ppxscal/embedding_network huggingface dataset:
Decentralized Utilization Control in Distributed Real-Time Systems
Authors: Xiaorui Wang, Dong Jia, Chenyang Lu, Xenofon Koutsoukos
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

Many real-time systems must control their CPU utilizations in order to meet end-to-end deadlines and prevent overload. Utilization control is particularly challenging in distributed real-time systems with highly unpredictable workloads and a large number of end-to-end tasks and processors. This paper presents the Decentralized End-to-end Utilization CONtrol (DEUCON) algorithm that can dynamically enforce desired utilizations on multiple processors in such systems. In contrast to centralized control schemes adopted in earlier work, DEUCON features a novel decentralized control structure that only requires localized coordination among neighbor processors. DEUCON is systematically designed based on recent advances in distributed model predictive control theory. Both control-theoretic analysis and simulations show that DEUCON can provide robust utilization guarantees and maintain global system stability despite severe variations in task execution times. Furthermore, DEUCON can effectively distribute the computation and communication cost to different processors and tolerate considerable communication delay between local controllers. Our results indicate that DEUCON can provide scalable and robust utilization control for large-scale distributed real-time systems executing in unpredictable environments.
On 0-1 matrices and small excluded submatrices
Authors: Gábor Tardos
Venue: Journal of Combinatorial Theory Series A (2005)

We say that a 0-1 matrix A avoids another 0-1 matrix (pattern) P if no matrix P' obtained from P by increasing some of the entries is a submatrix of A. Following the lead of (SIAM J. Discrete Math. 4 (1991) 17-27; J. Combin. Theory Ser. A 55 (1990) 316-320; Discrete Math. 103 (1992) 233-251) and other papers we investigate n by n 0-1 matrices avoiding a pattern P and the maximal number ex(n, P) of 1 entries they can have. Finishing the work of [8] we find the order of magnitude of ex(n, P) for all patterns P with four 1 entries. We also investigate certain collections of excluded patterns. These sets often yield interesting extremal functions different from the functions obtained from any one of the patterns considered.
A Scalable Security Architecture for Grid
Authors: Quan Zhou, Geng Yang, Jiangang Shen, Chunming Rong
Venue: Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (2005)

Grid is a distributed computing and resource environment. Security is an important issue in the grid environment. In this paper, we present a prototype of the grid security architecture. It shows that the architecture is scalable, and meets the security requirements of the grid.
Internet Integration of 3D-CAD Design and Manufacturing for Complex Products
Authors: Haruo Sakamoto, Takuya Kimura, Masaoki Sakamoto, Masaru Sawada
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

This paper describes internet integration for the 3D-CAD design and manufacturing of complex products. The Kochi University of Technology (KUT) in Kochi, Japan, has cooperated with Sakamoto Giken Co. (Sakamoto Co.) in Kochi, who in turn has collaborated with other companies using internet technology in the field of design and manufacturing. Using collaboration software, an internet camera, and an internet telephone, design meetings between engineers in distant locations were conducted. Several cases of collaboration design and manufacturing work are also introduced. Sakamoto Co. aims to produce complex products, which are difficult to design and manufacture. Rapid prototyping has also been conducted for activities between the university and the company, and among the companies. The use of the internet in this way reduces the time required for design and manufacturing and accelerates product development.
3D Face Recognition using Mapped Depth Images
Authors: Gang Pan, Shi Han, Zhaohui Wu, Yueming Wang
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

This paper addresses 3D face recognition from facial shape. Firstly, we present an effective method to automatically extract ROI of facial surface, which mainly depends on automatic detection of facial bilateral symmetry plane and localization of nose tip. Then we build a reference plane through the nose tip for calculating the relative depth values. Considering the non-rigid property of facial surface, the ROI is triangulated and parameterized into an isomorphic 2D planar circle, attempting to preserve the intrinsic geometric properties. At the same time the relative depth values are also mapped. Finally we perform eigenface on the mapped relative depth image. The entire scheme is insensitive to pose variance. The experiment using FRGC database v1.0 obtains the rank-1 identification score of 95%, which outperforms the result of the PCA base-line method by 4%, which demonstrates the effectiveness of our algorithm.
A Framework for Countering Denial-of-Information Attacks
Authors: Gregory Conti, Mustaque Ahamad
Venue: IEEE Security and Privacy (2005)

Denial-of-information (DoI) attacks degrade a given user's ability to seek, assimilate, and process information, and are becoming more prevalent due to the Internet's rapid growth. To counter such attacks, the authors' taxonomy provides structure to this area and proposes a model for describing the information space.
Semi-automatic video annotation based on active learning with multiple complementary predictors
Authors: Yan Song, Xian-Sheng Hua, Li-Rong Dai, Meng Wang
Venue: Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval (2005)

In this paper, we will propose a novel semi-automatic annotation scheme for video semantic classification. It is well known that the large gap between high-level semantics and low-level features is difficult to be bridged by full-automatic content analysis mechanisms. To narrow down this gap, relevance feedback has been introduced in a number of literatures, especially in those works addressing the problem of image retrieval. And at the same time, active learning is also suggested to accelerate the converging speed of the learning process by labeling the most informative samples. Generally an active learning scheme includes a sample selection engine and a learning engine. In this paper, we will discuss the limitations of existing active learning algorithms and propose a novel active learning scheme based on multiple complementary predictors and incremental model adaptation, which improves the efficiencies of both of the primary components of active learning. Firstly, an efficient sample selection scheme is proposed, in which multiple predictors are applied to find most informative samples. Then an incremental model adaptation technique, maximum likelihood linear regression (MLLR), is used to update the classifiers which tackle the issue of unbalance between the original training set and the newly labeled data. It is proved that the samples selected by the proposed scheme are more representative than general active learning scheme, as well as the incremental model adaptation scheme is effective especially when the newly added data size is small.
An Algebraic Condition Equivalent to Strong Stability of Stationary Solutions of Nonlinear Positive Semidefinite Programs
Authors: Toshihiro Matsumoto
Venue: SIAM Journal on Optimization (2005)

This paper addresses strong stability, in the sense of Kojima, of stationary solutions of nonlinear positive semidefinite programs (NSDP). First, we give a characterization of stability from the point of view of one-to-one maps under an LICQ condition generalized to these programs. Second, under the same condition we construct a method for NSDP that is analogous to Kojima's method for classical nonlinear programs (NLP) treated in his famous paper. From this construction we make clear the essential difference between NSDP and NLP, and we deduce an algebraic condition equivalent to strong stability for those NSDP to which there does not exist this difference.
A Novel Two Tiered Proxy Caching Scheme for Video on Demand Applications
Authors: Amir Nayyeri, Mahmoud Reza Hashemi, Nasser Yazdani
Venue: Proceedings of the 10th International Workshop on Web Content Caching and Distribution (2005)

Considering the constant increase of network traffic, and existing bandwidth limitations, caching Internet objects is an essential technique to improve the provided quality of service and to reduce the network load. Caching is particularly helpful for video objects due to their interactive nature, large size, long playback duration, real time constraints, and typically variable bitrate. Several caching schemes for video streams have been proposed in the literature. The performance of the existing methods generally degrades in applications like video on demand where random access is common. In this paper a new two tiered proxy caching scheme for random access applications has been proposed. The proposed design consists of two layers: the Cache layer and the Fetch layer. The Cache layer divides the incoming video stream into small segments, and selects the segments that should be cached based on their current access probability and the utility they provide. The Fetch layer organizes the outgoing requests according to the priority it assigns to them. Simulation results indicate that the proposed technique outperforms existing caching schemes when random access is significant. The provided utility is up to three times better than the existing solutions.
A Personal Recollection of Software's Early Days (1960-1979): Part 2
Authors: Ernest E. Keet
Venue: IEEE Annals of the History of Computing (2005)

The author was a participant in the early days of packaged software, an early participant in ADAPSO, and a pioneer in the early days of shrink-wrapped PC products. This article, the first of which appeared in the October-December 2004 issue of Annals, traces the author's career from running the Software Products Group at Dun & Bradstreet to the early days of Vanguard Atlantic Ltd.
Review of "Application of GPSS V to Discrete Systems Simulation, by Geoffrey Gordon", Prentice-Hall, 1975
Venue: ACM SIGSIM Simulation Digest (1976)

This volume is supposed to be compact enough for a single semester course and can be used without a GPSS manual. In its slightly less than 400 pages, the author packs in a substantial amount of information. After an introduction to the general principles of simulation, the author has provided detailed chapters to illustrate various major components of the GPSS language, such as storages and facilities, priority, creating and moving transaction in the system, preempting methods, statistical units, etc. 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
Adaptive Low-Complexity Erasure-Correcting Code-Based Protocols for QoS-Driven Mobile Multicast Services
Authors: Qinghe Du, Xi Zhang
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

We propose an adaptive hybrid ARQ-FEC erasurecorrecting scheme for QoS-driven mobile multicast services over wireless networks. The main features of our proposed scheme include: the low-complexity and dynamic adaptation to the variations of packet-loss levels and QoS-requirements. The low complexity is achieved by using the graph-code with linear time-complexity. To support diverse QoS-requirements and improve the error-control efficiency, we develop the twodimensional adaptive error-control scheme, which dynamically adjusts not only the error-control redundancy, but also the codemapping structure. By deriving and identifying the closed-form non-linear expressions for the optimal check-node degree and the required error-control redundancy in each adaptation step as the functions of the packet-loss level, we propose the non-uniformed two-dimensional adaptive coding scheme. Using this scheme, we develop an efficient hybrid ARQ-FEC protocol for mobile multicast services with diverse QoS requirements. Also conducted is a set of numerical and simulation results which analyze and compare our proposed adaptive scheme with those using the non-adaptive graph codes, Reed-Solomon Erasure codes, and pure ARQ-based approach. The simulation results show that our proposed scheme can efficiently support QoS-driven mobile multicast services and achieve well-balanced error-control redundancy while imposing low error-control complexity and overhead for mobile multicast services over wireless networks.
A Dynamic Dictionary for Priced Information with Application
Authors: Anil Maheshwari, Michiel Smid
Venue: Algorithmica (2006)

In this paper we design a dynamic dictionary for the priced information model initiated by Charikar et al. Assume that a set S consisting of n elements is given such that each element has an associated price, a positive real number. The cost of performing an operation on elements of S is a function of their prices. The cost of an algorithm is the sum of the costs of all operations it performs. The objective is to design algorithms which incur low cost. In this model we propose a dynamic dictionary, supporting search, insert and delete, for keys drawn from a linearly ordered set. As an application we show that the dictionary can be used in computing the trapezoidal map of a set of line segments, a fundamental problem in computational geometry.
Structured Noncommutative Multidimensional Linear Systems
Authors: Joseph A. Ball, Gilbert Groenewald, Tanit Malakorn
Venue: SIAM Journal on Control and Optimization (2005)

We introduce a class of multidimensional linear systems with evolution along a free semigroup. The transfer function for such a system is a formal power series in noncommuting indeterminates. Standard system-theoretic properties (the operations of cascade/parallel connection and inversion, controllability, observability, Kalman decomposition, state-space similarity theorem, minimal state-space realizations, Hankel operators, realization theory) are developed for this class of systems. We also draw out the connections with the much earlier studied theory of rational and recognizable formal power series. Applications include linear-fractional models for classical discrete-time systems with structured, time-varying uncertainty, dimensionless formulas in robust control, multiscale systems and automata theory, and the theory of formal languages.
Car License Plate Recognition through Hausdorff Distance Technique
Authors: Ratree Juntanasub, Nidapan Sureerattanan
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Many researches have been done on car license plate (CLP) recognition. However, these are no sufficient number of works on Thai CLP. The existing works on Thai CLP have been focused on localization, extraction, and partial recognition (only for upper line) of the license plate. Generally, Thai CLP has 2 lines (upper and lower). The upper line presents character category in 2-position formatted, following by running number (up to 4 digits). The lower line presents province name. Recognition of the lower line is a difficult task because Thai words can be composed of 4 levels (top level, above level, base line and below level). Hence, appearance of noises in the original image easily causes misrecognition. This paper presents an approach to recognize off-line entire Thai CLP using Hausdorff Distance technique (HD) for similarity measurement. The recognition rate obtained by the proposed method is 92%.
Dynamically configurable shared CMP helper engines for improved performance
Authors: Anahita Shayesteh, Glenn Reinman, Norman Jouppi, Suleyman Sair, Tim Sherwood
Venue: ACM SIGARCH Computer Architecture News (2005)

Technology scaling trends have forced designers to consider alternatives to deeply pipelining aggressive cores with large amounts of performance accelerating hardware. One alternative is a small, simple core that can be augmented with latency tolerant helper engines. As the demands placed on the processor core varies between applications, and even between phases of an application, the benefit seen from any set of helper engines will vary tremendously. If there is a single core, these auxiliary structures can be turned on and off dynamically to tune the energy/performance of the machine to the needs of the running application.As more of the processor is broken down into helper engines, and as we add more and more cores onto a single chip which can potentially share helpers, the decisions that are made about these structures become increasingly important. In this paper we describe the need for methods that effectively manage these helper engines. Our counter-based approach can dynamically turn off 3 helpers on average, while staying within 2% of the performance when running with all helpers. In a multicore environment, our intelligent and flexible sharing of helper engines, provides an average 24% speedup over static sharing in conjoined cores. Furthermore we show benefit from constructively sharing helper engines among multiple cores running the same application.
Ef.cient Texture Mapping Using Minimum Cut
Authors: Jun Yue, Wanjun Jin, Wenbin Chen, I-fan Shen
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

In this paper, we present a method for texturing arbitrary surface using minimum cut algorithm. This method is a general texturing method, where the user provides a 3D mesh and a texture sample, and gets the textured mesh as the output. Our method is very simple. We repeatedly paste texture patches onto the surface, which is segmented from a sample image. If a certain patch overlaps a part of textured surface, we use minimum cut algorithm to find out a stitching path that makes this patch fit the textured surface. We repeat this process until the whole surface has been textured. As this method is a patch-by-patch method, the computation cost is much lower than many other methods.
High performance spatial data mining: scalable methods for spatial autoregression
Authors: David J. Lilja, Shashi Shekhar
Venue:  (2005)

Explosive growth in the size of spatial databases has highlighted the need for spatial data mining techniques to mine the interesting but implicit spatial patterns within these large databases. This thesis deals with reducing the computational complexity of the exact and approximate spatial autoregression (SAR) model solutions. Estimation of the parameters of the SAR model using Maximum Likelihood (ML) theory is computationally very expensive because of the need to compute the logarithm of the determinant (log-det) of a large matrix in the log-likelihood function. The first part of the thesis introduces theory on SAR model solutions. The second part applies parallel processing techniques to the exact SAR model solutions. We proposed parallel formulations of the SAR model parameter estimation procedure based on ML theory using data parallelism with load-balancing techniques. Although this parallel implementation showed scalability up to eight processors, the exact SAR model solution still suffers from high computational complexity and memory requirements. These limitations have led us to investigate serial and parallel approximate solutions for SAR model parameter estimation. In the third part of the thesis, we present two candidate approximate-semi-sparse solutions of the SAR model based on Taylor's Series expansion and Chebyshev Polynomials. We showed that the differences between exact and approximate SAR parameter estimates have no significant effect on the prediction accuracy. We developed a new ML based approximate SAR model solution and its variants in the next part of the thesis. The new approximate SAR model solution is called the Gauss-Lanczos approximated SAR model solution. We algebraically rank the error of the Chebyshev Polynomial approximation, Taylor's Series approximation and the Gauss-Lanczos approximation to the solution of the SAR model and its variants. In other words, we established a novel relationship between the error in the log-det term; which is the approximated term in the concentrated log-likelihood function and the error in estimating the SAR parameter &rho; for all of the approximate model solutions. In the last part of the thesis, we present a faster, scalable and novel prediction and estimation technique for the exact SAR model solution (NORTHSTAR). We provide a proof of the correctness of ML based SAR model solutions by showing the objective function to be uni-modular.
Neural network classification of late gamma band electroencephalogram features
Authors: R. Ravi, Ramaswamy Palaniappan
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

This paper investigates the feasibility of using neural network (NN) and late gamma band (LGB) electroencephalogram (EEG) features extracted from the brain to identify the individuality of subjects. The EEG signals were recorded using 61 active electrodes located on the scalp while the subjects perceived a single picture. LGB EEG signals occur with jittering latency of above 280&#x00a0;ms and are not time-locked to the triggering stimuli. Therefore, LGB EEG could only be computed from single trials of EEG signals and the common method of averaging across trials to remove undesired background EEG (i.e. noise) is not possible. Here, principal component analysis has been used to extract single trials of EEG signals. Zero phase Butterworth filter and Parseval&#x2019;s time-frequency equivalence theorem were used to compute the LGB EEG features. These features were then classified by backpropagation and simplified fuzzy ARTMAP NNs into different categories that represent the individuality of the subjects. The results using a tenfold cross validation scheme gave a maximum classification of 97.33% when tested on 800 unseen LGB EEG features from 40 subjects. This pilot investigation showed that the method of identifying the individuality of subjects using NN classification of LGB EEG features is worth further study.
In Search of the System Concept
Authors: Olly Gotel
Venue: IEEE Software (2006)

Constructing and managing requirements documents can be both boring and difficult, and often they're not ideal for mediating communication between stakeholders during software development. Using a system concept--an explicit, compelling vision of what a project is all aboutcan simplify how you determine, handle, and communicate requirements in a busy world. They could even help you design more innovative software systems.
$L^\infty$-Estimates for Approximated Optimal Control Problems
Authors: C. Meyer, A. Rösch
Venue: SIAM Journal on Control and Optimization (2005)

An optimal control problem for a two-dimensional elliptic equation is investigated with pointwise control constraints. This paper is concerned with discretization of the control by piecewise linear functions. The state and the adjoint state are discretized by linear finite elements. Approximation of order $h$ in the $L^\infty$-norm is proved in the main result.