ppxscal/embedding_network huggingface dataset:
Multiple power-gating domain (multi-VGND) architecture for improved leakage power reduction
Authors: Ashoka Sathanur, Luca Benini, Alberto Macii, Enrico Macii, Massimo Poncino
Venue: Proceeding of the 13th international symposium on Low power electronics and design (2008)

Row-based power-gating has recently emerged as a meet-in-the-middle sleep transistor insertion paradigm between cell-level and block-level granularity, in which each layout row defines the unit of gating, and different rows can be clustered and share the same sleep transistor. Previous works, however, assume the availability of a single virtual ground voltage, thus making the decision of whether to gate or not a given cluster a binary choice: a cluster is either gated or not. In this work, we consider a limited set of virtual ground voltages, which allows us to assign to a cluster the virtual ground voltage that offers the best leakage-performance tradeoff for that cluster. We propose two algorithms for solving two power-gating variants: one in which the entire design is gated (given an allowable delay degradation), and another one in which only a subset of the rows is gated (given an allowable delay degradation and sleep transistor area). Our algorithm automatically finds the set of clusters with optimal virtual ground voltages so as to minimize leakage while respecting timing and area constraints. The number of power-gating domains can be user-bounded, in accordance with power grid or library characterization limitations. Results show that multiple virtual ground allow to improve by more than 34% over existing solutions that gate the entire design, and provide sizable savings also for the case of partial power-gating.
A nonmonotone trust-region method of conic model for unconstrained optimization
Authors: Shao-Jian Qu, Ke-Cun Zhang, Jian Zhang
Venue: Journal of Computational and Applied Mathematics (2008)

In this paper, we present a nonmonotone trust-region method of conic model for unconstrained optimization. The new method combines a new trust-region subproblem of conic model proposed in [Y. Ji, S.J. Qu, Y.J. Wang, H.M. Li, A conic trust-region method for optimization with nonlinear equality and inequality 4 constrains via active-set strategy, Appl. Math. Comput. 183 (2006) 217-231] with a nonmonotone technique for solving unconstrained optimization. The local and global convergence properties are proved under reasonable assumptions. Numerical experiments are conducted to compare this method with the method of [Y. Ji, S.J. Qu, Y.J. Wang, H.M. Li, A conic trust-region method for optimization with nonlinear equality and inequality 4 constrains via active-set strategy, Appl. Math. Comput. 183 (2006) 217-231].
Performance Analysis of Heuristic Algorithms for Lifetime-Aware Directional Multicasting in Wireless Ad Hoc Networks
Authors: Song Guo, Mianxiong Dong, Minyi Guo
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

WANET (Wireless Ad-hoc Network) is expected to be deployed in a wide range of civil and military applications. The communicating nodes in these networks might be distributed randomly and are assumed to have packet-forwarding capability in order to communicate with each other over a shared and limited radio channel. Building such networks usually poses a significant technical challenge because energy supplied by batteries is likely to be a scarce resource, and in some applications energy is entirely non-renewable. We consider the problem of maximizing the network lifetime for multicast communications in WANETs that use directional antennas. Recent research results have shown that it is NP problem. In order to provide a better understanding of the research challenges of the energy-aware multicast routing, this paper presents simulation based analysis to assess the performance of a group of state-of-the-art algorithms under various network configurations.
Undetected error probability of q-ary constant weight codes
Authors: Shu-Tao Xia, Fang-Wei Fu
Venue: Designs, Codes and Cryptography (2008)

In this paper, we introduce a new combinatorial invariant called q-binomial moment for q-ary constant weight codes. We derive a lower bound on the q-binomial moments and introduce a new combinatorial structure called generalized (s, t)-designs which could achieve the lower bounds. Moreover, we employ the q-binomial moments to study the undetected error probability of q-ary constant weight codes. A lower bound on the undetected error probability for q-ary constant weight codes is obtained. This lower bound extends and unifies the related results of Abdel-Ghaffar for q-ary codes and Xia-Fu-Ling for binary constant weight codes. Finally, some q-ary constant weight codes which achieve the lower bounds are found.
Equitable distribution energy consumption of wsns
Authors: Naif Abdo Alsharabi, LI Ren Fa, Maan Younis Abdullah, Fanzi Zeng
Venue: Proceeding of the 1st ACM international workshop on Foundations of wireless ad hoc and sensor networking and computing (2008)

Power consumption is the main challenge for expanding the wireless sensor network, since the active nodes are more vulnerable to energy consumption. How to save energy and extend the lifetime of wireless sensor networks imposes a great challenge addressed by this paper. This paper introduces the tasks of scheduling and distribution of roles dormant cells of wireless sensor network (TSDRDC) to curb excessive consumption of energy consumed in duplication and unhelpful tasks. Duplicate Dropping and Roles-Dormant Cells are proposed to achieve equitable distribution of energy consumption for all nodes on the network. Integrating the advantage of protocol existing LEACH with TSDRDC approach led to improve the formation of more homogenous clusters, better performance, and increased lifetimes of wireless sensor networks.
Efficiently learning linear-linear exponential family predictive representations of state
Authors: David Wingate, Satinder Singh
Venue: Proceedings of the 25th international conference on Machine learning (2008)

Exponential Family PSR (EFPSR) models capture stochastic dynamical systems by representing state as the parameters of an exponential family distribution over a shortterm window of future observations. They are appealing from a learning perspective because they are fully observed (meaning expressions for maximum likelihood do not involve hidden quantities), but are still expressive enough to both capture existing models and predict new models. While maximum-likelihood learning algorithms for EFPSRs exist, they are not computationally feasible. We present a new, computationally efficient, learning algorithm based on an approximate likelihood function. The algorithm can be interpreted as attempting to induce stationary distributions of observations, features and states which match their empirically observed counterparts. The approximate likelihood, and the idea of matching stationary distributions, may apply to other models.
Feature Extraction and Uncorrelated Discriminant Analysis for High-Dimensional Data
Authors: Wen-Hui Yang, Dao-Qing Dai, Hong Yan
Venue: IEEE Transactions on Knowledge and Data Engineering (2008)

High-dimensional data and small sample size problem occur in many modern pattern classification applications, such as face recognition and gene expression data analysis. To deal with such data, an important step is the dimensionality reduction. Principal component analysis(PCA) and between-group analysis(BGA) are two commonly used methods and various extensions exist. The principle of these two approaches comes from their best approximation. From a pattern recognition perspective we show that PCA based on total-scatter matrix preserves linear separability and BGA based on between-scatter matrix retains only the distances between class centroid. Moreover we propose a novel uncorrelated discriminant analysis (UDA) algorithm. It combines rank preserving dimensionality reduction and constraint discriminant analysis, and serves as a simple and complete solution for small sample size problem. We conduct a series of comparative study on face images and gene expression data sets to evaluate UDA in terms of classification accuracy and robustness.
A generic formal framework for protocol interoperability test and test cases minimization
Authors: Ning Zhong, Zun-wen He, Jing-ming Kuang
Venue: Proceedings of the 3rd international workshop on Automation of software test (2008)

A generic formal framework for protocol interoperability test is proposed, which consider the common situation of protocol interoperability test by introducing the multi-stimuli principle in the multi-port FSM. A novel interoperability test sequences minimization scheme based on genetic algorithm (GA) is proposed to avoid the state space explosion problem, which easily occur in multi-stimuli systems during the interoperability test. Interoperability test sequences always contain two parts: interoperability part and local part. Conventional algorithms only remove redundancy from conformance test sequences and do not consider the redundant path relevant for interoperability part. During our work, the minimal-complete-coverage criterion and GA are applied to remove redundancy in both local transitions and interoperability transitions. Experiment results show that compare to conventional algorithm, our algorithm can avoid the state space explosion problem effectively and more practical for it can reduce the length of the test sequences and maintain the same transition coverage.
Decomposing large graphs with small graphs of high density
Authors: Raphael Yuster
Venue: Journal of Graph Theory (1999)

It is shown that for every positive integer h, and for every &egr; > 0, there are graphs H = )VH EH) with at least h vertices and with density at least 0.5 - &egr; with the following property: If G = (VG, EG) is any graph with minimum degree at least ${|V_{G}|}\over{2}$ (1 + o(1)) and |EH| divides |EG|, then G has an H-decomposition. This result extends the results of [R. M. Wilson, Cong Numer XV (1925), 647&ndash;659] [T. Gustavsson, Ph.D. Thesis, U. Stockholm, 1991] [R. Yuster, Random Struc Algorith, 12 (1998), 237&ndash;251]. &copy; 1999 John Wiley & Sons, Inc. J Graph Theory 32: 27&ndash;40, 1999 http:--www.math.tau.ac.il-&sim;raphy
An Embedded Computing Platform for Robot
Authors: Ching-Han Chen, Sz-Ting Liou
Venue: Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008) (2008)

As the robotic industry is growing boomingly, the functionalities and system's architecture of robots are more and more complex. The development of robotic application system becomes a time-consuming and difficult task. In this paper, we propose an embedded computing platform for intelligent robot, and then design a reliable real-time operating system (RTOS) on the platform for rapid developing intelligent robotic applications. The proposed embedded computing platform includes a reconfigurable 8-bits processor core and some robot-dedicated hardware intellectual property (IP) which can be generated and reconfigured easily. Based on the embedded processor core, a real-time OS, uC/OS-II, is ported to this platform. The RTOS is adjusted and optimized due to the robot-specific requirements and the hardware resources constrains. Finally, a simple example is applied to demonstrate the software/hardware (SW/HW) co-design flow based on the proposed platform.
Extraction of mean frequency information from Doppler blood flow signals using a matching pursuit algorithm
Authors: Xinling Shi, Baodan Bai, Yufeng Zhang, Huahong Ma, Jianhua Chen
Venue: Signal Processing (2008)

The intensity-weighted mean frequency (IWMF) waveform of Doppler blood flow signals associates with the instantaneous mean blood velocities and has been found to be very useful to measure volumetric flow and detect arterial stenosis. These applications involving Doppler signals require the accurate estimation of the IWMF over short durations of the signal due to its nonstationarity. The traditional short-time Fourier transform (STFT) method requires stationarity of the signal during a finite window, making it inaccurate to analyze signals having relatively wide bandwidths that change rapidly with time. In order to accurately estimate the Doppler IWMF waveform, even when the temporal flow velocity is rapid (high nonstationarity), we extract the Doppler IWMF waveform from the time-frequency distribution estimated using the matching pursuit (MP) with stochastic time-frequency dictionaries in the present study. Because of its local adaptivity to transient structures, the MP algorithm provides a remarkably compact time-frequency description and high time-frequency resolution of a signal. A comparative evaluation has been made between the classic (STFT-based) and the MP-based algorithms. Experimental results indicate that the Doppler IWMF waveform estimated using the MP with stochastic dictionaries is more accurate than that based on the STFT.
Chaos shift keying spread spectrum with multicarrier modulation for secure digital communication
Authors: Yuu-Seng Lau, Zahir M. Hussain
Venue: Proceedings of the 4th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision (2004)

Combining chaos shift keying (CSK) spread spectrum (SS) system with the multicarrier modulation (MCM) scheme, orthogonal frequency division multiplexing (OFDM), and wavelet-based OFDM is presented in this paper. A chaotic sequence for chaos shift keying (CSK) (that provides auto- and cross-correlation properties that are similar to those of random white noise) is used for spread spectrum systems. Due to its bifurcation behavior depending on the initial condition, the number of chaotic sequences that can be generated by a single formula is not restricted and will not repeat itself. These characteristics provide an increase in system capacity and security performances. On the other hand, multicarrier modulation provides an efficient way to modulate multiple data into multiplexed data streams with the inherent ability to combat impulsive and narrowband noise. However, conventional OFDM multicarrier modulation scheme suffers from peak-to-average power ratio (PAPR) problem. Extensive research on this direction had found that wavelet-based OFDM (WOFDM) can provide a superior spectral containment and a lower PAR that leads to performance gains. This paper presents a comprehensive performance study for chaos shift keying SS-OFDM (CSK-OFDM) and chaos shift keying SS-wavelet OFDM (CSK-WOFDM). Simulation showed that wavelet based multicarrier system will provide a better BER performance.
Low power passive equalizer optimization using tritonic step response
Authors: Ling Zhang, Wenjian Yu, Haikun Zhu, Alina Deutsch, George A. Katopis, Daniel M. Dreps, Ernest Kuh, Chung-Kuan Cheng
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

A low power passive equalizer using RL terminator is proposed and optimized in this work. The equalizer includes an inductor in series with the resistive terminator, which boosts high frequency components and therefore improves the interconnect bandwidth with little overhead on power consumption. An analytic estimation method for eye-opening and jitter based on tritonic step response is also introduced in this work, which enables the optimization procedure. Our experimental results show that our estimation method is accurate and a board level transmission line of 50cm wire length can achieve 15Gb/s data rate. With 15GHz frequency input, the power consumption of the equalizer is less than 2.5mW, and the total power is 5mW.
An online self-improved fuzzy filter and its applications
Authors: Zhengrong Li, Meng Joo Er
Venue: Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing (2003)

In this paper, an online self-improved fuzzy filter (OSFF) is proposed. It is based on radial-basis-function networks (RBFN) and implements the TSK fuzzy systems functionally. As a prominent feature of OSFF, the system is hierarchically constructed and self-improved in the training process with a novel online clustering strategy for structure identification. Moreover, the filter is adaptively tuned to be an optimal status by a hybrid sequential algorithm for parameters determination. In detail, the proposed OSFF system has the following features: (1) Hierarchical structure self-construction. There is no predetermination initially for OSFF, i.e., it is not necessary to determine the initial number of fuzzy rules and input data space clustering in advance. The fuzzy rules, i.e., the RBF neurons are generated automatically in training process under a proposed criterion, minimum firing strength (MFS). (2) Online clustering. Instead of selecting the centers and widths of membership functions arbitrarily, an online clustering method is applied to ensure the reasonable representation of input terms of an input variable. It not only ensures the proper feature representation, but also optimizes the structure of the filter by reducing the number of fuzzy rules. (3) All free parameters in the premise and consequence parts are online determined by a hybrid sequential algorithm without repeated computation to make real-time applications possible. The centers and widths of membership functions of an input variable are allocated initially in the scheme of structure identification and optimized in the scheme of parameters determination. The parameters in the consequent parts of OSFF are updated in each iteration by a sequential recursive algorithm. Due to the hybrid learning algorithm, low computation load and less memory requirements are achieved. Simulation results, compared with other similar approaches for some benchmark problems, show that the proposed OSFF system can tackle these problems with fewer fuzzy rules and obtain better or same accuracy with lower system resource requirements.
Software Metrics for Agile Software Development
Authors: Martin Kunz, Reiner R. Dumke, Niko Zenker
Venue: Proceedings of the 19th Australian Conference on Software Engineering (2008)

Agile Software Development Methods are nowadays widespread and accepted. From the Software Measurement point-of-view not all metrics and methods from conventional lifecycle models can be used without adaptation. Distinct techniques in agile software development like refactoring needs new approaches and quality models in the area of software measurement.Therefore this paper describes a quality model, distinct metrics and their implementation into a measurement tool for quality management in agile software development.
The Role of Deliberate Artificial Design Elements in Software Engineering Experiments
Authors: Jo Hannay, Magne Jørgensen
Venue: IEEE Transactions on Software Engineering (2008)

Increased realism in software engineering experiments is often promoted as an important means to increase generalizability and industrial relevance. In this context, artificiality, e.g., the use of constructed tasks in place of realistic tasks, is seen as a threat. In this article, we examine the opposite view, that deliberately introduced artificial design elements may increase knowledge gain and enhance both generalizability and relevance. In the first part of the article, we identify and evaluate arguments and examples in favor of, and against, deliberately introducing artificiality into software engineering experiments. In the second part of the article, we summarize a content analysis of articles reporting software engineering experiments published over the ten-year period 1993-2002. The analysis reveals a striving for realism and external validity, but little awareness of for what and when, various degrees of artificiality and realism are appropriate. We conclude that an increased awareness and deliberation in these respects is essential. However, arguments in favor of artificial design elements should not be used to justify studies that are badly designed or that have research questions of low relevance.
Multiple defect diagnosis using no assumptions on failing pattern characteristics
Authors: Xiaochun Yu, R. D. Shawn Blanton
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

We propose an effective multiple defect diagnosis methodology that does not depend on failing pattern characteristics. The methodology consists of a conservative defect site identification and elimination algorithm, and an innovative path-based defect site elimination technique. The search space of the diagnosis method does not grow exponentially with the number of defects in the circuit under diagnosis. Simulation experiments show that this method can effectively diagnose circuits that are affected by 10 or more faults that include multiple stuck-at, bridge and transistor stuck-open faults.
An Application of the (max, +) Algebra to Information Flow Security
Authors: Matthias Werner, Michael A. Jaeger, Helge Parzyjegla
Venue: Proceedings of the Seventh International Conference on Networking (2008)

Confidentiality is one of the most important topics in computer security research. In order to check and ensure confidentiality information flow models are widely used. These models support the specification of valid flows of information. Furthermore, they provide means to formally check whether a given system fulfills a certain security property within this model. In this paper, we propose an information flow model which accounts for different security concerns. In this model, each participant of the communication may have a different role and, thus, different clearance levels for each security concern. Moreover, we demonstrate the application of the maxplus Algebra to analyze the security of a given system and provide an algebraic check for the security property. This includes a method to derive assignments of security clearance levels that do not invalidate the system's security.
GECCO-2008 new contest problem!: solving Rubik's Cube ($1,000 prize)
Authors: Steven Armentrout
Venue: ACM SIGEVOlution (2007)

In conjunction with the 2008 Genetic and Evolutionary Computation Conference (GECCO), Parabon Computation, the leading on-demand computation utility, announced today that it will sponsor a $1,000 prize competition in which contestants are challenged to evolve a program that can solve an arbitrarily scrambled Rubik's Cube. The competition is designed to demonstrate the combined capability of two complementary computing technologies provided by Parabon Computation. The Origin(tm) Evolutionary SDK (software development kit) uses computer-based evolutionary processes to derive (evolve) desired results and the Frontier Grid Platform harnesses the computational power of thousands of computers to deliver supercomputing as a service.
Optimizing automatic abstraction refinement for generalized symbolic trajectory evaluation
Authors: Yan Chen, Fei Xie, Jin Yang
Venue: Proceedings of the 45th annual Design Automation Conference (2008)

In this paper, we present a suite of optimizations targeting automatic abstraction refinement for Generalized Symbolic Trajectory Evaluation (GSTE). We optimize both model refinement and spec refinement supported by AutoGSTE: a counterexample-guided refinement loop for GSTE. Experiments on a family of benchmark circuits have shown that our optimizations lead to major efficiency improvements in verification involving abstraction refinement.