ppxscal/embedding_network huggingface dataset:
Designing energy-efficient fetch engines
Authors: Kevin Skadron
Venue:  (2006)

This dissertation evaluates factors that affect the energy-efficiency of the fetch engine in a programmable uniprocessor. The central thesis is that branch prediction is one of the key factors affecting overall processor energy-efficiency. Cooling costs, extending battery life in mobile devices, and reducing utility costs for wall-powered systems, especially data centers are growing concerns. Therefore, better understanding the factors that affect overall processor energy-efficiency has become important for virtually all new processor designs. For a processor to be energy-efficient, power consumption and performance must be balanced. The fetch unit is key to the processor's execution efficiency because it predicts and fetches all the instructions sent to the execution units. When fetching is stalled, or following an incorrectly predicted path, the rest of the processor is unable to perform useful work (and continues to consume energy). Many different fetch engine designs have been proposed in the research community and understanding how the fetch organization affects the processor's overall energy-efficiency is essential. For example, previous research has shown that trace caches can yield significant improvement in instruction throughput, but it is unclear whether trace caches are more energy-efficient than traditional instruction caches. Similarly, branch predictors improve fetch bandwidth by increasing instruction-level parallelism (ILP), but their energy-efficiency has not previously been systematically evaluated. This dissertation systematically evaluates a large portion of the fetch engine design space for energy-efficiency, determines that branch prediction is one of the key factors affecting overall processor energy-efficiency, shows the challenges in making trace cache organizations energy-efficient, and develops an analytical methodology for evaluating branch predictor energy-efficiency. This analytical framework can help designers cull the design space much more quickly than simulation-based analysis techniques.
A Semi-empirical Model of Test Quality in Symmetric Testing: Application to Testing Java Card APIs
Authors: Arnaud Gotlieb, Patrick Bernard
Venue: Proceedings of the Sixth International Conference on Quality Software (2006)

In the smart card quality assurance field, Software Testing is the privileged way of increasing the confidence level in the implementation correctness. When testing Java Card application programming interfaces (APIs), the tester has to deal with the classical oracle problem, i.e. to find a way to evaluate the correctness of the computed output. In this paper, we report on an experience in testing methods of the Oberthur Card Systems Cosmo 32 RSA Java Card APIs by using the Symmetric Testing paradigm. This paradigm exploits user-defined symmetry properties of Java methods as test oracles. We propose an experimental environment that combines random testing and symmetry checking for (oncard) cross testing of several API methods. We develop a semi-empirical model (a model fed by experimental data) to help deciding when to stop testing and to assess test quality.
Detecting Policy Violations through Traffic Analysis
Authors: Jeffrey Horton, Rei Safavi-Naini
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

Restrictions are commonly placed on the permitted uses of network protocols in the interests of security. These restrictions can sometimes be difficult to enforce. As an example, a permitted protocol can be used as a carrier for another protocol not otherwise permitted. However, if the observable behaviour of the protocol exhibits differences between permitted and non-permitted uses, it is possible to detect inappropriate use. We consider SSH, the Secure Shell protocol. This is an encrypted protocol with several uses. We attempt firstly to classify SSH sessions according to some different types of traffic for which the sessions have been used, and secondly, given a policy that permits SSH use for interactive traffic, to identify when a session appears to have been used for some other purpose.
Design Patterns Usage in Peer-to-Peer Systems--An Empirical Analysis
Authors: Markus Aleksy, Axel Korthaus, Christian Seifried
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

In this paper, we present the results of an empirical analysis regarding the application and realization of established design patterns in existing peer-to-peer system implementations. Among the goals of our research were the identification of relevant design patterns that are particularly helpful and well suited for the implementation of peer-to-peer architectures and the discovery of potential shortfalls with respect to the capitalization on design patterns in that domain. We describe which design pattern realizations were encountered in the analyzed system implementations and how frequently they were applied, and finally we draw some conclusions from our findings.
MARGIN: Maximal Frequent Subgraph Mining
Authors: Lini T. Thomas, Satyanarayana R. Valluri, Kamalakar Karlapalem
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

The exponential number of possible subgraphsmakes the problem of frequent subgraph mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set of frequent subgraphs, thus providing ample scope for pruning. MARGIN is a maximal subgraph mining algorithm that moves among promising nodes of the search space along the "border" of the infrequent and frequent subgraphs. This drastically reduces the number of candidate patterns considered in the search space. Experimental results validate the efficiency and utility of the technique proposed.
Some Real Experiences in Developing Virtual Environments
Authors: Roberto Andreoli, Rosario De Chiara, Ugo Erra, Antonio Iannaccone, Fernando La Greca, Vittorio Scarano
Venue: Proceedings of the conference on Information Visualization (2006)

The paper presents some experiences in developing a virtual environment using a videogame engine. It provides the details and the caveats met during development, with particular attentions to the architectural reconstruction problem, the textures resolution and the programmability. Some considerations are also reported from an historical point of view, emphasizing the importance of virtual reconstructions, and from a psychological point of view stressing how a narrative context enhances the learning process.
Instance Selection and Feature Weighting Using Evolutionary Algorithms
Authors: Jose-Federico Ramirez-Cruz, Olac Fuentes, Vicente Alarcon-Aquino, Luciano Garcia-Banuelos
Venue: Proceedings of the 15th International Conference on Computing (2006)

Machine learning algorithms are commonly used in real-world applications for solving complex problems where it is difficult to get a mathematical model. The goal of machine learning algorithms is to learn an objective function from a set of training examples where each example is defined by a feature set. Regularly, real world applications have many examples with many features; however, the objective function depends on few of them. The presence of noisy examples or irrelevant features in a dataset degrades the performance of machine learning algorithms; such is the case of k-nearest neighbor machine learning algorithm (k-NN). Thus choosing good instance and feature subsets may improve the algorithm's performance. Evolutionary algorithms proved to be good techniques for finding solutions in a large solution space and to be stable in the presence of noise. In this work, we address the problem of instance selection and feature weighting for instance-based methods by means of a Genetic Algorithm (GA) and Evolution strategies (ES). We show that combining GA and ES with a k-NN algorithm can improve the predictive accuracy of the resulting classifier.
Subjectivity Categorization of Weblog with Part-of-Speech Based Smoothing
Authors: Shen Huang, Jian-Tao Sun, Xuanhui Wang, Hua-Jun Zeng, Zheng Chen
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

Experts from different domains try to mine users' comments on weblogs for different reasons such as politics or commerce. All these needs necessitate automatically distinguishing subjective weblog contents from objective ones, namely subjectivity categorization. Since weblogs contain various topics from different domains, limited training data can hardly cover all the topics and "unseen words" becomes a serious problem for categorization tasks. In this paper, Part-Of-Speech (POS) based smoothing is proposed to alleviate the "unseen words" problem. In conjunction with a naïve Bayes model constructed from limited training data, the probability of an unseen word in a new domain can be well smoothed by the probability of its POS result. Empirical studies on five datasets show that our approach consistently outperforms the basic naïve Bayes with Laplace smoothing. In a cross-domain experiment, our approach achieves 22.0% improvement in Macro F1 and 24.4% in Micro F1 over basic naïve Bayes. These verify that POS based smoothing can indeed benefit subjectivity categorization, especially in the cases with a large number of unseen words.
Localized algorithms for energy efficient topology in wireless ad hoc networks
Authors: Wen-Zhan Song, Yu Wang, Xiang-Yang Li, Ophir Frieder
Venue: Mobile Networks and Applications (2005)

Topology control in wireless ad hoc networks is to select a subgraph of the communication graph (when all nodes use their maximum transmission range) with some properties for energy conservation. In this paper, we propose two novel localized topology control methods for homogeneous wireless ad hoc networks.Our first method constructs a structure with the following attractive properties: power efficient, bounded node degree, and planar. Its power stretch factor is at most ρ=1/1-(2sin π/k)β, and each node only has to maintain at most k + 5 neighbors where the integer k > 6 is an adjustable parameter, and β is a real constant between 2 and 5 depending on the wireless transmission environment. It can be constructed and maintained locally and dynamically. Moreover, by assuming that the node ID and its position can be represented in O(log n) bits each for a wireless network of n nodes, we show that the structure can be constructed using at most 24n messages, where each message is O(log n) bits.Our second method improves the degree bound to k, relaxes the theoretical power spanning ratio to ρ = √2β/1-(2√2sin π/k)β, where k > 8 is an adjustable parameter, and keeps all other properties. We show that the second structure can be constructed using at most 3n messages, where each message has size of O (log n) bits.We also experimentally evaluate the performance of these new energy efficient network topologies. The theoretical results are corroborated by the simulations: these structures are more efficient in practice, compared with other known structures used in wireless ad hoc networks and are easier to construct. In addition, the power assignment based on our new structures shows low energy cost and small interference at each wireless node.
Multi-period robust capacity planning based on product and process simulations
Authors: Emre Kazancioglu, Kazuhiro Saitou
Venue: Proceedings of the 36th conference on Winter simulation (2004)

This paper presents a method for allocating production capacity among flexible and dedicated machines based on uncertain demand forecasts of products in a production portfolio. Given multiple scenarios of future demands with the associated probabilities, the method provides alternative capacity allocations by quantifying the expected values of the product quality and cost. The product quality is estimated as the total performance variations from the nominal design for each product in a portfolio. The production cost is estimated as the total annual equivalent of investment and operation costs for each production period. A multi-objective genetic algorithm is utilized to compute the Pareto-optimal capacity allocations that quantify the tradeoffs between the expected product quality and cost. Case studies on an automotive valvetrain production are presented, where, under the demand forecasts with low uncertainty, the allocation of flexible machines is encouraged only at production steps critical to quality and cost.
On Composing Stream Applications in Peer-to-Peer Environments
Authors: Xiaohui Gu, Klara Nahrstedt
Venue: IEEE Transactions on Parallel and Distributed Systems (2006)

Stream processing has become increasingly important as many emerging applications call for continuous real-time processing over data streams, such as voice-over-IP telephony, security surveillance, and sensor data analysis. In this paper, we propose a composable stream processing system for cooperative peer-to-peer environments. The system can dynamically select and compose stream processing elements located on different peers into user desired applications. We investigate multiple alternative approaches to composing stream applications: 1) global-state-based centralized versus local-state-based distributed algorithms for initially composing stream applications at setup phase. The centralized algorithm performs periodical global state maintenance while the distributed algorithm performs on-demand state collection. 2) Reactive versus proactive failure recovery schemes for maintaining composed stream applications during runtime. The reactive failure recovery algorithm dynamically recomposes a new stream application upon failures while the proactive approach maintains a number of backup compositions for failure recovery. We conduct both theoretical analysis and experimental evaluations to study the properties of different approaches. Our study illustrates the performance and overhead trade-offs among different design alternatives, which can provide important guidance for selecting proper algorithms to compose stream applications in cooperative peer-to-peer environments.
On the expected time for Herman's probabilistic self-stabilizing algorithm
Authors: Toshio Nakata
Venue: Theoretical Computer Science (2005)

In this article we investigate the expected time for Herman's probabilistic self-stabilizing algorithm in distributed systems: suppose that the number of identical processes in a unidirectional ring, say n, is odd and n ≥ 3. If the initial configuration of the ring is not "legitimate", that is, the number of tokens differs from one, then execution of the algorithm made up of synchronous probabilistic procedures with a local parameter 0 < r < 1 results in convergence to a legitimate configuration with a unique token (Herman's algorithm). We then show that the expected time of the convergence is less than ((π2-8)/8r(1-r))n2. Note that if r = ½ then it is bounded by 0.936n2. Moreover, there exists a configuration whose expected time is Θ(n2). The method of the proof is based on the analysis of coalescing random walks.
Minimum Entropy Control Algorithm for General Dynamic Stochastic Systems
Authors: Jianfang Jia, Taiyuan Liu, Hong Yue, Hong Wang
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In order to measure the uncertainty of the stochastic systems subjected to arbitrary noise disturbance instead of Gaussian white noise, the minimum entropy control of tracking errors for dynamic stochastic systems is presented in this paper. Different from conventional hypothesis, it is assumed that the system output and noise obey multi-to-one mapping, which is more general in the practical application. A controller design was described based on minimizing system output error entropy and a recursive optimization algorithm was set up for dynamic, non-Gaussian and nonlinear system. This approach only used the formula of the probability density function of the tracking error to calculate the controller and it did not need to know the style of the system model and the probability density function of noise, which often is difficult to measure in fact. An illustrative example is utilized to demonstrate the efficiency of the minimum entropy control algorithm and the approving simulation results have been gained.
Selecting the best system and determining a set of feasible systems
Authors: Demet Batur
Venue: Proceedings of the 37th conference on Winter simulation (2005)

We present two fully sequential indifference-zone procedures to select the best system from a number of competing simulated systems, where best is defined by maximum or minimum expected performance. These two procedures have parabolic continuation regions rather than triangular continuation regions employed in a number of papers. Our procedures find the best or near-best system with at least a pre-specified probability of correctness when basic observations are independent and identically normally distributed. They allow for unequal and unknown variances across systems and the use of common random numbers, and show moderate improvement compared to other existing fully sequential procedures with triangular continuation regions. We also present procedures for finding a set of feasible or near-feasible systems with some statistical guarantee among a finite number of simulated systems in the presence of stochastic constraints on secondary performance measures. The proposed procedures can handle a large number of systems and stochastic constraints.
A robust adaptive Capon beamforming
Authors: Liu Hongqing, Liao Guisheng Zhang Jie
Venue: Signal Processing (2006)

Adaptive beamforming suffers from performance degradation in the presence of mismatch between the actual and presumed array steering vector of the desired signal. We propose a novel approach to adaptive beamforming that is robust to array errors. The proposed method involves two steps: the first step is to estimate the actual steering vector of the desired signal, and the second is to obtain optimal weight by utilizing the estimated steering vector. Our method belongs to the class of diagonal loading, but the optimal amount of diagonal loading level can be precisely calculated based on the uncertainty set of the steering vector. Moreover, the proposed robust Capon beamforming has an explicit closed-form solution. Computer simulation results demonstrate its excellent performance.
Point-based methods for estimating the length of a parametric curve
Authors: Michael S. Floater, Atgeirr F. Rasmussen
Venue: Journal of Computational and Applied Mathematics (2006)

This paper studies a general method for estimating the length of a parametric curve using only samples of points. We show that by making a special choice of points, namely the Gauss-Lobatto nodes, we get higher orders of approximation, similar to the behaviour of Gauss quadrature, and we derive some explicit examples.
Effective Incremental Clustering for Duplicate Detection in Large Databases
Authors: Francesco Folino, Giuseppe Manco, Luigi Pontieri
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

We propose an incremental algorithm for discovering clusters of duplicate tuples in large databases. The core of the approach is the usage of an indexing technique which, for any newly arrived tuple ì, allows to efficiently retrieve a set of tuples in the database which are mostly similar to ì, and which are likely to refer to the same real-world entity which is associated with ì. The proposed index is based on a hashing approach which tends to assign similar objects to the same buckets. Empirical and analytical evaluation demonstrates that the proposed approach achieves satisfactory efficiency results, at the cost of low accuracy loss.
Modeling and analysis of vector-quantized M-channel subband codecs
Authors: I. Jee, R. A. Haddad
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1995. on International Conference - Volume 02 (1995)

This paper demonstrates that the scalar nonlinear gain-plus-additive noise quantization model can be used to represent each vector quantizer in an M-band subband codec. The validity and accuracy of this analytic model is confirmed by comparing the calculated model quantization errors with actual simulation of the optimum LBG vector quantizer. We compute the mean squared reconstruction error (MSE) which depends on N the number of entries in each codebook, k the length of each codeword, and on the filter bank coefficients. We form this MSE measure in terms of the equivalent scalar quantization model and find the optimum FIR filter coefficients for each channel in the M-band structure for a given bit rate, given filter length, and given input signal correlation model. Specific design examples are worked out for a 4-tap filter in a two-band paraunitary structure. Theoretical results are confirmed by extensive Monte Carlo simulation.
An odds-ratio indifference-zone selection procedure for Bernoulli populations
Authors: Jamie R. Wieland, Barry L. Nelson
Venue: Proceedings of the 36th conference on Winter simulation (2004)

We present a new sequential, eliminating procedure for selecting the best system in a single-factor Bernoulli-response experiment with an odds-ratio indifference zone, where best refers to the system with the largest probability of success on any given trial. Analytical results show that the proposed procedure is more efficient than existing procedures in that it requires fewer observations to identify the best system when only two systems are being considered. Empirical results show that the procedure is more efficient for comparing up to five systems when the specified odds-ratio indifference zone is greater than two.
Kinetic Voronoi/Delaunay Drawing Tools
Authors: Chris Gold, Maciej Dakowicz
Venue: Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering (2006)

We describe two reversible line-drawing methods for cartographic applications based on the kinetic (moving-point) Voronoi diagram. Our objectives were to optimize the user's ability to draw and edit the map, rather than to produce the most efficient batchoriented algorithm for large data sets, and all our algorithms are based on local operations (except for basic point location). Because the deletion of individual points or line segments is a necessary part of the manual editing process, incremental insertion and deletion is used. The original concept used here is that, as a curve (line) is the locus of a moving point, then segments are drawn by maintaining the topology of a single moving point (MP, or the "pen") as it moves through the topological network (visualized as either the Voronoi diagram or Delaunay triangulation). The trailing line accumulates the adjacency relationships of MP. There are thus three parts to our method: the maintenance of MP in the DT/VD; the use of MP to draw the constrained edges in the Delaunay triangulation; and the use of MP to draw the line segment Voronoi diagram. In all cases deletion is the inverse of the original drawing: move MP so as to "roll up" the desired segment. This approach also has the interesting property that a "log file" of all operations may be preserved, allowing reversion to previous map states, or "dates", as required.