A programming language for learning environments

Most of the recent research on programming languages for education has been centered around the language Logo. In this paper we introduce another candidate language for learning environments, Nial, the nested interactive array language.
Nial is a general-purpose programming language based on a formal theory of mathematics called array theory. This paper introduces Nial as a language for learning programming and developing and using computer-aided instruction tools. A comparison with Logo is provided to evaluate these two languages in terms of their strengths and weaknesses as programming environments for novice programmers. We also demonstrate that a programming environment can be both simple to leam at the novice level and extendible to a powerful and sophisticated language.     

A multimedia framework for second language teaching in self-access environments

This paper presents an account of a self-access language teaching scheme operated at the University of Bologna during the last three years. The main goal of the D.I.A.P.A.S.O.N. (Distributed, Interactive, And Personalised Audio-visual Study Over Network) project is to teach English to university students up to intermediate level, by building a self-access environment freely available to learners. Some laboratories equipped with multimedia workstations, video stations, satellite receivers and specifically targeted courseware were set up and tested in one complete year of work. Here I will analyse some topics concerned with self-access language learning through CALL (Computer Aided Language Learning) and the complete structure of the DIAPASON courseware. Some data collected on a sample of students during the year are presented and an interpretation of the data suggested. The main result emerging from the data is that students are very busy and tend to spend only the minimum required time to study foreign languages, organising this activity in few short sessions during the week.     

A natural language model for managing TV-Anytime information in mobile environments

The TV-Anytime standard describes the structures of categories of digital TV program metadata, as well as user profile metadata for TV programs. We describe a natural language (NL) model for the users to interact with the TV-Anytime metadata and preview TV programs from their mobile devices. The language utilises completely the TV-Anytime metadata specifications (upper ontologies), as well as domain-specific ontologies. The interaction model does not use clarification dialogues, but it uses the user profiles as well as TV-Anytime metadata information and ontologies to rank the possible responses in case of ambiguities. We describe implementations of the model that run on a PDA and on a mobile phone, and manage the metadata on a remote TV-Anytime-compatible TV set. We present user evaluations of the approach. Finally, we propose a generalised implementation framework that can be used to easily provide NL interfaces for mobile devices for different applications and ontologies.     

Bilingual language supports in online science inquiry environments

Research over the past fifteen years has investigated and developed online science inquiry environments to support students engaging in authentic scientific inquiry practices. This research has focused on developing activity structures and tools to scaffold students in engaging in different aspects of these practices, but relatively little of this research has explored linguistic supports for language minority students studying science in their non-native language. These students are simultaneously learning science and the surrounding academic language in their second language. This study investigates the potential value of providing 8th grade Spanish-speaking English language learners access to content and supports in both English and Spanish as opposed to an English-only format in an online science inquiry environment. Learning outcomes are compared between the two conditions on an immediate post-test in English, a delayed post-test in English, a delayed post-test in Spanish, and a written essay in English in the form of a letter to the governor. The outcomes suggest significant benefits for providing ELL students with access to content and supports in both English and Spanish as opposed to the English-only format. The findings of this study carry important policy implications in light of the growing English-only political movements in the United States and similar political movements in other countries.     

A systematic approach to evaluating domain-specific modeling language environments for multi-agent systems

Multi-agent systems (MASs) include multiple interacting agents within an environment to provide a solution for complex systems that cannot be easily solved with individual agents or monolithic systems. However, the development of MASs is not trivial due to the various agent properties such as autonomy, responsiveness, and proactiveness, and the need for realization of the many different agent interactions. To support the development of MASs various domain-specific modeling languages (DSMLs) have been introduced that provide a declarative approach for modeling and supporting the generation of agent-based systems. To be effective, the proposed DSMLs need to meet the various stakeholder concerns and the related quality criteria for the corresponding MASs. Unfortunately, very often the evaluation of the DSML is completely missing or has been carried out in idiosyncratic approach. If the DSMLs are not well defined, then implicitly this will have an impact on the quality of the MASs. In this paper, we present an evaluation framework and systematic approach for assessing existing or newly defined DSMLs for MASs. The evaluation is specific for MAS DSMLs and targets both the language and the corresponding tools. To illustrate the evaluation approach, we first present SEA_ML, which is a model-driven MAS DSML for supporting the modeling and generation of agent-based systems. The evaluation of SEA_ML is based on a multi-case study research approach and provides both qualitative evaluation and quantitative analysis. We report on the lessons learned considering the adoption of the evaluation approach as well as the SEA_ML for supporting the generation of agent-based systems.     

A traffic priority language for collision-free navigation ofautonomous mobile robots in dynamic environments

This paper presents a generic traffic priority language, called KYKLOFORTA, used by autonomous robots for collision-free navigation in a dynamic unknown or known navigation space. In a previous work by X. Grossmman (1988), a set of traffic control rules was developed for the navigation of the robots on the lines of a two-dimensional (2-D) grid and a control center coordinated and synchronized their movements. In this work, the robots are considered autonomous: they are moving anywhere and in any direction inside the free space, and there is no need of a central control to coordinate and synchronize them. The requirements for each robot are i) visual perception, ii) range sensors, and iii) the ability of each robot to detect other moving objects in the same free navigation space, define the other objects perceived size, their velocity and their directions. Based on these assumptions, a traffic priority language is needed for each robot, making it able to decide during the navigation and avoid possible collision with other moving objects. The traffic priority language proposed here is based on a set of primitive traffic priority alphabet and rules which compose pattern of corridors for the application of the traffic priority rules.     

A stabilized multidomain approach for singular perturbation problems

We present a new technique of stabilization for finite difference or spectral approximations of singular perturbation problems. Here we allow the artificial viscosity to be constant and independent of the step size. The results are generalized to variable coefficient problems. Suitable multigrid components are proposed. Numerical results are presented which substantiate the usefulness of our technique.     

A multidomain spectral method for solving elliptic equations

We present a new solver for coupled nonlinear elliptic partial differential equations (PDEs). The solver is based on pseudo-spectral collocation with domain decomposition and can handle one- to three-dimensional problems. It has three distinct features. First, the combined problem of solving the PDE, satisfying the boundary conditions, and matching between different subdomains is cast into one set of equations readily accessible to standard linear and nonlinear solvers. Second, touching as well as overlapping subdomains are supported; both rectangular blocks with Chebyshev basis functions as well as spherical shells with an expansion in spherical harmonics are implemented. Third, the code is very flexible: The domain decomposition as well as the distribution of collocation points in each domain can be chosen at run time, and the solver is easily adaptable to new PDEs. The code has been used to solve the equations of the initial value problem of general relativity and should be useful in many other problems. We compare the new method to finite difference codes and find it superior in both runtime and accuracy, at least for the smooth problems considered here.     

Ray-tracing polymorphic multidomain spectral/hp elements for isosurface rendering

The purpose of this paper is to present a ray-tracing isosurface rendering algorithm for spectral/hp (high-order finite) element methods in which the visualization error is both quantified and minimized. Determination of the ray-isosurface intersection is accomplished by classic polynomial root-finding applied to a polynomial approximation obtained by projecting the finite element solution over element-partitioned segments along the ray. Combining the smoothness properties of spectral/hp elements with classic orthogonal polynomial approximation theory, we devise an adaptive scheme which allows the polynomial approximation along a ray-segment to be arbitrarily close to the true solution. The resulting images converge toward a pixel-exact image at a rate far faster than sampling the spectral/hp element solution and applying classic low-order visualization techniques such as marching cubes.     

The Schwarz algorithm for multidomain spectral approximation of elliptic problems

A multidomain Schwarz method is developed for the spectral approximation of a model elliptic problem. The spectral behavior of the error propagation operator of the algorithm is the same as in the Dirichlet-Neumann method presented in [11]. However, in the Schwarz method only the Dirichlet data have to be interchanged between subdomains, and there is no relaxation parameter to be chosen.     

Facilitating application of language skills in authentic environments with a mobile learning system

We uncovered two critical issues in earlier studies: (a) some studies have shown that mobile learning technology is not beneficial for all students due to complexity of learning environments and student prior knowledge, skills, and experience and (b) familiarity of students with the authentic environments in which they learn using mobile technology did not receive much attention in earlier studies. To address these issues, we designed three learning tasks for a class of 26 junior high school students. The students applied language skills by completing the tasks in authentic environments individually in a first task, loosely collaborating with peers in a second task, and tightly collaborating with peers in a third task. A mobile learning system was also designed in this study to support students to accomplish the tasks. The aim of this study was to explore students' learning experiences using the learning system, their perceptions towards the system, and to assess how differently the students perform on the three tasks. According to our design, in the first task, the students took pictures of objects and described them orally or in writing using the mobile learning system. In the second task, after the students completed assignments, each student received comments from a partner through the system. In comments, the partner indicated flaws in student assignments and suggested how to fix them. In the third task, the students completed assignments, shared them using the system, and then exchanged comments with their partners face to face regarding issues related to their completed assignments and suggested how to improve them. Such learning behaviours in the three tasks enabled the students to practise writing and speaking skills. Our results demonstrate that most of the students highly valued our learning system and intend to use it in the future. Furthermore, the results show that the students performed best when they collaborated; namely, student performance was enhanced the most after the third task that required tight collaboration. Based on our results, we learned that students' familiarity with authentic environments is very important and beneficial for their learning. In addition, we learned that even in complex environment, less skilled and experienced students with low prior knowledge can perform well when they tightly collaborate with more skilled and experienced students with high prior knowledge, and our learning system can facilitate such collaboration.     

Single and multidomain Chebyshev collocation methods for the Korteweg-de Vries equation

We propose spectral Chebyshev collocation algorithms for the approximation of the initial and boundary value problem for the Korteweg-de Vries equation. Both single and multidomain approaches are discussed. Different methods for the treatment of the boundary conditions are considered. The numerical analysis of the eigenvalues' behaviour of the spectral differentiation operators involved in the approximation suggests appropriate finite difference methods for time-marching. Several numerical experiments have been performed, which prove spectral convergence and stability of the proposed schemes.     

Spectral multidomain technique with Local Fourier Basis

A novel domain decomposition method for spectrally accurate solutions of PDEs is presented. A Local Fourier Basis technique is adapted for the construction of the elemental solutions in subdomains.C ¹ continuity is achieved on the interfaces by a matching procedure using the analytical homogeneous solutions of a one dimensional equation. The method can be applied to the solution of elliptic problems of the Poisson or Helmholtz type as well as to time discretized parabolic problems in one or more dimensions. The accuracy is tested for several stiff problems with steep solutions.The present domain decomposition approach is particularly suitable for parallel implementations, in particular, on MIMD type parallel machines.This research is supported partly by a grant from the French-Israeli Binational Foundation for 1991–1992.     

Physics-based character skinning using multidomain subspace deformations

In this extended version of our Symposium on Computer Animation paper, we describe a domain-decomposition method to simulate articulated deformable characters entirely within a subspace framework. We have added a parallelization and eigendecomposition performance analysis, and several additional examples to the original symposium version. The method supports quasistatic and dynamic deformations, nonlinear kinematics and materials, and can achieve interactive time-stepping rates. To avoid artificial rigidity, or “locking,” associated with coupling low-rank domain models together with hard constraints, we employ penaltybased coupling forces. The multidomain subspace integrator can simulate deformations efficiently, and exploits efficient subspace-only evaluation of constraint forces between rotated domains using a novel Fast Sandwich Transform (FST). Examples are presented for articulated characters with quasistatic and dynamic deformations, and interactive performance with hundreds of fully coupled modes. Using our method, we have observed speedups of between 3 and 4 orders of magnitude over full-rank, unreduced simulations.     

Software safety certification: a multidomain problem

Multidomain software-intensive system certification is a growing concern in international standards organizations. Certification is traditionally based on domain-specific technical and operational requirements, historical information about the reliability of the different subsystems, and historical accident data, but these may not be available for interdomain systems. There is a need for international and interdisciplinary legal recognition of certification authorities. The author explores both the legal and technical aspects of this critical, timely problem     

Tools for multiple-CPU environments

A brief overview precedes ten separate tool reviews. Five of the tools address the problems of performance analysis, testing, and debugging in a multiple-CPU environment. The first set of tools-Graspin PPSE, and Integral-supports this activity by providing specification or design languages for concurrent applications. The next pair of tools-Pie and Total-supports the development of multiple-CPU software by representing the software's behavior in a parallel or concurrent environment. The next set of five tools is aimed at the problem of serial-to-parallel conversions. The first three tools-E/SP, Mimdizer, and PRETS-recapture the design of the original source code and display it in a graphical form for analysis. The remaining tools-Pat and Aspar-support direct source-to-source transformations. These ten tools are representative of current approaches being taken to address the problem of multiple-CPU computing     

Radiosity for dynamic environments

In this paper we present a radiosity algorithm for dynamic scenes with a high level of frame-to-frame coherence. The algorithm is restricted to dynamic environments, where the object's movement is known a priori and the viewpoint is static. Each image is computed as the sum of two images: the base-level image, computed in a pre-process, and the frame-level image computed incrementally at each frame. The computation of the images is based on an importance-driven heuristic approach. The results of the implementation are analysed and discussed. © 1997 John Wiley & Sons, Ltd.     

Message-passing environments for metacomputing

In this paper, we present the three libraries PACX-MPI, PLUS, and PVMPI that provide message-passing between different high-performance computers in metacomputing environments. Each library supports the development and execution of distributed metacomputer applications.

The PACX-MPI approach offers a transparent interface for the communication between two or more MPI environments. PVAMPI allows the user spawning parallel processes under the MPI environment. The PLUS protocol bridges the gap between vendor-specific (e.g., MPL, NX, and PARIX) and vendor-independent message-passing environments (e.g., PVM and MPI). Moreover, it offers the ability to create and control processes at application runtime.     

Virtual environments for education

WWWIC, the NDSU World Wide Web Instructional Committee, is engaged in developing a range of virtual environments for education. These projects span a range of disciplines, from earth science to anthropology, and from business to biology. However, all of these projects share a strategy, a set of assumptions, an approach to assessment, and an emerging tool set, which allows each to leverage from the insights and advances of the others.     

MOSAIC for multiple-reward environments

Reinforcement learning (RL) can provide a basic framework for autonomous robots to learn to control and maximize future cumulative rewards in complex environments. To achieve high performance, RL controllers must consider the complex external dynamics for movements and task (reward function) and optimize control commands. For example, a robot playing tennis and squash needs to cope with the different dynamics of a tennis or squash racket and such dynamic environmental factors as the wind. In addition, this robot has to tailor its tactics simultaneously under the rules of either game. This double complexity of the external dynamics and reward function sometimes becomes more complex when both the multiple dynamics and multiple reward functions switch implicitly, as in the situation of a real (multi-agent) game of tennis where one player cannot observe the intention of her opponents or her partner. The robot must consider its opponent's and its partner's unobservable behavioral goals (reward function). In this article, we address how an RL agent should be designed to handle such double complexity of dynamics and reward. We have previously proposed modular selection and identification for control (MOSAIC) to cope with nonstationary dynamics where appropriate controllers are selected and learned among many candidates based on the error of its paired dynamics predictor: the forward model. Here we extend this framework for RL and propose MOSAIC-MR architecture. It resembles MOSAIC in spirit and selects and learns an appropriate RL controller based on the RL controller's TD error using the errors of the dynamics (the forward model) and the reward predictors. Furthermore, unlike other MOSAIC variants for RL, RL controllers are not a priori paired with the fixed predictors of dynamics and rewards. The simulation results demonstrate that MOSAIC-MR outperforms other counterparts because of this flexible association ability among RL controllers, forward models, and reward predictors.