ppxscal/embedding_network huggingface dataset:
Research on Optimum Position for Straight Lines Model
Authors: Li-Juan Qin, Yu-Lan Hu, Ying-Zi Wei, Hong Wang, Yue Zhou
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Quantization errors are the primary source that affects the accuracy of pose estimation. For the model at different placement positions, quantization errors have different effects on the results of pose estimation. The analysis of optimum displacement for the model can increase the accuracy of pose estimation. In this paper, mathematical model of the propagation of quantization errors from a two-dimensional image plane to the 3D model is set up. What's more, optimization function for the analysis of optimum placement position of model is set up. For given model, we obtain optimum placement position of model with respect to camera. At last, the simulation results show that it has better pose estimation accuracy at optimum place than at other places.
Cone-Realizations of Discrete-Time Systems with Delays
Authors: Tadeusz Kaczorek
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

A new notion of cone-realization for discrete-time linear systems with delays is proposed. Necessary and sufficient conditions for the existence of cone-realizations of discrete-time linear systems with delays are established. A procedure is proposed for computation of a cone-realization for a given proper rational matrix T(z). It is shown that there exists a (${\mathcal{P,Q,V}}$)-cone realization of T(z) if and only if there exists a positive realization of ${\bf \bar T}$ (z) = VT(z)Q ¿ 1 where V, Q and P are non-singular matrices generating the cones $\cal V$, $\cal Q$ and $\cal P$ respectively.
Global and Local Processes in a Model of Innovation
Authors: Marco Villani, Roberto Serra, Luca Ansaloni, David Lane
Venue: Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry (2008)

In this work we present the introduction of spatial constraints in a model of generation and diffusion of innovations. The presence of spatial limitations introduces several feedbacks, whose main effects are the decrease of global diversity in favour of a higher robustness, despite the apparent minor success of the individual agents. All these features hold contemporarily, but the individuated feedbacks are able to explain their only apparently contradictory nature. None of these results is obvious, nor can it be simply deduced from the qualitative theory. Moreover, the simulations could make possible comparisons between the model behaviours and the theory claims, indicating new ways of improvement and development
Improvement of Page Ranking Algorithm Based on Timestamp and Link
Authors: Shiguang Ju, Zheng Wang, Xia Lv
Venue: Proceedings of the 2008 International Symposiums on Information Processing (2008)

The traditional ranking algorithm favors the old pages, which makes old pages always appear on the top of the ranking results when pages are ranked according to the dynamic web by the static ranking algorithm. Therefore, this paper introduces temporal-link-analysis algorithm to resolve the problem. This algorithm uses the last modification time that returned by the HTTP response as the timestamp of nodes and links concerned. And the weight of the in-link and out-link are also integrated to compute the overall weight of the pages. Using the WTPR algorithm can make the old pages decline and new pages raise in the ranking result, meanwhile it can help the old pages which have high-quality get higher rank value than common old pages.
High performance architecture using speculative threads and dynamic memory management hardware
Authors: Krishna Kavi
Venue:  (2007)

With the advances in very large scale integration (VLSI) technology, hundreds of billions of transistors can be packed into a single chip. With the increased hardware budget, how to take advantage of available hardware resources becomes an important research area. Some researchers have shifted from control flow Von-Neumann architecture back to dataflow architecture again in order to explore scalable architectures leading to multi-core systems with several hundreds of processing elements.In this dissertation, I address how the performance of modern processing systems can be improved, while attempting to reduce hardware complexity and energy consumptions. My research described here tackles both central processing unit (CPU) performance and memory subsystem performance. More specifically I will describe my research related to the design of an innovative decoupled multithreaded architecture that can be used in multi-core processor implementations. I also address how memory management functions can be off-loaded from processing pipelines to further improve system performance and eliminate cache pollution caused by runtime management functions.
A Computational Model of Saliency Map Read-Out during Visual Search
Authors: Mia Šetić, Dražen Domijan
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

When searching for a target in a visual scene filled with distractors, the mechanism of inhibition of return prevents revisiting previously attended locations. We proposed a new computational model for the inhibition of return, which is able to examine priority or saliency map in a manner consistent with psychophysical findings. The basic elements of the model are two neural integrators connected with two inhibitory interneurons. The integrators keep the saliency value of the currently attended location in the working memory. The inhibitory inter-neurons modulate a feedforward flow of information between the saliency map and the output map which points to the location of interest. Computer simulations showed that the model is able to read-out the saliency map when the objects are moving or when eye movements are present. Also, it is able to simultaneously select more then one location, even when they are non-contiguous. The model can be considered as a neural implementation of the episodic theory of attention.
Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis
Authors: Matthew B. Blaschko, Christoph H. Lampert, Arthur Gretton
Venue: Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I (2008)

Kernel canonical correlation analysis (KCCA) is a fundamental technique for dimensionality reduction for paired data. By finding directions that maximize correlation in the space implied by the kernel, KCCA is able to learn representations that are more closely tied to the underlying semantics of the data rather than high variance directions, which are found by PCA but may be the result of noise. However, meaningful directions are not only those that have high correlation to another modality, but also those that capture the manifold structure of the data. We propose a method that is able to simultaneously find highly correlated directions that are also located on high variance directions along the data manifold. This is achieved by the use of semi-supervised Laplacian regularization in the formulation of KCCA, which has the additional benefit of being able to use additional data for which correspondence between the modalities is not known to more robustly estimate the structure of the data manifold. We show experimentally on datasets of images and text that Laplacian regularized training improves the class separation over KCCA with only Tikhonov regularization, while causing no degradation in the correlation between modalities. We propose a model selection criterion based on the Hilbert-Schmidt norm of the semi-supervised Laplacian regularized cross-covariance operator, which can be computed in closed form. Kernel canonical correlation analysis (KCCA) is a dimensionality reduction technique for paired data. By finding directions that maximize correlation, KCCA learns representations that are more closely tied to the underlying semantics of the data rather than noise. However, meaningful directions are not only those that have high correlation to another modality, but also those that capture the manifold structure of the data. We propose a method that is simultaneously able to find highly correlated directions that are also located on high variance directions along the data manifold. This is achieved by the use of semi-supervised Laplacian regularization of KCCA. We show experimentally that Laplacian regularized training improves class separation over KCCA with only Tikhonov regularization, while causing no degradation in the correlation between modalities. We propose a model selection criterion based on the Hilbert-Schmidt norm of the semi-supervised Laplacian regularized cross-covariance operator, which we compute in closed form.
Modelling of electrical impedance epigastrography signals to investigate the efficacy of a motion artifact rejection algorithm
Authors: M. R. Freedman, A. Gaitanis, N. M. Spyrou
Venue: Journal of Computational Methods in Sciences and Engineering (2005)

Electrical Impedance Epigastrography (EIE) is a non-invasive method that allows the assessment of gastric emptying rates without using ionizing radiation. This method works by applying an alternating current with a frequency of 32 kHz, which can be varied by the operator from 1 to 4 mA, through electrodes over the epigastric region, and measuring the potential difference between them. The post acquisition analysis relies on the Short-Time Fourier Transform (STFT) to extract the gastric motility component of the signal (centre frequency of 0.05 Hz with a bandwidth of 0.02 Hz). Motion artifacts that occur during the test have been found to produce positive and negative spikes. Software was produced to model the EIE signals and apply simulated motion artifacts of known amplitude at specific points in the signal. The signals were labelled pseudo EIE signals. Due to the large frequency range of a delta function, the spikes produced false positives in the frequency domain, suggesting the presence of gastric contractility when there was none, or exaggerating the magnitude of real events in both real and pseudo EIE signals. A motion artifact rejection algorithm (MARA) was developed for removing the artifacts in the time domain, before processing by the STFT. The efficacy of the algorithm was tested on the pseudo EIE signals by comparing the power density calculated by the STFT before and after the simulation of artifacts and after the application of the algorithm.
Plenary lecture VII: the spectral problems of some nonlinear differential equations
Authors: Gabriella Bognar
Venue: Proceedings of the American Conference on Applied Mathematics (2008)

The present study deals with eigenvalue problems of nonlinear differential equations with p-Laplacian. If p=1, these problems reduce to linear eigenvalue problems which are well understood and treated in many classical books. For the nonlinear differential equations we consider the eigenvalues and eigenfunctions concerning different domains, some isoperimetric problems and some properties of the periodic solutions. Our aim is to present results on the nonlinear differential equations involving p-Laplacian. We show similarities in the qualitatvive behavior of solutions of the linear and nonlinear problems, and we also point out phenomena where properties of solutions considerably differ.
Organising the Complexity of Behaviour
Authors: Stathis Kasderidis
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

In [1] we have developed a computational model for multiple goals. The agent behaviour is organised in families of competing goals (plans) for determining priorities of execution. This paper extends the previous model by providing a method for executing complex plans consisting of a number of goals and/or other sub-plans. The various dependencies among goals/plans are analysed and a mechanism is suggested which provides additional voting to the priority of a component goal. For the class of independent goals it is possible to interleave sub-goals for achieving better performance. A number of simulation experiments are described and results indicate a more flexible behaviour. We conclude with a summary of findings and a discussion for future work.
Formal Verification of ASM Models Using TLA +
Authors: Hocine El-Habib Daho, Djilali Benhamamouch
Venue: Proceedings of the 1st international conference on Abstract State Machines, B and Z (2008)

The notion of Abstract State Machines(ASMs) handles a practical new approach for modeling and analysing various kinds of discrete dynamic systems. In the context of the verification problem of ASM models, formal verification techniques based on variants of restricted first-order temporal logic have been used to verify correctness of restricted forms of ASM specifications. In this spirit, the current work shows how the state-based logic of TLA + can be employed to formally reason about dynamic systems formalised in terms of ASMs.
Archival image indexing with connectivity features using randomized masks
Authors: Arindam Biswas, Partha Bhowmick, Bhargab B. Bhattacharya
Venue: Applied Soft Computing (2008)

Connectivity properties capture a natural spatial feature of a binary image. Albeit they are easy to compute, more often than not, they alone fail to provide a good characterization of the image because of the fact that several different images may have the same connectivity features. Typically, other types of parameters, e.g., moments, are used to augment the connectivity feature for efficient indexing and retrieval purposes. In this work, an alternative approach is proposed. Instead of considering other diverse features, which are computationally intensive, only the connectivity features of the image are used iteratively using a novel concept of spatial masking. For this purpose, a greedy algorithm for constructing a spatial feature vector of variable length for a binary image, is proposed. The algorithm is based on XOR-ing the image bit-plane with a few pseudo-random synthetic masks, and its novelty lies in computing the feature vector iteratively, depending on the size and diversity of the image database. The classical Euler number and the two primary connectivity features from which it is derived, namely, the number of connected components and the number of holes, are used to finally generate a unique feature vector for each binary image in the database using a fuzzy membership function customized for the given database. The method is particularly suitable for large-sized image archives of a digital library, where each image contains one or more objects. It is found to converge within only three iterations for a postal stamp database consisting of 2598 images, and also for a logo database of 1034 images. A data structure called discrimination tree has been introduced for supporting efficient storage and indexing of the images using the above feature vector.
A throughput maximization strategy for scheduling transaction-intensive workflows on SwinDeW-G
Authors: Ke Liu, Jinjun Chen, Yun Yang, Hai Jin
Venue: Concurrency and Computation: Practice Experience (2008)

With the rapid development of e-business, workflow systems now have to deal with transaction-intensive workflows whose main characteristic is the huge number of concurrent workflow instances. For such workflows, it is important to maximize the overall throughput to provide good quality of service. However, most of the existing scheduling algorithms are designed for scheduling of a single complex scientific workflow instance and are not efficient enough for scheduling transaction-intensive workflows. To address this problem, we propose a throughput maximization strategy (TMS), which contains two specific algorithms for scheduling transaction-intensive workflows at the instance and task levels, respectively. The first algorithm called Opposite Average Load tries to maximize the overall throughput by pursuing the overall load balance at the instance level, whereas the second algorithm called Extended Min&ndash;Min tries to further maximize the overall throughput at the task level by increasing the utilization rate of resources within each local autonomous group. The comparison and simulation performed on Swinburne Decentralized Workflow for Grid (SwinDeW-G), a peer-to-peer-based grid workflow environment, demonstrate that our strategy can improve the overall throughput significantly over existing scheduling algorithms when scheduling transaction-intensive workflows. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Combination of Image Registration Algorithms for Patient Alignement in Proton Beam Therapy
Authors: Rachid Belaroussi, Guillaume Morel
Venue: Proceedings of the 3rd international conference on Image and Signal Processing (2008)

We propose a measure of patient alignment in a video by combining different image representations : grey level, edges, and a set of feature points. When patient head is correctly positionned, a reference image with its ellipse is stored as a template of correct alignment. Edges detection results in a second template of the correct head location. Corners inside the ellipse are detected and tracked: a set of N feature points composes a third template. Template matching computes a measure of similarity between a representation of the reference image and a window sliding around the reference location. Similarity with these three models are combined by the product rule. Location of window the most similar to the templates gives the translation T of the reference model in the image plane. This measure of patient misalignment could avoid X-ray verification of patient alignment, reducing patient dose and duration of treatment sessions.
Modeling a Hands-Free Controlled Power Wheelchair
Authors: Ludmila C. Silva, Torsten Felzer, Geraldo G. Delgado Neto, Rainer Nordmann, Franco G. Dedini
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper will present a study of the dynamics of the contact between the tire of a wheelchair and the ground. The model of the contact between road and tire has been implemented using a mathematical concept in a 2D multibody program, creating a laboratory. With this laboratory, it is possible to see the behavior of the wheelchair with different input sources. In this work the input is taken care of by a program called HaWCoS which allows the user to control a wheelchair without the need to use the hands. The results make it possible to develop new products for people with special needs and to develop better control systems by taking the dynamic behavior of wheelchairs into consideration.
Variable Gain Takagi-Sugeno Fuzzy Logic Controllers
Authors: Reghunadhan Rajesh, M. Ramachandra Kaimal
Venue: Informatica (2006)

Most of the Takagi-Sugeno Fuzzy (TSF) systems found in the literature have only used linear functions of input variables as rule consequent and can be called as TSF Models with Fixed Coefficient (TSFMFC). This paper presents TSF model with variable coefficient (TSFMVC) which can more closely approximate a class of nonlinear systems, nonlinear dynamic systems, and nonlinear control systems. It is also shown that TSFMFC is a special case of TSFMVC. Moreover Variable Gain TSF Controller (VGTSFC) is defined and it performs better, as shown by the simulation results, when compared with Fixed Gain TSF Controller (FGTSFC).
Learning to Select Team Strategies in Finite-Timed Zero-Sum Games
Authors: Manuela Veloso
Venue: Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing (2007)

Games, by definition, offer the challenge of the presence of an opponent, to which a playing strategy should respond. In finite-timed zero-sum games, the strategy should enable to win the game within a limited playing time. Motivated by robot soccer, in this talk, we will present several approaches towards learning to select team strategies in such finite-timed zero-sum games. We will introduce an adaptive playbook approach with implicit opponent modeling, in which multiple team strategies are represented as variable weighted plays. We will discuss different plays as a function of different game situations and opponents. In conclusion, we will present an MDP-based learning algorithm to reason in particular about current score and game time left. Through extensive simulated empirical studies, we will demonstrate the effectiveness of the learning approach. In addition, the talk will include illustrative examples from robot soccer. The major part of this work is in conjunction with my PhD student Colin McMillen.
Emerging coordination in infinite team Markov games
Authors: Francisco S. Melo, M. Isabel Ribeiro
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

In this paper we address the problem of coordination in multi-agent sequential decision problems with infinite statespaces. We adopt a game theoretic formalism to describe the interaction of the multiple decision-makers and propose the novel approximate biased adaptive play algorithm. This algorithm is an extension of biased adaptive play to team Markov games defined over infinite state-spaces. We establish our method to coordinate with probability 1 in the optimal strategy and discuss how this methodology can be combined with approximate learning architectures. We conclude with two simple examples of application of our algorithm.
Bayesian Assessment of Rounding-Based Disclosure Control
Authors: Jon J. Forster, Roger C. Gill
Venue: Proceedings of the UNESCO Chair in data privacy international conference on Privacy in Statistical Databases (2008)

In this paper, we consider how the security of a disclosure control mechanism based on randomised, but uncontrolled, rounding can be assessed by Bayesian methods. We develop a methodology, based on Markov chain Monte Carlo, for estimating the conditional (posterior) probability distribution for the original cell counts given the released rounded values. An effective rounding-based disclosure control will result in high posterior uncertainty about the true value. Conversely, a posterior distribution concentrated on a single value provides evidence of ineffective disclosure control.
Increasing ZigBee network lifetime with X-MAC
Authors: Pablo Suarez, Carl-Gustav Renmarker, Adam Dunkels, Thiemo Voigt
Venue: Proceedings of the workshop on Real-world wireless sensor networks (2008)

The ZigBee standard builds on the assumption that infrastructure nodes have a constant power supply. ZigBee therefore does not provide any power-saving mechanisms for routing nodes, which limits the lifetime of battery-powered ZigBee networks to a few days. This short lifetime drastically restricts the possible application scenarios for ZigBee. To expand the usefulness of ZigBee, we present a ZigBee implementation where we replace the default ZigBee MAC protocol with the power-saving MAC protocol X-MAC. Our results show that X-MAC reduces the power consumption for ZigBee routing nodes with up to 90%, leading to a ten-fold increase in network lifetime at the price of a slight increase in network latency. Furthermore, we are the first to experimentally quantify the energy-efficiency of X-MAC in a multihop scenario. Our results indicate that X-MAC reduces the power consumption of idle nodes that are within communication range of two communicating nodes, suggesting that X-MAC may be able to mitigate the hot-spot problem in sensor networks.