A b s t r a c t A neural network for classifcation problems with linguistic terms is proposed. A fuzzy input is represented as a LR-type fizzy set. A generalized pocket algorithm, called f izzy pocket algorithm, that utilizes .IR-type fuzzy sets operations and defuzziJication method is first applied to train a linear threshold unit ( LTU ). This LTU node will classrfj, as many fuzzy input insta...

Radiography plays an important role in detection of interproximal caries. The aim of study is to compare diagnostic ability of photo stimulable phosphor (PSP) with direct measurement using stereomicroscope in detecting proximal caries. Hundred proximal surfaces of 50 extracted human posterior teeth were radiographed with dental X-ray unit. The image receptors used was storage phosphor plate Vis...

Kearns et al. [18] de ned two notions for learning a distribution D. The rst is with generator, where the learner presents a generator that outputs a distribution identical or close to D. The other is with an evaluator, where the learner presents a procedure that on input x evaluates correctly (or approximates) the probability that x is generated by D. They showed an example where e cient learn...

In 2005, the Flemish/Dutch programme STEVIN supported the project N-Best which has the goal to evaluate the performance of present-day large vocabulary continuous speech recognition (LVCSR) systems for the Dutch language. For a number of years, several research groups in Flanders and the Netherlands have studied various aspects of LVCSR systems for Dutch. However, sofar is is hard to compare th...

Attribute grammars (AGs) were introduced by Knuth in 1968. The addition of attributes and semantic rules to Context Free Grammars (CFG), augmented their expressional capabilities, making them, by this way, a really useful tool for a considerable number of applications. However, the additional complexity imposed by the added characteristics, dictates the need for hardware solutions for the whole...

Finding the optimal value for a problem is usual in many areas of knowledge where in many cases it is needed to solve Nonlinear Optimization Problems. For some of those problems it is not possible to determine the expression for its objective function and/or its constraints, they are the result of experimental procedures, might be non-smooth, among other reasons. To solve such problems it was i...

In this demo proposal, we describe REEF, a framework that makes it easy to implement scalable, fault-tolerant runtime environments for a range of computational models. We will demonstrate diverse workloads, including extract-transform-load MapReduce jobs, iterative machine learning algorithms, and ad-hoc declarative query processing. At its core, REEF builds atop YARN (Apache Hadoop 2’s resourc...

We describe the architecture of an evolving algebra partial evaluator, a program which specializes an evolving algebra with respect to a portion of its input. We discuss the particular analysis, specialization, and optimization techniques used and show an example of its use.

In this paper, we discuss the evaluation measures proposed in a number of recent papers associated with the TUNA project1, and which have become an important component of the First NLG Shared Task and Evaluation Campaign (STEC) on attribute selection for referring expressions generation. Focusing on reference to individual objects, we discuss what such evaluation measures should be expected to ...

A board position evaluator is a crucial component for strong computer play in many games such as checkers, chess, and Reversi. The board evaluator is typically trained using pre-existing game data, an approach which is generally non-optimal, especially in the early stages of a game. Instead, we propose a new method which relies on Minimax search to train a series of models backwards from the en...