ppxscal/embedding_network huggingface dataset:
A Middleware Support for Agent-Based Application Mobility in Pervasive Environments
Authors: Yu Zhou, Jiannong Cao, Vaskar Raychoudhury, Joanna Siebert, Jian Lu
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems Workshops (2007)

Application mobility is an efficient way to mask uneven conditioning and reduce users' distractions in pervasive environments. However, since mobility brings more dynamism and uncertainty, it also raises new research issues in developing pervasive applications, including underlying application models, adaptive resource rebinding mechanisms, synchronization and fault tolerance techniques, etc. In this paper, we approach these problems from the middleware perspective. Inspired by software agent's inherent capability of autonomy and mobility, we investigate its potential use in application mobility and propose an agent-based architecture called MDAgent. Three salient features are emphasized: 1) Reduced mobility overhead. Flexible bindings of application components avoid migrating whole application. 2) Simplified mobility management. Mobile agent takes over the responsibility of mobility and synchronization, so user intervention is reduced. 3) Enhanced customizability and adaptability. Context information can be updated dynamically, and ontology-based reasoning ability embedded in autonomous agents can direct the application to adapt to the changes accordingly. On top of MDAgent, we have developed several applications, and evaluated the performance.
Robust estimation of rigid body 3-D motion parameters from point correspondences
Authors: T. Papadimitriou
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

The estimation of rigid body 3-D motion parameters from perspective views is typically very sensitive to noise and also to the presence of outliers in the measurements. In this paper we present a robust 3-D motion estimation approach based on a previously proposed method using SVD analysis of the measurements matrix. On the introduction of noise and outliers the performance of the old method was seen to deteriorate rapidly. Here the problem is attached by splitting the measurement set into smaller subsets and combining the properties of the resulting submatrices with the properties of the desired solution vector in order to obtain our estimate. The method is very robust and it has been successfully tested in both artificial datasets and real images with up to 50% presence of outliers. In addition, the method is fast and more importantly, the estimate quality is independent of the percentage of outliers.
Sound candy
Authors: Shuichi Ishibashi, Daisuke Uriu, Naohito Okude
Venue: Proceedings of the international conference on Advances in computer entertainment technology (2007)

Sound Candy is a device with which anyone in the world can create his/her own playground anywhere of using sounds and movements around him/her. In our daily life, we are surrounded by the "Kings of Entertainment" such as theme parks and home video game machines. However, the entertainment gives us only passively experience without our creation or creativity. In this paper, we suggest Sound Candy designed as the tool with which each user can create a new way of playing actively. In its small body, Sound Candy has two functions as follows. First, it has a recording function. Second, it has a function to integrate recorded sounds and signals from sensors, such as vibration or acceleration caused from variety of movements. Sound Candy can be attached to any part of user's body and almost objects in his/her environments. So users can convert the recorded sound to the one synchronized with various actions by selecting a play mode from four play modes including Angle, Vibration, Speed and Rotation Mode.
SIFT - A Component-Based Integration Architecture for Enterprise Analytics
Authors: Dave Thurman, Justin Almquist, Ian Gorton, Adam Wynne, Jack Chatterton
Venue: Proceedings of the Sixth International IEEE Conference on Commercial-off-the-Shelf (COTS)-Based Software Systems (2007)

Architectures and technologies for enterprise application integration are relatively mature, resulting in a range of standards-based and proprietary COTS middleware technologies. However, in the domain of complex analytical applications, integration architectures are not so well understood. Analytical applications such as those used in scientific discovery and financial and intelligence analysis exert unique demands on their underlying architectures. These demands make existing COTS integration middleware less suitable for use in enterprise analytics environments. In this paper we describe SIFT (Scalable Information Fusion and Triage), an application architecture designed for integrating the various components that comprise enterprise analytics applications. SIFT exploits a common pattern for composing analytical components, and extends an existing messaging platform with dynamic configuration mechanisms and scaling capabilities. We demonstrate the use of SIFT to create a decision support platform for quality control based on large volumes of incoming delivery data. The strengths and weaknesses of the SIFT solution are discussed, and we conclude by describing where further work is required to create a complete solution applicable to a wide range of analytical application domains.
Tuning Evolutionary Algorithm Performance Using Nature Inspired Heuristics
Authors: Ajith Abraham
Venue: Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2006)

Evolutionary algorithms have become an important problem solving methodology among many researchers working in the area of computational intelligence. The population based collective learning process; self adaptation and robustness are some of the key features of evolutionary algorithm when compared to other global optimization techniques. Due to its simplicity, evolutionary algorithms have been widely accepted for solving several important practical applications in engineering, business, commerce etc. However, experimental evidence had indicated cases where evolutionary algorithms are inefficient at fine tuning solutions, but better at finding global basins of attraction.
Faster integer multiplication
Authors: Martin Fürer
Venue: Proceedings of the thirty-ninth annual ACM symposium on Theory of computing (2007)

For more than 35 years, the fastest known method for integer multiplication has been the Schönhage-Strassen algorithm running in time O(n log n log log n). Under certain restrictive conditions there is a corresponding Ω(n log n) lower bound. The prevailing conjecture has always been that the complexity of an optimal algorithm is Θ(n log n). We present a major step towards closing the gap from above by presenting an algorithm running in time n log n, 2O(log* n). The main result is for boolean circuits as well as for multitape Turing machines, but it has consequences to other models of computation as well.
Dependency Management in Software Component Deployment
Authors: Meriem Belguidoum, Fabien Dagnat
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Component-based distributed systems are hard to deploy for two main reasons: the complexity of their structure and the complexity of the deployment tasks. Current tools do not manage these complexities properly because the descriptions that they allow lack of expressiveness. The absence of proper descriptions of system and component requirements makes it impossible to ensure safe installation and deinstallation. The goal of this paper is to present a formalization of deployment dependencies. These dependencies expressed in a logical language are associated with a deployment engine that allows installation and deinstallation of components in a system to be proved.
Comprehensive Evaluation of an Educational Software Engineering Simulation Environment
Authors: Emily Oh Navarro, Andre van der Hoek
Venue: Proceedings of the 20th Conference on Software Engineering Education & Training (2007)

Software engineering educational approaches are often evaluated only anecdotally, or in informal pilot studies. We describe a more comprehensive approach to evaluating a software engineering educational technique (SimSE, a graphical, interactive, customizable, game-based software engineering simulation environment). Our method for evaluating SimSE went above and beyond anecdotal experience and approached evaluation from a number of differ-ent angles through a family of studies designed to assess SimSE's effectiveness and guide its development. In this paper, we demonstrate the insights and lessons that can be gained when using such a multi-angled evaluation approach. Our hope is that, from this paper, educators will: (1) learn ideas about how to more comprehensively evaluate their own approaches, and (2) be provided with evidence about the educational effectiveness of SimSE.
A study of phylogenetic tools for genomic nomenclature data cleaning
Authors: Jonathan D. Marra, Katherine G. Herbert, Jason T. L. Wang
Venue: ACM SIGCSE Bulletin (2007)

In this poster we propose a method for addressing the genomic nomenclature problem by using phylogenetic tools along with the BIO-AJAX data cleaning framework.
Can the PC go green?
Authors: Aaron Weiss
Venue: netWorker (2007)

The usual depictions of modern life impacting the environment include images of traffic-jammed highways, smoke-belching factories, and perhaps a few schools of fish floating belly-up in polluted water. Rarely do we see people working at their PCs or stacks of servers in data centers. Computers don't have exhaust pipes, but their environmental impact is no longer invisible. The cumulative life cycles of billions of machines, from manufacture to usage to disposal, are combining into an environmental footprint large enough to attract widespread attention.
An efficient low-dimensional color indexing scheme for region-based image retrieval
Authors: Yining Deng
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

In this work, an efficient low-dimensional color indexing scheme for region-based image retrieval is presented. The colors in each image region are first quantized so that only a small number of cluster centroids are needed to represent the region color information. The proposed color feature descriptor consists of these quantized colors and their percentages in the region. A similarity distance measure is defined and shown to be equivalent to the quadratic color histogram distance measure. The quantized colors are indexed in the 3-D color space so that high-dimensional indexing can be avoided. During the search process, each quantized color in the query is used as a separate cue to find matches containing that color. The matches from all the query colors are then joined to obtain the final retrievals. Experimental results show that the proposed scheme is fast and accurate compared to the color histogram approach.
The evolution of an introductory computer engineering course
Authors: W. B. Hudson
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

EECE 241 is a required core course for Electrical and Computer Engineering students and a service course for other curricula. The presentation format has evolved to an integrated lecture and laboratory experience serving in excess of 100 students each semester. This course had been refined to: minimize faculty time commitment, allow hands on experiences, reinforce basic breadboarding and computer skills, encourage active learning, provide small group interaction, encourage time management skills, identify as early as possible students having difficulty, and provide a consistent student product. EECE 241, An Introduction to Computer Engineering, is a course in which we strive to introduce current technology while still teaching basic underlying concepts.
Source detection and localization using a multi-mode detector: a Bayesian approach
Authors: D. Cochran
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

This paper considers a class of detection/localization problems in which the detector offers multiple operating modes. The modes differ in their detection performance and geographical coverage: "focused" modes offer higher detection performance but less coverage area than "broad search" modes. It is assumed that a signal source is to be detected and localized using a sequence of tests, each possibly employing a different mode. The goal is to determine a strategy for mode selection in the sequence of tests that will yield optimal payoff in terms of a pre-established criterion. A mathematical model capturing the key characteristics of this situation is proposed and used to develop optimal mode selection strategies.
EPICS: interdisciplinary service learning using engineering design projects
Authors: W. C. Oakes
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 01 (2000)

Engineering Projects in Community Service, EPICS, is a service-learning program that was initiated at Purdue University in the Fall of 1995. Under this program, undergraduate students earn academic credit for long-term team projects that solve technology-based problems for local community service organizations. The program has grown to include 20 project teams with over 250 students participating during the 1999 academic year from 20 different academic departments. The goals of the EPICS program include: providing students with multi-year, team-based, design and development experience; teaching students, by direct experience, how to interact with each other and with customers to specify, design, develop and deploy systems that solve real problems. This paper provides an overview of the EPICS program as well as the inclusion of the non-engineering students, particularly those in Liberal Arts. Lessons learned from the interdisciplinary nature of the program are presented.
Decentralized Service Deployment for Collaborative Environments
Authors: Daniel Lazaro Iglesias, Joan Manuel Marques i Puig, Josep Jorba Esteve
Venue: Proceedings of the First International Conference on Complex, Intelligent and Software Intensive Systems (2007)

In this paper we present the design of a system which allows service deployment in a small-sized group of computers distributed through the Internet. These groups are formed by users who share a common interest, and voluntarily yield their own resources for the achievement of the collaborative activities of the group. Having enough resources contributed by the members of the group, our system guarantees service availability and the fact that the deployment and execution of the services is carried out using only the resources of the group. This management is done in a completely decentralized manner, and the system is self-organized in the presence of component connections, disconnections and failures. We demonstrate its validity through the implementation of a prototype and the execution of some tests, which allow us to guarantee that the system is self-organized, always reaching a consistent state.
Optimal dimensionality of metric space for classification
Authors: Wei Zhang, Xiangyang Xue, Zichen Sun, Yue-Fei Guo, Hong Lu
Venue: Proceedings of the 24th international conference on Machine learning (2007)

In many real-world applications, Euclidean distance in the original space is not good due to the curse of dimensionality. In this paper, we propose a new method, called Discriminant Neighborhood Embedding (DNE), to learn an appropriate metric space for classification given finite training samples. We define a discriminant adjacent matrix in favor of classification task, i.e., neighboring samples in the same class are squeezed but those in different classes are separated as far as possible. The optimal dimensionality of the metric space can be estimated by spectral analysis in the proposed method, which is of great significance for high-dimensional patterns. Experiments with various datasets demonstrate the effectiveness of our method.
Random sampling of moment graph: a stochastic Krylov-reduction algorithm
Authors: Zhenhai Zhu, Joel Phillips
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

In this paper we introduce a new algorithm for model order reduction in the presence of parameter or process variation. Our analysis is performed using a graph interpretation of the multi-parameter moment matching approach, leading to a computational technique based on Random Sampling of Moment Graph (RSMG). Using this technique, we have developed a new algorithm that combines the best aspects of recently proposed parameterized moment-matching and approximate TBR procedures. RSMG attempts to avoid both exponential growth of computational complexity and multiple matrix factorizations, the primary drawbacks of existing methods, and illustrates good ability to tailor algorithms to apply computational effort where needed. Industry examples are used to verify our new algorithms.
Infrared sensor modeling for realistic thermal image synthesis
Authors: C. Garnier
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

To generate realistic synthetic IR images, image acquisition by IR sensors must be reproduced. In this paper, we propose an IR sensor model based on physical laws governing effects involved in the IR imagery formation process. Our approach consists in a combination and an extension of current camera models used in visible and infrared image synthesis, and thus merges ray tracing and post-processing techniques. Our model represents the geometric and radiometric relationship between the points in the 3D observed scene and the corresponding pixels of the IR sensor output image. It offers the capability of simulating each IR sensor component in accordance with any given system technology and to any desired degree of precision. Moreover, it can also account for variations in many physical quantities through spatial, spectral, and temporal dimensions.
Efficient evaluation of trade-offs in waveform design for robust pulse amplitude modulation
Authors: T. N. Davidson
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

The design of a pulse shaping filter which provides maximal robustness to an unknown frequency-selective channel has previously been formulated as a convex optimization problem from which an optimal filter can be efficiently obtained. Robustness was measured by the worst-case 'peak' intersymbol interference over a class of deterministically bounded channels, and the optimization was subject to a constraint on the bandwidth of the filter. The purpose of the present paper is to show that the design trade-offs between bandwidth, performance in an ideal channel and robustness to unknown channel distortion can be efficiently evaluated using this convex optimization problem. In the design examples, these trade-offs are used to select chip waveforms with superior performance to those specified in standards for digital mobile telephony.
A game theoretic framework for interconnect optimization in deep submicron and nanometer design
Authors: N. Ranganathan
Venue:  (2006)

The continuous scaling of interconnect wires in deep submicron (DSM) circuits result in increased interconnect delay, power and crosstalk noise. In this dissertation, we address the problem of multi-metric optimization at post layout level in the design of deep submicron designs and develop a game theoretic framework for its solution. Traditional approaches in the literature can only perform single metric optimization and cannot handle multiple metrics. However, in interconnect optimization, the simultaneous optimization of multiple parameters such as delay, crosstalk noise and power is necessary and critical. Thus, the work described in this dissertation research addressing multi-metric optimization is an important contribution. Specifically, we address the problems of simultaneous optimization of interconnect delay and crosstalk noise during (i) wire sizing; (ii) gate sizing; (iii) integrated gate and wire sizing, and (iv) gate sizing considering process variations. Game theory provides a natural framework for handling conflicting situations and allows optimization of multiple parameters. This property is exploited in modeling the simultaneous optimization of various design parameters such as interconnect delay, crosstalk noise and power, which are conflicting in nature. The problem of multi-metric optimization is formulated as a normal form game model and solved using Nash equilibrium theory. In wire sizing formulations, the net segments within a channel are modeled as the players and the range of possible wire sizes forms the set of strategies. The payoff function is modeled as (i) the geometric mean of interconnect delay and crosstalk noise and (ii) the weighted-sum of interconnect delay, power and crosstalk noise, in order to study the impact of different cost functions with two and three metrics respectively. In gate sizing formulations, the range of possible gate sizes is modeled as the set of strategies and the payoff function is modeled as the geometric mean of interconnect delay and crosstalk noise. The gates are modeled as the players while performing gate sizing, whereas, the interconnect delay and crosstalk noise are modeled as players for integrated wire and gate sizing framework as well as for statistical gate sizing under the impact of process variations. The various algorithms proposed in this dissertation (i) perform multi-metric optimization; (ii) achieve significantly better optimization and run times than other methods such as simulated annealing, genetic search, and Lagrangian relaxation; (iii) have linear time and space complexities, and hence can be applied to very large SOC designs, and (iv) do not require rerouting or incur any area overhead. The computational complexity analysis of the proposed algorithms as well as their software implementations are described, and experimental results are provided that establish the efficacy of the proposed algorithms.