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Policy and practice documents are increasingly adopting a focus on outcomes. This article seeks to clarify what is meant by the term ‘outcome’, the outcomes that have been highlighted in key policy documents, and the extent to which they reflect the outcomes prioritised by service users. The discussion will draw on the early stages of a DoH‐funded project exploring the effectiveness of health and social care partnerships from the perspectives of service users.

There is currently much policy emphasis on both partnership working between health and social services in the UK and on the outcomes delivered by services. This article provides an account of two consecutive projects centred on these two themes. The first project, at the University of Glasgow, sought to address the lack of evidence about the outcomes delivered to service users by partnerships. Following from this project, the Joint Improvement Team of the Scottish Government commissioned the researchers to develop a toolkit to involve users and unpaid carers in performance management in community care in Scotland. The remit of this second project expanded during 2007 as it became linked with the development of the emerging National Outcomes Framework for community care in Scotland. This article outlines the outcomes‐based piloting work currently under way in Scotland.

Hexahedral meshing is one of the most important steps in performing an accurate simulation using the finite element analysis (FEA). However, the current hexahedral meshing method in the industry is a nonautomatic and inefficient method, i.e. manually decomposing the model into suitable blocks and obtaining the hexahedral mesh from these blocks by mapping or sweeping algorithms. The purpose of this paper is to propose an almost automatic decomposition algorithm based on the 3D frame field and model features to replace the traditional time-consuming and laborious manual decomposition method.

The proposed algorithm is based on the 3D frame field and features, where features are used to construct feature-cutting surfaces and the 3D frame field is used to construct singular-cutting surfaces. The feature-cutting surfaces constructed from concave features first reduce the complexity of the model and decompose it into some coarse blocks. Then, an improved 3D frame field algorithm is performed on these coarse blocks to extract the singular structure and construct singular-cutting surfaces to further decompose the coarse blocks. In most modeling examples, the proposed algorithm uses both types of cutting surfaces to decompose models fully automatically. In a few examples with special requirements for hexahedral meshes, the algorithm requires manual input of some user-defined cutting surfaces and constructs different singular-cutting surfaces to ensure the effectiveness of the decomposition.

Benefiting from the feature decomposition and the 3D frame field algorithm, the output blocks of the proposed algorithm have no inner singular structure and are suitable for the mapping or sweeping algorithm. The introduction of internal constraints makes 3D frame field generation more robust in this paper, and it can automatically correct some invalid 3–5 singular structures. In a few examples with special requirements, the proposed algorithm successfully generates valid blocks even though the singular structure of the model is modified by user-defined cutting surfaces.

The proposed algorithm takes the advantage of feature decomposition and the 3D frame field to generate suitable blocks for a mapping or sweeping algorithm, which saves a lot of simulation time and requires less experience. The user-defined cutting surfaces enable the creation of special hexahedral meshes, which was difficult with previous algorithms. An improved 3D frame field generation method is proposed to correct some invalid singular structures and improve the robustness of the previous methods.

The purpose of this paper is to describe a new ontological content‐based filtering method for ranking the relevance of items for readers of news items, and its evaluation. The method has been implemented in ePaper, a personalised electronic newspaper prototype system. The method utilises a hierarchical ontology of news; it considers common and related concepts appearing in a user's profile on the one hand, and in a news item's profile on the other hand, and measures the “hierarchical distances” between these concepts. On that basis it computes the similarity between item and user profiles and rank‐orders the news items according to their relevance to each user.

The paper evaluates the performance of the filtering method in an experimental setting. Each participant read news items obtained from an electronic newspaper and rated their relevance. Independently, the filtering method is applied to the same items and generated, for each participant, a list of news items ranked according to relevance.

The results of the evaluations revealed that the filtering algorithm, which takes into consideration hierarchically related concepts, yielded significantly better results than a filtering method that takes only common concepts into consideration. The paper determined a best set of values (weights) of the hierarchical similarity parameters. It also found out that the quality of filtering improves as the number of items used for implicit updates of the profile increases, and that even with implicitly updated profiles, it is better to start with user‐defined profiles.

The proposed content‐based filtering method can be used for filtering not only news items but items from any domain, and not only with a three‐level hierarchical ontology but any‐level ontology, in any language.

Robotic arm control is challenging due to the intrinsic nonlinearity. Proportional-integral-derivative (PID) controllers prevail in many robotic arm applications. However, it is usually nontrivial to tune the parameters in a PID controller. This paper aims to propose a model-based control strategy of robotic arms.

A Takagi–Sugeno (T-S) fuzzy model, which is capable of approximating nonlinear systems, is used to describe the dynamics of a robotic arm. Model predictive control (MPC) based on the T-S fuzzy model is considered, which optimizes system performance with respect to a user-defined cost function.

The control gains are optimized online according to the real-time system state. Furthermore, the proposed method takes into account the input constraints. Simulations demonstrate the effectiveness of the fuzzy MPC approach. It is shown that asymptotic stability is achieved for the closed-loop control system.

The T-S fuzzy model is discussed in the modeling of robotic arm dynamics. Fuzzy MPC is used for robotic arm control, which can optimize the transient performance with respect to a user-defined criteria.

To present a decision support system (DSS) enabling the analysis of the cost‐effectiveness of direct‐shipping long‐haul road transport policies, including full truck load (FTL) and less than truck load (LTL) modes, and to select the optimal carrier.

Analytical estimation of transportation costs is provided in a framework including an interactive computer procedure and a dedicated database structure capable of characterizing the logistics system.

Main criticalities of manual logistic planning are: sub‐optimal selection of carrier and excessive use of LTL transport, while the optimal FTL vs LTL trade‐off is not fully explored in practice.

This is an analysis tool of user‐defined scenarios and does not provide the automatic synthesis of shipments planning. Admittedly, this model does not attempt to optimize the shipping strategy, but to quantitatively assess the effects of the adopted decisions.

Alternative shipping policies can be compared to perform what‐if analyses and explore the outcome of alternative decisions (FTL vs LTL shipping modes) even in terms of transportation expenditures. Allows rapid selection of the optimal motor carrier and assesses the extra cost due to a sub‐optimal choice. Gives the experienced manager a framework for critical assessment of shipping decisions, suggesting improvement areas for cost reduction.

With respect to other software tools for carrier selection provides explicit analysis of extra costs incurred by manual planning, thus becoming a strategic tool for logistic decision making. Furthermore, enables managerial insights to be gained and makes manual planning more effective.

The purpose of this paper is to propose a framework for intelligent analysis of Twitter data. The purpose of the framework is to allow users to explore a collection of tweets by extracting topics with semantic relevance. In this way, it is possible to detect groups of tweets related to new technologies, events and other topics that are automatically discovered.

The framework is based on a three-stage process. The first stage is devoted to dataset creation by transforming a collection of tweets in a dataset according to the vector space model. The second stage, which is the core of the framework, is centered on the use of non-negative matrix factorizations (NMF) for extracting human-interpretable topics from tweets that are eventually clustered. The number of topics can be user-defined or can be discovered automatically by applying subtractive clustering as a preliminary step before factorization. Cluster analysis and word-cloud visualization are used in the last stage to enable intelligent data analysis.

The authors applied the framework to a case study of three collections of Italian tweets both with manual and automatic selection of the number of topics. Given the high sparsity of Twitter data, the authors also investigated the influence of different initializations mechanisms for NMF on the factorization results. Numerical comparisons confirm that NMF could be used for clustering as it is comparable to classical clustering techniques such as spherical k-means. Visual inspection of the word-clouds allowed a qualitative assessment of the results that confirmed the expected outcomes.

The proposed framework enables a collaborative approach between users and computers for an intelligent analysis of Twitter data. Users are faced with interpretable descriptions of tweet clusters, which can be interactively refined with few adjustable parameters. The resulting clusters can be used for intelligent selection of tweets, as well as for further analytics concerning the impact of products, events, etc. in the social network.

The purpose of this study is to develop an immune genetic algorithm (IGA) to solve the simple assembly line balancing problem of type 1 (SALBP-1). The objective is to minimize the number of workstations and workstation load for a given cycle time of the assembly line.

This paper develops a new solution method for SALBP-1, and a user-defined function named ψ(·) is proposed to convert all the individuals to satisfy the precedence relationships during the operation of IGA.

Computational experiments suggest that the proposed method is efficient.

An IGA is proposed to solve the SALBP-1 for the first time.

This paper presents a newly developed algorithm for selecting and locating mobile cranes on construction sites. The algorithm is incorporated into a computer system that integrates a selection module and three databases, dedicated respectively, for cranes, rigging equipment, and projects’ information. This paper focuses primarily on the selection module and its algorithm to support an efficient search for most suitable crane configurations and their associated lift settings. Data pertinent to crane lift configurations and settings are retrieved from the databases and processed to determine the near optimum selection of a crane configuration. The developed selection module features powerful graphics capabilities and a practical user‐friendly interface, designed to facilitate the considerations of user imposed lift and site constraints. The selection algorithm has been implemented within the crane selection module using MS‐Visual Basic programming language. A case example is presented in order to demonstrate the use of the developed selection module and to illustrate its essential features.

Spatial messaging is a direct extension to text and other multi‐media messaging services that have become highly popular with the current pervasiveness of mobile communication. It offers benefits especially to mobile computing, providing localized and therefore potentially more appropriate delivery of nearly arbitrary content. Location is one of the most interesting attributes that can be added to messages in current applications, including gaming, social networking, or advertising services. However, location is also highly critical in terms of privacy. If a spatial messaging platform could collect the location traces of all its users, detailed profiling would be possible – and, considering commercial value of such profiles, likely. The purpose of this paper is to present Air‐Writing, an approach to spatial messaging that fully preserves user privacy while offering global scalability, different client interface options, and flexibility in terms of application areas.

The authors contribute both an architecture and a specific implementation of an attribute‐based messaging platform with special support for spatial messaging and rich clients for J2ME, Google Android, and Apple iPhone. The centralized client/server approach utilizes groups for anonymous message retrieval and client caching and filtering, as well as randomized queries for obscuring traces.

Two user studies with 26 users show that the overall concept is easily understandable and that it seems useful to end‐users. An analysis of real‐world and simulated location traces shows that user privacy can be ensured, but with a trade‐off between privacy protection and consumed network resources.

Air‐Writing, both as an architectural concept and as a specific implementation, are immediately applicable to practical, globally scalable, private group messaging systems. A publicly available messaging platform is already online as beta version at http://airwriting.com Originality/value – Air‐Writing addresses three concerns: flexibility concerning arbitrary messaging applications, user privacy, and global scalability of the associated web service. To the best of the authors' knowledge, previous approaches focus on at most two of these issues, while the authors' approach allows all three requirements to be fulfilled.