Tools for Finding Inconsistencies in Real-world Logic-based Systems

Currently there is extensive theoretical work on inconsistencies in logic-based systems. Recently, algorithms for identifying inconsistent clauses in a single conjunctive formula have demonstrated that practical application of this work is possible. However, these algorithms have not been extended for full knowledge base systems and have not been applied to real-world knowledge. To address these issues, we propose a new algorithm for finding the inconsistencies in a knowledge base using existing algorithms for finding inconsistent clauses in a formula. An implementation of this algorithm is then presented as an automated tool for finding inconsistencies in a knowledge base and measuring the inconsistency of formulae. Finally, we look at a case study of a network security rule set for exploit detection (QRadar) and suggest how these automated tools can be applied.

Towards a general framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.

Communication Nonlinearities Techniques for Analysis of Passive Intermodulation

The X-parameter based nonlinear modelling tools have been adopted as the foundation for the advanced methodology
of experimental characterisation and design of passive nonlinear devices. Based upon the formalism of the Xparameters,
it provides a unified framework for co-design of antenna beamforming networks, filters, phase shifters and
other passive and active devices of RF front-end, taking into account the effect of their nonlinearities. The equivalent
circuits of the canonical elements are readily incorporated in the models, thus enabling evaluation of PIM effect on the
performance of individual devices and their assemblies. An important advantage of the presented methodology is its
compatibility with the industry-standard established commercial RF circuit simulator Agilent ADS.
The major challenge in practical implementation of the proposed approach is concerned with experimental retrieval of the X-parameters for canonical passive circuit elements. To our best knowledge commercial PIM testers and practical laboratory test instruments are inherently narrowband and do not allow for simultaneous vector measurements at the PIM and harmonic frequencies. Alternatively, existing nonlinear vector analysers (NVNA) support X-parameter measurements in a broad frequency bands with a range of stimuli, but their dynamic range is insufficient for the PIM characterisation in practical circuits. Further opportunities for adaptation of the X-parameters methodology to the PIM
characterisation of passive devices using the existing test instruments are explored.

Systematic review of tools to measure outcomes for young children with autism spectrum disorder

BACKGROUND: The needs of children with autism spectrum disorder (ASD) are complex and this is reflected in the number and diversity of outcomes assessed and measurement tools used to collect evidence about children's progress. Relevant outcomes include improvement in core ASD impairments, such as communication, social awareness, sensory sensitivities and repetitiveness; skills such as social functioning and play; participation outcomes such as social inclusion; and parent and family impact.

OBJECTIVES: To examine the measurement properties of tools used to measure progress and outcomes in children with ASD up to the age of 6 years. To identify outcome areas regarded as important by people with ASD and parents.

METHODS: The MeASURe (Measurement in Autism Spectrum disorder Under Review) research collaboration included ASD experts and review methodologists. We undertook systematic review of tools used in ASD early intervention and observational studies from 1992 to 2013; systematic review, using the COSMIN checklist (Consensus-based Standards for the selection of health Measurement Instruments) of papers addressing the measurement properties of identified tools in children with ASD; and synthesis of evidence and gaps. The review design and process was informed throughout by consultation with stakeholders including parents, young people with ASD, clinicians and researchers.

RESULTS: The conceptual framework developed for the review was drawn from the International Classification of Functioning, Disability and Health, including the domains 'Impairments', 'Activity Level Indicators', 'Participation', and 'Family Measures'. In review 1, 10,154 papers were sifted - 3091 by full text - and data extracted from 184; in total, 131 tools were identified, excluding observational coding, study-specific measures and those not in English. In review 2, 2665 papers were sifted and data concerning measurement properties of 57 (43%) tools were extracted from 128 papers. Evidence for the measurement properties of the reviewed tools was combined with information about their accessibility and presentation. Twelve tools were identified as having the strongest supporting evidence, the majority measuring autism characteristics and problem behaviour. The patchy evidence and limited scope of outcomes measured mean these tools do not constitute a 'recommended battery' for use. In particular, there is little evidence that the identified tools would be good at detecting change in intervention studies. The obvious gaps in available outcome measurement include well-being and participation outcomes for children, and family quality-of-life outcomes, domains particularly valued by our informants (young people with ASD and parents).

CONCLUSIONS: This is the first systematic review of the quality and appropriateness of tools designed to monitor progress and outcomes of young children with ASD. Although it was not possible to recommend fully robust tools at this stage, the review consolidates what is known about the field and will act as a benchmark for future developments. With input from parents and other stakeholders, recommendations are made about priority targets for research.

FUTURE WORK: Priorities include development of a tool to measure child quality of life in ASD, and validation of a potential primary outcome tool for trials of early social communication intervention.

STUDY REGISTRATION: This study is registered as PROSPERO CRD42012002223.

FUNDING: The National Institute for Health Research Health Technology Assessment programme.