3-D Unitary ESPRIT: Accurate attitude estimation for unmanned aerial vehicles with a hexagon-shaped ESPAR array

Accurate estimation of the attitude of unmanned aerial vehicles (UAVs) is crucial for their control and displacement. Errors in the attitude estimate may misuse the limited battery energy of UAVs or even cause an accident. For attitude estimation, proprioceptive sensors such as inertial measurement units (IMUs) are widely applied, but they are susceptible to inertial guidance error. With antenna arrays currently being installed in UAVs for communication with ground base stations, we can take advantage of the array structure in order to improve the estimates of IMUs via data fusion. In this paper, we therefore propose an attitude estimation system based on a hexagon-shaped 7-element electronically steerable parasitic antenna radiator (ESPAR) array. The ESPAR array is well-suited for installment in the UAVs with broad wings and short bodies. Our proposed solution returns an estimation for the pitch and roll based on the inter-element phase delay estimates of the line-of-sight path of the impinging signal over the antenna array. By exploiting the parallel and centrosymmetric structure in the hexagon-shaped ESPAR array, the 3-dimensional Unitary ESPRIT algorithm is applied for phase delay estimation to achieve high accuracy as well as computational efficiency. We devise an attitude estimation algorithm by exploiting the geometrical relationship between the UAV attitude and the estimated phase delays. An analytical closed-form expression of the attitude estimates is obtained by solving the established simultaneous nonlinear equations. Simulations results show the feasibility of our proposed solution for different signal-to-noise ratio levels as well as multipath scenarios.     

Parallel associative combinator evaluation II

A new evaluation model for SK combinator expressions is presented and used as a basis for the design of a novel processor. The resulting machine architecture resembles a dataflow ring, but executions are constrained to be fully lazy. An automatic dynamic load sharing mechanism for a distributed multiprocessor architecture is suggested, and initial simulation results are presented.     

Using the job-exposure matrix for elaborating job histories.

A first software (JHS) for the elaboration of job histories oriented toward risks was designed and results published In an article "A software for the elaboration of Job Histories". This article presents a second software (JES), based on the use of a job-exposure matrix designed for one company. The matrix is essentially a database, an organized gathering of information concerning the company. The two softwares are inter-faced and both run on a PC. When properly exploited, the two softwares can serve as an asset for epidemiological studies dealing with occupational health.     

Fast generic selection of features for neural network classifiers

The authors describe experiments using a genetic algorithm for feature selection in the context of neural network classifiers, specifically, counterpropagation networks. They present the novel techniques used in the application of genetic algorithms. First, the genetic algorithm is configured to use an approximate evaluation in order to reduce significantly the computation required. In particular, though the desired classifiers are counterpropagation networks, they use a nearest-neighbor classifier to evaluate features sets and show that the features selected by this method are effective in the context of counterpropagation networks. Second, a method called the training set sampling in which only a portion of the training set is used on any given evaluation, is proposed. Computational savings can be made using this method, i.e., evaluations can be made over an order of magnitude faster. This method selects feature sets that are as good as and occasionally better for counterpropagation than those chosen by an evaluation that uses the entire training set.     

Dialogue modelling of graphical user interfaces with a production system

In systems development it is essential for a piece of software to be able effectively to incorporate the requirements of the particular task domain that it is intended to address. This paper describes an approach that uses dialogue modelling to carry the requirements derived from task analysis through to the implementation phase of development. A notation based on production systems is used to develop an abstract specification of user and system behaviour which can subsequently be used as the basis for the implementation. The requirements for a computer-based tool are also discussed, with particular attention being given to ways in which the communication and reasoning about such a dialogue design can be supported.     

ConceptBase — A deductive object base for meta data management

Deductive object bases attempt to combine the advantages of deductive relational databases with those of object-oriented databases. We review modeling and implementation issues encountered during the development of ConceptBase, a prototype deductive object manager supporting the Telos object model. Significant features include: 1) The symmetric treatment of object-oriented, logic-oriented and graph-oriented perspectives, 2) an infinite metaclass hierarchy as a prerequisite for extensibility and schema evolution, 3) a simple yet powerful formal semantics used as the basis for implementation, 4) a client-server architecture supporting collaborative work in a wide-area setting. Several application experiences demonstrate the value of the approach especially in the field of meta data management.     

Update rates and fidelity in virtual environments

Interaction is the primary characteristic of a Virtual Environment and update rate is normally taken as an index or measure of the interactivity of the system. The speed of many systems is dictated by the slowest component which is often the Computer Image Generator (CIG). It is common for the workload of the CIG to vary and hence the performance of the system. This paper shows how a variable update rate can produce undesirable results. Two solutions to this problem are presented: service degradation and worst-case. In the case of the CIG, service degradation would require the quality of the image to be reduced such that the time taken never exceeds a given deadline. The worst-case technique works by finding the longest time taken to render any view and then uses that as the deadline for completion. The support of predictive methods is one of several benefits of this approach. An implementation of the worst-case technique is described which takes finer control over the CIG than usual and may be applied to many existing systems with little modification.     

Why cognitive science is not formalized folk psychology

It is often assumed that cognitive science is built upon folk psychology, and that challenges to folk psychology are therefore challenges to cognitive science itself. We argue that, in practice, cognitive science and folk psychology treat entirely non-overlapping domains: cognitive science considers aspects of mental life which do not depend on general knowledge, whereas folk psychology considers aspects of mental life which do depend on general knowledge. We back up our argument on theoretical grounds, and also illustrate the separation between cognitive scientific and folk psychological phenomena in a number of cognitive domains. We consider the methodological and theoretical significance of our arguments for cognitive science research.     

An objective, entropy-based approach to evaluating migration issues in computer IS

Recent breakthroughs in computing technology have created a set of perplexing new problems for information systems (IS) professionals. These revolve around decisions to be made about replacing current systems with newer technology, upgrading existing systems, and migrating to other platforms or environments. Many decision makers must rely on subjective assessments, such as their instincts or the recommendation of vendors rather than on an objective analysis of their information needs and how they can be met by various system alternatives. A model to quantify these issues, providing an objective measure for comparing system alternatives, including migration, would be valuable. Such a model is demonstrated here; it uses the Shannon-Weaver entropy model in conjunction with quality measures to quantify actual and potential system effectiveness.