A fuzzy linguistic algorithm for adaptive test in Intelligent Tutoring System based on competences

The Computerized Adaptive Tests (CAT) are common tools for the diagnosis process in Intelligent Tutor System based on Competency education (ITS-C). The item selection process to form a CAT plays a key role because it must ensure the selection of the item that best contributes to student assessment at any time. The item selection mechanisms proposed in the literature present some limitations that decrease the efficiency of CAT and its adaptation to the student profile. This paper introduces a new item selection algorithm, based on a multi-criteria decision model that integrates experts’ knowledge modeled by fuzzy linguistic information that overcomes previous limitations and enhances the accuracy of diagnosis and the adaptation of CAT to student’s competence level. Finally, such an algorithm is deployed in a mobile tool for an ITS-C.     

Knowledge acquisition and knowledge representation with class: the object-oriented paradigm

Knowledge acquisition and knowledge representation are the fundamental building blocks of knowledge-based systems (KBSs). How to efficiently elicit knowledge from experts and transform this elicited knowledge into a machine usable format is a significant and time consuming problem for KBS developers. Object-orientation provides several solutions to persistent knowledge acquisition and knowledge representation problems including transportability, knowledge reuse, and knowledge growth. An automated graphical knowledge acquisition tool is presented, based upon object-oriented principles. The object-oriented graphical interface provides a modeling platform that is easily understood by experts and knowledge engineers. The object-oriented base for the automated KA tool provides a representation independent methodology that can easily be mapped into any other object-oriented expert system or other object-oriented intelligent tools.     

Computerized conferencing for knowledge acquisition from multiple experts

The increasing complecity of many expert system application areas calls for the integration of the knowledge of multiple experts. The use of multiple experts introduces some interesting new problems during the process of knowledge acquisition. The problems are further complicated when the experts are geographically dispersed or unavailable for face-to-face interactions.

This article discusses the motivations for acquiring the knowledge of multiple experts, the problems related to knowledge acquisition, new issues that arise whens multiple experts interact, solutions that can be brought to bear in building multiple expert systems (particularly when experts are geographically dispersed), and new tools for knowledge engineers to use when dealing with multiple experts.     

The influence of automation on tumor contouring

Fully or semi-automatic contouring tools are increasingly being used in the tumor contouring task for radiotherapy. While the fully automatic contouring tools have not reached sufficient efficiency, the semi-automatic contouring tools balance more effectively between the human interaction and automation. This study evaluates the influences of a semi-automation contouring tool, called between-slice interpolation, on the resulting contours and the contouring process. The tumor contouring study was conducted on three patient cases with five physicians in a naturalistic setting. The contouring task consisted of initiating the 2D contour manually or with the interpolation tool and correcting that initial contour. The similarity of the resulting contours was pairwise measured within the manual or the interpolated category. Interactions with the software were recorded, and variations in the contouring workflows steps were compared. Results indicated that using the between-slice interpolation tool for creating the initial contour, instead of initiating it manually, influenced both the contouring process and outcomes. First, it was identified that contours initiated by the interpolation tool showed an increased similarity among themselves compared to the manually initiated contours. At the same time, influences to the resulting contours were below clinical relevance, and toward the desired direction—improved consistency of contours. Second, when interpolation was used, in two cases out of three, the average contouring time also decreased significantly. Therefore, the use of such an automation tool can be encouraged.     

Eliciting knowledge and transferring it effectively to aknowledge-based system

The knowledge acquisition bottleneck impeding the development of expert systems is being alleviated by the development of computer-based knowledge acquisition tools. These work directly with experts to elicit knowledge, and structure it appropriately to operate as a decision support tool within an expert system. However, the elicitation of expert knowledge and its effective transfer to a useful knowledge-based system is complex and involves diverse activities. The complete development of a decision support system using knowledge acquisition tools is illustrated. The example is simple enough to be completely analyzed but exhibits enough real-world characteristics to give significant insights into the processes and problems of knowledge engineering     

Combining open‐source natural language processing tools to parse clinical practice guidelines

Natural language processing (NLP) has been used to process text pertaining to patient records and narratives. However, most of the methods used were developed for specific systems, so new research is necessary to assess whether such methods can be easily retargeted for new applications and goals, with the same performance. In this paper, open‐source tools are reused as building blocks on which a new system is built. The aim of our work is to evaluate the applicability of the current NLP technology to a new domain: automatic knowledge acquisition of diagnostic and therapeutic procedures from clinical practice guideline free‐text documents. In order to do this, two publicly available syntactic parsers, several terminology resources and a tool oriented to identify semantic predications were tailored to increase the performance of each tool individually. We apply this new approach to 171 sentences selected by the experts from a clinical guideline, and compare the results with those of the tools applied with no tailoring. The results of this paper show that with some adaptation, open‐source NLP tools can be retargeted for new tasks, providing an accuracy that is equivalent to the methods designed for specific tasks.     

Mobile augmented reality for environmental monitoring

In response to dramatic changes in the environment, and supported by advances in wireless networking, pervasive sensor networks have become a common tool for environmental monitoring. However, tools for on-site visualization and interactive exploration of environmental data are still inadequate for domain experts. Current solutions are generally limited to tabular data, basic 2D plots, or standard 2D GIS tools designed for the desktop and not adapted to mobile use. In this paper, we introduce a novel augmented reality platform for 3D mobile visualization of environmental data. Following a user-centered design approach, we analyze processes, tasks, and requirements of on-site visualization tools for environmental experts. We present our multilayer infrastructure and the mobile augmented reality platform that leverages visualization of georeferenced sensor measurement and simulation data in a seamless integrated view of the environment.     

The user action framework: a reliable foundation for usability engineering support tools

Although various methods exist for performing usability evaluation, they lack a systematic framework for guiding and structuring the assessment and reporting activities. Consequently, analysis and reporting of usability data are ad hoc and do not live up to their potential in cost effectiveness, and usability engineering support tools are not well integrated. We developed the User Action Framework, a structured knowledge base of usability concepts and issues, as a framework on which to build a broad suite of usability engineering support tools. The User Action Framework helps to guide the development of each tool and to integrate the set of tools in the practitioner's working environment. An important characteristic of the User Action Framework is its own reliability in term of consistent use by practitioners. Consistent understanding and reporting of the underlying causes of usability problems are requirements for cost-effective analysis and redesign. Thus, high reliability in terms of agreement by users on what the User Action Framework means and how it is used is essential for its role as a common foundation for the tools. Here we describe how we achieved high reliability in the User Action Framework, and we support the claim with strongly positive results of a summative reliability study conducted to measure agreement among 10 usability experts in classifying 15 different usability problems. Reliability data from the User Action Framework are also compared to data collected from nine of the same usability experts using a classic heuristic evaluation technique.     

Interpolation of plans for time-critical adaptation

Most techniques for knowledge-based plan adaptation are search-intensive as they rely on a general search through plan libraries to find suitable items for development or adaptation. This degrades their usefulness for real-time computations. The paper states and illustrates a plan-construction technique, “plan interpolation”, whose purpose is to keep the amount of searching small. It selects two past plans, and then generates a new plan by a method that is similar to “interpolation” in the sense of numerical analysis. The approach and its details are illustrated by reference to examples drawn from the domain of ground operations control in an airport.     

Interpolation of rotation and motion

In Cosserat solids such as shear deformable beams and shells, the displacement and rotation fields are independent. The finite element implementation of these structural components within the framework of flexible multibody dynamics requires the interpolation of rotation and motion fields. In general, the interpolation process does not preserve fundamental properties of the interpolated field. For instance, interpolation of an orthogonal rotation tensor does not yield an orthogonal tensor, and furthermore, does not preserve the tensorial nature of the rotation field. Consequently, many researchers have been reluctant to apply the classical interpolation tools used in finite element procedures to interpolate these fields. This paper presents a systematic study of interpolation algorithms for rotation and motion. All the algorithms presented here preserve the fundamental properties of the interpolated rotation and motion fields, and furthermore, preserve their tensorial nature. It is also shown that the interpolation of rotation and motion is as accurate as the interpolation of displacement, a widely accepted tool in the finite element method. The algorithms presented in this paper provide interpolation tools for rotation and motion that are accurate, easy to implement, and physically meaningful.     

Adapting Virtual Reality for the Participatory Design of Work Environments

This paper describes the evolution of a standard PC-based virtual reality tool which has been adapted for the participatory design of work environments. Tool features, method of control and combination with other participatory design tools are investigated in the context of a particular design situation. This research is aimed at participatory design facilitators to aid in the adaptation of similar virtual reality systems for a similar purpose. The context of this work is the Envisionment Workshop, in which a group of workers participate with design experts in using full-scale modelling, pedagogical drama, and democratic meetings to (re)design their workplace. A series of prototypes have been developed and tested during the design of a new university in the region using a case study methodology to provide high ecological validity. These were preceded by a task analysis, brainstorming and pilot study. The results suggest that such a tool can be constructed and used successfully by a small group of people using projected virtual reality. However larger groups suffer from a bottleneck at the input devices such that a virtual reality expert must take control and build what the participants wish. This revised version was published online in August 2006 with corrections to the Cover Date.     

A hybrid cuckoo search-genetic algorithm for hole-making sequence optimization

Biologically-inspired algorithms are stochastic search methods that emulate the behavior of natural biological evolution to produce better solutions and have been widely used to solve engineering optimization problems. In this paper, a new hybrid algorithm is proposed based on the breeding behavior of cuckoos and evolutionary strategies of genetic algorithm by combining the advantages of genetic algorithm into the cuckoo search algorithm. The proposed hybrid cuckoo search-genetic algorithm (CSGA) is used for the optimization of hole-making operations in which a hole may require various tools to machine its final size. The main objective considered here is to minimize the total non-cutting time of the machining process, including the tool positioning time and the tool switching time. The performance of CSGA is verified through solving a set of benchmark problems taken from the literature. The amount of improvement obtained for different problem sizes are reported and compared with those by ant colony optimization, particle swarm optimization, immune based algorithm and cuckoo search algorithm. The results of the tests show that CSGA is superior to the compared algorithms.     

Formal Modeling and Verification of Safety-Critical Software

Rigorous quality demonstration is important when developing safety-critical software such as a reactor protection system (RPS) for a nuclear power plant. Although using formal methods such as formal modeling and verification is strongly recommended, domain experts often reject formal methods for four reasons: there are too many candidate techniques, the notations appear complex, the tools often work only in isolation, and output is often too difficult for domain experts to understand. A formal-methods-based process that supports development, verification and validation, and safety analysis can help domain experts overcome these obstacles. Nuclear engineers can also use CASE tools to apply formal methods without having to know details of the underlying formalism. The authors spent more than seven years working with nuclear engineers in developing RPS software and applying formal methods. The engineers and regulatory personnel found the process effective and easy to apply with the integrated tool support.     

Beam search algorithm for capacity allocation problem in flexible manufacturing systems

This study considers the operation assignment and tool allocation problem in flexible manufacturing systems. A set of operations together with their required tools are selected so as to maximize the total weight. The machines have limited time and tool magazine capacities and the tools are available in limited quantities. We develop a beam search algorithm and obtain near optimal solutions for large size problems very quickly.     

Printed Circuit Board Design via Organizational-Learning Agents

This paper proposes a novel evolutionary computation model: Organizational-Learning Oriented Classifier System (OCS), and describes its application to Printed Circuit Boards (PCBs) redesign problems in a computer aided design (CAD). Using the conventional CAD systems which explicitly decide the parts' placements by a knowledge base, the systems cannot effectively place the parts as done by human experts. Furthermore, the supports of human experts are intrinsically required to sa tisfy the constraints and to optimize a global objective function. However, in the proposed model OCS, the parts generate and acquire adaptive behaviors for an appropriate placement without explicit control. In OCS, we focus upon emergent processes in which the parts dynamically form an organized group with autonomously generating adaptive behaviors through local interaction among them. Using the model OCS, we have conducted intensive experiments on a practical PCB redesign problem for electric appliances. The experimental results have shown that: (1) it has found the feasible solutions of the same level as the ones by human experts, (2) solutions are locally optimal, and also globally better than the ones by human experts with regard to the total wiring length, and (3) the solutions are more preferable than those in the conventional CAD systems.     

Interactive Visualization of Flood and Heavy Rain Simulations

In this paper, we present a real‐time technique to visualize large‐scale adaptive height fields with C ‐continuous surface reconstruction. Grid‐based shallow water simulation is an indispensable tool for interactive flood management applications. Height fields defined on adaptive grids are often the only viable option to store and process the massive simulation data. Their visualization requires the reconstruction of a continuous surface from the spatially discrete simulation data. For regular grids, fast linear and cubic interpolation are commonly used for surface reconstruction. For adaptive grids, however, there exists no higher‐order interpolation technique fast enough for interactive applications. Our proposed technique bridges the gap between fast linear and expensive higher‐order interpolation for adaptive surface reconstruction. During reconstruction, no matter if regular or adaptive, discretization and interpolation artifacts can occur, which domain experts consider misleading and unaesthetic. We take into account boundary conditions to eliminate these artifacts, which include water climbing uphill, diving towards walls, and leaking through thin objects. We apply realistic water shading with visual cues for depth perception and add waves and foam synthesized from the simulation data to emphasize flow directions. The versatility and performance of our technique are demonstrated in various real‐world scenarios. A survey conducted with domain experts of different backgrounds and concerned citizens proves the usefulness and effectiveness of our technique.     

CBR for the management and reuse of image-processing expertise: a conversational system

The development of an image-processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. The major objective of the work described in this paper is to help IP experts reuse parts of their applications. A first step towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of an interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, the authors explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system’s implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application.     

A survey of artificial neural network training tools

Artificial neural networks (ANN) are currently an additional tool which the engineer can use for a variety of purposes. Classification and regression are the most common tasks; however, control, modeling, prediction and forecasting are common tasks as well. For over three decades, the field of ANN has been the center of intense research. As a result, one of the outcomes has been the development of a large set of software tools used to train these kinds of networks, making the selection of an adequate tool difficult for a new user. This paper aims to help the ANN user choose the most appropriate tool for its application by providing a large survey of the solutions available, as well as listing and explaining their characteristics and terms of use. The paper limits itself to focusing on the tools which were developed for ANN and the relevant characteristics of these tools, such as the operating systems, hardware requirements, license types, architectures and algorithms available.