Response normalization and blur adaptation:data and multi-scale model

Adapting to blurred or sharpened images alters perceived blur of a focused image (M. A. Webster, M. A. Georgeson, & S. M. Webster, 2002). We asked whether blur adaptation results in (a) renormalization of perceived focus or (b) a repulsion aftereffect. Images were checkerboards or 2-D Gaussian noise, whose amplitude spectra had (log-log) slopes from -2 (strongly blurred) to 0 (strongly sharpened). Observers adjusted the spectral slope of a comparison image to match different test slopes after adaptation to blurred or sharpened images. Results did not show repulsion effects but were consistent with some renormalization. Test blur levels at and near a blurred or sharpened adaptation level were matched by more focused slopes (closer to 1/f) but with little or no change in appearance after adaptation to focused (1/f) images. A model of contrast adaptation and blur coding by multiple-scale spatial filters predicts these blur aftereffects and those of Webster et al. (2002). A key proposal is that observers are pre-adapted to natural spectra, and blurred or sharpened spectra induce changes in the state of adaptation. The model illustrates how norms might be encoded and recalibrated in the visual system even when they are represented only implicitly by the distribution of responses across multiple channels.

A Generic model for the design and analysis of production systems

This dissertation studies the process of operations systems design within the context of the manufacturing organization. Using the DRAMA (Design Routine for Adopting Modular Assembly) model as developed by a team from the IDOM Research Unit at Aston University as a starting point, the research employed empirically based fieldwork and a survey to investigate the process of production systems design and implementation within four UK manufacturing industries: electronics assembly, electrical engineering, mechanical engineering and carpet manufacturing. The intention was to validate the basic DRAMA model as a framework for research enquiry within the electronics industry, where the initial IDOM work was conducted, and then to test its generic applicability, further developing the model where appropriate, within the other industries selected. The thesis contains a review of production systems design theory and practice prior to presenting thirteen industrial case studies of production systems design from the four industry sectors. The results and analysis of the postal survey into production systems design are then presented. The strategic decisions of manufacturing and their relationship to production systems design, and the detailed process of production systems design and operation are then discussed. These analyses are used to develop the generic model of production systems design entitled DRAMA II (Decision Rules for Analysing Manufacturing Activities). The model contains three main constituent parts: the basic DRAMA model, the extended DRAMA II model showing the imperatives and relationships within the design process, and a benchmark generic approach for the design and analysis of each component in the design process. DRAMA II is primarily intended for use by researchers as an analytical framework of enquiry, but is also seen as having application for manufacturing practitioners.

Memory effects in a non-equilibrium growth model

We study memory effects in a kinetic roughening model. For d=1, a different dynamic scaling is uncovered in the memory dominated phases; the Kardar-Parisi-Zhang scaling is restored in the absence of noise. dc=2 represents the critical dimension where memory is shown to smoothen the roughening front (a=0). Studies on a discrete atomistic model in the same universality class reconfirm the analytical results in the large time limit, while a different scaling behavior shows up for tmodel. Results can be generalized for other nonconservative systems.

Proteomic analysis of a noninvasive human model of acute inflammation and its resolution:the twenty-one day gingivitis model

The 21-day experimental gingivitis model, an established noninvasive model of inflammation in response to increasing bacterial accumulation in humans, is designed to enable the study of both the induction and resolution of inflammation. Here, we have analyzed gingival crevicular fluid, an oral fluid comprising a serum transudate and tissue exudates, by LC-MS/MS using Fourier transform ion cyclotron resonance mass spectrometry and iTRAQ isobaric mass tags, to establish meta-proteomic profiles of inflammation-induced changes in proteins in healthy young volunteers. Across the course of experimentally induced gingivitis, we identified 16 bacterial and 186 human proteins. Although abundances of the bacterial proteins identified did not vary temporally, Fusobacterium outer membrane proteins were detected. Fusobacterium species have previously been associated with periodontal health or disease. The human proteins identified spanned a wide range of compartments (both extracellular and intracellular) and functions, including serum proteins, proteins displaying antibacterial properties, and proteins with functions associated with cellular transcription, DNA binding, the cytoskeleton, cell adhesion, and cilia. PolySNAP3 clustering software was used in a multilayered analytical approach. Clusters of proteins that associated with changes to the clinical parameters included neuronal and synapse associated proteins.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

Earlier development of analytical than holistic object recognition in adolescence

Background. Previous research has shown that object recognition may develop well into late childhood and adolescence. The present study extends that research and reveals novel differences in holistic and analytic recognition performance in 7-12 year olds compared to that seen in adults. We interpret our data within a hybrid model of object recognition that proposes two parallel routes for recognition (analytic vs. holistic) modulated by attention. Methodology / Principal Findings. Using a repetition-priming paradigm, we found in Experiment 1 that children showed no holistic priming, but only analytic priming. Given that holistic priming might be thought to be more ‘primitive’, we confirmed in Experiment 2 that our surprising finding was not because children’s analytic recognition was merely a result of name repetition. Conclusions / Significance. Our results suggest a developmental primacy of analytic object recognition. By contrast, holistic object recognition skills appear to emerge with a much more protracted trajectory extending into late adolescence.

Uncatalysed and potassium-catalysed pyrolysis of the cell-wall constituents of biomass and their model compounds

Cell-wall components (cellulose, hemicellulose (oat spelt xylan), lignin (Organosolv)), and model compounds (levoglucosan (an intermediate product of cellulose decomposition) and chlorogenic acid (structurally similar to lignin polymer units)) have been investigated to probe in detail the influence of potassium on their pyrolysis behaviours as well as their uncatalysed decomposition reaction. Cellulose and lignin were pretreated to remove salts and metals by hydrochloric acid, and this dematerialized sample was impregnated with 1% of potassium as potassium acetate. Levoglucosan, xylan and chlorogenic acid were mixed with CHCOOK to introduce 1% K. Characterisation was performed using thermogravimetric analysis (TGA) and differential thermal analysis (DTA). In addition to the TGA pyrolysis, pyrolysis-gas chromatography-mass spectrometry (PY-GC-MS) analysis was introduced to examine reaction products. Potassium-catalysed pyrolysis has a huge influence on the char formation stage and increases the char yields considerably (from 7.7% for raw cellulose to 27.7% for potassium impregnated cellulose; from 5.7% for raw levoglucosan to 20.8% for levoglucosan with CHCOOK added). Major changes in the pyrolytic decomposition pathways were observed for cellulose, levoglucosan and chlorogenic acid. The results for cellulose and levoglucosan are consistent with a base catalysed route in the presence of the potassium salt which promotes complete decomposition of glucosidic units by a heterolytic mechanism and favours its direct depolymerization and fragmentation to low molecular weight components (e.g. acetic acid, formic acid, glyoxal, hydroxyacetaldehyde and acetol). Base catalysed polymerization reactions increase the char yield. Potassium-catalysed lignin pyrolysis is very significant: the temperature of maximum conversion in pyrolysis shifts to lower temperature by 70 K and catalysed polymerization reactions increase the char yield from 37% to 51%. A similar trend is observed for the model compound, chlorogenic acid. The addition of potassium does not produce a dramatic change in the tar product distribution, although its addition to chlorogenic acid promoted the generation of cyclohexane and phenol derivatives. Postulated thermal decomposition schemes for chlorogenic acid are presented. © 2008 Elsevier B.V. All rights reserved.

Evaluation of options for energy recovery from municipal solid waste in India using the hierarchical analytical network process

In this paper a Hierarchical Analytical Network Process (HANP) model is demonstrated for evaluating alternative technologies for generating electricity from MSW in India. The technological alternatives and evaluation criteria for the HANP study are characterised by reviewing the literature and consulting experts in the field of waste management. Technologies reviewed in the context of India include landfill, anaerobic digestion, incineration, pelletisation and gasification. To investigate the sensitivity of the result, we examine variations in expert opinions and carry out an Analytical Hierarchy Process (AHP) analysis for comparison. We find that anaerobic digestion is the preferred technology for generating electricity from MSW in India. Gasification is indicated as the preferred technology in an AHP model due to the exclusion of criteria dependencies and in an HANP analysis when placing a high priority on net output and retention time. We conclude that HANP successfully provides a structured framework for recommending which technologies to pursue in India, and the adoption of such tools is critical at a time when key investments in infrastructure are being made. Therefore the presented methodology is thought to have a wider potential for investors, policy makers, researchers and plant developers in India and elsewhere. © 2013 Elsevier Ltd. All rights reserved.

A four-factor user interaction model for content-based image retrieval

In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques in most existing CBIR systems still lack satisfactory user interaction although some work has been done to improve the interaction as well as the search accuracy. In this paper, we propose a four-factor user interaction model and investigate its effects on CBIR by an empirical evaluation. Whilst the model was developed for our research purposes, we believe the model could be adapted to any content-based search system.

Representing the assessment process for psychodynamic psychotherapy within a computerized model of human classification

This research describes a computerized model of human classification which has been constructed to represent the process by which assessments are made for psychodynamic psychotherapy. The model assigns membership grades (MGs) to clients so that the most suitable ones have high values in the therapy category. Categories consist of a hierarchy of components, one of which, ego strength, is analysed in detail to demonstrate the way it has captured the psychotherapist's knowledge. The bottom of the hierarchy represents the measurable factors being assessed during an interview. A questionnaire was created to gather the identified information and was completed by the psychotherapist after each assessment. The results were fed into the computerized model, demonstrating a high correlation between the model MGs and the suitability ratings of the psychotherapist (r = .825 for 24 clients). The model has successfully identified the relevant data involved in assessment and simulated the decision-making process of the expert. Its cognitive validity enables decisions to be explained, which means that it has potential for therapist training and also for enhancing the referral process, with benefits in cost effectiveness as well as in the reduction of trauma to clients. An adapted version measuring client improvement would give quantitative evidence for the benefit of therapy, thereby supporting auditing and accountability. © 1997 The British Psychological Society.

Total solution of Gibilaro and Rowe model for a segregating fluidised bed

This study re-examines the one-dimensional equilibrium model of Gibilaro and Rowe (1974) for a segregating gas fluidized bed. The model was based on volumetric jetsam concentration and divided the bed contents into bulk and wake phases, taking account of bulk and wake flux, segregation, exchange between the bulk and wake phases, and axial mixing. Due to the complex nature of the model and its unstable solution, the lack of computing power at the time prevented the authors from doing little more than the analytical solutions to specific cases of this model. This paper provides a numerical total solution and allows the effect of the respective parameters to be compared for the first time. There is also a comparison with experimental results, which showed a reasonable agreement.

Managing enterprises and ERP systems:a contingency model for the enterprization of operations

Purpose: The purpose of this paper is to investigate enterprise resource planning (ERP) systems development and emerging practices in the management of enterprises (i.e. parts of companies working with parts of other companies to deliver a complex product and/or service) and identify any apparent correlations. Suitable a priori contingency frameworks are then used and extended to explain apparent correlations. Discussion is given to provide guidance for researchers and practitioners to deliver better strategic, structural and operational competitive advantage through this approach; coined here as the "enterprization of operations". Design/methodology/approach: Theoretical induction uses a new empirical longitudinal case study from Zoomlion (a Chinese manufacturing company) built using an adapted form of template analysis to produce a new contingency framework. Findings: Three main types of enterprises and the three main types of ERP systems are defined and correlations between them are explained. Two relevant a priori frameworks are used to induct a new contingency model to support the enterprization of operations; known as the dynamic enterprise reference grid for ERP (DERG-ERP). Research limitations/implications: The findings are based on one longitudinal case study. Further case studies are currently being conducted in the UK and China. Practical implications: The new contingency model, the DERG-ERP, serves as a guide for ERP vendors, information systems management and operations managers hoping to grow and sustain their competitive advantage with respect to effective enterprise strategy, enterprise structure and ERP systems. Originality/value: This research explains how ERP systems and the effective management of enterprises should develop in order to sustain competitive advantage with respect to enterprise strategy, enterprise structure and ERP systems use. © Emerald Group Publishing Limited.

Statistical model of OFDMA cellular networks uplink interference using lognormal distribution

In this letter, we propose an analytical approach to model uplink intercell interference (ICI) in hexagonal grid based orthogonal frequency division multiple access (OFMDA) cellular networks. The key idea is that the uplink ICI from individual cells is approximated with a lognormal distribution with statistical parameters being determined analytically. Accordingly, the aggregated uplink ICI is approximated with another lognormal distribution and its statistical parameters can be determined from those of individual cells using Fenton-Wilkson method. Analytic expressions of uplink ICI are derived with two traditional frequency reuse schemes, namely integer frequency reuse schemes with factor 1 (IFR-1) and factor 3 (IFR-3). Uplink fractional power control and lognormal shadowing are modeled. System performances in terms of signal to interference plus noise ratio (SINR) and spectrum efficiency are also derived. The proposed model has been validated by simulations. © 2013 IEEE.

Thermal re-emission model

Starting from a continuum description, we study the nonequilibrium roughening of a thermal re-emission model for etching in one and two spatial dimensions. Using standard analytical techniques, we map our problem to a generalized version of an earlier nonlocal KPZ (Kardar-Parisi-Zhang) model. In 2 + 1 dimensions, the values of the roughness and the dynamic exponents calculated from our theory go like α ≈ z ≈ 1 and in 1 + 1 dimensions, the exponents resemble the KPZ values for low vapor pressure, supporting experimental results. Interestingly, Galilean invariance is maintained throughout.

Concentration polarization model of spiral-wound membrane modules with application to batch-mode RO desalination of brackish water

Batch-mode reverse osmosis (batch-RO) operation is considered a promising desalination method due to its low energy requirement compared to other RO system arrangements. To improve and predict batch-RO performance, studies on concentration polarization (CP) are carried out. The Kimura-Sourirajan mass-transfer model is applied and validated by experimentation with two different spiral-wound RO elements. Explicit analytical Sherwood correlations are derived based on experimental results. For batch-RO operation, a new genetic algorithm method is developed to estimate the Sherwood correlation parameters, taking into account the effects of variation in operating parameters. Analytical procedures are presented, then the mass transfer coefficient models are developed for different operation processes, i.e., batch-RO and continuous RO. The CP related energy loss in batch-RO operation is quantified based on the resulting relationship between feed flow rates and mass transfer coefficients. It is found that CP increases energy consumption in batch-RO by about 25% compared to the ideal case in which CP is absent. For continuous RO process, the derived Sherwood correlation predicted CP accurately. In addition, we determined the optimum feed flow rate of our batch-RO system.