ppxscal/embedding_network huggingface dataset:
Trans-dichotomous algorithms for minimum spanning trees and shortest paths
Authors: M. L. Fredman
Venue: Proceedings of the 31st Annual Symposium on Foundations of Computer Science (1990)

The fusion tree method is extended to develop a linear-time algorithm for the minimum spanning tree problem and an O(m+n log n/log log n) implementation of Dijkstra's shortest-path algorithm for a graph with n vertices and m edges. The shortest-path algorithm surpasses information-theoretic limitations. The extension of the fusion tree method involves the development of a new data structure, the atomic heap. The atomic heap accommodates heap (priority queue) operations in constant amortized time under suitable polylog restrictions on the heap size. The linear-time minimum spanning tree algorithm results from a direct application of the atomic heap. To obtain the shortest path algorithm, the atomic heap is used as a building block to construct a new data structure, the AF-heap, which has no size restrictions and surpasses information theoretic limitations. The AF-heap belongs to the Fibonacci heap family.
Clustering Oriented Architectures in Medical Sensor Environments
Authors: Eleni Klaoudatou, Elisavet Konstantinou, Georgios Kambourakis, Stefanos Gritzalis
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

Wireless sensor networks are expected to make a significant contribution in the healthcare sector by enabling continuous patient monitoring. Since medical services and the associated to them information are considered particularly sensitive, the employment of wireless sensors in medical environments poses many security issues and challenges. However, security services and the underlying key management mechanisms cannot be seen separately from the efficiency and scalability requirements. Network clustering used in both routing and group key management mechanisms can improve the efficiency and scalability and therefore can also be envisioned in medical environments. This paper introduces a general framework for cluster-based wireless sensor medical environments on the top of which efficient security mechanisms can rely. We describe two different scenarios for infrastructure and infrastructure-less application environments, covering this way a wide area of medical applications (in-hospital and medical emergencies). We also examine the existing group-key management schemes for cluster-based wireless networks and discuss which protocols fit best for each proposed scenario.
Universal motor NN modelling
Authors: José Carlos Quadrado
Venue: Proceedings of the 4th WSEAS International Conference on Systems Theory and Scientific Computation (2004)

The paper presents a hybrid modelling of electrical motors. To improve the performance, the analytical model is combined with Adaptive-Network-based Fuzzy Inference System (ANFIS) to compensate the modelling error. The architecture and hybrid learning procedure is presented. The method is applied to universal motors. In the first step, parameters of analytical model are identified by simple least-square method. Then, the modelling error is compensated by hybrid learning procedure, preserving the meaning of the physical parameters. The reliability of the obtained model is increased.
Emulating query-biased summaries using document titles
Authors: Hideo Joho, David Hannah, Joemon M. Jose
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Generating query-biased summaries can take up a large part of the response time of interactive information retrieval (IIR) systems. This paper proposes to use document titles as an alternative to queries in the generation of summaries. The use of document titles allows us to pre-generate summaries statically, and thus, improve the response speed of IIR systems. Our experiments suggest that title-biased summaries are a promising alternative to query-biased summaries.
Cooperative work in software testing
Authors: David Martin, John Rooksby, Mark Rouncefield, Ian Sommerville
Venue: Proceedings of the 2008 international workshop on Cooperative and human aspects of software engineering (2008)

Substantial effort in the development of any large system is invested in testing. Studies of testing tend to be either technical or concerned with the cognitive ability of testers. Our experience is that testing is not technical but socio-technical, involving a great deal of human and organisational effort, and that testing is not simply the kind of decontextualised 'puzzle solving' many cognitive approaches imply. We believe that cooperative work is foundational to getting testing done. In this position paper, we use data from four ethnographic studies to discuss just what that cooperative work is.
Brain Differences Visualized in the Blind Using Tensor Manifold Statistics and Diffusion Tensor Imaging
Authors: Agatha D. Lee, Natasha Leporé, Franco Lepore, Flamine Alary, Patrice Voss, Yiyu Chou, Caroline Brun, Marina Barysheva, Arthur W. Toga, Paul M. Thompson
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

Diffusion tensor magnetic resonance imaging (DTI) reveals the local orientation and integrity of white matter fiber structure based on imaging multidirectional water diffusion. Group differences in DTI images are often computed from single scalar measures, e.g., the Fractional Anisotropy (FA), discarding much of the information in the 6-parameter symmetric diffusion tensor. Here, we compute multivariate 6D tensor statistics to detect brain morphological changes in 12 blind subjects versus 14 sighted controls. After Log-Euclidean tensor denoising, images were fluidly registered to a common template. Fluidly-convected tensor signals were re-oriented by applying the local rotational and translational component of the deformation. Since symmetric, positive-definite matrices form a non-Euclidean manifold, we applied a Riemannian manifold version of the Hotelling's T 2 test to the logarithms of the tensors, using a log-Euclidean metric. Statistics on the full 6D tensor-valued images outperformed univariate analysis of scalar images, such as the FA and the geodesic anisotropy (GA).
Subdifferential characterization of approximate convexity: the lower semicontinuous case
Authors: A. Daniilidis, F. Jules, M. Lassonde
Venue: Mathematical Programming: Series A and B (2008)

It is known that a locally Lipschitz function is approximately convex if, and only if, its Clarke subdifferential is a submonotone operator. The main object of this work is to extend the above characterization to the class of lower semicontinuous functions. To this end, we establish a new approximate mean value inequality involving three points. We also show that an analogue of the Rockafellar maximal monotonicity theorem holds for this class of functions and we discuss the case of arbitrary subdifferentials.
On the Convergence of Fourier Series of Computable Lebesgue Integrable Functions
Authors: Philippe Moser
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2008)

This paper studies how well computable functions can be approximated by their Fourier series. To this end, we equip the space of L^p-computable functions (computable Lebesgue integrable functions) with a size notion, by introducing L^p-computable Baire categories. We show that L^p-computable Baire categories satisfy the following three basic properties. Singleton sets {f} (where f is L^p-computable) are meager, suitable infinite unions of meager sets are meager, and the whole space of L^p-computable functions is not meager. We give an alternative characterization of meager sets via Banach Mazur games. We study the convergence of Fourier series for L^p-computable functions and show that whereas for every p>1, the Fourier series of every L^p-computable function f converges to f in the L^p norm, the set of L^1-computable functions whose Fourier series does not diverge almost everywhere is meager.
Autonomic Patterns: Modelling Data Killing Patterns Using High-Level Petri Nets
Authors: Wallace A. Pinheiro, Geraldo Xexéo, Jano M. de Souza
Venue: Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems (2008)

Pattern development for complex systems is a common practice nowadays. These patterns delineate the development of many systems, identifying behaviours and structures that can be re-used in several problems. Autonomic Data Killing Patterns represent a need when thinking about the final destination of data. Nowadays, the knowledge on data killing is as important as the knowledge on data storage. This work discusses this idea and shows patterns to deal with related issues. This approach can help organizations and people to control irrelevant data through the knowledge of different ways to eliminate them. The patterns are described using high-level Petri nets and active rules. This strategy allows to monitor and to act in the environment, an important characteristic of autonomic systems.
Convergence of the Magnus Series
Authors: Per Christian Moan, Jitse Niesen
Venue: Foundations of Computational Mathematics (2008)

The Magnus series is an infinite series which arises in the study of linear ordinary differential equations. If the series converges, then the matrix exponential of the sum equals the fundamental solution of the differential equation. The question considered in this paper is: When does the series converge? The main result establishes a sufficient condition for convergence, which improves on several earlier results.
Community connections: lessons learned developing and maintaining a computer science service-learning program
Authors: Christopher H. Brooks
Venue: Proceedings of the 39th SIGCSE technical symposium on Computer science education (2008)

This paper describes Community Connections, an ongoing service-learning project at the University of San Francisco aimed at bridging the digital divide. We discuss Community Connections' work both in San Francisco and in Peru, the advantages and learning outcomes of incorporating service-learning into a traditional computer science curriculum, outline some of the pitfalls and challenges in implementing this program, and provide advice for implementing technology-oriented service-learning programs at other institutions based on our experiences.
Estimating the number of components in a mixture of multilayer perceptrons
Authors: M. Olteanu, J. Rynkiewicz
Venue: Neurocomputing (2008)

Bayesian information criterion (BIC) criterion is widely used by the neural-network community for model selection tasks, although its convergence properties are not always theoretically established. In this paper we will focus on estimating the number of components in a mixture of multilayer perceptrons and proving the convergence of the BIC criterion in this frame. The penalized marginal-likelihood for mixture models and hidden Markov models introduced by Keribin [Consistent estimation of the order of mixture models, Sankhya Indian J. Stat. 62 (2000) 49-66] and, respectively, Gassiat [Likelihood ratio inequalities with applications to various mixtures, Ann. Inst. Henri Poincare 38 (2002) 897-906] is extended to mixtures of multilayer perceptrons for which a penalized-likelihood criterion is proposed. We prove its convergence under some hypothesis which involve essentially the bracketing entropy of the generalized score-function class and illustrate it by some numerical examples.
Simulation Complexity
Authors: Nicholas J. Hay
Venue: Fundamenta Informaticae (2008)

In Algorithmic Information Theory, the algorithmic complexity of a sequence is the length of the shortest program which generates it. Is there a measure of the complexity of a computer? We define the simulation complexity of a computer to be the least cost of simulating that computer on a fixed universal computer. We generalise this to processes, computers which can have potentially infinite output (e.g. monotone Turingmachines). Thismeasure has monotone complexity as a special case. Simulation complexity has applications to sequence prediction, leading to a clarification of a central prediction error inequality and a stronger form of dominance. Enumerable semimeasures are functions which represent sequence predictors. These semimeasures can be in turn represented by processes. A universal process generates a universal semimeasure: one that outperforms any other predictor but for a cost depending on how complex that predictor is. This extra cost is exactly the simulation complexity of the predictor.
Fire danger monitoring using RADARSAT-1 over northern boreal forests
Authors: K. N. Abbott, B. Leblon, G. C. Staples, D. A. Maclean, M. E. Alexander
Venue: International Journal of Remote Sensing (2007)

The goal of this study was to evaluate the potential use of RADARSAT-1 images to assess daily variations in dead fuel moisture over a northern boreal forest area, as parameterized by the Canadian Forest Fire Weather Index (FWI) System. The study area was located in the south-central region of Canada's Northwest Territories and was comprised of three land cover classes (mature forest, burned forest, and fireguard areas). Nineteen RADARSAT-1 images were acquired over the study area in June 2000 and August 2002, and their backscatter was compared to weather data and to the FWI System components. In both cases, the influences of incident angle and land cover class were measured. Radar backscatter was related to rainfall, and strong relationships were observed with the FWI System codes and indexes, particularly for Duff Moisture Code (R 2 = 0.68-0.83), Drought Code (R 2 = 0.77-0.82), Build-up Index (R 2 = 0.72-0.86), and FWI (R 2 = 0.62-0.85). The best regression models were obtained using a stepwise regression procedure in which radar backscatter from the burned forest was used as the independent variable.
Grace hopper visits the neighborhood
Authors: Gloria Childress Townsend, Lecia Barker, Suzanne Menzel, J. McGrath Cohoon
Venue: Proceedings of the 39th SIGCSE technical symposium on Computer science education (2008)

This paper highlights several viewpoints concerning a small regional conference for women in computing, which is modeled after the successful and well-known Grace Hopper Celebration of Women in Computing. The viewpoints include rationale for the conference, descriptions of the celebration that provide a snapshot which captures the ease of organizing a similar event at other regional sites, additional sources for finding complete information (including a detailed how-to manual) and an account of the assessment of two recent regional celebrations performed by senior researchers at the National Center of Women and Information Technology (NCWIT).
Web Services for the Integration of XML-Based Content into Learning Platforms: A Three-level Model
Authors: Reinhold Kröger, Ulrike Lucke, Markus Schmid, Djamshid Tavangarian
Venue: Proceedings of the Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (2006)

Along with the increasing diversity of educational markup languages there is a strong need for flexible integration ofsuch content into learning platforms. Therefore, we have identified four basic mechanisms: plain linking from the platform to external content, conversion of content into the platforms native format, and service-based invocation of external content as well as specific functionality related to it. Architectural principles, benefits, and drawbacks of these concepts are compared, and exemplary realizations are described.
Improving sensor network immunity under worm attacks: a software diversity approach
Authors: Yi Yang, Sencun Zhu, Guohong Cao
Venue: Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing (2008)

Because of cost and resource constraints, sensor nodes do not have a complicated hardware architecture or operating system to protect program safety. Hence, the notorious buffer-overflow vulnerability that has caused numerous Internet worm attacks could also be exploited to attack sensor networks. We call the malicious code that exploits a buffer-overflow vulnerability in a sensor program sensor worm. Clearly, sensor worm will be a serious threat, if not the most dangerous one, when an attacker could simply send a single packet to compromise the entire sensor network. Despite its importance, so far little work has been focused on sensor worms. In this work, we first illustrate the feasibility of launching sensor worms through real experiments on Mica2 motes. Inspired by the survivability through heterogeneity philosophy, we then explore the technique of software diversity to combat sensor worms. Given a limited number of software versions, we design an efficient algorithm to assign the appropriate version of software to each sensor, so that sensor worms are restrained from propagation. We also examine the impact of sensor node deployment errors on worm propagation, which directs the selection of our system parameters based on percolation theory. Finally, extensive analytical and simulation results confirm the effectiveness of our scheme in containing sensor worms.
Software, Data and Modelling News: Visualization of a general family of growth functions and probability distributions - The Growth-curve Explorer
Authors: Oscar García
Venue: Environmental Modelling Software (2008)

A variety of growth-curve functions are used in many areas of environmental science. Closely related probability distributions are useful in simulation modelling. A model that includes many of these functions and distributions as special cases is discussed, and an interactive Java applet that facilitates the visual exploration of the various curve characteristics and interrelationships is presented.
Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: application to the urban area of Athens, Greece
Authors: M. Stathopoulou, C. Cartalis, M. Petrakis
Venue: International Journal of Remote Sensing (2007)

This study examines the potential of the combined use of the land cover/land use information provided by the Corine Land Cover (CLC) database with Landsat satellite data for the definition and quantitative correlation of emissivity with various land covers and land uses that describe a certain territory. Surface emissivity in the 10.5-12.5 µm wavelength range is derived using Landsat data and the Normalized Difference Vegetation Index Thresholds method (NDVITHM), whereas mean emissivity values for selected urban/non-urban land cover types are estimated by integrating the emissivity image with the land cover vector data. The method is applied to the greater Athens area, Greece, in order to estimate the emissivity of various land cover types found within the urban setting. Analysis of variance (ANOVA) indicates statistically significant differences in emissivity associated with different land cover types. Furthermore, statistical results demonstrate that the method is very effective and can provide emissivity values of different land cover types with good accuracy and therefore can quantitatively link emissivity with surface type.
Human-competitive evolved antennas
Authors: Jason d. Lohn, Gregory s. Hornby, Derek s. Linden
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (2008)

We present a case study showing a human-competitive design of an evolved antenna that was deployed on a NASA spacecraft in 2006. We were fortunate to develop our antennas in parallel with another group using traditional design methodologies. This allowed us to demonstrate that our techniques were human-competitive because our automatically designed antenna could be directly compared to a human-designed antenna. The antennas described below were evolved to meet a challenging set of mission requirements, most notably the combination of wide beamwidth for a circularly polarized wave and wide bandwidth. Two evolutionary algorithms were used in the development process: one used a genetic algorithm style representation that did not allow branching in the antenna arms; the second used a genetic programming style tree-structured representation that allowed branching in the antenna arms. The highest performance antennas from both algorithms were fabricated and tested, and both yielded very similar performance. Both antennas were comparable in performance to a hand-designed antenna produced by the antenna contractor for the mission, and so we consider them examples of human-competitive performance by evolutionary algorithms. Our design was approved for flight, and three copies of it were successfully flown on NASA's Space Technology 5 mission between March 22 and June 30, 2006. These evolved antennas represent the first evolved hardware in space and the first evolved antennas to be deployed.
A High Efficient Quality Control Strategy for Wavelet-Based ECG Data Compression System
Authors: Cheng-Tung Ku, King-Chu Hung, Huan-Sheng Wang
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 02 (2008)

Maintaining retrieved signal with desired quality is crucial for ECG data compression. In this paper, a high efficient quality control strategy is proposed for wavelet-based ECG data compression. The strategy is based on a modified non-linear quantization scheme that can obtain a linear distortion behavior with respective to a control variable. The linear distortion characteristic supports the design of a linear control variable prediction algorithm. By using the MIT-BIH arrhythmia database, the experimental results show that the linear control variable prediction method can effectively improve the convergence speed than the previous literatures.
Analyzing the evolution of eclipse plugins
Authors: Michel Wermelinger, Yijun Yu
Venue: Proceedings of the 2008 international working conference on Mining software repositories (2008)

Eclipse is a good example of a modern component-based complex system that is designed for long-term evolution, due to its architecture of reusable and extensible components. This paper presents our preliminary results about the evolution of Eclipse's architecture, based on a lightweight and scalable analysis of the metadata in Eclipse's sources. We find that the development of Eclipse follows a systematic process: most architectural changes take place in milestones, and maintenance releases only make exceptional changes to component dependencies. We also found a stable architectural core that remains since the first release.
Checkpoints and continuations instead of nested transactions
Authors: Eric Koskinen, Maurice Herlihy
Venue: Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures (2008)

We present a mechanism for partially aborting transactions through the use of data structure checkpoints and control-flow continuations. In particular, we show that boosted transactions [9] already have built-in restoration points and afford a simple, efficient implementation. Our mechanism is far simpler than previous work, which relied on complex nesting schemes to establish checkpoints. We demonstrate syntactic advantages and we quantify the overhead of checkpoints and explore several examples, illustrating the utility of partially aborting transactions. We additionally present a novel queue-based spin lock which allows threads to timeout and differ in priority. Unlike the known lock due to Craig [5], our lock is more efficient for priority schemes of few levels.
Connected but not path-connected subspaces of infinite graphs
Authors: Angelos Georgakopoulos
Venue: Combinatorica (2007)

Solving a problem of Diestel [9] relevant to the theory of cycle spaces of infinite graphs, we show that the Freudenthal compactification of a locally finite graph can have connected subsets that are not path-connected. However we prove that connectedness and path-connectedness to coincide for all but a few sets, which have a complicated structure.