ppxscal/embedding_network huggingface dataset:
Identity in virtual communities
Authors: Anri Kivimäki, Kaisa Kauppinen, Mike Robinson
Venue: ACM SIGGROUP Bulletin (1998)

The usability of Collaborative Virtual Environments is a function of technical affordances with the implicit and explicit intentions of users. Intentions can be revealed by 'cyborg ethnography' -- a close examination of interactions and conversations conducted in CVE's. Three CVE's were examined ethnographically and it is found that social conventions develop around the theme of producing identity. However, there is doubt that such conventions constitute evidence of a 'virtual' social system.
Probabilistic state space search
Authors: Andreas Kuehlmann, Kenneth L. McMillan, Robert K. Brayton
Venue: Proceedings of the 1999 IEEE/ACM international conference on Computer-aided design (1999)

This paper describes a probabilistic approach to state space search. The presented method applies a ranking of the design states according to their probability of reaching a given target state based on a random walk model. This ranking can be used to prioritize an explicit or partial symbolic state exploration to find a trajectory from a set of initial states to a set of target states. A symbolic technique for estimating the reachability probability is described which implements a smooth trade-off between accuracy and computing effort. The presented probabilistic state space search complements incomplete verification methods which are specialized in finding errors in large designs.
Extracting Rules from Composite Neural Networks for MedicalDiagnostic Problems
Authors: Mu-Chun Su, Hsiao-Te Chang
Venue: Neural Processing Letters (1998)

Recently, neural networks have been applied to many medical diagnostic problems because of their appealing properties, robustness, capability of generalization and fault tolerance. Although the predictive accuracy of neural networks may be higher than that of traditional methods (e.g., statistical methods) or human experts, the lack of explanation from a trained neural network leads to the difficulty that users would hesitate to take the advise of a black box on faith alone. This paper presents a class of composite neural networks which are trained in such a way that the values of the network parameters can be utilized to generate If-Then rules on the basis of preselected meaningful coordinates. The concepts and methods presented in the paper are illustrated through one practical example from medical diagnosis.
Indulgent algorithms (preliminary version)
Authors: Rachid Guerraoui
Venue: Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing (2000)

Informally, an indulgent algorithm is a distributed algorithm that tolerates unreliable failure detection: the algorithm is indulgent towards its failure detector. This paper formally characterises such algorithms and states some of their interesting features. We show that indulgent algorithms are inherently safe and uniform. We also state impossibility results for indulgent solutions to divergent problems like consensus, and failure-sensitive problems like non-blocking atomic commit and terminating reliable broadcast.
Disclosure Detection in Multivariate Categorical Databases: Auditing Confidentiality Protection Through Two New Matrix Operators
Authors: Sumit Dutta Chowdhury, George T. Duncan, Ramayya Krishnan, Stephen F. Roehrig, Sumitra Mukherjee
Venue: Management Science (1999)

As databases grow more prevalent and comprehensive, database administrators seek to limit disclosure of confidential information while still providing access to data. Practical databases accommodate users with heterogeneous needs for access. Each class of data user is accorded access to only certain views. Other views are considered confidential, and hence to be protected. Using illustrations from health care and education, this article addresses inferential disclosure of confidential views in multidimensional categorical databases. It demonstrates that any structural, so data-value-independent method for detecting disclosure can fail. Consistent with previous work for two-way tables, it presents a data-value-dependent method to obtain tight lower and upper bounds for confidential data values. For two-dimensional projections of categorical databases, it exploits the network structure of a linear programming (LP) formulation to develop two transportation flow algorithms that are both computationally efficient and insightful. These algorithms can be easily implemented through two new matrix operators, cell-maxima and cell-minima. Collectively, this method is called matrix comparative assignment (MCA). Finally, it extends both the LP and MCA approaches to inferential disclosure when accessible views have been masked.
On the Tradeoff Between Computational Simplicity and AsymptoticProperties in Multivariate Probit
Authors: Ayal Kimhi
Venue: Computational Economics (1999)

This paper discusses the most efficient estimator among Quasi Maximum Likelihood Estimators using at most two levels of numerical integration, for the multivariate probit model. Simulations show that this estimator is more efficient but not more costly than the second-best alternative. However, its added efficiency depends on the correlation structure.
Generating dynamic content at database-backed web servers: cgi-bin vs. mod_perl
Authors: Alexandros Labrinidis, Nick Roussopoulos
Venue: ACM SIGMOD Record (2000)

Web servers are increasingly being used to deliver dynamic content rather than static HTML pages. In order to generate web pages dynamically, servers need to execute a script, which typically connects to a DBMS. Although CGI was the first approach at server side scripting, it has significant performance shortcomings. Currently, there are many alternative server side scripting architectures which offer better performance than CGI. In this paper, we report our experiences using mod_perl, an Apache Server module, which can improve the performance of CGI scripts by at least an order of magnitude. Except for presenting results from our experiments, we also briefly describe the implementation of an industrial strength database-backed web site that we recently built and give a quick overview of the various server-side scripting mechanisms.
Quadratic Optimal Control of Well-Posed Linear Systems
Authors: Olof J. Staffans
Venue: SIAM Journal on Control and Optimization (1999)

We study the infinite horizon quadratic cost minimization problem for a well-posed linear system in the sense of Salamon and Weiss. The quadratic cost function that we seek to minimize need not be positive, but it is convex and bounded from below. We assume the system to be jointly stabilizable and detectable and give a feedback solution to the cost minimization problem. Moreover, we connect this solution to the computation of either a (J,S)-inner or an S-normalized coprime factorization of the transfer function, depending on how the problem is formulated. We apply the general theory to get factorization versions of the bounded and positive real lemmas. In the case where the system is regular it is possible to show that the feedback operator can be expressed in terms of the Riccati operator and that the Riccati operator is a stabilizing self-adjoint solution of an algebraic Riccati equation. This Riccati equation is nonstandard in the sense that the weighting operator in the quadratic term differs from the expected one, and the computation of the correct weighting operator is a nontrivial task.
Quantitative Characterization and Analysis of the I/O Behavior of a Commercial Distributed-Shared-Memory Machine
Authors: Rajesh A. Bordawekar
Venue: IEEE Transactions on Parallel and Distributed Systems (2000)

This paper presents a unified evaluation of the I/O behavior of a commercial clustered DSM machine, the HP Exemplar. Our study has the following objectives: 1) To evaluate the impact of different interacting system components, namely, architecture, operating system, and programming model, on the overall I/O behavior and identify possible performance bottlenecks, and 2) To provide hints to the users for achieving high out-of-box I/O throughput. We find that for the DSM machines that are built as a cluster of SMP nodes, integrated clustering of computing and I/O resources, both hardware and software, is not advantageous for two reasons. First, within an SMP node, the I/O bandwidth is often restricted by the performance of the peripheral components and cannot match the memory bandwidth. Second, since the I/O resources are shared as a global resource, the file-access costs become nonuniform and the I/O behavior of the entire system, in terms of both scalability and balance, degrades.We observe that the buffered I/O performance is determined not only by the I/O subsystem, but also by the programming model, global-shared memory subsystem, and data-communication mechanism. Moreover, programming-model support can be used effectively to overcome the performance constraints created by the architecture and operating system. For example, on the HP Exemplar, users can achieve high I/O throughput by using features of the programming model that balance the sharing and locality of the user buffers and file systems. Finally, we believe that at present, the I/O subsystems are being designed in isolation, and there is a need for mending the traditional memory-oriented design approach to address this problem.
On Exploiting Task Duplication in Parallel Program Scheduling
Authors: Ishfaq Ahmad, Yu-Kwong Kwok
Venue: IEEE Transactions on Parallel and Distributed Systems (1998)

One of the main obstacles in obtaining high performance from message-passing multicomputer systems is the inevitable communication overhead which is incurred when tasks executing on different processors exchange data. Given a task graph, duplication-based scheduling can mitigate this overhead by allocating some of the tasks redundantly on more than one processor. In this paper, we focus on the problem of using duplication in static scheduling of task graphs on parallel and distributed systems. We discuss five previously proposed algorithms and examine their merits and demerits. We describe some of the essential principles for exploiting duplication in a more useful manner and, based on these principles, propose an algorithm which outperforms the previous algorithms. The proposed algorithm generates optimal solutions for a number of task graphs. The algorithm assumes an unbounded number of processors. For scheduling on a bounded number of processors, we propose a second algorithm which controls the degree of duplication according to the number of available processors. The proposed algorithms are analytically and experimentally evaluated and are also compared with the previous algorithms.
Adaptive Image Segmentation With Distributed Behavior-Based Agents
Authors: Jiming Liu, Yuan Y. Tang
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1999)

This paper presents an autonomous agent-based image segmentation approach. In this approach, a digital image is viewed as a two-dimensional cellular environment in which the agents inhabit and attempt to label homogeneous segments. In so doing, the agents rely on some reactive behaviors such as breeding and diffusion. The agents that are successful in finding the pixels of a specific homogeneous segment will breed offspring agents inside their neighboring regions. Hence, the offspring agents will become likely to find more homogeneous-segment pixels. In the mean time, the unsuccessful agents will be inactivated, without further search in the environment.
Efficient resumption of interrupted warehouse loads
Authors: Wilburt Juan Labio, Janet L. Wiener, Hector Garcia-Molina, Vlad Gorelik
Venue: ACM SIGMOD Record (2000)

Data warehouses collect large quantities of data from distributed sources into a single repository. A typical load to create or maintain a warehouse processes GBs of data, takes hours or even days to execute, and involves many complex and user-defined transformations of the data (e.g., find duplicates, resolve data inconsistencies, and add unique keys). If the load fails, a possible approach is to &ldquo;redo&rdquo; the entire load. A better approach is to resume the incomplete load from where it was interrupted. Unfortunately, traditional algorithms for resuming the load either impose unacceptable overhead during normal operation, or rely on the specifics of transformations. We develop a resumption algorithm called DR that imposes no overhead and relies only on the high-level properties of the transformations. We show that DR can lead to a ten-fold reduction in resumption time by performing experiments using commercial software.
Database patchwork on the Internet
Authors: Reinhard Braumandl, Alfons Kemper, Donald Kossmann
Venue: Proceedings of the 1999 ACM SIGMOD international conference on Management of data (1999)

Naturally, data processing requires three kinds of resources: the data itself, the functionality (i.e. database operations) and the machines on which to run the operations. Because of the Internet we believe that in the long run there will be alternative providers for all of these three resources for any given application. Data providers will bring more and more data and more and more different kinds of data to the net. Likewise, function providers will develop new methods to process and work with the data; e.g., function providers might develop new algorithms to compress data or to produce thumbnails out of large images and try to sell these on the Internet. It is also conceivable, that some people allow other people to use spare cycles of their idle machines in the Internet (as in the Condor system of the University of Wisconsin) or that some companies (cycle providers) even specialize on selling computing time to businesses that occasionally need to carry out very complex operations for which regular hardware is not sufficient. At the University of Passau, we are currently developing a distributed database system to be used in the Internet. The goal is to ultimately have a system which is able to run on any machine, manage any kind of data, import any kind of data from other systems and import any kind of database operations. The system is entirely written in Java. One of the most important features of the system is that it is capable of dynamically loading (external) query operators, written in Java and supplied by any function provider, and executing these query operators in concert with pre-defined and other external operators in order to evaluate a query. Compared to object-relational database systems, which allow to integrate external data and functionality by the means of extensions (datablades, extenders or cartridges) or heterogeneous database systems such as Garlic [MS97] or Tsimmis [GMPQ+97], our approach makes it possible to place external query operators anywhere in a query evaluation plan as opposed to restricting the placement of external operations to the &ldquo;access level&rdquo; of plans. It would, for example, be possible to make our system execute a completely new relational join method, if somebody finds a new join method which is worth-while implementing. Because our system is written in Java, it is highly portable and could be used by data, function and cycle providers with almost no effort. Furthermore, our query engine is, of course, completely distributed providing all the required infrastructure for server-server communication, name services, etc.
A hardware-driven profiling scheme for identifying program hot spots to support runtime optimization
Authors: Matthew C. Merten, Andrew R. Trick, Christopher N. George, John C. Gyllenhaal, Wen-mei W. Hwu
Venue: Proceedings of the 26th annual international symposium on Computer architecture (1999)

This paper presents a novel hardware-based approach for identifying, profiling, and monitoring hot spots in order to support runtime optimization of general purpose programs. The proposed approach consists of a set of tightly coupled hardware tables and control logic modules that are placed in the retirement stage of a processor pipeline removed from the critical path. The features of the proposed design include rapid detection of program hot spots after changes in execution behavior, runtime-tunable selection criteria for hot spot detection, and negligible overhead during application execution. Experiments using several SPEC95 benchmarks, as well as several large WindowsNT applications, demonstrate the promise of the proposed design.
Power minimization of functional units partially guarded computation
Authors: Junghwan Choi
Venue: Proceedings of the 2000 international symposium on Low power electronics and design (2000)

This paper deals with power minimization problem for data-dominated applications based on a novel concept called partially guarded computation. We divide a functional unit into two parts - MSP (Most Significant Part) and LSP (Least Significant Part) - and allow the functional unit to perform only the LSP computation if the range of output data can be covered by LSP. We dynamically disable MSP computation to remove unnecessary transitions thereby reducing power consumption. We also propose a systematic approach for determining optimal location of the boundary between the two parts during high-level synthesis. Experimental results show about 10~44% power reduction with about 30~36% area overhead and less than 3% delay overhead in functional units.
APPN in heterogeneous environments
Authors: Jesper Nilausen
Venue: International Journal of Network Management (1999)

In this fifth article in the series on managing APPN networks we will discuss several examples of heterogeneous networking environments. Very few networks today, except for the smallest ones, are homogeneous in all aspects. Copyright &copy; 1999 John Wiley Sons, Ltd.
An Efficient Submesh Allocation Scheme for Two-Dimensional Meshes with Little Overhead
Authors: Ge-Ming Chiu, Shih-Kung Chen
Venue: IEEE Transactions on Parallel and Distributed Systems (1999)

This paper presents a submesh allocation scheme for two-dimensional mesh systems. The submesh detection process considers only those available free submeshes that border from the left on some allocated submeshes or have their left boundaries aligned with that of the mesh. Fragmentation in the system can be reduced as a result. More importantly, we present an efficient approach to facilitate the detection of such available submeshes. The basic idea of the approach is to place the allocated submeshes of the busy set in a certain order so as to reduce the complexity of subtraction operations required for submesh detection. The method is simple and causes an amount of overhead which is only a fraction of that produced by previous algorithms. Extensive simulation has been conducted to evaluate the performance of the proposed scheme. The results show that when allocation overhead is considered, the proposed scheme may outperform previous methods.
Asynchronous information space analysis architecture using content and structure-based service brokering
Authors: Ke-Thia Yao, In-Young Ko, Ragy Eleish, Robert Neches
Venue: Proceedings of the fifth ACM conference on Digital libraries (2000)

Our project focuses on rapid formation and utilization of custom collections of information for groups focused on high-paced tasks. Assembling such collections, as well as organizing and analyzing the documents within them, is a complex and sophisticated task. It requires understanding what information management services and tools are provided by the system, when they appropriate to use, and how those services can be composed together to perform more complex analyses. This paper describes the architecture of a prototype implementation of the information analysis management system that we have developed. The architecture uses metadata to describe collections of documents both in term of their content and structure. This metadata allows the system to dynamically and in a content-sensitive manner to determine the set of appropriate analysis services. To facilitate the invocation of those services, the architecture also provides an asynchronous and transparent service access mechanism.
Construction of Weighing Matrices W(17, 9)Having the Intersection Number 8
Authors: Hiroyuki Ohmori, Takashi Miyamoto
Venue: Designs, Codes and Cryptography (1998)

It is unknown ( [1], [2], [4] ) whether there exists a weighing matrix W(17,9) or not. The intersection number of W(17,9) is 6 or 8 . We completed the classification of weighing matrices W(17, 9) having the intersection number 8 . These matrices are classified into 925 non-equivalent classes. We shall show eight representative weighing matrices only together with their automorphism groups and g-distributions. Of these eight matrices, two have the same g-distribution.
Robust Parameter Estimation in Computer Vision
Authors: Charles V. Stewart
Venue: SIAM Review (1999)

Estimation techniques in computer vision applications must estimate accurate model parameters despite small-scale noise in the data, occasional large-scale measurement errors (outliers), and measurements from multiple populations in the same data set. Increasingly, robust estimation techniques, some borrowed from the statistics literature and others described in the computer vision literature, have been used in solving these parameter estimation problems. Ideally, these techniques should effectively ignore the outliers and measurements from other populations, treating them as outliers, when estimating the parameters of a single population. Two frequently used techniques are least-median of squares (LMS) [P. J. Rousseeuw, {J. Amer. Statist. Assoc., 79 (1984), pp. 871--880] and M-estimators [Robust Statistics: The Approach Based on Influence Functions, F. R. Hampel et al., John Wiley, 1986; Robust Statistics, P. J. Huber, John Wiley, 1981]. LMS handles large fractions of outliers, up to the theoretical limit of 50% for estimators invariant to affine changes to the data, but has low statistical efficiency. M-estimators have higher statistical efficiency but tolerate much lower percentages of outliers unless properly initialized.While robust estimators have been used in a variety of computer vision applications, three are considered here. In analysis of range images---images containing depth or X, Y, Z measurements at each pixel instead of intensity measurements---robust estimators have been used successfully to estimate surface model parameters in small image regions. In stereo and motion analysis, they have been used to estimate parameters of what is called the ''fundamental matrix,'' which characterizes the relative imaging geometry of two cameras imaging the same scene. Recently, robust estimators have been applied to estimating a quadratic image-to-image transformation model necessary to create a composite, ''mosaic image'' from a series of images of the human retina. In each case, a straightforward application of standard robust estimators is insufficient, and carefully developed extensions are used to solve the problem.
Duality Maps of Finite Abelian Groups and Their Applications to Spin Models
Authors: Etsuko Bannai, Akihiro Munemasa
Venue: Journal of Algebraic Combinatorics: An International Journal (1998)

Duality maps of finite abelian groups are classified. As a corollary, spin models on finite abelian groups which arise from the solutions of the modular invariance equations are determined as tensor products of indecomposable spin models. We also classify finite abelian groups whose Bose-Mesner algebra can be generated by a spin model.