Learning-theoretic perspectives of acceptable numberings

A class of recursive functionsC islimiting standardizable, in a programming system , iff there is an effective procedure which, given any -program (in the -system), synthesizes in the limit acanonical -program which is equivalent to the former. It can arguably be expected that notions similar to the above one would be relevant toGold-style function learning, which features, among other things, the effective limiting synthesis of programs for input recursive functions. Many learning classes have been characterized in terms of variants of the above notion. In this paper, we focus on the limiting standardizability of the entire class of recursive functions inEffective programming systems. To start with, we prove the independence of this notionvis-à-vis finitary recursion theorems. Secondly, we show that this motion does not entail acceptability, in the spirit of the results of Case, Riccardi and Royer on characterizations of the samevis-à-vis programming language control structures.     

An electron microscopic investigation of oxides related to ß-alumina

High resolution electron microscopic (HREM) investigation of potassium-alumina and the related gallate and ferrite has revealed that whereas the aluminate and gallate are highly disordered, consisting of random sequence of and units, the ferrite is more ordered. The aluminate and gallate are sensitive to electron beam irradiation exhibiting beam-induced damage similar to sodium-alumina. Significantly, the ferrite is beamstable, the difference in behaviour amongst these related oxides arising from the different mechanisms by which alkali metal nonstoichiometry is accommodated. Barium hexaaluminate and hexaferrite are both highly ordered; specimens prepared by the barium borate flux method exhibit a new 3a×3a superstructure of the hexagonal magnetoplumbite cell.Contribution No. 241 from the Solid State and Structural Chemistry Unit.     

Heating value of biomass and biomass pyrolysis products

Studies conducted on the heating value of various types of biomass components and their pyrolysis products such as char, liquids and gases are presented. Heating values of chars are comparable with those of lignite and coke; heating values of liquids are comparable with those of oxygenated fuels such as methanol and ethanol, which are much lower than those of petroleum fuels. Heating values of gases are comparable with those of producer gas or coal gas and are much lower than that of natural gas. It is also found that the heating values of products are functions of the initial composition of biomass; correlations are developed to express these. Also, correlations are developed which explain the influence of ash elements on heating values of the pyrolysis products and on percentage distribution of energy in the products.     

Development of environmentally responsive hydrogels with metal affinity behavior

This work describes initial efforts to incorporate affinity ligands within an environmentally responsive hydrogel. Metal affinity ligands were chosen as model affinity groups and thermally responsive N‐isopropyl acrylamide/acrylamide copolymers were used as the base hydrogels. The ? NH₂ group of the acrylamide serves as a reactive group for functionalization with metal affinity ligands. The gels were synthesized by free radical polymerization and Cu²⁺ was bound to the gel via 1,4‐butanediol diglycidyl ether (BDE) as a linker and iminodiacetic acid (IDA) as a chelating ligand. The base acrylamide gels were also functionalized with metal affinity ligands to allow for comparison with thermally responsive affinity gels. The results show the effectiveness of this technique for both these types of gels, and an improved method to immobilize metal affinity groups on to thermally sensitive N‐isopropyl acrylamide gels was also developed. It was seen that the yields for the reaction with BDE decreased with increased reaction time in both kinds of gels, whereas reaction with IDA showed a decrease in yields with increase in temperature for N‐isoporpyl acrylamide gels and increase in yields for acrylamide gels. Further techniques were developed to overcome diffusional resistances and stresses in the thermally responsive N‐isopropyl acrylamide gels so as to improve the distribution of Cu²⁺ ions. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2007     

Magnetization study of Fe-doped ZnO co-doped with Cu: Synthesized by wet chemical method

Fe- and Cu-doped ZnO of nominal compositions Zn_0.95Fe_0.05O and Zn_0.94Fe_0.05Cu_0.01O were synthesized by a wet chemical route. X-ray diffraction analysis of the samples annealed at 575 K showed that they are single phase without any secondary phases. DC magnetization measurements of Cu co-doped samples (Zn_0.94Fe_0.05Cu_0.01O) as a function of field at room temperature showed ferromagnetic signature while the samples without Cu co-doping (Zn_0.95Fe_0.05O) are paramagnetic in nature. On increasing the temperature of annealing from 575 K to 1,075 K an impurity phase emerges in both the samples, which has been identified as a variant of ZnFe₂O₄. Both the samples heated at and above 1,075 K are found to be paramagnetic at room temperature. These observations, the absence of room temperature ferromagnetism in Zn_0.95Fe_0.05O and the disappearance of ferromagnetism in Zn_0.94Fe_0.05Cu_0.01O on raising the temperature of annealing clearly rules out the likelihood of room temperature ferromagnetism arising from the impurity phases like γ-Fe₂O₃ and/or ZnFe₂O₄ that might have been formed during the synthesis. Our results strongly suggest that room temperature ferromagnetism in Zn_0.94Fe_0.05Cu_0.01O can be attributed to the formation of a secondary phase of Cu-doped ZnFe₂O₄.     

Estimation of composite damage model parameters using spectral finite element and neural network

A multi-layer perceptron (MLP) network using error back propagation algorithm is employed in this paper to estimate the damage parameters from broad-band spectral data as diagnostic signal. Various existing models of damage in laminated composite and the resulting stiffness degradation are discussed from comparative view-point. Degradation of ply properties can be considered to be one of the damage model parameters while monitoring transverse matrix cracks in cross-ply, splitting in longitudinal ply, and evolution of consecutive stages of damage, such as delaminations and fiber fracture. The stiffness degradation factor, the location and size of the damaged zone in laminated composite beam are considered as damage model parameters in the present paper. Fourier spectral data, which is typical to most of the diagnostic wave measurements, are used as input to the neural network. Since, training the neural network in such case involves many data sets and all of these data are difficult to generate using experiments, a spectral finite element model (SFEM) with embedded degraded zone in laminated composite beam is developed. Numerical simulation using this element is carried out, which shows the nature of temporal signal that are likely to be measured. Analytical studies on the performance of the neural network are presented based on numerically simulated data. Effect of measurement noise on the network performance is also reported.     

Neural networks for estimating the tool path length in concurrent engineering applications

This paper deals with the development of a neural computing system that can predict the cutting tool path length for milling an arbitrary pocket defined within the domain of a product design, in a computer numerically controlled (CNC) setting. Existing computer aided design and manufacturing systems (CAD/CAM) consume significant amounts of time in terms of data entry pertaining to the geometries and subsequent modifications to them. In the concurrent engineering environment, where even the designer needs information from the CAD/CAM systems, such time-consuming processes can be expensive. To alleviate this problem, a neural network system can be used to estimate machining time by predicting cost-dependent variables such as tool path length for the pocket milling operation. Pockets are characterized and classified into various groups. A randomized design is described so that the training samples that have been chosen represent the domain evenly. An appropriate network was built and trained with the sample pocket geometries. The analysis of the performance of the system in terms of tool path length prediction for new pocket geometries is presented.     

Design of fuzzy expert system for microarray data classification using a novel Genetic Swarm Algorithm

Knowledge gained through classification of microarray gene expression data is increasingly important as they are useful for phenotype classification of diseases. Different from black box methods, fuzzy expert system can produce interpretable classifier with knowledge expressed in terms of if-then rules and membership function. This paper proposes a novel Genetic Swarm Algorithm (GSA) for obtaining near optimal rule set and membership function tuning. Advanced and problem specific genetic operators are proposed to improve the convergence of GSA and classification accuracy. The performance of the proposed approach is evaluated using six gene expression data sets. From the simulation study it is found that the proposed approach generated a compact fuzzy system with high classification accuracy for all the data sets when compared with other approaches.     

A new fluoride mediated synthesis of mesoporous silica and their usefulness in controlled delivery of duloxetine hydrochloride a serotonin re-uptake inhibitor

A new type of mesoporous silica nanoparticle (MSN) was synthesized in fluoride media via sol–gel technique using TritonX 100 and Tween-20. The surface area and pore volume of the MSN particles were modified by varying the concentration of Tween-20. The prepared MSN nanoparticles with large surface area and pore volume (T-2, T-3) were selected to accommodate the model drug duloxetine hydrochloride (DX) for evaluation of their drug-loading and release abilities. Calcined and DX loaded nanoparticles were characterized by Brunauer–Emmett–Teller technique (BET), powder X-ray diffraction (XRD), scanning electron microscopy (SEM), thermogravimetric (TG) analysis and UV-diffuse reflectance (UV-DRS). In vitro release studies proved that the particle displays an initial burst release followed by sustained release for up to 140 h. From the studies it is evident that the synthesized particle may be useful as a carrier for sustained release of active pharmaceutical ingredients (APIs).