Conclusion : on multiple levels of analysis, context, contingency and capital

In this concluding chapter, we bring together the threads and reflections on the chapters contained in this text and show how they relate to multi-level issues. The book has focused on the world of Human Resource Management (HRM) and the systems and practices it must put in place to foster innovation. Many of the contributions argue that in order to bring innovation about, organisations have to think carefully about the way in which they will integrate what is, in practice, organisationally relevant — but socially distributed — knowledge. They need to build a series of knowledge-intensive activities and networks, both within their own boundaries and across other important external inter-relationships. In so doing, they help to co-ordinate important information structures. They have, in effect, to find ways of enabling people to collaborate with each other at lower cost, by reducing both the costs of their co-ordination and the levels of unproductive search activity. They have to engineer these behaviours by reducing the risks for people that might be associated with incorrect ideas and help individuals, teams and business units to advance incomplete ideas that are so often difficult to codify. In short, a range of intangible assets must flow more rapidly throughout the organisation and an appropriate balance must be found between the rewards and incentives associated with creativity, novelty and innovation, versus the risks that innovation may also bring.

Finding structures in information networks using the affinity network

This thesis proposes a novel graphical model for inference called the Affinity Network,which displays the closeness between pairs of variables and is an alternative to Bayesian Networks and Dependency Networks. The Affinity Network shares some similarities with Bayesian Networks and Dependency Networks but avoids their heuristic and stochastic graph construction algorithms by using a message passing scheme. A comparison with the above two instances of graphical models is given for sparse discrete and continuous medical data and data taken from the UCI machine learning repository. The experimental study reveals that the Affinity Network graphs tend to be more accurate on the basis of an exhaustive search with the small datasets. Moreover, the graph construction algorithm is faster than the other two methods with huge datasets. The Affinity Network is also applied to data produced by a synchronised system. A detailed analysis and numerical investigation into this dynamical system is provided and it is shown that the Affinity Network can be used to characterise its emergent behaviour even in the presence of noise.

Flexibility of short-strand RNA in aqueous solution as revealed by molecular dynamics simulation:are A′-RNA and A-RNA distinct conformational structures?

We use molecular dynamics simulations to compare the conformational structure and dynamics of a 21-base pair RNA sequence initially constructed according to the canonical A-RNA and A'-RNA forms in the presence of counterions and explicit water. Our study aims to add a dynamical perspective to the solid-state structural information that has been derived from X-ray data for these two characteristic forms of RNA. Analysis of the three main structural descriptors commonly used to differentiate between the two forms of RNA namely major groove width, inclination and the number of base pairs in a helical twist over a 30 ns simulation period reveals a flexible structure in aqueous solution with fluctuations in the values of these structural parameters encompassing the range between the two crystal forms and more. This provides evidence to suggest that the identification of distinct A-RNA and A'-RNA structures, while relevant in the crystalline form, may not be generally relevant in the context of RNA in the aqueous phase. The apparent structural flexibility observed in our simulations is likely to bear ramifications for the interactions of RNA with biological molecules (e.g. proteins) and non-biological molecules (e.g. non-viral gene delivery vectors). © CSIRO 2009.

Information management for viable organisations

The recent global „credit crunch? has brought sharply into focus the need for better understanding of what it takes for organisations to survive. This research seeks to help organisations maintain their „viability? – the ability to maintain a separate existence and survive on their own. Whilst there are a multitude of factors that contribute to organisational viability, information can be viewed as the lifeblood of organisations. This research increases our understanding of how organisations can manage information effectively to help maintain their viability. The viable systems model (VSM) is an established modelling technique that enables the detailed analysis of organisational activity to examine how the structure and functions performed in an organisation contribute to its „viability?. The VSM has been widely applied, in small/large companies, industries and governments. However, whilst the VSM concentrates on the structure and functions necessary for an organisation to be viable, it pays much less attention to information deployment in organisations. Indeed, the VSM is criticised in the literature for being unable to provide much help with detailed information and communication structures and new theories are called for to explore the way people interact and what information they need in the VSM. This research analyses qualitative data collected from four case studies to contribute to our understanding of the role that information plays in organisational viability, making three key contributions to the academic literature. In the information management literature, this research provides new insight into the roles that specific information plays in organisations. In the systems thinking literature, this research extends our understanding of the VSM and builds on its powerful diagnostic capability to provide further criteria to aid in the diagnosis of viable organisations. In the information systems literature, this research develops a framework that can be used to help organisations design more effective information systems.

Cognitive structures, strategies and instruction

This thesis is organised into three parts. In Part 1 relevant literature is reviewed and three critical components in the development of a cognitive approach to instruction are identified. These three components are considered to be the structure of the subject-matter, the learner's cognitive structures, and the learner's cognitive strategies which act as control and transfer devices between the instructional materials and the learner's cognitive structures. Six experiments are described in Part 2 which is divided into two methodologically distinct units. The three experiments of Unit 1 examined how learning from materials constructed from concept name by concept attribute matrices is influenced by learner or experimenter controlled sequence and organisation. The results suggested that the relationships between input organisation, output organisation and recall are complex and highlighted the importance of investigating organisational strategies at both acquisition and recall. The role of subjects previously acquired knowledge and skills in relation to the instructional material was considered to be an important factor. The three experiments of Unit 2 utilised a "diagramming relationships methodology" which was devised as one means of investigating the processes by which new information is assimilated into an individual's cognitive structure. The methodology was found to be useful in identifying cognitive strategies related to successful task performance. The results suggested that errors could be minimised and comprehension improved on the diagramming relationships task by instructing subjects in ways which induced successful processing operations. Part 3 of this thesis highlights salient issues raised by the experimental work within the framework outlined in Part 1 and discusses potential implications for future theoretical developments and research.

The discourse of academic seminars:structures and strategies of interaction

Seminar discussion is an important mode of instruction in Higher Education. However, the discourse of discussion in academic seminars has been little investigated. Until now, there has existed only a limited amount of empirically based language description which could be used to inform those working in the field of English for Academic Purposes. The present study investigates discussion in seminars on a MBA programme and offers frameworks to account for central aspects of the verbal interaction: exchange patterns; acts and moves initiating exchanges and strategies. Three subgenres of seminar discussion are examined: the discussion following the presentation by an outside speaker; the discussion following the presentation by students and non-presentation tutorial discussion. Exchanges are found to be basically two-part structures of initiation and response. Some extended patterns are brought to light and it is argued that the major impetus prolonging exchanges in discussion is a third-part move registering dissatisfaction with the initial responses given. Exchanges are observed to be driven by moves functioning as elicitations although acts at initiation both ask for information and ideas and propose them. Initiation may be complex and involves a mixture of the acts. Textual signalling and attitudinal strategies used in seminars are explicated. The latter are accounted for in terms of the face concerns of the speakers. The features are examined across the three subgenres. Some quantitative variations were observed. These variations are discussed in the light of situational variables such as levels of participant status and knowledge. Theoretical implications are drawn and applications for syllabus and methodology in English for Academic Purposes are suggested.

Optimum design of structures

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Capital and asset structures and their influence on the performance of Egyptian nationalised industries:an application of financial statement analysis and survey

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Network structures and resources for emergency communications

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Copper(II) complexes with unsymmetrical pentadentate ed3a-type diamino-tricarboxylate ligands. Crystal structures, configurational analysis and DFT study of complexes

The O–O–N–N–O-type pentadentate ligands H3ed3a, H3pd3a and H3pd3p (H3ed3a stands ethylenediamine-N,N,N′-triacetic acid; H3pd3a stands 1,3-propanediamine-N,N,N′-triacetic acid and H3pd3p stands 1,3-propanediamine-N,N,N′-tri-3-propionic acid) and the corresponding novel octahedral or square-planar/trigonal-bipyramidal copper(II) complexes have been prepared and characterized. H3ed3a, H3pd3a and H3pd3p ligands coordinate to copper(II) ion via five donor atoms (three deprotonated carboxylate atoms and two amine nitrogens) affording octahedral in case of ed3a3− and intermediate square-pyramidal/trigonal-bipyramidal structure in case of pd3a3− and pd3p3−. A six coordinate, octahedral geometry has been established crystallographically for the [Mg(H2O)6][Cu(ed3a)(H2O)]2 · 2H2O complex and five coordinate square-pyramidal for the [Mg(H2O)5Cu(pd3a)][Cu(pd3a)] · 2H2O. Structural data correlating similar chelate Cu(II) complexes have been used for the better understanding the pathway: octahedral → square-pyramidal ↔ trigonal- bipyramid geometry. An extensive configuration analysis is discussed in relation to information obtained for similar complexes. The infra-red and electronic absorption spectra of the complexes are discussed in comparison with related complexes of known geometries. Molecular mechanics and density functional theory (DFT) programs have been used to model the most stable geometric isomer yielding, at the same time, significant structural data. The results from density functional studies have been compared with X-ray data.

Defining an OWL ontology that could be used to integrate mental-health risk information within a decision support system

In the field of mental health risk assessment, there is no standardisation between the data used in different systems. As a first step towards the possible interchange of data between assessment tools, an ontology has been constructed for a particular one, GRiST (Galatean Risk Screening Tool). We briefly introduce GRiST and its data structures, then describe the ontology and the benefits that have already been realised from the construction process. For example, the ontology has been used to check the consistency of the various trees used in the model. We then consider potential uses in integration of data from other sources. © 2009 IEEE.

Arthur Lindo Patterson, his function and element preferences in early crystal structures

In 1934, Arthur Lindo Patterson showed that a map of interatomic vectors is obtainable from measured X-ray diffraction data without phase information. Such maps were interpretable for simple crystal structures, but proliferation and overlapping of peaks caused confusion as the number of atoms increased. Since the peak height of a vector between two particular atoms is related to the product of their atomic numbers, a complicated structure could effectively be reduced to a simple one by including just a few heavy atoms (of high atomic number) since their interatomic vectors would stand out from the general clutter. Once located, these atoms provide approximate phases for Fourier syntheses that reveal the locations of additional atoms. Surveys of small-molecule structures in the Cambridge Structural Database during the periods 1936-1969, when Patterson methods were commonly used, and 1980-2013, dominated by direct methods, demonstrate large differences in the abundance of certain elements. The moderately heavy elements K, Rb, As and Br are the heaviest elements in the structure more than 3 times as often in the early period than in the recent period. Examples are given of three triumphs of the heavy atom method and two initial failures that had to be overcome. © 2014 © 2014 Taylor & Francis.

Discovering knowledge structures in mind maps of mental health risks

This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

Design of an information system for metrology contents

Dimensional and form inspections are key to the manufacturing and assembly of products. Product verification can involve a number of different measuring instruments operated using their dedicated software. Typically, each of these instruments with their associated software is more suitable for the verification of a pre-specified quality characteristic of the product than others. The number of different systems and software applications to perform a complete measurement of products and assemblies within a manufacturing organisation is therefore expected to be large. This number becomes even larger as advances in measurement technologies are made. The idea of a universal software application for any instrument still appears to be only a theoretical possibility. A need for information integration is apparent. In this paper, a design of an information system to consistently manage (store, search, retrieve, search, secure) measurement results from various instruments and software applications is introduced. Two of the main ideas underlying the proposed system include abstracting structures and formats of measurement files from the data so that complexity and compatibility between different approaches to measurement data modelling is avoided. Secondly, the information within a file is enriched with meta-information to facilitate its consistent storage and retrieval. To demonstrate the designed information system, a web application is implemented. © Springer-Verlag Berlin Heidelberg 2010.

Topic extraction from microblog posts using conversation structures

Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo topics from the messages that they repost or reply. Our model captures the different extents that leader and follower messages may contain the key topical words, thus further enhances the quality of the induced topics. The results of thorough experiments demonstrate the effectiveness of our proposed model.