ppxscal/embedding_network huggingface dataset:
Efficient Algorithms for On-line Analysis Processing On Compressed Data Warehouses
Authors: Jianzhong Li
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Data compression is an effective technique to improve the performance of data warehouses. Aggregation and cube are important operations for on-line analytical processing (OLAP). It is a major challenge to develop efficient algorithms for aggregation and cube operations on compressed data warehouses. Many efficient algorithms to compute aggregation and cube for relational OLAP have been developed. Some work has been done on efficiently computing aggregation and cube for multidimensional data warehouses (MDWs) that store datasets in multidimensional arrays rather than in tables. However, to our knowledge, there is few to date in the literature describing aggregation algorithms on compressed data warehouses for multidimensional OLAP.
On collaborative content distribution using multi-message gossip
Authors: Yaacov Fernandess, Dahlia Malkhi
Venue: Journal of Parallel and Distributed Computing (2007)

We study epidemic schemes in the context of collaborative data delivery. In this context, multiple chunks of data reside at different nodes, and the challenge is to simultaneously deliver all chunks to all nodes. Here we explore the inter-operation between the gossip of multiple, simultaneous message-chunks. In this setting, interacting nodes must select which chunk, among many, to exchange in every communication round. We provide an efficient solution that possesses the inherent robustness and scalability of gossip. Our approach maintains the simplicity of gossip, and has low message, connections and computation overhead. Because our approach differs from solutions proposed by network coding, we are able to provide insight into the tradeoffs and analysis of the problem of collaborative content distribution. We formally analyze the performance of the algorithm, demonstrating its efficiency with high probability.
Cerebral
Authors: Aaron Barsky, Jennifer L. Gardy, Robert E. W. Hancock, Tamara Munzner
Venue: Bioinformatics (2007)

Summary: Cerebral (Cell Region-Based Rendering And Layout) is an open-source Java plugin for the Cytoscape biomolecular interaction viewer. Given an interaction network and subcellular localization annotation, Cerebral automatically generates a view of the network in the style of traditional pathway diagrams, providing an intuitive interface for the exploration of a biological pathway or system. The molecules are separated into layers according to their subcellular localization. Potential products or outcomes of the pathway can be shown at the bottom of the view, clustered according to any molecular attribute data—protein function—for example. Cerebral scales well to networks containing thousands of nodes. Availability: http://www.pathogenomics.ca/cerebral Contact: tmm@cs.ubc.ca Supplementary information: Supplementary data are available at Bioinformatics online.
Using Genetic Algorithm for Data Mining Optimization in an Image Database
Authors: Li Gao, Shangping Dai, Shijue Zheng, Guanxiang Yan
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Data Mining is rapidly evolving areas of research that are at the intersection of several disciplines, including statistics, databases, pattern recognition, and high- performance and parallel computing. In this paper, we propose a novel mining algorithm, called ARMAGA (Association rules mining Algorithm based on a novel Genetic Algorithm), to mine the association rules from an image database, where every image is represented by the ARMAGA representation. We first take advantage of the genetic algorithm designed specifically for discovering association rules. Second we propose the Algorithm Compared to the algorithm in [1], and the ARMAGA algorithm avoids generating impossible candidates, and therefore is more efficient in terms of the execution time.
Exploratory study on concurrent interaction in co-located collaboration
Authors: Christian Müller-Tomfelde, Claudia Schremmer, Anja Wessels
Venue: Proceedings of the 19th Australasian conference on Computer-Human Interaction: Entertaining User Interfaces (2007)

We present an exploratory lab study that provides observations and measures about the usage of interaction devices in co-located cooperative work situations at a tabletop display. We designed our experiment with the aim of providing a context for the collaboration that shares as many characteristics of real life as possible. Twenty-two participants were instructed to perform a shared goal task. They worked in co-located pairs on solving three sets of two jigsaw puzzles concurrently. They were allowed to use any combination of direct and indirect input device, i.e., touch and mouse, to achieve the goal. Additionally, a hidden task was imposed on the participants in the second and third puzzle task: They had to discover that pieces were mixed up between the two displayed puzzles. The role of the hidden task was to trigger spontaneous transitions from individual to collaborative work. Our observations focused on the participants' selection and usage of input devices during the task execution. Our study revealed amongst others that participants stuck to their preferred input device even when they got more engaged in coordination and communication with their partner. Our findings are based on log data, questionnaire data and video recordings.
Pattern Classifier Design by Linear Programming
Authors: F. W. Smith
Venue: IEEE Transactions on Computers (1968)

Abstract A common nonparametric method for designing linear discriminant functions for pattern classification is the iterative, or "adaptive," weight adjustment procedure, which designs the discriminant function to do well on a set of typical patterns. This paper presents a linear programming formulation of discriminant function design which minimizes the same objective function as the "fixed-increment" adaptive method. With this formulation, as with the adaptive methods, weights which tend to minimize the number of classification errors are computed for both separable and nonseparable pattern sets, and not just for separable pattern sets as has been the emphasis in previous linear programming formulations.
Programming environments
Authors: John Foderaro
Venue: ACM SIGPLAN Lisp Pointers (1988)

In this issue we feature a description of Delphi Common Lisp, an enhanced version of Kyoto Common Lisp. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Network Traffic Emulation for IDS Evaluation
Authors: Wang Yang, Jian Gong, Wei Ding, Xiong Wu
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

The Network traffic Emulation is used in generating background traffic for IDSs evaluation. The Background traffic can be used to evaluate the false positive level and the performance of the misuse IDSs and help training normal behavior profiles for anomaly IDSs. Currently the emulation methods for the background traffic are either restricted by the performance bottleneck of the software and hardware, or lack of the semantic of flow and session. So they can't satisfy the IDS evaluation requirement in highspeed network environment. After analyzing the requirement of IDSs evaluation and the characteristics of network traffic, this paper proposes a differential equation model of active flow rate. Based on the equation, a structural simulation model of network flow is constructed and used in the network traffic emulation for IDS evaluation. This model is both simple for high performance and similar to the reality. The experiments show that the model proposed can generate traffic both realistic and controllable.
Integrating Multi-Modal Circuit Features within an Efficient Encryption System
Authors: Evangelos Papoutsis, Gareth Howells, Andrew Hopkins, Klaus McDonald-Maier
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

The problem of the incorporation of pattern features with unusual distributions is well known within Pattern Recognition systems even if not easily addressed. The problem is more acute when features are derived from characteristics of given integrated electronic circuits. The current paper introduces novel efficient techniques for normalising sets of features which are highly multi-modal in nature, so as to allow them to be incorporated within a single encryption key generation system based primarily on measured hardware characteristics. The utility of the proposed system lies in the observation that the need for data sent to and from remote network nodes to be secure and verified is substantial. Security can be improved by using encryption techniques based on keys, which are based on unique properties of the individual nodes within the network. This will serve both to minimize the need for key storage and sharing as well as to validate the initiator node of a message.
Gorder: an efficient method for KNN join processing
Authors: Chenyi Xia, Hongjun Lu, Beng Chin Ooi, Jing Hu
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

An important but very expensive primitive operation of high-dimensional databases is the K-Nearest Neighbor (KNN) similarity join. The operation combines each point of one dataset with its KNNs in the other dataset and it provides more meaningful query results than the range similarity join. Such an operation is useful for data mining and similarity search. In this paper, we propose a novel KNN-join algorithm, called the Gorder (or the G-ordering KNN) join method. Gorder is a block nested loop join method that exploits sorting, join scheduling and distance computation filtering and reduction to reduce both I/O and CPU costs. It sorts input datasets into the G-order and applied the scheduled block nested loop join on the G-ordered data. The distance computation reduction is employed to further reduce CPU cost. It is simple and yet efficient, and handles high-dimensional data efficiently. Extensive experiments on both synthetic cluster and real life datasets were conducted, and the results illustrate that Gorder is an efficient KNN-join method and outperforms existing methods by a wide margin.
R68-17 Synthesis of Resistive Digital-to-Analog Conversion Ladders for Arbitrary Codes with Fixed Positive Weights
Authors: C. F. Crocker
Venue: IEEE Transactions on Computers (1968)

The purpose of this paper is to develop design equations for switched positive-resistance digital-to-analog converters. The authors state that no synthesis method heretofore has existed for the design of this type of ladder network. The problem to which the paper addresses itself is the following The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Algorithm 872: Parallel 2D constrained Delaunay mesh generation
Authors: Andrey N. Chernikov, Nikos P. Chrisochoides
Venue: ACM Transactions on Mathematical Software (TOMS) (2008)

Delaunay refinement is a widely used method for the construction of guaranteed quality triangular and tetrahedral meshes. We present an algorithm and a software for the parallel constrained Delaunay mesh generation in two dimensions. Our approach is based on the decomposition of the original mesh generation problem into N smaller subproblems which are meshed in parallel. The parallel algorithm is asynchronous with small messages which can be aggregated and exhibits low communication costs. On a heterogeneous cluster of more than 100 processors our implementation can generate over one billion triangles in less than 3 minutes, while the single-node performance is comparable to that of the fastest to our knowledge sequential guaranteed quality Delaunay meshing library (the Triangle).
Fibre Channel Switch Modeling at Fibre Channel-2 Level for Large Fabric Storage Area Network Simulations using OMNeT++: Preliminary Results
Authors: Timothy J. Brothers, Suresh Muknahallipatna, Jerry C. Hamann
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

Medium sized storage area networks using fibre channel have been a common implementation for data storage in enterprise data centers. The ever increasing demand for large storage pools has paved to the idea of implementing large distributed storage area networks also known as large fabrics. The large fabrics seem to experience fabric scaling and fabric stability issues. These scaling and stability issues are related to the performance of various fabric servers of fabric services, such as fabric controller, fabric login, directory, etc., which are part of the fibre channel-2 level of the fibre channel protocol. To determine the extent of scaling and stability issues of a large fabric an adequate tool is required. The tool could be an analytical model, a hardware simulator, or a discrete event software simulator. The discrete event software simulator provides a number of benefits over the analytical model and hardware simulator. In this paper, the modeling of a fibre channel switch using the OMNeT++ discrete event simulator and simulation of large fabric are presented. As a first step, only the fibre channel-2 level of the fibre channel switch is modeled since it is the layer containing various fabric services dealing with fabric building and managing. In this paper, the process of building a fabric and managing and how it is implemented in the simulator are discussed. Also, a preliminary analysis of the results in comparison to the test bed traffic is presented showing the accuracy and representation of an actual large fabric by the simulator.
Microprogramming for computer graphics
Authors: Andries van Dam
Venue: ACM SIGMICRO Newsletter (1972)

Interactive computer graphics (graphics) is the construction, storage, retrieval, manipulation, alteration and analysis of pictorial data, using an on-line display console with manual input (interaction) devices. Among such input devices are the alphanumeric and function keyboards for typing text and activating preprogrammed subroutines respectively, and the light pen and data tablet for identifying and entering graphic data by means of pointing and drawing.
An Automated Test Case Generation Approach by Genetic Simulated Annealing Algorithm
Authors: Bao-Lin Li, Zhi-Shu Li, Jing-Yu Zhang, Ji-Rong Sun
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

A new automatic test data generation approach is presented based on Length_N coverage criterion through genetic simulated annealing algorithm. The method mainly works on test data generation where the problem of test data generation is reduced to one of minimizing a function. Firstly, a new test coverage criterion called Length_N is proposed to aim at the feasible of path coverage criteria. To enhance the generated efficiency, we make some improvements on genetic simulated annealing algorithm and use the results to generate test data. Lastly, experiment results show the method has a better effect.
D-S Theory-based Trust Model FIRE^+ in Multi-agent Systems
Authors: Ping-Ping Lu, Bin Li, Mao-Lin Xing, Liang Li
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

In open multi-agent systems (MAS), interaction between agents is uncertain. Trust plays an important role in deciding with whom to interact and how to interact with it. Current trust models have solved the problem of how to quantify, deduce and evaluate trust, but there are still challenges. This paper presents FIRE^+ trust model using utility loss of issue to evaluate trust values. With the representation of matrix, it efficiently increases the rating information. Also by introducing D-S theory and WMA, it can handle uncertain information and dishonest witness finely. Meanwhile, our approach introduces the concept of information-amount to derive each issue's weight so as to gain the whole trust value of the target agent. It also takes witness reliability into account. Experiments show that FIRE^+ is more effective than others.
Cryptographic properties of some binary generalized cyclotomic sequences with the length p2
Authors: Tongjiang Yan, Bingjia Huang, Guozhen Xiao
Venue: Information Sciences: an International Journal (2008)

Herein, the cryptographic properties of some generalized cyclotomic sequences, with the period p^2, are investigated. Results show that these sequences always possess good balance and linear complexity (larger than half the period). Their autocorrelation functions are shown to be three-valued if p=3(mod4), and five-valued otherwise. Moreover, the distribution of patterns of length 2 are discussed.
Subspace-based prediction of linear time-varying stochastic systems
Authors: Kentaro Kameyama, Akira Ohsumi
Venue: Automatica (Journal of IFAC) (2007)

In this paper, a new subspace method for predicting time-varying stochastic systems is proposed. Using the concept of angle between past and present subspaces spanned by the extended observability matrices, the future signal subspace is predicted by rotating the present subspace in the geometrical sense, and time-varying system matrices are derived from the resultant signal subspace. Proposed algorithm is improved for fast-varying systems. Furthermore, recursive implementation of both algorithms is developed.
Tutorial Series 11 LSI/VLSI Building Blocks
Authors: J. R. Tobias
Venue: Computer (1981)

More circuits will continue to be placed on smaller chips, resulting in modular building blocks with better performance, more functionality, higher yields, and lower costs. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Best position algorithms for top-k queries
Authors: Reza Akbarinia, Esther Pacitti, Patrick Valduriez
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

The general problem of answering top-k queries can be modeled using lists of data items sorted by their local scores. The most efficient algorithm proposed so far for answering top-k queries over sorted lists is the Threshold Algorithm (TA). However, TA may still incur a lot of useless accesses to the lists. In this paper, we propose two new algorithms which stop much sooner. First, we propose the best position algorithm (BPA) which executes top-k queries more efficiently than TA. For any database instance (i.e. set of sorted lists), we prove that BPA stops as early as TA, and that its execution cost is never higher than TA. We show that the position at which BPA stops can be (m-1) times lower than that of TA, where m is the number of lists. We also show that the execution cost of our algorithm can be (m-1) times lower than that of TA. Second, we propose the BPA2 algorithm which is much more efficient than BPA. We show that the number of accesses to the lists done by BPA2 can be about (m-1) times lower than that of BPA. Our performance evaluation shows that over our test databases, BPA and BPA2 achieve significant performance gains in comparison with TA.
Pruning belief decision tree methods in averaging and conjunctive approaches
Authors: Salsabil Trabelsi, Zied Elouedi, Khaled Mellouli
Venue: International Journal of Approximate Reasoning (2007)

The belief decision tree (BDT) approach is a decision tree in an uncertain environment where the uncertainty is represented through the Transferable Belief Model (TBM), one interpretation of the belief function theory. The uncertainty can appear either in the actual class of training objects or attribute values of objects to classify. From the procedures of building BDT, we mention the averaging and the conjunctive approaches. In this paper, we develop pruning methods of belief decision trees induced within averaging and conjunctive approaches where the objective is to cope with the problem of overfitting the data in BDT in order to improve its comprehension and to increase its quality of the classification.
Brief paper: A swarm intelligence approach to the synthesis of two-dimensional IIR filters
Authors: Swagatam Das, Amit Konar
Venue: Engineering Applications of Artificial Intelligence (2007)

The concept of particle swarms, although initially introduced for simulating human social behaviors, has become very popular these days as an efficient means for intelligent search and optimization. The particle swarm optimization (PSO), as it is called now, does not require any gradient information of the function to be optimized, uses only primitive mathematical operators and is conceptually very simple. This paper investigates a novel approach to the designing of two-dimensional zero phase infinite impulse response (IIR) digital filters using the PSO algorithm. The design task is reformulated as a constrained minimization problem and is solved by a modified PSO algorithm. Numerical results are presented. The paper also demonstrates the superiority of the proposed design method by comparing it with two recently published filter design methods and two other state of the art optimization techniques.
A Fast Blind Deconvolution Algorithm Using Decorrelation and Block Matrix
Authors: Jun-an Yang, Xuefan He, Yunxiao Jiang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

In order to alleviate the shortcomings of most blind deconvolution algorithms, this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix. Althougth the original algorithm proposed in Ref. [5] can overcome the shortcomings of current blind deconvolution algorithms, but it has a constraint that the number of the source signals must be less than that of the channels'. The improved algorithm deletes this constraint by using decorrelation technique. Besides, the improved algorithm raises the separation speed in terms of improving the computing methods of output signals matrix. Simulation results demonstrate the validation and fast separation of the improved algorithm.
Strategies in supply chain management for the Trading Agent Competition
Authors: Yain-Whar Si, David Edmond, Marlon Dumas, Chan U. Chong
Venue: Electronic Commerce Research and Applications (2007)

Negotiating with suppliers and with customers is a key part of supply chain management. However, with recent technological advances, the mechanisms available to carry out such activities have become increasingly sophisticated, and the environment in which these activities take place has become highly dynamic. As a consequence, the overall planning of these complex trades, and the coordination of the various production and scheduling activities, need to be carefully considered by the businesses involved in the supply chain management. In order to guide the overall planning, production, scheduling, and allocation of resources, especially designed strategies are increasingly used by the businesses. In this setting, it is crucial that the intended behaviour, and through that, the desired outcomes, of these strategies be precisely understood. Using an empirical analysis, this paper investigates two fundamental strategies in supply chain management: buy-to-build and build-to-order.