ppxscal/embedding_network huggingface dataset:
Is citation normalization realistic?
Authors: Ronald N. Kostoff Wendy L. Martinez
Venue: Journal of Information Science (2005)

One method for assessing quality of research outputs across different technical disciplines is comparing citations received by the research output documents. However, crossdiscipline citation comparison studies require discipline normalization, in order to eliminate discipline differences in cultural citation practices and discipline differences in the number of active researchers available to cite. The 'definition' of, and number of documents used to represent, a discipline become critical. This study attempted to determine whether the citation characteristics (average, median) of a discipline's domain stabilized as the domain's size was decreased. A sample of papers (classified asresearch articles only, not review articles, by the Institute for Scientific Information) published in the journalOncogene in 1999 was clustered hierarchically, and the citation averages and medians were computed for each cluster at different cluster hierarchical levels. The citation characteristics became increasingly stratified as the clusters were reduced in size, raising serious questions about the credibility of a selected denominator for normalization studies. An interesting side result occurred when all the retrieved articles were sorted by number of citations. Thirteen of the fifty most highly cited research articles had 100 or more references, whereas zero of the fifty least citedresearch articles had 100 or more references.
Machine Learning for Clinical Diagnosis from Functional Magnetic Resonance Imaging
Authors: Lei Zhang, Dimitris Samaras, Dardo Tomasi, Nora Volkow, Rita Goldstein
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01 (2005)

Functional Magnetic Resonance Imaging (fMRI) has enabled scientists to look into the active human brain. FMRI provides a sequence of 3D brain images with intensities representing brain activations. Standard techniques for fMRI analysis traditionally focused on finding the area of most significant brain activation for different sensations or activities. In this paper, we explore a new application of machine learning methods to a more challenging problem: classifying subjects into groups based on the observed 3D brain images when the subjects are performing the same task. Here we address the separation of drug-addicted subjects from healthy non-drug-using controls. In this paper, we explore a number of classification approaches. We introduce a novel algorithm that integrates side information into the use of boosting. Our algorithm clearly outperformed well-established classifiers as documented in extensive experimental results. This is the first time that machine learning techniques based on 3D brain images are applied to a clinical diagnosis that currently is only performed through patient self-report. Our tools can therefore provide information not addressed by traditional analysis methods and substantially improve diagnosis.
On Scheduling Complex Dags for Internet-Based Computing
Authors: Grzegorz Malewicz, Arnold L. Rosenberg, Matthew Yurkewych
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01 (2005)

Conceptual tools are developed to aid in crafting a theory of scheduling complex computation-dags for Internetbased computing. The goal of the schedules produced is to render tasks eligible for allocation to remote clients (hence for execution) at the maximum possible rate. This allows one to utilize remote clients well, and also lessen the likelihood of the "gridlock" that ensues when a computation stalls for lack of eligible tasks. Earlier work has introduced a formalism for studying this optimization problem and has identified optimal schedules for several significant families of structurally uniform dags. The current paper extends this work via a methodology for devising optimal schedules for a much broader class of complex dags. These dags are obtained via composition from a prespecified collection of simple building-block dags. The paper introduces a suite of algorithms that decompose a given dag to expose its building-blocks, and a priority relation on buildingblocks. When the building-blocks are appropriately interrelated, the dag can be scheduled optimally.
bYOB [Build Your Own Bag]: a computationally-enhanced modular textile system
Authors: Gauri Nanda, Adrian Cable, V. Michael Bove, Moneta Ho, Han Hoang
Venue: Proceedings of the 3rd international conference on Mobile and ubiquitous multimedia (2004)

We present bYOB (Build Your Own Bag), a flexible, computationally enhanced modular textile system from which to construct smart fabric objects. bYOB was motivated by a desire to transform everyday surfaces into ambient displays for information and to make building with fabric as easy as playing with Lego blocks. In the realm of personal architecture, bYOB is an interactive material that encourages users to explore and experiment by creating new objects to seamlessly integrate into their lives. The physical configuration of the object mediates its computational behavior. Therefore, an object built out of the system of modular elements understands its geometry and responds appropriately without any end-user programming. Our current prototype is a bag built out of the system that understands it is a bag when the handle is attached to the mesh of modules, responds by illuminating its fabric and inner contents when the sun goes down (Fig 1), communicates the presence of objects placed in the bag, and interacts with the user via speech. We describe how bYOB contributes to and differs from existing work in modular based systems and fabric interfaces. We discuss our development process in respect to physical, electronic, and conceptual design. We also describe salient features and future applications enabled by this new construction kit.
LOGE: a highly effective system for logic design automation
Authors: W. Grass, H. M. Lipp
Venue: ACM SIGDA Newsletter (1979)

Nearly all activities which have been published or which are known concentrate on those topics of computer-aided design related to layout of chips and boards and to testing and documentation. Systems which support logic design itself are not very widespread and are often out of focus. One of the inherent reasons may be that design engineers for whom CAD tools for logic design are developed, show a lot of scepticism and prejudice against those aids. They don't accept the idea that part of their personal work could be substituted by computer based algorithms.
Numerical computations: its nature and research directions
Authors: J. R. Rice, C. W. Gear, J. Ortega, B. Parlett, M. Schultz, L. F. Shampine, P. Wolfe, J. F. Traub
Venue: ACM SIGNUM Newsletter (1979)

This report on research in numerical computation is part of the Computer Science and Engineering Research Study (COSERS) which is aimed at technically educated people outside the Computer Science field. This goal led the panel to face many difficult choices between precise, but excessively technical, descriptions and looser, but more accessible expositions. The panel hopes that all readers will keep this in mind.
Managing Pan-European Mammography Images and Data Using a Service Oriented Architecture
Authors: S. R. Amendolia, F. Estrella, R. McClatchey, D. Rogulin, T. Solomonides
Venue: Proceedings of the IDEAS Workshop on Medical Information Systems: The Digital Hospital (2004)

Medical conditions such as breast cancer, and mammograms as images, are extremely complex with many degrees of variability across the population. An effective solution for the management of disparate mammogram data sources that provides sufficient statistics for complex epidemiological study is a federation of autonomous multi-centre sites which transcends national boundaries. Grid-based technologies are emerging as open-source standards-based solutions for managing and collaborating distributed resources. In the light of these new computing solutions, the MammoGrid project, as one example of a HealthGrid, is developing a Grid-aware medical application which manages a European-wide database of mammograms. The MammoGrid solution utilizes the Grid technologies in seamlessly integrating distributed data sets and is investigating the potential of the Grid to support effective co-working among mammogram analysts throughout the EU.
Fault Tolerance Design in JPEG 2000 Image Compression System
Authors: Cung Nguyen, G. Robert Redinbo
Venue: IEEE Transactions on Dependable and Secure Computing (2005)

The JPEG 2000 image compression standard is designed for a broad range of data compression applications. The new standard is based on wavelet technology and layered coding in order to provide a rich feature compressed image stream. The implementations of the JPEG 2000 codec are susceptible to computer-induced soft errors. One situation requiring fault tolerance is remote-sensing satellites, where high energy particles and radiation produce single event upsets corrupting the highly susceptible data compression operations. This paper develops fault tolerance error-detecting capabilities for the major subsysyems that constitute a JPEG 2000 standard. The nature of the subsystem dictates the realistic fault model where some parts have numerical error impacts whereas others are properly modeled using bit-level variables. The critical operations of subunits such as Discrete Wavelet Transform (DWT) and quantization are protected against numerical errors. Concurrent error detection techniques are applied to accommodate the data type and numerical operations in each processing unit. On the other hand, the Embedded Block Coding with Optimal Truncation (EBCOT) system and the bitstream formation unit are protected against soft-error effects using binary decision variables and cyclic redundancy check (CRC) parity values, respectively. The techniques achieve excellent error-detecting capability at only a slight increase in complexity. The design strategies have been tested using Matlab programs and simulation results are presented.
Optimizing Multiple Seeds for Protein Homology Search
Authors: Daniel G. Brown
Venue: IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) (2005)

We present a framework for improving local protein alignment algorithms. Specifically, we discuss how to extend local protein aligners to use a collection of vector seeds or ungapped alignment seeds to reduce noise hits. We model picking a set of seed models as an integer programming problem and give algorithms to choose such a set of seeds. While the problem is NP-hard, and Quasi-NP-hard to approximate to within a logarithmic factor, it can be solved easily in practice. A good set of seeds we have chosen allows four to five times fewer false positive hits, while preserving essentially identical sensitivity as BLASTP.
Artistic rendering to represent quality of information
Authors: Katharine H. Wray
Venue: Journal of Computing Sciences in Colleges (2005)

The representation of information quality, also known as "verity visualization," can be explained as a judgment of the accuracy of specific information in a dataset relative to the whole. The visualization of information quality is an important factor in data comparison situations, or even to simply "highlight" regions of low quality information for further study. Depending on the scenario, the quality of the information could be related to the accuracy of the tools being used to gather the information, how recently the information was collected, etc. and, in general, the reliability of the source.
Distributed/Heterogeneous Query Processing in Microsoft SQL Server
Authors: Jose A. Blakeley, Conor Cunningham, Nigel Ellis, Balaji Rathakrishnan, Ming-Chuan Wu
Venue: Proceedings of the 21st International Conference on Data Engineering (2005)

This paper presents an architecture overview of the distributed, heterogeneous query processor (DHQP) in the Microsoft SQL Server database system to enable queries over a large collection of diverse data sources. The paper highlights three salient aspects of the architecture. First, the system introduces well-defined abstractions such as connections, commands, and rowsets that enable sources to plug into the system. These abstractions are formalized by the OLE DB data access interfaces. The generality of OLE DB and its broad industry adoption enables our system to reach a very large collection of diverse data sources ranging from personal productivity tools, to database management systems, to file system data. Second, the DHQP is built-in to the relational optimizer and execution engine of the system. This enables DH queries and updates to benefit from the cost-based algebraic transformations and execution strategies available in the system. Finally, the architecture is inherently extensible to support new data sources as they emerge as well as serves as a key extensibility point for the relational engine to add new features such as full-text search and distributed partitioned views.
VLSI Implementation of new arithmetic residue to binary decoders
Authors: Ahmad A. Hiasat
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2005)

This paper introduces two arithmetic decoders that decode the residue number system into its binary equivalent. The first one deals with the moduli set: (2n, 2n - 1, 2n + 1, 2n - 2(n + 1/2) + 1, 2n + 2(n + 1/2) + 1), while the other deals with the moduli set: (2n + 1, 2n - 1, 2n + 1, 2n - 2(n + 1/2) + 1, 2n + 2(n + 1/2) + 1), where n is odd. Compact forms for the multiplicative inverse of each modulus is introduced, which facilitates the implementation of these arithmetic decoders. The proposed hardware realizations for these decoders are based on using six carry save adders and one carry propagate adder. The hardware and time requirements of these decoders are much better than other similar decoders found in literature. A sub-micron silicon implementation for the decoder has been performed and reported.
Scalable density-based distributed clustering
Authors: Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
Venue: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (2004)

Clustering has become an increasingly important task in analysing huge amounts of data. Traditional applications require that all data has to be located at the site where it is scrutinized. Nowadays, large amounts of heterogeneous, complex data reside on different, independently working computers which are connected to each other via local or wide area networks. In this paper, we propose a scalable density-based distributed clustering algorithm which allows a user-defined trade-off between clustering quality and the number of transmitted objects from the different local sites to a global server site. Our approach consists of the following steps: First, we order all objects located at a local site according to a quality criterion reflecting their suitability to serve as local representatives. Then we send the best of these representatives to a server site where they are clustered with a slightly enhanced density-based clustering algorithm. This approach is very efficient, because the local detemination of suitable representatives can be carried out quickly and independently from each other. Furthermore, based on the scalable number of the most suitable local representatives, the global clustering can be done very effectively and efficiently. In our experimental evaluation, we will show that our new scalable density-based distributed clustering approach results in high quality clusterings with scalable transmission cost.
Energy macromodeling of embedded operating systems
Authors: T. K. Tan, A. Raghunathan, N. K. Jha
Venue: ACM Transactions on Embedded Computing Systems (TECS) (2005)

As embedded systems get more complex, deployment of embedded operating systems (OSs) as software run-time engines has become common. In particular, this trend is true even for battery-powered embedded systems, where maximizing battery life is a primary concern. In such OS-driven embedded software, the overall energy consumption depends very much on which OS is used and how the OS is used. Therefore, the energy effects of the OS need to be studied in order to design low-energy systems effectively.In this paper, we discuss the motivation for performing OS energy characterization and propose a methodology to perform the characterization systematically. The methodology consists of two parts. The first part is analysis, which is concerned with identifying a set of components that can be used to characterize the OS energy consumption, called energy characteristics. The second part is macromodeling, which is concerned with obtaining quantitative macromodels for the energy characteristics. It involves the process of experiment design, data collection, and macromodel fitting. The OS energy macromodels can be used conveniently as OS energy estimators in high-level or architectural optimization of embedded systems for low-energy consumption.As far as we know, this work is the first attempt to systematically tackle energy macromodeling of an embedded OS. To demonstrate our approach, we present experimental results for two well-known embedded OSs, namely, &mu;C/OS and embedded Linux OS.
WEBCAP: a capacity planning tool for web resource management
Authors: Sami Habib, Maytham Safar
Venue: Special interest tracks and posters of the 14th international conference on World Wide Web (2005)

A staggering number of multimedia applications are being introduced every day. Yet, the inordinate delays encountered in retrieving multimedia documents make it difficult to use the Web for real-time applications such as educational broadcasting, video conferencing, and multimedia streaming. The problem of delivering multimedia documents in time while placing the least demands on the client, network and server resources is a challenging optimization problem. The WEBCAP is ongoing project that explores applying capacity planning techniques to manage or tune the Web resources (client, network, server) for optimal or near optimal performance, subject to minimizing the retrieval cost while satisfying the real-time constraints and available resources. The WEBCAP project consists of four software modules: object extractor, object representer, object scheduler, and system tuner. The four modules are connected serially with 3 feedback-loops. In this paper, we focus on how to extract objects from multimedia document and how to represent them as object and operation flow graphs while maintaining precedence relations among the objects.
A higher-order velocity post-processing for the Helmholtz equation
Authors: Rivânia H. Paulino, Fernando Alves Rochinha
Venue: Finite Elements in Analysis and Design (2005)

A macroelement post-processing recovery technique of the velocity field based on residuals of the equilibrium equation and irrotational conditions for the Helmholtz equation is proposed. The derivatives are recovered by solving local variational problems, that are based on the residuals aforementioned and involve superconvergent derivatives of the acoustical pressure field on special points. Improved accuracy for derivative finite element approximation is obtained with low computational cost and easy implementation. A number of comprehensive simulations is presented in order to show the main features of the proposed methodology.
Simulating Chinese brush painting: a geometric model
Authors: Ross Girshick
Venue: Journal of Computing Sciences in Colleges (2004)

Three distinct problems arise in the attempt to simulate Chinese brush painting: modeling ink and water diffusion in paper, modeling soft brush dynamics, and creating a brush stroke input method. Recent research [1] demonstrates that attention to the problems of brush modeling more effectively captures the style of Chinese brush painting. Until recently, however, nearly all research has focused exclusively on the problem of diffusion.
Implicit, view invariant, linear flexible shape modelling
Authors: Bernard F. Buxton, M. Benjamin Dias
Venue: Pattern Recognition Letters (2005)

Flexible shape modelling in which the image of an object is represented by a finite set of landmark points is briefly reviewed. It is argued that variation in the apparent size and shape of the image of an object with change of viewpoint are extrinsic variations and that, under weak or para-perspective imaging, such changes should be taken into account by using the affine trifocal tensor to provide a mapping between image triplets. It is shown how the Procrustes error may be extended to accommodate such mappings, how the remaining intrinsic variations may be extracted, a pair of virtual basis views derived, and a statistical model constructed. An Integrated Shape and Pose Model (ISPM) that integrates a hierarchical principal components analysis model with a multi-view geometry model, was constructed and shown, on data from a small database of face images, to outperform previous models.
A novel compact piecewise-linear representation: Research Articles
Authors: Chengtao Wen, Shuning Wang, Hao Zhang, Muhammadnaid Junaid Khan
Venue: International Journal of Circuit Theory and Applications (2005)

A new compact MAX representation for 2-D continuous piecewise-linear (PWL) functions is developed in this paper. The representation is promising since it can be easily generalized into higher dimensions. We also establish the explicit functional form of basis function and demonstrate that the proposed basis function is the elementary &lsquo;building block&rsquo; from which a fully general 2-D PWL function can be constructed. In addition, we reveal the relationship of basis function with minimal degenerate intersection and Hinging Hyperplane, which shows that the MAX model can unify Chua's canonical expression, Li's representation, lattice PWL function and Bremann's Hinging Finding Algorithm into one common theoretical framework. Copyright &copy; 2005 John Wiley & Sons, Ltd.Project jointly supported by National Natural Science Foundation of China(60374061) and 973 program of China (2002CB312200).
A new method of estimating wavelet with desired features from a given signal
Authors: Anubha Gupta, Shiv Dutt Joshi, Surender Prasad
Venue: Signal Processing (2005)

This paper proposes a new method of estimating both biorthogonal compactly supported as well as semi-orthogonal infinitely/compactly supported wavelet from a given signal. The method is based on maximizing projection of the given signal onto successive scaling subspace. This results in minimization of energy of signal in the wavelet subspace. The idea used to estimate analysis wavelet filter is similar to a sharpening filter used in image enhancement. First, a new method is proposed that helps in the design of 2-band FIR biorthogonal perfect reconstruction filter bank from a given signal. This leads to the design of biorthogonal compactly supported wavelet. It is also shown that a wavelet with desired support as well as desired number of vanishing moments can be designed with the proposed method. Next, a method is proposed to design semi-orthogonal wavelets that are usually infinitely supported wavelets. Here, corresponding to FIR analysis filters, the resulting synthesis filters are IIR filters that satisfy the property of perfect reconstruction.
A training software tool for square root calculation
Authors: Anelia Vasileva, Angel Smrikarov, Teodora Toteva
Venue: Proceedings of the 5th international conference on Computer systems and technologies (2004)

The paper justifies the necessity to introduce the students from the 'Computer Systems and Technologies' degree course to algorithms, used for square root calculation in computers. Two of the most widely used iterative algorithms for fixed and floating point numbers square root approximation are discussed and the steps of development of the training environment are described.