Dynamic simulation of chemical plant

A CSSL- type modular FORTRAN package, called ACES, has been developed to assist in the simulation of the dynamic behaviour of chemical plant. ACES can be harnessed, for instance, to simulate the transients in startups or after a throughput change. ACES has benefited from two existing simulators. The structure was adapted from ICL SLAM and most plant models originate in DYFLO. The latter employs sequential modularisation which is not always applicable to chemical engineering problems. A novel device of twice- round execution enables ACES to achieve general simultaneous modularisation. During the FIRST ROUND, STATE-VARIABLES are retrieved from the integrator and local calculations performed. During the SECOND ROUND, fresh derivatives are estimated and stored for simultaneous integration. ACES further includes a version of DIFSUB, a variable-step integrator capable of handling stiff differential systems. ACES is highly formalised . It does not use pseudo steady- state approximations and excludes inconsistent and arbitrary features of DYFLO. Built- in debug traps make ACES robust. ACES shows generality, flexibility, versatility and portability, and is very convenient to use. It undertakes substantial housekeeping behind the scenes and thus minimises the detailed involvement of the user. ACES provides a working set of defaults for simulation to proceed as far as possible. Built- in interfaces allow for reactions and user supplied algorithms to be incorporated . New plant models can be easily appended. Boundary- value problems and optimisation may be tackled using the RERUN feature. ACES is file oriented; a STATE can be saved in a readable form and reactivated later. Thus piecewise simulation is possible. ACES has been illustrated and verified to a large extent using some literature-based examples. Actual plant tests are desirable however to complete the verification of the library. Interaction and graphics are recommended for future work.

The UK productivity gap in the service sector: do management practices matter?

Purpose – This paper aims to contribute to the debate on the drivers of the productivity gap that exists between the UK and its major international competitors. Design/methodology/approach – From the macro perspective the paper explores the quantitative evidence on the productivity differentials and how they are measured. From the micro perspective, the article explores the quantitative evidence on the role of management practices claimed to be a key determinant in promoting firm competitiveness and in bridging the UK gap. Findings – This study suggests that management practices are an ambiguous driver of firm productivity and higher firm performance. On the methodological side, qualitative and subjective measures of either management practices or firm performance are often used. This makes the results not comparable across studies, across firms or even within firms over time. Productivity and profitability are often and erroneously interchangeably used while productivity is only one element of firm performance. On the other hand, management practices are multi-dimensional constructs that generally do not demonstrate a straightforward relationship with productivity variables. To assume that they are the only driver of higher productivity may be misleading. Moreover, there is evidence of an inverse causal relationship between management practices and firm performance. This calls into question most empirical results of the extant literature based on the unidirectional assumption of direct causality between management practices and firm performance. Research limitations/implications – These and other issues suggest that more research is needed to deepen the understanding of the UK productivity gap and more quantitative evidence should be provided on the way in which management practices contribute to the UK competitiveness. Their impact is not easily measurable due to their complexity and their complementary nature and this is a fertile ground for further research. Originality/value – This paper brings together the evidence on the UK productivity gap and its main drivers, provided by the economics, management and performance measurement literature. This issue scores very highly in the agenda of policy makers and academics and has important implications for practitioners interested in evaluating the impact of managerial best practices.

A multivariate examination of the relationship between strategic planning and organisational performance

Strategic planning and more specifically, the impact of strategic planning on organisational performance has been the subject of significant academic interest since the early 1970's. However, despite the significant amount of previous work examining the relationship between strategic planning and organisational performance, a comprehensive literature review identified a number of areas where contributions to the domain of study could be made. In overview, the main areas for further study identified from the literature review were a) a further examination of both the dimensionality and conceptualisation of strategic planning and organisational performance and b) a further, multivariate, examination of the relationship between strategic planning and performance, to capture the newly identified dimensionality. In addition to the previously identified strategic planning and organisational performance constructs, a comprehensive literature based assessment was undertaken and five main areas were identified for further examination, these were a) organisational b) comprehensive strategic choice, c) the quality of strategic options generated, d) political behavior and e) implementation success. From this, a conceptual model incorporating a set of hypotheses to be tested was formulated. In order to test the conceptual model specified and also the stated hypotheses, data gathering was undertaken. The quantitative phase of the research involved a mail survey of senior managers in medium to large UK based organisations, of which a total of 366 fully useable responses were received. Following rigorous individual construct validity and reliability testing, the complete conceptual model was tested using latent variable path analysis. The results for the individual hypotheses and also the complete conceptual model were most encouraging. The findings, theoretical and managerial implications, limitations and directions for future research are discussed.

Service productivity:what stops service firms from measuring it?

Productivity measurement poses a challenge for service organizations. Conventional management wisdom holds that this challenge is rooted in the difficulty of accurately quantifying service inputs and outputs. Few service firms have adequate service productivity measurement (SPM) systems in place and implementing such systems may involve organizational transformation. Combining field interviews and literature-based insights, the authors develop a conceptual model of antecedents of SPM in service firms and test it using data from 276 service firms. Results indicate that one out of five antecedents affects the choice to use SPM, namely, the degree of service standardization. In addition, all five hypothesized antecedents and one additional antecedent (perceived appropriateness of the current SPM) predict the degree of SPM usage. In particular, the degree of SPM is positively influenced by the degree of service standardization, service customization, investments in service productivity gains, and the appropriateness of current service productivity measures. In turn, customer integration and the perceived difficulty of measuring service productivity negatively affect SPM. The fact that customer integration impedes actual measurement of service productivity is a surprising finding, given that customer integration is widely seen as a means to increase service productivity. The authors conclude with implications for service organizations and directions for research.

Consumer-based brand equity conceptualization and measurement:a literature review

Although there is a large body of research on brand equity, little in terms of a literature review has been published on this since Feldwick’s (1996) paper. To address this gap, this paper brings together the scattered literature on consumer based brand equity’s conceptualisation and measurement. Measures of consumer based brand equity are classified as either direct or indirect. Indirect measures assess consumer-based brand equity through its demonstrable dimensions and are superior from a diagnostic level. The paper concludes with directions for future research and managerial pointers for setting up a brand equity measurement system.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

Ontology-based protein-protein interactions extraction from literature using the hidden vector state model

This paper proposes a novel framework of incorporating protein-protein interactions (PPI) ontology knowledge into PPI extraction from biomedical literature in order to address the emerging challenges of deep natural language understanding. It is built upon the existing work on relation extraction using the Hidden Vector State (HVS) model. The HVS model belongs to the category of statistical learning methods. It can be trained directly from un-annotated data in a constrained way whilst at the same time being able to capture the underlying named entity relationships. However, it is difficult to incorporate background knowledge or non-local information into the HVS model. This paper proposes to represent the HVS model as a conditionally trained undirected graphical model in which non-local features derived from PPI ontology through inference would be easily incorporated. The seamless fusion of ontology inference with statistical learning produces a new paradigm to information extraction.

Mass spectrometry-based methods for identifying oxidized proteins in disease:advances and challenges

Many inflammatory diseases have an oxidative aetiology, which leads to oxidative damage to biomolecules, including proteins. It is now increasingly recognized that oxidative post-translational modifications (oxPTMs) of proteins affect cell signalling and behaviour, and can contribute to pathology. Moreover, oxidized proteins have potential as biomarkers for inflammatory diseases. Although many assays for generic protein oxidation and breakdown products of protein oxidation are available, only advanced tandem mass spectrometry approaches have the power to localize specific oxPTMs in identified proteins. While much work has been carried out using untargeted or discovery mass spectrometry approaches, identification of oxPTMs in disease has benefitted from the development of sophisticated targeted or semi-targeted scanning routines, combined with chemical labeling and enrichment approaches. Nevertheless, many potential pitfalls exist which can result in incorrect identifications. This review explains the limitations, advantages and challenges of all of these approaches to detecting oxidatively modified proteins, and provides an update on recent literature in which they have been used to detect and quantify protein oxidation in disease.

Ordered weighted averaging operators 1988-2014:a citation-based literature survey

This study surveys the ordered weighted averaging (OWA) operator literature using a citation network analysis. The main goals are the historical reconstruction of scientific development of the OWA field, the identification of the dominant direction of knowledge accumulation that emerged since the publication of the first OWA paper, and to discover the most active lines of research. The results suggest, as expected, that Yager's paper (IEEE Trans. Systems Man Cybernet, 18(1), 183-190, 1988) is the most influential paper and the starting point of all other research using OWA. Starting from his contribution, other lines of research developed and we describe them.

Ontology forecasting in scientific literature:semantic concepts prediction based on innovation-adoption priors

The ontology engineering research community has focused for many years on supporting the creation, development and evolution of ontologies. Ontology forecasting, which aims at predicting semantic changes in an ontology, represents instead a new challenge. In this paper, we want to give a contribution to this novel endeavour by focusing on the task of forecasting semantic concepts in the research domain. Indeed, ontologies representing scientific disciplines contain only research topics that are already popular enough to be selected by human experts or automatic algorithms. They are thus unfit to support tasks which require the ability of describing and exploring the forefront of research, such as trend detection and horizon scanning. We address this issue by introducing the Semantic Innovation Forecast (SIF) model, which predicts new concepts of an ontology at time t + 1, using only data available at time t. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed approach offers a competitive boost in mean average precision-at-ten compared to the baselines when forecasting over 5 years.