Case-based analysis in user requirements modelling for knowledge construction

Context: Learning can be regarded as knowledge construction in which prior knowledge and experience serve as basis for the learners to expand their knowledge base. Such a process of knowledge construction has to take place continuously in order to enhance the learners’ competence in a competitive working environment. As the information consumers, the individual users demand personalised information provision which meets their own specific purposes, goals, and expectations. Objectives: The current methods in requirements engineering are capable of modelling the common user’s behaviour in the domain of knowledge construction. The users’ requirements can be represented as a case in the defined structure which can be reasoned to enable the requirements analysis. Such analysis needs to be enhanced so that personalised information provision can be tackled and modelled. However, there is a lack of suitable modelling methods to achieve this end. This paper presents a new ontological method for capturing individual user’s requirements and transforming the requirements onto personalised information provision specifications. Hence the right information can be provided to the right user for the right purpose. Method: An experiment was conducted based on the qualitative method. A medium size of group of users participated to validate the method and its techniques, i.e. articulates, maps, configures, and learning content. The results were used as the feedback for the improvement. Result: The research work has produced an ontology model with a set of techniques which support the functions for profiling user’s requirements, reasoning requirements patterns, generating workflow from norms, and formulating information provision specifications. Conclusion: The current requirements engineering approaches provide the methodical capability for developing solutions. Our research outcome, i.e. the ontology model with the techniques, can further enhance the RE approaches for modelling the individual user’s needs and discovering the user’s requirements.

Enhancing pollinator biodiversity in intensive grasslands

Increased agricultural intensification has led to well-documented declines in the fauna and flora associated with intensive grasslands in the UK. We aimed to quantify the effectiveness of different field margin management strategies for putting bumblebee and butterfly biodiversity back into intensive grasslands. Using four intensive livestock farms in south-west England, we manipulated conventional management practices (addition of inorganic fertilizer, cutting frequency and height, and aftermath grazing) to generate seven grass-based treatments along a gradient of decreasing management intensity. We also tested two more interventionist treatments which introduced sown components into the sward: (i) a cereal, grass and legume mix, and (ii) a diverse conservation mix with kale, mixed cereals, linseed and legumes. These crop mixtures were intended to provide forage and structural resources for pollinators but were not intended to have agronomic value as livestock feed. Using a replicated block design, we monitored bumblebee and butterfly responses in 27 plots (10 x 50 m) in each farm from 2003 to 2006. Bumblebees were most abundant, species-rich and diverse in the sown treatments and virtually absent from the grass-based treatments. The diverse conservation mix treatment supported larger and more diverse bumblebee assemblages than the cereal, grass and legume mix treatment. The sown treatments, and the most extensively managed grass-based treatments, had the highest abundance, species richness and diversity of adult butterflies, whereas butterfly larvae were only found in the grass-based treatments. Bumblebee and butterfly assemblage structure was driven by floral abundance, floral richness, the availability of nectar resources, and sward structure. Only vegetation cover was correlated with butterfly larval abundance. Synthesis and applications. This study has identified management options in the margins of intensive grasslands which can enhance bumblebee and butterfly biodiversity. Extensification of conventional grass management by stopping fertilization, reducing cutting frequency and not grazing, benefits butterflies. However, to enhance bumblebees requires a more interventionist approach in the form of sowing flower-rich habitat. Both approaches are potentially suitable for adoption in agri-environment schemes in the UK and Europe.

Evaluation of NRC, UC Davis and ADAS approaches to estimate the metabolizable energy values of feeds at maintenance energy intake from equations utilizing chemical assays and in vitro determinations

Feed samples received by commercial analytical laboratories are often undefined or mixed varieties of forages, originate from various agronomic or geographical areas of the world, are mixtures (e.g., total mixed rations) and are often described incompletely or not at all. Six unified single equation approaches to predict the metabolizable energy (ME) value of feeds determined in sheep fed at maintenance ME intake were evaluated utilizing 78 individual feeds representing 17 different forages, grains, protein meals and by-product feedstuffs. The predictive approaches evaluated were two each from National Research Council [National Research Council (NRC), Nutrient Requirements of Dairy Cattle, seventh revised ed. National Academy Press, Washington, DC, USA, 2001], University of California at Davis (UC Davis) and ADAS (Stratford, UK). Slopes and intercepts for the two ADAS approaches that utilized in vitro digestibility of organic matter and either measured gross energy (GE), or a prediction of GE from component assays, and one UC Davis approach, based upon in vitro gas production and some component assays, differed from both unity and zero, respectively, while this was not the case for the two NRC and one UC Davis approach. However, within these latter three approaches, the goodness of fit (r(2)) increased from the NRC approach utilizing lignin (0.61) to the NRC approach utilizing 48 h in vitro digestion of neutral detergent fibre (NDF:0.72) and to the UC Davis approach utilizing a 30 h in vitro digestion of NDF (0.84). The reason for the difference between the precision of the NRC procedures was the failure of assayed lignin values to accurately predict 48 h in vitro digestion of NDF. However, differences among the six predictive approaches in the number of supporting assays, and their costs, as well as that the NRC approach is actually three related equations requiring categorical description of feeds (making them unsuitable for mixed feeds) while the ADAS and UC Davis approaches are single equations, suggests that the procedure of choice will vary dependent Upon local conditions, specific objectives and the feedstuffs to be evaluated. In contrast to the evaluation of the procedures among feedstuffs, no procedure was able to consistently discriminate the ME values of individual feeds within feedstuffs determined in vivo, suggesting that the quest for an accurate and precise ME predictive approach among and within feeds, may remain to be identified. (C) 2004 Elsevier B.V. All rights reserved.

Bayesian decision procedures for dose-escalation based on evidence of undesirable events and therapeutic benefit.

In this paper, Bayesian decision procedures are developed for dose-escalation studies based on bivariate observations of undesirable events and signs of therapeutic benefit. The methods generalize earlier approaches taking into account only the undesirable outcomes. Logistic regression models are used to model the two responses, which are both assumed to take a binary form. A prior distribution for the unknown model parameters is suggested and an optional safety constraint can be included. Gain functions to be maximized are formulated in terms of accurate estimation of the limits of a therapeutic window or optimal treatment of the next cohort of subjects, although the approach could be applied to achieve any of a wide variety of objectives. The designs introduced are illustrated through simulation and retrospective implementation to a completed dose-escalation study. Copyright © 2006 John Wiley & Sons, Ltd.

An evaluation of a Bayesian method of dose escalation based on bivariate binary responses

Recently, various approaches have been suggested for dose escalation studies based on observations of both undesirable events and evidence of therapeutic benefit. This article concerns a Bayesian approach to dose escalation that requires the user to make numerous design decisions relating to the number of doses to make available, the choice of the prior distribution, the imposition of safety constraints and stopping rules, and the criteria by which the design is to be optimized. Results are presented of a substantial simulation study conducted to investigate the influence of some of these factors on the safety and the accuracy of the procedure with a view toward providing general guidance for investigators conducting such studies. The Bayesian procedures evaluated use logistic regression to model the two responses, which are both assumed to be binary. The simulation study is based on features of a recently completed study of a compound with potential benefit to patients suffering from inflammatory diseases of the lung.

A novel parallel approach to the likelihood-based estimation of admixture in population genetics

Inferring population admixture from genetic data and quantifying it is a difficult but crucial task in evolutionary and conservation biology. Unfortunately state-of-the-art probabilistic approaches are computationally demanding. Effectively exploiting the computational power of modern multiprocessor systems can thus have a positive impact to Monte Carlo-based simulation of admixture modeling. A novel parallel approach is briefly described and promising results on its message passing interface (MPI)-based C implementation are reported.

Modern approaches to floristics and their impact on the region of SW Asia

Attitudes to floristics have changed considerably during the past few decades as a result of increasing and often more focused consumer demands, heightened awareness of the threats to biodiversity, information flow and overload, and the application of electronic and web-based techniques to information handling and processing. This paper will examine these concerns in relation to our floristic knowledge and needs in the region of SW Asia. Particular reference will be made to the experience gained from the Euro+Med PlantBase project for the preparation of an electronic plant-information system for Europe and the Mediterranean, with a single core list of accepted plant names and synonyms, based on consensus taxonomy agreed by a specialist network. The many challenges Ð scientific, technical and organisational Ð that it has presented will be discussed as well as the problems of handling nontaxonomic information from fields such as conservation, karyology, biosystematics and mapping. The question of regional cooperation and the sharing of efforts and resources will also be raised and attention drawn to the recent planning workshop held in Rabat (May 2002) for establishing a technical cooperation network for taxonomic capacity building in North Africa as a possible model for the SW Asia region.

Synthesis of a catechol-based poly(ether ether ketone) ("o-PEEK") by classical step-growth polymerization and by entropically driven ring-opening polymerization of macrocyclic oligomers

An amorphous, catechol-based analogue of PEEK ("o-PEEK") has been prepared by a classical step-growth polymerization reaction between catechol and 4,4'-difluorobenzophenone and shown to be readily soluble in a range of organic solvents. Copolymers with p-PEEK have been investigated, including an amorphous 50: 50 composition and a semicrystalline though still organic-soluble material comprising 70% p-PEEK. o-PEEK has also been obtained by entropy-driven ring-opening polymerization of the macrocyclic oligomers (MCO's) formed by cyclo-condensation of catechol with 4,4'-difluorobenzophenone under pseudo-high-dilution conditions. The principal products of this latter reaction were the cyclic dimer 3a (20 wt %), cyclic trimer 3b (16%) cyclic tetramer 3c (14%), cyclic pentamer 3d (13%) and cyclic hexamer 3e (12%). Macrocycles 3a-c were isolated as pure compounds by gradient column chromatography, and the structures of the cyclic dimer 3a and cyclic tetramer 3c were analyzed by single-crystal X-ray diffraction. A mixture of MCO's, 3, of similar composition, was obtained by cyclodepolymerization of high molar mass o-PEEK in dilute soluion.

Modelling for planning building design - a critique of available approaches

This paper reviews four approaches used to create rational tools to aid the planning and the management of the building design process and then proposes a fifth approach. The new approach that has been developed is based on the mechanical aspects of technology rather than subjective design issues. The knowledge base contains, for each construction technology, a generic model of the detailed design process. Each activity in the process is specified by its input and output information needs. By connecting the input demands of one technology with the output supply from another technology a map or network of design activity is formed. Thus, it is possible to structure a specific model from the generic knowledge base within a KBE system.

Evidence of systematic approaches to innovation in facilities management

Purpose – This paper seeks to examine the nature of “service innovation” in the facilities management (FM) context. It reviews recent thinking on “service innovation” as distinct from “product innovation”. Applying these contemporary perspectives it describes UK case studies of 11 innovations in different FM organisations. These include both in-house client-based innovations and third-party innovations. Design/methodology/approach – The study described in the paper encompasses 11 different innovations that constitute a mix of process, product and practice innovations. All of the innovations stem from UK-based organisations that were subject to in-depth interviews regarding the identification, screening, commitment of resources and implementation of the selected innovations. Findings – The research suggested that service innovation is highly active in the UK FM sector. However, the process of innovation rarely followed a common formalized path. Generally, the innovations were one-shot commitments at the early stage. None of the innovations studied failed to proceed to full adoption stage. This was either due to the reluctance of participating organisations to volunteer “tested but unsuccessful” innovations or the absence of any trial methods that might have exposed an innovations shortcomings. Research limitations/implications – The selection of innovations was restricted to the UK context. Moreover, the choice of innovations was partly determined by the innovating organisation. This selection process appeared to emphasise “one-shot” high profile technological innovations, typically associated with software. This may have been at the expense of less resource intensive, bottom-up innovations. Practical implications – This paper suggests that there is a role for “research and innovation” teams within larger FM organisations, whether they are client-based or third-party. Central to this philosophy is an approach that is open to the possibility of failure. The innovations studied were risk averse with a firm commitment to proceed at the early stage. Originality/value – This paper introduces new thinking on the subject of “service innovation” to the context of FM. It presents research and development as a planned solution to innovation. This approach will enable service organisations to fully test and exploit service innovations.

Theoretical and experimental approaches towards the determination of solute effective diffusivities in foods

The aim of this review paper is to present experimental methodologies and the mathematical approaches used to determine effective diffusivities of solutes in food materials. The paper commences by describing the diffusion phenomena related to solute mass transfer in foods and effective diffusivities. It then focuses on the mathematical formulation for the calculation of effective diffusivities considering different diffusion models based on Fick's second law of diffusion. Finally, experimental considerations for effective diffusivity determination are elucidated primarily based on the acquirement of a series of solute content versus time curves appropriate to the equation model chosen. Different factors contributing to the determination of the effective diffusivities such as the structure of food material, temperature, diffusion solvent, agitation, sampling, concentration and different techniques used are considered. (c) 2005 Elsevier Inc. All rights reserved.

Verification and FPGA circuits of a block-2 fast path-based predictor

This paper formally derives a new path-based neural branch prediction algorithm (FPP) into blocks of size two for a lower hardware solution while maintaining similar input-output characteristic to the algorithm. The blocked solution, here referred to as B2P algorithm, is obtained using graph theory and retiming methods. Verification approaches were exercised to show that prediction performances obtained from the FPP and B2P algorithms differ within one mis-prediction per thousand instructions using a known framework for branch prediction evaluation. For a chosen FPGA device, circuits generated from the B2P algorithm showed average area savings of over 25% against circuits for the FPP algorithm with similar time performances thus making the proposed blocked predictor superior from a practical viewpoint.

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

A swarm pattern transformation method based on macroscopic parameter operations

The work reported in this paper is motivated by biomimetic inspiration - the transformation of patterns. The major issue addressed is the development of feasible methods for transformation based on a macroscopic tool. The general requirement for the feasibility of the transformation method is determined by classifying pattern formation approaches an their characteristics. A formal definition for pattern transformation is provided and four special cases namely, elementary and geometric transformation based on repositioning all and some robotic agents are introduced. A feasible method for transforming patterns geometrically, based on the macroscopic parameter operation of a swarm is considered. The transformation method is applied to a swarm model which lends itself to the transformation technique. Simulation studies are developed to validate the feasibility of the approach, and do indeed confirm the approach.

Robust background model for pixel based people counting using a single uncalibrated camera

Several pixel-based people counting methods have been developed over the years. Among these the product of scale-weighted pixel sums and a linear correlation coefficient is a popular people counting approach. However most approaches have paid little attention to resolving the true background and instead take all foreground pixels into account. With large crowds moving at varying speeds and with the presence of other moving objects such as vehicles this approach is prone to problems. In this paper we present a method which concentrates on determining the true-foreground, i.e. human-image pixels only. To do this we have proposed, implemented and comparatively evaluated a human detection layer to make people counting more robust in the presence of noise and lack of empty background sequences. We show the effect of combining human detection with a pixel-map based algorithm to i) count only human-classified pixels and ii) prevent foreground pixels belonging to humans from being absorbed into the background model. We evaluate the performance of this approach on the PETS 2009 dataset using various configurations of the proposed methods. Our evaluation demonstrates that the basic benchmark method we implemented can achieve an accuracy of up to 87% on sequence ¿S1.L1 13-57 View 001¿ and our proposed approach can achieve up to 82% on sequence ¿S1.L3 14-33 View 001¿ where the crowd stops and the benchmark accuracy falls to 64%.