Qualifying input test data for model transformations

Model transformation is a core mechanism for model-driven engineering (MDE). Writing complex model transformations is error-prone, and efficient testing techniques are required as for any complex program development. Testing a model transformation is typically performed by checking the results of the transformation applied to a set of input models. While it is fairly easy to provide some input models, it is difficult to qualify the relevance of these models for testing. In this paper, we propose a set of rules and a framework to assess the quality of given input models for testing a given transformation. Furthermore, the framework identifies missing model elements in input models and assists the user in improving these models.

From model transformation to incremental bidirectional model synchronization

The model-driven software development paradigm requires that appropriate model transformations are applicable in different stages of the development process. The transformations have to consistently propagate changes between the different involved models and thus ensure a proper model synchronization. However, most approaches today do not fully support the requirements for model synchronization and focus only on classical one-way batch-oriented transformations. In this paper, we present our approach for an incremental model transformation which supports model synchronization. Our approach employs the visual, formal, and bidirectional transformation technique of triple graph grammars. Using this declarative specification formalism, we focus on the efficient execution of the transformation rules and how to achieve an incremental model transformation for synchronization purposes. We present an evaluation of our approach and demonstrate that due to the speedup for the incremental processing in the average case even larger models can be tackled.

A web services framework for distributed model management

Distributed model management aims to support the wide-spread sharing and usage of decision support models. Web services is a promising technology for supporting distributed model management activities such as model creation and delivery, model composition, model execution and model maintenance to fulfill dynamic decision-support and problem solving requests. We propose a web services based framework for model management (called MM-WS) to support various activities of the model management life cycle. The framework is based on the recently proposed Integrated Service Planning and Execution (ISP & E) approach for web services integration. We discuss encoding of domain knowledge (as individual models) and utilize the MM-WS framework to interleave synthesis of composite models with their execution. A prototypical implementation with an example is used to illustrate the utility of the framework to enable distributed model management and knowledge integration. Benefits and issues of using the framework to support model-based decision-making in organizational contexts are outlined.

CTL* model checking on a shared-memory architecture

In this article we present the parallelisation of an explicit-state CTL^* model checking algorithm for a virtual shared-memory high-performance parallel machine architecture. The algorithm uses a combination of private and shared data structures for implicit and dynamic load balancing with minimal synchronisation overhead. The performance of the algorithm and the impact that different design decisions have on the performance are analysed using both mathematical cost models and experimental results. The analysis shows not only the practicality and effective speedup of the algorithm, but also the main pitfalls of parallelising model checking for shared-memory architectures.

Model driven design and aspect weaving

A model is a simplified representation of an aspect of the world for a specific purpose. In complex systems, many aspects are to be handled, from architectural aspects to dynamic behavior, functionalities, user-interface, and extra-functional concerns (such as security, reliability, timeliness, etc.). For software systems, the design process can then be characterized as the weaving of all these aspects into a detailed design model. Model Driven Design aims at automating this weaving process, that is automatically deriving software systems from theirs models. This paper explores the relationship between modeling and aspect weaving. It points out some of the challenges related to such automatic model weaving, illustrating them with the example of a weaving process for behavioral models represented as scenarios. This work has been partially supported by the AOSD-Europe Network of Excellence.

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A multifactor approach to student model evaluation

Creating student models for Intelligent Tutoring Systems (ITS) in novel domains is often a difficult task. In this study, we outline a multifactor approach to evaluating models that we developed in order to select an appropriate student model for our medical ITS. The combination of areas under the receiver-operator and precision-recall curves, with residual analysis, proved to be a useful and valid method for model selection. We improved on Bayesian Knowledge Tracing with models that treat help differently from mistakes, model all attempts, differentiate skill classes, and model forgetting. We discuss both the methodology we used and the insights we derived regarding student modeling in this novel domain.

Improving a portlet usability model

Second-generation portals are far from being monolithic pieces of software. Their complexity calls for a component-based approach where portlets are the technical enabler. That being the case nowadays portals tend to be constructed by means of portlets, i.e. a multi-step, user-facing application to be delivered through a Web application. The proposal for and ample support given to the WSRP (Web Services for Remote Portlets) portlet standard predict an emerging portlet market. A main requirement for the blossoming of this market is the existence of portlet quality models that assist portal developers to select the appropriate portlet. This paper focuses on usability. The aim, therefore, is to develop a usability model for portlets. The paper presents such a model and its realisation for a sample case.

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems

Recently, multi-objective evolutionary algorithms have been applied to improve the difficult tradeoff between interpretability and accuracy of fuzzy rule-based systems. It is known that both requirements are usually contradictory, however, these kinds of algorithms can obtain a set of solutions with different trade-offs. This contribution analyzes different application alternatives in order to attain the desired accuracy/interpr-etability balance by maintaining the improved accuracy that a tuning of membership functions could give but trying to obtain more compact models. In this way, we propose the use of multi-objective evolutionary algorithms as a tool to get almost one improved solution with respect to a classic single objective approach (a solution that could dominate the one obtained by such algorithm in terms of the system error and number of rules). To do that, this work presents and analyzes the application of six different multi-objective evolutionary algorithms to obtain simpler and still accurate linguistic fuzzy models by performing rule selection and a tuning of the membership functions. The results on two different scenarios show that the use of expert knowledge in the algorithm design process significantly improves the search ability of these algorithms and that they are able to improve both objectives together, obtaining more accurate and at the same time simpler models with respect to the single objective based approach.

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A new model for time-series forecasting using radial basis functions and exogenous data

In this paper, we present a new model for time-series forecasting using radial basis functions (RBFs) as a unit of artificial neural networks (ANNs), which allows the inclusion of exogenous information (EI) without additional pre-processing. We begin by summarizing the most well-known EI techniques used ad hoc, i.e., principal component analysis (PCA) and independent component analysis (ICA). We analyze the advantages and disadvantages of these techniques in time-series forecasting using Spanish bank and company stocks. Then, we describe a new hybrid model for time-series forecasting which combines ANNs with genetic algorithms (GAs). We also describe the possibilities when implementing the model on parallel processing systems.

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Formalizing the structural semantics of domain-specific modeling languages

Model-based approaches to system design are now widespread and successful. These approaches make extensive use of model structure to describe systems using domain-specific abstractions, to specify and implement model transformations, and to analyze structural properties of models. In spite of its general importance the structural semantics of modeling languages are not well-understood. In this paper we develop the formal foundations for the structural semantics of domain-specific modeling languages (DSML), including the mechanisms by which metamodels specify the structural semantics of DSMLs. Additionally, we show how our formalization can complement existing tools, and how it yields algorithms for the analysis of DSMLs and model transformations.

3D facial model exaggeration builder for small or large sized model manufacturing

An action figure is a small human-shaped object used as a toy for children or artistic collection. In the past, the creation of action figures required intense manual effort. An initial trial to automate the process using recent scanning technology failed to yield figures with market appeal because the resulting action figures did not have sufficiently life-like shapes and expressions. The limiting factor which was not considered during this trial is the loss of individual characteristics resulting from either an increase or reduction in scale. We provide novel techniques for creating an exaggerated human face that retains all of the skin detail in the 3D scanned model, which will allow more characteristic figures to be easily created at any scale, thereby saving money and time during manufacturing. While traditional 3D printing applications utilize rigid models acquired using computer-aided design, our method demonstrates that deformable models (such as a human face) obtained from scanners are also suitable.

Online updating appearance generative mixture model for meanshift tracking

This paper proposes an appearance generative mixture model based on key frames for meanshift tracking. Meanshift tracking algorithm tracks an object by maximizing the similarity between the histogram in tracking window and a static histogram acquired at the beginning of tracking. The tracking therefore could fail if the appearance of the object varies substantially. In this paper, we assume the key appearances of the object can be acquired before tracking and the manifold of the object appearance can be approximated by piece-wise linear combination of these key appearances in histogram space. The generative process is described by a Bayesian graphical model. An Online EM algorithm is proposed to estimate the model parameters from the observed histogram in the tracking window and to update the appearance histogram. We applied this approach to track human head motion and to infer the head pose simultaneously in videos. Experiments verify that our online histogram generative model constrained by key appearance histograms alleviates the drifting problem often encountered in tracking with online updating, that the enhanced meanshift algorithm is capable of tracking object of varying appearances more robustly and accurately, and that our tracking algorithm can infer additional information such as the object poses. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.

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Ranked linear models and sequential patterns recognition

Ranked models in the form of linear transformations of multivariate feature vectors on a line can be found on the basis of a priori given order within particular pairs of objects or events. Such ranked transformations are designed to preserve given sequential order. In this way, the sequential patterns inside sets of the feature vectors can be discovered and modelled. Attention is paid here to combining problems of sequential patterns modelling and recognition with feature selection. The feature selection problem is aimed at the best representation of the sequential patterns. The convex and piecewise linear (CPL) criterion functions are used here both for designing ranked linear models and for feature selection.

MinGPU: a minimum GPU library for computer vision

In the field of computer vision, it is becoming increasingly popular to implement algorithms, in sections or in their entirety, on a graphics processing unit (GPU). This is due to the superior speed GPUs offer compared to CPUs. In this paper, we present a GPU library, MinGPU, which contains all of the necessary functions to convert an existing CPU code to GPU. We have created GPU implementations of several well known computer vision algorithms, including the homography transformation between two 3D views. We provide timing charts and show that our MinGPU implementation of homography transformations performs approximately 600 times faster than its C++ CPU implementation.

Extending obstacle avoidance methods through multiple parameter-space transformations

Obstacle avoidance methods approach the problem of mobile robot autonomous navigation by steering the robot in real-time according to the most recent sensor readings, being suitable to dynamic or unknown environments. However, real-time performance is commonly gained by ignoring the robot shape and some or all of its kinematic restrictions which may lead to poor navigation performance in many practical situations. In this paper we propose a framework where a kinematically constrained and any-shape robot is transformed in real-time into a free-flying point in a new space where well-known obstacle avoidance methods are applicable. Our contribution with this framework is twofold: the definition of generalized space transformations that cover most of the existing transformational approaches, and a reactive navigation system where multiple transformations can be applied concurrently in order to optimize robot motion decisions. As a result, these transformations allow existing obstacle avoidance methods to perform better detection of the surrounding free-space, through “sampling” the space with paths compatible with the robot kinematics. We illustrate how to design these space transformations with some examples from our experience with real robots navigating in indoor, cluttered, and dynamic scenarios. Also, we provide experimental results that demonstrate the advantages of our approach over previous methods when facing similar situations.

E-redesigning of society: towards experiential connectivity of generations in Lithuania

The paper reflects on the unique experience of social and technological development in Lithuania since the regaining of independence as a newly reshaped society constructing a distinctive competitive IST-based model at global level. This has presented Lithuanian pattern of how to integrate different experiences and relations between generations in implementing complex information society approaches. The resulting programme in general is linked to the Lisbon objectives of the European Union. The experience of transitional countries in Europe, each different but facing some common problems, may be useful to developing countries in Africa.

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Model transformation by example using inductive logic programming

Model transformation by example is a novel approach in model-driven software engineering to derive model transformation rules from an initial prototypical set of interrelated source and target models, which describe critical cases of the model transformation problem in a purely declarative way. In the current paper, we automate this approach using inductive logic programming (Muggleton and Raedt in J Logic Program 19-20:629–679, 1994) which aims at the inductive construction of first-order clausal theories from examples and background knowledge.

Ethical regulations on robotics in Europe

There are only a few ethical regulations that deal explicitly with robots, in contrast to a vast number of regulations, which may be applied. We will focus on ethical issues with regard to “responsibility and autonomous robots”, “machines as a replacement for humans”, and “tele-presence”. Furthermore we will examine examples from special fields of application (medicine and healthcare, armed forces, and entertainment). We do not claim to present a complete list of ethical issue nor of regulations in the field of robotics, but we will demonstrate that there are legal challenges with regard to these issues.

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The 2007 IEEE CEC simulated car racing competition

This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process, we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.

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Interacting with mobile services: an evaluation of camera-phones and visual tags

We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive, although they had several important reservations about camera-phone technology more generally. Data from our pointing-device task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings, design lessons for camera-phone and visual-tag applications are presented.

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