ppxscal/embedding_network huggingface dataset:
Bagging Evolutionary Feature Extraction Algorithm for Classification
Authors: Tianwen Zhao, Qijun Zhao, Hongtao Lu, David Zhang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Feature extraction is significant for pattern analysis and classification. Those based on genetic algorithms are promising owing to their potential parallelizability and possible applications in large scale and high dimensional data classification. Most recently, Zhao et al. presented a direct evolutionary feature extraction algorithm(DEFE) which can reduce the space complexity and improve the efficiency, thus overcoming the limitations of many genetic algorithm based feature extraction algorithms(EFE). However, DEFE does not consider the outlier problem which could deteriorate the classification performance, especially when the training sample set is small. Moreover, when there are many classes, the null space of within-class scatter matrix(Sw) becomes small, resulting in poor discrimination performance in that space. In this paper, we propose a bagging evolutionary feature extraction algorithm(BEFE) incorporating bagging into a revised DEFE algorithm to improve the DEFE's performance in cases of small training sets and large number of classes. The proposed algorithm has been applied to face recognition and testified using the Yale and ORL face databases.
Fast and Low Cost HW Bit Map for Memory Test Based on Residue Polynomial System over GF(2)
Authors: Jochen Rivoir
Venue: Proceedings of the 16th Asian Test Symposium (2007)

At-speed memory test demands increasing address rates from ATE bit maps. Today, the effective address rate is multiplied using multiple costly time-interleaved bit map copies. For the first time, address permutation is investigated for memory test in an attempt to multiply the address rate without increasing the overall memory size. However all published schemes create conflicts for some addresses sequences or require too many memories. This paper introduces a novel address partitioning scheme for arbitrarily few memories M = 2ì at the expense of an increased buffer per memory. For relevant address sequences which are based on powers of two, analytical considerations and exhaustive simulations prove that the effective address rate is increased by a factor of M , with zero memory size overhead.
The frequency and voltage dependent electrical characteristics of Al-TiW-Pd2Si/n-Si structure using I-V, C-V and G/ω-V measurements
Authors: İ. M. Afandiyeva, İ. Dökme, Ş. Altındal, L. K. Abdullayeva, Sh. G. Askerov
Venue: Microelectronic Engineering (2008)

The forward and reverse bias capacitance-voltage (C-V) and conductance-voltage (G/w-V) characteristics of Al-TiW-Pd"2Si/n-Si structures have been investigated over a wide frequency range of 5kHz-5MHz. These measurements allow to us the determination of the interface states density (N"s"s) and series resistance (R"s) distribution profile. The effect of R"s on C and G is found noticeable at high frequencies. The C-V-f and G/w-V-f characteristics of studied structures show fairly large frequency dispersion especially at low frequencies due to N"s"s in equilibrium with the semiconductor. The N"s"s profile was obtained both forward bias current-voltage (I-V) characteristics by using into account the bias dependent of the ideality factor and effective barrier height (@F"e) and low frequency (C"L"F)-high frequency (C"H"F) method. The plot of series resistance vs. voltage for the low frequencies gives a peak, decreasing with increasing frequencies. The frequency dependent C-V and G/w-V characteristics confirm that the R"s and N"s"s of the Al-TiW-Pd"2Si/n-Si structures are important parameters that strongly influence the electric parameters in device.
A KFCM-Based Fuzzy Classifier
Authors: Aimin Yang, Lingmin Jiang, Yongmei Zhou
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

A proposed KFCM-based fuzzy classifier was introduced. As for the process of constructing such classifier, firstly, the original sample space is mapped into a high dimensional feature space by selecting appropriate kernel function. Then in the feature space, training samples of each class are divided into some clusters by proposed KFCM algorithm. The optimal cluster number of every class is selected by our proposed method. For each created cluster, a fuzzy rule is defined with ellipsoidal regions. Finally, fuzzy classification rules are adjusted by GAs. The accuracy of the constructed classifier by our proposed methods are comparable to the maximum accuracy of the multilayer neural network classifier and the relational reference,and the training time is much shorter.
DpRouter: A Fast and Accurate Dynamic-Pattern-Based Global Routing Algorithm
Authors: Zhen Cao, Tong Jing, Jinjun Xiong, Yu Hu, Lei He, Xianlong Hong
Venue: Proceedings of the 2007 Asia and South Pacific Design Automation Conference (2007)

This paper presents a fast and accurate global routing algorithm, DpRouter, based on two efficient techniques: (1) dynamic pattern routing (Dpr), and (2) segment movement. These two techniques enable DpRouter to explore large solution space to achieve better routability with low time complexity. Compared with the state-of-the-arts, experimental results show that we consistently obtain better routing quality in terms of both congestion and wire length, while simultaneously achieving a more than 30x runtime speedup. We envision that this algorithm can be further leveraged in other routing applications, such as FPGA routing.
Model checking the probabilistic pi-calculus
Authors: Gethin Norman, Catuscia Palamidessi, David Parker, Peng Wu
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

We present an implementation of model checking for the probabilistic \pi-calculus, a process algebra which supports modelling of concurrency, mobility and discrete probabilistic behaviour. Formal verification techniques for this calculus have clear applications in several domains, including mobile ad-hoc network protocols and random security protocols. Despite this, no implementation of automated verification exists. Building upon the (non-probabilistic) \pi- calculus model checker MMC, we first show an automated procedure for constructing the Markov decision process representing a probabilistic \pi-calculus process. This can then be verified using existing probabilistic model checkers such as PRISM. Secondly, we demonstrate how for a large class of systems a more efficient, compositional approach can be applied, which uses our extension of MMC on each parallel component of the system and then translates the results into a high-level model description for the PRISM tool. The feasibility of our techniques is demonstrated through three case studies from the \pi-calculus literature.
A New Fuzzy Modeling Approach Based on Support Vector Regression
Authors: Long Yu, Jian Xiao, Yifeng Bai
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

New interpretable kernels created by conjoining the univariate fuzzy membership functions with a t-norm operator are proposed in this paper. Based on support vector regression with presented kernel, a learning algorithm consisting of two phases is developed to construct fuzzy system. In the first phase, the support vector regression learning model provides architecture to extract support vectors for generating fuzzy rules, and then characterizes the support vector expansion in TS fuzzy inference procedure through simple equivalent transform. In the second phase, a reduced set method is employed to simplify the obtained fuzzy model, and a bottom-up strategy with relative degree of sharing is suggested to obtain a transparent rule base, at the same time preserves the accuracy and generalization performance of the fuzzy model. Finally, the performance of the proposed fuzzy model is compared with hierarchical clustering based on using a self-organizing network modeling methods.
A New Data Hiding Scheme with Quality Control for Binary Images Using Block Parity
Authors: M. Venkatesan, P. Meenakshi Devi, K. Duraiswamy, K. Thiagarajah
Venue: Proceedings of the Third International Symposium on Information Assurance and Security (2007)

Data hiding is usually achieved by alternating some nonessential information in the host message. A more challenging problem is to hide data in a two -- color binary image. Hiding is difficult for the binary image since each of its black or white pixels requires only one bit representation. So that, changing a pixel can be easily detected. In this paper, we propose a new data hiding scheme using the parity of blocks. The original image is partitioned into m x n blocks. The new scheme ensures that for any bit that is modified in the host image, the bit must be adjacent to another bit that has the same value as the former's new value. Thus, the existence of secret information in the host image is difficult to detect. The invisible effect will be achieved by sacrificing some data hiding space, but the new scheme still offers a good data hiding ratio. Specifically, for each m x n block of host image, we will hide one bit of secret data by changing either one bit or without changing any bits in the block.
Multiple Positive Solutions for Second Order m-Point Boundary Value Problems
Authors: Zhenfeng Gao, Yunhai Wang, Yanping Guo
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

In this paper, the second order m-point boundary value problem {u"(t) + a(t)u'(t) + f(t,u) = 0, 0\leqslant t \leqslant 1,u' (0) - \sum\limits_{i = 1}^{m - 2} {k_i u'\left( {\xi _i } \right)}= 0, u(1) = 0 is studied, where k_i \ge 0(i = 1, 2,...,m-2), 0 \le \xi_1 \le \xi_2 \le \cdot \cdot \cdot \le \xi_{m-2} \le 1. We obtain the existence of at least three positive solutions by using the Leggett-Williams fixed point theorem and the properties.
Prepositional phrase attachment without oracles
Authors: Michaela Atterer, Hinrich Schütze
Venue: Computational Linguistics (2007)

Work on prepositional phrase (PP) attachment resolution generally assumes that there is an oracle that provides the two hypothesized structures that we want to choose between. The information that there are two possible attachment sites and the information about the lexical heads of those phrases is usually extracted from gold-standard parse trees. We show that the performance of reattachment methods is higher with such an oracle than without. Because oracles are not available in NLP applications, this indicates that the current evaluation methodology for PP attachment does not produce realistic performance numbers. We argue that PP attachment should not be evaluated in isolation, but instead as an integral component of a parsing system, without using information from the gold-standard oracle.
Study on the Web Service Composition and Connection Patterns
Authors: Sang-Yong Byun
Venue: Proceedings of the 5th ACIS International Conference on Software Engineering Research, Management & Applications (2007)

Web service technology is a component-oriented SOAP based interoperable technology widely used in enterprise application to application (A2A), business to business (B2B), and EAI. Web Service component composite and connection models are the key issues to make web service successful in the future. This paper presents a number of web service compositions and connection patterns which will facilitate the web service design.
Decision Support with EMPEROR
Authors: Michele A. Shaw, Raimund L. Feldmann, Forrest Shull
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

Selecting the right practice or technology for a given task should be based on the project goals and context. The selection process should be supported by empirical evidence and experiences with the practice in similar contexts [1]. Practitioners, however, usually do not have the time to search for existing empirical studies and to evaluate them in detail. A more centralized and practice-oriented approach is necessary to provide the required information in a convenient way. EMPEROR (Experience Management Portal using Empirical Results as Organizational Resources) was developed to address this issue.
Tool support for the compile-time execution structure of object-oriented programs with ownership annotations
Authors: Marwan Abi-Antoun, Jonathan Aldrich
Venue: Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering (2007)

Ownership domain annotations enable obtaining at compile-time the system's execution structure from the annotated program. The execution structure is sound, hierarchical (and thus more scalable) and conveys more design intent than flat object graphs obtained by existing static analyses that do not rely on annotations.
Toward EventWeb
Authors: Ramesh Jain
Venue: IEEE Distributed Systems Online (2007)

This keynote lecture by Ramesh Jain, given at PerCom 2007, presents the history of the World Wide Web and its evolution into a web of documents, discussing the current need for an EventWeb, or web of events.
Short Note: How to normalize Maxwell-Boltzmann electrons in transient plasma models
Authors: G. J. M. Hagelaar
Venue: Journal of Computational Physics (2007)

Proper normalization of a Maxwell-Boltzmann electron distribution in transient plasma models requires the self-consistent calculation of a reference density from a global electron conservation equation. This calculation tends to produce numerical oscillations in the time evolution of the plasma, in particular during the formation of the plasma sheath. The present paper proposes a simple numerical scheme to prevent these oscillations by artificial critical damping, which makes it possible to simulate transient plasma phenomena without electron-related time step conditions.
A robust and flexible model of hierarchical self-organizing maps for non-stationary environments
Authors: R. Salas, S. Moreno, H. Allende, C. Moraga
Venue: Neurocomputing (2007)

In this paper we extend the hierarchical self-organizing maps model (HSOM) to address the problem of learning topological drift under non-stationary and noisy environments. The new model, called robust and flexible hierarchical self-organizing maps (RoFlex-HSOM), combines the capabilities of robustness against noise and the flexibility to adapt to the changing environment. The RoFlex-HSOM model consists of a hierarchical tree structure of growing self-organizing maps (SOMs) that adapts its architecture based on the data. The model preserves the topology mapping from the high-dimensional time-dependent input space onto a neuron position in a low-dimensional hierarchical output space grid. Furthermore, the RoFlex-HSOM algorithm has the plasticity to track and adapt to the topological drift, it gradually forgets (but no catastrophically) previous learned patterns and it is resistant to the presence of noise. We empirically show the capabilities of our model with experimental results using synthetic sequential data sets and the ''El Nino'' real world data.
EDACluster: an Evolutionary Density and Grid-Based Clustering Algorithm
Authors: Cesar S. de Oliveira, Paulo Igor Godinho, Aruanda S. G. Meiguins, Bianchi S. Meiguins, Alex A. Freitas
Venue: Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications (2007)

This paper presents EDACluster, an Estimation of Distribution Algorithm (EDA) applied to the clustering task. EDA is an Evolutionary Algorithm used here to optimize the search for adequate clusters when very little is known about the target dataset. The proposed algorithm uses a mixed approach density and grid- based to identify sets of dense cells in the dataset. The output is a list of items and their associated clusters. Items in low-density areas are considered noise and are not assigned to any cluster. This work uses four public domain datasets to perform the tests that compare EDACluster with DBSCAN, a conventional density-based clustering algorithm.
A Model of Recoverability in Multilevel Systems
Authors: T. Anderson
Venue: IEEE Transactions on Software Engineering (1978)

Backward error recovery (that is, resetting an erroneous state of a system to a previous error-free state) is an important general technique for recovery from faults in a system, especially those faults which were not foreseen. However, the provision of backward error recovery can be complex, particularly if the implementation of the system is "multilever" and recovery is to be provided at a number of these levels. This paper discusses two distinct categories of multilevel system, and then examines in detail the issues involved in providing backward error recovery in both types of system.
The Concept of Coverage and Its Effect on the Reliability Model of a Repairable System
Authors: T. F. Arnold
Venue: IEEE Transactions on Computers (1973)

Duplication is a technique frequently employed to achieve high reliability for a repairable system. Although the philosophy of duplication is that it takes two faults to place a system out of service, there are generally some critical single faults that cause a system failure. This paper considers the effect of such a set of faults on a repairable system's reliability. It is shown that even a small number of such faults may severely degrade the mean time to system failure and the expected downtime for an otherwise highly reliable system.
Fixed-effect variable selection in linear mixed models using R2 statistics
Authors: Jean G. Orelien, Lloyd J. Edwards
Venue: Computational Statistics Data Analysis (2008)

In the linear mixed model (LMM), several R^2 statistics have been proposed for assessing the goodness-of-fit of fixed effects. However, the performance of these statistics has not been fully demonstrated either analytically or through simulations. We report results of simulations to asses the ability of these statistics to select the most parsimonious model. R^2 statistics from a full model were compared to other models in which fixed-effect covariates were removed. The full model was also compared to an overfitted model that included additional covariates not linked to the outcome. All models compared involved the same random effects. In this paper, we show that R^2 statistics that involve the residuals are unable to adequately discriminate between the correct model and one from which important fixed-effect covariates are omitted if the computation of the predicted values for the residuals included the random effects (referred to as conditional R^2 statistics). However, if the random effects are excluded from the computation of the predicted values that lead to the residuals, these R^2 statistics (referred to as marginal R^2 statistics) are able to select the most parsimonious model. Other R^2 statistics that have been proposed by Xu [2003. Measuring explained variation in linear mixed effects models. Statist. Med. 22(22), 3527-3541] performed poorly in that there was little variation in the value of these statistics from a full model to a reduced model.
Node-searching problem on block graphs
Authors: Hsin-Hung Chou, Ming-Tat Ko, Chin-Wen Ho, Gen-Huey Chen
Venue: Discrete Applied Mathematics (2008)

The node-searching problem, introduced by Kirousis and Papadimitriou, is equivalent to several important problems, such as the interval thickness problem, the path-width problem, the vertex separation problem, and so on. In this paper, we generalize the avenue concept, originally proposed for trees, to block graphs whereby we design an efficient algorithm for computing both the search numbers and optimal search strategies for block graphs. It answers the question proposed by Peng et al. of whether the node-searching problem on block graphs can be solved in polynomial time.
Petascale Computing Research Challenges - A Manycore Perspective
Authors: Steve Pawlowski
Venue: Proceedings of the 2007 IEEE 13th International Symposium on High Performance Computer Architecture (2007)

Future High Performance Computing will undoubtedly reach Petascale and beyond. Today's HPC is tomorrow's Personal Computing. What are the evolving processor architectures towards Multi-core and Many-core for the best performance per watt; memory bandwidth solutions to feed the ever more powerful processors; intra-chip interconnect options for optimal bandwidth vs. power? With Moore's Law continuing to prove its viability and shrinking transistors' geometry, improving reliability is even more challenging. Intel Senior Fellow and Chief Technology Officer of Intel's Digital Enterprise Group, Steve Pawlowski, will provide his technology vision, insight and research challenges to achieve the vision of Petascale computing and beyond.
FPGA accelerator for real-time skin segmentation
Authors: B. de Ruijsscher, G. N. Gaydadjiev
Venue: Proceedings of the 2006 IEEE/ACM/IFIP Workshop on Embedded Systems for Real Time Multimedia (2006)

Many real-time image processing applications are confronted with performance limitations when implemented in software. The skin segmentation algorithm utilized in hand gesture recognition as developed by the ICT department of Delft University of Technology presents an example of such an application. This paper presents the design of an FPGA based accelerator which alleviates the host PC's computational effort required for real-time skin segmentation. We show that our design utilizes no more than 88% of the resources available within the targeted XC2VP30 device. In addition, the proposed approach is highly portable and not limited to the considered real-time image processing algorithm only
Bayesian Estimation of Follower and Leader Vehicle Poses with a Virtual Trailer Link Model
Authors: Teck Chew Ng, Martin Adams, Javier Ibañez-Guzmán
Venue: International Journal of Robotics Research (2008)

Autonomous Vehicle Following can be achieved if the poses of both the follower and leader vehicles are continuously estimated. This can be achieved by using a Bayesian estimation technique together with a virtual trailer link model. The advantage of such a model is that the follower vehicle will trail a virtual trailer, modeled as an attachment to the leader vehicle, instead of the leader vehicle itself, so that a safe spacing between the two vehicles is guaranteed. The key to a tractable solution to this vehicle following problem is the justifiable assumption that the pose of the follower vehicle is statistically independent of that of the leader. This assumption is valid when conditioned on the history of the follower vehicle's inputs and the sensor observations made by the follower vehicle. Hence, a factored solution to the joint estimate of the follower and leader poses can be formulated. Due to the factored solution, the pose of the follower vehicle is estimated separately using a recursive estimator. In a separate estimator, the poses of the virtual tailer and the leader vehicle are augmented in the tracking process of the leader vehicle. The aim is to command the follower vehicle to trail the estimated pose of the virtual trailer link model. The pose of the virtual trailer is computed with an on-board sensor mounted on the follower vehicle. A case study on the implementation of the proposed formulation, using an Extended Kalman Filter as the main estimator, is presented. First, simulation results are presented. To make the simulation results comparable to the actual system, the variances of sensor measurements are set according to real sensor data-sheet values. Various types of vehicle maneuver, such as straight paths and clothoids with left and right transition paths, are considered. Real experiments are also carried out in a car park. A comparison of the estimated paths and the best available ground truth is presented. The path deviations of the proposed system are also compared with similar systems in the literature.