ppxscal/embedding_network huggingface dataset:
Queuing Models for Field Defect Resolution Process
Authors: Swapna S. Gokhale, Robert E. Mullen
Venue: Proceedings of the 17th International Symposium on Software Reliability Engineering (2006)

This paper explores a novel application of queuing theory to the corrective software maintenance problem to support quantitative balancing between resources and responsiveness. Initially, we provide a detailed description of the states a defect traverses from find to fix and a definition and justification of mean time to resolution as a useful process metric. We consider the effect of queuing system structures, priority levels and priority disciplines on the differential mean times to resolution of defects of different severities. We find that modeling the defect resolution capacity of a software engineering group as n identical M/M/1 servers provides a flexible and realistic approximation to the queuing behavior of four different organizations. We consider three queuing disciplines. Though purely preemptive and non-preemptive priority disciplines may be suited for other groups, our data was best fit by a mixed discipline, one in which only the most severe defects preempt ongoing service activities of lesser severities. We provide two examples of the utility of such a model: Given the reasonable assumption that the most severe defects have the highest impact on reliability, we find that the reduction of the resolution time for these defects must come from changes reducing the service time. On the other hand the effect of additional engineering resources on the resolution time of less severe defects is easily computed and can be significant.
Logic and refinement for charts
Authors: Greg Reeve, Steve Reeves
Venue: Proceedings of the 29th Australasian Computer Science Conference - Volume 48 (2006)

We introduce a logic for reasoning about and constructing refinements for µ-Charts, a rational simplification and reconstruction of Statecharts. The method of derivation of the logic is that a semantics for the language is constructed in Z and the existing logic and refinement calculus of Z is then used to induce the logic and refinement calculus of µ-Charts, proceeding by a series of definitions and conservative extensions and hence generating a sound logic for µ-Charts, given that the soundness of the Z logic has already been established.
A neural network for robust LCMP beamforming
Authors: Youshen Xia, Gang Feng
Venue: Signal Processing (2006)

Calculating an optimal beamforming weight is a main task of beamforming. Quadratic constraints on the weight vector of an adaptive linearly constrained minimum power (LCMP) beamformer can improve robustness to pointing errors and to random perturbations in sensor parameters. This paper presents a neural network approach to the robust LCMP beamformer with the quadratic constraint. Compared with the existing neural networks for the LCMP beamformer, the proposed neural network converges fast to an optimal weight. Compared with the existing adaptive algorithms for the robust LCMP beamformer, in addition to parallel implementation, the proposed neural network is guaranteed to converge exponentially to an optimal weight. Simulations demonstrate that the proposed neural network has better interference suppression and faster convergence than the existing neural networks and the adaptive algorithms.
Chaotification via feedback control: theories, methods, and applications
Authors: Guanrong Chen
Venue: Proceedings of the 2003 International Conference on Physics and Control - Volume 2 (2003)

This article introduces the notion of chaotification (or, anticontrol of chaos), which means to make an originally non-chaotic dynamical system chaotic, or to enhance the existing chaos of a chaotic system, via feedback control techniques. The discrete case is discussed in somewhat detail, while the continuous case is outlined briefly. Basic theories and methods are described, and potential applications are mentioned as motivation of the research.
Speech enhancement using the bispectrum
Authors: R. Fulchiero, A. S. Spanias
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1993. ICASSP-93 Vol 4., 1993 IEEE International Conference on - Volume 04 (1993)

The authors present a study on the enhancement of speech that has been corrupted by additive wideband Gaussian noise. A least squares bispectrum reconstruction algorithm is used as a means for attenuating wideband Gaussian noise. A systematic approach is presented for processing speech records and estimating the bispectrum on a frame-by-frame basis. Performance evaluations are given using phonetically balanced sentences and signal-to-noise ratios.
Critical Configurations for Projective Reconstruction from Multiple Views
Authors: Richard Hartley, Fredrik Kahl
Venue: International Journal of Computer Vision (2007)

This paper investigates a classical problem in computer vision: Given corresponding points in multiple images, when is there a unique projective reconstruction of the 3D geometry of the scene points and the camera positions? A set of points and cameras is said to be critical when there is more than one way of realizing the resulting image points. For two views, it has been known for almost a century that the critical configurations consist of points and camera lying on a ruled quadric surface. We give a classification of all possible critical configurations for any number of points in three images, and show that in most cases, the ambiguity extends to any number of cameras.The underlying framework for deriving the critical sets is projective geometry. Using a generalization of Pascal's Theorem, we prove that any number of cameras and scene points on an elliptic quartic form a critical set. Another important class of critical configurations consists of cameras and points on rational quartics. The theoretical results are accompanied by many examples and illustrations.
Research trends in real-time computing for embedded systems
Authors: Giorgio Buttazzo
Venue: ACM SIGBED Review (2006)

Most of today's embedded systems are required to work in dynamic environments, where the characteristics of the computational load cannot always be predicted in advance. Still timely responses to events have to be provided within precise timing constraints in order to guarantee a desired level of performance. Hence, embedded systems are, by nature, inherently real-time. Moreover, most of embedded systems work under several resource constraints, due to space, weight, energy, and cost limitations imposed by the specific application. As a consequence, efficient resource management is a critical aspect in embedded systems, that must be considered at different architecture levels.The objective of this document is to present the major research trends identified by the international community on real-time systems to make the next generation embedded systems more predictable and adaptive to environmental changes. After describing the characteristics of modern embedded applications, the paper presents the problems of the current approaches and discusses the new research trends in operating systems and scheduling emerging to overcome them.
A family of empirical studies to compare informal and optimization-based planning of software releases
Authors: Gengshen Du, Jim McElroy, Guenther Ruhe
Venue: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (2006)

Replication of experiments, or performing a series of related studies, aims at attaining a higher level of validity of results. This paper reports on a series of empirical studies devoted to comparing informal release planning with two variants of optimization-based release planning.Two research questions were studied: How does optimization-based release planning compare with informal planning in terms of (i) time to generate release plans, and the feasibility and quality of those plans, and (ii) understanding and confidence of generated solutions and trust in the release planning process.For the family of empirical studies, the paper presents two types of results related to (i) the two research questions to compare the release planning techniques, and (ii) the evolution and lessons learned while conducting the studies.
Grid Organizational Memory: A Versatile Solution for Ontology Management in the Grid
Authors: Bartosz Kryza, Jan Pieczykolan, Jacek Kitowski
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Recent developments in the field of Grid computing reveal the strong need of managing metadata on much higher level than it used to be done previously. Standard solutions like MDS provide relatively efficient means of managing Grid resources on a low level basis, usually available for Grid experts and simple search tools. However in order to manage resources among multiple Virtual Organizations composed of highly heterogeneous entities, joining and leaving the Grid in a dynamic manner, a more flexible way of describing and managing their resources is required. In this paper, a solution to this problem based on ontologies and distributed knowledge base is presented. The knowledge base distributed architecture is discussed with the flexibility and fault-tolerance outlined. The performance evaluation for typical use cases shows, that ontology separation and various configurations of GOM make it useful for managing knowledge in multiple domains.
Adaptive Clonal Selection with Elitism-Guided Crossover for Function Optimization
Authors: Jiang-qiang Hu, Chen Guo, Tie-shan Li, Jian-chuan Yin
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

Based on clonal selection principle, a novel evolutionary algorithm encoded in floating-point-number is proposed to solve function optimization problems. A micro-mutation operator and an elitism-guided crossover operator are defined respectively for the best and medium antibodies. The main features of the algorithm are combination of meticulous local with double-quick global search, and automatic adjustment of run-time parameters (adaptive extension or shrink of search space). The algorithm is empirically compared with similar approaches from the literature. The results demonstrate that the proposed algorithm can promptly and accurately locate the global optimum of complex function and has good stabilization.
On the Use of Structure and Sequence-Based Features for Protein Classification and Retrieval
Authors: Keith Marsolo, Srinivasan Parthasarathy
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

The need to retrieve or classify protein molecules using structure or sequence-based similarity measures underlies a wide range of biomedical applications. In drug discovery, researchers search for proteins that share specific chemical properties as possible sources for new treatment. With folding simulations, similar intermediate structures might be indicative of a common folding pathway. To derive any type of similarity, however, one must have an effective model of the protein that allows for easy comparison. In this work, we present two normalized, stand-alone representations of proteins that enable fast and efficient object retrieval based on sequence or structure. To create our sequence-based representation, we take the frequency and scoring matrices returned by the PSI-BLAST alignment algorithm and create a normalized summary using a discrete wavelet transform. Our structural descriptor is constructed using an algorithm we developed previously. First, we transform each 3D structure into a 2D distance matrix by calculating the pair-wise distance between the amino acids of a protein. We normalize this matrix and apply a 2D wavelet decomposition to generate a set of approximation coefficients, which serve as our feature vector. We also concatenate the sequence and structural descriptors together to create a hybrid solution. We evaluate the generality of our models by using them as database indices for nearest-neighbor and range-based retrieval experiments as well as feature vectors for classification using support vector machines. We find that our methods provide excellent performance when compared with the current state-of-the-art techniques of each task. Our results show that the sequence-based representation is on par with, or out-performs, the structure-based representation. Moreover, we find that in the classification context, the hybrid strategy affords a significant improvement over sequence or structure.
Compositional type systems for stack-based low-level languages
Authors: Ando Saabas, Tarmo Uustalu
Venue: Proceedings of the 12th Computing: The Australasian Theroy Symposium - Volume 51 (2006)

It is widely believed that low-level languages with jumps must be difficult to reason about by being inherently non-modular. We have recently argued that this in untrue and proposed a novel method for developing compositional natural semantics and Hoare logics for low-level languages and demonstrated its viability on the example of a simple low-level language with expressions (Saabas & Uustalu 2005). The central idea is to use the implicit structure of finite disjoint unions present in low-level code as an (ambiguous) phrase structure.Here we apply our method to a stack-based language and develop it further. We define a compositional natural semantics and Hoare logic for this language and go then on to show that, in addition to Hoare logics, one can also derive compositional type systems as weaker specification languages with the same method. We describe type systems for stack-error freedom and secure information flow.
Automatic playlist generation based on tracking user's listening habits
Authors: Andreja Andric, Goffredo Haus
Venue: Multimedia Tools and Applications (2006)

Algorithms for automatic playlist generation solve the problem of tedious and time consuming manual selection of musical playlists. These algorithms generate playlists according to the user's music preferences of the moment. The user describes his preferences either by manually inputting a couple of example songs, or by defining constraints for the choice of music. The approaches to automatic playlist generation up to now were based on examining the metadata attached to the music pieces. Some of them took also the listening history into account. But anyway, a heavy accent has been put on the metadata, while the listening history, if it was used at all, had a minor role. Missings and errors in metadata frequently appear, especially when the music is acquired from the Internet. When the metadata is missing or wrong, the approaches proposed so far cannot work. Besides, entering constraints for the playlist generation can be a difficult activity. In our approach we ignored the metadata and focused on examining the listening habits. We developed two simple algorithms that track the listening habits and form a listener model--a profile of listening habits. The listener model is then used for automatic playlist generation. We developed a simple media player which tracks the listening habits and generates playlists according to the listener model. We tried the solution with a group of users. The experiment was not a successful one, but it threw some new light on the relationship between the listening habits and playlist generation.
ServOSims: A Service Oriented Framework for Composing and Executing Multidisciplinary Simulations
Authors: Evangelos Floros, Yiannis Cotronis
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Web Service technologies and Service Oriented Architectures (SOAs) are gaining momentum in the context of Grid Computing infrastructure design and development. In this paper 1 we present such a SOA for the composition and execution of Multidisciplinary Simulation Models exposed as stateful WSRF Web Services. We introduce an XML Schema that simplifies the manifestation of the data meshes typically produced or consumed by simulation models. We demonstrate how simulations are composed using a dataoriented approach and how the resultant workflows can be choreographed with the usage of notifications. Finally, we present a simulation composition and execution scenario.
ReAgents: behavior-based remote agents and their performance
Authors: Eugene Hung, Joseph Pasquale
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

We present a performance analysis of an agent-based middleware system we have developed based on "reAgents," remotely executing agents that enhance the performance of client/server-based Internet applications. ReAgents simplify the use of mobile agent technology by transparently handling data migration and run-time network communications, and provide a general interface for programmers to more easily implement application-specific logic. This is made possible through the use of behaviors, i.e., common patterns of actions that exploit the ability to process and communicate remotely. We model the performance of each of the primary behaviors, and provide an experimental evaluation of reAgent performance.
Reasoning, Models, and Images: Behavioral Measures and Cortical Activity
Authors: Markus Knauff, Thomas Fangmeier, Christian C. Ruff, P. N. Johnson-laird
Venue: Journal of Cognitive Neuroscience (2003)

The goal of this study was to investigate the neurocognitive processes of mental imagery in deductive reasoning. Behavioral studies yielded four sorts of verbal relations: (1) visuospatial relations that are easy to envisage both visually and spatially; (2) visual relations that are easy to envisage visually but hard to envisage spatially; (3) spatial relations that are hard to envisage visually but easy to envisage spatially; and (4) control relations that are hard to envisage both visually and spatially. In three experiments, visual relations slowed the process of reasoning in comparison with control relations, whereas visuospatial and spatial relations yielded inferences comparable to those of control relations. An experiment using functional magnetic resonance imaging showed that in the absence of any correlated visual input (problems were presented acoustically via headphones), all types of reasoning problems evoked activity in the left middle temporal gyrus, in the right superior parietal cortex, and bilaterally in the precuneus. In the prefrontal cortex, increased activity was found in the middle and inferior frontal gyri. However, only the problems based on visual relations also activated areas of the visual association cortex corresponding to V2. The results indicate that cortical activity during reasoning depends on the nature of verbal relations. All relations elicit mental models that underlie reasoning, but visual relations in addition elicit visual images. This account resolves inconsistencies in the previous literature.
Grid Services Toolkit for Process Data Processing
Authors: T. O. Muller, T. Jejkal, R. Stotzka, M. Sutter, V. Hartmann, H. Gemmeke
Venue: Proceedings of the Second IEEE International Conference on e-Science and Grid Computing (2006)

Grid is a rapidly growing new technology that will provide easy access to vast amounts of computer resources, both hardware and software. As these resources become available soon, more and more scientific users are interested in benefiting from them. At this time the main problem accessing Grid is that scientific user usually need to know a lot about Grid methods and technologies besides their own field of application. This paper describes a toolkit which is based om Grid Services designed especially for the field of process data processing providing database access and management, common methods of statistical data analysis and project specific methods. The toolkit will fill to some extent the gap between high-level scientific Grid users and low-level functions in Grid environments, thus simplifying and accelerating the development of scientific Grid applications.
Neurophysiological Correlates of Emotion Regulation in Children and Adolescents
Authors: Marc D. Lewis, Connie Lamm, Sidney J. Segalowitz, Jim Stieben, Philip David Zelazo
Venue: Journal of Cognitive Neuroscience (2006)

Psychologists consider emotion regulation a critical developmental acquisition. Yet, there has been very little research on the neural underpinnings of emotion regulation across childhood and adolescence. We selected two ERP components associated with inhibitory control&mdash;the frontal N2 and frontal P3. We recorded these components before, during, and after a negative emotion induction, and compared their amplitude, latency, and source localization over age. Fifty-eight children 5&ndash;16 years of age engaged in a simple go/no-go procedure in which points for successful performance earned a valued prize. The temporary loss of all points triggered negative emotions, as confirmed by self-report scales. Both the frontal N2 and frontal P3 decreased in amplitude and latency with age, consistent with the hypothesis of increasing cortical efficiency. Amplitudes were also greater following the emotion induction, only for adolescents for the N2 but across the age span for the frontal P3, suggesting different but overlapping profiles of emotion-related control mechanisms. No-go N2 amplitudes were greater than go N2 amplitudes following the emotion induction at all ages, suggesting a consistent effect of negative emotion on mechanisms of response inhibition. No-go P3 amplitudes were also greater than go P3 amplitudes and they decreased with age, whereas go P3 amplitudes remained low. Finally, source modeling indicated a developmental decline in central-posterior midline activity paralleled by increasing activity in frontal midline regions suggestive of the anterior cingulate cortex. Negative emotion induction corresponded with an additional right ventral prefrontal or temporal generator beginning in middle childhood.
Building credible input models
Authors: Lawrence M. Leemis
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Most discrete-event simulation models have stochastic elements that mimic the probabilistic nature of the system under consideration. A close match between the input model and the true underlying probabilistic mechanism associated with the system is required for successful input modeling. The general question considered here is how to model an element (e.g., arrival process, service times) in a discrete-event simulation given a data set collected on the element of interest. For brevity, it is assumed that data is available on the aspect of the simulation of interest. It is also assumed that raw data is available, as opposed to censored data, grouped data, or summary statistics. This example-driven tutorial examines introductory techniques for input modeling. Most simulation texts (e.g., Law and Kelton 2000, Fishman 2001) have a broader treatment of input modeling than presented here. Nelson and Yamnitsky (1998) survey advanced techniques.
Estimating efficacy of progressive planning for air traffic flow management
Authors: Lynne Fellman, James S. DeArmon, Kelly A. Connolly
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Air traffic flow management (TFM) is a set of processes and procedures which seek to balance the demand for airspace resources with the capacity of these resources. Examples of resources are airports, sectors (airspace volumes managed by air traffic controllers), and fixes (imaginary points in space used for navigation). The Federal Aviation Administration (FAA) is continually looking for ways to provide new tools and techniques for TFM personnel. As the TFM function improves, flight efficiency improves, and the experience of the flying public is likewise improved.In this paper, we describe a simulation modeling exercise to assess the benefit, if any, of a proposed new feature of TFM called Progressive Planning (P2). P2 allows the flow manager to model the impact of multiple concurrent flow management actions. It is envisioned that the improved modeling leads to better decision-making, which leads to greater flight efficiency.