ppxscal/embedding_network huggingface dataset:
Effects of orness and dispersion on WOWA sensitivity
Authors: Vicenç Torra
Venue: Proceeding of the 2008 conference on Artificial Intelligence Research and Development: Proceedings of the 11th International Conference of the Catalan Association for Artificial Intelligence (2008)

The WOWA operator is an aggregation operator that generalizes the weighted mean and the OWA operator. In this paper we study the sensitivity of this operator with respect to the interpolation method used in its calculation. We analyze the sensitivity with respect to the orness and dispersion (entropy) of the weighting vector.
Direct Pore Matching for Fingerprint Recognition
Authors: Qijun Zhao, Lei Zhang, David Zhang, Nan Luo
Venue: Proceedings of the Third International Conference on Advances in Biometrics (2009)

Sweat pores on fingerprints have proven to be useful features for personal identification. Several methods have been proposed for pore matching. The state-of-the-art method first matches minutiae on the fingerprints and then matches the pores based on the minutia matching results. A problem of such minutia-based pore matching method is that the pore matching is dependent on the minutia matching. Such dependency limits the pore matching performance and impairs the effectiveness of the fusion of minutia and pore match scores. In this paper, we propose a novel direct approach for matching fingerprint pores. It first determines the correspondences between pores based on their local features. It then uses the RANSAC (RANdom SAmple Consensus) algorithm to refine the pore correspondences obtained in the first step. A similarity score is finally calculated based on the pore matching results. The proposed pore matching method successfully avoids the dependency of pore matching on minutia matching results. Experiments have shown that the fingerprint recognition accuracy can be greatly improved by using the method proposed in this paper.
Chairs' Introduction to Workshop on Computational Finance and Business Intelligence
Authors: Yong Shi, Shouyang Wang, Xiaotie Deng
Venue: Proceedings of the 9th International Conference on Computational Science (2009)

We have been organizing the Workshop on Computational Finance and Business Intelligence (CFBI) at International Conference on Computational Science (ICCS) since 2003. This workshop at ICCS, Baton Rouge, Louisiana, U.S.A., May 25-27, 2009 focuses on computational science aspects of asset and derivatives pricing, financial risk management, and related topics to business intelligence. It will include but not limited to modeling, numeric computation, algorithmic and complexity issues in arbitrage, asset pricing, future and option pricing, risk management, credit assessment, interest rate determination, insurance, foreign exchange rate forecasting, online auction, cooperative game theory, general equilibrium, information pricing, network band witch pricing, rational expectation, repeated games, etc.
Enhanced graph-based dimensionality reduction with repulsion Laplaceans
Authors: E. Kokiopoulou, Y. Saad
Venue: Pattern Recognition (2009)

Graph-based methods for linear dimensionality reduction have recently attracted much attention and research efforts. The main goal of these methods is to preserve the properties of a graph representing the affinity between data points in local neighborhoods of the high-dimensional space. It has been observed that, in general, supervised graph-methods outperform their unsupervised peers in various classification tasks. Supervised graphs are typically constructed by allowing two nodes to be adjacent only if they are of the same class. However, such graphs are oblivious to the proximity of data from different classes. In this paper, we propose a novel methodology which builds on 'repulsion graphs', i.e., graphs that model undesirable proximity between points. The main idea is to repel points from different classes that are close by in the input high-dimensional space. The proposed methodology is generic and can be applied to any graph-based method for linear dimensionality reduction. We provide ample experimental evidence in the context of face recognition, which shows that the proposed methodology (i) offers significant performance improvement to various graph-based methods and (ii) outperforms existing solutions relying on repulsion forces.
The factorization structure in the reflective subcategory
Authors: Cerbu Olga
Venue: Proceedings of the 15th american conference on Applied mathematics (2009)

We examine the relations between factorization structure of the category and of the reflective subcategory. These problems appear in study of the left exact reflective functors and in study of the semireflexive subcategories.
The LEMO annotation framework: weaving multimedia annotations with the web
Authors: Bernhard Haslhofer, Wolfgang Jochum, Ross King, Christian Sadilek, Karin Schellner
Venue: International Journal on Digital Libraries (2009)

Cultural institutions and museums have realized that annotations contribute valuable metadata for search and retrieval, which in turn can increase the visibility of the digital items they expose via their digital library systems. By exploiting annotations created by others, visitors can discover content they would not have found otherwise, which implies that annotations must be accessible and processable for humans and machines. Currently, however, there exists no widely adopted annotation standard that goes beyond specific media types. Most institutions build their own in-house annotation solution and employ proprietary annotation models, which are not interoperable with those of other systems. As a result, annotation data are usually stored in closed data silos and visible and processable only within the scope of a certain annotation system. As the main contribution of this paper, we present the LEMO Annotation Framework. It (1) provides a uniform annotation model for multimedia contents and various types of annotations, (2) can address fragments of various content-types in a uniform, interoperable manner and (3) pulls annotations out of closed data silos and makes them available as interoperable, dereferencable Web resources. With the LEMO Annotation Framework annotations become part of the Web and can be processed, linked, and referenced by other services. This in turn leads to even higher visibility and increases the potential value of annotations.
Compact approximations of mixture distributions for state estimation in multiagent settings
Authors: Prashant Doshi
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2 (2009)

In order to act rationally, an agent must track the state of the environment over time. In the presence of other agents who themselves act, observe, and update their beliefs the agent must track not only the physical state but also the possible states of others. This is because others' actions may affect the evolution of the physical state and the agent's payoffs. One approach is to generalize the Bayes filter to multiagent settings, in which an agent tracks the evolution of the interactive state [2]. In practice, the estimation may be carried out using the interactive PF (I-PF) [2] that generalizes the PF to the multiagent setting.
Macroprogramming scalable sensor networks
Authors: Ananth Grama
Venue:  (2008)

Recent prototypical systems have demonstrated applications of wireless sensor networks in diverse sensing and data processing domains. As applications of sensor networks mature, there is an increasing realization of the complexity associated with programming large numbers of resource and energy constrained heterogeneous devices that operate cooperatively in highly dynamic environments. In this thesis, we investigate sensor network macroprogramming: a novel high-level programming model that entails specification of aggregate distributed system behavior. Our macroprogramming architecture facilitates development of self-organized sensor network systems that are scalable, energy-efficient, and verifiable. This model is in contrast to the state of the art that involves programming of low-level behavior of individual nodes, which is a non-trivial, effort-intensive, and error-prone task.We undertake a comprehensive study to address fundamental challenges in macro-programming sensor networks. Specifically, we make the following contributions towards realization of a comprehensive macroprogramming infrastructure. First, we present a high-level programming model and associated infrastructure, COSMOS, which allows explicit specification of distributed coordinated behavior in contrast to the traditional model of programming individual nodes. We present a lean operating system that supports COSMOS applications, and features support for scalable distributed data flow based programs. Second, we examine the complexity of developing applications that adaptively manage resource tradeoffs under constraints, and argue that such applications require static behavioral verification. To this end we propose a high-level logic language and an associated synthesis engine that verifies user programs and generates robust applications. Third, we present a compiler for sensor network applications that generates energy-efficient and low messaging cost primitives from specifications of complex distributed sensornet protocols. Finally, we present an in-network data compression protocol that enables application independent high-resolution sensor monitoring while minimizing the energy footprint. We support claims of efficiency and effectiveness of our macroprogramming infrastructure with experiences from a real-world deployment of our system and comprehensive empirical evaluation.
Quantum error control codes
Authors: Andreas Klappenecker
Venue:  (2008)

It is conjectured that quantum computers are able to solve certain problems more quickly than any deterministic or probabilistic computer. For instance, Shor&rsquo;s algorithm is able to factor large integers in polynomial time on a quantum computer. A quantum computer exploits the rules of quantum mechanics to speed up computations. However, it is a formidable task to build a quantum computer, since the quantum mechanical systems storing the information unavoidably interact with their environment. Therefore, one has to mitigate the resulting noise and decoherence effects to avoid computational errors. In this dissertation, I study various aspects of quantum error control codes &ndash; the key component of fault-tolerant quantum information processing. I present the fundamental theory and necessary background of quantum codes and construct many families of quantum block and convolutional codes over finite fields, in addition to families of subsystem codes. This dissertation is organized into three parts: Quantum Block Codes. After introducing the theory of quantum block codes, I establish conditions when BCH codes are self-orthogonal (or dual-containing) with respect to Euclidean and Hermitian inner products. In particular, I derive two families of nonbinary quantum BCH codes using the stabilizer formalism. I study duadic codes and establish the existence of families of degenerate quantum codes, as well as families of quantum codes derived from projective geometries. Subsystem Codes . Subsystem codes form a new class of quantum codes in which the underlying classical codes do not need to be self-orthogonal. I give an introduction to subsystem codes and present several methods for subsystem code constructions. I derive families of subsystem codes from classical BCH and RS codes and establish a family of optimal MDS subsystem codes. I establish propagation rules of subsystem codes and construct tables of upper and lower bounds on subsystem code parameters. Quantum Convolutional Codes. Quantum convolutional codes are particularly well-suited for communication applications. I develop the theory of quantum convolutional codes and give families of quantum convolutional codes based on RS codes. Furthermore, I establish a bound on the code parameters of quantum convolutional codes &ndash; the generalized Singleton bound. I develop a general framework for deriving convolutional codes from block codes and use it to derive families of non-catastrophic quantum convolutional codes from BCH codes. The dissertation concludes with a discussion of some open problems.
Land cover change detection with a cross-correlogram spectral matching algorithm
Authors: Le Wang, Jin Chen, Peng Gong, Hiroto Shimazaki, Masayuki Tamura
Venue: International Journal of Remote Sensing (2009)

Timely extraction of reliable land cover change information is increasingly needed at a wide continuum of scales. Few methods developed from previous studies have proved to be robust when noise, changes in atmospheric and illumination conditions, and other scene-and sensor-dependent variables are present in the multitemporal images. In this study, we developed a new method based on cross-correlogram spectral matching (CCSM) with the aim of identifying interannual land cover changes from time-series Normalized Difference Vegetation Index (NDVI) data. In addition, a new change index is proposed with integration of two parameters that are measured from the cross-correlogram: the root mean square (RMS) and (1-R max), where R max is the maximum correlation coefficient in a correlogram. Subsequently, a method was proposed to derive the optimal threshold for judging 'change' or 'non-change' with the acquired change index. A pilot study was carried out using SPOT VGT-S images acquired in 1998 and 2000 at Xianghai Park in Jilin Province. The results indicate that CCSM is superior to a traditional Change Vector Analysis (CVA) when noise is present with the data. Because of an error associated with the ground truthing data, a more comprehensive assessment of the developed method is still in process using better ground truthing data and images at a larger time interval. It is worth noting that this method can be applied not only to NDVI datasets but also to other index datasets reflecting surface conditions sampled at different time intervals. In addition, it can be applied to datasets from different satellites without the need to normalize sensor differences.
Visibility-based modelling and control for network-based robotics
Authors: Sang Il Lee, Byoung In Cho, Jae-Kyu Lee, Seongjin Ahn, Jin Wook Chung
Venue: Pattern Recognition Letters (2009)

We present an algorithm to model 3D workspace and to understand test scene for navigation or human computer interaction in network-based mobile robot. This was done by line-based modelling and recognition algorithm. Line-based recognition using 3D lines has been tried by many researchers however its reliability still needs improvement due to ambiguity of 3D line feature information from original images. To improve the outcome, we approach firstly to find real planes using the given 3D lines and then to implement recognition process. The methods we use are principle component analysis (PCA), plane sweep, visibility test, and iterative closest point (ICP). During the implementation, we also use 3D map information for localization. We apply this algorithm to real test scene images and to find out our result can be useful to identify doors or walls in indoor environment with better efficiency.
Computer Aided Support for Content Management Development
Authors: Antti Lehtinen, Airi Salminen
Venue: Proceeding of the 2007 conference on Information Modelling and Knowledge Bases XVIII (2007)

Content management development searches for improvements in the utilization of information and communication technology in the management of various information resources, and for more systematic ways for the management. The goal of the development may be, for example, integration of different software systems, improvements in information retrieval or archival, building new kinds of services for people working in the development domain, or all these together. The paper discusses the differences in the content management and information systems development and the information modelling needs in content management development. The paper introduces a computer aided modelling tool built over a metaCASE tool for content management development. The tool has been used to analyze and describe content management in the Finnish legislative work. The paper reports experiences of using the tool.
Extractive summaries for educational science content
Authors: Sebastian de la Chica, Faisal Ahmad, James H. Martin, Tamara Sumner
Venue: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers (2008)

This paper describes an extractive summarizer for educational science content called COGENT. COGENT extends MEAD based on strategies elicited from an empirical study with domain and instructional experts. COGENT implements a hybrid approach integrating both domain independent sentence scoring features and domain-aware features. Initial evaluation results indicate that COGENT outperforms existing summarizers and generates summaries that closely resemble those generated by human experts.
Parallel error detection for leading zero anticipation
Authors: Ge Zhang, Wei-Wu Hu, Zi-Chu Qi
Venue: Journal of Computer Science and Technology (2006)

The algorithm and its implementation of the leading zero anticipation (LZA) are very vital for the performance of a high-speed floating-point adder in today's state of art microprocessor design. Unfortunately, in predicting "shift amount" by a conventional LZA design, the result could be off by one position. This paper presents a novel parallel error detection algorithm for a general-case LZA. The proposed approach enables parallel execution of conventional LZA and its error detection, so that the error-indication signal can be generated earlier in the stage of normalization, thus reducing the critical path and improving overall performance. The circuit implementation of this algorithm also shows its advantages of area and power compared with other previous work.
End-to-end performance forecasting: finding bottlenecks before they happen
Authors: Ali G. Saidi, Nathan L. Binkert, Steven K. Reinhardt, Trevor Mudge
Venue: Proceedings of the 36th annual international symposium on Computer architecture (2009)

Many important workloads today, such as web-hosted services, are limited not by processor core performance but by interactions among the cores, the memory system, I/O devices, and the complex software layers that tie these components together. Architects designing future systems for these workloads are challenged to identify performance bottlenecks because, as in any concurrent system, overheads in one component may be hidden due to overlap with other operations. These overlaps span the user/kernel and software/hardware boundaries, making traditional performance analysis techniques inadequate. We present a methodology for identifying end-to-end critical paths across software and simulated hardware in complex networked systems. By modeling systems as collections of state machines interacting via queues, we can trace critical paths through multiplexed processing engines, identify when resources create bottlenecks (including abstract resources such as flow-control credits), and predict the benefit of eliminating bottlenecks by increasing hardware speeds or expanding available resources. We implement our technique in a full-system simulator and analyze a TCP microbenchmark, a web server, the Linux TCP/IP stack, and an Ethernet controller. From a single run of the microbenchmark, our tool--within minutes--correctly identifies a series of bottlenecks, and predicts the performance of hypothetical systems in which these bottlenecks are successively eliminated, culminating in a total speedup of 3X.We then validate these predictions through hours of additional simulation, and find them to be accurate within 1--17%. We also analyze the web server, find it to be CPU-bound, and predict the performance of a system with an additional core within 6%.
NVivo Essentials
Authors: Bengt Edhlund
Venue:  (2007)

A user guide that helps you gain a better understanding of the new NVivo 7. Step-by-step instructions are combined with helpful comments to explain the terms used within qualitative analysis. NVivo 7 is a great step forward towards an environment more consistent with the Windows standard. NVivo 7 can handle all languages and alphabets supported by Windows. NVivo can also import and export Word and Excel files. Several categories of nodes can be created: Free nodes, Tree nodes, Cases, Relationships, and Matrices. The query methods are now much more diversified and this book clearly explains how queries are constructed and results are saved. You can also create reports and graphical models for presentations and team discussions. This book can be used as course literature or for self-teaching. A comprehensive yet clear list of contents, glossary, and index ensures the ease of finding the solution to problems that may occur. 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
Combinary Competence Reflections on Multidisicplinary Approaches to Digital Media and Learning
Authors: Gunnar Liestøl
Venue: Proceeding of the 2005 conference on Towards Sustainable and Scalable Educational Innovations Informed by the Learning Sciences: Sharing Good Practices of Research, Experimentation and Innovation (2005)

Recent developments in the convergence and divergence of digital media and learning have made it obvious that multidisciplinary research and development is both a challenge and a problem in need of serious reflection and understanding. Interdisciplinarity is in one way or the other, involved in most research efforts aimed at exploiting the potential and promise of digital media in the context of learning. Based on practical experience with how theories and methodologies of both computer science and the humanities have been conjoined in developing digital solutions for learning, this paper discuss the benefits and problems of such a combined approach. Drawing from perspectives in epistemology (Bateson and Wittgenstein) the notion of a combinatory competence is suggested as a prospect for handling the compatibilities and incompatibilities of multidisciplinary research and development in the complex, but exciting field of digital media in education.
A numerical algorithm for viscous incompressible interfacial flows
Authors: Jin Wang, Greg Baker
Venue: Journal of Computational Physics (2009)

We present a new algorithm to numerically simulate two-dimensional viscous incompressible flows with moving interfaces. The motion is updated in time by using the backward difference formula through an iterative procedure. At each iteration, the pseudo-spectral technique is applied in the horizontal direction. The resulting semi-discretized equations constitute a boundary value problem in the vertical coordinate which is solved by decoupling growing and decaying solutions. Numerical tests justify that this method achieves fully second-order accuracy in both the temporal variable and vertical coordinate. As an application of this algorithm, we study the motion of Stokes waves in the presence of viscosity. Our numerical results are consistent with the recently published asymptotic solution for Stokes waves in slightly viscous fluids.