Space–Time Power Schedule for Distributed MIMO Links Without Instantaneous Channel State Information at the Transmitting Nodes

A space-time optimal power schedule for multiple distributed multiple-input multiple-output (MIMO) links without the knowledge of the instantaneous channel state information (CSI) at the transmitting nodes is proposed. A readily computable expression for the ergodic sum capacity of the MIMO links is derived. Based on this expression, which is a non-convex function of power allocation vectors, a projected gradient algorithm is developed to optimize the power allocation. For a symmetric set of MIMO links with independent identically distributed channels, it is observed that the space-time optimal power schedule reduces to a uniform isotropic power schedule when nominal interference is low, or to an orthogonal isotropic power schedule when nominal interference is high. Furthermore, the transition region between the latter two schedules is seen to be very sharp in terms of nominal interference-to-noise ratio (INR). For MIMO links with correlated channels, the corresponding space-time optimal power schedule is developed based on the knowledge of the channel correlation matrices. It is shown that the channel correlation has a great impact on the ergodic capacity and the optimality of different power scheduling approaches.     

Carbon nanofibers as hydrogen adsorbing materials for power sources

Porous carbon nanofibers are synthesized by CVD method from acetylene with use of iron-containing catalysts. Activation of the nanofibers in melted potassium hydroxide results in increasing surface area from initial 300–400 m² g⁻¹ to 1700 m² g⁻¹. As follows from XRD data, activated nanofibers do not contain regular packages of graphene layers, but retain high electric conductivity. Deposition of copper improves electrochemical hydrogen storing characteristics of carbon nanofibers. Carbon nanomaterials obtained can be used as hydrogen storing materials in batteries instead of hydride forming metals.     

Use of recycled copper slag for blended cements

Copper slag is a by‐product generated during smelting to extract copper metal from the ore. The copper slag obtained may exhibit pozzolanic activity and may therefore be used in the manufacture of addition‐containing cements. In this paper the effect of the incorporation of the copper slag in cement is measured. Blends of copper slag with Portland cement generally possess properties equivalent to Portland cement containing fly ash, but very different to the silica fume incorporation. Copper slag and fly ash reduce the heat of hydration more effectively than silica fume in mortars. The replacement of 30% cement by copper slag reduces the flexural and compressive strength in a similar way to fly ash; however, after 28 days, the reduction is less than the percentage of substitution. Hydrated calcium aluminate phases were analysed using scanning electron microscopy (SEM) and X‐ray diffraction (XRD) techniques. The pozzolanic activity of copper slag is similar to that of fly ash and higher than silica fume. In the presence of low water/cement ratios, certain pozzolanic materials produce a very compact cement paste that limits the space available for hydration products, a determining factor in the formation of hydrated calcium aluminates. SEM was found to be a useful analytical technique when aluminates are formed and can be clearly detected by XRD. Copyright © 2008 Society of Chemical Industry     

Xylene Isomerization in a ZSM-5/SS Membrane Reactor

A membrane reactor containing different types of ZSM-5/porous SS membranes was used to perform the xylene isomerization reaction. The parent Na-ZSM-5 layer was synthesized by secondary growth on top of porous stainless steel tubes. The xylene isomerization reaction was carried out at different temperatures in the membrane reactor and in a fixed-bed reactor of identical geometry for comparison. Two different kinds of membranes were prepared by ion exchange: a Pt/H-ZSM-5 catalytic membrane and two Ba-ZSM-5 composites with different Ba²⁺ concentration. The p-xylene production using 100% exchanged Ba-membrane was about 28% higher than the fixed-bed reactor at 370 °C, when m-xylene was fed.     

Ultrasonic treatment restores the photoelectric parameters of silicon solar cells degraded under the action of <Superscript>60</Superscript>Co gamma radiation

The photoelectric parameters of silicon solar cells degraded under the action of ⁶⁰Co gamma-radiation can be partly restored using an ultrasonic treatment (UST). The growth of the maximum output power of solar cells after the UST is related to a redistribution of the radiation defects and an increase in the homogeneity of a semiconductor crystal structure.     

Phase states of a two-dimensional non-Heisenberg ferromagnet

The effects of a biquadratic exchange and an external magnetic field on the phase states of a twodimensional non-Heisenberg ferromagnet have been studied with allowance for magnetoelastic and magnetodipolar interactions.     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced     

Lattice structure on some fuzzy algebraic systems

In this paper, we study the lattice structure of some fuzzy algebraic systems such as (G-)fuzzy groups, some fuzzy ordered algebras and fuzzy hyperstructures. We prove that under suitable conditions, these structures form a distributive or modular lattice. This research partially is supported by the “ Fuzzy Systems and its Applications Center of Excelence, Shahid Bahonar University of Kerman, Iran”.     

The LilyPad Arduino: Toward Wearable Engineering for Everyone

Electronic textiles, or e-textiles, are an increasingly important part of wearable computing, helping to make pervasive devices truly wearable. These soft, fabric-based computers can function as lovely embodiments of Mark Weiser's vision of ubiquitous computing: providing useful functionality while disappearing discreetly into the fabric of our clothing. E-textiles also give new, expressive materials to fashion designers, textile designers, and artists, and garments stemming from these disciplines usually employ technology in visible and dramatic style. Integrating computer science, electrical engineering, textile design, and fashion design, e-textiles cross unusual boundaries, appeal to a broad spectrum of people, and provide novel opportunities for creative experimentation both in engineering and design. Moreover, e-textiles are cutting- edge technologies that capture people's imagination in unusual ways. (What other emerging pervasive technology has Vogue magazine featured?) Our work aims to capitalize on these unique features by providing a toolkit that empowers novices to design, engineer, and build their own e-textiles.     

Sensor Selection in Arbitrary Dimensions

We address the sensor selection problem which arises in tracking and localization applications. In sensor selection, the goal is to select a small number of sensors whose measurements provide a good estimate of a target's state (such as location). We focus on the bounded uncertainty sensing model where the target is a point in the d -dimensional Euclidean space. Each sensor measurement corresponds to a convex polyhedral subset of the space. The measurements are merged by intersecting corresponding sets. We show that, on the plane, four sensors are sufficient (and sometimes necessary) to obtain an estimate whose area is at most twice the area of the best possible estimate (obtained by intersecting all measurements). We also extend this result to arbitrary dimensions and show that a constant number of sensors suffice for a constant factor approximation in arbitrary dimensions. Both constants depend on the dimensionality of the space but are independent of the total number of sensors in the network.