Greedy hot-potato routing on the two-dimensional mesh

Summary We propose hot-potato (or, deflection) packet routing algorithms on the two-dimensional mesh. The algorithms are strongly greedy in the sense that they attempt to send packets in good directions whenever possible. Furthermore, the routing operations are simple and independent of the time that has elapsed. The first algorithm gives the best evacuation time known for delivering all the packets to their destinations. A batch ofk packets with maximal source-to-destination distanced _max is delivered in 2(k-1)+d _max. The second algorithm improves this bound tok+d _max when all packets are destined to the same node. This also implies a new bound for the multitarget case, which is the first to take into account the number of in-edges of a node. The third algorithm is designed for routing permutations with source-to-destination distance at most three, in which case the algorithm terminates in at most seven steps. We also show a lower bound of five steps for this problem. Ishai Ben-Aroya received the B.A. and M.Sc. in computer science from the Technion (Israel Institute of Technology). He is currently working with Microsoft Israel R&D group. His main interests include Routing Algorithms, Cryptography and Computer Security. Tamar Eilam received the B.A. degree in Computer Science from the Technion IIL in 1995, and is currently studying towards her M.A. degree. Assaf Schuster received his B.A., M.A. and Ph.D. degrees in Computer Science from the Hebrew University of Jerusalem (the last one in 1991). He is currently a lecturer at the Technion IIL. His main interests include Networks and Routing Algorithms, Parallel and Distributed Computation, Optical Computation and Communication, Dynamically Reconfiguring Networks, and Greedy Hot Potato Routing.This work was supported in part by the French-Israeli grant for cooperation in Computer Science, and by a grant from the Israeli Ministry of Science. An extended abstract appeared in proc. 2nd European Symposium on Algorithms, September 1994     

Novel supports for nickel-based catalysts for the partial oxidation of methane

Zirconia-supported nickel catalysts with different amounts of aluminum (Al/Zr = 0.2, 1 and 2) were studied in this work in order to find alternative supports for nickel-based catalysts for the partial oxidation of methane. This reaction is a promising route for producing hydrogen and syngas for different applications. Samples were prepared by precipitation and impregnation techniques, characterized by several techniques and evaluated in the partial oxidation of methane in the range of 450–750 °C and 1 atm. It was found that aluminum affects the textural and catalytic properties of zirconia-supported nickel catalysts. The tetragonal phase of zirconia was stabilized by aluminum and gamma-alumina was also found in the aluminum-richest samples. Aluminum increased the porosity and the specific surface area of the solids. The catalytic activity also increased with the amount of aluminum in solids probably due to the stronger interaction of nickel with the support, which slowly generates active sites during the reduction step. The methane conversion and hydrogen selectivity increased with temperature, indicating no deactivation. The hydrogen to carbon monoxide molar ratio decreased due to aluminum but was not significantly affected by temperature. The coke produced was not harmful to the catalysts and aluminum affected its amount, although no simple relationship was found between these parameters. The most promising catalyst was the sample with aluminum to zirconium molar ratio of 2, which showed high activity and hydrogen selectivity and was stable under the reaction condition.     

Electrical Insulation Characteristics of Silicone and EPDM Polymeric Blends. I

The typical parts of a polymeric insulator are core, metal end fittings and polymeric housing material. The housing is intended to protect the fibre glass rod from the environment and electrical surface discharges. Since the housing materials are made of organic polymeric material, its insulation characteristics need to be studied. Amongst the many different polymers available, this work focuses on silicone rubber and ethylene propylene diene monomer (EPDM). Blends of EPDM and silicone rubber are prepared in a two roll mixing mill. Dicumyl peroxide is used as vulcanizing agent. The blends consisting of various proportions of component polymers are prepared, compression moulded into sheets, and post cured. The blends are tested for their insulation characteristics as per IEC and ASTM standards. Volume and surface resistivity, dielectric strength, dielectric constant, tan delta, tracking resistance, arc resistance, comparative tracking index, tensile strength, and percentage elongation at break of the blends are studied and discussed. The test results show that the increasing proportion of silicone enhances the electrical insulation properties whereas increasing weight percentage of EPDM improves the mechanical strength of the blends.     

Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model

The design and sustainability of reinforced concrete deep beam are still the main issues in the sector of structural engineering despite the existence of modern advancements in this area. Proper understanding of shear stress characteristics can assist in providing safer design and prevent failure in deep beams which consequently lead to saving lives and properties. In this investigation, a new intelligent model depending on the hybridization of support vector regression with bio-inspired optimization approach called genetic algorithm (SVR-GA) is employed to predict the shear strength of reinforced concrete (RC) deep beams based on dimensional, mechanical and material parameters properties. The adopted SVR-GA modelling approach is validated against three different well established artificial intelligent (AI) models, including classical SVR, artificial neural network (ANN) and gradient boosted decision trees (GBDTs). The comparison assessments provide a clear impression of the superior capability of the proposed SVR-GA model in the prediction of shear strength capability of simply supported deep beams. The simulated results gained by SVR-GA model are very close to the experimental ones. In quantitative results, the coefficient of determination (R²) during the testing phase (R² = 0.95), whereas the other comparable models generated relatively lower values of R² ranging from 0.884 to 0.941. All in all, the proposed SVR-GA model showed an applicable and robust computer aid technology for modelling RC deep beam shear strength that contributes to the base knowledge of material and structural engineering perspective.

     

A Scalable Parallel Algorithm for Reachability Analysis of Very Large Circuits

This paper presents a scalable method for parallelizing symbolic reachability analysis on a distributed-memory environment of workstations. We have developed an adaptive partitioning algorithm that significantly reduces space requirements. The memory balance is maintained by dynamically repartitioning the state space throughout the computation. A compact BDD representation allows coordination by shipping BDDs from one machine to another. This representation allows for different variable orders in the sending and receiving processes. The algorithm uses a distributed termination protocol, with none of the memory modules preserving a complete image of the set of reachable states. No external storage is used on the disk. Rather, we make use of the network, which is much faster.We implemented our method on a standard, loosely-connected environment of workstations, using a high-performance model checker. Initial performance evaluation of several large circuits shows that our method can handle models too large to fit in the memory of a single node. The partitioning algorithm achieves reduction in space, which is linear in the number of workstations employed. A corresponding decrease in space requirements is measured throughout the reachability analysis. Our results show that the relatively slow network does not become a bottleneck, and that computation time is kept reasonably small.     

Le monde de la recherche

The factors used in this model are financial stability, experience, references, past performance, current work load, staff availability, manpower resources, company organization, office location, experience in geographic location of project, quality performance, failure to complete contracts, procurement experience, safety consciousness and claim attitude.     

Electrodeposition behavior of zinc–nickel–iron alloys from sulfate bath

The present work is directed at collecting the properties of Zn–Ni and Zn–Fe alloys in one alloy via the electrodeposition of Zn–Ni–Fe ternary alloy. Electrodeposition of ternary Zn–Ni–Fe alloy was investigated and compared with the characteristics of Zn–Ni electrodeposits. The electrodeposition was performed from a sulfate bath onto a steel substrate. Structural analysis by X-ray diffraction (XRD) method revealed that the Zn–Ni–Fe alloys consisted of a mixture of zinc, and (γ-Ni₂Zn₁₁) and (Fe₃Ni₂) phases. The study was carried out using electrochemical methods such as cyclic voltammetry and galvanostatic for electrodeposition, while anodic linear polarization resistance and anodic linear sweeping voltammetry techniques were used for the corrosion study. Surface morphology and chemical composition of the deposits were also examined by using scanning electron microscopy and atomic absorption spectroscopy, respectively. It was found that the obtained Zn–Ni–Fe alloy exhibited more preferred surface appearance and better corrosion resistance without adding any organic brighteners to the plating bath in comparison to Zn–Ni alloy that electrodeposited at similar conditions. Results obtained revealed that the increase in corrosion resistance of ternary deposits is not only attributed to the formation of (γ-Ni₂Zn₁₁) phase, but also to iron codeposition and formation of (Fe₃Ni₂) phase.     

Certain Biominerals in Leaves Function as Light Scatterers

Cystoliths are amorphous calcium carbonate bodies that form in the leaves of some plant families. Cystoliths are regularly distributed in the epidermis and protrude into the photosynthetic tissue, the mesophyll. The photosynthetic pigments generate a steep light gradient in the leaf. Under most illumination regimes the outer mesophyll is light saturated, thus the photosynthetic apparatus is kinetically unable to use the excess light for photochemistry. Here we use micro‐scale modulated fluorometry to demonstrate that light scattered by the cystoliths is distributed from the photosynthetically inefficient upper tissue to the efficient, but light deprived, lower tissue. The results prove that the presence of light scatterers reduces the steep light gradient, thus enabling the leaf to use the incoming light flux more efficiently. MicroCT and electron microscopy confirm that the spatial distribution of the minerals is compatible with their optical function. During the study we encountered large calcium oxalate druses in the same anatomical location as the cystoliths. These druses proved to have similar light scattering functions as the cystoliths. This study shows that certain minerals in the leaves of different plants distribute the light flux more evenly inside the leaf.     

Synthesis and characterization of polycaprolactone/acrylic acid (PCL/AA) hydrogel for controlled drug delivery

In the present work biodegradable pH-sensitive polycaprolactone/acrylic acid (PCL/AA) hydrogels have been developed using ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide as initiator. For these prepared hydrogels swelling studies, sol-gel fraction analysis and porosity measurements were performed. Results show that swelling of the hydrogels decreases on increasing the concentration of PCL and EGDMA, however swelling of hydrogels increases on increasing the concentration of AA. Results of sol-gel fraction analysis show that gel fraction increases on increasing concentration of monomer AA, polymer PCL as well as cross-linker EGDMA. As far as porosity is concerned, it increases on increasing the concentration of AA and PCL while porosity decreases on increasing the concentration of EGDMA. Hydrogels were characterized by measuring diffusion coefficient (D) and equilibrium water content (EWC). Network formation, morphology and crystallinity of PCL/AA hydrogels were investigated using FTIR, SEM and XRD, respectively. Tramadol hydrochloride was loaded as model drug and its release pattern was analysed using various kinetic models like zero order, first order, Higuchi and Peppas. Results indicated that most of the samples followed non-Fickian release mechanism.