Are we justified in inferring a general rule from observations that frequently confirm it? This is the usual statement of the problem of induction. The present paper argues that this question is relevant for the understanding of Machine Learning, but insufficient. Research in Machine Learning has prompted another, more fundamental question: the number of possible rules grows exponentially wi th...

Technology advances allow integrating on a single chip entire system, including memories and peripherals. The test of these devices is becoming a major issue for manufacturing industries. This paper presents a methodology for inducing testprograms similar to genetic programming. However, it includes the ability to explicitly specify registers and resorts to directed acyclic graphs instead of tr...

Although recurrent neural nets have been moderately successful in learning to emulate nite-state machines (FSMs), the continuous internal state dynamics of a neural net are not well matched to the discrete behavior of an FSM. We describe an architecture, called DOLCE, that allows discrete states to evolve in a net as learning progresses. dolce consists of a standard recurrent neural net trained...

We have witnessed the research progress of machine translation from phrase/syntax-based to semanticsbased and from single sentence-based to discourse and document-based. This talk presents our work of word sense-based translation model for statistical machine translation, which is one of semantics-based SMT research at word sense level. The sense in which a word is used determines the translati...

This paper discusses the integration of traditional abductive and inductive reasoning methods in the development of machine learning systems. In particular, the paper discusses our recent work in two areas: 1) The use of traditional abductive methods to propose revisions during theory re nement, where an existing knowledge base is modi ed to make it consistent with a set of empirical data; and ...

Most textbooks on electric machines present a classical five-element constant impedance equivalent circuit for modeling polyphase induction machines operating under balanced polyphase sinusoidal steady-state conditions. Yet it is known for cage rotor machines that the rotor element impedances vary significantly with rotor j-equency. Research is in progress to determine a better ac equivalent ci...

A new dual stator winding induction machine drive is described in this paper. The proposed induction machine consists of a standard squirrel-cage rotor and a stator with two separate windings wound for a dissimilar number of poles. Each stator winding is fed from an independent variable-frequency variablevoltage inverter. The proposed drive offers such advantages as speed sensor less operation,...

problem of generating a model to recognize any string is how to generate one that is generalized enough to accept strings with similar patterns and, at the same time, is specific enough to reject the non-target strings. This research focus on generating a model in the form of a state machine to recognize strings derived from the direction information of character's images. The state machine ind...

Turing machines are playing an increasingly significant role in Computer Science domains such as bioinformatics. Instead of directly formulating a solution to a problem, a Turing machine which produces a solution algorithm is generated. The original problem is reduced to that of inducing an acceptor for a recursively enumerable language or a Turing machine transducer. This paper reports on a ge...

In this paper, we are interested, in a first time, at the study and the implementation of a V/f control for induction machine in real time. After, We are attached to a comparison of the results by simulation and experiment for, speed responses, flux and currents of the real machine, with a DSPACE card and model established by classical identification (Direct Current test , blocked-rotor test, n...