Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed. (c) 2004 Elsevier Ltd. All rights reserved.

Comparison and evaluation of the specificity and binding capacity of commercial and in house affinity columns used in sample preparation for analysis of growth-promoting drugs

Immunoaffinity chromatography (IAC) and affinity chromatography (AC:) are widely used for extraction of drugs from biological samples. Fifteen column types were purchased from five different manufacturers and;their ability to bind specific drugs including beta-agonists and anabolic steroids over a range of analyte concentrations in fortified bovine urine samples was assessed. The performance data obtained from these columns were compared with columns produced in this laboratory (in house columns). The in house columns gave the highest recoveries, ranging from 92 to 100% at the 1 ng spiking concentration, for five of the seven analytes assessed. Forty percent (11 of 27) of all the commercial column assessments recorded recoveries of less than 50% even when the lowest spiking concentration was applied (1 ng). For one manufacturer, only one of seven different columns purchased delivered extraction efficiencies greater than 50%. The extraction efficiencies of the clenbuterol columns were the highest with all commercially prepared columns showing at least 50% binding of radiolabelled tracer. Recoveries of alpha-nortestosterone were the lowest. The variability of these products with respect to quality control requires constant monitoring.

Kinetics of methylene blue (MB) photocatalyzed reduction and dark regeneration in a colorimetric oxygen sensor

Performance data for a dye based, regenerable oxygen sensor (Mills and Lawrie [1], Mills et al. [2]) are analyzed to develop useful kinetic models for sensor photoactivation (dye reduction) and dark, oxygen detection (dye oxidation). The titania loaded, thin film sensor exhibits an apparent first order photoactivation of the dye, which we demonstrate (Section 3.2 and Fig. 4) is due to a kinetic disguise of a zero order photoreaction occurring through a non-uniformly illuminated sensor film. The observed zero order, slow recovery due to dye oxidation by dioxygen (O2 detection) appears best rationalized by a model assuming a near O2-impermeable skin developing on the sensor surface as solvent is evaporatively removed following sensor film casting and curing.

Optimal deployment of geographically distributed workflow engines on the cloud

When orchestrating Web service workflows, the geographical placement of the orchestration engine (s) can greatly affect workflow performance. Data may have to be transferred across long geographical distances, which in turn increases execution time and degrades the overall performance of a workflow. In this paper, we present a framework that, given a DAG-based workflow specification, computes the optimal Amazon EC2 cloud regions to deploy the orchestration engines and execute a workflow. The framework incorporates a constraint model that solves the workflow deployment problem, which is generated using an automated constraint modelling system. The feasibility of the framework is evaluated by executing different sample workflows representative of scientific workloads. The experimental results indicate that the framework reduces the workflow execution time and provides a speed up of 1.3x-2.5x over centralised approaches.

DocLite: A Docker-Based Lightweight Cloud Benchmarking Tool

Existing benchmarking methods are time consuming processes as they typically benchmark the entire Virtual Machine (VM) in order to generate accurate performance data, making them less suitable for real-time analytics. The research in this paper is aimed to surmount the above challenge by presenting DocLite - Docker Container-based Lightweight benchmarking tool. DocLite explores lightweight cloud benchmarking methods for rapidly executing benchmarks in near real-time. DocLite is built on the Docker container technology, which allows a user-defined memory size and number of CPU cores of the VM to be benchmarked. The tool incorporates two benchmarking methods - the first referred to as the native method employs containers to benchmark a small portion of the VM and generate performance ranks, and the second uses historic benchmark data along with the native method as a hybrid to generate VM ranks. The proposed methods are evaluated on three use-cases and are observed to be up to 91 times faster than benchmarking the entire VM. In both methods, small containers provide the same quality of rankings as a large container. The native method generates ranks with over 90% and 86% accuracy for sequential and parallel execution of an application compared against benchmarking the whole VM. The hybrid method did not improve the quality of the rankings significantly.

Generating Data Augmented Spectroscopic Data For Performance Enhancement

The application of chemometrics in food science has revolutionized the field by allowing the creation of models able to automate a broad range of applications such as food authenticity and food fraud detection. In order to create effective and general models able to address the complexity of real life problems, a vast amount of varied training samples are required. Training dataset has to cover all possible types of sample and instrument variability. However, acquiring a varied amount of samples is a time consuming and costly process, in which collecting samples representative of the real world variation is not always possible, specially in some application fields. To address this problem, a novel framework for the application of data augmentation techniques to spectroscopic data has been designed and implemented. This is a carefully designed pipeline of four complementary and independent blocks which can be finely tuned depending on the desired variance for enhancing model's robustness: a) blending spectra, b) changing baseline, c) shifting along x axis, and d) adding random noise.
This novel data augmentation solution has been tested in order to obtain highly efficient generalised classification model based on spectroscopic data. Fourier transform mid-infrared (FT-IR) spectroscopic data of eleven pure vegetable oils (106 admixtures) for the rapid identification of vegetable oil species in mixtures of oils have been used as a case study to demonstrate the influence of this pioneering approach in chemometrics, obtaining a 10% improvement in classification which is crucial in some applications of food adulteration.

Drivetrain Effects on Small Engine Performance

Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the methods developed previously by Callahan, et al. (1) to examine a variety of two-stroke engines and one four-stroke engine. The two-stroke engines were: a high performance single-cylinder, a low performance single-cylinder, a high performance multi-cylinder, and a medium performance multi-cylinder. The four-stroke engine was a high performance single-cylinder unit. Each engine was modeled in Virtual Engines, which is a fully detailed one-dimensional thermodynamic engine simulator. Measured or predicted in-cycle speed data were input into the engine models. Predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The simulations for the high performance single-cylinder two-stroke engine predicted significant in-cycle crankshaft speed fluctuation amplitudes and significant changes in performance when the fluctuations were input into the engine model. This was validated experimentally on a firing test engine based on a Yamaha YZ250. The four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation assumed in the model. Measured speed fluctuations from a firing Yamaha YZ400F engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar fluctuation profiles and changes in performance. It is shown that the gear reduction between the crankshaft and clutch allowed for this similar behavior. The multi-cylinder, high performance two-stroke engine also showed significant changes in performance, in this case depending on the firing configuration. The low output two-stroke engine simulation showed only a negligible change in performance in spite of high amplitude speed fluctuations. This was due to its flat torque versus speed characteristic. The medium performance multi-cylinder two-stroke engine also showed only a negligible change in performance, in this case due to a relatively high inertia rotating assembly and multiple cylinder firing events within the revolution. These smoothed the net torque pulsations and reduced the amplitude of the speed fluctuation itself.

Directional performance in motion transparency

Motion transparency provides a challenging test case for our understanding of how visual motion, and other attributes, are computed and represented in the brain. However, previous studies of visual transparency have used subjective criteria which do not confirm the existence of independent representations of the superimposed motions. We have developed measures of performance in motion transparency that require observers to extract information about two motions jointly, and therefore test the information that is simultaneously represented for each motion. Observers judged whether two motions were at 90 to one another; the base direction was randomized so that neither motion taken alone was informative. The precision of performance was determined by the standard deviations (S.D.s) of probit functions fitted to the data. Observers also made judgments of orthogonal directions between a single motion stream and a line, for one of two transparent motions against a line and for two spatially segregated motions. The data show that direction judgments with transparency can be made with comparable accuracy to segregated (non-transparent) conditions, supporting the idea that transparency involves the equivalent representation of two global motions in the same region. The precision of this joint direction judgment is, however, 2–3 times poorer than that for a single motion stream. The precision in directional judgment for a single stream is reduced only by a factor of about 1.5 by superimposing a second stream. The major effect in performance, therefore, appears to be associated with the need to compute and compare two global representations of motion, rather than with interference between the dot streams per se. Experiment 2tested the transparency of motions separated by a range of angles from 5 to 180 by requiring subjects to set a line matching the perceived direction of each motion. The S.D.s of these settings demonstrated that directions of transparent motions were represented independently for separations over 20. Increasing dot speeds from 1 to 10 deg/s improved directional performance but had no effect on transparency perception. Transparency was also unaffected by variations of density between 0.1 and 19 dots/deg2

Examining architects' performance in Nigeria private and public sectors building projects

Abstract: Purpose – The aim of this paper is to examine and compare the performance of architects with respect to clients' rating of importance over a set of performance criteria in Nigerian public and private sector building projects. Design/methodology/approach – A survey involving clients from both public and private sectors of recently completed building projects in Nigeria was undertaken. Data analysis includes comparing similarities and differences using standardised ratio, Mann Whitney U and Wilcoxon tests. Findings – The results show that private sector clients are likely to be more concerned with cost, while public sector clients are more concerned with buildability of design. A total of 79 per cent of the criteria were similarly selected by both sectors with respect to importance of the criteria. Architects need to improve their performance significantly in about 82 per cent of the whole set of 28 criteria. The architects performed better in the public sector than the private sector and 14 per cent of the criteria were indicated as being statistically different in terms of architects' performance. Originality/value – The results provide feedback which can be incorporated in architects' future projects so as to ensure successful project implementation in the building delivery process.

Client's assessment of architects' performance in building delivery process: Evidence from Nigeria

The overall intent of this research is to provide architects with information that can be used to improve their performance so as to optimally satisfy the client's requirements and achieve high-quality overall project performance in Nigerian construction industry. Architect performance criteria were identified based on literature within the domain of architect responsibilities. The assessment of architects’ performance was carried out through a questionnaire survey of clients of recently completed building projects in Nigeria. Analysis of data includes comparison of criteria using importance–performance index analysis. Factor analysis was carried out on criteria where architects are falling below average, to group and explore the latent structure of the criteria in the data. The results showed that the architect needs to focus on management skills and ability, buildability, design quality, project communication, project integration and client focus. These results would encourage architects to perform better within their full responsibilities in the building delivery process and deliver high-quality projects within Nigerian construction industry.