ppxscal/embedding_network huggingface dataset:
Temporal association rule methodologies for geo-spatial decision support*
Authors: Sherri Kay Weitl Harms
Venue:  (2002)

This dissertation presents data mining algorithms that enable knowledge discovery in the framework of an intelligent, distributed Geo-spatial Decision Support System (GDSS). It provides an overview of the GDSS framework and uses the National Agricultural Decision Support System (NADSS) [17] to demonstrate the effectiveness of building knowledge discovery into a GDSS.The data mining approaches that are developed, Representative Episodal Association Rules (REAR), and Minimal Occurrences With Constraints and Time Lags (MOW-CATL), facilitate knowledge discovery for sequential data mining problems that have groupings of events that occur close together, even if they occur relatively infrequently over the entire dataset. They work well for problems that have periodic occurrences when the signature of one sequence is present in other sequences, even when the multiple sequences are not globally correlated or spatially co-located. They also are able to handle a delay in time between the occurrence of the signature and the effect in the other sequences. Because of their flexibility, these data mining algorithms are well suited to handle knowledge discovery needs within the GDSS framework. For the REAR approach, formal concept analysis is employed to develop the notion of frequent closed episodes from temporal data. The concept of representative association rules [35] is formalized in the context of event sequences. Constraints are used to target highly significant rules between infrequently occurring events. The REAR approach results in a significant reduction in the number of rules generated as compared to previous methods, while maintaining the minimum set of relevant association rules and retaining the ability to generate the entire set of association rules with respect to the given constraints. MOWCATL is an efficient method for mining frequent sequential association rules from multiple data sets with a time lag between the occurrence of an antecedent sequence and the corresponding consequent sequence. This approach finds patterns in one or more sequences that precede the occurrence of patterns in other sequences, with respect to user-specified antecedent and consequent constraints. The aim of this dissertation is to enhance the body of work in the area of data mining by using representative association rules [35], closures [56], constraints [61], and time lags in the context of event sequences. It also shows how these methods can enable knowledge discovery in the context of a GDSS, and provide examples of their application to the drought risk management problem. *This research was supported in part by NSF Digital Government Grant No. EIA-0091530 and NSF EPSCOR, Grant No. EPS-0091900.
Run-time support for dynamically reconfigurable computing systems
Authors: Martyn Edwards, Peter Green
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2003)

Reconfigurable computing systems normally consist of an instruction-set processor connected to a block of reconfigurable logic. The reconfigurable logic, for example, an field programmable gate arrays (FPGA), can usually be adapted during the run-time of an application to perform different tasks. This paper describes a novel FPGA support system (FSS) that facilitates the execution of hardware-based tasks on a reconfigurable Xilinx 6264 FPGA connected to an ARM 7 processor. The FSS provides the mechanisms to support the placement, execution, and removal of tasks on the FPGA. A key feature of the FSS is the ability to provide communication facilities between concurrently active hardware and software tasks during the run-time of an application. The design, implementation and status of the FSS are discussed, together with initial results based on the implementation of a wavelet image compression application. The paper concludes by considering how our experiences with this system have influenced the development of an enhanced FSS for the later generation of Xilinx Virtex FPGAs.
Classification of Web Documents Using a Naive Bayes Method
Authors: Yong Wang, Julia Hodges, Bo Tang
Venue: Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (2003)

This paper presents an automatic document classification system, WebDoc, which classifies Web documents according to the Library of Congress classification scheme. WebDoc constructs a knowledge base from the training data and then classifies the documents based on information in the knowledge base. One of the classification algorithms used in WebDoc is based on Bayes' theorem from probability theory. This paper focuses upon three aspects of this approach: different event models for the naive Bayes method, different probability smoothing methods, and different feature selection methods. In this paper, we report theperformance of each method in terms of recall, precision, and F-measures. Experimental results show that the WebDoc system can classify Web documents effectively and efficiently.
Topology properties of Ad hoc networks with random waypoint mobility
Authors: Christian Bettstetter
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (2003)

Given is a wireless multihop network with n nodes moving according to the random waypoint model on a system area of size A. Each node has a fixed transmission range r0. We derive a closed-form approximation for the critical (r0, n)-pairs that are needed to keep the mobile network connected during at least P(con)=99% of the time. In addition, we calculate the average degree &mu; experienced by a node during its movement and the node-to-node distance distribution f s(s).
Sampling the Disparity Space Image
Authors: Richard Szeliski, Daniel Scharstein
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

Abstract--A central issue in stereo algorithm design is the choice of matching cost. Many algorithms simply use squared or absolute intensity differences based on integer disparity steps. In this paper, we address potential problems with such approaches. We begin with a careful analysis of the properties of the continuous disparity space image (DSI) and propose several new matching cost variants based on symmetrically matching interpolated image signals. Using stereo images with ground truth, we empirically evaluate the performance of the different cost variants and show that proper sampling can yield improved matching performance.
Formalization of information hiding design methods
Authors: David Alex Lamb, Kevin A. Schneider
Venue: Proceedings of the 1992 conference of the Centre for Advanced Studies on Collaborative research - Volume 1 (1992)

The theory-model paradigm views the design verification problem as checking whether a database of design facts (the model) satisfies the type checking and other design rules of a design method (the theory). We present an abstract theory of modular information-hiding design methods, which captures aspects of many different languages (potentially including Modula, C, and Ada). We specialize the theory for the Turing Plus programming language, and validate it by extracting a design database from a pre-existing Turing Plus program, TXL, and verifying that it satisfies the design rules.This work is part of the Advanced Software Design Technology project, which aims to produce a prototype tool, 4Thought, to aid software designers. Design theories such as ours would become part of a 4Thought library.
Note: Ranking DMUs with Infeasible Super-Efficiency DEA Models
Authors: Mei Xue, Patrick T. Harker
Venue: Management Science (2002)

It has been suggested in the data envelopment analysis (DEA) literature that it is impossible to obtain a full ranking of decision-making units (DMUs) when infeasible subproblems arise in the so-called super-efficiency DEA models under different returns to scale (RTS) assumptions other than constant returns to scale (CRS) andconsequently the application of the super-efficiency DEA models under different RTS conditions other than CRS should be restricted. The implications of the infeasibility in super-efficiency DEA models with respect to the efficiency ranking of the DMUs is explored. Based on the analysis, we show that it is still possible to obtain the full ranking of the entire observation set when infeasibilities arise in super-efficiency DEA models.
Probabilistic Space-Time Video Modeling via Piecewise GMM
Authors: Hayit Greenspan, Jacob Goldberger, Arnaldo Mayer
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2004)

Abstract--In this paper, we describe a statistical video representation and modeling scheme. Video representation schemes are needed to segment a video stream into meaningful video-objects, useful for later indexing and retrieval applications. In the proposed methodology, unsupervised clustering via Gaussian mixture modeling extracts coherent space-time regions in feature space, and corresponding coherent segments (video-regions) in the video content. A key feature of the system is the analysis of video input as a single entity as opposed to a sequence of separate frames. Space and time are treated uniformly. The probabilistic space-time video representation scheme is extended to a piecewise GMM framework in which a succession of GMMs are extracted for the video sequence, instead of a single global model for the entire sequence. The piecewise GMM framework allows for the analysis of extended video sequences and the description of nonlinear, nonconvex motion patterns. The extracted space-time regions allow for the detection and recognition of video events. Results of segmenting video content into static versus dynamic video regions and video content editing are presented.
Hermite WENO schemes and their application as limiters for Runge-Kutta discontinuous Galerkin method: one-dimensional case
Authors: Jianxian Qiu, Chi-Wang Shu
Venue: Journal of Computational Physics (2004)

In this paper, a class of fifth-order weighted essentially non-oscillatory (WENO) schemes based on Hermite polynomials, termed HWENO (Hermite WENO) schemes, for solving one-dimensional nonlinear hyperbolic conservation law systems is presented. The construction of HWENO schemes is based on a finite volume formulation, Hermite interpolation, and nonlinearly stable Runge-Kutta methods. The idea of the reconstruction in the HWENO schemes comes from the original WENO schemes, however both the function and its first derivative values are evolved in time and used in the reconstruction, while only the function values are evolved and used in the original WENO schemes. Comparing with the original WENO schemes of Liu et al. [J. Comput. Phys. 115 (1994) 200] and Jiang and Shu [J. Comput. Phys. 126 (1996) 202], one major advantage of HWENO schemes is its compactness in the reconstruction. For example, five points are needed in the stencil for a fifth-order WENO (WENO5) reconstruction, while only three points are needed for a fifth-order HWENO (HWENO5) reconstruction. For this reason, the HWENO finite volume methodology is more suitable to serve as limiters for the Runge-Kutta discontinuous Galerkin (RKDG) methods, than the original WENO finite volume methodology. Such applications in one space dimension is also developed in this paper.
The ACORN multi-agent system
Authors: Stephen Marsh, Ali A. Ghorbani, Virendra C. Bhavsar
Venue: Web Intelligence and Agent Systems (2003)

ACORN (Agent-based Community Oriented Routing Network) is a distributed multi-agent architecture for the search, distribution and management of information in networks. ACORN utilizes the concept of 'information as agent' together with an application of Stanley Milgram's Small World Problem (the idea of Six Degrees of Separation) in order to route individual items of information around networks of people and agents. The ACORN ideal is to achieve a state where a web of users is created such that information distribution, queries and search, and browsing behaviour are encapsulated in a single adaptive architecture which learns community behaviour and knowledge in order to route agents to relevant destinations (users).This paper describes the ACORN architecture and its implementation. We introduce a novel idea of agent meeting places, or Cafés, to carry out community-based information sharing among mobile agents in ACORN. ACORN is compared with similar work, and evaluations of ACORN for information sharing among mobile agents are described.Applications of ACORN include Business to Business and Business to Consumer based e-Commerce solutions, virtual community creation and support systems, peer reviewing systems, and personalized directed information handling (search, dissemination and growth).
The computational science major at SUNY Brockport
Authors: Leigh J. Little
Venue: Future Generation Computer Systems (2003)

The field of computational science is a recent addition to academic study. While the content of such an education is generally agreed upon, effective methods for imparting this knowledge are still being investigated. This paper describes the current state of the computational science degree programs at SUNY Brockport and the successes that have been obtained. Issues relating to the implementation of such programs in the context of a small, liberal arts college are also discussed.
On Local Expansion of Vertex-Transitive Graphs
Authors: András Lukács
Venue: Combinatorics, Probability and Computing (1998)

Let X be a vertex-transitive graph and let S be an arbitrary finite subset of its vertices. Denote by @&part;S the set of vertices adjacent to S but not in S. Babai and Szegedy proved that for an infinite, connected, locally finite X with subexponential growth we have***** Insert equation here *****where d(S) is the diameter of S. The aim of this note is to provide a slightly better, tight lower bound on this quantity. We prove that***** Insert equation here *****under the same conditions.
Curve Tracer with a Personal Computer and LabvIEW
Authors: E. Moreno-García
Venue: Proceedings of the 14th International Conference on Electronics, Communications and Computers (2004)

The circuits and programs that conform theprototype of a curve tracer, operated under the controlof a personal computer (PC) are presented. Theprototype uses a data acquisition board that generatesthe signals applied to the base and collector terminals ofthe tracer. This board also carries out the necessarymeasurements to trace the characteristic curves of thedevice under test. It was designed an additional boardwith the appropriate circuit for the base and collectorterminals. A program was written in the graphicallanguage G of LabViewTM to program the completeoperation of the tracer and to control the externalcircuits. The developed program presents the results in agraphic indicator as a family of curves, it can store in afile the parameters of the characterization process, andalso, the program can open files to plot the informationstored.
A Fast Algorithm for Computing Hypergraph Transversals and its Application in Mining Emerging Patterns
Authors: James Bailey, Thomas Manoukian, Kotagiri Ramamohanarao
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

Computing the minimal transversals of a hypergraph isan important problem in computer science that has significantapplications in data mining. In this paper, we present anew algorithm for computing hypergraph transversals andhighlight their close connection to an important class ofpatterns known as emerging patterns. We evaluate our techniqueon a number of large datasets and show that it out-performsprevious approaches by a factor of 9-29 times.
Learning over sets using kernel principal angles
Authors: Lior Wolf, Amnon Shashua
Venue: The Journal of Machine Learning Research (2003)

We consider the problem of learning with instances defined over a space of sets of vectors. We derive a new positive definite kernel f(A,B) defined over pairs of matrices A,B based on the concept of principal angles between two linear subspaces. We show that the principal angles can be recovered using only inner-products between pairs of column vectors of the input matrices thereby allowing the original column vectors of A,B to be mapped onto arbitrarily high-dimensional feature spaces.We demonstrate the usage of the matrix-based kernel function f(A,B) with experiments on two visual tasks. The first task is the discrimination of "irregular" motion trajectory of an individual or a group of individuals in a video sequence. We use the SVM approach using f(A,B) where an input matrix represents the motion trajectory of a group of individuals over a certain (fixed) time frame. We show that the classification (irregular versus regular) greatly outperforms the conventional representation where all the trajectories form a single vector. The second application is the visual recognition of faces from input video sequences representing head motion and facial expressions where f(A,B) is used to compare two image sequences.
A Parallel Architectural Implementation Of The New Three-Step Search Algorithm For Block Motion Estimation
Authors: Kavish Seth, P. Rangarajan, S. Srinivasan, V. Kamakoti, V. Bala Kuteshwar
Venue: Proceedings of the 17th International Conference on VLSI Design (2004)

This paper describes a fully pipelined parallelarchitecture for the New Three Step Search (NTSS)hierarchical search block-matching algorithm for theestimation of small motions in video coding. Techniquesfor reducing external memory accesses are alsodeveloped. The proposed architecture produces efficientsolution for real-time motion estimation required in videoapplications with low memory bandwidth requirement.This architecture is the best tradeoff in terms of hardwareoverload and speed among the all-existing Three StepSearch (TSS) architectures and is also suitable forestimation of small motion in video coding. Thisarchitecture can be used for various video applicationsfrom low bit-rate video to HDTV systems.
A case for fractured mirrors
Authors: Ravishankar Ramamurthy, David J. DeWitt, Qi Su
Venue: The VLDB Journal &mdash; The International Journal on Very Large Data Bases (2003)

Abstract.The decomposition storage model (DSM) vertically partitions all attributes of a table and has excellent I/O behavior when the number of attributes accessed by a query is small. It also has a better cache footprint than the standard storage model (NSM) used by most database systems. However, DSM incurs a high cost in reconstructing the original tuple from its partitions. We first revisit some of the performance problems associated with DSM and suggest a simple indexing strategy and compare different reconstruction algorithms. Then we propose a new mirroring scheme, termed fractured mirrors, using both NSM and DSM models. This scheme combines the best aspects of both models, along with the added benefit of mirroring to better serve an ad hoc query workload. A prototype system has been built using the Shore storage manager, and performance is evaluated using queries from the TPC-H workload.
Automatic Verification of Safety and Liveness for XScale-Like Processor Models Using WEB Refinements
Authors: Panagiotis Manolios, Sudarshan K. Srinivasan
Venue: Proceedings of the conference on Design, automation and test in Europe - Volume 1 (2004)

We show how to automatically verify that complex XScale-like pipelined machine models satisfy the same safety and liveness properties as their corresponding instruction set architecture models, by using the notion of Well-founded Equivalence Bisimulation (WEB) refinement. Automation is achieved by reducing the WEB-refinement proof obligation to a formula in the logic of Counter arithmetic with Lambda expressions and Uninterpreted functions (CLU). We use the tool UCLID to transform the resulting CLU formula into a Boolean formula, which is then checked with a SAT solver. The models we verify include features such as out of order completion, precise exceptions, branch prediction, and interrupts. We use two types of refinement maps. In one, flushing is used to map pipelined machine states to instruction set architecture states; in the other, we use the commitment approach, which is the dual of flushing, since partially completed instructions are invalidated. We present experimental results for all the machines modeled, including verification times. For our application, we found that the time spent proving liveness accounts for about 5% of the overall veri.cation time.
A modular reduction for GCD computation
Authors: Sidi Mohammed Sedjelmaci
Venue: Journal of Computational and Applied Mathematics (2004)

Most of integer GCD algorithms use one or several basic transformations which reduce at each step the size of the inputs integers u and v. These transformations called reductions are studied in a general framework. Our investigations lead to many applications such as a new integer division and a new reduction called Modular Reduction or MR for short. This reduction is, at least theoretically, optimal on some subset of reductions, if we consider the number of bits chopped by each reductions. Although its computation is rather difficult, we suggest, as a first attempt, a weaker version which is more efficient in time. Sequential and parallel integer GCD algorithms are designed based on this new reduction and our experiments show that it performs as well as the Weber's version of the Sorenson's k-ary reduction.
Cati dance: self-edited, self-synchronized music video
Authors: Tristan Jehan, Michael Lew, Cati Vaucelle
Venue: ACM SIGGRAPH 2003 Sketches Applications (2003)

This sketch presents a real-time system that aims to bridge a gap between machine listening technology, and self-editing, self-synchronizing video: a movie organizes itself from "listening" to music. In our current demonstration, a series of short video clips of "Cati" dancing, originally shot at different tempi, are arbitrarily sequenced, always in sync with the analyzed beat, i.e., if the music slows down, the dance slows down accordingly. When no beat is found, e.g., the music is mellow, then Cati stops dancing and waits, apparently bored.
A Parameterized Cost Model to Order Classes for Class-based Testing of C ++ Applications
Authors: Brian A. Malloy, Peter J. Clarke, Errol L. Lloyd
Venue: Proceedings of the 14th International Symposium on Software Reliability Engineering (2003)

In this paper we present the design and implementationof a Class Ordering System that is driven by a parameterizedcost model. The parameters to the modelassign weights to the edge types that describe the relationshipsbetween the classes in the graphical representationof the program. The nodes in the graph are classesand the edges express relationships between the classes.Previous research has included three or four edge typesin the graph. However, to accommodate the full complementof C++ language constructs, which include templateclasses and functions and nested classes, we extend thegraph to include six edge types. The parameters to thecost model can be tuned to remove certain types of edgesin an attempt to reduce the cost of the testing effort orto reduce the cost of breaking cycles in the graph. Ourcase study indicates that inclusion of inheritance edgesin cycle breaking considerations may reduce the numberof edge removals by a factor of two or more.