Jennifer Seitzer

Optimal algorithms for the channel-assignment problem on a reconfigurable array of processors with wider bus networks

The computation model on which the algorithms are developed is the reconfigurable array of processors with wider bus networks (abbreviated to RAPWBN). The main difference between the RAPWBN model and other existing reconfigurable parallel processing systems is that the bus width of each network is bounded within the range [2,[/spl radic/(N)]]. Such a strategy not only saves the silicon area of the chip as well as increases the computational power enormously, but the strategy also allows the execution speed of the proposed algorithms to be tuned by the bus bandwidth. To demonstrate the computational power of the RAPWBN, the channel-assignment problem is derived in this paper. For the channel-assignment problem with N pairs of components, we first design an O(T + [N//spl omega/]) time parallel algorithm using 2N processors with a 2N-row by 2N-column bus network, where the bus width of each bus network is /spl omega/-bit for 2 /spl les/ /spl omega/ /spl les/ [/spl radic/N] and T = [log/sub /spl omega//N] + 1. By tuning the bus bandwidth to the natural log N-bit and the extended N/sup 1/c/-bit (N/sup 1/c/ > log N) for any constant c and c /spl ges/ 1, two more results which run in O(log N/log log N) and O(1) time, respectively, are also derived. When compared to the algorithms proposed by Olariu et al. [17] and Lin [14], it is shown that our algorithm runs in the equivalent time complexity while significantly reducing the number of processors to O(N).

A paradigm for detecting cycles in large data sets via fuzzy mining

Traditional data mining algorithms identify associations in data that are not explicit. Cycle mining algorithms identify meta-patterns of these associations depicting inferences forming chains of positive and negative rule dependencies. This paper describes a formal paradigm for cycle mining using fuzzy techniques. To handle cycle mining of large data sets, which are inherently noisy, we present the /spl alpha/-cycle and /spl beta/-cycle, the underlying formalism of the paradigm. Specifically, we show how /spl alpha/-cycles, desirable cycles, can be reinforced such that complete positive cycles are created, and how /spl beta/-cycles can be identified and weakened. To accomplish this, we introduce the concept of /spl Omega/ nodes that employ an alterability quantification, as well as using standard rule and node weighting (with associated thresholds).

Fast computation of the 3-D Euclidean distance transform on the EREW PRAM model

In a two or three-dimensional image array, the computation of Euclidean distance transform (EDT) is an important task. With the increasing application of 3D voxel images, it is useful to consider the distance transform of a 3D digital image array. Because the EDT is a global operation, it is prohibitively time consuming when performing the EDT for image generation. In order to provide the efficient transform computations, parallelism is employed. In this paper we first derive several important geometry relations and properties among parallel planes. We then develop a parallel algorithm for the three-dimensional Euclidean distance transform (3D-EDT) on the EREW PRAM computation model. The time complexity of our parallel algorithm is O(log/sup 2/ N) for an N/spl times/N/spl times/N image array.

Extending the shortest-path swarm algorithm to cycle detection

Swarm programming is a method that uses many simple agents to collectively perform a complex task. The approach is based on the emergent behavior of a swarm of simple agents as they interact with each other and the environment. The swarming algorithms of our work extend the shortest path swarm agent algorithm. In this paper, we present four swarm algorithms used to discover graph cycles, along with respective performance analyses

Using rays cycle mining to clarify sentiment analysis

The goal of sentiment analysis is to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. Cycles are of use in identifying particularly interesting patterns of opinion. In this paper we use RAY cycle mining to determine sentiment. RAY cycles are defined and an example is shown to illustrate how RAY cycles can be of benefit in sentiment analysis.

Here today, gone today ELEGE: Ephemeral links — Encrypt, Glimpse, and Eliminate

Web structure mining attempts to use modeling techniques, such as graph theory, to represent the connection between web pages through hyperlinks, on the Internet. Static or flat web pages remain on a web server until a human removes them. Dynamic and active web pages are created by programs at the time a user accesses a hyperlink. This inclusion of dynamic content by the Internet has allowed its structure to dynamically explode and morph. In this work, we introduce the entity of the ephemeral link, which induces an inverse morphing operation. We present a methodology and implementation where pages are dynamically removed in real time by a web-user accessing the page and clicking these links. In this paper, we emphasize the justification for ephemeral links in the realm of high security and present the architecture and algorithms of system ELEGE (read “elegy”) that implements the creation and use of ephemeral links.

A data parallel implementation of an intelligent reasoning system

We present an implementation of a data parallel system. A sequential knowledge-based deductive and inductive system, INDED, is transformed into a parallel system. In this parallel system the learning algorithm, the fundamental component of the induction engine, is distributed among many processors. The parallel system is implemented with a master node and several worker nodes. The master node is responsible for coordinating the activity of the worker nodes, and organizing the overall learning process. All the worker nodes share the processing of the basic induction algorithms and report their results to the master node. The goal of the data parallel system is to produce, more efficiently, rules that are equal to or better than those produced by the serial system. In this paper, we present the architecture of the parallel version of INDED, and comparison results involving execution speeds and quality of generated rules of the new parallel system to those of the serial system.

Cycle Mining in Active Database Environments

Traditional data mining algorithms identify patterns in data that are not explicit. These patterns are denoted in the form of IF-THEN rules (IF antecedent THEN consequent), where the antecedent and consequent are logical conjunctions of propositions or first-order predicates. Generally, the mined rules apply to all time periods and specify no temporal interval between antecedent detection and consequent firing. Cycle mining algorithms identify meta-patterns of these associations depicting inferences forming cyclic chains of rule dependencies. Because traditional rules comprise these cycles, the mined cycles also apply to all time periods and do not currently possess the temporal interval of applicability. An active database is one that responds to stimuli in real time, operating in the event-condition-action (ECA) paradigm where a specific event is monitored, a condition is evaluated, and one or more actions are taken. The actions often involve real-time modification of the database. In this paper, we introduce the concepts and present algorithms for mining rules with firing intervals, and intervals of applicability. Using an active database environment, we describe a real time framework that incorporates the active database concept in order to ascertain previously undefined cycles in data over a specific time interval and thereby introduce the concept of interval of discovery. Comprised of discovered rules with firing intervals and intervals of applicability, the encompassing discovered cycles also possess a variation of these attributes. We illustrate this framework with an example from an E-commerce endeavor where data is mined for rules with firing intervals and intervals of applicability, which amalgamate to form a cycle in its interval of discovery. We describe the computer system INDED, the authors implementation of cycle mining, which we are currently interfacing to an active Oracle database using triggers and PL/SQL stored procedures.