ppxscal/embedding_network huggingface dataset:
Preconditioning via a Schur Complement Method: An Application in State Estimation
Authors: Luise Blank
Venue: SIAM Journal on Scientific Computing (2003)

In this work the Schur complement is analyzed and applied for preconditioning symmetric matrices. In particular we eliminate the in modulo extreme eigenvalues by computing the Schur complement with respect to a coarse subspace, which captures the corresponding eigenvectors. The potential of this method is presented as an application in state estimation, where we employ a multiscale approach based on a wavelet-Galerkin discretization. The hierarchy of arising optimization problems is solved in the framework of nested iterations. Due to the wavelet approach, for all scales we can use one coarse adapted subspace in the Schur complement method. Typically this provides not only a reduced condition number but also large gaps in the arising eigenvalue distribution, which is favorable for several iterative methods. Numerical investigations show the enormous reduction in the condition number, the necessary cg-iteration steps and, consequently, in the computation time.
Digital Background Gain Error Correction in Pipeline ADCs
Authors: Antonio J. Ginés, Eduardo J. Peralías, Adoración Rueda
Venue: Proceedings of the conference on Design, automation and test in Europe - Volume 1 (2004)

This paper presents a new digital technique for background calibration of gain errors in Pipeline ADCs. The proposed algorithm estimates and corrects both the MDAC gain error of the stage under calibration and the global gain error associated to the uncalibrated stages without interruption of the conversion and without reduction of the dynamic rate. It is based on the use of a stage with two input-output characteristics, depending on the value of a digital noise signal.
An Information Architecture to Support Dynamic Composition of Interactive Lessons and Reuse of Learning Objects
Authors: Melanie Kellar, Henry Stern, Carolyn Watters, Michael Shepherd
Venue: Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 1 - Volume 1 (2004)

In this paper we describe an information architecture that supports the dynamic composition of Web based lessons based on a database of fine grained components that can be tailored for communities of users. Our goal is to support Web accessible resources of pedagogical material that can be used and reused in a variety of contexts from teacher remediation and lesson preparation to the use of lessons that reflects the diversity of individual learning styles. The Web based lessons are generated on the fly from a database of fine grained components that include explanations, interactive activities, worksheets, images, videos, audio, FAQ's, online questions and challenges. This architecture had been used in the development of learning support systems for two different communities; users of middle school mathematics in one case and users of health informatics learning modules in the other case.
Information Theoretic Clustering of Sparse Co-Occurrence Data
Authors: Inderjit S. Dhillon, Yuqiang Guan
Venue: Proceedings of the Third IEEE International Conference on Data Mining (2003)

A novel approach to clustering co-occurrence data posesit as an optimization problem in information theory whichminimizes the resulting loss in mutual information. A divisiveclustering algorithm that monotonically reduces thisloss function was recently proposed. In this paper we showthat sparse high-dimensional data presents special challengeswhich can result in the algorithm getting stuck atpoor local minima. We propose two solutions to this problem:(a) a "prior" to overcome infinite relative entropy valuesas in the supervised Naive Bayes algorithm, and (b)local search to escape local minima. Finally, we combinethese solutions to get a robust algorithm that is computationallyefficient. We present experimental results to showthat the proposed method is effective in clustering documentcollections and outperforms previous information-theoreticclustering approaches.
Triangulation and display of rational parametric surfaces
Authors: Chandrajit L. Bajaj, Andrew Royappa
Venue: Proceedings of the conference on Visualization '94 (1994)

We present a comprehensive algorithm to construct a topologically correct triangulation of the real affine part of a rational parametric surface with few restrictions on the defining rational functions. The rational functions are allowed to be undefined on domain curves (pole curves) and at certain special points (base points), and the surface is allowed to have nodal or cuspidal self-intersections. We also recognize that for a complete display some real points on the parametric surface may be generated only by complex parameter values, and that some finite points on the surface may be generated only by infinite parameter values; we show how to compensate for these conditions. Our techniques for handling these problems have applications in scientific visualization, rendering non-standard NURBS, and in finite-element mesh generation.
On lists and other abstract data types in the calculus of constructions
Authors: Jonathan P. Seldin
Venue: Mathematical Structures in Computer Science (2000)

The representation of the inductively defined abstract data type for lists was left incomplete in Seldin (1997, Section 9). Here that representation is completed, and it is proved that all extra axioms needed are consistent. Among the innovations of this paper is a definition of cdr, whose definition was left for future work in Seldin (1997, Section 9). The results are then extended to other abstract data types &ndash; those of Berardi (1993). The method used to define cdr for lists is extended to obtain the definition of an inverse for each argument of each constructor of an abstract data type. These inverses are used to prove the injective property for the constructors. Also, Dedekind's method of defining the natural numbers is used to define a predicate associated with each abstract data type, and the use of this predicate makes it unnecessary to postulate the induction principle. The only axioms left to be proved are those asserting the disjointness of the co-domains of different constructors, and it is shown that those axioms can be proved consistent.
Distributed approaches to design network services in rapidly deployable wireless networks
Authors: Sanket Satish Nesargi
Venue:  (2002)

Rapidly Deployable Wireless Networks (RDWNs) are wireless networks without any fixed infrastructure. They consist of networks in which all the nodes are mobile. We have developed protocols for two types of RDWNs, viz., Virtual Cellular Networks (VCNs) and Mobile Ad Hoc Networks (MANETs). VCNs consist of nodes in a two level hierarchy, viz., Mobile Base Stations (MBSs) at the backbone level and Mobile Nodes (MNs) at the short-hop level which are served by their nearest MBSs. All nodes are connected by wireless links. MNs communicate with other MNs via their serving MBSs. MANETs, on the other hand, have a flat topology. The mobile nodes communicate with each other via other mobile nodes and form a multi-hop network. Nodes in RDWNs expect certain services from the network to operate effectively. These include services to configure IP addresses and allocate communication channels. These services are provided in wired networks by protocols with centralized implementations. However, network services in RDWNs need to be completely distributed. As part of our research, we have developed distributed protocols to provide these services. The protocols illustrate general approaches which can be used to develop distributed network services for RDWNs. We have also developed frameworks to facilitate the porting of existing distributed services to operate effectively and efficiently in RDWNs, and design scalable network services in RDWNs.
A multiscale framework for blind separation of linearly mixed signals
Authors: Pavel Kisilev, Michael Zibulevsky, Yehoshua Y. Zeevi
Venue: The Journal of Machine Learning Research (2003)

We consider the problem of blind separation of unknown source signals or images from a given set of their linear mixtures. It was discovered recently that exploiting the sparsity of sources and their mixtures, once they are projected onto a proper space of sparse representation, improves the quality of separation. In this study we take advantage of the properties of multiscale transforms, such as wavelet packets, to decompose signals into sets of local features with various degrees of sparsity. We then study how the separation error is affected by the sparsity of decomposition coefficients, and by the misfit between the probabilistic model of these coefficients and their actual distribution. Our error estimator, based on the Taylor expansion of the quasi-ML function, is used in selection of the best subsets of coefficients and utilized, in turn, in further separation. The performance of the algorithm is evaluated by using noise-free and noisy data. Experiments with simulated signals, musical sounds and images, demonstrate significant improvement of separation quality over previously reported results.
Image database retrieval utilizing affinity relationships
Authors: Mei-Ling Shyu, Shu-Ching Chen, Min Chen, Chengcui Zhang, Kanoksri Sarinnapakorn
Venue: Proceedings of the 1st ACM international workshop on Multimedia databases (2003)

Recent research effort in Content-Based Image Retrieval (CBIR) focuses on bridging the gap between low-level features and high-level semantic contents of images as this gap has become the bottleneck of CBIR. In this paper, an effective image database retrieval framework using a new mechanism called the Markov Model Mediator (MMM) is presented to meet this demand by taking into consideration not only the low-level image features, but also the high-level concepts learned from the history of user's access pattern and access frequencies on the images in the database. Also, the proposed framework is efficient in two aspects: 1) Overhead for real-time training is avoided in the image retrieval process because the high-level concepts of images are captured in the off-line training process. 2) Before the exact similarity matching process, Principal Component Analysis (PCA) is applied to reduce the image search space. A training subsystem for this framework is implemented and integrated into our system. The experimental results demonstrate that the MMM mechanism can effectively assist in retrieving more accurate results from image databases.
WALRUS: A Similarity Retrieval Algorithm for Image Databases
Authors: Apostol Natsev, Rajeev Rastogi, Kyuseok Shim
Venue: IEEE Transactions on Knowledge and Data Engineering (2004)

Abstract--Approaches for content-based image querying typically extract a single signature from each image based on color, texture, or shape features. The images returned as the query result are then the ones whose signatures are closest to the signature of the query image. While efficient for simple images, such methods do not work well for complex scenes since they fail to retrieve images that match the query only partially, that is, only certain regions of the image match. This inefficiency leads to the discarding of images that may be semantically very similar to the query image since they may contain the same objects. The problem becomes even more apparent when we consider scaled or translated versions of the similar objects. In this paper, we propose WALRUS (WAveLet-based Retrieval of User-specified Scenes), a novel similarity retrieval algorithm that is robust to scaling and translation of objects within an image. WALRUS employs a novel similarity model in which each image is first decomposed into its regions and the similarity measure between a pair of images is then defined to be the fraction of the area of the two images covered by matching regions from the images. In order to extract regions for an image, WALRUS considers sliding windows of varying sizes and then clusters them based on the proximity of their signatures. An efficient dynamic programming algorithm is used to compute wavelet-based signatures for the sliding windows. Experimental results on real-life data sets corroborate the effectiveness of WALRUS's similarity model.
A Biology Inspired Neural Learning Algorithm for Analysing Protein Sequences
Authors: Emily Berry, Zheng Rong Yang, XiKun Wu
Venue: Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence (2003)

This paper presents a biology inspired neural learning algorithm called bio-basis function neuralnetwork (BBFNN) for analysing protein sequences. The basic principle is to replace radial basis functions of conventional radial basis function neural networks with amino acid similarity measurement matrices. From this, model complexity can be significantly reduced and hence model robustness can be enhanced dramatically. We have applied the algorithm to the prediction of the phosphorylation sites in proteins and the cleavage sites in hepatitis C virus (HCV) polyproteins with success.
Prediction and knowledge mining with in vitro fertilization data
Authors: I. Jurisica
Venue: ACM SIGBIO Newsletter (1998)

TA3 is a case-based reasoning system with knowledge discovery (KD) capabilities.TA3 uses efficient and flexible variable context similarity-based retrieval.KD component is used for 3 main tasks:1. TA3 optimization: locating descriptors relevant for a given context & task; and organizing case base into context-based clusters2. Case base and domain knowledge evolution: adding descriptors to assist case discrimination during prediction and classification; removing redundant cases and descriptors; creating hierarchies of descriptors and their values; finding associations3. Evidence-based medicine: analyzing created clusters, hierarchies and associations to identify underlying principles in the domain
Protecting Personal Data: Can IT Security Management Standards Help?
Authors: Giovanni Iachello
Venue: Proceedings of the 19th Annual Computer Security Applications Conference (2003)

Compelled to improve information security by the introductionof personal data protection legislation, organizationsworldwide are adopting standardized securitymanagement guidelines to inform their internal processes.This paper analyzes whether existing security managementstandards support process requirements for personaldata management, drawing from experience withsecurity policies in private organizations and through ananalysis of current European and US legislation. Variousaspects of personal data management not commonly addressedby security standards are identified, and a numberof generally applicable enhancements are proposed toone common standard, IS17799. The appropriateness ofincluding data protection guidelines in security standardsis discussed, showing how these enhancements could simplifythe definition of personal data management proceduresin organizations.
A Consensus Protocol for CAN-Based Systems
Authors: G. M. A. Lima, A. Burns
Venue: Proceedings of the 24th IEEE International Real-Time Systems Symposium (2003)

Consensus is known to be a fundamental problem infault-tolerant distributed systems. Solving this problem providesthe means for distributed processes to agree on a singlevalue. This, however, requires extra communication efforts.For some real-time communication networks such effortsmay have undesirable performance implications dueto their limited bandwidth. This is certainly the case withthe Controller Area Network (CAN), which is widely used tosupport real-time systems. This paper shows how some underlyingproperties of CAN can be used to solve the consensusproblem. The proposed consensus protocol tolerates themaximum number of process crashes, is efficient and flexible.The described solution is proved correct, its complexityis analysed and its performance is evaluated by simulation.
Maximum Log-Likelihood Function-Based QAM Signal Classification over Fading Channels
Authors: Yawpo Yang, Jen-Ning Chang, Ji-Chyun Liu, Ching-Hwa Liu
Venue: Wireless Personal Communications: An International Journal (2004)

In this paper, we propose a modulation classification algorithm for M-ary QAM signals in Rician and Rayleigh fading channels. The developed algorithms are based on the maximum log-likelihood functions, which are derived from received signals. First of all, we derived the amplitude PDF of M-ary QAM signal over flat and slowly Rayleigh and Rician fading channel, then we developed the log-likelihood functions and then the decision functions for classification. To demonstrate the performance of the proposed classifier, we give an example to classify the 16/32 QAM signals. Results indicate that the performance of classifier is heavily dependent on the severity of channel fading. When channel is AWGN, which means that there exists only one path (may be specular path) between transmitter and receiver, and the Rician factor k, approaches infinity in this case, henceforth, the performance is the best. The performance, however, is degraded with the decrease of k, and finally the classifier performs worst when channel becomes Rayleigh. Further performance improvement can be achieved by increasing the length of record.
Channel model based on semi-Markovian processes. An approach for HAPS systems
Authors: José Luis Cuevas-Ruíz, José A. Delgado-Penín
Venue: Proceedings of the 14th International Conference on Electronics, Communications and Computers (2004)

In the planning and design of aTelecommunication System model a factor of importance isthe channel. The deterioration to which the signal is exposeddetermines the QoS that a system can get, as well as also somuch of the characteristic of the channel influence thedesign of the transmitter and receiver systems. A channelmodel that represents the behaviour of a propagationmedium is an useful tool to analyze and evaluate systemsunder diverse conditions and situations. Here is presentedthe analysis of a system based on HAPS, using a model ofchannel considering semi-Markov random processes with 2and 3 states. Results obtained in both cases are analyzed andcompared.
Trans Type: Development-Evaluation Cycles to Boost Translator's Productivity
Authors: Philippe Langlais, Guy Lapalme
Venue: Machine Translation (2002)

We present TransType: a new approach to Machine-Aided Translation in which the human translator maintains control of the translation process while being helped by real-time completions proposed by a statistical translation engine. The TransType approach is first presented through a series of prototypes that illustrate their underlying translation model and graphical interface. The results of two rounds of in situ evaluation of TransType prototypes are discussed followed by a set of lessons learned in these experiments. It will be shown that this approach is valued by translators but given the short time allotted for the evaluation, translators were not able to quantitatively increase their productivity. TransType is compared with other approaches and new perspectives are elaborated for a new version being developed in the context of a Fifth Framework European Community Project.
Generating Scenarios from Use Case Map Specifications
Authors: Daniel Amyot, Xiangyang He, Yong He, Dae Yong Cho
Venue: Proceedings of the Third International Conference on Quality Software (2003)

The Use Case Map (UCM) notation is being standardizedas part of the User Requirements Notation(URN), the most recent addition to ITU-T's family of languages.UCM models describe functional requirementsand high-level designs with causal paths superimposed ona structure of components. The generation of individualscenarios from UCM specifications enables the validationof requirements and facilitates the transition from requirementsto design. In this paper, we address the challengesfaced during the automated generation of such scenarios.Scenario definitions and traversal algorithms arefirst used to extract individual scenarios from UCMs andto store them as XML files. Transformations to other scenariolanguages (for instance, Message Sequence Charts)are then achieved using XSLT. Possible applications ofthis two-step generation process include early validationand synthesis of design models. Illustrative examples aregiven based on our current tools and recent experiments.
Evaluating the effectiveness of a computer based letter formation system for children
Authors: Linda Snape, Tony Nicol
Venue: Proceedings of the 2003 conference on Interaction design and children (2003)

A series of letter formation experiments were carried out to test the effectiveness of a computer assisted learning program which assists and monitors children forming letters. The experiment reported in this paper suggests that the rate of letter formation skill development increased for children using the computer based system.
Some families of Mordell curves associated to cubic fields
Authors: Katsuya Miyake
Venue: Journal of Computational and Applied Mathematics (2003)

We introduce some Mordell curves of two different natures both of which are associated to cubic fields. One set of them consists of those elliptic curves whose rational points over the rational number field are described by or closely related to cubic fields. The other is a one-parameter family of Mordell curves which gives all (cyclic) cubic twists and all quadratic twists of the Fermat curve X3 + Y3 + Z3=0.
Construction and arithmetics of H-matrices
Authors: Lars Grasedyck, Wolfgang Hackbusch
Venue: Computing (2003)

In previous papers hierarchical matrices were introduced which are data-sparse and allow an approximate matrix arithmetic of nearly optimal complexity. In this paper we analyse the complexity (storage, addition, multiplication and inversion) of the hierarchical matrix arithmetics. Two criteria, the sparsity and idempotency, are sufficient to give the desired bounds. For standard finite element and boundary element applications we present a construction of the hierarchical matrix format for which we can give explicit bounds for the sparsity and idempotency.
A framework of individually-focused teleconferencing (IFT) via an efficient 3D reprojection technique
Authors: Qi Li, Chris Brown, Chandra Kambhamettu, Tao Li, Shenghuo Zhu
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

In this paper, we propose a framework on individually-focused teleconferencing (IFT) which is supported by an efficient 3D reprojection technique. The goal of designing IFT is to provide sufficient 3D pose information to each teleconference participant in order to establish lively communication in a teleconference on low-bandwidth internet. A novel IFT deployment and an efficient 3D reprojection technique are two major contributions of this paper. Our 3D reprojection technique uses a mirror reference view in three-view epipolar geometry. It overcomes the inefficiency in previous techniques and provides visually good recovery of pose information of teleconference participants even though it is theoretically an approximation scheme.
Pervasive Healthcare
Authors: Upkar Varshney
Venue: Computer (2003)

Wireless technologies can reduce medical costs and improve quality of service.
Visualizing 3D velocity fields near contour surfaces
Authors: Nelson Max, Roger Crawfis, Charles Grant
Venue: Proceedings of the conference on Visualization '94 (1994)

Vector field rendering is difficult in 3D because the vector icons overlap and hide each other. We propose four different techniques for visualizing vector fields only near surfaces. The first uses motion blurred particles in a thickened region around the surface. The second uses a voxel grid to contain integral curves of the vector field. The third uses many antialiased lines through the surface, and the fourth uses hairs sprouting from the surface and then bending in the direction of the vector field. All the methods use the graphics pipeline, allowing real time rotation and interaction, and the first two methods can animate the texture to move in the flow determined by the velocity field.