ppxscal/embedding_network huggingface dataset:
Simultaneous short-path and long-path timing optimization for FPGAs
Authors: R. Fung, V. Betz, W. Chow
Venue: Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design (2004)

This work presents the routing cost valleys (RCV) algorithm - the first published algorithm that simultaneously optimizes all short- and long-path timing constraints in a field-programmable gate array (FPGA). RCV is comprised of a new slack allocation algorithm that produces both minimum and maximum delay budgets for each circuit connection, and a new router that strives to meet and, if possible, surpass these connection delay constraints. RCV achieves excellent results. On a set of 100 large circuits, RCV improves both long-path and short-path timing slack significantly vs. an earlier computer-aided design (CAD) system that focuses solely on long-path timing. Even with no short-path timing constraints, RCV improves the clock speed of circuits by 3.9% on average. Finally, RCV is able to meet timing on all 72 peripheral component interconnect (PCI) cores tested, while an earlier algorithm fails to achieve timing on all 72 cores.
The semantics of BI and resource tableaux
Authors: D. Galmiche, D. Méry, D. Pym
Venue: Mathematical Structures in Computer Science (2005)

The logic of bunched implications, BI, provides a logical analysis of a basic notion of resource that is rich enough, for example, to form the logical basis for &lsquo;pointer logic&rsquo; and &lsquo;separation logic&rsquo; semantics for programs that manipulate mutable data structures. We develop a theory of semantic tableaux for BI, so providing an elegant basis for efficient theorem proving tools for BI. It is based on the use of an algebra of labels for BI's tableaux to solve the resource-distribution problem, the labels being the elements of resource models. For BI with inconsistency, $\bot$, the challenge consists in dealing with BI's Grothendieck topological models within such a proof-search method, based on labels. We prove soundness and completeness theorems for a resource tableaux method TBI with respect to this semantics and provide a way to build countermodels from so-called dependency graphs. Then, from these results, we can define a new resource semantics of BI, based on partially defined monoids, and prove that this semantics is complete. Such a semantics, based on partiality, is closely related to the semantics of BI's (intuitionistic) pointer and separation logics. Returning to the tableaux calculus, we propose a new version with liberalised rules for which the countermodels are closely related to the topological Kripke semantics of BI. As consequences of the relationships between semantics of BI and resource tableaux, we prove two new strong results for propositional BI: its decidability and the finite model property with respect to topological semantics.
Automatic Classification of Web Information Based on Site Structure
Authors: Gao Kening, Yang Leiming, Zhang Bin, Chai Qiaozi, Ma Anxiang
Venue: Proceedings of the 2005 International Conference on Cyberworlds (2005)

How to classify automatically web information that grows explosive is becoming an imminent problem needed to be resolved. Based on site structure, we propose, in this paper, a new mechanism of automatic classification of web information, which downloads web pages within a web site, records the hyperlinks among web pages, catches the site structure, extracts the classifying system of the site itself, and then links categorizing information with the correspondent position in the site structure. Therefore automatic classification of web information can be realized through matching the positions of categorizing information with the positions of web pages. Experiments show that such classification based on site structure works more accurately and efficiently.
GLARE: A Grid Activity Registration, Deployment and Provisioning Framework
Authors: Mumtaz Siddiqui, Alex Villazon, Jurgen Hofer, Thomas Fahringer
Venue: Proceedings of the 2005 ACM/IEEE conference on Supercomputing (2005)

Resource management is a key concern for implementing effective Grid middleware and shielding application developers from low level details. Existing resource managers concentrate mostly on physical resources. However, some advanced Grid programming environments allow application developers to specify Grid application components at high level of abstraction which then requires an effective mapping between high level application description (activity types) and actual deployed software components (activity deployments). This paper describes GLARE framework that provides dynamic registration, automatic deployment and on-demand provision of application components (activities) that can be used to build Grid applications. GLARE simplifies description and presentation of both activity types and deployments so that they can easily be located in the Grid and thus become available on-demand. GLARE has been implemented based on a super-peer model with support for activity leasing, self management, and fault tolerance. Experiments are shown to reflect the effectiveness of the GLARE.
The Strong Chromatic Index of Random Graphs
Authors: Alan Frieze, Michael Krivelevich, Benny Sudakov
Venue: SIAM Journal on Discrete Mathematics (2005)

The strong chromatic index of a graph $G$, denoted by $\chi_s(G)$, is the minimum number of colors needed to color its edges so that each color class is an induced matching. In this paper we analyze the asymptotic behavior of this parameter in a random graph $G(n,p)$, for two regions of the edge probability $p=p(n)$. For the dense case, where $p$ is a constant, $0
Information access at the data item level: approaches to indicator retrieval from survey archive data bases
Authors: Ekkehard Mochmann
Venue: ACM SIGSOC Bulletin (1974)

Data archives are being challenged to provide more transparent and directly accessible data. Given the scope of already available materials and the yearly increase of the data base, effective means of information retrieval had to be developed.
A Framework to Evaluate Blocking Performance of Time-slotted Optical Burst Switched Networks
Authors: Ou Liang, Tan Xiansi, Ma Yajie, Yang Zongkai
Venue: Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary (2005)

Time-slotted optical burst switched network is a new paradigm to support IP over WDM by combining Time Division Multiplexing and Optical Burst switching technology. This paper presents a framework to evaluate blocking performance of time-slotted OBS networks with multi-fiber wavelength channels. The model is applied to analyze effect of the change of network parametesr as well as multiple-class traffics in the TS-OBS network. The effectiveness of our model is validated by simulation results. Our study shows that multi-fiber TS-OBS network is a potential technique to provide acceptable blocking performance for future Internet services.
A Boosting Approach to remove Class Label Noise
Authors: Amitava Karmaker, Stephen Kwek
Venue: Proceedings of the Fifth International Conference on Hybrid Intelligent Systems (2005)

Ensemble methods have been known to improve prediction accuracy over the base learning algorithm. AdaBoost is well-recognized for that in its class. However, it is susceptible to overfitting the training instances corrupted by class label noise. This paper proposes a modification to AdaBoost that is more tolerant to class label noise, which further enhances its ability to boost prediction accuracy. In particular, we observe that in Adaboost, the weight-hike of noisy examples can be constrained by careful application of a cut-off in their weights. Effectiveness of our algorithm is demonstrated empirically using some artificially generated data. We also corroborate this on a number of data sets from UCI repository [1]. In both experimental settings, the results obtained affirm the efficacy of our approach. Finally, some of the significant characteristics of our technique related to noisy environments have been investigated.
The GRAPE Project
Authors: Junichiro Makino
Venue: Computing in Science and Engineering (2006)

The goal of the Gravity Pipe (GRAPE) project is to accelerate astrophysical N-body simulations. Because almost all computing time is spent evaluating the gravitational force between particles, we can greatly accelerate many N-body simulations by developing a specialized hardware system for the force calculation.
A Hybrid Method for Fingerprint Image Quality Calculation
Authors: Jinqing Qi, Desiree Abdurrachim, Dongju Li, Hiroaki Kunieda
Venue: Proceedings of the Fourth IEEE Workshop on Automatic Identification Advanced Technologies (2005)

This paper proposes a new hybrid scheme to measure fingerprint image quality by combining both local and global features of a fingerprint image. Distinguished from traditional methods (e.g. local standard deviation or orientation information based method, etc.), not only the local texture features but also some global factors such as foreground area, central position of foreground, the number of minutiae and the existence of singular points, are taken into account in the proposed method. Besides the detail definitions of seven quality indices, two weighting methods are also proposed for finding the correlation between the finalquality value and each quality index. Experimental results on FVC2002 and our private database show that the EER (equal error rate) value can be downed by 12%-34% with 10% images rejected. It demonstrates that the hybrid method is an effective and efficient scheme to discard poor quality images and, hence, can be used to guarantee the reliability and performance of fingerprint recognition system.
Multi-Objective Genetic Algorithms for Vehicle Routing Problem with Time Windows
Authors: Beatrice Ombuki, Brian J. Ross, Franklin Hanshar
Venue: Applied Intelligence (2006)

The Vehicle Routing Problem with Time windows (VRPTW) is an extension of the capacity constrained Vehicle Routing Problem (VRP). The VRPTW is NP-Complete and instances with 100 customers or more are very hard to solve optimally. We represent the VRPTW as a multi-objective problem and present a genetic algorithm solution using the Pareto ranking technique. We use a direct interpretation of the VRPTW as a multi-objective problem, in which the two objective dimensions are number of vehicles and total cost (distance). An advantage of this approach is that it is unnecessary to derive weights for a weighted sum scoring formula. This prevents the introduction of solution bias towards either of the problem dimensions. We argue that the VRPTW is most naturally viewed as a multi-objective problem, in which both vehicles and cost are of equal value, depending on the needs of the user. A result of our research is that the multi-objective optimization genetic algorithm returns a set of solutions that fairly consider both of these dimensions. Our approach is quite effective, as it provides solutions competitive with the best known in the literature, as well as new solutions that are not biased toward the number of vehicles. A set of well-known benchmark data are used to compare the effectiveness of the proposed method for solving the VRPTW.
An approach for fault tolerant and secure data storage in collaborative work environments
Authors: Arun Subbiah, Douglas M. Blough
Venue: Proceedings of the 2005 ACM workshop on Storage security and survivability (2005)

We describe a novel approach for building a secure and fault tolerant data storage service in collaborative work environments, which uses perfect secret sharing schemes to store data. Perfect secret sharing schemes have found little use in managing generic data because of the high computation overheads incurred by such schemes. Our proposed approach uses a novel combination of XOR secret sharing and replication mechanisms, which drastically reduce the computation overheads and achieve speeds comparable to standard encryption schemes. The combination of secret sharing and replication manifests itself as an architectural framework, which has the attractive property that its dimension can be varied to exploit tradeoffs amongst different performance metrics. We evaluate the properties and performance of the proposed framework and show that the combination of perfect secret sharing and replication can be used to build efficient fault-tolerant and secure distributed data storage systems.
Automatic Model-Driven Recovery in Distributed Systems
Authors: Kaustubh R. Joshi, William H. Sanders, Matti A. Hiltunen, Richard D. Schlichting
Venue: Proceedings of the 24th IEEE Symposium on Reliable Distributed Systems (2005)

Automatic system monitoring and recovery has the potential to provide a low-cost solution for high availability. However, automating recovery is difficult in practice because of the challenge of accurate fault diagnosis in the presence of low coverage, poor localization ability, and false positives that are inherent in many widely used monitoring techniques. In this paper, we present a holistic model-based approach that overcomes these challenges and enables automatic recovery in distributed systems. To do so, it uses theoretically sound techniques including Bayesian estimation and Markov decision theory to provide controllers that choose good, if not optimal, recovery actions according to a user-defined optimization criteria. By combining monitoring and recovery, the approach realizes benefits that could not have been obtained by using them in isolation. In this paper, we present two recovery algorithms with complementary properties and trade-offs, and validate our algorithms (through simulation) by fault injection on a realistic e-commerce system.
Analysis of simulation with common random numbers: a note on Heikes et al. (1976)
Authors: Jack P. C. Kleijnen
Venue: ACM SIGSIM Simulation Digest (1979)

If different random number streams are used then traditional Analysis of Variance can be applied. However, the standard errors of the estimated effects should account for heterogeneity of variance. If common random numbers are used then the quite complicated procedure proposed by Heikes et al. in 1976, may be replaced by the simple Student t-statistic combined with the so-called Bonferroni - inequality. The statistical techniques are illustrated with a simple case study.
Are RFIDs Coming to Get You?
Authors: Martin Libicki
Venue: IEEE Security and Privacy (2005)

A review of the book, "RFID Applications, Security, and Privacy," edited by Simson Garfinkel and Beth Rosenberg.
WIGGLE: A new constrained molecular dynamics algorithm in Cartesian coordinates
Authors: Sang-Ho Lee, Kim Palmo, Samuel Krimm
Venue: Journal of Computational Physics (2005)

The theory of conventional constrained molecular dynamics (MD) simulations is reexamined based on a projection operator approach. A new algorithm, named WIGGLE, is presented for MD simulations with internal constraints. At each time step, the algorithm utilizes the constrained accelerations derived from velocity adjustments to satisfy the hidden constraints, and provides both initial and final constrained values that are almost an order of magnitude closer to the desired values than does RATTLE. Its performance is compared with those of RATTLE and SHAKE for an octane molecule. Also presented are a formalism to additionally constrain the angular momentum about the center of mass and an expression for the local energy drift during each integration time step.
WINP: A Window-Based Incremental and Parallel Clustering Algorithm for Very Large Databases
Authors: Zhang Qiang, Zhao Zheng, Sun Zhi Wei, Edward Daley
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

We introduce a new clustering algorithm called WINP for very large databases. Two different sizes of handling objects were used in WINP to acquire high accuracy and efficiency. WINP creates a window to detect approximate locations of clusters before accurate clustering processing. Clustering on these locations will reduce a lot of computations and get a good performance. WINP is the first algorithm to realize both incremental clustering and distributed parallel clustering. The advantages of our new approach are (1) It is very efficient; (2) It realizes distributed parallel processing and can be run on a number of workstations connected via local area network; (3) It introduces a novel incremental clustering method for new coming data in an already processed database; (4) It is effective in discovering clusters of arbitrary shape; (5) It is not sensitive to noise; and (6) It has some ability to deal with high dimensional points.
Intrusion detection in mobile ad hoc networks
Authors: Bo Sun
Venue:  (2004)

Most existent protocols, applications and services for Mobile Ad Hoc NETworks (MANETs) assume a cooperative and friendly network environment and do not accommodate security. Therefore, Intrusion Detection Systems (IDSs), serving as the second line of defense for information systems, are indispensable for MANETs with high security requirements. Central to the research described in this dissertation is the proposed two-level nonoverlapping Zone-Based Intrusion Detection System (ZBIDS) which fit the unique requirement of MANETs. First, in the low-level of ZBIDS, I propose an intrusion detection agent model and present a Markov Chain based anomaly detection algorithm. Local and trusted communication activities such as routing table related features are periodically selected and formatted with minimum errors from raw data. A Markov Chain based normal profile is then constructed to capture the temporal dependency among network activities and accommodate the dynamic nature of raw data. A local detection model aggregating abnormal behaviors is constructed to reflect recent subject activities in order to achieve low false positive ratio and high detection ratio. A set of criteria to tune parameters is developed and the performance trade-off is discussed. Second, I present a nonoverlapping Zone-based framework to manage locally generated alerts from a wider area. An alert data model conformed to the Intrusion Detection Message Exchange Format (IDMEF) is presented to suit the needs of MANETs. Furthermore, an aggregation algorithm utilizing attribute similarity from alert messages is proposed to integrate security related information from a wider area. In this way, the gateway nodes of ZBIDS can reduce false positive ratio, improve detection ratio, and present more diagnostic information about the attack. Third, MANET IDSs need to consider mobility impact and adjust their behavior dynamically. I first demonstrate that nodes' moving speed, a commonly used parameter in tuning IDS performance, is not an effective metric for the performance measurement of MANET IDSs. A new feature&mdash;link change rate&mdash;is then proposed as a unified metric for local MANET IDSs to adaptively select normal profiles. Different mobility models are utilized to evaluate the performance of the adaptive mechanisms.
Statistical analyses and markov modeling of duplication in genome evolution
Authors: Bhubaneswar Mishra
Venue:  (2005)

Genome evolution, especially duplications, was studied using a computational approach. The motivation of the thesis work comes from the &ldquo;evolution by gene duplication&rdquo; theory proposed by Susumu Ohno in 1970's, which postulates that duplication is one of the main forces in driving genome evolution and creating genome complexity. The research described in this dissertation investigates the duplication process systematically by analyzing whole-genome data. In particular, it studies the molecular mechanisms of the segmental duplications in mammalian genomes; the influence of duplications and other evolutionary processes on the genome statistical structures; and the measurement of phylogenetic distances between genomes based on the number of duplications and other evolutionary events. During the process, we have developed computational methods and mathematical models that take into account the nature of the data and incorporate the dynamics of the evolutionary processes. Using a Markov model of the segmental duplication process in the mammalian genomes, we found that about 12% of these recent segmental duplications were caused by recombination mediated by the recent active interspersed repeats in the mammalian genomes. In addition, the physical instabilities in the DNA sequence may also affect the process by introducing &ldquo;fragile&rdquo; sites in the genomes. A &ldquo;rich gets richer&rdquo; dynamics of the duplication process is suggested by the results of the analysis on the copy number distributions of the segmental duplications as well as other genomic components. Based on these observations, we propose a parsimonious genome evolution model, which includes three elementary processes: substitution, duplication and deletion. Using this model as our prior, we further developed a novel alignment-independent method that estimates the genomic evolutionary distance based on their word copy number variations. The phylogenomic distance measured using our method reflects the total number of substitution, duplication and deletion events since the divergence of the two genomes. Combined with conventional phylogenomic methods, we can study the modulation of the three different evolutionary processes in different lineages.
Ontology-driven content search for personalized education
Authors: Apple W. P. Fok
Venue: Proceedings of the 13th annual ACM international conference on Multimedia (2005)

Striving towards our education vision, Personalized Education, a Personalized Education System (PES) framework has been proposed [3] to exploit the vast amount of multimedia learning content on the Web. PEOnto, a fundamental component of PE, composes of multiple education ontologies to support communications among personalized education agents that provide a variety of PE services. Our research in PEOnto focuses on investigating techniques and a computation framework for supporting ontology-driven search and retrieval of multimedia learning content to meet various learning objectives.
Negative bias temperature instability (NBTI) in SiO2 and SiON gate dielectrics understood through disorder-controlled kinetics
Authors: B. Kaczer, V. Arkhipov, M. Jurczak, G. Groeseneken
Venue: Microelectronic Engineering (2005)

The acceleration of Negative Bias Temperature Instability (NBTI) in oxynitride gate dielectrics is explained within the framework of disorder-controlled hydrogen kinetics. Nitrogen is assumed to introduce deeper localized hydrogen states in gate oxide film, thus increasing the dispersion of hydrogen transport. The dispersion parameter is linked with the temperature-dependent NBTI power-law exponent, while hydrogen hopping frequency is inferred from the temperature dependence of NBTI power-law prefactor. NBTI exponents up to 0.5 are explained by transport of charged hydrogen.
Delay Test Generation with All Reachable Output Propagation and Multiple Excitations
Authors: Bhushan Vaidya, Mehdi B. Tahoori
Venue: Proceedings of the 20th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems (2005)

Delay testing based on transition faults propagated to all reachable outputs (TARO) is more effective in detecting defective chips compared to conventional transition faults. This paper describes efficient approaches to generate delay tests pattern based on TARO metric using Boolean Satisfiability (SAT). Different excitation paths are activated when multiple vectors are required for TARO propagation (N-detect) for better coverage of unmodeled faults. An efficient TARO test compaction method is also presented. Experimental results on several benchmarks show the effectiveness of this ATPG technique. Specifically, the increase in the number of test patterns due to using our TARO ATPG instead of transition fault testing (31%) is much smaller than previous TARO test generation techniques (2200%).