-1km^-1 at a 1.55-mum wavelength. According to simulation, ultraflattened dispersion of 0 plusmn 0.5 ps/nm/km is obtained in a 1.46- to 1.66-mum wavelength with low confinement losses less than 0.06 dB/km in the entire band of interest.     

Synthesis of Ruthenium Hydride Complexes Containing beta‐Aminophosphine Ligands Derived from Amino Acids and their use in the H2‐Hydrogenation of Ketones and Imines

The new complexes RuHCl(PPh₂CH₂CHRNH₂)₂ and RuHCl(PPh₂CH₂CHRNH₂)(R‐ binap), R=H (Pgly), R=Me [(R)‐Pala] were prepared by the substitution of the PPh₃ ligands in RuHCl(PPh₃)₃ or RuHCl(PPh₃)[(R)‐binap] with beta‐aminophosphines derived from amino acids. The complex trans‐RuHCl(Pgly)[(R)‐binap] has been characterized by X‐ray crystallography. The complex trans‐RuHCl[(S)‐Ppro]₂ where (S)‐Ppro is derived from proline was also prepared and characterized by X‐ray crystallography. These were used as catalyst precursors in the presence of a base (KOPr‐i or KOBu‐t) for the hydrogenation of various ketones and imines to the respective alcohols and amines with H₂ gas (1–11 atm) at room temperature. Acetophenone was hydrogenated to (S)‐1‐phenylethanol in low ee (up to 40%) when catalyzed by the enantiomerically pure complexes. These complexes are especially active in the hydrogenation of sterically congested and electronically deactivated ketones and imines and are selective for the hydrogenation of CO bonds over CC bonds.     

Heat treatment and effects of Cr and Ni in low alloy steel

The effects of Cr and Ni on low carbon steel was observed. Undissolved carbide particles refine the austenite grain size. In the presence of nickel, chromium carbide is less effective in austenite grain refinement than chromium carbide in absence of nickel at temperature below 975°C. Nickel does not produce any austenite grain refinement but presence of nickel promotes the formation of acicular ferrites. It was also found that Ni and Cr as chromium carbide also refines the ferrite grain size and morphology. Cr as chromium carbide is more effective in refining ferrite grain size than nickel.     

Topology based placement of multicast capable nodes for supporting efficient multicast communication in WDM optical networks

Most existing algorithms for the problem of optical signal splitter placement or multicast splitting-capable node placement in a WDM network are based on the performance of attempting a large set of randomly generated multicast sessions in the network. Experiments show that placement of multicast capable nodes based on their importance for routing one set of multicast sessions may not be a right choice for another set of multicast sessions. In this work, we propose placement algorithms that are based on network topology and the relative importance of a node in routing multicast sessions, which is measured by our proposed metrics. Since a network topology is fixed once given, the proposed algorithms are essentially network traffic independent. We evaluate the proposed placement algorithms given static sets of multicast sessions as well as under dynamic traffic conditions, which are routed using our splitter constrained multicast routing algorithm. Our results show that the proposed algorithms perform better, compared to existing algorithms.     

A therapy-driven gamification framework for hand rehabilitation

Rehabilitative therapy is usually very expensive and confined to specialized rehabilitation centers or hospitals, leading to slower recovery times for corresponding patients. Therefore, there is a high demand for the development of technology-based personalized solutions to guide and encourage patients towards performing online rehabilitation program that can help them live independently at home. This paper introduces an innovative e-health framework that develops adaptive serious games for people with hand disabilities. The aim of this work is to provide a patient-adaptive environment for the gamification of hand therapies in order to facilitate and encourage rehabilitation issues. Theoretical foundations (i.e., therapy and patient models) and algorithms to match therapy-based hand gestures to navigational movements in 3D space within the serious game environment have been developed. A novel game generation module is introduced, which translates those movements into a 3D therapy-driven route on a real-world map and with different levels of difficulty based on the patient profile and capabilities. In order to enrich the user navigation experience, a 3D spatio-temporal validation region is also generated, which tracks and adjusts the patient movements throughout the session. The gaming environment also creates and adds semantics to different types of attractive and repellent objects in space depending on the difficulty level of the game. Relevant benchmarks to assess the patient interaction with the environment along with a usability and performance testing of our framework are introduced to ensure quantitative as well as qualitative improvements. Trial tests in one disability center were conducted with a total number of five subjects, having hand motor controls problems, who used our gamified physiotherapy solution to help us in measuring the usability and users’ satisfaction levels. The obtained results and feedback from therapists and patients are very encouraging.     

Genetics Based Compact Fuzzy System for Visual Sensor Network

As a component of Wireless Sensor Network (WSN), Visual-WSN (VWSN) utilizes cameras to obtain relevant data including visual recordings and static images. Data from the camera is sent to energy efficient sink to extract key-information out of it. VWSN applications range from health care monitoring to military surveillance. In a network with VWSN, there are multiple challenges to move high volume data from a source location to a target and the key challenges include energy, memory and I/O resources. In this case, Mobile Sinks(MS) can be employed for data collection which not only collects information from particular chosen nodes called Cluster Head (CH), it also collects data from nearby nodes as well. The innovation of our work is to intelligently decide on a particular node as CH whose selection criteria would directly have an impact on QoS parameters of the system. However, making an appropriate choice during CH selection is a daunting task as the dynamic and mobile nature of MSs has to be taken into account. We propose Genetic Machine Learning based Fuzzy system for clustering which has the potential to simulate human cognitive behavior to observe, learn and understand things from manual perspective. Proposed architecture is designed based on Mamdani’s fuzzy model. Following parameters are derived based on the model residual energy, node centrality, distance between the sink and current position, node centrality, node density, node history, and mobility of sink as input variables for decision making in CH selection. The inputs received have a direct impact on the Fuzzy logic rules mechanism which in turn affects the accuracy of VWSN. The proposed work creates a mechanism to learn the fuzzy rules using Genetic Algorithm (GA) and to optimize the fuzzy rules base in order to eliminate irrelevant and repetitive rules. Genetic algorithm-based machine learning optimizes the interpretability aspect of fuzzy system. Simulation results are obtained using MATLAB. The result shows that the classification accuracy increase along with minimizing fuzzy rules count and thus it can be inferred that the suggested methodology has a better protracted lifetime in contrast with Low Energy Adaptive Clustering Hierarchy (LEACH) and LEACH-Expected Residual Energy (LEACH-ERE).     

Maximizing quality of experience through context‐aware mobile application scheduling in cloudlet infrastructure

Application software execution requests, from mobile devices to cloud service providers, are often heterogeneous in terms of device, network, and application runtime contexts. These heterogeneous contexts include the remaining battery level of a mobile device, network signal strength it receives and quality‐of‐service (QoS) requirement of an application software submitted from that device. Scheduling such application software execution requests (from many mobile devices) on competent virtual machines to enhance user quality of experience (QoE) is a multi‐constrained optimization problem. However, existing solutions in the literature either address utility maximization problem for service providers or optimize the application QoS levels, bypassing device‐level and network‐level contextual information. In this paper, a multi‐objective nonlinear programming solution to the context‐aware application software scheduling problem has been developed, namely, QoE and context‐aware scheduling (QCASH) method, which minimizes the application execution times (i.e., maximizes the QoE) and maximizes the application execution success rate. To the best of our knowledge, QCASH is the first work in this domain that inscribes the optimal scheduling problem for mobile application software execution requests with three‐dimensional context parameters. In QCASH, the context priority of each application is measured by applying min–max normalization and multiple linear regression models on three context parameters—battery level, network signal strength, and application QoS. Experimental results, found from simulation runs on CloudSim toolkit, demonstrate that the QCASH outperforms the state‐of‐the‐art works well across the success rate, waiting time, and QoE. Copyright © 2016 John Wiley & Sons, Ltd.