ppxscal/embedding_network huggingface dataset:
A Smoothing Newton Method for General Nonlinear Complementarity Problems
Authors: Hou-Duo Qi, Li-Zhi Liao
Venue: Computational Optimization and Applications (2000)

Smoothing Newton methods for nonlinear complementarity problems NCP(F) often require F to be at least a P0-function in order to guarantee that the underlying Newton equation is solvable. Based on a special equation reformulation of NCP(F), we propose a new smoothing Newton method for general nonlinear complementarity problems. The introduction of Kanzow and Pieper's gradient step makes our algorithm to be globally convergent. Under certain conditions, our method achieves fast local convergence rate. Extensive numerical results are also reported for all complementarity problems in MCPLIB and GAMSLIB libraries with all available starting points.
Computational Complexity of Sorting and Joining Relations with Duplicates
Authors: M. Abdelguerfi, A. K. Sood
Venue: IEEE Transactions on Knowledge and Data Engineering (1991)

It is shown that the existence of duplicate values in some attribute columns has a significant impact on the computational complexity of the sorting and joining operations. This is especially true when the number of distinct tuple values is a small fraction of the total number of tuples. The authors characterize a multirelation M(n, L) by its cardinality n and the number of distinct elements L it contains. Under this characterization, the worst time complexity of sorting such a multirelation with binary comparisons as basic operations is investigated. Upper and lower bounds on the number of three-branch comparisons needed to sort such a multirelation are established. Thereafter, the methodology used to study the complexity of sorting is applied to the natural join operation. It is shown that the existence of duplicate values in the join attribute columns can be exploited to reduce the computational complexity of the natural join operation.
Interactive Visualization for Rapid Noninvasive Cardiac Assessment
Authors: Meiyappan Solaiyappan, Tim Poston, Pheng Ann Heng, Elliot R. McVeigh, Michael A. Guttman, Elias A. Zerhouni
Venue: Computer (1996)

New developments in computerized visualization may let doctors use one noninvasive exam to thoroughly evaluate patients with heart problems, saving both time and money. The authors describe how improved visualization techniques, combined with the latest in magnetic resonance imaging (MRI) technology, could provide doctors with improved 3D images for evaluating patient heart performance. In addition, the technology could lead to instant exam results. This would let doctors conduct more tests on the spot if more information were needed. Now, because doctors must wait for exam results, patients must return for more testing if more information is needed. Virtual reality technology could improve the process even more.The key to such a comprehensive heart exam, the authors explain, will be developing computerized visualization tools that can adequately analyze and display MRI data. Techniques such as dynamic volume rendering and ellipsoidal rendering may help accomplish this.
A comparative study of business practices of North American and European on-line companies
Authors: Nicholas Protogeros
Venue: Information and Management (2002)

During the last year, a large research study was funded by the European Commission; its aim was to determine on-line company characteristics and their Web business strategies while assessing their Web site efficiency. A comparative comparison of North American company practices and comparable ones in Europe was also made. Some of the interesting results are presented here.
Performance Implications of Tolerating Cache Faults
Authors: A. F. Pour, M. D. Hill
Venue: IEEE Transactions on Computers (1993)

The authors investigate how much cache miss ratios increase when blocks are disabled. It is shown how the mean miss ratio increase can be characterized as a function of the miss ratios of related caches, an efficient approach is developed for calculating the exact distribution of miss ratio increases from all fault patterns, and this approach is applied to the ATUM traces. Results reveal that the mean relative miss ratio increase from a few faults decreases with increasing cache size and is negligible (>2% per defect) unless a set is completely disabled by faults. The maximum relative increase is also acceptable (5% per fault) if no set is entirely disabled.
Complete Mining of Frequent Patterns from Graphs: Mining Graph Data
Authors: Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda
Venue: Machine Learning (2003)

Basket Analysis, which is a standard method for data mining, derives frequent itemsets from database. However, its mining ability is limited to transaction data consisting of items. In reality, there are many applications where data are described in a more structural way, e.g. chemical compounds and Web browsing history. There are a few approaches that can discover characteristic patterns from graph-structured data in the field of machine learning. However, almost all of them are not suitable for such applications that require a complete search for all frequent subgraph patterns in the data. In this paper, we propose a novel principle and its algorithm that derive the characteristic patterns which frequently appear in graph-structured data. Our algorithm can derive all frequent induced subgraphs from both directed and undirected graph structured data having loops (including self-loops) with labeled or unlabeled nodes and links. Its performance is evaluated through the applications to Web browsing pattern analysis and chemical carcinogenesis analysis.
IPS-2: The Second Generation of a Parallel Program Measurement System
Authors: B. P. Miller, M. Clark, J. Hollingsworth, S. Kierstead, S. S. Lim, T. Torzewski
Venue: IEEE Transactions on Parallel and Distributed Systems (1990)

IPS, a performance measurement system for parallel and distributed programs, is currently running on its second implementation. IPS's model of parallel programs uses knowledge about the semantics of a program's structure to provide two important features. First, IPS provides a large amount of performance data about the execution of a parallel program, and this information is organized so that access to it is easy and intuitive. Secondly, IPS provides performance analysis techniques that help to guide the programmer automatically to the location of program bottlenecks. The first implementation of IPS was a testbed for the basic design concepts, providing experience with a hierarchical program and measurement model, interactive program analysis, and automatic guidance techniques. It was built on the Charlotte distributed operating system. The second implementation, IPS-2, extends the basic system with new instrumentation techniques, an interactive and graphical user interface, and new automatic guidance analysis techniques. This implementation runs on 4.3BSD UNIX systems, on the VAX, DECstation, Sun 4, and Sequent Symmetry multiprocessor.
Intrusion Detection via System Call Traces
Authors: Andrew P. Kosoresow, Steven A. Hofmeyr
Venue: IEEE Software (1997)

Computer use leaves trails of activity that can reveal signatures of misuse as well as of legitimate activity. Depending on the audit method used, one can record a user's keystrokes, the system resources used, or the system calls made by some collection of processes. The authors have done preliminary work on the analysis of system call traces, particularly their structure during normal and anomalous behavior, and have found the anomalies to be temporally localized. These techniques could eventually lead to an effective, automatic analysis and monitoring system, and might even be extensible to handle other kinds of anomalous behavior.
Supporting structured credentials and sensitive policies through interoperable strategies for automated trust negotiation
Authors: Ting Yu, Marianne Winslett, Kent E. Seamons
Venue: ACM Transactions on Information and System Security (TISSEC) (2003)

Business and military partners, companies and their customers, and other closely cooperating parties may have a compelling need to conduct sensitive interactions on line, such as accessing each other's local services and other local resources. Automated trust negotiation is an approach to establishing trust between parties so that such interactions can take place, through the use of access control policies that specify what combinations of digital credentials a stranger must disclose to gain access to a local resource. A party can use many different strategies to negotiate trust, offering tradeoffs between the length of the negotiation, the amount of extraneous information disclosed, and the computational effort expended. To preserve parties' autonomy, each party should ideally be able to choose its negotiation strategy independently, while still being guaranteed that negotiations will succeed whenever possible---that the two parties' strategies will interoperate. In this paper we provide the formal underpinnings for that goal, by formalizing the concepts of negotiation protocols, strategies, and interoperation. We show how to model the information flow of a negotiation for use in analyzing strategy interoperation. We also present two large sets of strategies whose members all interoperate with one another, and show that these sets contain many practical strategies. We develop the theory for black-box propositional credentials as well as credentials with internal structure, and for access control policies whose contents are (respectively are not) sensitive. We also discuss how these results fit into TrustBuilder, our prototype system for trust negotiation.
Analysis of bulk fabrics and microstructure variations using tesselations of autocorrelation functions
Authors: Renée Heilbronner
Venue: Computers Geosciences (2002)

"Lazy ACF Tiles", a macro written for the public domain program "NIH Image", is presented. The macro permits the user to calculate local and bulk autocorrelation functions (ACFs) of halftone images such as photomicrographs of geological thin sections. Single ACFs, rows, or tessellations of ACFs can be calculated. ACF analysis is especially useful for the detection of subtle microstructures (weak anisotropies), and for the evaluation of large data sets. Segmentation of images (grain boundary contouring) is not necessary. Images do not have to be square. The macro is in the public domain and a powerpoint manual is provided with it. As an example, the application of "Lazy ACF Tiles" to an experimentally deformed sample of quartzite is demonstrated. The ACF analysis reveals a periodic flattening intensity along the compressional axis of the sample, which cannot be detected with the unaided eye.
A Comprehensive Analytical Performance Model for Disk Devices under Random Workloads
Authors: P. Triantafillou, S. Christodoulakis, C. A. Georgiadis
Venue: IEEE Transactions on Knowledge and Data Engineering (2002)

Our goal with this paper is to contribute a common theoretical framework for studying the performance of disk-storage devices. Understanding the performance behavior of these devices will allow prediction of the I/O cost in modern applications. Current disk technologies differ in terms of the fundamental modeling characteristics, which include the magnetic/optical nature, angular and linear velocities, storage capacities, and transfer rates. Angular and linear velocities, storage capacities, and transfer rates are made constant or variable in different existing disk products. Related work in this area has studied Constant Angular Velocity (CAV) magnetic disks and Constant Linear Velocity (CLV) optical disks. In this work, we present a comprehensive analytical model, validated through simulations, for the random retrieval performance of disk devices which takes into account all the above-mentioned fundamental characteristics and includes, as special cases, all the known disk-storage devices. Such an analytical model can be used, for example, in the query optimizer of large traditional databases as well as in an admission controller of multimedia storage servers. Besides the known models for magnetic CAV and optical CLV disks, our unifying model is also reducible to a model for a more recent disk technology, called zoned disks, the retrieval performance of which has not been modeled in detail before. The model can also be used to study the performance retrieval of possible future technologies which combine a number of the above characteristics and in environments containing different types of disks (e.g., magnetic-disk-based secondary storage and optical-disk-based tertiary storage). Using our model, we contribute an analysis of the performance behavior of zoned disks and we compare it against that for the traditional CAV disks, as well as against that of some possible/future technologies. This allows us to gain insights into the fundamental performance trade-offs.
Analytic Modeling of Clustered RAID with Mapping Based on Nearly Random Permutation
Authors: Arif Merchant, Philip S. Yu
Venue: IEEE Transactions on Computers (1996)

A Redundant Array of Independent Disks (RAID) of G disks provides protection against single disk failures by adding one parity block for each G¿ 1 data blocks. In a clustered RAID, the G data/parity blocks are distributed over a cluster of C disks (C > G), thus reducing the additional load on each disk due to a single disk failure. However, most methods proposed for implementing such a mapping do not work for general C and G values.In this paper, we describe a fast mapping algorithm based on almost-random permutations. An analytical model is constructed, based on the queue with a permanent customer, to predict recovery time and read/write performance. The accuracy of the results derived from this model is validated by comparing with simulations. Our analysis shows that clustered RAID is significantly more tolerant of disk failure than the basic RAID scheme. Both recovery time and performance degradation during recovery are substantially reduced in clustered RAID; moreover, these gains can be achieved using fairly small C/G ratios.
Algorithms for Distributed Constraint Satisfaction: A Review
Authors: Makoto Yokoo, Katsutoshi Hirayama
Venue: Autonomous Agents and Multi-Agent Systems (2000)

When multiple agents are in a shared environment, there usually exist constraints among the possible actions of these agents. A distributed constraint satisfaction problem (distributed CSP) is a problem to find a consistent combination of actions that satisfies these inter-agent constraints. Various application problems in multi-agent systems can be formalized as distributed CSPs. This paper gives an overview of the existing research on distributed CSPs. First, we briefly describe the problem formalization and algorithms of normal, centralized CSPs. Then, we show the problem formalization and several MAS application problems of distributed CSPs. Furthermore, we describe a series of algorithms for solving distributed CSPs, i.e., the asynchronous backtracking, the asynchronous weak-commitment search, the distributed breakout, and distributed consistency algorithms. Finally, we show two extensions of the basic problem formalization of distributed CSPs, i.e., handling multiple local variables, and dealing with over-constrained problems.
A Linear Programming Approach for the Weighted Graph Matching Problem
Authors: H. A. Almohamad, S. O. Duffuaa
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (1993)

A linear programming (LP) approach is proposed for the weighted graph matching problem. A linear program is obtained by formulating the graph matching problem in L/sub 1/ norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a simplex-based algorithm. Then, approximate 0-1 integer solutions are obtained by applying the Hungarian method on the real solutions of the linear program. The complexity of the proposed algorithm is polynomial time, and it is O(n/sup 6/L) for matching graphs of size n. The developed algorithm is compared to two other algorithms. One is based on an eigendecomposition approach and the other on a symmetric polynomial transform. Experimental results showed that the LP approach is superior in matching graphs than both other methods.
SLICC: a low latency interface for collective communications
Authors: Allan D. Knies, William J. Harrod, F. Ray Barriuso, George B. Adams,  III
Venue: Proceedings of the 1994 ACM/IEEE conference on Supercomputing (1994)

Several recent parallel computers have implemented logically shared, physically distributed memory systems which allow processors to directly access memory in other processors without interrupting the referenced PE. Because this kind of architecture provides greater flexibility for interprocessor communications than private address space computers, different software models can be developed to take advantage of these machines. In this paper, we describe a low-level collective communications interface specifically tailored for shared address space parallel computers. We also provide performance results for an implementation on the Cray T3D and compare its performance to Cray's PVM implementation. These results show that SLICC can be more than 10 times faster than PVM on the T3D.
Efficiently Adapting Java Binaries in Limited Memory Contexts
Authors: Pramod G. Joisha, Samuel P. Midkiff, Mauricio J. Serrano, Manish Gupta
Venue: International Journal of Parallel Programming (2002)

This paper presents a compilation framework that allows executable code to be shared across different Java Virtual Machine (JVM) instances. Current compliant JVMs for servers are burdened with large memory footprints (because of the size of the increasingly complicated compilers) and high startup costs, while compliant JVMs for embedded devices typically rely on interpretation. This paper describes a quasi-static approach that allows execution of a read-only version of the code, enabling compiled Java binaries to be embedded in ROM in an embedded environment or shared across multiple applications in a server environment. We have implemented this approach in the Quicksilver quasi-static compiler for the Jikes RVM (Jikes Research Virtual Machine). On the SPECjvm98 benchmark suite, our approach gives writable memory space savings of between 82&ndash;89% over that of our previous (non-sharable, non-ROMable) quasi-static approach, while delivering performance that is typically within 1&ndash;7% of that approach, and is competitive with the performance of the Jikes RVM adaptive optimization system.
Interrupt Processing in Concurrent Processors
Authors: Wade Walker, Harvey G. Cragon
Venue: Computer (1995)

This paper presents a taxonomy of interrupt processing strategies for concurrent processors. Such a taxonomy helps processor designers systematically explore possible interrupt processing system implementations. It also provides a framework to which new information about interrupt processing can easily be added. This paper also discusses other issues which relate to interrupt processing, such as preciseness, interrupt nesting, and interrupt- specific hardware.
Efficient and scalable cache coherence schemes for shared memory hypercube multiprocessors
Authors: Akhilesh Kumar, Phanindra K. Mannava, Laxmi N. Bhuyan
Venue: Proceedings of the 1994 ACM/IEEE conference on Supercomputing (1994)

Large scale shared memory multiprocessors use directory based cache coherence scheme. The basic directory scheme, called full-map, is efficient but has a large memory overhead. Therefore, limited directory schemes have been proposed which limit the number of pointers in the directories. These schemes tradeoff smaller memory overhead for larger memory access latencies. In this paper, we propose a new limited directory scheme, which achieves lower memory overhead as well as smaller memory access latencies. The scheme uses ring embedding in a hypercube in conjunction with wormhole routing to reduce the invalidation delays. The proposed scheme performs as good as full-map for smaller degree of sharing and performs better than full-map for larger degree of sharing.
Learning Temporally Encoded Patterns in Networks of SpikingNeurons
Authors: Berthold Ruf, Michael Schmitt
Venue: Neural Processing Letters (1997)

Networks of spiking neurons are very powerful and versatile models for biological and artificial information processing systems. Especially for modelling pattern analysis tasks in a biologically plausible way that require short response times with high precision they seem to be more appropriate than networks of threshold gates or models that encode analog values in average firing rates. We investigate the question how neurons can learn on the basis of time differences between firing times. In particular, we provide learning rules of the Hebbian type in terms of single spiking events of the pre- and postsynaptic neuron and show that the weights approach some value given by the difference between pre- and postsynaptic firing times with arbitrary high precision.
Tracking Pitches for Broadcast Television
Authors: André Guéziec
Venue: Computer (2002)

During the 2001 major league baseball season, the strike zone received special attention when officials decided to enforce the game's original definition, which made tracking pitches especially important. Tracking the flight of a pitch during a live broadcast presents two major challenges, however: speed and image-processing reliability.Meeting these challenges required developing a complex system that fuses high-end computer graphics with a sophisticated algorithm for calculating flight trajectories.ESPN's K Zone pitch-tracking system uses computer-generated graphics to create a shaded, translucent box that outlines the strike zone boundaries for viewers. Behind the flashy graphics, K Zone provides a sophisticated computing subsystem that monitors each pitch's trajectory. Its development model may well prove effective in future computer vision projects, regardless of the application domain.
Performance Evaluation of Client-Server Systems
Authors: O. C. Ibe, H. Choi, K. S. Trivedi
Venue: IEEE Transactions on Parallel and Distributed Systems (1993)

A client-server system is a distributed system where a server station receives requestsfrom its client stations, processes the requests and returns replies to the requestingstations. The authors consider client-server systems in which a set of workstationsaccess a file server over a local area network. The systems are modelled by a class ofstochastic Petri nets. The mean response time, the throughput and the parametricsensitivities are evaluated for a client-server system based on token ring network and asystem based on CSMA/CD network. These models are different from the prevalentperformance models of token ring or CSMA/CD network systems because of the messageinterdependencies introduced by the clients-server structure. An approximateanalytic-numeric method rather than simulation is used to solve the models. The solutionmethod and the accuracy of approximation are also discussed.
The evolution of software evolvability
Authors: Chris Lüer, David S. Rosenblum, André van der Hoek
Venue: Proceedings of the 4th International Workshop on Principles of Software Evolution (2001)

We analyze two trends that have influenced the evolvability of component-based applications: increase of component exchangeability and increase of component distance. Exchangeability mechanisms can be classified either as code reuse or as service reuse. Component distance can vary from file scope to Internet scope. We discuss the various stages of evolvability in these dimensions, describe the state of the art, and speculate on future developments.
Linearization and Penalty Functions
Authors: Yu. M. Danilin
Venue: Cybernetics and Systems Analysis (2002)

Author's works on solving problems of nonlinear programming and variational inequalities, based on problem linearization proposed and developed by B. N. Pshenichnyi, are reviewed in the paper.