Firework inspired load balancing approach for wireless sensor networks

Wireless Networks - In Wireless Sensor Networks (WSNs), where power consumption is a huge concern, the improvement of the network’s lifetime is an area of constant study and innovation. The...     

Evolution of properties of parts during MIM and sintering of recycled oxide particles

Metal injection moulding (MIM) is an established process for high volume production of complex shaped metallic parts using commercially available feedstocks. The characteristics of parts after moulding, debinding, and sintering cannot be simply predictable from raw materials because the properties get altered with the process parameters and the corresponding levels of porosity during processing steps. In this study, physical properties, microstructure, and mechanical properties of the MIM parts have been characterised to understand the evolution of strength during various steps in MIM processing. Feedstocks with different binder loading show a considerable difference in physical as well as mechanical characteristics. During sintering of parts which have solid loading of grinding sludge, simultaneous in situ reduction and densification takes place, whereas only densification occurs in carbonyl iron parts. It is, therefore, possible to make complex shaped parts of different levels of porosity from downgraded shop floor metallic waste.     

Healing substrates with mobile, particle-filled microcapsules: designing a 'repair and go' system.

We model the rolling motion of a fluid-driven, particle-filled microcapsule along a heterogeneous, adhesive substrate to determine how the release of the encapsulated nanoparticles can be harnessed to repair damage on the underlying surface. We integrate the lattice Boltzmann model for hydrodynamics and the lattice spring model for the micromechanics of elastic solids to capture the interactions between the elastic shell of the microcapsule and the surrounding fluids. A Brownian dynamics model is used to simulate the release of nanoparticles from the capsule and their diffusion into the surrounding solution. We focus on a substrate that contains a damaged region (e.g. a crack or eroded surface coating), which prevents the otherwise mobile capsule from rolling along the surface. We isolate conditions where nanoparticles released from the arrested capsule can repair the damage and thereby enable the capsules to again move along the substrate. Through these studies, we establish guidelines for designing particle-filled microcapsules that perform a 'repair and go' function and thus, can be utilized to repair damage in microchannels and microfluidic devices.     

Thio Sol–Gel Process for the Synthesis of Titanium Disulfide

A thio sol–gel process for the synthesis of titanium disulfide using titanium alkoxide as the metal source is demonstrated. The alkoxide reacts at room temperature with H₂S to form a precipitate which is a precursor to the sulfide. Through infrared spectroscopy and chemical analysis of the powder and gas chromatographic analysis of the liquid byproducts of the reaction, it is shown that a partially sulfidized alkoxide precursor forms through the displacement of alkoxy groups from the alkoxide by sulfur-bearing thiol groups. This thiolysis reaction is very similar to that which occurs in the case of sol–gel reactions to form oxides. The alkoxy–thiol species then undergo condensation–polymerization by the liberation of H₂S. When it is heat-treated in H₂S, this precursor transforms to TiS₂ at ∼700°C. Systematic heat treatments have been performed and the formation of TiS₂ has been observed using X-ray diffractometry. The change in the morphology has also been studied using scanning electron microscopy.     

Thiophene-based dendronized macromonomers and polymers

The synthesis of thiophene-containing second (G2) and third generation (G3) dendronized macromonomers with methacrylate polymerizable units as well as their corresponding dendronized polymers is reported. The dendrons are prepared from branched thiophene oligomers and are decorated with straight alkyl chains for solubility reasons. The polymerization reactions were done with AIBN as initiator and the polymers were characterized by NMR spectroscopy, elemental analysis and GPC. Molar masses are in the range of 2.2-5.4 × 10⁵ g mol⁻¹ (G2) and 1.3-3.0 × 10⁴ g mol⁻¹ (G3) for different runs. These polymers are investigated by cyclic voltammetry and optical spectroscopy.     

Damage Development and Moduli Reductions in Nicalon—Calcium Aluminosilicate Composites under Static Fatigue and Cyclic Fatigue

Unidirectional and cross-ply Nicalon fiber-reinforced calcium aluminosilicate (CAS) glass-ceramic composite specimens were subjected to tension–tension cyclic fatigue and static fatigue loadings. Microcrack densities, longitudinal Young's modulus, and major Poisson's ratio were measured at regular intervals of load cycles and load time. The matrix crack (0° plies) density and transverse crack (90° plies) density increased gradually with fatigue cycles and load time. The crack growth is environmentally driven and depends on the maximum load and time. Young's modulus and Poisson's ratio decreased gradually with fatigue cycles and load time. The saturation crack densities under fatigue loadings were found to be comparable to those under monotonic loading. A matrix crack growth limit strain exists, below which matrix cracks do not grow significantly under fatigue loading. This limit coincides with the matrix crack initiation strain. Linear correlations between crack density and moduli reductions obtained from quasi-static data can predict the moduli reductions under cyclic loading, using experimentally measured crack densities. A logarithmic correlation can predict the Young's modulus reduction in a limited stress range. A fatigue crack growth model is proposed to explain the presence of two distinct regimes of crack growth and Young's modulus reduction.     

A modified model and algorithm for flow‐enhanced crystallization—Application to fiber spinning

The graft copolymerization of acrylamide (AAm) monomer onto polyethylene‐coated polypropylene (PE‐co‐PP) nonwoven fabric was carried out by the mutual irradiation method. The general peculiarities of the grafting have been studied by gravimetric, scanning electron microscope (SEM), mechanical properties, and Fourier transform infrared (FTIR) methods. The influence of absorbed dose, dose rate, as well as the monomer concentration on the degree of grafting has been determined. Metal ions uptake of Cu²⁺, Co²⁺, Ni²⁺ by the grafted fabrics was evaluated. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 3240–3245, 2006     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

Graphical models for interactive POMDPs: representations and solutions

We develop new graphical representations for the problem of sequential decision making in partially observable multiagent environments, as formalized by interactive partially observable Markov decision processes (I-POMDPs). The graphical models called interactive influence diagrams (I-IDs) and their dynamic counterparts, interactive dynamic influence diagrams (I-DIDs), seek to explicitly model the structure that is often present in real-world problems by decomposing the situation into chance and decision variables, and the dependencies between the variables. I-DIDs generalize DIDs, which may be viewed as graphical representations of POMDPs, to multiagent settings in the same way that I-POMDPs generalize POMDPs. I-DIDs may be used to compute the policy of an agent given its belief as the agent acts and observes in a setting that is populated by other interacting agents. Using several examples, we show how I-IDs and I-DIDs may be applied and demonstrate their usefulness. We also show how the models may be solved using the standard algorithms that are applicable to DIDs. Solving I-DIDs exactly involves knowing the solutions of possible models of the other agents. The space of models grows exponentially with the number of time steps. We present a method of solving I-DIDs approximately by limiting the number of other agents’ candidate models at each time step to a constant. We do this by clustering models that are likely to be behaviorally equivalent and selecting a representative set from the clusters. We discuss the error bound of the approximation technique and demonstrate its empirical performance.