Annual Review in Automatic Programming最新文献

Significant prior work exists on scheduling for the ‘simple-tasks-single-processor’, ‘simple-tasks-multiple-processor’, and ‘complex-tasks-single-processor’, but few researchers have yet considered the ‘complex-tasks-multiple-processor’ model. We propose a new algorithm, Least Space-Time First (LSTF), to deal with the general ‘complex-task-multiple-processor’ model. We demonstrate that LSTF outperforms the Highest-Level-First, Earliest-Deadline-First and Least-Laxity-First scheduling disciplines in the sense of minimizing maximum tardiness of a set of tasks. LSTF can gracefully incorporate some realistic overhead assumptions, including context switch and communication. The Unit Precedence Graph and Soft-Precedence Edges significantly facilitate implementation of LSTF.

This paper addresses issues related to the implementation of real-time software. A proposal to enhance real-time programming systems based on C under real-time UNIX operating systems with PEARL high-level time constructs is described. The ideas have been implemented and applied to some case-studies. Experience has shown that the approach represents a powerful and expressive instrument for distributed real-time systems programming.

A concept of control for municipal waste water treatment plants is developed. The used fuzzy approach to real-time control aims at an operation of the plant that guarantees satisfactory performance of cleaning in different situations of load. The problem of nitrogen removal using flexible nitrification and denitrification volumes is tackled by means of fuzzy control. Important aspects of a simulation based analysis of the process including the structure of control are reported. Special emphasis is laid on the results obtained for conventional and fuzzy control in respect to a reduction of total inorganic nitrogen and lowering of running costs.

This text describes our generic approaches to monitoring and prognostic, emphasizing the application of learning techniques, and focuses on model-free specific supervision entities that can be realized by a learning-from-examples method. All necessary tools for the generation of a supervised learning of a process situation classifier will be outlined. Statistical feature selection and inductive numerical learning constitute the basis for the proposed architecture. A particular supervised nonparametric learning method, developed in-house, the Q^∗ -algorithm will be presented. Practical experiments for the monitoring of a lathe are carried out.

As part of the ESPRIT Projects HINT, a method for designing user interfaces, tailored for applications based on the HINT architecture, has been developed. The method consists of a set of steps, each with well defined objectives and results, and associated guidelines.

It is widely accepted that visual programming techniques can offer increased productivity and reduced costs during the programming stage of real-time systems development and to a lesser extent at other phases in the system development life cycle. It is this author's belief, however, that while visual programming languages have much to recommend them, their current usage is erroneous. Current trends will prevent visual programming languages from being successfully applied to complex real-time systems and in the development of correct systems. We present a case for visual methods of real-time system development, that recognize visual programming as a single component of a more complex development method; we conclude by briely describing one such method.

This paper describes a real-time architecture based on a deadline driven dataflow machine and the hardware implementation of the architecture in the form of resource adequate Simple-processors (S-processors). The machine-level language and a high-level visual language are described, which enable implementation-detail-free programs to be written. The implementation of a real-time system on a resource adequate S-processor architecture requires no effort to be spent on schedulability analysis for temporal correctness.

Adaptive and dynamic behaviour is seen as one of the key characteristics of next generation hard real-time systems. Whilst fixed priority pre-emptive scheduling is becoming a de facto standard in real-time system implementation, it remains inflexible in its purest form. One approach to countering this criticism is to allow optional components, not guaranteed offline, to be executed at run-time. Optional components may be guaranteed a minimum set of resources at run-time, with competing resource requests scheduled according to the best-effort approach. This allows increased dynamic behaviour and improves the utility of the system. In this paper, we discuss this integration of fixed priority and best-effort scheduling.

This paper presents the actual work in real-time planning as search [1] [2]. Based in this work we tried to solve the path planning in numerical state space. We found that precision, performance, and time were very linked. In real-time problem solving, the agent can fall in traps made of forbidden zones and to go out it, have to spend too much computing time. To solve this problem we propose a multilayer inference based in subgoals computation. An architecture based in two agents, one for low level task with the maximum precision and other for subgoals computation is proposed here.

Increasingly artificial neural networks are finding applications in a process engineering environment. Recently the Department of Trade and Industry in the UK has supported the transfer of neural technology to industry with a £5.7M campaign. As part of the campaign, the University of Newcastle and EDS Advanced Technologies Group have set up a Process Monitoring and Control Club.

This paper presents two case studies from the work of the Club. Firstly, the ability of neural networks to provide enhanced modelling performance over traditional linear techniques is demonstrated on real process data. Secondly, the ability of neural networks to capture non-linear system characteristics is exploited in a novel way in a condition monitoring exercise. The process studied in both applications is the melter stage of the BNFL Vitrification Process. The process involves the encapsulation of highly active liquid waste in glass blocks to provide a safe and convenient method of storage.