Efficient dissemination of personalized information using content-based multicast

There has been a surge of interest in the delivery of personalized information to users (e.g., personalized stocks or travel information), particularly as mobile users with limited terminal device capabilities increasingly desire updated and targeted information in real time. When the number of information recipients is large and there is sufficient commonality in their interests, as is often the case, IP multicast is an efficient way of delivering the information. However, IP multicast services do not consider the structure and semantics of the information in the multicast process. We propose the use of Content-Based Multicast (CBM) where extra content filtering is performed at the interior nodes of the IP multicast tree; this will reduce network bandwidth usage and delivery delay, as well as the computation required at the sources and sinks. We evaluate the situations in which CBM is advantageous. The benefits of CBM depend critically upon how well filters are placed at interior nodes of the IP multicast tree and the costs depend upon those introduced by filters themselves. Further, we consider the benefits of allowing the filters to be mobile so as to respond to user mobility or changes in user interests and the corresponding costs of filter mobility. The criterion that we consider is the total network bandwidth utilization. For this criterion, we develop an optimal filter placement algorithm, as well as a heuristic that executes faster than the optimal algorithm. We evaluate the algorithms by means of simulation experiments. Our results indicate that filters can be effective in substantially reducing bandwidth. We also find filter mobility is worthwhile if there is marked large-scale user mobility. We conclude with suggestions for further work.     

Revisiting Continental U.S. Hydrologic Change in the Latter Half of the 20th Century

An intensified hydrologic cycle and a large amount of monitoring flow data in the latter half of the 20th century attracted a lot of research on the continental U.S. hydrologic change. However, most previous studies are based on HCDN (Hydro-Climate Data Network) dataset with a period of ~1950s ?1988. This study analyzed hydrologic change in continental U.S. based on MOPEX (international Model Parameter Estimation Experiment) hydrology dataset with a period of ~1950s ?2000 for 302 watersheds (gages) across diverse climate, vegetation and soil conditions. This dataset is more representative of the latter half of the 20th century than HCDN. In contrast with previous studies, this study shows that only 20–30 % of watersheds present increasing trends in flow (streamflow, Q; baseflow, Q_bf; baseflow index, BFI), and most (> 65 %) watersheds presents non-significant trends. Similar to previous studies, the watersheds with increasing trends in Q and Q_bf are concentrated in Midwest and high plain (North-Central area) of USA. Climate contributes more to Q change (61?±?25 % vs. 39?±?25 %) but slightly less to Q_bf change than human activity (49?±?26 % vs. 51?±?26 %) and much less to BFI change than human activity (?5?±?61 % vs. 105?±?61 %). A step change at ~1971 in Q and Q_bf was found for 35–45 % but not for a large proportion of watersheds (50 % or more was reported by previous studies). This study provides new insights on the latter half of the 20th century’s hydrologic cycle for the continental U.S. with a more representative dataset of this period.     

A facile novel synthesis of delafossite CuFeO2 powders

P-type transparent conducting oxides copper delafossite CuFeO₂ powders have been successfully synthesized by using hydrothermal method. The influence of synthesis conditions on the crystal structure, morphology, optical and magnetic properties was systematically studied using X-ray diffraction, scanning electron microscope (SEM), UV–Vis–NIR scanning spectrophotometer and vibrating sample magnetometer. The results indicated the precipitated precursor at pH value of 12 using 1 M NaOH as a base in the presence of hydrazine hydrate as a reducing agent hydrothermally treated at 280 °C for 96 h was transformed to pure rhombohedral 3R delafossite phase. SEM observations of these powders confirmed their hexagonal like structure. The transmittance of the sample was around 65 %. The optical band gap of delafossite–CuFeO₂ sample prepared was 3.5 eV as a visible transparent material. Furthermore, magnetic properties behavior was identified and paramagnetism property was found at a room temperature. The saturation magnetization and coercive force for the pure sample were 1.2 emu/g and 58.35 Oe, respectively.     

Structural,Microstructure, Mechanical and Electrical Properties of Porous Zr4+-Cordierite Ceramic Composites

Zirconium-cordierite ceramic composites have been synthesized by a co-precipitation method using MgCl₂·6H₂O, NaAlO₂, Na₂SiO₃·5H₂O, and ZrOCl₂·8H₂O as starting materials. XRD, FT-IR, and SEM techniques were employed to study the effect of zirconium on the crystal structure and microstructure of the samples. XRD results revealed that spinel MgAl₂O₄ and t-ZrO₂ phases were predominant in the samples with low Zr⁴⁺ content (10 wt.%), whereas zircon ZrSiO₄ was predominant with high Zr⁴⁺ content (≥15 wt.%). The densification behavior was improved from 30.4 to 44.6% of the theoretical density (2.6 g/cm³) at 15 wt.% of Zr⁴⁺. However, microhardness of the sintered samples was enhanced from 7.1 to 7.5 GPa with increasing the Zr⁴⁺ dose from 0 to 25 wt.%. On the other hand, the gradual increase in Zr⁴⁺ content from 0 to 25 wt.% led to suppression in the electrical resistivity (ρ) from 16.6 to 2.8 × 10⁹ Ω/cm, respectively. In addition, the dielectric permittivity (ε) of the pure cordierite was decreased with Zr⁴⁺ ion addition. The maximum dielectric permittivity (ε) at low frequencies (10 MHz) was 18.7 at 10 wt.% Zr⁴⁺ content, whereas at high frequencies (1 GHz) it was 38.8 at 15 wt.% Zr⁴⁺ content.     

Improved mechanical properties of magnesium–graphene composites with copper–graphene hybrids

New magnesium nanocomposites reinforced with copper–graphene nanoplatelet hybrid particles have been prepared through the semipowder metallurgy method. Compared with the monolithic Mg, the Mg–1Cu–xGNPs nanocomposites exhibited higher tensile and compressive strength. In tension, nanocomposites revealed substantial enhancement in elastic modulus, 0.2% yield strength, ultimate tensile strength and failure strain (up to +89, +117, +58 and +96% respectively) compared to monolithic Mg. In compression, the nanocomposites showed the greatest improvement in 0.2% yield strength, and the ultimate compressive strength and failure strain (%) (up to +34, +59 and +61% respectively), whilst the compressive elastic modulus first increases and then decreases with an increase in the graphene nanoplatelets (GNPs) contents. The enhanced strength of the composites is likely to result from strengthening mechanisms invoked by the addition of Cu–GNPs hybrids.     

Enhanced separation and extraction of cadmium and lead by a novel magnetite-immobilized-gelatin nano-sorbent

A novel magnetic nano-sorbent was synthesized by Schiff’s base formation via covalent bonding of gelatin to the surface of nano-magnetite-immobilized-3-aminopropyltrimethoxysilane (Nano-Fe₃O₄-Si-N=Gelatin). The structure was confirmed by the FT-IR, TGA, and SEM. The maximum capacity of Cd(II) and Pb(II) were identified as 440 and 400 µmol g^?1, respectively. The separation characteristics were evaluated in presence of various controlling factors. The sorption processes of Cd(II) and Pb(II) were found to follow the postulates of Langmuir, Brunauer-Emmer-Teller, and Dubinin Radushkevich isotherm models. The potential applications of Nano-Fe₃O₄-Si-N=Gelatin in water treatment of Cd(II) and Pb(II) were successfully accomplished using a micro-column technique.     

Processing of High‐Density Magnesia Spinel Electro‐Conducting Ceramic Composite and its Oxidation at 1400°C

Dense conductive ceramic composites of MgAl₂O₄ and MoSi₂ were processed using combustion synthesis under‐load methodology. The starting reactants were blends of MoO₃, SiO₂, MgO, and Al powders. The study revealed that to obtain dense composite with homogeneous microstructure, 30 wt. % of MoSi₂, 18.5 μm Al average particle size, and 175 MPa load are required. The produced dense composite was found to have a low apparent porosity (<1.0 vol. %), moderate density 4.61 g/cm³, and low electrical resistivity 0.3 Ωcm. The dense composite exhibited excellent thermodynamic stability between its phases at 1400°C in open atmosphere.     

Silicon Seed Priming Combined with Foliar Spray of Sulfur Regulates Photosynthetic and Antioxidant Systems to Confer Drought Tolerance in Maize (Zea mays L.)

Silicon - The present study evaluated the effect of silicon (Si) seed priming and sulfur (S) foliar spray on drought tolerance of two contrasting maize hybrids viz. drought tolerant Hi-Corn 11 and...     

A novel multi-model neuro-fuzzy-based MPPT for three-phase grid-connected photovoltaic system

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three multi-layered feed forwarded Artificial Neural Networks (ANN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated ANN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and nonlinear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network and the Perturb and Observe (P&O) algorithm dispositive.     

Wideband Low‐Reflection Transmission Lines for Bare Chip on Multilayer PCB

The pad pitch of modern radio frequency integrated circuits is in the order of few tens of micrometers. Connecting a large number of high‐speed I/Os to the outside world with good signal fidelity at low cost is an extremely challenging task. To cope with this requirement, we need reflection‐free transmission lines from an on‐chip pad to on‐board SMA connectors. Such a transmission line is very hard to design due to the difference in on‐chip and on‐board feature size and the requirement for extremely large bandwidth. In this paper, we propose the use of narrow tracks close to chip and wide tracks away from the chip. This narrow‐to‐wide transition in width results in impedance discontinuity. A step change in substrate thickness is utilized to cancel the effect of the width discontinuity, thus achieving a reflection‐free microstrip. To verify the concept, several microstrips were designed on multilayer FR4 PCB without any additional manufacturing steps. The TDR measurements reveal that the impedance variation is less than 3 Ω for a 50 Ω microstrip and S11 better than –9 dB for the frequency range 1 GHz to 6 GHz when the width changes from 165 µm to 940 µm, and substrate thickness changes from 100 µm to 500 µm.