ppxscal/embedding_network huggingface dataset:
AsAP: A Fine-Grained Many-Core Platform for DSP Applications
Authors: Bevan Baas, Zhiyi Yu, Michael Meeuwsen, Omar Sattari, Ryan Apperson, Eric Work, Jeremy Webb, Michael Lai, Tinoosh Mohsenin, Dean Truong, Jason Cheung
Venue: IEEE Micro (2007)

Many emerging and future applications require significant levels of complex digital signal processing and operate within limited power budgets. Moreover, dramatically rising VLSI fabrication and design costs make programmable and reconfigurable solutions increasingly attractive. The AsAP project addresses these challenges with a chip multiprocessor composed of simple processors with small memories, achieving high energy efficiency and throughput in a small chip area.
Accuracy analysis of acceleration schemes for stiff multiscale problems
Authors: Christophe Vandekerckhove, Dirk Roose
Venue: Journal of Computational and Applied Mathematics (2008)

In the context of multiscale computations, techniques have recently been developed that enable microscopic simulators to perform macroscopic level tasks (equation-free multiscale computations). The main tool is the so-called coarse-grained time-stepper, which implements an approximation of the unavailable macroscopic time-stepper using only the microscopic simulator. Several schemes were developed to accelerate the coarse-grained time-stepper, exploiting the smoothness in time of the macroscopic dynamics. To date, mainly the stability of these methods was analyzed. In this paper, we focus on their accuracy properties, mainly in the context of parabolic problems. We study the global error of the different methods, compare with explicit stiff ODE solvers, and use the theoretical results to develop more accurate variants. Our theoretical results are confirmed by various numerical experiments.
ANIMENGINE: An Engineering Animation System
Authors: Tsukasa Noma, Tosiyasu Kunii
Venue: IEEE Computer Graphics and Applications (1985)

CIM animation systems are designed to provide exact and unambiguous displays of moving objects. This system also offers a special geometric model for almost real-time display.
A New Data Protecting Scheme Based on TPM
Authors: Mingdi Xu, Jian He, Bo Zhang, Huanguo Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Trusted platform model (TPM) is special-purpose integrated circuits built into a variety of platforms to enable strong user authentication and machine attestation-essential to prevent inappropriate access to confidential and sensitive information and to protect against compromised networks. As a necessary component for multifarious platforms, storage device keeps on a mass of data including confidential and secretive information. How to ensure data not to be accessed by unauthorized users effectively, and to guarantee information to be in safe and secure state? Aiming at these problems, we put forward a novel scheme for protecting data on personal computer platform. By combing trusted computing platform, we propose a secure and reliable model for user authentication and data encryption. The model uses storage protocol to establish a password system to encrypt data, and uses TPM to authenticate different users. We also implement this model by adding it into trusted computing platform. The enhanced platform can not only encrypt data per sector drastically, but also exclude those who can't be authenticated. Some external software attacks and physical theft also cut no ice.
A Set of Invariants Within the Power Spectrum of Unitary Transformations
Authors: S. Wendling
Venue: IEEE Transactions on Computers (1978)

This correspondence presents a device for designing unitary transformations based on the Hadamard transform process. The notion of "invariants" within the power spectrum of one-dimensional transformations is developed and the specific case of some widespread transformations is considered. The results are extended to two-dimensional transformations and a character recognition experiment using the invariants thus obtained is presented.
MedTAKMI-CDI: interactive knowledge discovery for clinical decision intelligence
Authors: Akihiro Inokuchi, Koichi Takeda, Noriko Inaoka, Fumihiko Wakao
Venue: IBM Systems Journal (2007)

This paper describes MedTAKMI-CDI, an online analytical processing system that enables the interactive discovery of knowledge for clinical decision intelligence (CDI). CDI supports decision making by providing in-depth analysis of clinical data from multiple sources. We discuss the fundamental challenges we faced and explain how we met those challenges and developed a prototype experimental CDI system that currently handles clinical information for about 7,000 patients at the National Cancer Center in Japan. We elaborate on a three-layer model (attribute-value pairs, ordered sequences of events, and time-stamped sequences of events) for clinical information, which can represent three different levels of abstraction. This flexibility supports a broad range of analysis, from simple demographic analysis to a mission-critical clinical-path pattern analysis. Rather than a collection of rigid relational schema for clinical information, our relational database system employs a metaschema with patient identifier, time stamp, attribute name, and attribute values. This allows us to modify the representation of clinical information without having to reload the data and rewrite the analytic components. We also describe the analytic functions that are used to understand clinical care practice at the hospital, to obtain an overview of the clinical information, to navigate the clinical information by using the layers of abstraction and the ontologies, and to extract the patterns and rules for clinical paths.
Managing and Deployment of Applications with OSGi in the Context of Smart Home
Authors: Charles Gouin-Vallerand, Sylvain Giroux
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

The presence of a multitude of heterogeneous devices in a Smart Home environment create a whole puzzle when comes the time to deploy, update, or manage applications on these devices. The configuration and the updating of applications in that context can be expensive, as well as resource and time consuming, especially when there are several similar environments to implement. This paper considers those problems, brings a glimpse on possible solutions, and proposes the use of the OSGi framework to ease the deployment and the management of applications. Moreover this paper presents a summary of a distributed system currently in last phase of development that will resolve the proposed problematic. This system allows the remote managing and deployment in the context of a distributed and pervasive environment for cognitively impaired people.
Freshness Control of XML Documents for Query Load Balancing
Authors: Stephane Gancarski, Cecile Le Pape, Alda Lopes Gancarski
Venue: Proceedings of the 18th International Conference on Database and Expert Systems Applications (2007)

We present an approach for controlling the freshness of replicated XML documents. The main idea is that read-only transactions may accept to read stale data, provided they can express an upper bound on the stalenessof the data they read. Controlling the freshness of data accessed by read-only transactions greatly improves load balancing since it allows for choosing a node for executing the transaction even if it is not perfectly fresh. Such a routing is based on detecting which partsof a document are likely to be updated by a given transaction. Due to the rich nature of XML, the problem isquite more complex than for relational SQL data. We present a new algorithm for conflict detection between transactions, needed to estimate freshness of data according to the missing transactions on a node. WE alsopresent new freshness measures, in order to take into account the structure/content nature of XML.
Visualizing Diversity and Depth over a Set of Objects
Authors: Jason Pearlman, Penny Rheingans, Marie des Jardins
Venue: IEEE Computer Graphics and Applications (2007)

When visualizing a set of objects, it can be useful to visualize both the set as a whole and the individual attributes of each member of the set. A user may be interested in whether the set includes objects with specific attribute values, but also care about the distribution of attribute values within the set. The authors use the term depth to refer to the prevalence of particular desired values in the set, and diversity to refer to the distribution of these values across a range. Their approach for visualizing a set of objects uses glyphs overlaid on a composite representation of the entire set to convey objects' depth and the set's diversity. They test and apply this technique to three application domains: analyzing student applicant pools of a particular school or department, building an effective fantasy football team, and analyzing traffic activity on a network.
Good Lattice Points-Based Particle Swarm Optimizer
Authors: Shoubao Su, Jiwen Wang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

The mechanism of the classical particle swarm optimization and the comparison criterion of different natural computing methods is investigated by introducing the discrepancy and good lattice points in number theory and proposes a novel optimization method, called good lattice points-based particle swarm optimization algorithm, which intends to produce faster and more accurate convergence because it has a solid theoretical basis and better global search ability, meanwhile the global convergence of the presented algorithm with asymptotic probability one is proved by the property of the optimal lattice. Finally experiment results are very promising to illustrate the outstanding feature of the presented algorithm.
Robustness through prior knowledge: using explanation-based learning to distinguish handwritten Chinese characters
Authors: Qiang Sun, Li-Lun Wang, Shiau Hong Lim, Gerald DeJong
Venue: International Journal on Document Analysis and Recognition (2007)

Handwritten Chinese character recognition is difficult due to the unstructured and noisy nature of its training examples. There are often too few training examples for a statistical learner like SVM to overcome the noise and extract useful information reliably. Existing prior domain knowledge represents a valuable source of information for classifying handwritten characters. Explanation-based learning (EBL) provides a way to incorporating prior domain knowledge into the learner. The dynamic bias formed by the interaction of domain knowledge with training examples can yield solution knowledge of potential higher quality. Two EBL approaches, one that uses a special feature kernel function in SVM, the other uses a conventional kernel for the SVM but provides additional preference in choosing the classification hyperplane, are reported.
Algorithms for spherical harmonic lighting
Authors: Ian G. Lisle, S.-L. Tracy Huang
Venue: Proceedings of the 5th international conference on Computer graphics and interactive techniques in Australia and Southeast Asia (2007)

Spherical harmonic (SH) lighting models require efficient and general libraries for evaluation of SH functions and of Wigner matrices for rotation. We introduce an efficient algebraic recurrence for evaluation of SH functions, and also implement SH rotation via Wigner matrices constructed for the real SH basis by a recurrence. Using these algorithms, we provide a freely distributable C / OpenGL implementation for SH diffuse unshadowed, shadowed and inter-reflected models. Our implementation allows flexible switching of scene, light probe, SH degree and lighting model at run time.
New Block-Based Statistical Timing Analysis Approaches Without Moment Matching
Authors: Ruiming Chen, Hai Zhou
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

With aggressive scaling down of feature sizes in VLSI fabrication, process variation has become a critical issue in designs. We show that two necessary conditions for the "Max" operation are actually not satisfied in the moment matching based statistical timing analysis approaches. We propose two correlation-aware block-based statistical timing analysis approaches that keep these necessary conditions, and prove that our approaches always achieve tight lower bound and upper bound of the yield. Especially, our approach always gets the tight upper bound of the yield irrespective of the distributions that random variables have.
Characterizing the Function Space for Bayesian Kernel Models
Authors: Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert
Venue: The Journal of Machine Learning Research (2007)

Kernel methods have been very popular in the machine learning literature in the last ten years, mainly in the context of Tikhonov regularization algorithms. In this paper we study a coherent Bayesian kernel model based on an integral operator defined as the convolution of a kernel with a signed measure. Priors on the random signed measures correspond to prior distributions on the functions mapped by the integral operator. We study several classes of signed measures and their image mapped by the integral operator. In particular, we identify a general class of measures whose image is dense in the reproducing kernel Hilbert space (RKHS) induced by the kernel. A consequence of this result is a function theoretic foundation for using non-parametric prior specifications in Bayesian modeling, such as Gaussian process and Dirichlet process prior distributions. We discuss the construction of priors on spaces of signed measures using Gaussian and Lévy processes, with the Dirichlet processes being a special case the latter. Computational issues involved with sampling from the posterior distribution are outlined for a univariate regression and a high dimensional classification problem.
Children as Unwitting End-User Programmers
Authors: Marian Petre, Alan F. Blackwell
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

Children who are active on the internet are performing significant design and programming activity without realising it, in the course of hacking little animations, game scripts and so on. What does such effortless learning suggest about how to support end-user programming? This paper presents observations of "unwitting' design and programming activity by a small group of teenagers, aged 12-17. It analyses their adoption and appropriation of technology, and discusses how such practices are embedded in social networks.
Data Coherence Problem in a Multicache System
Authors: W. C. Yen
Venue: IEEE Transactions on Computers (1985)

A coherence problem may occur in a multicache system as soon as data inconsistency exists in the private caches and the main memory. Without an effective solution to the coherence problem, the effectiveness of a multicache system will be inherently limited. The problem is closely examined in this paper and previous solutions, both centralized approaches and distributed approaches, are analyzed based on the notion of semicritical sections. A state model is then presented which clarifies various coherence mechanisms as well as introduces a new state to enable the multicache system to more efficiently handle the processor writes. Software guidance, for performance and not for integrity, is advocated in a new proposal which in a practical multicache environment explores the benefit of the new state with little cost.
Analytical and numerical study of coupled atomistic-continuum methods for fluids
Authors: Weiqing Ren
Venue: Journal of Computational Physics (2007)

The stability and convergence rate of coupled atomistic-continuum methods are studied analytically and numerically. These methods couple a continuum model with molecular dynamics through the exchange of boundary conditions in the continuum-particle overlapping region. Different coupling schemes, including velocity-velocity, flux-velocity, velocity-flux and flux-flux, are studied. It is found that the velocity-velocity and flux-velocity schemes are stable. The flux-flux scheme is weakly unstable. The stability of the velocity-flux scheme depends on the parameter T"c which is the length of the time interval between successive exchange of boundary conditions. It is stable when T"c is small and unstable when T"c is large. For steady-state problems, the flux-velocity scheme converges faster than the other coupling schemes.
The Computation of Window Operations on a Parallel Organized Computer A Case Study
Authors: Shi-Kuo Chang
Venue: IEEE Transactions on Computers (1973)

The computation of window operations and arbitrary local operations on a parallel organized computer is studied. It is shown that for the window operations, the computation time can be minimized, subject to the restriction of memory accessibility. It is also shown that the computation time increases as the degree of disorderliness of a local operation increases.
Universal Intelligence: A Definition of Machine Intelligence
Authors: Shane Legg, Marcus Hutter
Venue: Minds and Machines (2007)

A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: we take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines.
Trust on a Nationwide Scale
Authors: Vanessa Gratzer, David Naccache
Venue: IEEE Security and Privacy (2007)

Singapore is a small island nation with roughly 4.5 million inhabitants, but it has a highly developed international economy based on trade, services, and knowledge management. Singapore has also been a good laboratory for public policy ideas, which the authors investigate in more detail in this article about trust tokens.
Power Minimization Problems of Logic Networks
Authors: S. Yajima
Venue: IEEE Transactions on Computers (1974)

As a method for greatly reducing power dissipation in logic networks, we propose some logic organization techniques for logic networks. By such techniques, their power dissipation is to be minimized under certain input conditions, or the average power dissipation in the whole network should be minimized. A logic network in which these problems are taken into account will be called a power minimized logic circuit (PML).
Comments on "A Readily Implemented Single-Error-Correcting Unit-Distance Counting Code"
Authors: R. C. Devries
Venue: IEEE Transactions on Computers (1979)

Kautz, in the above paper1has presented a method of correcting single errors in SIB3codes that does not displace the count by more than two counts in the counting sequence, assuming the two most significant bits are correct. This paper presents a correction method that does not require the two most significant bits to be correct and does not displace the count by more than on
On the Evolution of Management Approaches, Frameworks and Protocols: A Historical Perspective
Authors: George Pavlou
Venue: Journal of Network and Systems Management (2007)

Network, system and service management has evolved into an important scientific discipline over the last 20 years. While management problem solving is expected to continue ad infinitum, one would have expected that, after 20 years of research and standardization, an agreement would have been reached regarding a common management framework and protocol. But despite relevant progress and various available solutions, there seems to exist a permanent quest for the all encompassing next generation management technology. This paper looks at the evolution of management approaches, frameworks and protocols over the last 20 years, proposes a relevant taxonomy, presents the salient features of the representative tecnologies and discusses relevant issues. The purpose of this paper is to document historically this evolution, highlight important design choices and explain the how's and why's behind the various frameworks and technologies. The paper is concluded with a summary and future outlook.
An Equivalent Vector Optimization Problem for Nonsmooth Multiobjective Programming Problem
Authors: Shu-li Xu, Jun Jiang, Qiu-ting Wang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

for a solution of a invex nonsmooth program- ming problem is introduced. An equivalent -approximated vector optimization problem is constructed by a modification of the objec- tive and the constraint functions in the orig- inal multiobjective programming problem and its equivalent -approximated vector optimiza- tion problem is proved. In this way, optimal- ity conditions for nonsmooth constrained multi- objective programming problems having gener- alized invex objective and constraint functions (with respect to the same function )are ob- tained. Key word: invex nonsmooth multiobjective programming ; -approximated vector opti- mization; (weak)efficient solution
A Smooth Surface Based on Biquadratic Patches
Authors: Herbert Steinberg
Venue: IEEE Computer Graphics and Applications (1984)

Ray tracing can generate high-quality color images of free-form surfaces. To reduce CPU time, introduce extra knots into the system and use biquadratics instead of bicubics. 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
Classifying EEG for brain computer interfaces using Gaussian processes
Authors: Mingjun Zhong, Fabien Lotte, Mark Girolami, Anatole Lécuyer
Venue: Pattern Recognition Letters (2008)

Classifying electroencephalography (EEG) signals is an important step for proceeding EEG-based brain computer interfaces (BCI). Currently, kernel based methods such as the support vector machine (SVM) are considered the state-of-the-art methods for this problem. In this paper, we apply Gaussian process (GP) classification to binary discrimination of motor imagery EEG data. Compared with the SVM, GP based methods naturally provide probability outputs for identifying a trusted prediction which can be used for post-processing in a BCI. Experimental results show that the classification methods based on a GP perform similarly to kernel logistic regression and probabilistic SVM in terms of predictive likelihood, but outperform SVM and K-nearest neighbor (KNN) in terms of 0-1 loss class prediction error.