This paper presents a method for evaluating functions based on piecewise polynomial approximation with a novel hierarchical segmentation scheme. The use of a novel hierarchy scheme of uniform segments and segments with size varying by powers of two enables us to approximate nonlinear regions of a function particularly well. This partitioning is automated: efficient look-up tables and their coef...

Using SVMs for named entity recognition, we are often confronted with the multi-class problem. Larger as the number of classes is, more severe the multiclass problem is. Especially, one-vs-rest method is apt to drop the performance by generating severe unbalanced class distribution. In this study, to tackle the problem, we take a two-phase named entity recognition method based on SVMs and dicti...

In this paper, we propose a deadlock-free routing in irregular networks using pre x routing. Pre x routing is a special type of routing with a compact routing table associated with each node (processor). Basically, each outgoing channel of a node is assigned a special label and an outgoing channel is selected if its label is a pre x of the label of the destination node. Node and channel labelin...

We propose several simple interpolations of the isotherms for real fluids in the region below the binodal curve, where data concerning the equation of state is absent, especially in the thermodynamically prohibited region. All interpolations satisfy the boundary conditions at the points on the binodal curve. The Maxwell rule is also fulfilled. As an example,we construct several isotherms for re...

A deadlock-free multicast scheme called prefix multicasting in irregular networks is studied. In prefix routing, a compact routing table is associated with each node (processor). Basically, each outgoing channel of a node is assigned a special label and an outgoing channel is selected if its label is a prefix of the label of the destination node. Node and channel labeling in an irregular networ...

Linguistic decision tree (LDT) [7] is a classification model based on a random set based semantics which is referred to as label semantics [4]. Each branch of a trained LDT is associated with a probability distribution over classes. In this paper, two hybrid learning models by combining linguistic decision tree and fuzzy Naive Bayes classifier are proposed. In the first model, an unlabelled ins...