Parallel algorithms for recognizing and representing interval orders are proposed for differ. ent models of parallel random access machines (PRAM). The algorithms accept as input a transitively~losed directed graph with N nodes and M edges. They run in time O0og N) with O(N + M~ processors and O{N + M} space and in co , tam time with O(N z) proces~rs and O{N ~) space depending on the data struc...

We describe our partially completed work on a set of morphological algorithms for recognizing handwritten numerals. The basic morphological operations { dilation, erosion, opening and closing { are used to extract characteristic features of these characters and check for their appropriate topological con guration. The paper describes the key shape characterization for two groups containing a to...

The goal of MuSA is to create a robust and reliable system for recognizing and visualizing tonal patterns using the Spiral Array model for tonality [1]. This endeavor requires the developing of algorithms for abstracting and extracting pitch/time structures (see Figure 1) in music information. The resulting algorithms are fundamental tools for automated transcription, computer music analysis, c...

We present a new algorithm, called MCS-M, for computing minimal triangulations of graphs. Lex-BFS, a seminal algorithm for recognizing chordal graphs, was the genesis for two other classical algorithms: Lex-M and MCS. Lex-M extends the fundamental concept used in Lex-BFS, resulting in an algorithm that also computes a minimal triangulation of an arbitrary graph. MCS simplified the fundamental c...

The competency to detect and to recognize the different denomination of coins is an essential expertise in the human beings life. This paper represents different algorithms for the detection and the recognition of coins which are highly overlapped. The proposed system includes three principal steps detection, extraction and recognition. This system is efficient in detecting and recognizing the ...

Goal recognition is the problem of recognizing the goal of an agent based on an incomplete sequence of observations. Recognizing goals with minimal domain knowledge as an agent executes its plan requires efficient algorithms to sift through a large space of hypotheses. In this paper, we develop an online approach to recognize goals in both continuous and discrete domains using a combination of ...

Wireless sensor networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing and tracking. In this paper, we study the problem of recognizing the boundary nodes of a WSN. We firstly identify the factors that influence...

Online goal recognition is the problem of recognizing the goal of an agent based on an incomplete sequence of incrementally revealed observations as early along the recognition process as possible. Recognizing goals with minimal domain knowledge as an agent executes its plan requires efficient algorithms to sift through a large space of hypotheses. We develop an online approach to goal recognit...

We present a machine learning approach for classifying sentences as one-liner jokes or normal sentences. We use no deep analysis of the meaning to try to see if it is humorous, instead we rely on a combination of simple features to see if these are enough to detect humor. Features such as word overlap with other jokes, presence of words common in jokes, ambiguity and word overlap with common id...