A sequential algorithm for sparse support vector classifiers

Support vector machines (SVMs), though accurate, are not preferred in applications requiring high classification speed or when deployed in systems of limited computational resources, due to the large number of support vectors involved in the model. To overcome this problem we have devised a primal SVM method with the following properties: (1) it solves for the SVM representation without the need to invoke the representer theorem, (2) forward and backward selections are combined to approach the final globally optimal solution, and (3) a criterion is introduced for identification of support vectors leading to a much reduced support vector set. In addition to introducing this method the paper analyzes the complexity of the algorithm and presents test results on three public benchmark problems and a human activity recognition application. These applications demonstrate the effectiveness and efficiency of the proposed algorithm.


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DemTect:a new, sensitive cognitive screening test to support the diagnosis of mild cognitive impairment and early dementia

To design a new, highly sensitive psychometric screening to identify patients with mild cognitive impairment (MCI) and patients with dementia in the early stages of the disease.

Climate change adaptation : a decision support framework to encourage environmentally responsible behaviour

Structured Abstract:
Purpose: Very few studies investigate environmentally responsible behaviour (ERB). This paper presents a new 'Awareness Behaviour Intervention Action' (ABIA) Decision Support Framework to sustain ERB.

Design/methodology/approach: Previous ERB programmes have failed to deliver lasting results; they have not appropriately understood and provided systems to address ERB (Costanzo et al., 1986). These programmes were based on assumptions (Moloney et al., 2010), which this paper addresses. The ABIA Framework has been developed through a case study of social housing tenants waiting for low or zero carbon homes.

Findings: The ABIA Framework enables a better understanding of current attitudes to environmental issues and provides support for ERB alongside technological interventions employed to promote and sustain carbon reduction.

Research limitations/implications: The ABIA Framework should be tested on individuals and communities in a variety of socio-economic, political and cultural contexts. This will help unpack how it can impact on the behaviours of individuals and communities including stakeholders.

Practical implications: This type of research and the ABIA Framework developed from it are crucial if the UK pledge to become the first country in the World where all new homes from 2016 are to be zero carbon.

Social implications: The Framework encourages both individual and community discussion and solving of sustainability issues.

Originality/value: There are few, if any, studies that have developed a framework which can be used to support behavioural change for adaptation to sustainable living in low or zero carbon homes.

THE ROLE OF SENSE OF CONTROL AND SOCIAL SUPPORT IN MEDIATING THE IMPACT OF PSYCHOLOGICAL DISTRESS - A TEST OF THE HYPOTHESIS OF FUNCTIONAL SUBSTITUTION

The purpose of this paper is to examine the manner in which beliefs relating to sense of control and perceived social support mediate the impact of objective circumstances on psychological distress. In particular it focuses on the nature of the interaction between such variables. The results provide no evidence favouring the displacement hypothesis whereby the benefits of social support involve costs in terms of independence. Consistent support, however, is found for the functional substitution hypothesis. The conclusion is unaffected by the introduction of distinctions relating to types of support and types of power.