A pattern language for goals

Previous work has established the value of goal-oriented approaches to requirements engineering. Achieving clarity and agreement about stakeholders’ goals and assumptions is critical for building successful software systems and managing their subsequent evolution. In general, this decision-making process requires stakeholders to understand the implications of decisions outside the domains of their own expertise. Hence it is important to support goal negotiation and decision making with description languages that are both precise and expressive, yet easy to grasp. This paper presents work in progress to develop a pattern language for describing goal refinement graphs. The language has a simple graphical notation, which is supported by a prototype editor tool, and a symbolic notation based on modal logic.

The state of veterinary epidemiology and economics

Recent developments in the fields of veterinary epidemiology and economics are critically reviewed and assessed. The impacts of recent technological developments in diagnosis, genetic characterisation, data processing and statistical analysis are evaluated. It is concluded that the acquisition and availability of data remains the principal constraint to the application of available techniques in veterinary epidemiology and economics, especially at population level. As more commercial producers use computerised management systems, the availability of data for analysis within herds is improving. However, consistency of recording and diagnosis remains problematic. Recent trends to the development of national livestock databases intended to provide reassurance to consumers of the safety and traceability of livestock products are potentially valuable sources of data that could lead to much more effective application of veterinary epidemiology and economics. These opportunities will be greatly enhanced if data from different sources, such as movement recording, official animal health programmes, quality assurance schemes, production recording and breed societies can be integrated. However, in order to realise such integrated databases, it will be necessary to provide absolute control of user access to guarantee data security and confidentiality. The potential applications of integrated livestock databases in analysis, modelling, decision-support, and providing management information for veterinary services and livestock producers are discussed. (c) 2004 Elsevier B.V. All rights reserved.

Knowledge-based clinical pathway for medical quality improvement

Clinical pathways have been adopted for various diseases in clinical departments for quality improvement as a result of standardization of medical activities in treatment process. Using knowledge-based decision support on the basis of clinical pathways is a promising strategy to improve medical quality effectively. However, the clinical pathway knowledge has not been fully integrated into treatment process and thus cannot provide comprehensive support to the actual work practice. Therefore this paper proposes a knowledgebased clinical pathway management method which contributes to make use of clinical knowledge to support and optimize medical practice. We have developed a knowledgebased clinical pathway management system to demonstrate how the clinical pathway knowledge comprehensively supports the treatment process. The experiences from the use of this system show that the treatment quality can be effectively improved by the extracted and classified clinical pathway knowledge, seamless integration of patient-specific clinical pathway recommendations with medical tasks and the evaluating pathway deviations for optimization.

Unified framework for construction of rule based classification systems

Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

Integrating science into humanitarian and development planning and practice to enhance community resilience

There has been an increased emphasis upon the application of science for humanitarian and development planning, decision-making and practice; particularly in the context of understanding, assessing and anticipating risk (e.g. HERR, 2011). However, there remains very little guidance for practitioners on how to integrate sciences they may have had little contact with in the past (e.g. climate). This has led to confusion as to which ‘science’ might be of use and how it would be best utilised. Furthermore, since this integration has stemmed from a need to be more predictive, agencies are struggling with the problems associated with uncertainty and probability. Whilst a range of expertise is required to build resilience, these guidelines focus solely upon the relevant data, information, knowledge, methods, principles and perspective which scientists can provide, that typically lie outside of current humanitarian and development approaches. Using checklists, real-life case studies and scenarios the full guidelines take practitioners through a five step approach to finding, understanding and applying science. This document provides a short summary of the five steps and some key lessons for integrating science.

Improving productivity and water use efficiency: a case study of farms in England

The idea of Sustainable Intensification comes as a response to the challenge of avoiding resources such as land, water and energy being overexploited while increasing food production for an increasing demand from a growing global population. Sustainable Intensification means that farmers need to simultaneously increase yields and sustainably use limited natural resources, such as water. Within the agricultural sector water has a number of uses including irrigation, spraying, drinking for livestock and washing (vegetables, livestock buildings). In order to achieve Sustainable Intensification measures are needed that enable policy makers and managers to inform them about the relative performance of farms as well as of possible ways to improve such performance. We provide a benchmarking tool to assess water use (relative) efficiency at a farm level, suggest pathways to improve farm level productivity by identifying best practices for reducing excessive use of water for irrigation. Data Envelopment Analysis techniques including analysis of returns to scale were used to evaluate any excess in agricultural water use of 66 Horticulture Farms based on different River Basin Catchments across England. We found that farms in the sample can reduce on average water requirements by 35% to achieve the same output (Gross Margin) when compared to their peers on the frontier. In addition, 47% of the farms operate under increasing returns to scale, indicating that farms will need to develop economies of scale to achieve input cost savings. Regarding the adoption of specific water use efficiency management practices, we found that the use of a decision support tool, recycling water and the installation of trickle/drip/spray lines irrigation system has a positive impact on water use efficiency at a farm level whereas the use of other irrigation systems such as the overhead irrigation system was found to have a negative effect on water use efficiency.

Governing calculative practices: An investigation of development viability modelling in the English planning system

Over the last decade the English planning system has placed greater emphasis on the financial viability of development. ‘Calculative’ practices have been used to quantify and capture land value uplifts. Development viability appraisal (DVA) has become a key part of the evidence base used in planning decision-making and informs both ‘site-specific’ negotiations about the level of land value capture for individual schemes and ‘area-wide’ planning policy formation. This paper investigates how implementation of DVA is governed in planning policy formation. It is argued that the increased use of DVA raises important questions about how planning decisions are made and operationalised, not least because DVA is often poorly understood by some key stakeholders. The paper uses the concept of governance to thematically analyse semi-structured interviews conducted with the producers of DVAs and considers key procedural issues including (in)consistencies in appraisal practices, levels of stakeholder consultation and the potential for client and producer bias. Whilst stakeholder consultation is shown to be integral to the appraisal process in order to improve the quality of the appraisals and to legitimise the outputs, participation is restricted to industry experts and excludes some interest groups, including local communities. It is concluded that, largely because of its recent adoption and knowledge asymmetries between local planning authorities and appraisers, DVA is a weakly governed process characterised by emerging and contested guidance and is therefore ‘up for grabs’.

A multi-scale framework for strategic management of diffuse pollution

A multi-scale framework for decision support is presented that uses a combination of experiments, models, communication, education and decision support tools to arrive at a realistic strategy to minimise diffuse pollution. Effective partnerships between researchers and stakeholders play a key part in successful implementation of this strategy. The Decision Support Matrix (DSM) is introduced as a set of visualisations that can be used at all scales, both to inform decision making and as a communication tool in stakeholder workshops. A demonstration farm is presented and one of its fields is taken as a case study. Hydrological and nutrient flow path models are used for event based simulation (TOPCAT), catchment scale modelling (INCA) and field scale flow visualisation (TopManage). One of the DSMs; The Phosphorus Export Risk Matrix (PERM) is discussed in detail. The PERM was developed iteratively as a point of discussion in stakeholder workshops, as a decision support and education tool. The resulting interactive PERM contains a set of questions and proposed remediation measures that reflect both expert and local knowledge. Education and visualisation tools such as GIS, risk indicators, TopManage and the PERM are found to be invaluable in communicating improved farming practice to stakeholders. (C) 2008 Elsevier Ltd. All rights reserved.

Mitigation of diffuse phosphorus pollution during rewetting of fen peat soils: A trans-European case study

Intensive cultivation of fen peat soils (Eutric Histosols) for agricultural purposes, started in Europe about 250 years ago, resulting in decreased soil fertility, increased oxidation of peat and corresponding CO2-emissions to the atmosphere, nutrient transfer to aquatic ecosystems and losses in the total area of the former native wetlands. To prevent these negative environmental effects set-aside programs and rewetting measures were promoted in recent years. Literature results and practical experiences showed that large scale rewetting of intensively used agricultural Histosols may result in the mobilisation of phosphorus (P), its transport to adjacent surface waters and an accelerated eutrophication risk. The paper summarises results from an international European Community sponsored research project and demonstrates how results obtained at different scales and from different scientific disciplines were compiled to derive a strategy to carry out rewetting measures. A decision support system (DSS) for a hydrologically sensitive area in the Droemling catchment in north-eastern Germany was developed and is presented as a tool to regulate rewetting in order to control P release. It is demonstrated that additional laboratory experiments to identify essential processes of P release during rewetting and the site-specific management of the water table, the involvement of specific knowledge and experience of the stakeholders are necessary to develop an applicable DSS. The presented DSS is practically used to prevent freshwater resources from diffuse P pollution.

Drought, pod yield, pre-harvest Aspergillus infection and aflatoxin contamination on peanut in Niger

Soil moisture and soil temperature affect pre-harvest infection with Aspergillus flavus and production of aflatoxin. The objectives of our field research in Niger, West Africa, were to: (i) examine the effects of sowing date and irrigation treatments on pod yield, infection with A. flavus and aflatoxin concentration; and (ii) to quantify relations between infection, aflatoxin concentration and soil moisture stress. Seed of an aflatoxin susceptible peanut cv. JL24 was sown at two to four different sowing dates under four irrigation treatments (rainfed and irrigation at 7, 14 and 21 days intervals) between 1991 and 1994, giving 40 different 'environments'. Average air and soil temperatures of 28-34 degrees C were favourable for aflatoxin contamination. CROPGRO-peanut model was used to simulate the occurrence of moisture stress. The model was able to simulate yields of peanut well over the 40 environments (r(2) = 0.67). In general, early sowing produced greater pod yields, as well as less infection and lower aflatoxin concentration. There were negative linear relations between infection (r(2) = 0.62) and the average simulated fraction of extractable soil water (FESW) between flowering and harvest, and between aflatoxin concentration (r(2) = 0.54) and FESW in the last 25 days of pod-filling. This field study confirms that infection and aflatoxin concentration in peanut can be related to the occurrence of soil moisture stress during pod-filling when soil temperatures are near optimal for A. flavus. These relations could form the basis of a decision-support system to predict the risk of aflatoxin contamination in peanuts in similar environments. (c) 2005 Elsevier B.V. All rights reserved.

An integrated mathematical model to evaluate nutrient partition in dairy cattle between the animal and its environment

In the past decade, a number of mechanistic, dynamic simulation models of several components of the dairy production system have become available. However their use has been limited due to the detailed technical knowledge and special software required to run them, and the lack of compatibility between models in predicting various metabolic processes in the animal. The first objective of the current study was to integrate the dynamic models of [Brit. J. Nutr. 72 (1994) 679] on rumen function, [J. Anim. Sci. 79 (2001) 1584] on methane production, [J. Anim. Sci. 80 (2002) 2481 on N partition, and a new model of P partition. The second objective was to construct a decision support system to analyse nutrient partition between animal and environment. The integrated model combines key environmental pollutants such as N, P and methane within a nutrient-based feed evaluation system. The model was run under different scenarios and the sensitivity of various parameters analysed. A comparison of predictions from the integrated model with the original simulation models showed an improvement in N excretion since the integrated model uses the dynamic model of [Brit. J. Nutr. 72 (1994) 6791 to predict microbial N, which was not represented in detail in the original model. The integrated model can be used to investigate the degree to which production and environmental objectives are antagonistic, and it may help to explain and understand the complex mechanisms involved at the ruminal and metabolic levels. A part of the integrated model outputs were the forms of N and P in excreta and methane, which can be used as indices of environmental pollution. (C) 2004 Elsevier B.V All rights reserved.

HDC poinsettia tracker: flexible graphical tracking software

Growing pot poinsettia and similar crops involves careful crop monitoring and management to ensure that height specifications are met. Graphical tracking represents a target driven approach to decision support with simple interpretation. HDC (Horticultural Development Council) Poinsettia Tracker implements a graphical track based on the Generalised Logistic Curve, similar to that of other tracking packages. Any set of curve parameters can be used to track crop progress. However, graphical tracks must be expected to be site and cultivar specific. By providing a simple Curve fitting function, growers can easily develop their own site and variety specific ideal tracks based on past records with increasing quality as more seasons' data are added. (C) 2009 Elsevier B.V. All rights reserved.