Accurate modeling of the wind energy conversion system is necessary to design and implementation of the control loop for the generator and the frequency converter, in order to extract maximum power from the wind and to investigate the effects of interconnection between wind farms and power system. In this paper the combination of a permanent magnet synchronous generator loaded with a diode rect...

This paper discusses and illustrates the application of Empirical Modelling (EM), as developed by the author and his collaborators, to computer programming. The discussion centres on the perspective EM gives on procedural and experiential vs. declarative and logical approaches to knowledge representation. The illustration focuses on demonstrating the potential for pedagogical use of EM in teach...

We show that, with k-set consensus, any number of processes can emulate k state machines of which at least one progresses. This generalizes the celebrated universality of consensus which enables to build a state machine that always progresses. Besides some interesting extensions and even potential “practical” applications, theoretically, a fundamental ramification of our main result, derived by...

We describe a Byzantine-fault-tolerant state machine replication algorithm that reduces computation and communication costs in the fault-free case, and is reasonably efficient even in the presence of faults. Such an algorithm is practically significant, because failures are the exception than the norm, and much of a system’s runtime is fault-free. The algorithm is geared towards applications th...

In this paper, we consider the problem of extending existing submodule construction techniques that have been developed for finite state models into more expressive and compact behavioral models that handle data through parameterized interactions, state variables and simple guards. We provide a behavioral model based on extended Input-Output Automata and describe an algorithm that provides the ...

The problem of machine translation can be viewed as consisting of two subproblems (a) Lexical Selection and (b) Lexical Reordering. We propose stochas-tic nite-state models for these two subproblems in this paper. Stochastic nite-state models are ee-ciently learnable from data, eeective for decoding and are associated with a calculus for composing models which allows for tight integration of co...

Information hiding is a long established principle in software engineering. However, in the context of finite state machines a contrary principle of information exposure has been suggested. Using a simple example, we examine why a proven abstraction mechanism which works well in other areas may be less successful when applied to a finite state machine model. After using Statecharts [3] to speci...

A method of universal binary entropy coding using simple state machines is presented. We provide a natural rationale for the use of state machines. We discuss the building of state machines which produce uniquely decodable bit streams. Some state machines implement known codes, while others implement finite or even infinite variable length to variable length codes. Once a decodable state machin...

We overview a series of our research on implementing finite automata in vitro and in vivo in the framework of DNA-based computing [2, 3]. First, we employ the lengthencoding technique proposed and presented in [5, 4] to implement finite automata in test tube. In the length-encoding method, the states and state transition functions of a target finite automaton are effectively encoded into DNA se...

In this paper, we consider how to hide information into finite state machine (FSM), one of the popular computation models. The key advantage of hiding information in FSM is that the hidden information becomes inexpensive to retrieve, yet still hard to remove or delete. This is due to the fact that verifying certain FSM properties is easy, but changing them requires efforts equivalent to redoing...