ppxscal/embedding_network huggingface dataset:
Using games in introductory courses: tips from the trenches
Authors: Jessica D. Bayliss
Venue: Proceedings of the 40th ACM technical symposium on Computer science education (2009)

Computer Science degree program enrollments have fallen precipitously since the year 2000 and it is not surprising that novel approaches to education are being tried to both attract and retain students. One of the areas with a record of success is with using games in introductory programming courses. While there are several successful programs, the drawbacks of these approaches are not commonly discussed along with their benefits. Having run a successful game-based program that retained students within the CS major at a 93% rate, we discuss both the benefits of the program as well as the problems that need to be considered and overcome.
The Analysis on Angle Noise Produced by Blinking Jamming
Authors: Ping Li, Xiao-ming Geng, Yan Zhang, Zhen-gang Zhai
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

Blinking jamming is an effective countermeasure against monopulse radar seeker. It causes line-of-sight angle to step continuously between the two angular positions through jamming resources emitting by turns. The expression of angle noise in synchronous blinking jamming and the relationship between the parameter of jamming resource and Angle Noise are analyzed on the basis of the situation of line-of-sight angle position between missile and target. The relationship between the parameter of jamming resources and Angle Noise is important in application of blinking jamming.
FORCE schemes on unstructured meshes I: Conservative hyperbolic systems
Authors: Eleuterio F. Toro, Arturo Hidalgo, Michael Dumbser
Venue: Journal of Computational Physics (2009)

This paper is about the construction of numerical fluxes of the centred type for one-step schemes in conservative form for solving general systems of conservation laws in multiple space dimensions on structured and unstructured meshes. The work is a multi-dimensional extension of the one-dimensional FORCE flux and is closely related to the work of Nessyahu-Tadmor and Arminjon. The resulting basic flux is first-order accurate and monotone; it is then extended to arbitrary order of accuracy in space and time on unstructured meshes in the framework of finite volume and discontinuous Galerkin methods. The performance of the schemes is assessed on a suite of test problems for the multi-dimensional Euler and Magnetohydrodynamics equations on unstructured meshes.
3D seismic imaging through reverse-time migration on homogeneous and heterogeneous multi-core processors
Authors: Mauricio Araya-Polo, Félix Rubio, Raúl de la Cruz, Mauricio Hanzich, José María Cela, Daniele Paolo Scarpazza
Venue: Scientific Programming (2009)

Reverse-Time Migration (RTM) is a state-of-the-art technique in seismic acoustic imaging, because of the quality and integrity of the images it provides. Oil and gas companies trust RTM with crucial decisions on multi-million-dollar drilling investments. But RTM requires vastly more computational power than its predecessor techniques, and this has somewhat hindered its practical success. On the other hand, despite multi-core architectures promise to deliver unprecedented computational power, little attention has been devoted to mapping efficiently RTM to multi-cores. In this paper, we present a mapping of the RTM computational kernel to the IBM Cell/B.E. processor that reaches close-to-optimal performance. The kernel proves to be memory-bound and it achieves a 98% utilization of the peak memory bandwidth. Our Cell/B.E. implementation outperforms a traditional processor (PowerPC 970MP) in terms of performance (with an 15.0&times; speedup) and energy-efficiency (with a 10.0&times; increase in the GFlops/W delivered). Also, it is the fastest RTM implementation available to the best of our knowledge. These results increase the practical usability of RTM. Also, the RTM-Cell/B.E. combination proves to be a strong competitor in the seismic arena.
Implementing an Intuitive Reasoner for Predicting Continuous Weather Variables
Authors: Yung-Chien Sun, O. Grant Clark
Venue: Proceedings of the 2009 International Conference on Computer Modeling and Simulation (2009)

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Five weather variables from those data were chosen as the "target variables" whose values were predicted. A "complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. Multiple linear regression was employed to induce rules from the data subsets. The intuitive reasoner was tested for its ability to use the induced rules to predict the values of the target variables. For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same five target variables. The intuitive reasoner showed potential by achieving prediction accuracy which compared favorably with that of the reference approach for two target variables, based on rules induced from only about 10% of the total data.
Efficient block-based parameterized timing analysis covering all potentially critical paths
Authors: Khaled R. Heloue, Sari Onaissi, Farid N. Najm
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

In order for the results of timing analysis to be useful, they must provide insight and guidance on how the circuit may be improved so as to fix any reported timing problems. A limitation of many recent variability-aware timing analysis techniques is that, while they report delay distributions, or verify multiple corners, they do not provide the required guidance for re-design. We propose an efficient block-based parameterized timing analysis technique that can accurately capture circuit delay at every point in the parameter space, by reporting all paths that can become critical. Using an efficient pruning algorithm, only those potentially critical paths are carried forward, while all other paths are discarded during propagation. This allows one to examine local robustness to parameters in different regions of the parameter space, not by considering differential sensitivity at a point (which would be useless in this context) but by knowledge of the paths that can become critical at nearby points in parameter space. We give a formal definition of this problem and propose a technique for solving it that improves on the state of the art, both in terms of theoretical computational complexity and in terms of run time on various test circuits.
Graphical Congestion Games
Authors: Vittorio Bilò, Angelo Fanelli, Michele Flammini, Luca Moscardelli
Venue: Proceedings of the 4th International Workshop on Internet and Network Economics (2008)

We consider congestion games with linear latency functions in which each player is aware only of a subset of all the other players. This is modeled by means of a social knowledge graph G in which nodes represent players and there is an edge from i to j if i knows j. Under the assumption that the payoff of each player is affected only by the strategies of the adjacent ones, we first give a complete characterization of the games possessing pure Nash equilibria. We then investigate the impact of the limited knowledge of the players on the performance of the game. More precisely, given a bound on the maximum degree of G, for the convergent cases we provide tight lower and upper bounds on the price of stability and asymptotically tight bounds on the price of anarchy. All the results are then extended to load balancing games.
SVM Based Speaker Recognition Using Maximum a posteriori Linear Regression
Authors: Xiang Zhang, Qingwei Zhao, Yonghong Yan
Venue: Proceedings of the 2009 International Conference on Electronic Computer Technology (2009)

Maximum likelihood linear regression (MLLR) is a widely used technique for speaker adaptation in large vocabulary speech recognition system. Recently, using MLLR transforms as features for SVM based speaker recognition tasks has been proposed, achieving performance comparable to that obtained with cepstral features. In this paper, we focus on calculating the transforms based on a GMM universal background model (UBM). Rather than estimating the transforms using maximum likelihood criterion, this paper describes a new feature extraction technique for speaker recognition based on maximum a posteriori linear regression (MAPLR), which uses maximum a posteriori (MAP) as estimation criterion. We perform experiments on a NIST SRE 2008 corpus. Experimental results show that the system based on MAPLR technique outperforms MLLR in the task of speaker recognition.
Malaca: A component and aspect-oriented agent architecture
Authors: Mercedes Amor, Lidia Fuentes
Venue: Information and Software Technology (2009)

The production of maintainable and reusable agents depends largely on how well the agent architecture is modularized. Most commercial agent toolkits provide an Object-Oriented (OO) framework, whose agent architecture does not facilitate separate (re)use of the domain-specific functionality of an agent from other concerns. This paper presents Malaca, an agent architecture that combines the use of Component-based Software Engineering and Aspect-Oriented Software Development, both of which promote better modularization of the agent architecture while increase at the architectural level. Malaca supports the separate (re)use of the domain-specific functionality of an agent from other communication concerns, providing explicit support for the design and configuration of agent architectures and allows the development of agent-based software so that it is easy to understand, maintain and reuse.
Sparse Maximum Margin Logistic Regression for Credit Scoring
Authors: Sabyasachi Patra, Kripa Shanker, Debasis Kundu
Venue: Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (2008)

The objective of credit scoring model is to categorizethe applicants as either accepted or rejected debtors prior to granting credit. A modified logistic loss function is proposed which can approximate hinge loss and therefore the resulting model, maximum margin logistic regression (MMLR), has the classification capability of support vector machine (SVM) with low computational cost. Finally, to classify credit applicants, an efficient algorithm is also described for MMLR based on epsilon-boosting which can provide sparse estimation of coefficients for better stability and interpretability.
The EOQ problem with decidable warehouse capacity: Analysis, solution approaches and applications
Authors: C. T. Ng, T. C. E. Cheng, Vladimir Kotov, Mikhail Y. Kovalyov
Venue: Discrete Applied Mathematics (2009)

The Economic Order Quantity (EOQ) problem is a fundamental problem in supply and inventory management. In its classical setting, solutions are not affected by the warehouse capacity. We study a type of EOQ problem where the (maximum) warehouse capacity is a decision variable. Furthermore, we assume that the warehouse cost dominates all the other inventory holding costs. We call this the EOQ-Max problem and the D-EOQ-Max problem, if the product is continuously divisible and discrete, respectively. The EOQ-Max problem admits a closed form optimal solution, while the D-EOQ-Max problem does not because its objective function may have several local minima. We present an optimal polynomial time algorithm for the discrete problem. Construction of this algorithm is supported by the fact that continuous relaxation of the D-EOQ-Max problem provides a solution that can be up to 50% worse than the optimal solution, and this worst-case error bound is tight. Applications of the D-EOQ-Max problem include supply and inventory management, logistics and scheduling.
Model-based Control for 6-DOF Parallel Manipulator
Authors: Chifu Yang, Qitao Huang, Jingfeng He, Hongzhou Jiang, Junwei Han
Venue: Proceedings of the 2009 International Asia Conference on Informatics in Control, Automation and Robotics (2009)

A novel model-based controller for six-degree-of- freedom (DOF) parallel manipulator is proposed in this paper, in order to abatement the influence of platform load variety and compel the steady state errors converge to zero. In this paper, 6-DOF parallel manipulator is described as multi-rigid-body systems, the mathematical model of the 6-DOF parallel manipulator including dynamics based on Kane method and kinematics used closed-form solutions and Newton-Raphson method is built in generalized coordinate system. The model-based controller is presented with the feedback of cylinders positions of platform, desired trajectories and dynamics gravity as the input and the servovalve current as its output. The performance of the control scheme for 6-DOF parallel manipulator is analyzed. Simulation of the parallel manipulator with model-based controller is executed in MATLAB/Simulink, the simulation results indicate the model-based controller can reduce the influence of load variety of platform and eliminate steady state error of 6-DOF hydraulic driven parallel manipulator.
Extracting Coarse-Grained Pipelined Parallelism Out of Sequential Applications for Parallel Processor Arrays
Authors: Dimitris Syrivelis, Spyros Lalis
Venue: Proceedings of the 22nd International Conference on Architecture of Computing Systems (2009)

We present development and runtime support for building application specific data processing pipelines out of sequential code, and for executing them on a general purpose platform that features a reconfigurable Parallel Processor Array (PPA). Our approach is to let the programmer annotate the source of the application to indicate the desired pipeline stages and associated data flow, with little code restructuring. A pre-processor is then used to transform the annotated program into different code segments according to the indicated pipeline structure, generate the corresponding executable code, and produce a bundled application package containing all executables and deployment information for the target platform. There are special mechanisms for setting up the application-specific pipeline structure on the PPA and achieving integrated execution in the context of a general-purpose operating system, enabling the pipelined application to access the usual system peripherals and run concurrently with other conventional programs. To verify our approach, we have built a prototype system using soft processor arrays on an embedded FPGA platform, and transformed a well-known application into a pipelined version that executes successfully on our prototype.
Gold codes, Hadamard partitions and the security of CDMA systems
Authors: Derek H. Smith, Richard P. Ward, Stephanie Perkins
Venue: Designs, Codes and Cryptography (2009)

Let V = {1, 2, . . . , M} and let $${\{H_i{:} i \in V\}}$$ be a set of Hadamard matrices with the property that the magnitude of the dot product of any two rows of distinct matrices is bounded above. A Hadamard partition is any partition of the set of all rows of the matrices H i into Hadamard matrices. Such partitions have an application to the security of quasi-synchronous code-division multiple-access radio systems when loosely synchronized (LS) codes are used as spreading codes. A new generation of LS code can be used for each information bit to be spread. For each generation, a Hadamard matrix from some partition is selected for use in the code construction. This code evolution increases security against eavesdropping and jamming. One security aspect requires that the number of Hadamard partitions be large. Thus the number of partitions is studied here. If a Kerdock code construction is used for the set of matrices, the Hadamard partition constructed is shown to be unique. It is also shown here that this is not the case if a Gold (or Gold-like) code construction is used. In this case the number of Hadamard partitions can be enumerated, and is very large.
Analytical framework for dimensioning hierarchical WiMax-WiFi networks
Authors: Marc Ibrahim, Kinda Khawam, Abed Ellatif Samhat, Samir Tohme
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2009)

Providing diverse, ubiquitous and cost-effective broadband services is a foremost challenge for the telecommunication community. Fixed WiMAX or IEEE 802.16d is one of the most promising radio access technologies, providing high performance similar to wired xDSL systems, yet superior to that of current 3G mobile technologies. Numerous deployment concepts are foreseen for WiMAX networks. They are designed to cover isolated areas, thus embodying an appealing solution for cellular networks or wireless backhaul for WiFi access. The latter concept is of interest in this paper that puts forward an analytical model based on the economical aspects to dimension hierarchical WiMax-WiFi networks. The proposed model consists in replacing a finite number of nodes by an equivalent continuum. Its key feature lies in accounting for the effect of interference as well as for the physical layer and channel characteristics in an easy and straightforward manner. On the one hand, the model takes into consideration frequency planning and scheduling aspects; and on the other hand, it provides tractable formulae of the end-user mean capacity and coverage probability in order to properly dimension the hybrid network. Last but not least, the economical facet of network planning is considered to unravel the design trade-offs between maximizing the service provider profit and satisfying the end user requirements in terms of performance.
Computing needs time
Authors: Edward A. Lee
Venue: Communications of the ACM (2009)

The passage of time is essential to ensuring the repeatability and predictability of software and networks in cyber-physical systems.
Robust reconfigurable filter design using analytic variability quantification techniques
Authors: Arthur Nieuwoudt, Jamil Kawa, Yehia Massoud
Venue: Proceedings of the 2008 IEEE/ACM International Conference on Computer-Aided Design (2008)

In this paper, we develop a variability-aware design methodology for reconfigurable filters used in multi-standard wireless systems. To model the impact of statistical circuit component variations on the predicted manufacturing yield, we implement several different analytic variability quantification techniques based on a double-sided implementation of the first and second order reliability methods (FORM and SORM), which provide several orders of magnitude improvement in computational complexity over statistical sampling methods. Leveraging these efficient analytic variability quantification techniques, we employ an optimization approach using Sequential Quadratic Programming to simultaneously determine the fixed and tunable/switchable circuit element values in an arbitrary-order canonical filter to improve the overall robustness of the filter design when statistical variations are present. The results indicate that reconfigurable filters and impedance matching networks designed using the proposed methodology meet the specified performance requirements with a 26% average absolute yield improvement over circuits designed using deterministic techniques.
Application-aware management of parallel simulation collections
Authors: Siu Yau, Vijay Karamcheti, Denis Zorin, Kostadin Damevski, Steven G. Parker
Venue: ACM SIGPLAN Notices (2009)

This paper presents a system deployed on parallel clusters to manage a collection of parallel simulations that make up a computational study. It explores how such a system can extend traditional parallel job scheduling and resource allocation techniques to incorporate knowledge specific to the study. Using a UINTAH-based helium gas simulation code (ARCHES) and the SimX system for multi-experiment computational studies, this paper demonstrates that, by using application-specific knowledge in resource allocation and scheduling decisions, one can reduce the run time of a computational study from over 20 hours to under 4.5 hours on a 32-processor cluster, and from almost 11 hours to just over 3.5 hours on a 64-processor cluster.
Blind source separation with dynamic source number using adaptive neural algorithm
Authors: Tsung-Ying Sun, Chan-Cheng Liu, Shang-Jeng Tsai, Sheng-Ta Hsieh
Venue: Expert Systems with Applications: An International Journal (2009)

A difficult blind source separation (BSS) issue dealing with an unknown and dynamic number of sources is tackled in this study. In the past, the majority of BSS algorithms familiarize themselves with situations where the numbers of sources are given, because the settings for the dimensions of the algorithm are dependent on this information. However, such an assumption could not be held in many advanced applications. Thus, this paper proposes the adaptive neural algorithm (ANA) which designs and associates several auto-adjust mechanisms to challenge these advanced BSS problems. The first implementation is the on-line estimator of source numbers improved from the cross-validation technique. The second is the adaptive structure neural network that combines feed-forward architecture and the self-organized criterion. The last is the learning rate adjustment in order to enhance efficiency of learning. The validity and performance of the proposed algorithm are demonstrated by computer simulations, and are compared to algorithms with state of the art. From the simulation results, these have been confirmed that the proposed ANA performed better separation than others in static BSS cases and is feasible for dynamic BSS cases.
Supply chain risks analysis by using jump-diffusion model
Authors: Xianzhe Chen, Jun Zhang
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

This paper investigates the effects of demand risk on the performance of supply chain in continuous time setting. The inventory level has been modeled as a jump-diffusion process and the two-number inventory policy has been implemented in the supply chain system. The simulated annealing algorithm has been used to search the optimal critical values of the two-number policy. The jump magnitude has been considered in two cases: constant and Laplace distribution which has favorable property, i.e. leptokurtic. Numerical studies have been conducted for various scenarios to provide insights of effects of demand disruption on the performance of the supply chain.
Overhead Analysis of Grid Workflow Applications
Authors: Francesco Nerieri, Radu Prodan, Thomas Fahringer, Hong-linh Truong
Venue: Proceedings of the 7th IEEE/ACM International Conference on Grid Computing (2006)

In this paper we propose a systematic approach to performance analysis of workflow applications on the Grid. We introduce an ideal model for the workflow execution time and explain the difference to the real measured times based on a hierarchy of performance overheads for Grid computing. We describe how to systematically measure and compute the overheads from individual activities to entire workflow applications. We adjusted well-known parallel processing metrics to the scope of Grid computing, comprising speedup and efficiency. We have implemented and largely automatised our analysis approach in the context of the ASKALON Grid application development and computing environment. We present experimental results that show detailed overhead analysis of two real-world workflow applications executed in a national Grid environment.