13 resultados para FOOD-WEB STRUCTURE
em Aston University Research Archive
Resumo:
We present a vision and a proposal for using Semantic Web technologies in the organic food industry. This is a very knowledge intensive industry at every step from the producer, to the caterer or restauranteur, through to the consumer. There is a crucial need for a concept of environmental audit which would allow the various stake holders to know the full environmental impact of their economic choices. This is a di?erent and parallel form of knowledge to that of price. Semantic Web technologies can be used e?ectively for the calculation and transfer of this type of knowledge (together with other forms of multimedia data) which could contribute considerably to the commercial and educational impact of the organic food industry. We outline how this could be achieved as our essential ob jective is to show how advanced technologies could be used to both reduce ecological impact and increase public awareness.
Resumo:
The aim of this study was to explore how the structure of mealtimes within the family setting is related to children's fussy eating behaviours. Seventy-five mothers of children aged between 2 and 4 years were observed during a typical mealtime at home. The mealtimes were coded to rate mealtime structure and environment as well as the child's eating behaviours (food refusal, difficulty to feed, eating speed, positive and negative vocalisations). Mealtime structure emerged as an important factor which significantly distinguished children with higher compared with lower levels of food fussiness. Children whose mothers ate with their child and ate the same food as their child were observed to refuse fewer foods and were easier to feed compared with children whose mothers did not. During mealtimes where no distractors were used (e.g. no TV, magazines or toys), or where children were allowed some input into food choice and portioning, children were also observed to demonstrate fewer fussy eating behaviours. Findings of this study suggest that it may be important for parents to strike a balance between structured mealtimes, where the family eats together and distractions are minimal, alongside allowing children some autonomy in terms of food choice and intake.
Resumo:
Purpose – This study seeks to provide valuable new insight into the timeliness of corporate internet reporting (TCIR) by a sample of Irish-listed companies. Design/methodology/approach – The authors apply an updated version of Abdelsalam et al. TCIR index to assess the timeliness of corporate internet reporting. The index encompasses 13 criteria that are used to measure the TCIR for a sample of Irish-listed companies. In addition, the authors assess the timeliness of posting companies’ annual and interim reports to their web sites. Furthermore, the study examines the influence of board independence and ownership structure on the TCIR behaviour. Board composition is measured by the percentage of independent directors, chairman’s dual role and average tenure of directors. Ownership structure is represented by managerial ownership and blockholder ownership. Findings – It is found that Irish-listed companies, on average, satisfy only 46 per cent of the timeliness criteria assessed by the timeliness index. After controlling for size, audit fees and firm performance, evidence that TCIR is positively associated with board of director’s independence and chief executive officer (CEO) ownership is provided. Furthermore, it is found that large companies are faster in posting their annual reports to their web sites. The findings suggest that board composition and ownership structure influence a firm’s TCIR behaviour, presumably in response to the information asymmetry between management and investors and the resulting agency costs. Practical implications – The findings highlight the need for improvement in TCIR by Irish-listed companies in many areas, especially in regard to the regular updates of information provided on their web sites. Originality/value – This study represents one of the first comprehensive examinations of the important dimension of the TCIR in Irish-listed companies.
Resumo:
Modern procurement is being shifted from paper-based, people-intensive buying systems toward electronic-based purchase procedures that rely on Internet communications and Web-enhanced buying tools. Develops a typology of e-commerce tools that have come to characterize cutting-edge industrial procurement. E-commerce aspects of purchasing are organized into communication and transaction tools that encompass both internal and external buying activities. Further, a model of the impact of e-commerce on the structure and processes of an organization's buying center is developed. The impact of the changing buying center on procurement outcomes in terms of efficiency and effectiveness is also analyzed. Finally, implications for business-to-business marketers and researchers are discussed.
Resumo:
This article proposes a framework of alternative international marketing strategies, based on the evaluation of intra- and inter-cultural behavioural homogeneity for market segmentation. The framework developed in this study provides a generic structure to behavioural homogeneity, proposing consumer involvement as a construct with unique predictive ability for international marketing strategy decisions. A model-based segmentation process, using structural equation models, is implemented to illustrate the application of the framework.
Resumo:
Hierarchical knowledge structures are frequently used within clinical decision support systems as part of the model for generating intelligent advice. The nodes in the hierarchy inevitably have varying influence on the decisionmaking processes, which needs to be reflected by parameters. If the model has been elicited from human experts, it is not feasible to ask them to estimate the parameters because there will be so many in even moderately-sized structures. This paper describes how the parameters could be obtained from data instead, using only a small number of cases. The original method [1] is applied to a particular web-based clinical decision support system called GRiST, which uses its hierarchical knowledge to quantify the risks associated with mental-health problems. The knowledge was elicited from multidisciplinary mental-health practitioners but the tree has several thousand nodes, all requiring an estimation of their relative influence on the assessment process. The method described in the paper shows how they can be obtained from about 200 cases instead. It greatly reduces the experts’ elicitation tasks and has the potential for being generalised to similar knowledge-engineering domains where relative weightings of node siblings are part of the parameter space.
Resumo:
Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.
Resumo:
Purpose – This study seeks to provide valuable new insight into the timeliness of corporate internet reporting (TCIR) by a sample of Irish-listed companies. Design/methodology/approach – The authors apply an updated version of Abdelsalam et al. TCIR index to assess the timeliness of corporate internet reporting. The index encompasses 13 criteria that are used to measure the TCIR for a sample of Irish-listed companies. In addition, the authors assess the timeliness of posting companies’ annual and interim reports to their web sites. Furthermore, the study examines the influence of board independence and ownership structure on the TCIR behaviour. Board composition is measured by the percentage of independent directors, chairman’s dual role and average tenure of directors. Ownership structure is represented by managerial ownership and blockholder ownership. Findings – It is found that Irish-listed companies, on average, satisfy only 46 per cent of the timeliness criteria assessed by the timeliness index. After controlling for size, audit fees and firm performance, evidence that TCIR is positively associated with board of director’s independence and chief executive officer (CEO) ownership is provided. Furthermore, it is found that large companies are faster in posting their annual reports to their web sites. The findings suggest that board composition and ownership structure influence a firm’s TCIR behaviour, presumably in response to the information asymmetry between management and investors and the resulting agency costs. Practical implications – The findings highlight the need for improvement in TCIR by Irish-listed companies in many areas, especially in regard to the regular updates of information provided on their web sites. Originality/value – This study represents one of the first comprehensive examinations of the important dimension of the TCIR in Irish-listed companies.
A conceptual framework for supply chain collaboration:empirical evidence from the agri-food industry
Resumo:
Purpose - The purpose of this paper is to analyse the concept of supply chain collaboration and to provide an overall framework that can be used as a conceptual landmark for further empirical research. In addition, the concept is explored in the context of agri-food industry and particularities are identified. Finally, the paper submits empirical evidence from an exploratory case study in the agri-food industry, at the grower-processor interface, and information regarding the way the concept is actually applied in small medium-sized enterprises (SMEs) is presented. Design/methodology/approach - The paper employed case study research by conducting in-depth interviews in the two companies. Findings - Supply chain collaboration concept is of significant importance for the agri-food industry however, some constraints arise due to the nature of industry's products, and the specific structure of the sector. Subsequently, collaboration in the supply chain is often limited to operational issues and to logistics-related activities. Research limitations/implications - Research is limited to a single case study and further qualitative testing of the conceptual model is needed in order to adjust the model before large scale testing. Practical implications - Case study findings may be transferable to other similar dual relationships at the grower-processor interface. Weaker parts in asymmetric relationships have opportunities to improve their position, altering the dependence balance, by achieving product/process excellence. Originality/value - The paper provides evidence regarding the applicability of the supply chain collaboration concept in the agri-food industry. It takes into consideration not relationships between big multinational companies, but SMEs. © Emerald Group Publishing Limited.
Resumo:
Learning user interests from online social networks helps to better understand user behaviors and provides useful guidance to design user-centric applications. Apart from analyzing users' online content, it is also important to consider users' social connections in the social Web. Graph regularization methods have been widely used in various text mining tasks, which can leverage the graph structure information extracted from data. Previously, graph regularization methods operate under the cluster assumption that nearby nodes are more similar and nodes on the same structure (typically referred to as a cluster or a manifold) are likely to be similar. We argue that learning user interests from complex, sparse, and dynamic social networks should be based on the link structure assumption under which node similarities are evaluated based on the local link structures instead of explicit links between two nodes. We propose a regularization framework based on the relation bipartite graph, which can be constructed from any type of relations. Using Twitter as our case study, we evaluate our proposed framework from social networks built from retweet relations. Both quantitative and qualitative experiments show that our proposed method outperforms a few competitive baselines in learning user interests over a set of predefined topics. It also gives superior results compared to the baselines on retweet prediction and topical authority identification. © 2014 ACM.
Resumo:
Data integration for the purposes of tracking, tracing and transparency are important challenges in the agri-food supply chain. The Electronic Product Code Information Services (EPCIS) is an event-oriented GS1 standard that aims to enable tracking and tracing of products through the sharing of event-based datasets that encapsulate the Electronic Product Code (EPC). In this paper, the authors propose a framework that utilises events and EPCs in the generation of "linked pedigrees" - linked datasets that enable the sharing of traceability information about products as they move along the supply chain. The authors exploit two ontology based information models, EEM and CBVVocab within a distributed and decentralised framework that consumes real time EPCIS events as linked data to generate the linked pedigrees. The authors exemplify the usage of linked pedigrees within the fresh fruit and vegetables supply chain in the agri-food sector.
Resumo:
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.
Resumo:
Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.