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The paper proposes a high-level conceptual and technological approach to manage the ensemble-based simulation, taking into account changing states of both simulated system and system of models. The approach includes systematization of ensemble-based modeling and simulation techniques, analysis of simulation results, quality assessments, and detailed analysis of ensemble management procedures using classification operators. The technological basis for such an approach includes ensemble-based simulation techniques using domain-specific software combined within a composite application; data science approaches for analysis of available datasets (simulation data, observations, situation assessments, etc.). Within this work, a set of case studies is addressed to examine the opportunities provided by the developed approach considering ensemble-based simulation of storm surges for flood prediction in St. Petersburg, Russia as an example. [ABSTRACT FROM AUTHOR]

Non-trivial software systems are written using multiple programming languages. While the logic of a system is encoded using one or several general-purpose languages, more specialized parts of the systems are realized using domain-specific languages for aspects such as the user interface, configuration mechanisms, querying of databases, or support for internationalization. To bind all of these different parts together, the artifacts in individual languages are connected by using cross-language links which address artifacts across language boundaries. Many different ways for specifying and using such links have been conceived, and developers have to adhere to the concrete rules mandated by the runtime, framework or library which later performs the link resolution. In this paper, we present a taxonomy of the mechanisms of encoding cross-language linking in well-known open source frameworks from a developers perspective, which shows the choices that have been made and the options available in practice. We describe the process we followed, which is based in part on a survey of language combinations on GitHub and a survey of professional developers, list the dimensions and characteristics of our taxonomy in full, show the classifications of 22 frameworks and mechanisms, four of which are described in detail, and discuss the impact of the choices on application developers. [ABSTRACT FROM AUTHOR]

GoodRelations has existed since 2008 to aid businesses in describing their products and services. It provides a variety of definitions and terminology useful for improving a company's online retail presence. In this paper, we go beyond using GoodRelations simply for structured data in web pages, and combine it with a domain-specific ontology. The goals of the work are threefold, to define a set of retail-oriented Ontology Design Patterns (ODPs) that makes it easier to understand and reuse GoodRelations, to show how ontologies can be integrated with GoodRelations, and to illustrate several retail applications enabled by the use of ontologies. The paper presents a climbing gear ontology which is integrated with GoodRelations to define a set of retail ODPs, and enable creating customer- and business-oriented solutions that could be used in multiple scenarios. [ABSTRACT FROM AUTHOR]

In this study, an implicit finite-difference code for nonlinear consolidation and secondary compression was developed and implemented in a publicly available JavaScriptWeb application. The rate of secondary compression was defined based on the distance in e-log10(σ'v) space between a current point and a corresponding point on a reference secondary compression line (RSCL). Modeling secondary compression in this manner enables simultaneous occurrence of primary consolidation and secondary compression. The finitedifference code was first verified by comparison with three benchmarks. The influence of secondary compression on settlement versus time was then studied and found to be important for thick and/or low-permeability layers for which primary consolidation requires significant time. Overconsolidated soil was observed to result in an apparent increase in Cα with time, which was also observed in experimental data. Finally, secondary compression was found to be capable of generating excess pore pressure in soils with impeded drainage boundaries. [ABSTRACT FROM AUTHOR]

Programming frameworks are an accepted fixture in the object-oriented world, motivated by the need for code reuse, developer guidance and restriction. A new trend is emerging where frameworks require domain experts to provide declarations using a domain-specific language, influencing the structure and behaviour of the resulting application. These mechanisms address concerns such as user privacy. Although many popular open platforms such as Android are based on declaration-driven frameworks, current implementations provide ad hoc and narrow solutions to concerns raised by their openness to non-certified developers. Most widely used frameworks fail to address serious privacy leaks and provide the user with little insight into application behaviour. To address these shortcomings, we show that declaration-driven frameworks can limit privacy leaks, as well as guide developers, independently from the underlying programming paradigm. To do so, we identify concepts that underlie declaration-driven frameworks and apply them systematically to an object-oriented language, Java and a dynamic functional language, Racket. The resulting programming framework generators are used to develop a prototype mobile application, illustrating how we mitigate a common class of privacy leaks. Finally, we explore the possible design choices and propose development principles for developing domain-specific language compilers to produce frameworks, applicable across a spectrum of programming paradigms. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Despite the wide range of existing tool support, constructing a design environment for a complex domain-specific language (DSL) is still a tedious task as the large number of derived features and well-formedness constraints complementing the domain metamodel necessitate special handling. Such derived features and constraints are frequently defined by declarative techniques (such graph patterns or OCL invariants). However, for complex domains, derived features and constraints can easily be formalized incorrectly resulting in inconsistent, incomplete or ambiguous DSL specifications. To detect such issues, we propose an automated mapping of EMF metamodels enriched with derived features and well-formedness constraints captured as graph queries in EMF-IncQuery or (a subset of) OCL invariants into an effectively propositional fragment of first-order logic which can be efficiently analyzed by back-end reasoners. On the conceptual level, the main added value of our encoding is (1) to transform graph patterns of the EMF-IncQuery framework into FOL and (2) to introduce approximations for complex language features (e.g., transitive closure or multiplicities) which are not expressible in FOL. On the practical level, we identify and address relevant challenges and scenarios for systematically validating DSL specifications. Our approach is supported by a tool, and it will be illustrated on analyzing a DSL in the avionics domain. We also present initial performance experiments for the validation using Z3 and Alloy as back-end reasoners. [ABSTRACT FROM AUTHOR]

Domain-specific accelerators (DSAs), which sacrifice programmability for efficiency, are a reaction to the waning benefits of device scaling. This article demonstrates that there are commonalities between DSAs that can be exploited with programmable mechanisms. The goals are to create a programmable architecture that can match the benefits of a DSA and to create a platform for future accelerator investigations. [ABSTRACT FROM AUTHOR]

Reusing the data from healthcare information systems can effectively facilitate clinical trials (CTs). How to select candidate patients eligible for CT recruitment criteria is a central task. Related work either depends on DBA (database administrator) to convert the recruitment criteria to native SQL queries or involves the data mapping between a standard ontology/information model and individual data source schema. This paper proposes an alternative computer-aided CT recruitment paradigm, based on syntax translation between different DSLs (domain-specific languages). In this paradigm, the CT recruitment criteria are first formally represented as production rules. The referenced rule variables are all from the underlying database schema. Then the production rule is translated to an intermediate query-oriented DSL (e.g., LINQ). Finally, the intermediate DSL is directly mapped to native database queries (e.g., SQL) automated by ORM (object-relational mapping). [ABSTRACT FROM AUTHOR]

We describe NIMBLE, a system for programming statistical algorithms for general model structures within R. NIMBLE is designed to meet three challenges: flexible model specification, a language for programming algorithms that can use different models, and a balance between high-level programmability and execution efficiency. For model specification, NIMBLE extends the BUGS language and creates model objects, which can manipulate variables, calculate log probability values, generate simulations, and query the relationships among variables. For algorithm programming, NIMBLE provides functions that operate with model objects using two stages of evaluation. The first stage allows specialization of a function to a particular model and/or nodes, such as creating a Metropolis-Hastings sampler for a particular block of nodes. The second stage allows repeated execution of computations using the results of the first stage. To achieve efficient second-stage computation, NIMBLE compiles models and functions via C++, using the Eigen library for linear algebra, and provides the user with an interface to compiled objects. The NIMBLE language represents a compilable domain-specific language (DSL) embedded within R. This article provides an overview of the design and rationale for NIMBLE along with illustrative examples including importance sampling, Markov chain Monte Carlo (MCMC) and Monte Carlo expectation maximization (MCEM). Supplementary materials for this article are available online. [ABSTRACT FROM AUTHOR]

Just as people vary in their perceptual expertise with a given domain, they also vary in their abilities to imagine objects. Visual imagery and perception share common mechanisms. However, it is unclear whether domain-specific expertise is relevant to visual imagery. Although the vividness of visual imagery is typically measured as a domain-general construct, a component of this vividness may be domain-specific. For example, individuals who have gained perceptual expertise with a specific domain might experience clearer mental images within this domain. Here we investigated whether perceptual expertise for cars relates to visual imagery vividness in the same domain, by assessing the correlations between a widely used domain-general measure of visual imagery vividness (the Vividness of Visual Imagery Questionnaire; Marks in British Journal of Psychology, 64, 17-24, 1973), a new measure of visual imagery vividness specific to cars, and behavioral tests of car expertise. We found that domain-specific imagery relates most strongly to general imagery vividness and less strongly to self-reported expertise, while it does not relate to perceptual or semantic expertise. [ABSTRACT FROM AUTHOR]

Domain-specific design patterns provide developers with proven solutions to common design problems that arise, particularly in a target application domain, facilitating them to produce quality designs in the domain contexts. However, research in this area is not mature and there are no techniques to support their detection. Towards this end, we propose a methodology which, when applied on a collection of websites in a specific domain, facilitates the automated identification of domain-specific design patterns. The methodology automatically extracts the conceptual models of the websites, which are subsequently analyzed in terms of all of the reusable design fragments used in them for supporting common domain functionalities. At the conceptual level, we consider these fragments as recurrent patterns consisting of a configuration of front-end interface components that interrelate each other and interact with end-users to support certain functionality. By performing a pattern-based analysis of the models, we locate the occurrences of all the recurrent patterns in the various website designs which are then evaluated towards their consistent use. The detected patterns can be used as building blocks in future designs, assisting developers to produce consistent and quality designs in the target domain. To support our case, we present a case study for the educational domain. [ABSTRACT FROM AUTHOR]

WebML is a domain-specific language used to design complex data-intensive Web applications at a conceptual level. As WebML was devised to support design tasks, the need to define a visual notation for the language was identified from the very beginning. Each WebML element is consequently associated with a separate graphical symbol which was mainly defined with the idea of providing simple and expressive modelling artefacts rather than by adopting a rigorous scientific approach. As a result, the graphical models defined with WebML may sometimes prevent proper communication from taking place between the various stakeholders. In fact, this is a common issue for most of the existing model-based proposals that have emerged during the last few years under the umbrella of model-driven engineering. In order to illustrate this issue and foster in using a scientific basis to design, evaluate, improve and compare visual notations, this paper analyses WebML according to a set of solid principles, based on the theoretical and empirical evidence concerning the cognitive effectiveness of visual notations. As a result, we have identified a set of possible improvements, some of which have been verified by an empirical study. Furthermore, a number of findings, experiences and lessons learnt on the assessment of visual notations are presented. [ABSTRACT FROM AUTHOR]

Enterprise models assist the governance and transformation of organizations through the specification, communication and analysis of strategy, goals, processes, information, along with the underlying application and technological infrastructure. Such models cross-cut different concerns and are often conceptualized using domain-specific modelling languages. This paper explores the application of graph-based semantic techniques to specify, integrate and analyse multiple, heterogeneous enterprise models. In particular, the proposal described in this paper (1) specifies enterprise models as ontological schemas, (2) uses transformation mapping functions to integrate the ontological schemas and (3) analyses the integrated schemas with graph querying and logical inference. The proposal is evaluated through a scenario that integrates three distinct enterprise modelling languages: the business model canvas, e3value, and the business layer of the ArchiMate language. The results show, on the one hand, that the graph-based approach is able to handle the specification, integration and analysis of enterprise models represented with different modelling languages and, on the other, that the integration challenge resides in defining appropriate mapping functions between the schemas. [ABSTRACT FROM AUTHOR]

The discrete time 'bomber problem' has been one of the longest standing open problems in operations research. In particular, the validity of one of the natural monotonicity conjectures-known as property (B)-has been an unresolved issue since 1968. In this paper we report 41 counterexamples to property (B) of this problem. We have found them by computing the exact solutions for nearly one million pairs of parameter values utilizing the GNU multiple precision arithmetic library. All our counterexamples can readily be verified using a simple Mathematica program included in this paper. [ABSTRACT FROM AUTHOR]

In this paper, an automatic generation of domain-specific stopwords from a large labeled corpus is proposed. In the majority of text mining tasks, stopwords are removed according to a standard stopword list and/or using high and low document frequencies. In this paper, a new approach for stopword extraction, based on the notion of backward filter-level performance and data sparsity index, is proposed. First, based on the proposed model to evaluate the extracted stopwords, we examine high document frequency filtering for stopword reduction. Secondly, a new algorithm for building general and domain-specific stopword lists is proposed. For the method, it is assumed that a set of candidate stopwords must have a minimum information content and prediction capacity that is measured by the performance of a classifier. We show that to avoid obtaining the classifier performance, it can be estimated by the sparsity of the training dataset. Moreover, it is confirmed that even if a given term ranking measure can perform well for the feature selection, the measure is not necessarily efficient for selecting poor features (stopwords). According to the comparative study, the newly devised approach offers more promising results that guarantee a minimum information loss by filtering out most stopwords. [ABSTRACT FROM AUTHOR]

Usage-based (UB) accounts conceive of language learning as continuous, locally contingent construction learning, i.e., a lifelong process of developing and honing the repertoire of constructional patterns geared to the optimization of a language user’s communicative ability across a wide range of language domains. The continuous nature of the process entails that a full UB model needs to account for not only the dynamics of language learning at early stages of acquisition, but also the functionally motivated adaptations of the language system at more advanced levels of proficiency. We present a design based on naturalistic second language (L2) written productions that sets out to reconstruct the states of constructional knowledge of advanced L2 learners through the statistical analysis of their productions. Irrespective of theoretical framing, the study provides foundational data relevant for any property theory of language learning, i.e., any theory that is concerned with the nature of the language system to be acquired, which logically precedes a transition theory of the developmental processes of L2 acquisition. [ABSTRACT FROM AUTHOR]

Agent-based models (ABMs) have shown themselves to be very suitable for examining complex phenomena. Their rise in popularity and multi-disciplinary interest has spurred many researchers to seek more efficient algorithms and methodologies, such as parameter optimisation, interaction redundancy reduction, model induction and meta-modelling. Some of these efforts are directed towards reducing the difficulty associated with them, which has limited the wider adoption of ABM. Several Domain-specific languages (DSLs) have been developed, many of which ease the difficulty faced by programmers from disciplines unrelated to computer science. Aside from the need of knowledge in programming, some researchers have also expressed a need to model larger systems. These can easily become too computationally expensive, and more difficult to build and manage. In this work, we propose a simple extensible DSL which performs behaviour generation using domain-specific knowledge, whilst avoiding run-time interpretation and abstraction penalties. This is done using a simple evolutionary optimiser, which operates directly on program syntax trees, computing recombinations. We allow the user to explore uncertainty and discover models in a guided manner; as opposed to tedious trial-and-error. Our DSL makes use of the Multi-Stage Programming paradigm within Terra, in order to just-in-time compile generated programs at run-time, as well as allowing the optimiser to modify program syntax trees. The goal of the optimiser is to reduce uncertain syntax constructs to concrete ones while exploring the search space of a given objective function. This results in a guided modelling language with high performance and extensibility. We discuss the implementation of this language, with its compiler architecture, as well as the incorporation of the evolutionary optimiser, and we demonstrate the use of this approach in solving the Santa Fe Ant Trail problem. [ABSTRACT FROM AUTHOR]

Cell phone cameras have small apertures, which limits the number of photons they can gather, leading to noisy images in low light. They also have small sensor pixels, which limits the number of electrons each pixel can store, leading to limited dynamic range. We describe a computational photography pipeline that captures, aligns, and merges a burst of frames to reduce noise and increase dynamic range. Our system has several key features that help make it robust and efficient. First, we do not use bracketed exposures. Instead, we capture frames of constant exposure, which makes alignment more robust, and we set this exposure low enough to avoid blowing out highlights. The resulting merged image has clean shadows and high bit depth, allowing us to apply standard HDR tone mapping methods. Second, we begin from Bayer raw frames rather than the demosaicked RGB (or YUV) frames produced by hardware Image Signal Processors (ISPs) common on mobile platforms. This gives us more bits per pixel and allows us to circumvent the ISP's unwanted tone mapping and spatial denoising. Third, we use a novel FFT-based alignment algorithm and a hybrid 2D/3D Wiener filter to denoise and merge the frames in a burst. Our implementation is built atop Android's Camera2 API, which provides per-frame camera control and access to raw imagery, and is written in the Halide domain-specific language (DSL). It runs in 4 seconds on device (for a 12 Mpix image), requires no user intervention, and ships on several mass-produced cell phones. [ABSTRACT FROM AUTHOR]

Most Domain-Specific Metamodeling Languages (DSMML) use informal method to define their semantics, so it is difficult to precisely and automatically analyze characteristics of metamodels built based on DSMML. In response, based on formalization of DSMML called XMML developed by us, the paper proposes an approach for automatically verifying metamodels consistency by an automatic mapping mechanism to automatically translate metamodels to the corresponding first-order logic system. Firstly, we briefly present our approach for formalizing XMML and its metamodels, and then, we establish an automatic mapping mechanism for formalizing metamodels, finally, we develop an automatic mapping tool for formalizing metamodels and perform relevant experiments to validate our method. [ABSTRACT FROM AUTHOR]

Rapid development of smart devices has lead people to be able to read books through their devices anytime and anywhere. Even though its popularity, e-books have ingrained disadvantages such as: (1) It does not have an expandable scheme that allows readers to add multimedia contents or their emotional expressions to books. (2) It is not easy to add multimedia resources as an author. (3) Due to the variety of resolutions on devices, the current ebook format tends to be uncomfortable for readers. The user constantly has to zoom in by pinching the screen when reading on a small device. (4) It is not easy to navigate contents within an e-book because of the absence of an e-book linking feature. To tackle the above mentioned problems, we design and use an external domain-specific language (DSL) within our research. We propose a collaborative social tagging framework for e-books. The goals of this paper are (1) to define a model of an evolvable social resources taggable book (modeling of collaborative e-book), (2) to make readers read rich content e-book easily regardless of their type of devices as well as screen size. (Responsiveness), and (3) to provide e-book resources with the Representational State Transfer (RESTful) address style by which other systems can identify the self-descriptive resources of an e-books (interoperability). The experimental results show that e-book featured social tagging makes readers more interested in reading e-books rather than plain e-books. Further work includes user experience (UX) improvement, and a visual DSL approach with which the authors could write books easier. [ABSTRACT FROM AUTHOR]

High-level synthesis (HLS) is increasingly popular for the design of high-performance and energy-efficient heterogeneous systems, shortening time-to-market and addressing today’s system complexity. HLS allows designers to work at a higher-level of abstraction by using a software program to specify the hardware functionality. Additionally, HLS is particularly interesting for designing field-programmable gate array circuits, where hardware implementations can be easily refined and replaced in the target device. Recent years have seen much activity in the HLS research community, with a plethora of HLS tool offerings, from both industry and academia. All these tools may have different input languages, perform different internal optimizations, and produce results of different quality, even for the very same input description. Hence, it is challenging to compare their performance and understand which is the best for the hardware to be implemented. We present a comprehensive analysis of recent HLS tools, as well as overview the areas of active interest in the HLS research community. We also present a first-published methodology to evaluate different HLS tools. We use our methodology to compare one commercial and three academic tools on a common set of C benchmarks, aiming at performing an in-depth evaluation in terms of performance and the use of resources. [ABSTRACT FROM AUTHOR]

Model Driven Development (MDD) witnessed a boom both in research and practical applications starting from 2001. Its main innovative idea was the model transformation languages as a real support for MDD. A couple of years ago MDD survived a deep crisis due to disillusionment by practitioners in support for it. However, recently it got a revival in the form of Domain Specific Languages, this again stimulated the research and usage of transformation languages. One of the obstacles for MDD adoption in industry has been the reluctance of practitioners to learn a new language. This paper offers a new approach how the well-known extension LINQ of the popular C# language can be used for defining model transformations. Especially the functional style supported by LINQ is promoted, which has not been widely used in the existing transformation languages. [ABSTRACT FROM AUTHOR]

This paper presents SPOON, a library for the analysis and transformation of Java source code. SPOON enables Java developers to write a large range of domain-specific analyses and transformations in an easy and concise manner. SPOON analyses and transformations are written in plain Java. With SPOON, developers do not need to dive into parsing, to hack a compiler infrastructure, or to master a new formalism. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Programming languages grow over time that requires frequent changes in language manipulations such as compilation, interpretation, and analysis. Because the very first step of most language manipulations is parsing, whether parsing can adapt to changes easily, quickly, and correctly, it affects the scalability of language manipulations. Even though various parsing techniques have been well studied theoretically, their practical experiences in scalable frameworks have not been available. In this paper, we present our experiences with parsing in scalable frameworks. We first describe our trials and errors using various parsing techniques in developing parsers for the Fortress programming language. Because Fortress was a scientific language under development, its mathematical and growable syntax introduced new challenges in parsing. We summarize the lessons learned from parsing Fortress, and we share our experience of applying the lessons to parsing the JavaScript programming language. While JavaScript is one of the most widely used languages, JavaScript itself and its diverse variants keep extending its syntax, and the extremely dynamic features of JavaScript also add new challenges in parsing. Using automatic generation tools and methods like staged parsing and automatic extraction and testing of examples in language specifications, our methodology for scalable parsing has shown to be very effective in practice. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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Two new methods are proposed for an unsupervised adaptation of a language model (LM) with a single sentence for automatic transcription tasks. At the training phase, training documents are clustered by a method known as Latent Dirichlet allocation (LDA), and then a domain-specific LM is trained for each cluster. At the test phase, an adapted LM is presented as a linear mixture of the now trained domain-specific LMs. Unlike previous adaptation methods, the proposed methods fully utilize a trained LDA model for the estimation of weight values, which are then to be assigned to the now trained domainspecific LMs; therefore, the clustering and weightestimation algorithms of the trained LDA model are reliable. For the continuous speech recognition benchmark tests, the proposed methods outperform other unsupervised LM adaptation methods based on latent semantic analysis, non-negative matrix factorization, and LDA with n-gram counting. [ABSTRACT FROM AUTHOR]

In software testing process, test data generation represents an important step for high quality software, even for mobile devices. As proposed in previous works, a potential source for random data generation is represented by the UI layout files that are used for almost all mobile platforms (Android, iOS, Windows Phone/Mobile). This paper continues the previous work and presents a test data generation system based on Android layout files. The test data generator uses DSL files as input and generates test data that conform to several testing principles. The generated test data could be stored in XML files or any format required by the testing frameworks. [ABSTRACT FROM AUTHOR]

Biomedical modelling that is mathematically described by ordinary differential equations (ODEs) is often one of the most computationally intensive parts of simulations. With high inherent parallelism, hardware acceleration based on field programmable gate array has great potential to increase the computational performance of the ODE model integration while being very power efficient. ODE-based Domain-specific Synthesis Tool is a tool we proposed previously to automatically generate the complete hardware/software co-design framework for computing biomedical models based on CellML. Although it provides remarkable performance improvement and high energy efficiency compared with CPUs and GPUs, there is still a great potential for optimisation. In this paper, we investigate a set of optimisation strategies including compiler optimisation, resource fitting and balancing, and multiple pipelines. They all have in common that they can be performed automatically and hence can be integrated in our domain-specific high level synthesis tool. We evaluate the optimised hardware accelerator modules generated by ODE-based Domain-specific Synthesis Tool on real hardware based on their resource usage, processing speed and power consumption. The results are compared with single threaded and multi-core CPUs with/without Streaming SIMD Extension (SSE) optimisation and a graphics card. The results show that the proposed optimisation strategies provide significant performance improvement and result in even more energy-efficient hardware accelerator modules. Furthermore, the resources of the target field programmable gate array device can be more efficiently utilised in order to fit larger biomedical models than before. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A domain specific language (DSL) focuses on the essential concepts in a specific problem domain, and abstracts from low-level implementation details. The development of DSLs usually centers around the meta-model, grammar and code generator, possibly extended with transformations to analysis models. Typically, little attention is given to the formal semantics of the language, whereas this is essential for reasoning about DSL models, and for assessing the correctness of the generated code and analysis models. We argue that the semantics of a DSL should be defined explicitly and independently of any code generator, to avoid all kinds of complexities from low-level implementation details. As the generated analysis models must reflect some of these implementation details, we propose to formalize them separately. To assess the correctness and consistency of the generated code and analysis models in a practical way, we use conformance testing. We extensively illustrate this general approach using specific formalizations for an industrial DSL on collision prevention. We do not aim for a generic semantic model for any DSL, but this specific DSL indicates the potential of a modular semantics to facilitate reuse among DSLs. [ABSTRACT FROM AUTHOR]

The same data can be visualized using various visual styles that each is suitable for specific requirements, e.g., 3D geodata visualized using photorealistic, cartographic, or illustrative styles. In contrast to feature-based styling, image-based styling performed in image space at image resolution allows decoupling styling from image generation and output-sensitive, expressive styling. However, leveraging image-based styling is still impeded. No previous approach allows specifying image-based styling expressively with an extensive inventory of composable operators, while providing styling functionality in a service-oriented, interoperable manner. In this article, we present an interactive system for specifying and providing the functionality of image-based styling. As key characteristics, it separates concerns of styling from image generation and facilitates specifying styling as algebraic compositions of high-level operators using a unified 3D model representation. We propose a generalized visualization model, an image-based styling algebra, two declarative DSLs, an operator taxonomy, an operational model, and a standards-based service interface. The approach facilitates expressive specifications of image-based styling for design, description, and analysis and leveraging the functionality of image-based styling in a service-oriented, interoperable, reusable, and composable manner. [ABSTRACT FROM AUTHOR]

Supervised learning methods require sufficient labeled examples to learn a good model for classification or regression. However, available labeled data are insufficient in many applications. Active learning (AL) and domain adaptation (DA) are two strategies to minimize the required amount of labeled data for model training. AL requires the domain expert to label a small number of highly informative examples to facilitate classification, while DA involves tuning the source domain knowledge for classification on the target domain. In this paper, we demonstrate how AL can efficiently minimize the required amount of labeled data for DA. Since the source and target domains usually have different distributions, it is possible that the domain expert may not have sufficient knowledge to answer each query correctly. We exploit our active DA framework to handle incorrect labels provided by domain experts. Experiments with multimedia data demonstrate the efficiency of our proposed framework for active DA with noisy labels. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to understand clinicians' and parents' perceptions of communication within consultations for respiratory tract infections (RTI) in children and what influence clinician communication had on parents' understanding of antibiotic treatment.Methods: We video recorded 60 primary care consultations for children aged 3 months to 12 years who presented with RTI and cough in 6 primary care practices in England. We then used purposive sampling to select 27 parents and 13 clinicians for semistructured video-elicitation interviews. The videos were used as prompts to investigate participants' understanding and views of communication within the consultations. We analyzed the interview data thematically.Results: While clinicians commonly told parents that antibiotics are not effective against viruses, this did not have much impact on parents' beliefs about the need to consult or on their expectations concerning antibiotics. Parents believed that antibiotics were needed to treat more severe illnesses, a belief that was supported by the way clinicians accompanied viral diagnoses with problem-minimizing language and antibiotic prescriptions with more problem-oriented language. Antibiotic prescriptions tended to confirm parents' beliefs about what indicated illness severity, which often took into account the wider impact on a child's life. While parents understood antimicrobial resistance poorly, most held beliefs that supported reduced antibiotic prescribing. A minority attributed it to resource rationing, however.Conclusions: Clinician communication and prescribing behavior confirm parents' beliefs that antibiotics are needed to treat more severe illnesses. Interventions to reduce antibiotic expectations need to address communication within the consultation, prescribing behavior, and lay beliefs. [ABSTRACT FROM AUTHOR]

Background: The Biomedical Research Integrated Domain Group (BRIDG) model is a formal domain analysis model for protocol-driven biomedical research, and serves as a semantic foundation for application and message development in the standards developing organizations (SDOs). The increasing sophistication and complexity of the BRIDG model requires new approaches to the management and utilization of the underlying semantics to harmonize domain-specific standards. The objective of this study is to develop and evaluate a Semantic Web-based approach that integrates the BRIDG model with ISO 21090 data types to generate domain-specific templates to support clinical study metadata standards development. Methods: We developed a template generation and visualization system based on an open source Resource Description Framework (RDF) store backend, a SmartGWT-based web user interface, and a "mind map" based tool for the visualization of generated domain-specific templates. We also developed a RESTful Web Service informed by the Clinical Information Modeling Initiative (CIMI) reference model for access to the generated domain-specific templates. Results: A preliminary usability study is performed and all reviewers (n = 3) had very positive responses for the evaluation questions in terms of the usability and the capability of meeting the system requirements (with the average score of 4.6). Conclusions: Semantic Web technologies provide a scalable infrastructure and have great potential to enable computable semantic interoperability of models in the intersection of health care and clinical research. [ABSTRACT FROM AUTHOR]

One of the important classes of computational problems is problem-oriented workflow applications executed in distributed computing environment. A problem-oriented workflow application can be represented by a directed graph whose vertices are tasks and arcs are data flows. For a problem-oriented workflow application, we can get a priori estimates of the task execution time and the amount of data to be transferred between the tasks. A distributed computing environment designed for the execution of such tasks in a certain subject domain is called problem-oriented environment. To efficiently use resources of the distributed computing environment, special scheduling algorithms are applied. Nowadays, a great number of such algorithms have been proposed. Some of them (like the DSC algorithm) take into account specific features of problem-oriented workflow applications. Others (like Min-Min algorithm) take into account many-core structure of nodes of the computational network. However, none of them takes into account both factors. In this paper, a mathematical model of problem-oriented computing environment is constructed, and a new problem-oriented scheduling (POS) algorithm is proposed. The POS algorithm takes into account both specifics of the problem-oriented jobs and multi-core structure of the computing system nodes. Results of computational experiments comparing the POS algorithm with other known scheduling algorithms are presented. [ABSTRACT FROM AUTHOR]

Domain-specific databases are essential resources for the biomedical community, leveraging expert knowledge to curate published literature and provide access to referenced data and knowledge. The limited scope of these databases, however, poses important challenges on their infrastructure, visibility, funding and usefulness to the broader scientific community. CollecTF is a community-oriented database documenting experimentally validated transcription factor (TF)-binding sites in the Bacteria domain. In its quest to become a community resource for the annotation of transcriptional regulatory elements in bacterial genomes, CollecTF aims to move away from the conventional data-repository paradigm of domain-specific databases. Through the adoption of well-established ontologies, identifiers and collaborations, CollecTF has progressively become also a portal for the annotation and submission of information on transcriptional regulatory elements to major biological sequence resources (RefSeq, UniProtKB and the Gene Ontology Consortium). This fundamental change in database conception capitalizes on the domain-specific knowledge of contributing communities to provide high-quality annotations, while leveraging the availability of stable information hubs to promote long-term access and provide high-visibility to the data. As a submission portal, CollecTF generates TF-binding site information through direct annotation of RefSeq genome records, definition of TF-based regulatory networks in UniProtKB entries and submission of functional annotations to the Gene Ontology. As a database, CollecTF provides enhanced search and browsing, targeted data exports, binding motif analysis tools and integration with motif discovery and search platforms. This innovative approach will allow CollecTF to focus its limited resources on the generation of high-quality information and the provision of specialized access to the data. [ABSTRACT FROM AUTHOR]

Many algorithms for scientific visualization and image analysis are rooted in the world of continuous scalar, vector, and tensor fields, but are programmed in low-level languages and libraries that obscure their mathematical foundations. Diderot is a parallel domain-specific language that is designed to bridge this semantic gap by providing the programmer with a high-level, mathematical programming notation that allows direct expression of mathematical concepts in code. Furthermore, Diderot provides parallel performance that takes advantage of modern multicore processors and GPUs. The high-level notation allows a concise and natural expression of the algorithms and the parallelism allows efficient execution on real-world datasets. [ABSTRACT FROM AUTHOR]

This article describes DSL3S, a domain specific modelling language for Spatial Simulation in the field of Geographic Information Systems (GIS). Techniques such as cellular automata and agent-based modelling have long been used to capture and simulate the temporal dynamics of spatial information. Tools commonly employed to implement spatial simulation models include code libraries and pre-compiled models; the former require advanced programming skills while the latter impose relevant constraints on application scope. Previous attempts to produce domain specific languages in the field have invariably resulted in new textual programming languages (e.g. SELES, NetLogo, Ocelet) that are platform specific and in some cases with weak GIS support and interoperability. DSL3S synthesises relevant concepts of spatial simulation in a UML profile, that allows the design of simulation models through the arrangement of graphical elements. An implementation of this language is also presented, that relies on Model Driven Development (MDD) tools distributed with the Eclipse IDE. This includes a code generation infrastructure, that produces ready to run simulations from DSL3S models, supported by the MASON simulation tool-kit. Finally, DSL3S models for three simple and classical simulations allows to better illustrate and discuss the usage of the language. [ABSTRACT FROM AUTHOR]

Domain-specific languages (DSLs) provide high-level and domain-specific abstractions that allow expressive and concise algorithm descriptions. Since the description in a DSL hides also the properties of the target hardware, DSLs are a promising path to target different parallel and heterogeneous hardware from the same algorithm description. In theory, the DSL description can capture all characteristics of the algorithm that are required to generate highly efficient parallel implementations. However, most frameworks do not make use of this knowledge and the performance cannot reach that of optimized library implementations. In this article, we present the HIPAcc framework, a DSL and source-to-source compiler for image processing. We show that domain knowledge can be captured in the language and that this knowledge enables us to generate tailored implementations for a given target architecture. Back ends for CUDA, OpenCL, and Renderscript allow us to target discrete graphics processing units (GPUs) as well as mobile, embedded GPUs. Exploiting the captured domain knowledge, we can generate specialized algorithm variants that reach the maximal achievable performance due to the peak memory bandwidth. These implementations outperform state-of-the-art domain-specific languages and libraries significantly. [ABSTRACT FROM AUTHOR]

Machine learning is one of the most important subfields of computer science and can be used to solve a variety of interesting artificial intelligence problems. There are different languages, framework and tools to define the data needed to solve machine learning-based problems. However, there is a great number of very diverse alternatives which makes it difficult the intercommunication, portability and re-usability of the definitions, designs or algorithms that any developer may create. In this paper, we take the first step towards a language and a development environment independent of the underlying technologies, allowing developers to design solutions to solve machine learning-based problems in a simple and fast way, automatically generating code for other technologies. That can be considered a transparent bridge among current technologies. We rely on Model-Driven Engineering approach, focusing on the creation of models to abstract the definition of artifacts from the underlying technologies. [ABSTRACT FROM AUTHOR]

Morality and emotions are linked, but what is the nature of their correspondence? Many “whole number” accounts posit specific correspondences between moral content and discrete emotions, such that harm is linked to anger, and purity is linked to disgust. A review of the literature provides little support for these specific morality–emotion links. Moreover, any apparent specificity may arise from global features shared between morality and emotion, such as affect and conceptual content. These findings are consistent with a constructionist perspective of the mind, which argues against a whole number of discrete and domain-specific mental mechanisms underlying morality and emotion. Instead, constructionism emphasizes the flexible combination of basic and domain-general ingredients such as core affect and conceptualization in creating the experience of moral judgments and discrete emotions. The implications of constructionism in moral psychology are discussed, and we propose an experimental framework for rigorously testing morality–emotion links. [ABSTRACT FROM AUTHOR]

Service-oriented computing has emerged as an effective approach for integrating business (and systems) that might spread throughout different organizations. A service is a unit of logic modularization that hides implementation details using well-defined contracts. However, existing languages for contract specification in this domain present several limitations. For instance, both WSDL and Swagger use language-independent data formats (XML and JSON) that are not suitable for specifying contracts and often lead to heavyweight specifications. Interface description languages, such as CORBA IDL and Apache Thrift, solve this issue by providing specific languages for contract specifications. Nevertheless, these languages do not target to the REST architectural style and lack support for language extensibility. In this paper we present the design and implementation of NeoIDL, an extensible domain specific language and program generator for writing REST based contracts that are further translated into service's implementations. In addition, we also present a systematic evaluation of our approach from different perspectives, which involved the implementation of different services using NeoIDL from the domain of Command & Control. In particular, we found initial evidences that shows that NeoIDL can contribute: (i) to bring return on investment with respect to the design and development of NeoIDL, after the implementation of 4 to 7 services; and (ii) to reduce significantly the number of lines of specification when compared to an existing service specification language such as Swagger. [ABSTRACT FROM AUTHOR]

This paper presents a set of computer-aided tools for problem analysis in the software development process. Jackson's problem diagrams are used to model the problem owners' needs and relevant contexts for the software to be built. An algorithm based on three classes of rules is provided for the systematic transformation of these models into behavioral descriptions of the software. This work is part of our long-term research efforts aiming at embedding and empirically evaluating Jackson's Problem Frames framework (PF) in requirements engineering practice. [ABSTRACT FROM AUTHOR]

Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document summarization approach. We compare the tokens in the sentence with cue words. A sentence ranking method is used to extract the important sentences. The existing summarizers are used for performance analysis. [ABSTRACT FROM AUTHOR]

The organisation of corporate wikis tends to deteriorate as time goes by. Rearranging categories, structuring articles and even moving sections among articles are cumbersome tasks in current wiki engines. This discourages the layman. But, it is the layman who writes the articles, knows the wiki content and detects refactoring opportunities. Our goal is to improve the refactoring affordances of current wiki engines by providing an alternative front-end tuned to refactoring. This is achieved by (1) surfacing the structure of the wiki corpus as a mind map, and (2) conducting refactoring as mind map reshaping. To this end, we introduceWikiWhirl, a domain-specific language for wiki refactoring.WikiWhirlis supported as an extension ofFreeMind, a popular mind mapping tool. In this way, refactoring operations are intuitively conducted as actions upon mind map nodes. In a refactoring session a user imports the wiki structure as aFreeMindmap; next, conducts the refactoring operations on the map, and finally, the effects are saved in the wiki database. The operational semantics of theWikiWhirloperations follow refactoring good practices (e.g., authorship preservation). Results from a controlled experiment suggest thatWikiWhirloutperformsMediaWikiin three main affordance enablers: understandability, productivity and fulfillment of refactoring good practices. [ABSTRACT FROM PUBLISHER]

Delta modeling is a modular, yet flexible approach to capture variability by explicitly representing differences between system variants or versions. The conceptual idea of delta modeling is language-independent. But, to apply delta modeling to a concrete language, either a generic transformation language has to be used or the corresponding delta language has to be manually developed for each considered base language. Generic languages and their tool support often lack readability and specific context condition checking, since they are unrelated to the base language. In this paper, we present a process that allows synthesizing a delta language from the grammar of a given base language. Our method relies on an automatically generated language extension that can be manually adapted to meet domain-specific needs. We illustrate our method using delta modeling on a textual variant of architecture diagrams. Furthermore, we evaluate our method using a comparative case study. This case study covers an architectural, a structural, and a behavioral language and compares the preexisting handwritten grammars to the generated grammars as well as the manually tailored grammars. This paper is an extension of Haber et al. (Proceedings of the 17th international software product line conference (SPLC'13), pp 22-31, ). [ABSTRACT FROM AUTHOR]

The article focuses on the Functional Abstraction of Symbolic Transducers (FAST) language for programs to manipulate trees using domains. Topics discussed include development of tree transducers and tree automata by FAST, integration of symbolic automata using FAST, information on Domain-Specific Languages (DSL), and extensible markup language (XML) transformations of tree transducers.