Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.

Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this
ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

Rigorous Specification and Low-Latency Implementation of Technical Market Indicators

Technical market indicators are tools used by technical an- alysts to understand trends in trading markets. Technical (market) indicators are often calculated in real-time, as trading progresses. This paper presents a mathematically- founded framework for calculating technical indicators. Our framework consists of a domain specific language for the un- ambiguous specification of technical indicators, and a run- time system based on Click, for computing the indicators. We argue that our solution enhances the ease of program- ming due to aligning our domain-specific language to the mathematical description of technical indicators, and that it enables executing programs in kernel space for decreased latency, without exposing the system to users’ programming errors.

Fusion rules for merging uncertain information

In previous papers, we have presented a logic-based framework based on fusion rules for merging structured news reports. Structured news reports are XML documents, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume structured news reports do not require natural language processing. Fusion rules are a form of scripting language that define how structured news reports should be merged. The antecedent of a fusion rule is a call to investigate the information in the structured news reports and the background knowledge, and the consequent of a fusion rule is a formula specifying an action to be undertaken to form a merged report. It is expected that a set of fusion rules is defined for any given application. In this paper we extend the approach to handling probability values, degrees of beliefs, or necessity measures associated with textentries in the news reports. We present the formal definition for each of these types of uncertainty and explain how they can be handled using fusion rules. We also discuss the methods of detecting inconsistencies among sources.

Reconfigurable system-on-a-chip motion estimation architecture for multi-standard video coding

A new domain-specific, reconfigurable system-on-a-chip (SoC) architecture is proposed for video motion estimation. This has been designed to cover most of the common block-based video coding standards, including MPEG-2, MPEG-4, H.264, WMV-9 and AVS. The architecture exhibits simple control, high throughput and relatively low hardware cost when compared with existing circuits. It can also easily handle flexible search ranges without any increase in silicon area and can be configured prior to the start of the motion estimation process for a specific standard. The computational rates achieved make the circuit suitable for high-end video processing applications, such as HDTV. Silicon design studies indicate that circuits based on this approach incur only a relatively small penalty in terms of power dissipation and silicon area when compared with implementations for specific standards. Indeed, the cost/performance achieved exceeds that of existing but specific solutions and greatly exceeds that of general purpose field programmable gate array (FPGA) designs.

Folkbiology doesn’t come from Folkpsychology: evidence from Yukatek Maya in cross-cultural perspective

Nearly all psychological research on basic cognitive processes of category formation and reasoning uses sample populations associated with large research institutions in technologically-advanced societies. Lopsided attention to a select participant pool risks biasing interpretation, no matter how large the sample or how statistically reliable the results. The experiments in this article address this limitation. Earlier research with urban-USA children suggests that biological concepts are (1) thoroughly enmeshed with their notions of naive psychology, and (2) strikingly human-centered. Thus, if children are to develop a causally appropriate model of biology, in which humans are seen as simply one animal among many, they must undergo fundamental conceptual change. Such change supposedly occurs between 7 and 10 years of age, when the human-centered view is discarded. The experiments reported here with Yukatek Maya speakers challenge the empirical generality and theoretical importance of these claims. Part 1 shows that young Maya children do not anthropocentrically interpret the biological world. The anthropocentric bias of American children appears to owe to a lack of cultural familiarity with non-human biological kinds, not to initial causal understanding of folkbiology as such. Part 2 shows that by age of 4-5 (the earliest age tested in this regard) Yukatek Maya children employ a concept of innate species potential or underlying essence much as urban American children seem to, namely, as an inferential framework for understanding the affiliation of an organism to a biological species, and for projecting known and unknown biological properties to organisms in the face of uncertainty. Together, these experiments indicate that folkpsychology cannot be the initial source of folkbiology. They also underscore the possibility of a species-wide and domain-specific basis for acquiring knowledge about the living world that is constrained and modified but not caused or created by prior nonbiological thinking and subsequent cultural experience.

Self-esteem and self-efficacy: Associations with alcohol consumption in a sample of adolescents in Northern Ireland

Cross-sectional and longitudinal studies have reported equivocal findings regarding the association between self-esteem, self-efficacy and adolescent alcohol use. Data were collected from a sample of 11-16-year olds in Northern Ireland (n = 4088) over two consecutive academic years measuring global self-esteem, academic, social and emotional self-efficacy and alcohol involvement. Results showed a domain-specific association between alcohol involvement and self-efficacy, with more problematic alcohol use associated with higher social self-efficacy but lower emotional and academic self-efficacy. Additionally, regression analyses revealed that all self-concept measures significantly predicted drinking group membership. The results are discussed in terms of reported drinking behaviour, interventions with adolescent groups and general development.

Targeting heterogeneous architectures via macro data flow

We propose a data flow based run time system as an efficient tool for supporting execution of parallel code on heterogeneous architectures hosting both multicore CPUs and GPUs. We discuss how the proposed run time system may be the target of both structured parallel applications developed using algorithmic skeletons/parallel design patterns and also more "domain specific" programming models. Experimental results demonstrating the feasibility of the approach are presented. © 2012 World Scientific Publishing Company.

The link between logic, mathematics and imagination: evidence from children with developmental dyscalculia and mathematically gifted children

This study examined performance on transitive inference problems in children with developmental dyscalculia (DD), typically developing controls matched on IQ, working memory and reading skills, and in children with outstanding mathematical abilities. Whereas mainstream approaches currently consider DD as a domain-specific deficit, we hypothesized that the development of mathematical skills is closely related to the development of logical abilities, a domain-general skill. In particular, we expected a close link between mathematical skills and the ability to reason independently of one's beliefs. Our results showed that this was indeed the case, with children with DD performing more poorly than controls, and high maths ability children showing outstanding skills in logical reasoning about belief-laden problems. Nevertheless, all groups performed poorly on structurally equivalent problems with belief-neutral content. This is in line with suggestions that abstract reasoning skills (i.e. the ability to reason about content without real-life referents) develops later than the ability to reason about belief-inconsistent fantasy content.A video abstract of this article can be viewed at http://www.youtube.com/watch?v=90DWY3O4xx8.

Multi-standard sub-pixel interpolation architecture for video motion estimation

A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.

Support for the Multidimensional Adolescent Stress Questionnaire in a Sample of Adolescents in the United Kingdom

Adolescence is a time of physical, social and emotional development, and this development can be accompanied by feelings of stress. The Adolescent Stress Questionnaire is a 56-item scale measuring stress in 10 domains. Developed in Australia, the scale has been translated, and its reliability and validity have been tested in a number of countries across Europe, where the 10-factor, 56-item version of the scale has received little support. The present study tested the factor structure, construct validity and reliability in a sample (n=610) of adolescents in the United Kingdom. Support was found for the 10-factor, 56-item version of the scale, and correlations with self-concept measures, sex scores on stress factors and Cronbach's α-values, suggesting that the scale may be a viable assessment tool for adolescent stress. Results for alcohol-specific analyses support the domain-specific nature of the scale. Future work may seek to investigate the stability of age-specific stress domains (e.g. the stress of Emerging Adult Responsibility) in samples that include younger adolescents. 

Behavioral Model Generation from Use Cases Based on Ontology Mapping and GRASP Patterns

This paper contributes a new approach for developing UML software designs from Natural Language (NL), making use of a meta-domain oriented ontology, well established software design principles and Natural Language Processing (NLP) tools. In the approach described here, banks of grammatical rules are used to assign event flows from essential use cases. A domain specific ontology is also constructed, permitting semantic mapping between the NL input and the modeled domain. Rules based on the widely-used General Responsibility Assignment Software Principles (GRASP) are then applied to derive behavioral models.

Design patterns percolating to parallel programming framework implementation

Structured parallel programming is recognised as a viable and effective means of tackling parallel programming problems. Recently, a set of simple and powerful parallel building blocks RISC pb²l) has been proposed to support modelling and implementation of parallel frameworks. In this work we demonstrate how that same parallel building block set may be used to model both general purpose parallel programming abstractions, not usually listed in classical skeleton sets, and more specialized domain specific parallel patterns. We show how an implementation of RISC pb² l can be realised via the FastFlow framework and present experimental evidence of the feasibility and efficiency of the approach.

Knowledge Management Techniques to Augment Textual CBR (PhD Thesis)

The past decade had witnessed an unprecedented growth in the amount of available digital content, and its volume is expected to continue to grow the next few years. Unstructured text data generated from web and enterprise sources form a large fraction of such content. Many of these contain large volumes of reusable data such as solutions to frequently occurring problems, and general know-how that may be reused in appropriate contexts. In this work, we address issues around leveraging unstructured text data from sources as diverse as the web and the enterprise within the Case-based Reasoning framework. Case-based Reasoning (CBR) provides a framework and methodology for systematic reuse of historical knowledge that is available in the form of problemsolution
pairs, in solving new problems. Here, we consider possibilities of enhancing Textual CBR systems under three main themes: procurement, maintenance and retrieval. We adapt and build upon the stateof-the-art techniques from data mining and natural language processing in addressing various challenges therein. Under procurement, we investigate the problem of extracting cases (i.e., problem-solution pairs) from data sources such as incident/experience
reports. We develop case-base maintenance methods specifically tuned to text targeted towards retaining solutions such that the utility of the filtered case base in solving new problems is maximized. Further, we address the problem of query suggestions for textual case-bases and show that exploiting the problem-solution partition can enhance retrieval effectiveness by prioritizing more useful query suggestions. Additionally, we illustrate interpretable clustering as a tool to drill-down to domain specific text collections (since CBR systems are usually very domain specific) and develop techniques for improved similarity assessment in social media sources such as microblogs. Through extensive empirical evaluations, we illustrate the improvements that we are able to
achieve over the state-of-the-art methods for the respective tasks.

Home and Workplace Built Environment Supports for Physical Activity

BACKGROUND: Physical inactivity has been associated with obesity and related chronic diseases. Understanding built environment (BE) influences on specific domains of physical activity (PA) around homes and workplaces is important for public health interventions to increase population PA.

PURPOSE: To examine the association of home and workplace BE features with PA occurring across specific life domains (work, leisure, and travel).

METHODS: Between 2012 and 2013, telephone interviews were conducted with participants in four Missouri metropolitan areas. Questions included sociodemographic characteristics, home and workplace supports for PA, and dietary behaviors. Data analysis was conducted in 2013; logistic regression was used to examine associations between BE features and domain-specific PA.

RESULTS: In home neighborhoods, seven of 12 BE features (availability of fruits and vegetables, presence of shops and stores, bike facilities, recreation facilities, crime rate, seeing others active, and interesting things) were associated with leisure PA. The global average score of home neighborhood BE features was associated with greater odds of travel PA (AOR=1.99, 95% CI=1.46, 2.72); leisure PA (AOR=1.84, 95% CI=1.44, 2.34); and total PA (AOR=1.41, 95% CI=1.04, 1.92). Associations between workplace neighborhoods' BE features and workplace PA were small but in the expected direction.

CONCLUSIONS: This study offers empirical evidence on BE supports for domain-specific PA. Findings suggest that diverse, attractive, and walkable neighborhoods around workplaces support walking, bicycling, and use of public transit. Public health practitioners, researchers, and worksite leaders could benefit by utilizing worksite domains and measures from this study for future BE assessments.