Twinning-induced sluggish evolution of texture during recrystallization in AISI 316L stainless steel after cold rolling

This paper deals with the evolution of texture in AISI 316L austenitic stainless steel during annealing after 95 pct cold rolling. After 95 pct cold rolling, the texture is mainly of the brass type {110}〈112〉, along with a scatter toward the S orientation {123}〈634〉 and Goss orientation {011}〈100〉. Weak evidence of Cu component is observed at this high deformation level. During annealing, recovery is observed before any detectable recrystallization. Recrystallization proceeds through nucleation of subgrain by twinning within the deformed matrix and, later, preferential growth of those to consume the deformed matrix. After recrystallization, the overall texture intensity was weak; however, there are some discernible texture components. There was no existence of the brass component at this stage. Major components are centered on Goss orientation and Cu component {112}〈111〉 as well as the BR component {236}〈385〉. Also, a few orientations come up after recrystallization (i.e., {142}〈2−11〉 and {012}〈221〉). With increase in annealing temperature, the textural evolution shows emergence of weak texture with another new component, {197}〈211〉. The evolution of texture was correlated with the deformation texture through twin chain reaction.     

Utilizing Genetic Algorithms to Optimize Membership Functions for Fuzzy Weighted Association Rules Mining

It is not an easy task to know a priori the most appropriate fuzzy sets that cover the domains of quantitative attributes for fuzzy association rules mining. In general, it is unrealistic that experts can always provide such sets. And finding the most appropriate fuzzy sets becomes a more complex problem when items are not considered to have equal importance and the support and confidence parameters required for the association rules mining process are specified as linguistic terms. Existing clustering based automated methods are not satisfactory because they do not consider the optimization of the discovered membership functions. In order to tackle this problem, we propose Genetic Algorithms (GAs) based clustering method, which dynamically adjusts the fuzzy sets to provide maximum profit based on user specified linguistic minimum support and confidence terms. This is achieved by tuning the base values of the membership functions for each quantitative attribute with respect to two different evaluation functions maximizing the number of large itemsets and the average of the confidence intervals of the generated rules. To the best of our knowledge, this is the first effort in this direction. Experiments conducted on 100 K transactions from the adult database of United States census in year 2000 demonstrate that the proposed clustering method exhibits good performance in terms of the number of produced large itemsets and interesting association rules.     

Neural network optimized with evolutionary computing technique for solving the 2-dimensional Bratu problem

In this paper, a stochastic technique is developed to solve 2-dimensional Bratu equations using feed-forward artificial neural networks, optimized with genetic and interior-point algorithms. The 2-dimensional equations are first transformed into a 1-dimensional boundary value problem, and a mathematical model of the transformed equation is then formulated with neural networks using an unsupervised error. Network weights are optimized to minimize the error. Evolutionary computing based on genetic algorithms is used as a tool for global search, integrated with an interior-point method for rapid local convergence. The methodology is applied to solve three cases of boundary value problems for the Bratu equations. The accuracy, convergence and effectiveness of the scheme is validated for a large number of simulations. Comparison of results is made with the exact solution derived using MATHEMATICA, and is found to be in good agreement.     

Term rewriting and its application to recognizing handwritten Hindu numerals

In this paper the theoretical basis is presented and the implementation of a term rewriting system based on algebraic specifications is described. The input to this system is represented by an algebraic specification language, which forms not only the set of axioms but also the sorts, variables, operators and terms of a specific simulated theory or application. Rewriting and matching mechanisms provide the formal methodology for evaluating terms and proving assertions in an algebraic theory. Specifications are evaluated by interpreting terms by means of rewrite rules. The rules are described by the axioms of the specifications where the finite termination and congruence properties are assumed. A term rewriting system to recognize handwritten Hindu numerals is introduced as a case study. Besides rewriting, a robust algorithm is proposed to segment the numeral's image into strokes based on feature points and to identify cavity features. A syntactic representation (term) of the input image is matched and rewritten against a set of rules. Experimental results proved that the proposed system is tolerant to recognize a variety of numeral shapes with 96% successful recognition rate.     

An integrated approach for groundwater potential zoning in shallow fracture zone aquifers

This study presents an integrated approach for the identification of groundwater occurrences in shallow fracture zone (SFZ) aquifers using remote-sensing, geological, and geophysical data. The Central Eastern Desert of Egypt was selected as a test site for the present study. The distribution of major faults and shear zones was extracted from a fusion image generated by injecting high-spatial resolution phased array L-band synthetic aperture radar (PALSAR) images into Landsat Enhanced Thematic Mapper images. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) digital elevation model was processed to extract the drainage systems, slope, and topographic wetness index (TWI). The multidate PALSAR imagery acquired during rainy and dry seasons was used to estimate the relative soil moisture content. The lithology, fractures, drainage density, slope, TWI, and soil moisture content were used as thematic layers for groundwater occurrence in the SFZ aquifers. A GIS model of groundwater potential was developed by selecting the most probable locations for groundwater in each layer. The results indicate that the spatial distribution of the existing water wells is in agreement with the model where all wells fall in the regions of high groundwater potential zones. A geophysical survey was conducted using ground penetrating radar (GPR), indicating that the high groundwater potential zones are promising for drilling shallow wells. The adopted approach can be used as a cost-effective tool for groundwater exploration in the SFZ aquifers in the study area and in areas of similar geologic and hydrogeologic settings elsewhere.     

The use of new technologies in coloration of textile fibers

Textile coloration is a wet process that uses dyes, chemicals, and large volume of water. The chemical wet processing of textiles continues to expand each year using new technologies. The driving force being the need for cleaner, cost-effective, and value-added textile products. This review will provide a summary of recent developments in the coloration of textile fiber. Emphasis will be paid to the new technologies, in particular those based on physicochemical means such as nanotechnology, electrochemistry, supercritical carbon dioxide coloration, plasma, ultrasonic and microwave, and their uses in the coloration of textile fibers.     

A tool to minimize the time costs of parallel computations through optimal processing power allocation

In this paper, we present a software system, OPAS (Optimal Allocation System), that incorporates the optimal allocation policy in the analysis of the time-cost behaviour of parallel computations. OPAS assumes that the underlying system which supports the executions of parallel computations has a finite number of processors, that all the processors have the same speed and that the communication is achieved through a shared memory. OPAS defines the time cost as a function of the input, the algorithm, the data structure, the processor speed, the number of processors and the processing power allocation. In analysing the time cost of a computation, OPAS first uses the optimal allocation policy that we developed previously to determine the amount of processing power each node receives and then derives the computation's time cost. OPAS can evaluate different time-cost behaviours, such as the minimum time cost, the maximum time cost, the average time cost and the time-cost variance. It can also determine the speed-up and efficiency, and plot the time-cost curve and time-cost distribution.     

Development of controlled strength-loss resorbable beta-tricalcium phosphate bioceramic structures

Controlling the strength-loss rate during biodegradation is a bottleneck in developing viable resorbable ceramic implants. Resorbable beta-tricalcium phosphate (β-TCP) bioceramic is known for its excellent biocompatibility. However, it exhibits poor sinterability and poor flexural strength. Here, we improved sintering behavior and biaxial flexural strength of β-TCP bioceramic without altering its biocompatibility by introducing multi-oxide sintering additives, in small quantities. These additives could also tailor the rate of resorption and hardness deterioration of β-TCP. A range of additives were prepared and introduced into β-TCP powder. Resultant powders were uniaxially pressed and sintered at 1250 °C, in air. Considerable improvement in densification (up to 33%) and biaxial flexural strength (up to 43%) were achieved. X-ray powder diffraction (XRD) analysis confirmed that the additives didn't alter the phase purity. In vitro cytotoxicity and biocompatibility analyses were performed using a prostate cancer cell-line. Results showed that the doped and pure β-TCP structures were non-toxic and biocompatible.     

A copper–cyclen coordination complex associated with a polyoxometalate anion: Synthesis,crystal structure and electrochemistry of [Cu(cyclen)(MeCN)][W6O19]

The reaction between Cu(NO₃)₂·3H₂O and a tetra-aza macrocycle, more specifically, cyclen in 1:1 MeCN–MeOH solvent mixture forms a Cu²⁺–cyclen coordination complex in situ, that has been reacted with an isopolyanion [W₆O₁₉]^2? in a slow diffusion technique, resulting in the isolation of an ion-pair solid [Cu(cyclen)(MeCN)][W₆O₁₉] (1). Single crystal structural investigation on 1 shows a square pyramidal geometry around the metal centre (copper ion) with an axially bound MeCN solvent molecule. The title compound 1 is the first crystallographically characterized ion-pair compound, in which a transition metal coordination complex of a tetra-aza-crown ether (cyclen) has been associated with a polyoxometalate cluster anion. This communication deals with synthesis, spectroscopic, structural and electrochemical analyses of compound 1.