A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Computational learning of the conditional phase-type (C-Ph) distribution: Learning C-Ph distributions

This paper presents a new algorithm for learning the structure of a special type of Bayesian network. The conditional phase-type (C-Ph) distribution is a Bayesian network that models the probabilistic causal relationships between a skewed continuous variable, modelled by the Coxian phase-type distribution, a special type of Markov model, and a set of interacting discrete variables. The algorithm takes a dataset as input and produces the structure, parameters and graphical representations of the fit of the C-Ph distribution as output.The algorithm, which uses a greedy-search technique and has been implemented in MATLAB, is evaluated using a simulated data set consisting of 20,000 cases. The results show that the original C-Ph distribution is recaptured and the fit of the network to the data is discussed.

Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

A design model: the Autism Spectrum Disorder Classroom Design Kit

Architects and designers have a responsibility to provide an inclusive built environment. However for those with a diagnosis of Autism Spectrum Disorder (ASD), the built environment can be a frightening and confusing place, difficult to negotiate and tolerate. The challenge of integrating more fully into society is denied by an alienating built environment. For ASD pupils in a poorly designed school, their environment can distance them from learning. Instead, if more at ease in their surroundings, in an ASD-friendly environment, the ASD pupil stands a greater chance of doing better.

However a difficulty exists in that most architects are not knowledgeable in designing for those with ASD. Any available design guidelines for architects tend, because of the inherent difficulties associated with a spectrum, to be general in their information. Therefore, if wanting to provide an ASD-friendly learning environment, there is a need to ensure that teachers, as the experts, can most clearly and effectively impart their knowledge and requirements to architects.

This paper sets out the challenges and difficulties inherent in the design process when designing for ASD. It then sets out an alternative strategy to the usual method of drawing-centric dialogue between teacher and architect by using models instead as a basis for a more common language. An ASD Classroom Design Kit was designed and developed by Queen’s University of Belfast Architecture students. It was then used by ASD teaching staff from the Southern Education and Library Board in Northern Ireland as a case study to trial its effectiveness. The paper outlines how the study was carried out before concluding with reflections by both teaching staff and architect on using the ASD Classroom Design Kit.

It is hoped that this paper will firstly highlight the need for better dialogue between expert and architect when considering ASD and the Built Environment and secondly, that it may encourage others to consider using models to convey their ideas and knowledge when designing, not just for ASD, but for other Special Educational Needs and disabilities.

Visuomotor transformation for interception:catching while fixating

Catching a ball involves a dynamic transformation of visual information about ball motion into motor commands for moving the hand to the right place at the right time. We previously formulated a neural model for this transformation to account for the consistent leftward movement biases observed in our catching experiments. According to the model, these biases arise within the representation of target motion as well as within the transformation from a gaze-centered to a body-centered movement command. Here, we examine the validity of the latter aspect of our model in a catching task involving gaze fixation. Gaze fixation should systematically influence biases in catching movements, because in the model movement commands are only generated in the direction perpendicular to the gaze direction. Twelve participants caught balls while gazing at a fixation point positioned either straight ahead or 14 degrees to the right. Four participants were excluded because they could not adequately maintain fixation. We again observed a consistent leftward movement bias, but the catching movements were unaffected by fixation direction. This result refutes our proposal that the leftward bias partly arises within the visuomotor transformation, and suggests instead that the bias predominantly arises within the early representation of target motion, specifically through an imbalance in the represented radial and azimuthal target motion.

Ethnic Competition and the logic of party system transformation

This article adapts and expands a recent model of ethnic competition by exploring its implications over a long period spanning crucial stages in the modernisation of the political system. It illustrates the model by reference to developments in Northern Ireland since its modern party system was launched in the 1880s. This offers an exceptionally clear example of the interaction of central elements of the model: the initial bedding down of a system of bipartisan ethnic competition, with two parties having a remarkable capacity to resist ethnic outbidding; the fragmentation of this system following the introduction of a set of major institutional forms that facilitated ethnic outbidding; and the continuing resilience of ethnically based parties in warding off challenges from groups seeking to prioritise other political dimensions. The model's implications are tested against a comprehensive collection of ecological and survey data.

The principles and practice of interpreting cardiac rhythm strips: a seven-step model

This open learning zone article examines the cardiac cycle and the interpretation of cardiac rhythm strips. The article begins with a brief revision of related physiology followed by a description of normal sinus rhythm and the main cardiac rhythm abnormalities. The article concludes by providing easy to follow steps for use in the interpretation of cardiac rhythm strips with practice examples presented in the CPD task section.

AßPP over-expressing transgenic rat model of Alzheimer's disease utilizing the Tg2576 mouse protocol.

The current study examined behavioral and histological effects of amyloid-ß (Aß) protein precursor (AßPP) overexpression in transgenic (Tg) rats created using the same gene, mutation, and promoter as the Tg2576 mouse model of Alzheimer's disease (AD). Male Tg+ rats were bred with female wild-type rats to generate litters of hemizygous Tg+ and Tg- offspring. Tg+ rats and Tg- littermates were tested for memory deficits at 4, 8, and 12 months old using a water-maze procedure. There were no significant behavioral differences between Tg+ rats and Tg- littermates at 4 months old but there were significant differences at 8 and 12 months old, and in probe trials at 8 and 12 months old, the Tg+ rats spent significantly less time and covered less distance in the platform zone. Under acquisition of a fixed-consecutive number schedule at 3 months old, Tg- littermates demonstrated a longer latency to learning the response rule than Tg+ rats; while this might seem paradoxical, it is consistent with the role of overexpression of AßPP in learning. Histological analyses revealed activated astrocytes in brains of Tg+ rats but not Tg- littermates at 6 months old, and thioflavin-S positive staining in the hippocampus and cortex of 17-month old Tg+ rats but not Tg- littermates. Quantification of Aß load in the brain at 22 months indicated high levels of Aß38, Aß40, and Aß42 in the Tg+ rats. These data suggest this model might provide a valuable resource for AD research.

Reviewing child deaths - Learning from the American experience

Current systems for investigating child deaths in England, Wales and Northern Ireland have come under intense scrutiny in recent years and questions have been raised about the accuracy of child death investigations and resulting statistics. Research has highlighted the ways in which multidisciplinary input can contribute to investigative and review processes, a perspective which is further supported by recent UK policy developments. The experience of creating multidisciplinary child death review teams (CDRTs) in America highlights the potential benefits the introduction of a similar system might have. These benefits include improved multi-agency working and communication, more effective identification of suspicious cases, a decrease in inadequate death certification and a broader and more in-depth understanding of the causes of child deaths through the systematic collection and analysis of data. While a lack of funding, regional coordination and evaluation limit the impact of American CDRTs, the positive aspects of this process make it worthwhile, and timely, to consider how such a model might fit within our own context. Current policy developments such as the Home Office review of coroner services, the Children Bill and related Department for Education and Skills (DfES) work on developing screening groups demonstrate that strides have been made in respect of introducing a multidisciplinary process. Similarly, the development of local protocols for the investigation and/or review of child deaths in England, Wales and Northern Ireland highlights an increased focus on multidisciplinary processes. However, key issues from the American experience, such as the remit of CDRTs/screening panels, the need for national coordination and the importance of rigorous evaluation, can inform the development of a similar process in the UK. Copyright ©2005 John Wiley & Sons, Ltd.

The identification of p130cas-binding proteins and their role in cellular transformation

Adaptor proteins play an important role in signal transduction by regulating the establishment and maintenance of functionally important protein complexes. A recently described member of this group of proteins is p130cas (CAS), which contains numerous sequence motifs predicted to be involved in mediating protein-protein interactions. We propose that adaptor molecules like CAS may help determine the response of a cell to a particular signal by interacting with specific subsets of cellular proteins. To test this hypothesis, we have identified potential binding partners of CAS that may play a rote in cellular transformation by the oncoproteins v-SRC and/or v-CRK. We show that individual domains of CAS associate with specific subsets of proteins in vitro, and that many of these interactions are dependent on the state of tyrosine-phosphorylation of CAS. Sequences necessary for interacting with the focal adhesion kinase pp125FAK (FAK), v-SRC and v-CRK have been mapped to distinct regions of CAS. In addition, the identification of a number of putative CAS-binding partners that are present in crk-transformed cell extracts but undetectable in normal and src-transformed cell extracts supports a model in which unique protein complexes are formed in response to different signals.

The link between the learning organisation and curriculum innovation:A comparative study of public and private primary schools in Greece

This article examines the relationship between the learning organisation and the implementation of curriculum innovation within schools. It also compares the extent of innovative activity undertaken by schools in the public and the private sectors. A learning organisation is characterised by long-term goals, participatory decision-making processes, collaboration with external stakeholders, effective mechanisms for the internal communication of knowledge and information, and the use of rewards for its members. These characteristics are expected to promote curriculum innovation, once a number of control factors have been taken into account. The article reports on a study carried out in 197 Greek public and private primary schools in the 1999-2000 school year. Structured interviews with school principals were used as a method of data collection. According to the statistical results, the most important determinants of the innovative activity of a school are the extent of its collaboration with other organisations (i.e. openness to society), and the implementation of development programmes for teachers and parents (i.e. communication of knowledge and information). Contrary to expectations, the existence of long-term goals, the extent of shared decision-making, and the use of teacher rewards had no impact on curriculum innovation. The study also suggests that the private sector, as such, has an additional positive effect on the implementation of curriculum innovation, once a number of human, financial, material, and management resources have been controlled for. The study concludes by making recommendations for future research that would shed more light on unexpected outcomes and would help explore the causal link between variables in the research model.

Learning fluid prescription skills: why is it so challenging?

IIt is well recognised that medical students and junior doctors find fluid prescription a challenging topic. This study was designed to gain a greater understanding of the experiences that medical students face related to learning about fluid prescribing. Methods: A qualitative approach, using focus groups, was employed in this research. Final-year medical students in academic year 2011-12 at Queen's University Belfast were invited to participate during their 'Assistantship' placement in March 2012. Discussions in focus groups, consisting of between six and eight students, were recorded and transcribed verbatim. The research team, consisting of three separate investigators, conducted thematic analysis independently. A final consensus regarding emerging themes was reached by discussion within the whole research team. Medical students and junior doctors find fluid prescription a challenging topic Results: Five prominent themes emerged: 'Teaching experience: a disruptive variation'; 'Curricular disconnections'; 'The driving test: Theory-practice transformation'; 'Role modelling: which standard to aspire to?'; and finally 'Reconciling the perceived risk'. Discussion: This re search provided insights into medical students' opinions of the teaching practices and learning experiences related to fluid prescribing. The learning of prescribing skills is complex andcontextual. In the development of such skills, medical students are often exposed to conflicting educational experiences that challenge the novicelearner in making judgements on best prescribing practice. This study adds to the body of evidence that fluid prescription is a difficult topic, and has generated a number of multifaceted and strategic recommendations to potentially improve fluid prescription teaching.

Developing a best practice model for partnership practice between specialist palliative care and intellectual disability services: a mixed methods study

Background: The lack of access to good quality palliative care for people with intellectual disabilities is highlighted in the international literature. In response, more partnership practice in end-of-life care is proposed. 
Aim: This study aimed to develop a best practice model to guide and promote partnership practice between specialist palliative care and intellectual disability services. 
Design: A mixed methods research design involving two phases was used, underpinned by a conceptual model for partnership practice. 
Setting/participants: Phase 1 involved scoping end-of-life care to people with intellectual disability, based on self-completed questionnaires. In all, 47 of 66 (71.2%) services responded. In Phase 2, semi-structured interviews were undertaken with a purposive sample recruited of 30 health and social care professionals working in intellectual disability and palliative care services, who had provided palliative care to someone with intellectual disability. For both phases, data were collected from primary and secondary care in one region of the United Kingdom. 
Results: In Phase 1, examples of good practice were apparent. However, partnership practice was infrequent and unmet educational needs were identified. Four themes emerged from the interviews in Phase 2: challenges and issues in end-of-life care, sharing and learning, supporting and empowering and partnership in practice. 
Conclusion: Joint working and learning between intellectual disability and specialist palliative care were seen as key and fundamental. A framework for partnership practice between both services has been developed which could have international applicability and should be explored with other services in end-of-life care.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

Parental leave regulations and the persistence of the male breadwinner model: Using fuzzy-set ideal type analysis to assess gender equality in an enlarged Europe

his paper uses fuzzy-set ideal type analysis to assess the conformity of European leave regulations to four theoretical ideal typical divisions of labour: male breadwinner, caregiver parity, universal breadwinner and universal caregiver. In contrast to the majority of previous studies, the focus of this analysis is on the extent to which leave regulations promote gender equality in the family and the transformation of traditional gender roles. The results of this analysis demonstrate that European countries cluster into five models that only partly coincide with countries’ geographical proximity. Second, none of the countries considered constitutes a universal caregiver model, while the male breadwinner ideal continues to provide the normative reference point for parental leave regulations in a large number of European states. Finally, we witness a growing emphasis at the national and EU levels concerning the universal breadwinner ideal, which leaves gender inequality in unpaid work unproblematized.