ppxscal/embedding_network huggingface dataset:
A hybrid convolution tree kernel for semantic role labeling
Authors: Wanxiang Che, Min Zhang, Ting Liu, Sheng Li
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

A hybrid convolution tree kernel is proposed in this paper to effectively model syntactic structures for semantic role labeling (SRL). The hybrid kernel consists of two individual convolution kernels: a Path kernel, which captures predicate-argument link features, and a Constituent Structure kernel, which captures the syntactic structure features of arguments. Evaluation on the datasets of CoNLL-2005 SRL shared task shows that the novel hybrid convolution tree kernel out-performs the previous tree kernels. We also combine our new hybrid tree kernel based method with the standard rich flat feature based method. The experimental results show that the combinational method can get better performance than each of them individually.
On the use of one-way chain based authentication protocols in secure control systems
Authors: Bogdan Groza, Toma-Leonida Dragomir
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

The use of one-way chains in authentication protocols is a technique of great importance which has many applications. Employing cryptographic techniques in the area of industrial control systems has gained significant interest in the last few years. This paper proposes the use of a one-way chain based authentication protocol in a robust control system. Some enhancements of a generic one-way chain based authentication protocol are required by the scenario of secure robust and they are intended for achieving lower authentication delays and computational costs while preserving the control robust in the presence of potential attackers. We also underline that the techniques described in this paper are not restricted to the subject of authentication in robust control systems since the presented protocols may be useful for other applications as well.
Fluidic Shadow Dance Using Interactive Fluid Animation
Authors: Jeongjin Lee, Moon Koo Kang, Yeong Gil Shin
Venue: Proceedings of the 16th International Conference on Artificial Reality and Telexistence--Workshops (2006)

This paper proposes an interactive artwork to visualize the internal conflicts of an individual reacting to environmental impulses. This artwork is implemented using an enhanced particle dynamics simulation method with pre-integrated volume rendering. The computational efficiency is achieved using small number of particles for representing a significant volume. In this artwork, the viewer in front of a video camera touches a pair of columns on which arrays of sensors are located to serve as virtual fluid injectors. The sensor signal and the video image are transmitted to the computer and the video processor, and the computer simulates particle fluids being virtually injected into the shadow of the viewer. The processed shadows and the computer rendered images are then superposed to create a visual illusion that appears as if the fluid is injected into the body and then reacts to diverse body postures accordingly, associating the mental functions of ego.
Engineering open environments for multi-agent simulation systems
Authors: Rym Zalila Mili
Venue:  (2006)

In this work, we present the idea that agents and the environment play an equally important role in MAS design and propose an architecture for Agent Environment System (AES). We consider environments as first class entities and propose a specification, design and implementation of the DIVAs environment. DIVAs is a large scale multi-agent simulation tool in which agents represent social entities and the environment an artificial world. Our architecture is based on software engineering concepts such as separation of concerns, modularity and information hiding. This leads to adaptable systems that can support multiple application domains. We discuss a Specification and a Simulation Tool that illustrate the applicability of our results to various problems.
Nonlinear system identification with recurrent neural networks and dead-zone Kalman filter algorithm
Authors: José de Jesús Rubio, Wen Yu
Venue: Neurocomputing (2007)

Compared to normal learning algorithms, for example backpropagation, Kalman filter-based algorithm has some better properties, such as faster convergence, although this algorithm is more complex and sensitive to the nature of noises. In this paper, extended Kalman filter is applied to train state-space recurrent neural networks for nonlinear system identification. In order to improve robustness of Kalman filter algorithm dead-zone robust modification is applied to Kalman filter. Lyapunov method is used to prove that the Kalman filter training is stable.
Error-rate analysis of the adaptive successive interference canceler for DS/CDMA signals
Authors: Kuei-Chiang Lai
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

The adaptive successive interference canceler (ASIC) is a multistage nonlinear detector that sequentially estimates multiple users in a direct-sequence code-division multiple-access (DS/CDMA) system. In order to successfully regenerate the multiple access interference and subtract it from the received signal, the ASIC requires accurate estimates of the users' received amplitudes. In this paper, we analyze the bit-error-rate performance of the ASIC employing a single antenna element in a synchronous DS/CDMA system. Computer simulations verify the accuracy of the analysis, and a numerical example illustrates the sensitivity of the SIC to incorrect amplitude estimates.
An investigation, using co-evolution, to evolve an Awari player
Authors: J. E. Davis, G. Kendall
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

Awari is a two-player game of perfect information, played using 12 "pits" and 48 seeds or stones. The aim is for one player to capture more than half the seeds. In this work we show how an awari player can be evolved using a co-evolutionary approach where computer players play against one another, with the strongest players surviving and being mutated using an evolutionary strategy (ES). The players are represented using a simple evaluation function, representing the current game state, with each term of the function having a weight which is evolved using the ES. The output of the evaluation function is used in a mini-max search. We play the best evolved player against one of the strongest shareware programs (Awale) and are able to defeat the program at three of its four levels of play.
Automating the construction of compiler heuristics using machine learning
Authors: Saman Amarasinghe
Venue:  (2006)

Compiler writers are expected to create effective and inexpensive solutions to NP-hard problems such as instruction scheduling and register allocation. To make matters worse, separate optimization phases have strong interactions and competing resource constraints. Compiler writers deal with system complexity by dividing the problem into multiple phases and devising approximate heuristics for each phase. However, to achieve satisfactory performance, developers are forced to manually tweak their heuristics with trial-and-error experimentation. In this dissertation I present meta optimization, a methodology for automatically constructing high quality compiler heuristics using machine learning techniques. This thesis describes machine-learned heuristics for three important compiler optimizations: hyperblock formation, register allocation, and loop unrolling. The machine-learned heuristics outperform (by as much as 3x in some cases) their state-of-the-art hand-crafted counterparts. By automatically collecting data and systematically analyzing them, my techniques discover subtle interactions that even experienced engineers would likely overlook. In addition to improving performance, my techniques can significantly reduce the human effort involved in compiler design. Machine learning algorithms can design critical portions of compiler heuristics, thereby freeing the human designer to focus on compiler correctness. The progression of experiments I conduct in this thesis leads to collaborative compilation, an approach which enables ordinary users to transparently train compiler heuristics by running their applications as they normally would. The collaborative system automatically adapts itself to the applications in which a community of users is interested. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Guided Quaternary Reaching Method for Wavelet-based Image Compression
Authors: Xiteng Liu
Venue: Proceedings of the 2007 Data Compression Conference (2007)

In this paper, a simple easy to understand, easy to implement high performance wavelet-based image compression algorithm using guided quaternary reaching (GQR) method is proposed. Compared with JPEG2000, GQR algorithm has two remarkable merits: 1). much lower algorithmic complexity and 2). higher compression efficiency. In a wavelet-based image compression system, wavelet coefficients are rearranged into hierarchical subbands.
Tutorial T4B: Formal Assertion-Based Verification in Industrial Setting
Authors: Praveen Tiwari, Raj Mitra, Manu Chopra, Alok Jain
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Increased complexities of hardware designs have made exhaustive simulation of designs near impossible - thereby creating a need for some complementary verification technique. This has generated a renewed interest in use of Formal Analysis on industrial hardware designs. Formal Analysis of hardware design involves use of mathematical techniques to prove that the design implementation confirms to the specification. The specification is a set of properties which should hold on the design under verification. Advances in Formal Analysis techniques with more sophisticated heuristics, have made them usable on big blocks of hardware. In this tutorial, we begin by giving a brief theoretical introduction to various methods applied in formal hardware verification, and then discuss various automated and manual techniques to handle the state explosion problem. Application of Formal Analysis techniques on appropriate designs and in a methodical way is key to successful verification. In this tutorial we elaborate on how one can effectively plan for formal verification, and successfully close verification. We illustrate these techniques using several case studies. Finally we present the future directions for commercial tools in this domain.
Certified software factory: open software toolsuites, safe methodologies and system architectures
Authors: J. U. Gärtner
Venue: Proceedings of the eleventh Australian workshop on Safety critical systems and software - Volume 69 (2007)

This paper discusses model-based design in the context of the Safety Critical Application Development Environment (SCADE), developed by Esterel Technologies.1 The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Implementing PLS for distance-based regression: computational issues
Authors: Eva Boj, Aurea Grané, Josep Fortiana, M. Mercè Claramunt
Venue: Computational Statistics (2007)

Distance-based regression allows for a neat implementation of the partial least squares recurrence. In this paper, we address practical issues arising when dealing with moderately large datasets (n ~ 104) such as those typical of automobile insurance premium calculations.
MAX: A Multi Objective Memory Architecture eXploration Framework for Embedded Systems-on-Chip
Authors: T. S. Rajesh Kumar, C. P. Ravikumar, R. Govindarajan
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Today's feature-rich multimedia products require embedded system solution with complex System-on-Chip (SoC) to meet market expectations of high performance at a low cost and lower energy consumption. The memory architecture of the embedded system strongly influences these parameters. Hence the embedded system designer performs a complete memory architecture exploration. This problem is a multi-objective optimization problem and can be tackled as a two-level optimization problem. The outer level explores various memory architecture while the inner level explores placement of data sections (data layout problem) to minimize memory stalls. Further, the designer would be interested in multiple optimal design points to address various market segments. However, tight time-to-market constraints enforces short design cycle time. In this paper we address the multi-level multi-objective memory architecture exploration problem through a combination of Multi-objective Genetic Algorithm (Memory Architecture exploration) and an efficient heuristic data placement algorithm. At the outer level the memory architecture exploration is done by picking memory modules directly from a ASIC memory Library. This helps in performing the memory architecture exploration in a integrated framework, where the memory allocation, memory exploration and data layout works in a tightly coupled way to yield optimal design points with respect to area, power and performance. We experimented our approach for 3 embedded applications and our approach explores several thousand memory architecture for each application, yielding a few hundred optimal design points in a few hours of computation time on a standard desktop.
Magpie: precise garbage collection for c
Authors: Matthew Flatt
Venue:  (2006)

C and C++ provide fast, flexible substrata for programs requiring speed or tight coupling with the operating system or hardware. Both languages have well established user and code bases, including programs still in use after decades of development. Unfortunately, with C and C++'s speed and flexibility come increased complexity, including complication in managing memory. Programs must create and destroy objects explicitly, and small mistakes in doing so can cause severe complications. In other languages, precise garbage collection solves these problems by having the computer manage the program's memory. However, until now, adding precise garbage collection to standard C programs has been a considerable amount of work. This dissertation describes Magpie, a system that uses several analyses and conversion techniques to relieve much of the burden of this conversion. It also describes the effects of the conversion on several sample programs. Finally, debugging tools and language runtimes can perform additional interesting tasks given an existing garbage collection infrastructure. This dissertation outlines several such extensions, and discusses one---memory accounting---in detail.
Compact finite difference method for American option pricing
Authors: Jichao Zhao, Matt Davison, Robert M. Corless
Venue: Journal of Computational and Applied Mathematics (2007)

A compact finite difference method is designed to obtain quick and accurate solutions to partial differential equation problems. The problem of pricing an American option can be cast as a partial differential equation. Using the compact finite difference method this problem can be recast as an ordinary differential equation initial value problem. The complicating factor for American options is the existence of an optimal exercise boundary which is jointly determined with the value of the option. In this article we develop three ways of combining compact finite difference methods for American option price on a single asset with methods for dealing with this optimal exercise boundary. Compact finite difference method one uses the implicit condition that solutions of the transformed partial differential equation be nonnegative to detect the optimal exercise value. This method is very fast and accurate even when the spatial step size h is large (h>=0.1). Compact difference method two must solve an algebraic nonlinear equation obtained by Pantazopoulos (1998) at every time step. This method can obtain second order accuracy for space x and requires a moderate amount of time comparable with that required by the Crank Nicolson projected successive over relaxation method. Compact finite difference method three refines the free boundary value by a method developed by Barone-Adesi and Lugano [The saga of the American put, 2003], and this method can obtain high accuracy for space x. The last two of these three methods are convergent, moreover all the three methods work for both short term and long term options. Through comparison with existing popular methods by numerical experiments, our work shows that compact finite difference methods provide an exciting new tool for American option pricing.
Resource-Locking Durations in EDF-Scheduled Systems
Authors: Nathan Fisher, Marko Bertogna, Sanjoy Baruah
Venue: Proceedings of the 13th IEEE Real Time and Embedded Technology and Applications Symposium (2007)

The duration of time for which each application locks each shared resource is critically important in composing multiple independently-developed applications upon a shared "open" platform. The concept of resource hold time (RHT) -- the largest length of time that may elapse between the instant that an application system locks a resource and the instant that it subsequently releases the resource--is formally defined and studied in this paper. An algorithm is presented for computing resource hold times for every resource in an application that is scheduled using Earliest Deadline First scheduling, with resource access arbitrated using the Stack Resource Policy. An algorithm is presented for decreasing these RHT's without changing the semantics of the application or compromising application feasibility.
A parallel framework for loopy belief propagation
Authors: Alexander Mendiburu, Roberto Santana, Jose A. Lozano, Endika Bengoetxea
Venue: Proceedings of the 2007 GECCO conference companion on Genetic and evolutionary computation (2007)

There are many innovative proposals introduced in the literature under the evolutionary computation field, from which estimation of distribution algorithms (EDAs) is one of them. Their main characteristic is the use of probabilistic models to represent the (in) dependencies between the variables of a concrete problem. Such probabilistic models have also been applied to the theoretical analysis of EDAs, providing a platform for the implementation of other optimization methods that can be incorporated into the EDA framework. Some of these methods, typically used for probabilistic inference, are belief propagation algorithms. In this paper we present a parallel approach for one of these inference-based algorithms, the loopy belief propagation algorithm for factor graphs. Our parallel implementation was designed to provide an algorithm that can be executed in clusters of computers or multiprocessors in order to reduce the total execution time. In addition, this framework was also designed as a flexible tool where many parameters, such as scheduling rules or stopping criteria, can be adjusted according to the requirements of each particular experiment and problem.
Online algorithms for the provision of quality of service in networks
Authors: Ping Yuen Fung
Venue:  (2005)

New Internet applications require the underlying network to provide different levels of more reliable service. The concept of Quality of Service (QoS) was designed to meet this demand. A number of algorithmic issues arise in the provision of QoS, and in this study we consider three related online scheduling problems for QoS. These three problems, besides having practical applications, are also of considerable theoretical interest. The first problem is an online preemptive scheduling problem, in which a set of jobs with varying release times, deadlines, processing times and weights must be scheduled so as to maximize the total value obtained. Unlike classical scheduling problems, partially completed jobs can obtain partial values proportional to their amounts processed. This problem has applications in multimedia QoS provisioning in networks as well as other practical applications. The second problem is a packet scheduling problem for network switches supporting QoS. Packets with different QoS values arrive at a network switch and are to be sent along an outgoing link. Due to overloading conditions, some packets have to be dropped. The objective is to maximize the total value of packets that are sent. We formulate this as an online unit job scheduling problem, where each job is specified by its release time, deadline, and weight. In the third problem, a set of pages is to be broadcasted to clients on demand. Requests asking for the same page can be satisfied in a single broadcast. Each request is associated with a deadline, and the objective is to maximize the profit on requests satisfied before their deadlines. We provide new and improved online algorithms and lower bounds on the competitive ratios for these problems. In some cases the bounds are tight. Some major contributions include: (1) a 1.58-competitive timesharing algorithm for the scheduling of jobs with partial values, and a 1.618 lower bound on the competitive ratio of non-timesharing algorithms; (2) a randomized lower bound of 1.25 which applies simultaneously to the scheduling of partial value jobs, unit jobs,' and broadcasts with deadlines, as well as their variations; (3) optimal and improved algorithms for some special cases of unit job scheduling; and (4) extension of the scheduling problems to the multiprocessor case, including a new multiprocessor algorithm for unit job scheduling. We also show that the three problems have interesting connections, and that some of the techniques we have developed can be applied to more than one of these problems.
On the minimum length of some linear codes
Authors: E. J. Cheon, T. Maruta
Venue: Designs, Codes and Cryptography (2007)

We determine the minimum length n q (k, d) for some linear codes with k ¿ 5 and q ¿ 3. We prove that n q (k, d) = g q (k, d) + 1 for $$q^{k-1}-2q^{\frac{k-1}{2}}-q+1 \le d \le q^{k-1}-2q^{\frac{k-1}{2}}$$ when k is odd, for $$q^{k-1}-q^{\frac{k}{2}}-q^{{\frac{k}{2}}-1} -q+1 \le d \le q^{k-1}-q^{\frac{k}{2}}-q^{{\frac{k}{2}}-1}$$ when k is even, and for $$2q^{k-1}-2q^{k-2}-q^2-q+1 \le d \le 2q^{k-1}-2q^{k-2}-q^2$$ .
Mobile Computing Systems Programming: A Graduate Distributed Computing Course
Authors: Lars Kulik
Venue: IEEE Distributed Systems Online (2007)

To address the large mobile systems market and demand for students seeking career opportunities, the University of Melbourne's Computer Science and Software Engineering Department created a Master of Engineering in Distributed Computing degree program. A key course is Mobile Computing Systems Programming, which gives students hands-on experience working with real mobile devices and deploying small applications.
Multicast Extension of Unicast Charging for QoS Services
Authors: Antonio Bueno, Pere Vila, Ramon Fabregat
Venue: Proceedings of the Fourth European Conference on Universal Multiservice Networks (2007)

In order to successfully deploy multicast services in QoS-aware networks, pricing architectures must take into account the particular characteristics of multicast sessions. With this objective, we propose a charging scheme for QoS multicast services, assuming that the unicast cost of each interconnecting link is determined and that such cost is expressed in terms of quality of service (QoS) parameters. Our scheme allows determining the cost distribution of a multicast session along a Cost Distribution Tree (CDT), and basing such distribution in those pre-existing unicast cost functions. The paper discusses in detail the main characteristics of the problem in a realistic inter-domain scenario and how the proposed scheme would contribute to its solution.