ppxscal/embedding_network huggingface dataset:
A Reinforcement Learning Technique with an Adaptive Action Generator for a Multi-robot System
Authors: Toshiyuki Yasuda, Kazuhiro Ohkura
Venue: Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats (2008)

We have developed a new reinforcement learning (RL) technique called Bayesian-discrimination-function-based reinforcement learning (BRL). BRL is unique, in that it does not have state and action spaces designed by a human designer, but adaptively segments them through the learning process. Compared to other standard RL algorithms, BRL has been proven to be more effective in handling problems encountered by multi-robot systems (MRS), which operate in a learning environment that is naturally dynamic. Furthermore, we have developed an extended form of BRL in order to improve the learning efficiency. Instead of generating a random action when a robot functioning within the framework of the standard BRL encounters an unknown situation, the extended BRL generates an action determined by linear interpolation among the rules that have high similarity to the current sensory input. In this study, we investigate the robustness of the extended BRL through further experiments. In both physical experiments and computer simulations, the extended BRL shows higher robustness and relearning ability against an environmental change as compared to the standard BRL.
Generating High Dimensional Data and Query Sets
Authors: Sang-Wook Kim, Seok-Ho Yoon, Sang-Cheol Lee, Junghoon Lee, Miyoung Shin
Venue: Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science (2007)

Previous researches on multidimensional indexes typically have used synthetic data sets distributed uniformly or normally over multidimensional space for performance evaluation. These kinds of data sets hardly reflect the characteristics of multimedia database applications. In this paper, we discuss issues on generating high dimensional data and query sets for resolving the problem. We first identify the requirements of the data and query sets for fair performance evaluation of multidimensional indexes, and then propose HDDQ_Gen (High-Dimensional Data and Query Generator) that satisfies such requirements. HDDQ_Gen has the following features: (1) clustered distribution, (2) various object distribution in each cluster, (3) various cluster distribution, (4) various correlations among different dimensions, and (5) query distribution depending on data distribution. Using these features, users are able to control the distribution characteristics of data and query sets appropriate for their target applications.
On the Application of Invariant Image Parameters to Fractal Encoding of Bi-Level Images
Authors: Jonas Valantinas, Tomas Žumbakis
Venue: Informatica (2007)

Fractal image compression is an engaging and worthwhile technology that may be successfully applied to still image coding, especially at high compression ratios. Unfortunately, the large amount of computation needed for the image compression (encoding) stage is a major obstacle that needs to be overcome. In spite of numerous and many-sided attempts to accelerate fractal image compression times, the &ldquo;speed problem&rdquo; is far from being carried to its conclusion. In the paper, a new version (strategy) of the fractal image encoding technique, adapted to process bi-level (black and white) images, is presented. The strategy employs the necessary image similarity condition based on the use of invariant image parameters (image smoothness indices, image coloration ratios, etc.). It is shown that no images can be similar (in the mean squared error sense) if their respective parameter values differ more than somewhat. In the strategy proposed, the necessary image similarity condition plays a key role - it is applied to speed-up the search process for optimal pairings (range block-domain block), i.e., it enables to narrow the domain pool (search region) for each range block. Experimental analysis results show that implementation of the new fractal image encoding strategy accelerates bi-level image compression times considerably. Exceptionally good results (compression times and quality of restored images) are obtained for silhouette images.
Mutual Information of High Area Scale Space Images
Authors: Yan Li, Xiaoping Fan, Gang Li
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Medical image registration methods based on the maximization of mutual information have shown promising results. But it needs much computing time. This paper presents a new method to rigid registration based on the combination of scale images and mutual information. Firstly, the concept of area morphology is introduced. And then, the scale images are constructed with the area morphological operators. Not only the noise in the image is removed, but also the intensity levels are decreased in the scale image by area morphological operators. Moreover, the images do not be blurred. As a result, the matching process is accelerated while the accuracy and the robustness of the method is hold. For magnetic resonance and computed tomography images, behavior of mutual information matching is examined in a scale scheme. The normalized mutual information and the area scale space are combined in registration for the first time. Experimental results show that the scale approach to mutual information matching works well.
The Ingredients of Successful IT Management and Governance
Authors: Todd W. Kolb
Venue: IT Professional (2008)

Successful employees are the foundation of successful companies, but what blend of experiences and backgrounds are required to help promote such a positive experience?
Interacting Quantum Observables
Authors: Bob Coecke, Ross Duncan
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part II (2008)

We formalise the constructive content of an essential feature of quantum mechanics: the interaction of complementary quantum observables, and information flow mediated by them. Using a general categorical formulation, we show that pairs of mutually unbiased quantum observables form bialgebra-like structures. We also provide an abstract account on the quantum data encoded in complex phases, and prove a normal form theorem for it. Together these enable us to describe all observables of finite dimensional Hilbert space quantum mechanics. The resulting equations suffice to perform computations with elementary quantum gates, translate between distinct quantum computational models, establish the equivalence of entangled quantum states, and simulate quantum algorithms such as the quantum Fourier transform. All these computations moreover happen within an intuitive diagrammatic calculus.
Chaos and Graphics: Drawing and computing external rays in the multiple-spiral medallions of the Mandelbrot set
Authors: M. Romera, G. Alvarez, D. Arroyo, A. B. Orue, V. Fernandez, G. Pastor
Venue: Computers and Graphics (2008)

The multiple-spiral medallions are beautiful decorations of the Mandelbrot set. Computer graphics provide an invaluable tool to study the structure of these decorations with point symmetry (i.e., the medallions can be rotated 180^o about a central point to form an identical structure). The multiple-spiral medallions are formed by an infinity of baby Mandelbrot sets. Until now, the external arguments of the external rays landing at the cusps of the cardioids of these baby Mandelbrot sets could not be calculated. Recently, a new algorithm has been proposed in order to calculate the external arguments in the Mandelbrot set. In this paper, we use an extension of this algorithm for the calculation of the binary expansions of the external arguments of the baby Mandelbrot sets in the multiple-spiral medallions.
Research of Period Doubling Bifurcation in PWM Buck DC-DC Converter Using Harmonic Balance
Authors: Wei Li, Jinbo Zhang
Venue: Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 02 (2008)

This paper studies the period doubling bifurcation in buck converters using harmonic balance. A dynamic model of a buck converter under voltage mode control is derived. An exact harmonic balance analysis is used to obtain a necessary condition for a period doubling bifurcation to occur and provide information on its exact location. Using the condition for bifurcation, a feedforward control scheme is designed to eliminate a period doubling bifurcation. The simulation results indicate that a wider operating range for the source voltage is achieved, along with output voltage regulation.
Education---Oriented Virtual Environment for Clothing Thermal Functional Performance
Authors: Xiaonan Luo, Wenbang Hou, Yi Li
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

This paper presents a simulation environment for the education of clothing thermal function. It allows learners in a virtual environment to learn the clothing thermal comfort theory and identify the most important factors that influence clothing thermal functional performance. The virtual wearing case is defined with primary parameters and the numerical simulation results are visualized with 3D virtual environment and 2D animation, which provide virtual reality based interpretation of the thermal state and the dynamic thermal processes of the human-clothing system. This system can also be used as an effective visualization tool by textile researchers.
Skew Estimation and Correction of Text Using Bounding Box
Authors: Muhammad Sarfraz, Zeehasham Rasheed
Venue: Proceedings of the 2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation (2008)

This paper, in addition to reporting some existing techniques, proposes a new technique for skew correction. It includes a novel document skew detection algorithm based on bounding box technique. The algorithm works quite efficiently for detecting the skew and then correcting it. The method has been experimented on various text documents and very promising results have been achieved given more than 97% accuracy. A comparative study has been reported to provide a detailed analysis of the proposed method together with some other existing methods in the literature.
An empirical study of the test error versus training error in artificial neural networks
Authors: Fernando ernando Dias, Ana Antunes
Venue: Proceedings of the 9th WSEAS International Conference on International Conference on Automation and Information (2008)

This paper reports an empirical study of the behavior of the test and training errors in different systems. Frequently the test error of Artificial Neural Networks is presented with a monotonic decreasing behavior as a function of the iteration number, while the training error also continuously decreases. The present paper shows examples where such behavior does not hold, with data collected from systems where it is corrupted by either noise or actuation delay. This shows that selecting the best model is not a simple question and points to automatic procedures for the selection of models as the best solution to optimize their capacity, either with the Regularization or Early Stopping techniques.
Grid Computing 101: What's All the Fuss About?
Venue: IT Professional (2004)

The technology that aids scientists in the search for life on other planets might benefit your compute-intensive processing. 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
Stochastic Modeling of Composite Web Services for Closed-Form Analysis of Their Performance and Reliability Bottlenecks
Authors: N. Sato, K. S. Trivedi
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Web services providers often commit service-level agreements (SLAs) with their customers for guaranteeing the quality of the services. These SLAs are related not just to functional attributes of the services but to performance and reliability attributes as well. When combining several services into a composite service, it is non-trivial to determine, prior to service deployment, performance and reliability values of the composite service appropriately. Moreover, once the service is deployed, it is often the case that during operation it fails to meet its SLA and needs to detect what has gone wrong (i.e., performance/reliabilty bottlenecks).To resolve these, we develop a continuous-time Markov chain (CTMC) formulation of composite services with failures. By explicitly including failure states into the CTMC representation of a service, we can compute accurately both its performance and reliability using the single CTMC. We can also detect its performance and reliability bottlenecks by applying the formal sensitivity analysis technique. We demonstrate our approach by choosing a representative example of composite Web services and providing a set of closed-form formulas for its bottleneck detection.
Cluster Identification in Nearest-Neighbor Graphs
Authors: Markus Maier, Matthias Hein, Ulrike Luxburg
Venue: Proceedings of the 18th international conference on Algorithmic Learning Theory (2007)

Assume we are given a sample of points from some underlying distribution which contains several distinct clusters. Our goal is to construct a neighborhood graph on the sample points such that clusters are "identified": that is, the subgraph induced by points from the same cluster is connected, while subgraphs corresponding to different clusters are not connected to each other. We derive bounds on the probability that cluster identification is successful, and use them to predict "optimal" values of k for the mutual and symmetric k-nearest-neighbor graphs. We point out different properties of the mutual and symmetric nearest-neighbor graphs related to the cluster identification problem.
Team Algorithms Based on Ant Colony Optimization --- A New Multi-Objective Optimization Approach
Authors: Christian Lezcano, Diego Pinto, Benjamín Barán
Venue: Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X (2008)

This paper proposes a novel Team Algorithm (TA) approach based on Ant Colony Optimization (ACO) for multi-objective optimization problems. The proposed method has shown a significant cooperative effect of different algorithms combined in a team of algorithms, achieving robustness in the resolution of a set of various combinatorial problems. Experimentally, the proposed approach has verified a balance on different performance measures in problems as the Traveling Salesman Problem (TSP), the Quadratic Assignment Problem (QAP) and the Vehicle Routing Problem with Time Windows (VRPTW). Robustness and balance are achieved due to a novel classification and selection of the algorithms to be used by the team, considering Pareto concept.
Hybrid Local Search for Constrained Financial Portfolio Selection Problems
Authors: Luca Gaspero, Giacomo Tollo, Andrea Roli, Andrea Schaerf
Venue: Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (2007)

Portfolio selection is a relevant problem arising in finance and economics. While its basic formulations can be efficiently solved through linear or quadratic programming, its more practical and realistic variants, which include various kinds of constraints and objectives, have in many cases to be tackled by approximate algorithms. In this work, we present a hybrid technique that combines a local search, as master solver, with a quadratic programming procedure, as slave solver. Experimental results show that the approach is very promising and achieves results comparable with, or superior to, the state of the art solvers.
Incremental optimization
Authors: Dexter Kozen
Venue:  (2008)

Typical optimization problems aim to select a single solution of maximum or minimum value from a large space of feasible solutions. For many such problems, feasible solutions are subsets of a global set of elements that meet certain constraints and achieve certain goals. Recent trends in optimization literature have shown a drift from classic optimization problems, which deal with static problems, to dynamic optimization paradigms such as the online methodology. We introduce a general framework for dynamic optimization, incremental optimization, in which problem constraints are allowed to develop monotonically in discrete time steps. Solutions to such problems are sequences of tensible solutions, one for each time step, such that later solutions build on earlier solutions incrementally. Our abstract model for dynamic optimization can be applied with minimal effort to any static packing or covering problem. In this dissertation we give a formal description of this incremental model and three relevant evaluation metrics. We also demonstrate how this model can be used to incrementalize a variety of static optimization problems. We enumerate results for incremental versions of several canonical optimization problems, including maximum flow, minimum cut, and maximum-weight matching. We also present some general-purpose approximation schemes for incremental packing and covering problems. Our findings reveal that incremental considerations expose a new and diverse level of complexity in conventional optimization problems.
End-user editing of interactive multimedia documents
Authors: Maria da Graça C. Pimentel, Renan G. Cattelan, Erick L. Melo, Cesar A.C. Teixeira
Venue: Proceeding of the eighth ACM symposium on Document engineering (2008)

The problem of allowing user-centric control within multimedia presentations is important to document engineering when the presentations are specified as structured multimedia documents. In this paper we investigate the problem in the context of end-user "real-time" editing of interactive video programs.
Psychophysics & computational modeling of visual motion perception
Authors: William J. Welch
Venue:  (2007)

The goal of the research described in this dissertation is to understand the mechanisms by which the brain senses motion. I have performed a detailed psychophysical characterisation of visual motion perception in general and the peculiar omega effect originally discovered by Rose Blake in particular in which dynamic random noise in the form of random dots displayed in a circular annulus evokes the illusion of rotary motion. I have also found that a model based on the Watson Ahumada motion detector is able to explain most and key parts of the psychophysical data such as the very delicate effects of frame duration on motion perception, independence of observer performance on dot density in the display and the surprising reverse phi motion caused by contrast reversing dots. In addition to explaining the psychophysical data, the model relates reasonably well to what is known about the neurobiology of motion sensitive cells in the brain making it a realistic model of human visual motion sensing. Some other highlights of the dissertation are as follows: (1) I find that the intrinsic cortical noise in the brain which manifests itself as uncertainty in motion estimation can play an important role in perception by significantly improving detectability of subliminal motion cues at the expense of a very modest drop in performance for a suprathreshold signal ala stochastic resonance. (2) I also did experiments on observers under the influence of marijuana and found that the THC in marijuana can cause an impairment of motion perception abilities&mdash;observer performance decreases by as much as 15% and reaction time increases by as much as 222&plusmn;96 ms. (3) I find that the observer performance is invariant to dot density in the display and argue that this provides very powerful evidence against motion models based on matching dots to nearest neighbors in successive frames ala (Ullman, 1979; Dawson, 1991) etc. (4) I find and prove that the rotary motion signal does not depend on the center of rotation relative to which it is computed which explains the experimentally observed position invariance of MST(d) cells found by (Graziano, Andersen, Snowden, 1994).
Ad Auctions --- Current and Future Research
Authors: Anna R. Karlin
Venue: Proceedings of the 3rd international conference on Algorithmic Aspects in Information and Management (2007)

An exploding market has emerged during the last few years on the internet, the market of sponsored search slots. Advertisers are able to buy space on the webpages produced by popular search engines and place advertisements to promote their products alongside the regular algorithmic search results. The allocation of these advertising slots and their pricing is done via auctions. Since the introduction of this concept in 1998, sponsored search has evolved into a major source of revenue for internet giants such as Google, Yahoo!, MSN and others. Its success can be attributed partly to its effectiveness as a form of highly targeted advertising, and partly to the appealing framework that allows even small-scale advertisers to use it easily and effectively while only paying when their ad is clicked upon.Numerous interesting mathematical, algorithmic and game-theoretic questions arise when one starts to think about these auctions. How should the auctions be designed so as to maximize search engine profit? What bidding strategies should the advertisers use? What are the dynamics and convergence properties of these systems? These questions are of extreme importance to the industry as even a minor change in the framework or in the way the advertisers bid could results in millions of dollars in profit or loss for both the advertisers and the search providers.In this talk, we survey recent research on these kinds of questions and discuss open problems in the area.
Service Management for Development Tools
Authors: Y. Babich, O. Spaniol, D. Thißen
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

Tools used in development processes in chemical engineering and plastics processing are often highly heterogeneous with respect to the necessary software and hardware. In the previous chapter, several functionalities for improving a development process in different aspects was presented. But one problem still remains: when coupling such heterogeneous tools, many technical details are to be considered.This section describes a service management platform that aims at hiding such technical details from new tools as well as from developers, and at ensuring a performant execution of all tools and services. The integrative support presented in this section is located at a lower level. Here, the focus is on the provision of a transparent, efficient, and fault-tolerant access to services within the prototype developed in IMPROVE. A framework was developed that allows efficient communication support, and the management of both, integrated tools and external services. The framework also allows an a-posteriori integration of existing development tools into the management platform. Framework and management are applied at platform level in this section.