ppxscal/embedding_network huggingface dataset:
Correlating real-time monitoring data for mobile network management
Authors: Nanyan Jiang, Guofei Jiang, Haifeng Chen, Kenji Yoshihira
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

With a proliferation of new mobile data services, the complexity of wireless mobile networks is rapidly growing. While large amount of operational monitoring data such as performance measurement statistics is available, it is a great challenge to correlate such data effectively for real time performance analysis. Meantime, the dynamics of mobile applications and environments introduce another dimension of complexity for us to track the evolving system status. In this paper, we analyze the spatial and temporal correlations of Key Performance Indicators (KPIs) to track and interpret the operational status of wide-area cellular systems. We first correlate large number of raw measurements into limited number of KPIs. Further we exploit spatial and temporal correlations of these KPIs for cellular network management. We use large volume of field data collected from real cellular systems in our analysis. Experimental results demonstrate that it is promising to build a real-time data management and support system by effectively correlating KPIs.
Induced aggregation operators in decision making with the Dempster-Shafer belief structure
Authors: J. M. Merigó, M. Casanovas
Venue: International Journal of Intelligent Systems (2009)

In this study, we analyze the induced aggregation operators. The analysis begins with a revision of some basic concepts such as the induced ordered weighted averaging operator and the induced ordered weighted geometric operator. We then analyze the problem of decision making with Dempster-Shafer (D-S) theory of evidence. We suggest the use of induced aggregation operators in decision making with the D-S theory. We focus on the aggregation step and examine some of its main properties, including the distinction between descending and ascending orders and different families of induced operators. Finally, we present an illustrative example in which the results obtained with different types of aggregation operators can be seen. &copy; 2009 Wiley Periodicals, Inc.
Evaluation of a software engineering course by reflection
Authors: Ohad Barzilay, Orit Hazzan, Amiram Yehudai
Venue: ACM SIGCSE Bulletin (2009)

The evaluation of an advanced software engineering (SE) course is a challenging task that should be addressed as part of the course design. In this paper, we describe an implementation of the reflective practitioner perspective as part of an advanced SE course and introduce its use for feedback purposes. Reflective feedback goes beyond merely using feedback questionnaires. Furthermore, we show, using both qualitative and quantitative empirical data, that the course on which the perspective was applied meets its objectives and fosters students' awareness to the multidimensional nature of SE.
A method for topological entity correspondence in a replicated collaborative CAD system
Authors: Shu-xu Jing, Fa-zhi He, Soon-hung Han, Xian-tao Cai, Hua-Jun Liu
Venue: Computers in Industry (2009)

In order to utilize the potential advantages of replicated collaborative CAD system to support natural, free, fast and less-constrained multi-user human-to-human interaction, a local-locking mechanism, which can provide fast modeling response, is adopted as concurrency control mechanism for a replicated on-line collaborative CAD system. A human-human interactive modeling is achieved by immediate local execution of modeling operations and exchange of modeling operations across all collaborative sites real-time. In particular, an approach to achieve topological entity correspondence across collaborative sites during modeling procedure, which is critical to guarantee the correctness and consistency of collaborative modeling result, is proposed. A prototype system based on the ACIS geometric modeling kernel is implemented to verify availability of the proposed solution.
Characteristic set method for differential-difference polynomial systems
Authors: X. S. Gao, J. Van der Hoeven, C. M. Yuan, G. L. Zhang
Venue: Journal of Symbolic Computation (2009)

In this paper, we present a characteristic set method for mixed differential and difference polynomial systems. We introduce the concepts of coherent, regular, proper irreducible, and strongly irreducible ascending chains and study their properties. We give an algorithm which can be used to decompose the zero set for a finitely generated differential and difference polynomial sets into the union of the zero sets of regular and consistent ascending chains. As a consequence, we solve the perfect ideal membership problem for differential and difference polynomials.
Range and Roots: Two common patterns for specifying and propagating counting and occurrence constraints
Authors: Christian Bessiere, Emmanuel Hebrard, Brahim Hnich, Zeynep Kiziltan, Toby Walsh
Venue: Artificial Intelligence (2009)

We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints specified using these patterns thus directly inherit a propagation algorithm. To illustrate the capabilities of the Range and Roots constraints, we specify a number of global constraints taken from the literature. Preliminary experiments demonstrate that propagating counting and occurrence constraints using these two patterns leads to a small loss in performance when compared to specialised global constraints and is competitive with alternative decompositions using elementary constraints.
The stochastic p-hub center problem with service-level constraints
Authors: Thaddeus Sim, Timothy J. Lowe, Barrett W. Thomas
Venue: Computers and Operations Research (2009)

Small package delivery companies offer services where packages are guaranteed to be delivered within a given time-frame. With variability in travel time, the configuration on the hub-and-spoke delivery network is vital in ensuring a high probability of meeting the service-level guarantee. We present the stochastic p-hub center problem with chance constraints, which we use to model the service-level guarantees. We discuss analytical results, propose solution heuristics, and present the results from computational experiments.
Ranking interesting subgroups
Authors: Stefan Rueping
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Subgroup discovery is the task of identifying the top k patterns in a database with most significant deviation in the distribution of a target attribute Y. Subgroup discovery is a popular approach for identifying interesting patterns in data, because it combines statistical significance with an understandable representation of patterns as a logical formula. However, it is often a problem that some subgroups, even if they are statistically highly significant, are not interesting to the user. We present an approach based on the work on ranking Support Vector Machines that ranks subgroups with respect to the user's concept of interestingness, and finds more interesting subgroups. This approach can significantly increase the quality of the subgroups.
An Ensemble Kalman-Particle Predictor-Corrector Filter for Non-Gaussian Data Assimilation
Authors: Jan Mandel, Jonathan D. Beezley
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

An Ensemble Kalman Filter (EnKF, the predictor) is used make a large change in the state, followed by a Particle Filer (PF, the corrector), which assigns importance weights to describe a non-Gaussian distribution. The importance weights are obtained by nonparametric density estimation. It is demonstrated on several numerical examples that the new predictor-corrector filter combines the advantages of the EnKF and the PF and that it is suitable for high dimensional states which are discretizations of solutions of partial differential equations.
Fault emulation for dependability evaluation of VLSI systems
Authors: David de Andrés, Juan Carlos Ruiz, Daniel Gil, Pedro Gil
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2008)

Advances in semiconductor technologies are greatly increasing the likelihood of fault occurrence in deep-submicrometer manufactured VLSI systems. The dependability assessment of VLSI critical systems is a hot topic that requires further research. Field-programmable gate arrays (FPGAs) have been recently proposed as a means for speeding-up the fault injection process in VLSI systems models (fault emulation) and for reducing the cost of fixing any error due to their applicability in the first steps of the development cycle. However, only a reduced set of fault models, mainly stuck-at and bit-flip, have been considered in fault emulation approaches. This paper describes the procedures to inject a wide set of faults representative of deep-submicrometer technology, like stuck-at, bit-flip, pulse, indetermination, stuck-open, delay, short, open-line, and bridging, using the best suitable FPGA-based technique. This paper also sets some basic guidelines for comparing VLSI systems in terms of their availability and safety, which is mandatory in mission and safety critical application contexts. This represents a step forward in the dependability benchmarking of VLSI systems and towards the definition of a framework for their evaluation and comparison in terms of performance, power consumption, and dependability.
Adapting an NER-system for German to the biomedical domain
Authors: Marc Rössler
Venue: Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (2004)

In this paper, we report the adaptation of a named entity recognition (NER) system to the biomedical domain in order to participate in the "Shared Task Bio-Entity Recognition". The system is originally developed for German NER that shares characteristics with the biomedical task. To facilitate adaptability, the system is knowledge-poor and utilizes unlabeled data. Investigating the adaptability of the single components and the enhancements necessary, we get insights into the task of bio-entity recognition.
Is Web Genre Identification Feasible?
Authors: Benno Stein, Sven Meyer zu Eissen
Venue: Proceeding of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy (2006)

This paper contributes to a facet from the area of Web Information Retrieval that has recently received much attention: The satisfaction of a user's personal information need with respect to text type, presentation type, or information quality. We imply that such properties can be quantified for all kinds of Web documents, and we subsume them under the term “Web genre” or “genre”. Recent surveys show that there is---to a certain degree---a common understanding of Web genre. However, the strictness by which genre and non-genre aspects of a document are experienced is an individual matter. To get a better understanding of the challenges of Web genre identification and its possible limits we investigate in this paper a very interesting question, which has not been posed by now: Given a categorization C of documents (or bookmarks, links, document identifiers), can we provide a reliable assessment whether C is governed by topic or by genre considerations?
Probabilistic approximate algorithms for distributed data mining in peer-to-peer networks
Authors: Hillol Kargupta
Venue:  (2008)

Peer-to-peer(P2P) computing is emerging as a new distributed computing paradigm for novel applications that involves exchange of information among peers with little centralized coordination. Analyzing data distributed in P2P networks requires peer-to-peer data mining algorithms that can mine the data without data centralization. However, replicating result of centralized data mining in an exact fashion is often communication-wise expensive. Approximate algorithms can be a realistic and communication-efficient alternative in this case. This dissertation concentrates on developing approximate data mining algorithms suitable for P2P networks, that closely estimates the result of centralized data mining algorithm with probabilistic guarantee using minimal communication. The dissertation introduces the concept of approximate local algorithms that can estimate data mining result within desired accuracy boundary with user-specified probabilistic guarantee by operating within a spatial locality of the executioner-node. As a foundation of probabilistic approximation in P2P network, a random-walk based uniform data sampling approach is proposed, that removes the bias and dependence in sampling caused by varying degrees of connectivity and sizes of data shared. Then the sampling technique is applied to develop approximate local algorithms for solving the specific data mining problem of K-means clustering and frequent itemset mining in the context of P2P network. Two K-means clustering algorithms are developed, one of which extends the concept of centralized K-means algorithm to distributed dynamic peer-to-peer environment, while the other provides probabilistic guarantee on accuracy of clustering result in a static P2P network. A frequent itemset mining algorithm is developed as a direct application of the uniform data sampling technique that discovers most of the frequent itemsets with high probability using bounded communication. The main contribution of this research work is to introduce the concept of approximate local algorithms for data mining in P2P network that provides probabilistic guarantee of accuracy. It builds a basic tool for approximate data analysis in P2P network, a uniform data sampling technique, and develops communication efficient approximate local algorithms for mining data distributed in such network. The algorithms developed here provide data mining results within desired accuracy level and probabilistic guarantee, and shows good scalability with low communication overhead.
LINQ Quickly
Authors: N. Satheesh Kumar
Venue:  (2007)

This book gets you started with LINQ and shows how it will make your programming life easier by making use of new features from the .NET Framework 3.0. This book is split into seven chapters, each of which is dedicated to presenting a feature of LINQ and its usage in real-life scenarios. Language Integrated Query (LINQ) is a new feature in Visual Studio 2008 that extends its query capabilities, using C# and Visual Basic. Visual Studio 2008 comes with LINQ provider assemblies that enable the use of LINQ with data sources such as in-memory collections, SQL relational databases, ADO.NET Datasets, XML documents, etc. In Visual Studio 2008, Visual C# and Visual Basic are the languages that implement the LINQ language extensions. LINQ language extensions use the new standard query operators API, which is the query language for any collection that implements IEnumerable. LINQ to Objects LINQ to XMLLINQ to SQLLINQ to DataSetsLINQ to XSD This book introduces the reader to the basic concepts of LINQ, and takes them through using LINQ with an example-driven approach. This book is for .NET developers who want to find out exactly what LINQ is, what it can do for them, and how to program with LINQ. This book presumes a sound knowledge of XML, ADO.NET, and .NET data access--No knowledge of LINQ is presumed. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Energy-based VAD with grey magnitude spectral subtraction
Authors: Cheng-Hsiung Hsieh, Ting-Yu Feng, Po-Chin Huang
Venue: Speech Communication (2009)

In this paper, we propose a novel voice activity detection (VAD) scheme for low SNR conditions with additive white noise. The proposed approach consists of two parts. First, a grey magnitude spectral subtraction (GMSS) is applied to remove additive noise from a given noisy speech. By this doing, an estimated clean speech is obtained. Second, the enhanced speech by the GMSS is segmented and put into an energy-based VAD to determine whether it is a speech or non-speech segment. The approach presented in this paper is called the GMSS/EVAD. Simulation results indicate that the proposed GMSS/EVAD outperforms VAD in G.729 and GSM AMR for the given low SNR examples. To investigate the performance of the GMSS/EVAD for real-life background noises, the babble and volvo noises in the NOISEX-92 database are under consideration. The simulation results for the given examples indicate that the GMSS/EVAD is able to handle appropriately for the cases of the babble noise with the SNR above 10dB and the cases of the volvo noise with SNR 15dB and up.
A Multi-Stage Neural Network Model for Human Color Vision
Authors: Charles Q. Wu
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

The contemporary "Standard Model" for human color vision is a two-stage model: The first stage consists of three types of receptors at the retina of the eye, and the second stage consists of three opponent-color neural channels: Red-Green, Blue-Yellow, and Black-White. In this paper I call upon the phenomena of complementary afterimages and of the "flight of colors" to show that this model is not an adequate explanation for these color phenomena in specific and for color vision in general. To remedy the theoretical inadequacy of the "Standard Model", I propose a neural stage for color complementarity directly corresponding to our color sensation. Mapping onto the anatomical organization of human visual system, I further suggest that layer 4C in the primary visual cortex is the neural substrate directly responsible for color complementarity in particular and for color appearance (that is, color consciousness) in general.
Windows Movie Maker BASICS, 1st edition
Authors: Jennifer Gipp
Venue:  (2009)

Windows Movie Maker BASICS teaches readers how to create professional-looking movies and slide shows, complete with design elements such as transitions and sound. The text includes all of the information needed to master skills from importing media from various sources to publishing content to a variety of channels, and everything in between. The BASICS series suits many learning styles and provides several projects for a hands-on learning experience. Although introductory in nature, this text is comprehensive enough to cover the most important features of Windows Movie Maker 6.0.
QoS Support for Mobile Users Using NSIS
Authors: Roland Bless, Martin Röhricht
Venue: Proceedings of the 8th International IFIP-TC 6 Networking Conference (2009)

Resource reservations in the Internet become more and more important with the advent of real-time multimedia services like Voice-over-IP and IPTV. At the same time we see an increasing interest in accessing Internet services by using mobile devices. In this paper we describe how Quality-of-Service guarantees can be achieved in mobile environments across different domains using the Next Steps in Signaling (NSIS) framework. We provide an analysis of mobility scenarios in combination with QoS signaling and propose to use an additional node local Flow Information Service element that supplies the necessary mobility support within NSIS capable mobility-aware nodes. We show that reservations can be setup quickly along the new path after a handover happened. Even the tear down of the reservation of the old path after a successful handover is performed quickly.
Context in the Collaborative Building of an Answer to a Question
Authors: Patrick Brezillon
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

We describe how contextual graphs allow the analysis of oral corpus from person-to-person collaboration. The goal was to build a task model that would be closer to the effective task(s) than the prescribed task. Such a “contextualized prescribed task” is possible, thanks to a formalism allowing a uniform representation of elements of decision and of contexts. The collaborative process of answer building identified includes a phase of building of the shared context attached to the collaboration, shared context in which each participant introduces contextual elements from his/her individual context in order to build the answer with the other. Participants in the collaborative building process agree on the contextual elements in the shared context and organize, assemble and structure them in a proceduralized context to build the answer. The proceduralized-context building is an important key of the modeling of a collaborative decision making process.
An intensional approach to qualitative and quantitative periodicity-dependent temporal constraints
Authors: Luca Anselma, Stefania Montani, Paolo Terenziani
Venue: International Journal of Intelligent Systems (2009)

In this paper, we propose a framework for representing and reasoning about qualitative and quantitative temporal constraints between periodic events. In particular, our contribution is twofold: (i) we provide a formalism to deal with both qualitative and quantitative &ldquo;periodicity-dependent&rdquo; constraints between repeated events, considering user-defined periodicities as well; and (ii) we propose an intensional approach to temporal reasoning, which is based on the operations of intersection and composition. Such a comprehensive approach, to the best of our knowledge, represents an innovative contribution that integrates and extends results from both the artificial intelligence and the temporal databases literature. &copy; 2009 Wiley Periodicals, Inc.
Technical communique: Mittag-Leffler stability of fractional order nonlinear dynamic systems
Authors: Yan Li, YangQuan Chen, Igor Podlubny
Venue: Automatica (Journal of IFAC) (2009)

In this paper, we propose the definition of Mittag-Leffler stability and introduce the fractional Lyapunov direct method. Fractional comparison principle is introduced and the application of Riemann-Liouville fractional order systems is extended by using Caputo fractional order systems. Two illustrative examples are provided to illustrate the proposed stability notion.
Better Naive Bayes classification for high-precision spam detection
Authors: Yang Song, Aleksander Kołcz, C. Lee Giles
Venue: Software&mdash;Practice Experience (2009)

Email spam has become a major problem for Internet users and providers. One major obstacle to its eradication is that the potential solutions need to ensure a very low false-positive rate, which tends to be difficult in practice. We address the problem of low-FPR classification in the context of naive Bayes, which represents one of the most popular machine learning models applied in the spam filtering domain. Drawing from the recent extensions, we propose a new term weight aggregation function, which leads to markedly better results than the standard alternatives. We identify short instances as ones with disproportionally poor performance and counter this behavior with a collaborative filtering-based feature augmentation. Finally, we propose a tree-based classifier cascade for which decision thresholds of the leaf nodes are jointly optimized for the best overall performance. These improvements, both individually and in aggregate, lead to substantially better detection rate of precision when compared with some of the best variants of naive Bayes proposed to date. Copyright &copy; 2009 John Wiley & Sons, Ltd. This work was done when the first author was an intern at Microsoft Live Labs Research.