Trigeneration using biomass energy for sustainable development

Purpose: The paper aims to design and prove the concept of micro-industry using trigeneration fuelled by biomass, for sustainable development in rural NW India. Design/methodology/approach: This is being tested at village Malunga, near Jodhpur in Rajasthan. The system components comprise burning of waste biomass for steam generation and its use for power generation, cooling system for fruit ripening and the use of steam for producing distilled water. Site was selected taking into account the local economic and social needs, biomass resources available from agricultural activities, and the presence of a NGO which is competent to facilitate running of the enterprise. The trigeneration system was designed to integrate off-the-shelf equipment for power generation using boilers of approximate total capacity 1 tonne of fuel per hour, and a back-pressure steam turbo-generator (200 kW). Cooling is provided by a vapour absorption machine (VAM). Findings: The financial analysis indicates a payback time of less than two years. Nevertheless, this is sensitive to market fluctuations and availabilities of raw materials. Originality/value: Although comparable trigeneration systems already exist in large food processing industries and in space heating and cooling applications, they have not previously been used for rural micro-industry. The small-scale (1-2 m3/h output) multiple effect distillation (3 effect plus condenser) unit has not previously been deployed at field level. © Emerald Group Publishing Limited.

Issues in learning an ontology from text

Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. This paper describes an experiment in ontology construction from text for the animal behaviour domain. Our objective was to see how much could be done in a simple and relatively rapid manner using a corpus of journal papers. We used a sequence of pre-existing text processing steps, and here describe the different choices made to clean the input, to derive a set of terms and to structure those terms in a number of hierarchies. We describe some of the challenges, especially that of focusing the ontology appropriately given a starting point of a heterogeneous corpus. Results - Using mainly automated techniques, we were able to construct an 18055 term ontology-like structure with 73% recall of animal behaviour terms, but a precision of only 26%. We were able to clean unwanted terms from the nascent ontology using lexico-syntactic patterns that tested the validity of term inclusion within the ontology. We used the same technique to test for subsumption relationships between the remaining terms to add structure to the initially broad and shallow structure we generated. All outputs are available at http://thirlmere.aston.ac.uk/~kiffer/animalbehaviour/ webcite. Conclusion - We present a systematic method for the initial steps of ontology or structured vocabulary construction for scientific domains that requires limited human effort and can make a contribution both to ontology learning and maintenance. The method is useful both for the exploration of a scientific domain and as a stepping stone towards formally rigourous ontologies. The filtering of recognised terms from a heterogeneous corpus to focus upon those that are the topic of the ontology is identified to be one of the main challenges for research in ontology learning.

Issues in learning an ontology from text

Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. This paper describes an experiment in ontology construction from text for the Animal Behaviour domain. Our objective was to see how much could be done in a simple and rapid manner using a corpus of journal papers. We used a sequence of text processing steps, and describe the different choices made to clean the input, to derive a set of terms and to structure those terms in a hierarchy. We were able in a very short space of time to construct a 17000 term ontology with a high percentage of suitable terms. We describe some of the challenges, especially that of focusing the ontology appropriately given a starting point of a heterogeneous corpus.

A randomised controlled trial investigating the effect of nutritional supplementation on visual function in normal, and age-related macular disease affected eyes:design and methodology [ISRCTN78467674]

Background: Age-related macular disease is the leading cause of blind registration in the developed world. One aetiological hypothesis involves oxidation, and the intrinsic vulnerability of the retina to damage via this process. This has prompted interest in the role of antioxidants, particularly the carotenoids lutein and zeaxanthin, in the prevention and treatment of this eye disease. Methods: The aim of this randomised controlled trial is to determine the effect of a nutritional supplement containing lutein, vitamins A, C and E, zinc, and copper on measures of visual function in people with and without age-related macular disease. Outcome measures are distance and near visual acuity, contrast sensitivity, colour vision, macular visual field, glare recovery, and fundus photography. Randomisation is achieved via a random number generator, and masking achieved by third party coding of the active and placebo containers. Data collection will take place at nine and 18 months, and statistical analysis will employ Student's t test. Discussion: A paucity of treatment modalities for age-related macular disease has prompted research into the development of prevention strategies. A positive effect on normals may be indicative of a role of nutritional supplementation in preventing or delaying onset of the condition. An observed benefit in the age-related macular disease group may indicate a potential role of supplementation in prevention of progression, or even a degree reversal of the visual effects caused by this condition.

Researching experiences of cancer:the importance of methodology

This paper draws on contributions to and discussions at a recent MRC HSRC-sponsored workshop 'Researching users' experiences of health care: the case of cancer'. We focus on the methodological and ethical challenges that currently face researchers who use self-report methods to investigate experiences of cancer and cancer care. These challenges relate to: the theoretical and conceptual underpinnings of research; participation rates and participant profiles; data collection methods (the retrospective nature of accounts, description and measurement, and data collection as intervention); social desirability considerations; relationship considerations; the experiences of contributing to research; and the synthesis and presentation of findings. We suggest that methodological research to tackle these challenges should be integrated into substantive research projects to promote the development of a strong knowledge base about experiences of cancer and cancer care.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.

Design software architecture models using ontology

Software architecture plays an essential role in the high level description of a system design, where the structure and communication are emphasized. Despite its importance in the software engineering process, the lack of formal description and automated verification hinders the development of good software architecture models. In this paper, we present an approach to support the rigorous design and verification of software architecture models using the semantic web technology. We view software architecture models as ontology representations, where their structures and communication constraints are captured by the Web Ontology Language (OWL) and the Semantic Web Rule Language (SWRL). Specific configurations on the design are represented as concrete instances of the ontology, to which their structures and dynamic behaviors must conform. Furthermore, ontology reasoning tools can be applied to perform various automated verification on the design to ensure correctness, such as consistency checking, style recognition, and behavioral inference.

New product development proficiency and multi-country product rollout timeliness

Purpose: The purpose of this paper is to address a gap in the understanding of the indirect effects of marketing and technical factors on time efficiency in developing a new product and international new product launch. Design/methodology/approach: This paper adopts a contingency perspective in examining the relationships between antecedents and on-time completion (or timeliness) of new product development (NPD) and international new product rollout (INPR). A conceptual framework is tested based on data obtained on 232 NPD projects undertaken by Korean firms. Findings: The results show that NPD proficiencies mediate to a greater or lesser extent the effects of key antecedents (e.g. cross-functional linkages, project fit with available marketing resources, and effective coordination of headquarters-subsidiary/agents' activities) on timeliness in NPD and INPR. Research limitations/implications: Empirical research on the role of marketing and technical proficiencies in improving NPD timeliness and rollout timeliness in the context of international NPD affirms the importance of adopting a contingency perspective in examining the antecedents of NPD and multi-market entry timeliness. Practical implications: This paper lends insight into the role of overseas subsidiaries or agents in helping to build the technical proficiencies of emerging country companies. Originality/value: This is the first review focusing on the mediating influences on time dimensions (e.g. timeliness) in multi-country product launches. © Emerald Group Publishing Limited.

Measuring employee innovation:a review of existing scales and the development of the innovative behavior and innovation support inventories across cultures

Purpose - The paper develops a model of employee innovative behavior conceptualizing it as distinct from innovation outputs and as a multi-faceted behavior rather than a simple count of ‘innovative acts’ by employees. It understands individual employee innovative behaviors as a micro-foundation of firm intrapreneurship that is embedded in and influenced by contextual factors such as managerial, organizational and cultural support for innovation. Building from a review of existing employee innovative behavior scales and theoretical considerations we develop and validate the Innovative Behavior Inventory (IBI) and the Innovation Support Inventory (ISI). Design/methodology/approach – Two pilot studies, a third validation study in the Czech Republic and a fourth cross-cultural validation study using population representative samples from Switzerland, Germany, Italy and the Czech Republic (N=2812 employees and 450 entrepreneurs) were conducted. Findings - Both inventories were reliable and showed factorial, criterion, convergent and discriminant validity as well as cross-cultural equivalence. Employee innovative behavior was supported as comprising of idea generation, idea search, idea communication, implementation starting activities, involving others and overcoming obstacles. Managerial support was the most proximal contextual influence on innovative behavior and mediated the effect of organizational support and national culture. Originality/value - The paper advances our understanding of employee innovative behavior as a multi-faceted phenomenon and the contextual factors influencing it. Where past research typically focuses on convenience samples within a particular country, we offer first robust evidence that our model of employee innovative behavior generalizes across cultures and types of samples. Our model and the IBI and ISI inventories enable researchers to build a deeper understanding of the important micro-foundation underpinning intrapreneurial behavior in organizations and allow practitioners to identify their organizations’ strengths and weaknesses related to intrapreneurship.

Measurement resource planning:a methodology that uses quality characteristics mapping

Integration of the measurement activity into the production process is an essential rule in digital enterprise technology, especially for large volume product manufacturing, such as aerospace, shipbuilding, power generation and automotive industries. Measurement resource planning is a structured method of selecting and deploying necessary measurement resources to implement quality aims of product development. In this research, a new mapping approach for measurement resource planning is proposed. Firstly, quality aims are identified in the form of a number of specifications and engineering requirements of one quality characteristics (QCs) at a specific stage of product life cycle, and also measurement systems are classified according to the attribute of QCs. Secondly, a matrix mapping approach for measurement resource planning is outlined together with an optimization algorithm for combination between quality aims and measurement systems. Finally, the proposed methodology has been studied in shipbuilding to solve the problem of measurement resource planning, by which the measurement resources are deployed to satisfy all the quality aims. © Springer-Verlag Berlin Heidelberg 2010.

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.