ppxscal/embedding_network huggingface dataset:
Programming in mobile ad hoc networks
Authors: Justin Collins, Rajive Bagrodia
Venue: Proceedings of the 4th Annual International Conference on Wireless Internet (2008)

The possibility for spontaneous ad hoc networks between mobile devices has been increasing as small devices become more capable of hosting useful networked applications. These applications face the challenges of frequent disconnections, highly dynamic network topologies, and varying communication patterns, a combination unique to mobile ad hoc networks. This is the first survey to examine current MANET programming approaches including tuple spaces, remote objects, publish/subscribe, and code migration through analysis and experimental results. We suggest that these approaches are essentially extensions to existing distributed and parallel computing concepts and new abstractions may be necessary to fully handle the programming issues presented by MANETs.
A swarm-inspired projection algorithm
Authors: Mu-Chun Su, Shi-Yong Su, Yu-Xiang Zhao
Venue: Pattern Recognition (2009)

In this paper a new data projection algorithm which was inspired by the foraging behaviors of doves is proposed. We name the new data projection the swarm-inspired projection (SIP) algorithm. The algorithm allows us to visually estimate the number of clusters existing in a data set. Based on the projection result, we may then partition the data set into the corresponding number of clusters. The SIP algorithm regards each data pattern in a data set as a piece of crumb which will be sequentially tossed to a flock of doves on the ground. The doves will adjust their physical positions to compete for crumbs. Gradually, the flock of doves will be divided into several groups according to the distributions of the crumbs. The formed groups will naturally correspond to the underlying data structures in the data set. By viewing the scatter plot of the final positions of the doves we can estimate the number of clusters existing in the data set. Several data sets were used to demonstrate the effectiveness of the proposed SIP algorithm.
An evaluation of inertial sensor based pointing device using multidirectional point-and-select task
Authors: Josip Music, Mojmil Cecic, Mirjana Bonkovic
Venue: Proceedings of the 10th WSEAS international conference on Automation & information (2009)

In the paper we propose a novel hands-free pointing device for the disabled based on commercially available inertial sensors (XSens MTx) and evaluate its performance on twelve test subjects using multi-directional point-and-select task and experimental design adopted from [1]. In experiments throughput was chosen as a main performance parameter, with error rate being the additional parameter. Two pointing modes were tested, as well as two selection techniques. Additionally, all test subjects were given questionnaires in which they had to rate pointing device comfort and performance. Obtained results are presented and discussed.
Dependable Monitoring of Discrete-Event Systems with Uncertain Temporal Observations
Authors: Gianfranco Lamperti, Marina Zanella
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

In discrete-event system monitoring, a set of candidate diagnoses is output at the reception of each observation fragment. However, when the observation is uncertain, this result may be not dependable: the sets of diagnoses, relevant to consecutive observation fragments, may be unrelated to one another, and, even worse, they may be unrelated to the actual diagnosis. To cope with this problem, the notion of monotonic monitoring is introduced, which is supported by specific constraints on the fragmentation of the uncertain observation, leading to the notion of stratification.
Computational Probability: Algorithms and Applications in the Mathematical Sciences, 1st edition
Authors: John H. Drew, Diane L. Evans, Andrew G. Glen, Lawrence M. Leemis
Venue:  (2007)

Computational probability encompasses data structures and algorithms that have emerged over the past decade that allow researchers and students to focus on a new class of stochastic problems. COMPUTATIONAL PROBABILITY is the first book that examines and presents these computational methods in a systematic manner. The techniques described here address problems that require exact probability calculations, many of which have been considered intractable in the past. The first chapter introduces computational probability analysis, followed by a chapter on the Maple computer algebra system. The third chapter begins the description of APPL, the probability modeling language created by the authors. The book ends with three applications-based chapters that emphasize applications in survival analysis and stochastic simulation. The algorithmic material associated with continuous random variables is presented separately from the material for discrete random variables. Four sample algorithms, which are implemented in APPL, are presented in detail: transformations of continuous random variables, products of independent continuous random variables, sums of independent discrete random variables, and order statistics drawn from discrete populations. The APPL computational modeling language gives the field of probability a strong software resource to use for non-trivial problems and is available at no cost from the authors. APPL is currently being used in applications as wide-ranging as electric power revenue forecasting, analyzing cortical spike trains, and studying the supersonic expansion of hydrogen molecules. Requests for the software have come from fields as diverse as market research, pathology, neurophysiology, statistics, engineering, psychology, physics, medicine, and chemistry.
Empirical Evidence for Correct Iris Match Score Degradation with Increased Time-Lapse between Gallery and Probe Matches
Authors: Sarah E. Baker, Kevin W. Bowyer, Patrick J. Flynn
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

We explore the effects of time lapse on iris biometrics using a data set of images with four years time lapse between the earliest and most recent images of an iris (13 subjects, 26 irises, 1809 total images). We find that the average fractional Hamming distance for a match between two images of an iris taken four years apart is statistically significantly larger than the match for images with only a few months time lapse between them. A possible implication of our results is that iris biometric enrollment templates may undergo aging and that iris biometric enrollment may not be "once for life." To our knowledge, this is the first and only experimental study of iris match scores under long (multi-year) time lapse.
Segmentation, Classification and Denoising of a Time Series Field by a Variational Method
Authors: Piero Barone, Maria Francesca Carfora, Riccardo March
Venue: Journal of Mathematical Imaging and Vision (2009)

Many real life problems can be represented by an ordered sequence of digital images. At a given pixel a specific time course is observed which is morphologically related to the time courses at neighbor pixels. Useful information can be usually extracted from a set of such observations if we are able to classify pixels in groups, according to some features of interest for the final user. Moreover parameters with a physical meaning can be extracted from the time courses. In a continuous setting we can formalize the problem by assuming to observe a noisy version of a positive real function defined on a bounded set ${\mathcal{T}}\times\Omega\subset\mathbb{R}\times\mathbb{R}^{2}$ , parameterized by a vector of unknown functions defined on ¿2 with discontinuities along regular curves in ¿ which separate regions with different features. Suitable regularity conditions on the parameters are also assumed in order to take into account the physical constraints. The problem consists in estimating the parameter functions, segmenting ¿ in subsets with regular boundaries and assigning to each subset a label according to the values that the parameters assume on the subset. A global model is proposed which allows to address all of the above subproblems in the same framework. A variational approach is then adopted to compute the solution and an algorithm has been developed. Some numerical results obtained by using the proposed method to solve a dynamic Magnetic Resonance imaging problem are reported.
Extracting semantic annotations from legal texts
Authors: Leonardo Lesmo, Alessandro Mazzei, Daniele P. Radicioni
Venue: Proceedings of the 20th ACM conference on Hypertext and hypermedia (2009)

This paper illustrates a system designed to automatically extract semantic annotations of the normative modifications present in legal texts. The work relies on a deep parsing approach. The problem of semantically annotating legal texts is cast to the problem of mapping parse trees to semantic frames representing such modifications. We report a preliminary experimentation along with the dataset employed, and discuss the results to point out future improvements.
Statistical performance analysis and optimization of digital circuits
Authors: David Blaauw
Venue:  (2008)

Aggressive device scaling has made it imperative to account for process variations in the design flow. A robust model of process variations is an essential requirement for any meaningful variation aware design analysis and optimization. In the first part of this work, we present an approach to extract spatial variation models based on the theory of spatial statistics. The proposed approach uses the concept of variogram function that represents how parameters can co-vary as a function of spatial distance. In the second part of this work, we present a new approach to compute the statistical maximum for improving the accuracy of existing statistical timing analysis approaches. Existing approaches use the results given by Clark for analytically computing the mean and variance of the maximum of two normal arrival time distributions. In practice due to the nonlinear maximum operation the arrival time distributions are found to be non-normal and skewed. Using skew-normal representation for arrival time distribution, analytical results are derived for propagating the skewed arrival time distributions. We then present an optimization method for yield optimization under simultaneous leakage power and timing constraints. The optimization approach uses a leakage power and performance analysis that is statistical in nature and considers the correlation between leakage power and performance to enable accurate computation of circuit yield under power and delay limits. The key to our approach is a new method to incrementally compute the gradient of yield with respect to gate sizes in the circuit with high efficiency and accuracy. Finally, we present a framework to perform full-chip gate oxide reliability analysis in the presence of process variations. The conventional approach for full chip oxide reliability analysis scales pre-characterized device level oxide reliability models assuming a uniform oxide thickness for all devices. Due to manufacturing variations, an alternative reliability analysis approach is needed for modeling oxide thickness variations. A statistical approach is proposed for performing chip level gate oxide reliability analysis while considering both die-to-die and within-die components of thickness variation.
A hybrid model in analyzing nonlinearly loaded dipole antenna and finite antenna array in the frequency domain
Authors: Saeed Reza Ostadzadeh, Majid Tayarani, Mohammad Soleimani
Venue: International Journal of RF and Microwave Computer-Aided Engineering (2009)

In this article, a hybrid model is introduced in which our previous fuzzy inference approach is used for extracting the behavior of receiving antenna and predicting the induced current and mutual coupling effects with an excellent accuracy and then it is combined with Volterra series model to analyze nonlinearly loaded finite antenna array. As it is expected, the computation time of the resulted hybrid model is much faster than the accurate ones, without loss of accuracy. &copy; 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE 2009.
Approaches to Efficient Resource-Constrained Project Rescheduling
Authors: Jürgen Kuster, Dietmar Jannach
Venue: Proceeding of the 2006 conference on STAIRS 2006: Proceedings of the Third Starting AI Researchers' Symposium (2006)

The intrinsic and pervasive uncertainty of the real world causes unforeseen disturbances during the execution of plans. The continuous adaptation of existing schedules is necessary in response to the corresponding disruptions. Affected Operations Rescheduling (AOR) and Matchup Scheduling (MUP) have proven to be efficient techniques for this purpose, as they take only a subset of future activities into account. However, these approaches have mainly been investigated for the job shop scheduling problem, which is too restrictive for many practical scheduling problems outside the shop floor. Thus, this paper analyzes and describes how the respective concepts can be extended for the more generic problem class of the Resource-Constrained Project Scheduling Problem (RCPSP). The conducted evaluation reveals that particularly our generalized version of AOR (GAOR) can yield significant performance improvements in comparison to the strategy of rescheduling all future activities.
A Heuristic Based Seller Agent for Simultaneous English Auctions
Authors: Patricia Anthony, Edwin Law
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

The popularity of online auction emerges due to the flexibility and convenience that it offers to consumers. Sellers offer a variety of items for sale with the aims of obtaining more profit. To obtain a reasonable profit, the reserve price for the item must be determined before the item is put up for sale. However, setting the price too high may result in no sale, while setting the price too low may yield a lower profit. In real auction, this is the main selling problem since most sellers fail to place a strategic reserve price for a given item which results in a lower profit. In this work, we develop a seller agent that proposes the item's reserve price based upon several selling constraints that comprise of the number of competitors, the number of bidders, the duration of the auction and the degree of profit that the seller desires when disposing the item. This paper describes the detail implementation and design of our agent's strategy. The seller strategy will be evaluated across a wide context of diverse and varying selling environment using a simulated auction marketplace.
Large-Scale, Less-than-Truckload Service Network Design
Authors: Ahmad I. Jarrah, Ellis Johnson, Lucas C. Neubert
Venue: Operations Research (2009)

We present a novel formulation for the service network design problem in the context of large-scale, less-than-truckload (LTL) freight operations. The formulation captures the basic network design constraints; the load-planning requirement that all freight at a location, irrespective of the freight's origin, loads to the same next terminal; and other important LTL-specific requirements. Our modeling scheme fragments the underlying massive network design model with up to 1.3 million 0--1 variables and 1.3 million rows into a separate and efficient integer programming (IP) problem for each destination terminal along with a coordinating master network design problem. We produce high-quality solutions in very reasonable CPU times (∼2 hours) using slope scaling and load-planning tree generation with corresponding potential annual savings of $20--25 million dollars for the target company for which the research was conducted.
Algorithmic developments and complexity results for finding maximum and exact independent sets in graphs
Authors: Vadim V. Lozin
Venue:  (2007)

We consider the MAXIMUM INDEPENDENT SET and MAXIMUM WEIGHT INDEPENDENT SET problems in graphs. As these problems are generally NP-hard, we study their complexity in hereditary graph classes, that is, in graph classes defined by a set F of forbidden induced subgraphs.We describe a condition on the set F , which guarantees that the MAXIMUM INDEPENDENT SET problem remains NP-hard in the class of F -free graphs. The same hardness result remains valid even under the additional restriction that the graphs are planar and of maximum degree at most three.We exhibit several cases where the condition is violated, and the problem admits a polynomial-time solution. More specifically, we present polynomial-time algorithms for the MAXIMUM INDEPENDENT SET problem in: (1) two graph classes that properly contain claw-free graphs (thus generalizing the classical result for claw-free graphs); (2) various subclasses of planar and more general graphs; (3) weighted graphs in certain subclasses of graphs of bounded vertex degree.Our algorithms are based on various approaches. In particular, we develop an extension of the method of finding augmenting graphs. We also make extensive use of some other well-known graph decompositions.We also introduce and study the exact version of the problem, where, instead of finding an independent set of maximum weight, the goal is to find an independent set of given weight. Determining the computational complexity of this problem for line graphs, or for line graphs of bipartite graphs would resolve long standing open problems. Here, we show that: (1) The EXACT WEIGHTED INDEPENDENT SET problem is strongly NP-complete for cubic bipartite graphs. (2) The problem is solvable in pseudo-polynomial time for any of the following graph classes: mK2-free graphs, interval graphs and their generalizations k-thin graphs, circle graphs, chordal graphs, AT-free graphs, (claw, net)-free graphs, distance-hereditary graphs, and graphs of bounded tree- or clique-width.Finally, we show how modular decomposition can be applied to the EXACT WEIGHTED INDEPENDENT set problem. As a corollary, we obtain pseudo-polynomial solutions for the problem in certain subclasses of P5-free and fork-free graphs.
Learning concurrently partition granularities and rule bases of Mamdani fuzzy systems in a multi-objective evolutionary framework
Authors: Michela Antonelli, Pietro Ducange, Beatrice Lazzerini, Francesco Marcelloni
Venue: International Journal of Approximate Reasoning (2009)

In this paper we propose a multi-objective evolutionary algorithm to generate Mamdani fuzzy rule-based systems with different good trade-offs between complexity and accuracy. The main novelty of the algorithm is that both rule base and granularity of the uniform partitions defined on the input and output variables are learned concurrently. To this aim, we introduce the concepts of virtual and concrete rule bases: the former is defined on linguistic variables, all partitioned with a fixed maximum number of fuzzy sets, while the latter takes into account, for each variable, a number of fuzzy sets as determined by the specific partition granularity of that variable. We exploit a chromosome composed of two parts, which codify the variables partition granularities, and the virtual rule base, respectively. Genetic operators manage virtual rule bases, whereas fitness evaluation relies on an appropriate mapping strategy between virtual and concrete rule bases. The algorithm has been tested on two real-world regression problems showing very promising results.
Limitation and Possibilities of Automation on the Way from Intention → Program
Authors: Victor Malyshkin, Yuri Zagorulko
Venue: Proceeding of the 2005 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the fourth SoMeT_W05 (2005)

The paper is devoted to the discussion of the limitations and possibilities of the automation of the process of program construction from an informal specification.
Mastering Autodesk VIZ 2008
Authors: Jon McFarland
Venue:  (2007)

In Mastering Autodesk VIZ 2008, VIZ expert Jon McFarland teaches you how to get the most out of Autodesk's potent 3D modeling, animation, and rendering software. As you follow real-world examples, you'll quickly see how to apply these techniques to your design projects. Whether you're entirely new to VIZ or simply want to master its newest features, this book offers the clear explanations and step-by-step instruction you need to make VIZ work for you. Coverage includes: Finding your way around in VIZ Linking to AutoCAD files Modeling using primitive and compound objects Editing using modifers and sub-objects Creating complex shapes with surface modeling tools Managing your design data more efficiently Simulating lighting effects accurately with global illumination Rendering real-world surfaces with Architectural material Setting up animated walk-throughs Using radiosity to create accurate scene lighting Using mental ray to achieve the most realistic rendering Producing design presentation views Understanding keyframes and function curve editing Acquiring 3D models and props from the Web 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
A strategy-based process for effectively determining system requirements in eCRM development
Authors: Ing-Long Wu, Ching-Yi Hung
Venue: Information and Software Technology (2009)

Customer relationship management (CRM) is an important concept to maintain competitiveness at e-commerce. Thus, many organizations hastily implement eCRM and fail to achieve its goal. CRM concept consists of a number of compound components on product designs, marketing attributes, and consumer behaviors. This requires different approaches from traditional ones in developing eCRM. Requirements engineering is one of the important steps in software development. Without a well-defined requirements specification, developers do not know how to proceed with requirements analysis. This research proposes a strategy-based process for requirements elicitation. This framework contains three steps: define customer strategies, identify consumer and marketing characteristics, and determine system requirements. Prior literature lacks discussing the important role of customer strategies in eCRM development. Empirical findings reveal that this strategy-based view positively improves the performance of requirements elicitation.
Daios: Efficient Dynamic Web Service Invocation
Authors: Philipp Leitner, Florian Rosenberg, Schahram Dustdar
Venue: IEEE Internet Computing (2009)

Systems based on the service-oriented architecture (SOA) paradigm must be able to bind to arbitrary Web services at runtime. However, current service frameworks are predominantly used through precompiled service-access components, which are invariably hard-wired to a specific service provider. The Dynamic and Asynchronous Invocation of Services framework is a message-based service framework that supports SOA implementation, allowing dynamic invocation of SOAP/WSDL-based and RESTful services. It abstracts from the target service's internals, decoupling clients from the services they use.
Research Article: Search of regular sequences in promoters from eukaryotic genomes
Authors: Andrew Shelenkov, Eugene Korotkov
Venue: Computational Biology and Chemistry (2009)

In this paper, the notion of ''regularity'' is introduced to describe the structural features of DNA sequences. This notion expands the ''latent periodicity'' term. The novel method for revealing regularity based on the runs test is described. The search of regular sequences in eukaryotic promoters has shown that more than 60% of them possess a regularity property on statistically significant level. Possible biological functions of regularity are discussed together with the possibility of using this characteristic for performing promoter annotation.