ppxscal/embedding_network huggingface dataset:
The Blackford Northbridge Chipset for the Intel 5000
Authors: Sivakumar Radhakrishnan, Sundaram Chinthamani, Kai Cheng
Venue: IEEE Micro (2007)

The Intel 5000 is a shared-memory, symmetric dual-processor system based on the energy-efficient, high-performance Intel Core 2 dual- and quad-core processors. A key component is the northbridge, which interconnects processor, memory, and I/O interfaces. The Blackford northbridge chipset provides multicore processor support and platform-level features and technologies. Its critical microarchitectural improvements offer significant performance advantages.
Integrated Generic Association Rule Based Classifier
Authors: Ines Bouzouita, Samir Elloumi
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

Associative classification is a supervised classification method. Many experimental studies have shown that associative classification is a promising approach. There are several associative classification approaches. However, the latter suffer from a major drawback: the huge number of the generated classification rules which takes efforts to select the best ones in order to construct the classifier. To overcome such drawback, we propose in this paper a new direct associative classification method called IGARC, an improvement of GARC approach, that extracts directly generic associative classification rules from a training set in order to reduce the number of associative classification rules without jeopardizing the classification accuracy. A detailed description of this method is presented, as well as the experimentation study on 12 benchmark data sets proving that IGARC is highly competitive in terms of accuracy in comparison with popular classification approaches.
End-user privacy in human-computer interaction
Authors: Giovanni Iachello, Jason Hong
Venue: Foundations and Trends in Human-Computer Interaction (2007)

The purpose of this article is twofold. First, we summarize research on the topic of privacy in Human-Computer Interaction (HCI), outlining current approaches, results, and trends. Practitioners and researchers can draw upon this review when working on topics related to privacy in the context of HCI and CSCW. The second purpose is that of charting future research trends and of pointing out areas of research that are timely but lagging. This work is based on a comprehensive analysis of published academic and industrial literature spanning three decades, and on the experience of both ourselves and of many of our colleagues.
Note: A note on occurrence of gapped patterns in i.i.d. sequences
Authors: Vladimir Pozdnyakov
Venue: Discrete Applied Mathematics (2008)

A new martingale technique is developed to find formulas for the expected value and generating function of the waiting time until one observes a gapped pattern (or a structured motif) in an i.i.d. sequence of random letters from a finite alphabet.
Retargeting Images and Video for Preserving Information Saliency
Authors: Vidya Setlur, Tom Lechner, Marc Nienhaus, Bruce Gooch
Venue: IEEE Computer Graphics and Applications (2007)

A nonphotorealistic algorithm for retargeting images adapts large images so that important objects in the image are still recognizable when displayed at a lower target resolution. Unlike existing image manipulation techniques such as cropping and scaling, the retargeting algorithm can handle multiple important objects in an image. The authors' approach constructs a topologically constrained epitome of an image based on a visual attention model that is both comprehensible and size varying, making the method suitable for display-critical applications. They extend this algorithm to other types of imagery such as medical data.
Approximation techniques for the transformation of fuzzy sets into random sets
Authors: Mihai Cristian Florea, Anne-Laure Jousselme, Dominic Grenier, Éloi Bossé
Venue: Fuzzy Sets and Systems (2008)

With the recent rising of numerous theories for dealing with uncertain pieces of information, the problem of connection between different frames has become an issue. In particular, questions such as how to combine fuzzy sets with belief functions or probability measures often emerge. The alternative is either to define transformations between theories, or to use a general or unified framework in which all these theories can be framed. Random set theory has been proposed as such a unified framework in which at least probability theory, evidence theory, possibility theory and fuzzy set theory can be represented. Whereas the transformations of belief functions or probability distributions into random sets are trivial, the transformations of fuzzy sets or possibility distributions into random sets lead to some issues. This paper is concerned with the transformation of fuzzy membership functions into random sets. In practice, this transformation involves the creation of a large number of focal elements (subsets with non-null probability) based on the @a-cuts of the fuzzy membership functions. In order to keep a computationally tractable fusion process, the large number of focal elements needs to be reduced by approximation techniques. In this paper, we propose three approximation techniques and compare them to classical approximations techniques used in evidence theory. The quality of the approximations is quantified using a distance between two random sets.
Application Briefs
Venue: IEEE Computer Graphics and Applications (1982)

Large-area AC gas discharge panels have been produced as part of a joint venture of Magnavox and Photonics. 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
IEEE P1014?A Standard for the High-Performance VME Bus
Authors: Wayne Fischer
Venue: IEEE Micro (1985)

The popular VME bus allows high-speed interaction between 8-, 16-, and 32-bit microprocessors. This proposed standard outlines a flexible, asynchronous design capable of accommodating a full 32-bit address and data path. 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
Research on Threshold Denoising of FPRGA
Authors: MingYi Cui, XinXiang Zhang, HuiChao Mi
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

Genetic algorithm (GA) was widely used to engineering and optimization fields. The performance of GA and extension of its application fields were affected by the limitation of its code. Floating point representation (FPR) is super to other codes in function and constraint optimization fields. Noise was brought by the FPR in selection and crossover operation, its influence to the performance of GA was not noticed by researchers. In this paper, the property of the noise in FPR is mostly analyzed in inherit operation. The mechanism of denoising in FPR is researched with wavelet threshold coefficient. Denoising is implemented by mutation. That wavelet theory used in floating point representation genetic algorithm (FPRGA) is credible for reducing noise level, the method is feasible, is indicated by its results of research and experiment.
Geodesic Bezier Curves: a Tool for Modeling on Triangulations
Authors: Dimas Martinez Morera, Paulo Cezar Carvalho, Luiz Velho
Venue: Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing (2007)

We define a new class of curves, called geodesic Bezier curves, that are suitable for modeling on manifold triangulations. As a natural generalization of Bezier curves, the new curves are as smooth as possible. We discuss the construction of C^0 and C^1 piecewise Bezier splines. We also describe how to perform editing operations, such as trimming, using these curves. Special care is taken to achieve interactive rates for modeling tasks.
Billing attacks on SIP-based VoIP systems
Authors: Ruishan Zhang, Xinyuan Wang, Xiaohui Yang, Xuxian Jiang
Venue: Proceedings of the first USENIX workshop on Offensive Technologies (2007)

Billing is fundamental to any commercial VoIP services and it has direct impact on each individual VoIP subscriber. One of the most basic requirements of any VoIP billing function is that it must be reliable and trustworthy. From the VoIP subscriber's perspective, VoIP billing should only charge them for the calls they have really made and for the duration they have called. Existing VoIP billing is based on VoIP signaling. Therefore, any vulnerability in VoIP signaling is a potential vulnerability of VoIP billing. In this paper, we examine how the vulnerabilities of SIP can be exploited to compromise the reliability and trustworthiness of the billing of SIP-based VoIP systems. Specifically, we focus on the billing attacks that will create inconsistencies between what the VoIP subscribers received and what the VoIP service providers have provided. We present four billing attacks on VoIP subscribers that could result in charges on the calls the subscribers have not made or overcharges on the VoIP calls the subscribers have made. Our experiments show that Vonage and AT&T VoIP subscribers are vulnerable to these billing attacks.
What is it thinking?: game AI opponent computer-human interaction using descriptive schema and explanatory capabilities
Authors: Andrew Chiou
Venue: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts (2007)

In strategy-based games, it is sometimes beneficial to understand the evaluation processes of the game AI opponent, e.g. What strategic or tactical motives is it inferring? Why did it make the previous move? However, the mechanics available to allow the game AI to convey these processes to the [human] player or game designer is complex to implement, more so than the actual mechanics of the game AI itself. This paper proposes a method that provides the mechanism for a game AI to communicate its evaluation processes using descriptive schemata and explanatory functions. A case study will be presented that includes an implementation of a game AI opponent that is capable of describing its inferential processes while playing a tabletop wargame.
A Description and Evaluation of Various 3-D Models
Authors: Brian Barsky
Venue: IEEE Computer Graphics and Applications (1984)

Overcoming the limitations of polygonal techniques, parametric representations of curved lines and surfaces have evolved into powerful tools for today's computer graphics modeling applications.
An Novel Association Rule Mining Based Missing Nominal Data Imputation Method
Authors: Jianhua Wu, Qinbao Song, Junyi Shen
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Data quality is an important but usually been ignored issue in data mining. However, in this paper, we just focus on the missing data problem, which is one factor that affects data quality. Firstly we propose an association rule mining based missing nominal data imputation method and the corresponding association rule ranking approach, then we used three publicly available data sets to evaluate the method with K-NN imputation as a benchmark. The results suggest that the proposed method outperforms the k-NN imputation methods.
Enhancing a process-oriented approach to literacy and language learning: The role of corpus consultation literacy
Authors: Íde O'Sullivan
Venue: ReCALL (2007)

Corpora and concordancing have become much more widely available as researchers recognise that they can significantly enrich the language learning environment. There is still, however, a strong resistance towards corpus use by teachers and learners (Römer, 2006:122). An understanding of the implications and relevance of corpus use for pedagogy may help teachers and learners overcome this resistance, and hence accelerate the process of “percolation” (McEnery & Wilson, 1997:5) or the “trickle down” (Leech, 1997:2) of corpus research to language teaching and learning. The pedagogical context in which learners' consultation of corpora (corpus consultation literacy) can be developed is fundamental in understanding this new literacy and developing it so that it leads to successful language teaching and learning. This paper seeks to investigate the role which corpus consultation literacy plays in enhancing the language learning process and, consequently, aims to establish whether this new literacy can contribute to a process-oriented approach to language learning. Firstly, a theoretical overview of a process-oriented approach to language learning will be outlined, before investigating if corpus consultation can potentially enhance such an approach. This will be supported by evidence from a number of published empirical studies, covering aspects such as learning within a constructivist framework, and the development of cognitive and metacognitive skills through the use of cognitive and developmental tools. Learners' comments from related studies, namely Chambers and O'Sullivan (2004), O'Sullivan (2006), and O'Sullivan and Chambers (2006), which pertain to the learning process and the influence of corpus consultation literacy on this same process, will also be considered. The hypothesis presented here is that corpus consultation literacy can enhance a process-oriented approach to language teaching and learning. It is envisaged that this research will contribute towards the establishment of a sound theoretical and pedagogical foundation for the integration of corpus consultation literacy into language teaching and learning.
Experiments with "Characteristic Loci" for Recognition of Handprinted Characters
Authors: A. L. Knoll
Venue: IEEE Transactions on Computers (1969)

Recognition experiments have been performed on handprinted characters using a set of features which has not been applied previously to handprinting. Glucksman's "characteristic loci" were utilized in experiments with the well-known Highleyman data, as well as samples generated at Stanford Research Institute and Honeywell. Two recognition algorithms were tested. Results on numeric samples compare favorably with those of other investigators despite the small dimensionality of the feature vector. On the constrained Honeywell samples, recognition rates exceeding 98 percent were achieved using the simpler algorithm. With alphabetic samples, some problems remain in resolving persistent ambiguities, and methods for attacking these problems are considered.
Algebraic Characterization of CNOT-Based Quantum Circuits with its Applications on Logic Synthesis
Authors: Mehdi Saeedi, Morteza Saheb Zamani, Mehdi Sedighi
Venue: Proceedings of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools (2007)

The exponential speed up of quantum algorithms and the fundamental limits of current CMOS process for future design technology have directed attentions toward quantum circuits. In this paper, the matrix specification of a broad category of quantum circuits, i.e. CNOT-based circuits, are investigated. We prove that the matrix elements of CNOT-based circuits can only be zeros or ones. In addition, the columns or rows of such a matrix have exactly one element with the value of 1. Furthermore, we show that these specifications can be used to synthesize CNOT-based quantum circuits. In other words, a new scheme is introduced to convert the matrix representation into its SOP equivalent using a novel quantum-based Karnaugh map extension. We then apply a search-based method to transform the obtained SOP into a CNOT-based circuit. Experimental results prove the correctness of the proposed concept.
Maximum Entropy Image Reconstruction
Authors: S. J. Wernecke
Venue: IEEE Transactions on Computers (1977)

Two-dimensional digital image reconstruction is an important imaging process in many of the physical sciences. If the data are insufficient to specify a unique reconstruction, an additional criterion must be introduced, either implicitly or explicitly before the best estimate can be computed. Here we use a principle of maximum entropy, which has proven useful in other contexts, to design a procedure for reconstruction from noisy measurements. Implementation is described in detail for the Fourier synthesis problem of radio astronomy. The method is iterative and hence more costly than direct techniques; however, a number of comparative examples indicate that a significant improvement in image quality and resolution is possible with only a few iterations. A major component of the computational burden of the maximum entropy procedure is shown to be a two-dimensional convolution sum, which can be efficiently calculated by fast Fourier transform techniques.
Offset Approximation Algorithm for Subdivision Surfaces
Authors: Junqing Yang, Min Zhou, Xiaohong An, Lining Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Based on Catmull-Clark Subdivision scheme, a valid algorithm of offset approximation for Subdivision Surface is proposed. It can overcome the defect that previous approaches treat offset surface only as parametric surface, functional surface and algebraic surface. In this paper, by making the limit positions corresponding to new control vertices of offset surface are at their exact offset positions, we convert offset approximation problem into solving linear equation system. We also present a method for error control of offset approximation, meanwhile, how to compute maximum offset distance without self-intersection is discussed. The examples in the paper demonstrate explicitness and efficiency of our method.
Global convergence of a modified BFGS-type method for unconstrained non-convex minimization
Authors: Qiang Guo, Jian-Guo Liu
Venue: Journal of Applied Mathematics and Computing (2007)

To the unconstrained programme of non-convex function, this article give a modified BFGS algorithm associated with the general line search model. The idea of the algorithm is to modify the approximate Hessian matrix for obtaining the descent direction and guaranteeing the efficacious of the new quasi-Newton iteration equation Bk+1 sk = yk*, where yk* is the sum of yk and Aksk, and Ak is some matrix. The global convergence properties of the algorithm associating with the general form of line search is proved.
Optimal chunking of large multidimensional arrays for data warehousing
Authors: E. J. Otoo, Doron Rotem, Sridhar Seshadri
Venue: Proceedings of the ACM tenth international workshop on Data warehousing and OLAP (2007)

Very large multidimensional arrays are commonly used in data intensive scientific computations as well ason-line analytical processing applications referred to as MOLAP. The storage organization of such arrays on disks is done by partitioning the large global array into fixed size sub-arrays called chunks or tiles that form the units of data transfer between disk and memory. Typical queries involve the retrieval of sub-arrays in a manner that access all chunks that overlap the query results. An important metric of the storage efficiency is the expected number of chunks retrieved over all such queries. The question that immediately arises is "what shapes of array chunks give theminimum expected number of chunks over a query workload?" The problem of optimal chunking was first introduced by Sarawagi and Stonebraker [11] who gave an approximate solution. In this paper we develop exact mathematical models of the problem and provide exact solutions using steepest descent and geometric programming methods. Experimental results, using synthetic and real life workloads, show that our solutions are consistently within than 2.0% of the true number of chunks retrieved for any number of dimensions. In contrast, the approximate solution of [11] can deviate considerably from the true result with increasing number of dimensions and also may lead suboptimal chunk shapes.
A Novel Statistical Recognition Method Based on Hypersphere Model for Radar HRRP ATR
Authors: Lan Du, Hongwei Liu, Zheng Bao, Feng Chen
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

Different from general Gaussian-distributed data, L_2 normalized samples are applied to HRRP-based recognition to deal with the amplitude-scale sensitivity problem, therefore, geometrically speaking, power transformed HRRP samples spread on a unit hypersphere. This paper proposes a novel statistical recognition method for power transformed HRRP samples under the jointly multivariate Gaussian distribution hypothesis, in which the hyperspherical spread of HRRP samples and the effectively discriminating information contained in the noise subspace can be fully utilized without increasing computation complexity. The experimental results based on measured data show that our proposed method can greatly improve the recognition performance.
A Middleware Supporting Context-Aware Services Based on Context Business Objects
Authors: Jinhua Xiong, Manfred Wojciechowski
Venue: Proceedings of the Sixth International Conference on Grid and Cooperative Computing (2007)

Although the demand for context-aware applications seems very high, not many applications are in real use. Besides the strenuosity, their insufficient adaptability to changing environment is a major reason. To address the issue, we proposed a VINCA-cc approach and a context middleware to support business-level dynamic configuration of context-aware service. In our approach, all kinds of context information are abstracted to standardized context business objects (CBO), registered in the context middleware. The business-level context model, CBO, represents a set of business-level properties and abstract unified operations that are applicable to all context information. Based on the visual business-level service composition language-VINCA and CBO model, context-aware services can be visually (re-)configured at the business-level. The paper focuses on the context middleware, CBO model and its application.
Unsupervised High Order Boltzmann Machine and Its Application on Medicine
Authors: Sun Zhanquan, Xi Guangcheng, Yi Jianqiang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

Based on current work about high order Boltzmann Machine (BM) and unsupervised BM, an unsupervised learning algorithm based on high order BM is proposed. It is different from supervised BM in that it has no training samples for output units. In the unsupervised BM, the maximization of the mutual information based on Shannon entropy is used as an unsupervised criterion. As we all know, the computation cost of BM with hidden units is very expensive. When two restrictions are considered, that is the absence of hidden units and the restriction to classification problems, the high order BM can make up for the losing of hidden unit which can save lots of the computation cost. This domain of problems is very broad. The algorithm is the same with discrete variables and continuous variables. At last, the unsupervised high order BM is used to classify some medical data.