ppxscal/embedding_network huggingface dataset:
An Incomplete Data Analysis Approach Based on the Rough Set Theory and Divide-and-Conquer Idea
Authors: Zaimei Zhang, Renfa Li, Zhongsheng Li, Haiyan Zhang, Guangxue Yue
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Data missing is inevitable in practical fields, how to analyze these incomplete data more efficient is important for data mining. Many methods such as statistical strategy are generally used, but all have some faults. The approach based on rough set theory is proved to be more excellent, but the existed method is still not perfect. This paper extends the valued tolerance relation in rough set theory, introduces divide-and-conquer idea, and accordingly proposes a new incomplete data analysis approach "RSDIDA". This approach more fully utilizes the potential knowledge and laws suggested by the data in information system, can give better completeness analysis to incomplete data, and enhance the efficiency greatly. Experimental result demonstrates its superiority, and it can be adopted as a pre-processing method in data mining.
VIPS: A Visual Debugger
Authors: S. Isoda
Venue: IEEE Software (1987)

Testing Ada programs is easier with this visual debugger that graphically depicts what the program as doing and how it is being done.
Approximation and inapproximability results for maximum clique of disc graphs in high dimensions
Authors: Peyman Afshani, Hamed Hatami
Venue: Information Processing Letters (2008)

We prove algorithmic and hardness results for the problem of finding the largest set of a fixed diameter in the Euclidean space. In particular, we prove that if A^* is the largest subset of diameter r of n points in the Euclidean space, then for every @e>0 there exists a polynomial time algorithm that outputs a set B of size at least |A^*| and of diameter at most r(2+@e). On the hardness side, roughly speaking, we show that unless P=NP for every @e>0 it is not possible to guarantee the diameter r(4/3-@e) for B even if the algorithm is allowed to output a set of size (9594-@e)^-^1|A^*|.
Programming Strategies In the Game of Push-Over
Authors: Tho Le-Ngoc, Louis Vroomen
Venue: IEEE Micro (1982)

Strategies devised for playing games by computer can be extended to the solution of realworld problems. Here, the classic minimax strategy takes on a new challenger.
COBRA A Multi-path Adaptive Local Load Sensing Routing Protocol for Wireless Sensor Networks
Authors: Venkatesh Ramaswamy, Anders Hansson, Stephan Eidenbenz
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

We propose a family of location-based load balancing routing algorithms for wireless sensor networks (WSNs) called COBRA. In this approach, we combine local load balancing with shortest path routing to strike a balance be- tween hop-count efficiency and load distribution. COBRA's advantages over traditional routing protocols are: (i) a sig- nificant reduction of hot-spot occurrences (i.e., nodes or ar- eas of high congestion level), thus enabling longer unin- terrupted operation of WSNs, (ii) a light-weight and scal- able implementation that requires only local congestion up- dates, ideal for implementation on computationally chal- lenged platforms, and (iii) combination of routing and con- gestion avoidance tasks in the protocol stack--a feature that leads to smoother TCP operation over wireless channels with fewer false positives on existing congestion and sub- sequent sending rate reduction by TCP. We show through simulation that COBRA's local load sensing in combina- tion with a shortest path routing component is a promis- ing paradigm that improves global performance in terms of throughput and scalability, while matching other protocols in the traditional energy efficiency objective.
Formal Modeling of Virtual Machines
Authors: A. B. Cremers
Venue: IEEE Transactions on Software Engineering (1978)

A preliminary example of program development demonstrates that the control-independent implementation of data types can lead to very inefficient code. The concept of a data space, which emphasizes the interaction between data and control structures, is introduced as a formal model of virtual machines. The model consists of three components: a state space X, an information structure F, and a control component p. Formally, X is a set of objects, F a set of functions with common domain X mapping the states to the value sets of certain data types, and p a partial function X ? X. Two important points of investigation are the characterization of state space structure and the mechanism of implementation. Good state description is characterized by "completeness" and "orthogonality." Either property plays a prominent role for the concept of implementation which, in turn, is formally defined as a mapping from a "virtual" space to a "real" space, via some "macro" space. These notions are illugtrated by means of several examples from the area of programming languages.
Berkeley Array Processor
Authors: W. Y. Dere, D. J. Sakrison
Venue: IEEE Transactions on Computers (1970)

The Berkeley array processor is a special-purpose computer designed to perform the operations of correlation, convolution, recursive filtering, matrix multiplication, as well as a variant of the Cooley-Tukey algorithm, and others. This note describes the logical organization and performance of this device.
Geodesic-based and projection-based neural blind deconvolution algorithms
Authors: Simone Fiori
Venue: Signal Processing (2008)

The present contribution studies a geodesic-based and a projection-based learning algorithm over a curved parameter space for blind deconvolution (BD) application. The chosen deconvolving structure appears as a single neuron model whose learning rules naturally arise from criterion-function minimization over a smooth manifold. We consider the BD performances of the two classes of algorithms as well as their computational burden. Also, numerical comparisons with seven BD algorithms known from the scientific literature are illustrated and discussed.
Anti-periodic Boundary Value Problem for Impulsive Differential Equations with Delay
Authors: Fengqin Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

The method of upper and lower solutions coupled with monotone iterative technique is used to obtain the results of existence and uniqueness for an anti-periodic boundary value problem of impulsive differential equations with delay.
Lattice-Based Volumetric Global Illumination
Authors: Feng Qiu Fang Xu Zhe Fan Neophytou Neophytos Arie Kaufman, Klaus Mueller
Venue: IEEE Transactions on Visualization and Computer Graphics (2007)

We describe a novel volumetric global illumination framework based on the Face-Centered Cubic (FCC) lattice. An FCC lattice has important advantages over a Cartesian lattice. It has higher packing density in the frequency domain, which translates to better sampling efficiency. Furthermore, it has the maximal possible kissing number (equivalent to the number of nearest neighbors of each site), which provides optimal 3D angular discretization among all lattices. We employ a new two-pass (illumination and rendering) global illumination scheme on an FCC lattice. This scheme exploits the angular discretization to greatly simplify the computation in multiple scattering and to minimize illumination information storage. The GPU has been utilized to further accelerate the rendering stage. We demonstrate our new framework with participating media and volume rendering with multiple scattering, where both are significantly faster than traditional techniques with comparable quality.
On-line multi-modal speaker diarization
Authors: Athanasios Noulas, Ben J. A. Krose
Venue: Proceedings of the 9th international conference on Multimodal interfaces (2007)

This paper presents a novel framework that utilizes multi-modal information to achieve speaker diarization. We use dynamic Bayesian networks to achieve on-line results. We progress from a simple observation model to a complex multi-modal one as more data becomes available. We present an efficient way to guide the learning procedure of the complex model using the early results achieved with the simple model. We present the results achieved in various real-world situations, including videos coming from webcameras, human computer interaction and video conferences.
Statistical methods for automated generation of service engagement staffing plans
Authors: J. Hu, B. K. Ray, M. Singh
Venue: IBM Journal of Research and Development (2007)

In order to successfully deliver a labor-based professional service, the right people with the right skills must be available to deliver the service when it is needed. Meeting this objective requires a systematic, repeatable approach for determining the staffing requirements that enable informed staffing management decisions. We present a methodology developed for the Global Business Services (GBS) organization of IBM to enable automated generation of staffing plans involving specific job roles, skill sets, and employee experience levels. The staffing plan generation is based on key characteristics of the expected project as well as selection of a project type from a project taxonomy that maps to staffing requirements. The taxonomy is developed using statistical clustering techniques applied to labor records from a large number of historical GBS projects. We describe the steps necessary to process the labor records so that they are in a form suitable for analysis, as well as the clustering methods used for analysis, and the algorithm developed to dynamically generate a staffing plan based on a selected group. We also present results of applying the clustering and staffing plan generation methodologies to a variety of GBS projects.
Parallel Mining of Association Rules from Gene Expression Databases
Authors: Mahdi Asadpour, Mohammad Hadi Sadreddini, Gholamhossein Dastghaibyfard
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Gene Expression (GE) databases are high-dimensional and have a large number of genes/columns in each pro- file experiment. Recently, Mining Association Rules (ARM) from these databases has attracted much interest. Several sequential ARM methods have been devised for this pur- pose, but, to the best of our knowledge, there is no parallel ARM specially designed for GE databases. On the other hand, the existing parallel ARMs are not suitable for such databases because they usually do not take into account the high-dimensionality of the data. In this paper, we pro- pose a parallel ARM specially designed for GE databases. We show that our method parallelizes not only the tasks of reading from databases and computing the supports, but also the tasks of computing the combination between items and generating association rules, which here are very time- consuming. We analyze computation and communication costs, speed-up, and present some experimental results on real databases, as well.
The Influence of Masking Phenomenon on Coverage Capability of Single Fault Test Sets in PLA's
Authors: J. Rajski
Venue: IEEE Transactions on Computers (1986)

It is relatively easy to generate a complete single contact fault detection test set Tc for a PLA. However such a test set may fail to detect all multiple faults due to the phenomenon of masking. In previous papers attempting to quantitatively predict the multiple fault coverage capability of a single fault detection test set Tc in PLA's, it was proved that every multiple contact fault in an irredundant PLA is detected by Tc if the multiple fault does not contain any four-way masking cycle. In this correspondence, the masking relations are studied in detail and it is shown that Tc in fact detects a signifilcant percentage of faults with four-way masking. Based on these results more realistic bounds of the coverage capability of Tc are determined. It is shown that the multiple fault coverage ratio of Tc increases with the increasing number m of rows of a PLA and for m = 24 Tc detects 99 percent of all contact faults of size 8 or less.
Efficient Integrated Services in an Enterprise Network
Authors: Martin J. Fischer, Denise M. Bevilacqua Masi, Patrick V. McGregor
Venue: IT Professional (2007)

Engineering an enterprise to efficiently support integrated voice and data services requires sophisticated queuing disciplines to meet quality of service requirements. This study evaluates tradeoffs with three queuing schemes.
An Immune Middleware for Embedded System
Authors: Wei Zheng, Xiaofeng Meng, Qun Sun
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

With embedded system being used in every corner of military and civil electronic industries, its security problem is prominent. Inspired by the natural immune system, the paper proposes an immune middleware to prevent embedded system from misacting when net intrusion or inner mistake happens. Firstly a flexible bus that has three-layer architecture is presented to help the embedded system acquire compatibility, multifunctionality and standardization. Then based on this multiplayer bus architecture, the middleware evolved from the concept of antigen and antibody is proposed. The design principle, the immune strategy, the architecture and the working flow of the immune middleware are introduced in detail afterwards. Finally an experimental case demonstrates the validity of the proposed method.
Unsteady Cavitation and Cryogenic Flow Cavitation around 2D Body
Authors: Seyoung Lee, Changjin Lee, Soohyung Park
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

Since the coupling of cavitation modeling with turbulent flow is the difficulty topic, a numerical simulation for two phase flow remains as one of the challenging issues in the society. This research focuses on the development of numerical code to deal with incompressible two phase flow around 2D hydrofoil combined with cavitation model suggested by Kunz et al. with k-å turbulent model. The simulation results are compared to experimental data to verify the validity of the developed code. Also, the comparison of the calculation results is made with LES results to evaluate the capability of conventional turbulence models such as k-å model. The calculation results show very good agreement with experimental observations even though this code can not grasp the small scaled bubbles in the calculation whereas LES can hold the real physics. Also, the calculation of cavitation in cryogenic fluid was done by implementing the temperature sensitivity in government equations. Even though the results show good agreement with previous calculation results, further research will be needed to account for real physics of the formation of cavitation in cryogenic fluid due to temperature sensitivity. This code will be further extended to 3D compressible two phase flow for the study on the fluid dynamics around inducers and impellers in turbo pump system.
Evolving parameters of multi-scale radial basis function kernels for support vector machines
Authors: Tanasanee Phienthrakul, Boonserm Kijsirikul
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

In support vector machines (SVMs), kernel functions are used to compute dot product in a higher dimensional feature space. The performance of classification depends on the chosen kernel. The radial basis function (RBF) kernel is a most popular kernel that succeeded in many tasks. In order to obtain a more flexible kernel function, a family of RBF kernels is proposed. Multi-scale RBF kernels are combined by including weights. This new kernel is proved to be a Mercer's kernel. Then, the evolutionary strategies (ESs) are used to adjust the weights and the widths of the RBF kernels. The training accuracy, the bound of generalization error, and subsets cross-validation are used to be objective functions in the evolutionary process. The experimental results show that the proposed kernel allows better discrimination in the feature space. Moreover, subsets cross-validation is a good objective function and yields the effective results on benchmarks.
MODLEX: A Multi Objective Data Layout EXploration Framework for Embedded Systems-on-Chip
Authors: T. S. Rajesh Kumar, C. P. Ravikumar, R. Govindarajan
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

The memory subsystem is a major contributor to the performance, power, and area of complex SoCs used in feature rich multimedia products. Hence, memory architecture of the embedded DSP is complex and usually custom designed with multiple banks of single-ported or dual ported on-chip scratch pad memory and multiple banks of off-chip memory. Building software for such large complex memories with many of the software components as individually optimized software IPs is a big challenge. In order to obtain good performance and a reduction in memory stalls, the data buffers of the application need to be placed carefully in different types of memory . In this paper we present a unified framework (MODLEX) that combines different data layout optimizations to address the complex DSP memory architectures. Our method models the data layout problem as multi-objective Genetic Algorithm (GA) with performance and power being the objectives and presents a set of solution points which is attractive from a platform design viewpoint. While most of the work in the literature assumes that performance and power are non-conflicting objectives, our work demonstrates that there is significant trade-off (up to 70%) that is possible between power and performance.
FPGA implementation of a systems identification module based upon Hopfield networks
Authors: Miguel Atencia, Hafida Boumeridja, Gonzalo Joya, Francisco García-Lagos, Francisco Sandoval
Venue: Neurocomputing (2007)

The aim of this contribution is to implement a hardware module that performs parametric identification of dynamical systems. The design is based upon the methodology of optimization with Hopfield neural networks, leading to an adapted version of these networks. An outstanding feature of this modified Hopfield network is the existence of weights that vary with time. Since weights can no longer be stored in read-only memories, these dynamic weights constitute a significant challenge for digital circuits, in addition to the usual issues of area occupation, fixed-point arithmetic and nonlinear functions computations. The implementation, which is accomplished on FPGA circuits, achieves modularity and flexibility, due to the usage of parametric VHDL to describe the network. In contrast to software simulations, the natural parallelism of neural networks is preserved, at a limited cost in terms of circuitry cost and processing time. The functional simulation and the synthesis show the viability of the design. In particular, the FPGA implementation exhibits a reasonably fast convergence, which is required to produce accurate parameter estimations. Current research is oriented towards integrating the estimator within an embedded adaptive controller for autonomous systems.
A MSD-HMM Approach to Pen Trajectory Modeling for Online Handwriting Recognition
Authors: L. Ma, F. Soong, P. Liu, Y.-J. Wu
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

In modeling online handwritten characters, imaginary strokes have been conveniently generated by connecting ad- jacent real strokes together to form a continuous trajectory. However, this approach causes confusions among charac- ters with similar but actually different trajectories. In this paper, we propose to use Multi-Space probability Distri- bution (MSD) to model imaginary strokes jointly with real strokes. With the proposed MSD, real and imaginary strokes become observations from different probability spaces and they are modeled stochastically. Also, the flexibility in MSD to assign different feature dimensions to each individual space enables us to ignore certain features that can cause singularity problem in modeling. Experimental results ob- tained in handwritten Chinese character recognition indi- cate MSD provides 1.3% - 2.8% character recognition ac- curacy improvement across different recognition systems where MSD significantly improves discrimination among confusable characters with similar trajectories (e.g., ` -b' v.s. and ` -h' ).
Estimation in bivariate nonnormal distributions with stochastic variance functions
Authors: Moti L. Tiku, M. Qamarul Islam, Hakan S. Sazak
Venue: Computational Statistics Data Analysis (2008)

Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distributions. Estimation of parameters in such situations is considered when the mean and variance of one variable is a linear and a positive function of the other variable. This is typically true of bivariate t distribution. The resulting estimators are found to be remarkably efficient. Hypothesis testing procedures are developed and shown to be robust and powerful. Real life examples are given.
Clustering people according to their preference criteria
Authors: Jorge Díez, Juan José del Coz, Oscar Luaces, Antonio Bahamonde
Venue: Expert Systems with Applications: An International Journal (2008)

Learning preferences is a useful task in application fields such as collaborative filtering, information retrieval, adaptive assistants or analysis of sensory data provided by panels. SVMs, using preference judgments, can induce ranking functions that map objects into real numbers, in such a way that more preferable objects achieve higher values. In this paper we present a new algorithm to build clusters of people with closely related tastes, and hence people whose preference judgment sets can be merged in order to learn more reliable ranking functions. In some application fields, these clusters can be seen as market segments that demand different kinds of products. The method proposed starts representing people's preferences in a metric space, where it is possible to define a kernel based similarity function; finally a clustering algorithm discovers significant groups with homogeneous tastes. The key point of our proposal is to use the ranking functions induced from the preference judgments of each person; we will show that those functions codify the criteria used by each person to decide her preferences. To illustrate the performance of our approach, we present two experimental cases. The first one deals with the collaborative filtering database EachMovie. The second database describes a real case of consumers of beef meat.
Solid Modeling and the Interface Between Design and Manufacture
Authors: M. Pratt
Venue: IEEE Computer Graphics and Applications (1984)

Many challenges must be faced before an automatic process-planning system will be practical for individual application¿specifically, the recognition and simulation of a part's ¿form features.¿ 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