ppxscal/embedding_network huggingface dataset:
Spectral radial basis functions for full sphere computations
Authors: Philip W. Livermore, Chris A. Jones, Steven J. Worland
Venue: Journal of Computational Physics (2007)

The singularity of cylindrical or spherical coordinate systems at the origin imposes certain regularity conditions on the spectral expansion of any infinitely differentiable function. There are two efficient choices of a set of radial basis functions suitable for discretising the solution of a partial differential equation posed in either such geometry. One choice is methods based on standard Chebyshev polynomials; although these may be efficiently computed using fast transforms, differentiability to all orders of the obtained solution at the origin is not guaranteed. The second is the so-called one-sided Jacobi polynomials that explicitly satisfy the required behavioural conditions. In this paper, we compare these two approaches in their accuracy, differentiability and computational speed. We find that the most accurate and concise representation is in terms of one-sided Jacobi polynomials. However, due to the lack of a competitive fast transform, Chebyshev methods may be a better choice for some computationally intensive timestepping problems and indeed will yield sufficiently (although not infinitely) differentiable solutions provided they are adequately converged.
Research and Design of an Attribute-managed Storage-cluster Based on TCP/IP Network
Authors: QinQi Wei, ChangSheng Xie, Xu Li, Qiang Cao
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

With the growing scale of storage system, its requirements of performance, reliability, availability, and security are getting more and more complicated. The costs to manage storage systems will keep increasing and finally be higher than the systems themselves if this trend continues. Thus, Intelligent and self-managing systems are required to automatically address the needs of these requirements. The proposed attribute-managed method in this paper describes and classifies the requirements of storage system with attributes, relating the attributes with certain access and storage strategies. Data are accessed and stored with the most appropriate strategies according to attributes pertaining to them. We finally present a prototype of an attribute-managed storage-cluster based on TCP/IP network with extensions to existing protocols and discuss the implementation structure in detail as part of this research.
A combined PMHT and IMM approach to multiple-point target tracking in infrared image sequence
Authors: Mukesh A. Zaveri, S. N. Merchant, Uday B. Desai
Venue: Journal on Image and Video Processing (2007)

Data association and model selection are important factors for tracking multiple targets in a dense clutter environment. In this paper, we provide an effective solution to the tracking of multiple single-pixel maneuvering targets in a sequence of infrared images by developing an algorithm that combines a sequential probabilistic multiple hypothesis tracking (PMHT) and interacting multiple model (IMM). We explicitly model maneuver as a change in the target's motion model and demonstrate its effectiveness in our tracking application discussed in this paper. We show that inclusion of IMM enables tracking of any arbitrary trajectory in a sequence of infrared images without any a priori special information about the target dynamics. IMM allows us to incorporate different dynamic models for the targets and PMHT helps to avoid the uncertainty about the observation origin. It operates in an iterative mode using expectation-maximization (EM) algorithm. The proposed algorithm uses observation association as missing data.
CLIPPER: Counter-based Low Impact Processor Power Estimation at Run-time
Authors: J. Peddersen, S. Parameswaran
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

Numerous dynamic power management techniques have been proposed which utilize the knowledge of processor power/energy consumption at run-time. So far, no efficient method to provide run-time power/energy data has been presented. Current measurement systems draw too much power to be used in small embedded designs and existing performance counters can not provide sufficient information for run-time optimization. This paper presents a novel methodology to solve the problem of run-time power optimization by designing a processor that estimates its own power/energy consumption. Estimation is performed by the addition of small counters that tally events which consume power. This methodology has been applied to an existing processor resulting in an average power error of 2% and energy estimation error of 1.5%. The system adds little impact to the design, with only a 4.9% increase in chip area and a 3% increase in average power consumption. A case study of an application that utilizes the processor showcases the benefits the methodology enables in dynamic power optimization.
Issue of Event Sequence in time of Distributed Intrusion Detection System
Authors: Lin Guoyuan, Huang Hao, Cao Tianjie
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Distributed Intrusion Detection System (DIDS) is one of important devices for information security. In this field, how to improve detection rate is one of key issues. In this paper, the importance of event sequence in time is presented. Then, we discuss three factors, i.e. timestamp precision, time synchronization and network delay, which effect detection rate on the view of event sequence in time. On the three aspects, timestamp precision is the key to keep internal event sequence, time synchronization is the base of correcting event sequence among computers, and that network delay makes time-series analysis not true. Accordingly, we address some methods, i.e. raising timestamp precision, active selfadapting time synchronization algorithm and state turnabout mechanism. Experiments indicate that anyone of three measures can elevate detection performance to a certain extent. If they all are adopted, better detection results are revealed.
A Formal Model of Crash Recovery in a Distributed System
Authors: D. Skeen
Venue: IEEE Transactions on Software Engineering (1983)

A formal model for atomic commit protocols for a distributed database system is introduced. The model is used to prove existence results about resilient protocols for site failures that do not partition the network and then for partitioned networks. For site failures, a pessimistic recovery technique, called independent recovery, is introduced and the class of failures for which resilient protocols exist is identified. For partitioned networks, two cases are studied: the pessimistic case in which messages are lost, and the optimistic case in which no messages are lost. In all cases, fundamental limitations on the resiliency of protocols are derived.
Testing RF Components with Supply Current Signatures
Authors: S. Sermet Akbay, Shreyas Sen, Abhijit Chatterjee
Venue: Proceedings of the 16th Asian Test Symposium (2007)

We propose a technique for low-cost testing of radio-frequency components integrating current signatures and alternate test methodology. The technique is suitable for non-invasive built-in test as well as low-cost automated test equipment (ATE) applications. Main features of the technique are (1) minimum loading on signal path by sampling supply current, (2) flexible test stimulus generation based on system constraints, (3) test time reduction by using a single test stimulus and data acquisition, and (4) accurate prediction of all specification values from the single excitation. Two experiments using the proposed implementation demonstrate the accuracy and efficiency of the technique on both single-balanced and double-balanced mixers built with two different technologies.
Industrial Computer Vision in Japan
Authors: M. Yachida
Venue: Computer (1980)

Japanese research in pattern analysis and machine intelligence has focused on industrial applications. A number of successful computer vision systems are now employed in Japanese manufacturing.
Topological Landscapes: A Terrain Metaphor for Scientific Data
Authors: Gunther Weber, Peer-Timo Bremer, Valerio Pascucci
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

Scientific visualization and illustration tools are designed to help people understand the structure and complexity of scientific data with images that are as informative and intuitive as possible. In this context the use of metaphors plays an important role since they make complex information easily accessible by using commonly known concepts. In this paper we propose a new metaphor, called &#x201C;Topological Landscapes,&#x201D; which facilitates understanding the topological structure of scalar functions. The basic idea is to construct a terrain with the same topology as a given dataset and to display the terrain as an easily understood representation of the actual input data. In this projection from an $n$-dimensional scalar function to a two-dimensional (2D) model we preserve function values of critical points, the persistence (function span) of topological features, and one possible additional metric property (in our examples volume). By displaying this topologically equivalent landscape together with the original data we harness the natural human proficiency in understanding terrain topography and make complex topological information easily accessible.
Human Image Preference and Document Degradation Models
Authors: C. Hale, E. Barney-Smith
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

Because most degraded documents are created by people, the preferences individuals have in relation to degraded documents are quite important. Their preferences may determine whether or not the documents they created are appropriate for machines. The goal of this study was to find relationships between preference and several parame- ters of a scanner degradation model. It was found that the difference in binarization threshold and the difference in edge displacement caused by the degradation both had strong linear relationships to preference. The width of the point spread function did not show such a relationship. These relationships were counterintuitive because degraded characters with thicker stroke widths than the original were preferred to those that had stroke widths closer to the original character.
A New Method for Detection of Active Brain Regions with Event-Related fMRI Time Series Analysis
Authors: Juliano J. Duque, Marcio J. Sturzbecher, Draulio B. Araujo, Joaquim C. Felipe
Venue: Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing (2007)

Functional magnetic resonance imaging (fMRI) has been applied with several purposes in clinical environment as well as in basic neuroscience studies. The main purpose of fMRI is to map brain activity, which is achieved by applying statistical methods to time series of each voxel intensity, related to changes in blood oxygen level, in response to a short stimulus. In this work, we propose a new method for the analysis of event-related fMRI based in the use of the Dynamic Time Warping technique to compare pixel intensity time series. The results show the ability to discriminate activated brain regions, when subjects were engaged in a motor task.
Evaluation of the CFA Test Programs Via Formal Computer Descriptions
Authors: M. R. Barbacci
Venue: Computer (1977)

This article describes an architectural research facility used for the comparison of computer architectures. The facility consists of a compiler, simulator, symbolic translator, and data analysis programs.
CoViCAD: Comprehensive Visualization of Coronary Artery Disease
Authors: Maurice Termeer Javier Oliván Bescós Marcel Breeuwer Anna Vilanova, Frans Gerritsen Eduard Gröller
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We present novel, comprehensive visualization techniques for the diagnosis of patients with Coronary Artery Disease using segmented cardiac MRI data. We extent an accepted medical visualization technique called the bull's eye plot by removing discontinuities, preserving the volumetric nature of the left ventricular wall and adding anatomical context. The resulting volumetric bull's eye plot can be used for the assessment of transmurality. We link these visualizations to a 3D view that presents viability information in a detailed anatomical context. We combine multiple MRI scans (whole heart anatomical data, late enhancement data) and multiple segmentations (polygonal heart model, late enhancement contours, coronary artery tree). By selectively combining different rendering techniques we obtain comprehensive yet intuitive visualizations of the various data sources.
Modeling and Verification of TTCAN Startup Protocol Using Synchronous Calendar
Authors: Indranil Saha, Suman Roy, Kuntal Chakraborty
Venue: Proceedings of the Fifth IEEE International Conference on Software Engineering and Formal Methods (2007)

We describe the modeling and verification of TTCAN startup protocol using SAL model checker. For the modeling purposes we propose a new modeling framework called Synchronous Calendar which can be seen as an adaptation of Calendar based models introduced by Duterte and Sorea. A Synchronous Calendar can express dense time systems without relying on continuously varying clocks and supports synchronous message transmission. We capture both fault-free and faulttolerant aspects of startup algorithm of TTCAN in two different models and verify the safety and liveness properties for them. Our verification technique relies on induction and abstraction methods which are supported by SAL model checker. To our knowledge this is the first work towards a formal analysis of TTCAN startup protocol.
Conference Report: Hierarchical Design Stressed at Design Automation Conference
Authors: J. P. Gray
Venue: Computer (1978)

Until recently the general attitude of engineers to design automation was confused-they questioned its value yet deplored its limited availability. To increase the amount of DA knowledge in the public domain, the 15th in the series of Annual Design Automation Conferences was held June 19-21 at Caesar's Palace, Las Vegas. Due either to this enlightened choice of venue or to spreading paranoia over handling VLSI designs, this year's conference was extremely well attended-650 delegates, an increase of 50 percent over last year. However, for those expecting ing to learn of new tools for survival in technologies governed by Moore's Laws, this conference may have been somewhat disappointing. It was largely more of the same-PWB layout, testing, IC layout, design languages, logic design, simulation, CAM, and graphics. 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
Microcomputer Peripherals Status and Trends
Authors: Andrew Allison
Venue: IEEE Micro (1984)

The mass storage and input/output needs of microcomputer systems are driving the development of a broad range of peripheral products. Fortunately, no one technology is lagging?the capabilities of all peripherals are advancing at compatible rates. 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
Application of GARCH Model in the Forecasting of Day-Ahead Electricity Prices
Authors: Chengjun Li, Ming Zhang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In the new deregulated electric power industry, price forecasting is becoming increasingly important for the producers and consumers to estimate and maximize their profits. A generalized autoregressive conditional heteroskedastic (GARCH) methodology is presented to predict day-ahead electricity prices. For the high volatility of the electricity prices, the GARCH model is more suitable for illustrating the time series data than other forecast model adopted generally. The prediction error is assumed to be serially correlated other than independent variable with zero mean and constant variance, which can be modeled by an Auto Regressive process. Based on the initial values of the parameters of the model gained by Eviews software, Genetic arithmetic is used to optimize them to improve its performance. A detailed explanation of GARCH models is presented and empirical results from the California deregulated electricity-markets are discussed.
Trends in data warehousing: a practitioner's view
Authors: William O'Connell
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

This talk will present emerging data warehousing reference architectures, and focus on trends and directions that are shaping these enterprise installations. Implications will be highlighted, including both of new and old technology. Stack seamless integration is also pivotal to success, which also has significant implications on things such as Metadata.
High-Level Semantic Based Image Characterization Using Artificial Neural Networks
Authors: Eduardo Ferreira Ribeiro, Celia Aparecida Zorzo Barcelos, Marcos Aurelio Batista
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

Low-level attributes such as color, shape and texture generally fail in describing the high-level semantic con- cepts. This work presents, through the formation of a high- level characteristics vector, the representation of the sub- jective knowledge used by humans for the verification of which aspects are most important for image characteriza- tion. Such vector will be formed by using the Artificial In- telligence techniques, more specifically the Artificial Neu- ral Networks, which will generate, through predefined ex- amples, the low-level characteristics forming the new high- level vector, making image retrieval possible. Finally, some tests results are presented and discussed to demonstrate the potentiality of the method.
A survey of cryptographic primitives and implementations for hardware-constrained sensor network nodes
Authors: Rodrigo Roman, Cristina Alcaraz, Javier Lopez
Venue: Mobile Networks and Applications (2007)

In a wireless sensor network environment, a sensor node is extremely constrained in terms of hardware due to factors such as maximizing lifetime and minimizing physical size and overall cost. Nevertheless, these nodes must be able to run cryptographic operations based on primitives such as hash functions, symmetric encryption and public key cryptography in order to allow the creation of secure services. Our objective in this paper is to survey how the existing research-based and commercial-based sensor nodes are suitable for this purpose, analyzing how the hardware can influence the provision of the primitives and how software implementations tackles the task of implementing instances of those primitives. As a result, it will be possible to evaluate the influence of provision of security in the protocols and applications/scenarios where sensors can be used.
A Genetic Neural Network for Predicting Materials Mechanical Properties
Authors: Jianlin Xu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

A genetic neural network model for predicting materials mechanical properties is set up in the paper. The network mode has some advantage of its globe optimal searching and quick convergence speed, which can reduce experimentation times and short exploitation circle in researching materials. The fundamental of predicting materials mechanical properties, method of establishing the model and training of genetic network are discussed particulars in the paper. Simulating and analyzing results show that the network model can effectual predict materials mechanical properties, analyze influence tendency of parameters to mechanical properties. It has great instructing function for material research.
Effective protocols for kNN search on broadcast multi-dimensional index trees
Authors: Chuan-Ming Liu, Shu-Yu Fu
Venue: Information Systems (2008)

In a wireless mobile environment, data broadcasting provides an efficient way to disseminate data. Via data broadcasting, a server can provide location-based services to a large client population in a wireless environment. Among different location-based services, the k nearest neighbors (kNN) search is important and is used to find the k closest objects to a given point. However, the kNN search in a broadcast environment is particularly challenging due to the sequential access to the data on a broadcast channel. We propose efficient protocols for the kNN search on a broadcast R-tree, which is a popular multi-dimensional index tree, in a wireless broadcast environment in terms of latency and tuning time as well as memory usage. We investigate how a server schedules the broadcast and provide the corresponding kNN search algorithms at the mobile clients. One of our kNN search protocols further allows a kNN search to start at an arbitrary time instance and it can skip the waiting time for the beginning of a broadcast cycle, thereby reducing the latency. The experimental results validate that our mechanisms achieve the objectives.
A dimensionality reduction technique for efficient time series similarity analysis
Authors: Qiang Wang, Vasileios Megalooikonomou
Venue: Information Systems (2008)

We propose a dimensionality reduction technique for time series analysis that significantly improves the efficiency and accuracy of similarity searches. In contrast to piecewise constant approximation (PCA) techniques that approximate each time series with constant value segments, the proposed method-piecewise vector quantized approximation-uses the closest (based on a distance measure) codeword from a codebook of key-sequences to represent each segment. The new representation is symbolic and it allows for the application of text-based retrieval techniques into time series similarity analysis. Experiments on real and simulated datasets show that the proposed technique generally outperforms PCA techniques in clustering and similarity searches.
Change Distilling: Tree Differencing for Fine-Grained Source Code Change Extraction
Authors: Beat Fluri, Michael Wuersch, Martin PInzger, Harald Gall
Venue: IEEE Transactions on Software Engineering (2007)

A key issue in software evolution analysis is the identification of particular changes that occur across several versions of a program. We present change distilling, a tree differencing algorithm for fine-grained source code change extraction. For that, we have improved the existing algorithm of Chawathe et al. for extracting changes in hierarchically structured data. Our algorithm detects changes by finding a match between nodes of the compared two abstract syntax trees and a minimum edit script. We can identify change types between program versions according to our taxonomy of source code changes. We evaluated our change distilling algorithm with a benchmark we developed that consists of 1,064 manually classified changes in 219 revisions from three different open source projects. We achieved significant improvements in extracting types of source code changes: our algorithm approximates the minimum edit script by 45% better than the original change extraction approach by Chawathe et al. We are able to find all occurring changes and almost reach the minimum conforming edit script, i.e., we reach a mean absolute percentage error of 34%, compared to 79% reached by the original algorithm. The paper describes both the change distilling and the results of our evaluation.