ppxscal/embedding_network huggingface dataset:
On the Ramsey Number of Sparse 3-Graphs
Authors: Brendan Nagle, Sayaka Olsen, Vojt&#x011b;ch R&#x00f6;dl, Mathias Schacht
Venue: Graphs and Combinatorics (2008)

We consider a hypergraph generalization of a conjecture of Burr and Erd&#x0151;s concerning the Ramsey number of graphs with bounded degree. It was shown by Chv&#x00e1;tal, R&#x00f6;dl, Trotter, and Szemer&#x00e9;di [The Ramsey number of a graph with bounded maximum degree, J. Combin. Theory Ser. B 34 (1983), no. 3, 239&#x2013;243] that the Ramsey number R(G) of a graph G of bounded maximum degree is linear in |V(G)|. We derive the analogous result for 3-uniform hypergraphs.
On sequential track extraction within the PMHT framework
Authors: Monika Wieneke, Wolfgang Koch
Venue: EURASIP Journal on Advances in Signal Processing (2008)

Tracking multiple targets in a cluttered environment is a challenging task. Probabilistic multiple hypothesis tracking (PMHT) is an efficient approach for dealing with it. Essentially PMHT is based on expectation-maximization for handling with association conflicts. Linearity in the number of targets and measurements is the main motivation for a further development and extension of this methodology. In particular, the problem of track extraction and deletion is apparently not yet satisfactorily solved within this framework. A sequential likelihood-ratio (LR) test for track extraction has been developed and integrated into the framework of traditional Bayesian multiple hypothesis tracking by Günter van Keuk in 1998. As PMHT is a multiscan approach as well, it also has the potential for track extraction. In this paper, an analogous integration of a sequential LR test into the PMHT framework is proposed. We present an LR formula for track extraction and deletion using the PMHT update formulae. The LR is thus a by-product of the PMHT iteration process, as PMHT provides all required ingredients for a sequential LR calculation. Therefore, the resulting update formula for the sequential LR test affords the development of track-before-detect algorithms for PMHT. The approach is illustrated by a simple example.
Sampling Archimedean copulas
Authors: Marius Hofert
Venue: Computational Statistics Data Analysis (2008)

The challenge of efficiently sampling exchangeable and nested Archimedean copulas is addressed. Specific focus is put on large dimensions, where methods involving generator derivatives are not applicable. Additionally, new conditions under which Archimedean copulas can be mixed to construct nested Archimedean copulas are presented. Moreover, for some Archimedean families, direct sampling algorithms are given. For other families, sampling algorithms based on numerical inversion of Laplace transforms are suggested. For this purpose, the Fixed Talbot, Gaver Stehfest, Gaver Wynn rho, and Laguerre series algorithm are compared in terms of precision and runtime. Examples are given, including both exchangeable and nested Archimedean copulas.
Wilson's theorem for consensus functions on hierarchies
Authors: R. C. Powers, J. M. White
Venue: Discrete Applied Mathematics (2008)

Wilson in 1972 gave a generalization of Arrow's theorem without the Pareto axiom. We prove a version of Wilson's theorem for consensus functions on hierarchies.
Service Based Enabling Service Availability in the MaTRICS: A Model-Driven Approach
Authors: Markus Bajohr, Tiziana Margaria, Bernhard Steffen
Venue: Proceedings of the Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (2006)

In today's business the availability of services is of central importance. To guarantee a higher availability of a service, like a web-service, it can be installed on several machines which are running in a hot-standby operation. In case of a fault one hot-standby service can take over the work of the faulty service. Novel to our approach is that this kind of redundancy can be applied to services, that normally do not support service availability concepts. The switching of one machine running in hot-standby mode to active can be done from an external system monitoring the service. MaTRICS is an architecture that allows the configuration of any service provided by a specific server. The specification is done by service logic graphs, which can be validated by model checking.
Context-oriented programming: beyond layers
Authors: Martin von Löwis, Marcus Denker, Oscar Nierstrasz
Venue: Proceedings of the 2007 international conference on Dynamic languages: in conjunction with the 15th International Smalltalk Joint Conference 2007 (2007)

While many software systems today have to be aware of the context in which they are executing, there is still little support for structuring a program with respect to context. A first step towards better context-orientation was the introduction of method layers. This paper proposes two additional language concepts, namely the implicit activation of method layers, and the introduction of dynamic variables.
Feedback scheduling of real-time divisible loads in clusters
Authors: Duc Luong, Jitender Deogun, Steve Goddard
Venue: ACM SIGBED Review (2008)

Quality of Service (QoS) provisioning for divisible loads in clusters can be enabled using real-time scheduling theory, but is based on an important assumption: that the scheduler knows the execution time of every task in the workload. Information from production clusters, however, shows that estimated execution times of tasks are often inaccurate. Most of the work on scheduling divisible loads on clusters is based on this information, and therefore maybe of limited use when applied in practice. In this paper, we present our ongoing work to develop an EDF (earliest deadline first) scheduling algorithm with a feedback mechanism that is able to solve this problem. The objective of the new algorithm is to provide QoS provisioning of divisible loads when estimated execution times of tasks are inaccurate.
Time distributed update of the NLMS algorithm coefficients for acoustic echo cancellers
Authors: Fotis E. Andritsopoulos, Yannis M. Mitsos, Christos N. Charopoulos, Gregory A. Doumenis, Constantin N. Papaodysseus
Venue: Proceedings of the 5th WSEAS International Conference on Applied Mathematics (2004)

Hands free operation is a standard feature of many fixed and mobile telephone sets. In hands free telephony, echoes appear at the far end, because of the open-air acoustic path between the loudspeaker and microphone at the near end. This paper presents an efficient realization of an Acoustic Echo Cancellation (AEC) algorithm, as well as its implementation structure and performance aspects. The algorithm is based on the Least Mean Square (LMS) family of algorithms [2]. The innovative features of this algorithm provide significant gains in terms of computational complexity and signal quality. The proposed method is based on the segmentary update of the coefficients of the N-LMS filter. It is proved that the convergence behavior of the introduced algorithm is similar to the N-LMS; it is also proved that segmentary update provides similar quality to the original N-LMS, while significantly reducing complexity. The algorithm can be easily implemented and it is particularly suited for simultaneous echo cancellation on multiple voice channels. It is hence appropriate for echo cancellation implementation in access devices as well as in central office equipment. The results presented in this paper have been collected from the algorithm's implementation on a standard commercial DSP.
Scale-sensitive dimensions, uniform convergence, and learnability
Authors: N. Alon
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

Learnability in Valiant's PAC learning model has been shown to be strongly related to the existence of uniform laws of large numbers. These laws define a distribution-free convergence property of means to expectations uniformly over classes of random variables. Classes of real-valued functions enjoying such a property are also known as uniform Gliveako-Cantelli classes. In this paper we prove, through a generalization of Sauer's lemma that may be interesting in its own right, a new characterization of uniform Glivenko-Cantelli classes. Our characterization yields Dudley, Gine, and Zinn's previous characterization as a corollary. Furthermore, it is the first based on a simple combinatorial quantity generalizing the Vapnik-Chervonenkis dimension. We apply this result to characterize PAC learnability in the statistical regression framework of probabilistic concepts, solving an open problem posed by Kearns and Schapire. Our characterization shows that the accuracy parameter plays a crucial role in determining the effective complexity of the learner's hypothesis class.
Estimating software size with UML models
Authors: Ghislain Levesque, Valery Bevo, De Tran Cao
Venue: Proceedings of the 2008 C3S2E conference (2008)

Function points have been used for more than 25 years for estimating software size and building productivity models. Today, three methods to do it are accepted as ISO standards. The theory behind this type of measurement is more explicit but none of these methods have yet been fully automated. All of them still require the involvement of an expert in order to be used correctly. Why is it so difficult to implement those methods? In our opinion, the main reason lies in the fact that each method has its own vocabulary and its own way of modeling software. The research work presented here has been realised mainly through two doctoral theses, one trying to automate the measure from a UML perspective and the other to add an objective measure of complexity to a standard measure in COSMIC-FFP in order to reach a higher level of confidence with those measures. So far, it can be concluded that, from UML use-cases and Actor-Object sequence diagrams of a system application, the number of messages exchanged correspond to the number of function points according to the COSMIC-FFP method. Going farther and adding the number of conditions or decisions to be applied according to UML version 2.0 would add more precision taking into account the complexity of the processes.
Investigating students' perceived satisfaction, behavioral intention, and effectiveness of e-learning: A case study of the Blackboard system
Authors: Shu-Sheng Liaw
Venue: Computers Education (2008)

Although the benefits of e-learning have been discussed in various previous studies; it is a critical issue of better understanding the reasons why some learners are dissatisfied with the e-learning experience. Therefore, this research investigates learners' satisfaction, behavioral intentions, and the effectiveness of the Blackboard e-learning system. A total of 424 university students were surveyed using a standard questionnaire. The results showed that perceived self-efficacy is a critical factor that influences learners' satisfaction with the Blackboard e-learning system. Perceived usefulness and perceived satisfaction both contribute to the learners' behavioral intention to use the e-learning system. Furthermore, e-learning effectiveness can be influenced by multimedia instruction, interactive learning activities, and e-learning system quality. This research proposes a conceptual model for understanding learners' satisfaction, behavioral intention, and effectiveness of using the e-learning system.
Deriving State Machines from TinyOS Programs Using Symbolic Execution
Authors: Nupur Kothari, Todd Millstein, Ramesh Govindan
Venue: Proceedings of the 7th international conference on Information processing in sensor networks (2008)

The most common programming languages and platforms for sensor networks foster a low-level programming style. This design provides fine-grained control over the underlying sensor devices, which is critical given their severe resource constraints. However, this design also makes programs difficult to understand, maintain, and debug. In this paper, we describe an approach to automatically recover the high-level system logic from such low-level programs, along with an instantiation of the approach for nesC programs running on top of the TinyOS operating system. We adapt the technique of symbolic execution from the program analysis community to handle the event-driven natureof TinyOS, providing a generic component for approximating the behavior of a sensor network application or system component. We then employ a form of predicate abstraction on the resulting information to automatically produce a finite state machine representation of the component. We have used our tool, called FSMGen, to automatically produce compact and fairly accurate state machines for several TinyOS applications and protocols. We illustrate how this high-level program representation can be used to aid programmer understanding, error detection, and program validation.
Designing Workflows for Grid Enabled Internet Instruments
Authors: David Stirling, Ian Welch, Peter Komisarczuk
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

To analyse malicious activity on the Internet, instruments such as network telescopes and honeypots are effective tools that can be deployed. Such tools can be deployed in large scale using Grid computing. Manual deployment of instruments wastes resources because common tasks and solutions are reinvented by different deployers and the resulting architectures are often not interoperable or sufficiently scalable. Research is underway to develop a framework for scalable and automated deployment, with Grid technologies providing a promising basis. The integration of Grid technology with instrumentation has two inititiatives. These are CIMA and GRIDCC, with GRIDCC being available as open source. A key area is workflow within the framework, for which BPEL (Business Process Execution Language) is used in GRIDCC and considered for initial use for Grid Enabled Internet Instruments. We have found BPEL has limitations when implementing such as framework, particularly in the areas of concurrency and statefullness. We propose implementation independent workflows and identify extensions to BPEL in order to realise them. We believe that BPEL with modification can be used to implement a framework for Internet instruments-Grid computing integration.
Anomaly detection in hyperspectral imagery based on maximum entropy and nonparametric estimation
Authors: Lin He, Quan Pan, Wei Di, Yuanqing Li
Venue: Pattern Recognition Letters (2008)

This paper presents several maximum entropy and nonparametric estimation detectors (MENEDs) which belong to two categories to detect anomaly targets in hyperspectral imagery. First, probability density of target is estimated using Principle of Maximum Entropy according to the low-probability occurrence of target, which simplifies the generalize likelihood ratio test to merely testing background likelihood. Then considering the high complexity of hyperspectral data, in conjunction with the low-probability occurrence of target, sample-depended multimode model (SDMM) is presented to obtain the probability density of the background. Finally, the estimated probability density of the background is tested to detect targets. The proposed MENEDs greatly depend on hyperspectral data sample, rather than the statistical model, to extract the statistical information, which alleviates statistical model discrepancy and has explicit physical mechanism on detection. Experimental results on visible/near-infrared hyperspectral imagery of type I Operational Modular Imaging Spectrometer (OMIS-I) demonstrate that MENEDs perform better than several known detectors, including RX detector (RXD), normalized RXD (NRXD), modified RXD (MRXD), correlation matrix based NRXD (CNRXD), correlation matrix based MRXD (CMRXD), unified target detector (UTD) and low probability detection (LPD).
Determining numbers of workstations and operators for a linear walking-worker assembly line
Authors: Q. Wang, G. W. Owen, A. R. Mileham
Venue: International Journal of Computer Integrated Manufacturing (2007)

This paper presents an investigation into a system of linear walking-worker (WW) assembly lines that have been implemented in a local small and medium enterprise (SME). The work aims to observe the relevant impact on logical interactions and interrelationships between the number of workstations and the number of walking workers against the system performance and to minimize these numbers providing a quick response in re-configuration of the system to meet a given output and cycle time. This has been achieved by developing a simulation model for a theoretical study into the linear WW system using a manufacturing-focused simulation tool. By examination of the results of a series of simulation experiments, a minimization of the numbers of workstations and walking workers for a linear WW line configuration can be quantified. The research concluded that this multiskilled linear WW assembly line is able to sustain a higher flexibility and efficiency as compared with a conventional linear fixed-worker (FW) assembly line under similar conditions.
A quantum bit commitment scheme provably unbreakable by both parties
Authors: G. Brassard
Venue: Proceedings of the 1993 IEEE 34th Annual Foundations of Computer Science (1993)

We describe a complete protocol for bit commitment based on the transmission of polarized photons. We show that under the laws of quantum physics, this protocol cannot be cheated by either party except with exponentially small probability (exponential in the running time needed to implement the honest protocol). A more thorough analysis is required to adjust all the constants used in this paper to get the best performance from our construction. Better performances may probably be achieved by using a third conjugate transmission-reception basis of circular polarization.
Robust matching and recognition using context-dependent kernels
Authors: Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabarisoa, Renaud Keriven
Venue: Proceedings of the 25th international conference on Machine learning (2008)

The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to handle fixed-length data, their extension to unordered, variable-length data became more than necessary for real pattern recognition problems such as object recognition and bioinformatics. We focus in this paper on object recognition using a new type of kernel referred to as "context-dependent". Objects, seen as constellations of local features (interest points, regions, etc.), are matched by minimizing an energy function mixing (1) a fidelity term which measures the quality of feature matching, (2) a neighborhood criterion which captures the object geometry and (3) a regularization term. We will show that the fixed-point of this energy is a "context-dependent" kernel ("CDK") which also satisfies the Mercer condition. Experiments conducted on object recognition show that when plugging our kernel in SVMs, we clearly outperform SVMs with "context-free" kernels.
Revisiting stochastic loss networks: structures and algorithms
Authors: Kyomin Jung, Yingdong Lu, Devavrat Shah, Mayank Sharma, Mark S. Squillante
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

This paper considers structural and algorithmic problems in stochastic loss networks. The very popular Erlang approximation can be shown to provide relatively poor performance estimates, especially for loss networks in the critically loaded regime. This paper proposes a novel algorithm for estimating the stationary loss probabilities in stochastic loss networks based on structural properties of the exact stationary distribution, which is shown to always converge, exponentially fast, to the asymptotically exact results. Using a variational characterization of the stationary distribution, an alternative proof is provided for an important result due to Kelly, which is simpler and may be of interest in its own right. This paper also determines structural properties of the inverse Erlang function characterizing the region of capacities that ensures offered traffic is served within a set of loss probabilities. Numerical experiments investigate various issues of both theoretical and practical interest.
Quadratic dynamical systems
Authors: Y. Rabinovich
Venue: Proceedings of the 33rd Annual Symposium on Foundations of Computer Science (1992)

The paper promotes the study of computational aspects, primarily the convergence rate, of nonlinear dynamical systems from a combinatorial perspective. The authors identify the class of symmetric quadratic systems. Such systems have been widely used to model phenomena in the natural sciences, and also provide an appropriate framework for the study of genetic algorithms in combinatorial optimisation. They prove several fundamental general properties of these systems, notably that every trajectory converges to a fixed point. They go on to give a detailed analysis of a quadratic system defined in a natural way on probability distributions over the set of matchings in a graph. In particular, they prove that convergence to the limit requires only polynomial time when the graph is a tree. This result demonstrates that such systems, though nonlinear, are amenable to quantitative analysis.
Usability Aspects of WCET Analysis
Authors: Jan Gustafsson
Venue: Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (2008)

Knowing the program timing characteristics is fundamental to the successful design and execution of real-time systems. A critical timing measure is the worst-case execution time (WCET) of a program. Often, timing analysis in industry is done by measurements. Recently, tools for deriving WCET estimates have reached the market. With more widespread use of WCET tools in industry, the usability aspects of these tools will be of growing importance. In this paper we discuss usability using the results of the WCET Challenge 2006, which was the first event that compared different WCET tools using the same set of benchmarks. Another source of input to the discussion are experiences from industrial case-studies of WCET tools. Finally, we point out some areas for future research and development for WCET analysis methods and tools.
Hybrid evolutionary built decision trees for prediction of perspective cross-country skiers
Authors: Milan Zorman, Branimir Černohorski, Gregor Goršek, Ojsteršek Milan
Venue: Proceedings of the 4th WSEAS International Conference on Applied Informatics and Communications (2004)

In this paper we present an application of intelligent systems using hybrid evolutionary built decision trees to extract new knowledge from a small 'Cross-country skiers' database. Evolutionary built decision trees approach is a combination of one well known machine learning approach - decision trees and recently very popular evolutionary algorithms. By combining both approaches we were aiming for a method, that would combine the advantages of both approaches and should find optimal solution sooner than classical decision tree method. Such method is very suitable for application in fields like medicine and health care, where we have to combine high accuracy of the classifier and transparent knowledge representation. In the particular case of 'Cross-country skiers' database, our main goal was to develop a classifier, that would have as high prediction accuracy as possible for all three outcomes. On the other hand we were also interested in attributes that are the most important for the prediction of cross-country skier's competition potentials. The results of testing are relatively good. Overall accuracy of the classifier, which was tested on the test set ranged from 62.5% to 87.5%. In some cases we were also able to achieve relatively high average class accuracies, which was not a trivial task on database with three possible decisions and small unbalanced training set.