ppxscal/embedding_network huggingface dataset:
Precise Oculomotor Correlates of Visuospatial Mental Rotation and Circular Motion Imagery
Authors: Claudio De'sperati
Venue: Journal of Cognitive Neuroscience (2003)

Visual imagery is a basic form of cognition central to activities such as problem solving or creative thinking. Phenomena such as mental rotation, in which mental images undergo spatial transformations, and motion imagery, in which we imagine objects in motion, are very elusive. For example, although several aspects of visual imagery and mental rotation have been reconstructed through mental chronometry, their instantaneous evolution has never been directly observed. We paired mental chronometry to eye movement recording in subjects performing a visuospatial mental rotation task and an instructed circular motion imagery task. In both tasks, sequences of spontaneous saccades formed curved trajectories with a regular spatio-temporal evolution. In the visuospatial mental rotation task, saccadic amplitude decreased progressively within each sequence, resulting in an average gaze rotation with a bell-shaped asymmetrical angular velocity profile whose peak and mean increased with the amount of the to-be-performed rotation, as in reaching movements. In the second task, the average gaze rotation reproduced faithfully the to-be-imagined constant-velocity circular motion, thus excluding important distortions in the oculomotor performance. These findings show for the first time the instantaneous spatio-temporal evolution of mental rotation and motion imagery. Moreover, the fact that visuospatial mental rotation is modeled as a reaching act suggests that reaching pertains to the realm of visuospatial thinking, rather than being restricted to the motor domain. This approach based on eye movement recording can be profitably coupled to methods such as event-related potentials, transcranial magnetic stimulation, or functional magnetic resonance to study the precise neuronal dynamics associated with an ongoing mental activity.
Polarimetric Image Segmentation via Maximum-Likelihood Approximation and Efficient Multiphase Level-Sets
Authors: Ismail Ben Ayed, Amar Mitiche, Ziad Belhadj
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2006)

This study investigates a level set method for complex polarimetric image segmentation. It consists of minimizing a functional containing an original observation term derived from maximum-likelihood approximation and a complex Wishart/Gaussian image representation and a classical boundary length prior. The minimization is carried out efficiently by a new multiphase method which embeds a simple partition constraint directly in curve evolution to guarantee a partition of the image domain from an arbitrary initial partition. Results are shown on both synthetic and real images. Quantitative performance evaluation and comparisons are also given.
Visual Speech Recognition Using Image Moments and Multiresolution Wavelet Images
Authors: Wai C. Yau, Dinesh K. Kumar, Sridhar P. Arjunan, Sanjay Kumar
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

This paper describes a new technique for recognizing speech using visual speech information. The video data of the speaker's mouth is represented using grayscale images named as motion history image (MHI). MHI is generated by applying accumulative image differencing on the frames of the video to implicitly represent the temporal information of the mouth movement. The MHIs are decomposed into wavelet sub images using Discrete Stationary Wavelet Transform (SWT). Three moment-based features (geometric moments, Zernike moments and Hu moments) are extracted from the SWT approximate sub images. Multilayer perceptron (MLP) type artificial neural network (ANN) with back propagation learning algorithm is used to classify the moments features. This paper evaluates and compares the image representation ability of the different moments. The initial experiments show that this method can classify English consonants with an error rate less than 5%.
Analysis and implications of student contact patterns derived from campus schedules
Authors: Vikram Srinivasan, Mehul Motani, Wei Tsang Ooi
Venue: Proceedings of the 12th annual international conference on Mobile computing and networking (2006)

Characterizing mobility or contact patterns in a campus environment is of interest for a variety of reasons. Existing studies of these patterns can be classified into two basic approaches - model based and measurement based. The model based approach involves constructing a mathematical model to generate movement patterns while the measurement based approach measures locations and proximity of wireless devices to infer mobility patterns. In this paper, we take a completely different approach. First we obtain the class schedules and class rosters from a university-wide Intranet learning portal, and use this information to infer contacts made between students. The value of our approach is in the population size involved in the study, where contact patterns among 22341 students are analyzed. This paper presents the characteristics of these contact patterns, and explores how these patterns affect three scenarios. We first look at the characteristics from the DTN perspective, where we study inter-contact time and time distance between pairs of students. Next, we present how these characteristics impact the spread of mobile computer viruses, and show that viruses can spread to virtually the entire student population within a day. Finally, we consider aggregation of information from a large number of mobile, distributed sources, and demonstrate that the contact patterns can be exploited to design efficient aggregation algorithms, in which only a small number of nodes (less than 0.5%) is needed to aggregate a large fraction (over 90%) of the data.
Performance evaluation of ASAP3 for steady-state output analysis
Authors: Natalie M. Steiger, Emily K. Lada, James R. Wilson
Venue: Proceedings of the 37th conference on Winter simulation (2005)

An experimental performance evaluation of ASAP3 is presented, including several queueing systems with characteristics typically encountered in practical applications of steady-state simulation analysis procedures. Based on the method of nonoverlapping batch means, ASAP3 is a sequential procedure designed to produce a confidence-interval estimator of a steady-state mean response that satisfies user-specified precision and coverage-probability requirements. ASAP3 is compared with its predecessor ASAP and the batch means procedure of Law and Carson (LC) in the following test problems: (a) queue waiting times in the M/M/1/LIFO, M/H2/1, and M/M/1 queues with 80% server utilization; and (b) response (sojourn) times in a central server model of a computer system. Regarding conformance to the given precision and coverage-probability requirements, ASAP3 compared favorably with the ASAP and LC procedures. Regarding the average sample sizes needed to satisfy progressively more stringent precision requirements, ASAP3's efficiency was reasonable for the given test problems.
Complex-order dynamics in hexapod locomotion
Authors: Manuel F. Silva, J. A. Tenreiro Machado, Ramiro S. Barbosa
Venue: Signal Processing (2006)

This paper studies the dynamics of foot-ground interaction in hexapod locomotion systems. For that objective the robot motion is characterized in terms of several locomotion variables and the ground is modelled through a non-linear spring-dashpot system, with parameters based on the studies of soil mechanics. Moreover, it is adopted an algorithm with foot-force feedback to control the robot locomotion. A set of model-based experiments reveals the influence of the locomotion velocity on the foot-ground transfer function, which presents complex-order dynamics.
Efficient Processing of Narrow Range Queries in Multi-dimensional Data Structures
Authors: Michal Kratky, Vaclav Snasel, Jaroslav Pokorny, Pavel Zezula
Venue: Proceedings of the 10th International Database Engineering and Applications Symposium (2006)

Multi-dimensional data structures are applied in many real index applications, i.e. data mining, indexing multimedia data, indexing of text documents and so on. Many index structures and algorithms have been proposed. There are two major approaches to multi-dimensional indexing: data structures to indexing metric and vector spaces. R-trees, R*-trees and (B)UB-trees are representatives of the vector data structures. These data structures provide efficient processing of many types of queries, i.e. point queries, range queries and so on. As far as the vector data structures are concerned, the range query retrieves all points in defined hyper box in an n-dimensional space. The narrow range query is an important type of the range query. Its processing is inefficient in vector data structures. Moreover, the efficiency decreases as the dimension of the indexed space increases. We depict an application of the signature for more efficient processing of narrow range queries. The approach puts the signature into the multi-dimensional data structures like R-tree or UB-tree but original functionalities are preserved, i.e. the range query algorithm for general range query. The novel data structure is called the signature data structure, e.g., Signature R-tree or Signature UB-tree.
Some Applications to Variational&mdash;Hemivariational Inequalities of the Principle of Symmetric Criticality for Motreanu---Panagiotopoulos Type Functionals
Authors: Hannelore Lisei, Csaba Varga
Venue: Journal of Global Optimization (2006)

Using the principle of symmetric criticality for Motreanu---Panagiotopoulos type functionals we give some existence and multiplicity results for a class of variational---hemivariational inequalities on $$\mathbb {R}$$ L+M .
CRYSTAL - A new density-based fast and efficient clustering algorithm
Authors: Priyadarshi Bhattacharya, Marina L. Gavrilova
Venue: Proceedings of the 3rd International Symposium on Voronoi Diagrams in Science and Engineering (2006)

In this paper, we present a fast O(nlogn) clustering algorithm based on Delaunay Triangulation for identifying clusters of different shapes, not necessarily convex. The clustering result is similar to human perception of clusters. The novelty of our method is the growth model we follow in the cluster formation that resembles the natural growth of a crystal. Our algorithm is able to identify dense as well as sparse clusters and also clusters connected by bridges. We demonstrate clustering results on several synthetic datasets and provide a comparison with popular KMeans based clustering methods. The clustering is based purely on proximity analysis in the Delaunay Triangulation and avoids usage of global parameters. It is robust in the presence of noise. Finally, we demonstrate the capability of our clustering algorithm in handling very large datasets.
Recent progress in robust and quality Delaunay mesh generation
Authors: Qiang Du, Desheng Wang
Venue: Journal of Computational and Applied Mathematics (2006)

In this paper, some current issues of Delaunay mesh generation and optimization are addressed, with particular emphasis on the robustness of the meshing procedure and the quality of the resulting mesh. We also report new progress on the robust conforming and constrained boundary recovery in three dimensions, along with the quality mesh generation based on Centroidal Voronoi tessellations. Applications to the numerical solution of differential equations and integrations with other softwares are discussed, including a brief discussion on the joint mesh and solver adaptation strategy.
Building High-Performance and Reconfigurable Bandwidth Controllers with Adaptive Clustering
Authors: Chien-Hua Chiu, Chin-Yen Lee, Pan-Lung Tsai, Chun-Ying Huang, Chin-Laung Lei
Venue: Proceedings of the International Conference on Systems and Networks Communication (2006)

As quality of service gains more and more attention, bandwidth controllers gradually become one of the most important network systems used in modern Internet environment. The demand for high-performance in-line bandwidth controllers is driven by the growing bandwidth available in the last mile WAN links as well as the sophisticated packet processing functions that become essential in current computer networks. In this paper, we propose an adaptive clustering scheme to scale the throughput of in-line devices and implement the bandwidth control functions over a cluster of in-line devices. The proposed scheme aggregates the processing power of multiple in-line devices in the cluster by making incoming traffic self-dispatched in a transparent fashion, and incorporates a flow migration mechanism that keeps the load of each device balanced. The resulted cluster is also able to tolerate device failures and hence is run-time reconfigurable. Based on the proposed scheme, we successfully design a distributed policy adjustment algorithm, the proportional bandwidth allocation algorithm, and implement a clustered bandwidth controller over embedded Linux. The results of performance evaluation suggest that the proposed traffic redistribution mechanism and distributed policy adjustment algorithm can be used together to realize high-performance and reconfigurable bandwidth controllers.
Adaptive wireless-network testbed for cognitive radio technology
Authors: Kentaro Ishizu, Yoshia Saito, Zhou Lan, Masahiro Kuroda
Venue: Proceedings of the 1st international workshop on Wireless network testbeds, experimental evaluation characterization (2006)

Coordination is expected between mobile terminals, base stations/access points, and spectrum-management servers in cognitive-enabled wireless networks. A testbed for cognitive radio needs to deal with these components to verify low-level configuration protocols and functions on cognitive-radio devices, and to evaluate high-level network protocols and throughputs including new MACs designed for cognitive radio using various applications running on large numbers of nodes. We propose a testbed for an adaptive wireless network under which terminals communicate using both real cognitive-radio devices and those virtually configured. All the stacks from the MAC to the application layer are programmable conforming to the common interface for the MIRAI Cognitive Radio Execution Framework (MIRAI-CREF). The configuration for the physical layer is selected from either a real device or a software-defined pseudo device, which together provide real physical-layer phenomena dependent on device implementations and scalability in the number of nodes. The testbed works with the two physical-layer configurations mixed at the same time. The testbed is flexible enough to configure cognitive-radio device functions and protocols. It is also intended to be used not only by local users but also remote users via the Internet to evaluate protocols and various cognitive features.
Optimal Portfolio with Consumption Choice under Jump-Diffusion Process
Authors: Shuping Wan
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 2 (2006)

The optimal portfolio problem for a single riskless bond and risky stock modeled by jump-diffusion process has been established. The investment objective is maximizing the utility of his consumption and terminal wealth. The problem is formulated as a stochastic optimal control problem. The verification theorem and HJB equation for the optimal trading strategies are given by stochastic optimal control theory. The analytic solution for the constant relative risk aversion utility are obtained, and some simulation results are presented.
Control Theory and Fast Marching Techniques for Brain Connectivity Mapping
Authors: Emmanuel Prados, Stefano Soatto, Christophe Lenglet, Jean-Philippe Pons, Nicolas Wotawa, Rachid Deriche, Olivier Faugeras
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

We propose a novel, fast and robust technique for the computation of anatomical connectivity in the brain. Our approach exploits the information provided by Diffusion Tensor Magnetic Resonance Imaging (or DTI) and models the white matter by using Riemannian geometry and control theory. We show that it is possible, from a region of interest, to compute the geodesic distance to any other point and the associated optimal vector field. The latter can be used to trace shortest paths coinciding with neural fiber bundles. We also demonstrate that no explicit computation of those 3D curves is necessary to assess the degree of connectivity of the region of interest with the rest of the brain. We finally introduce a general local connectivity measure whose statistics along the optimal paths may be used to evaluate the degree of connectivity of any pair of voxels. All those quantities can be computed simultaneously in a Fast Marching framework, directly yielding the connectivity maps. Apart from being extremely fast, this method has other advantages such as the strict respect of the convoluted geometry of white matter, the fact that it is parameter-free, and its robustness to noise. We illustrate our technique by showing results on real and synthetic datasets. OurGCM(Geodesic Connectivity Mapping) algorithm is implemented in C++ and will be soon available on the web.
Compensation Based Grid Scheduling
Authors: R. Anitha, N. Rajkumar
Venue: Proceedings of the 9th International Conference on Information Technology (2006)

In the grid-computing environment, resources are autonomous, distributed with varying pricing policies. The Grid comprises of the contributors and the users who each play a role for certain compensational benefits. The proposed model is a Tender Contract type that envisages a real market operating on the supply and demand perspectives of a defined commodity. It allows a decentralized selection of contributors by the user for the execution of his job. The goal is to compensate the contributor for his resource and the user to pay less for his job. The contributor benefits by profits and fairness, which is evident as pricing of the resource based on its demand and efficiency. The user is compensated with the successful completion of jobs and fine amount borne by the contributor for not guaranteeing the defined deadline requirements. Simulation and results show that both the contributors and the users are compensated equally well.
Regularity of an Euler-Bernoulli equation with Neumann control and collocated observation
Authors: Bao-Zhu Guo, Zhi-Chao Shao
Venue: Journal of Dynamical and Control Systems (2006)

This paper studies the regularity of an Euler-Bernoulli plate equation on a bounded domain of Rn, n ≥ 2, with partial Neumann control and collocated observation. It is shown that the system is not only well posed in the sense of D. Salamon but also regular in the sense of G. Weiss. It is also shown that the corresponding feedthrough operator is zero.
Simulation optimization using balanced explorative and exploitative search
Authors: Andrei A. Prudius, Sigrún Andradóttir
Venue: Proceedings of the 36th conference on Winter simulation (2004)

We present a new random search method for solving simulation optimization problems. Our approach emphasizes the need for maintaining the right balance between exploration and exploitation during various stages of the search. Exploration represents global search for promising solutions within the entire feasible region, while exploitation involves local search of promising subregions. Preliminary numerical results are provided that show the performance of the method applied to solve deterministic and stochastic optimization problems.
A Mobile Service Middleware Supported 4G Adaptive Multimedia Applications
Authors: Baode Fan, Zhaolin Yin, Sainan Zhang
Venue: Proceedings of the Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (2006)

With the development of mobile devices and wireless communication technologies, users and devices will face an environment full of changes. It is indispensable for a system to adapt to the environment changes, which we call context-awareness. This paper introduces the adaptive mechanisms for embedded systems from the point of view of the data. The data in a context-aware system are in three different forms in different stage: the sensor data, the context, the situation. This paper introduces the context model which consists of three layers and the adaptive mechanisms in different layer to enable the system adaptive to contexts. Besides, we develop an example to show how the clustering and reasoning technology are used to recognize and derive the higher level context.
A cutting process for random mappings
Authors: Jennie C. Hansen, Jerzy Jaworski
Venue: Random Structures Algorithms (2007)

In this paper we consider a cutting process for random mappings. Specifically, for 0 < m < n, we consider the initial (uniform) random mapping digraph Gn on n labeled vertices, and we delete (if possible), uniformly and at random, m noncyclic directed edges from Gn. The maximal random digraph consisting of the unicyclic components obtained after cutting the m edges is called the trimmed random mapping and is denoted by G nm. If the number of noncyclic directed edges is less than m, then G nm consists of the cycles, including loops, of the initial mapping Gn. We consider the component structure of the trimmed mapping G nm. In particular, using the exact distribution we determine the asymptotic distribution of the size of a typical random connected component of G nm as n, m &rsquo; . This asymptotic distribution depends on the relationship between n and m and we show that there are three distinct cases: (i) $m=o(\sqrt{n})$, (ii) $m=\beta\sqrt{n}$, where &sup2; > 0 is a fixed parameter, and (iii) $\sqrt{n}=o(m)$. This allows us to study the joint distribution of the order statistics of the normalized component sizes of G nm. When $m=o(\sqrt{n})$, we obtain the PoissonDirichlet(1/2) distribution in the limit, whereas when $\sqrt{n}=o(m)$ the limiting distribution is PoissonDirichlet(1). Convergence to the PoissonDirichlet(&tilde;) distribution breaks down when $m=O(\sqrt{n})$, and in particular, there is no smooth transition from the ${\cal P}$D(1/2) distribution to the ${\cal P}$D(1) via the PoissonDirichlet distribution as the number of edges cut increases relative to n, the number of vertices in Gn. &copy; 2006 Wiley Periodicals, Inc. Random Struct. Alg., 2006
Provenance-Aware Sensor Data Storage
Authors: Jonathan Ledlie, Chaki Ng, David A. Holland
Venue: Proceedings of the 21st International Conference on Data Engineering Workshops (2005)

Sensor network data has both historical and realtime value. Making historical sensor data useful, in particular, requires storage, naming, and indexing. Sensor data presents new challenges in these areas. Such data is location-specific but also distributed; it is collected in a particular physical location and may be most useful there, but it has additional value when combined with other sensor data collections in a larger distributed system. Thus, arranging location-sensitive peer-to-peer storage is one challenge. Sensor data sets do not have obvious names, so naming them in a globally useful fashion is another challenge. The last challenge arises from the need to index these sensor data sets to make them searchable. The key to sensor data identity is provenance, the full history or lineage of the data. We show how provenance addresses the naming and indexing issues and then present a research agenda for constructing distributed, indexed repositories of sensor data.