Compact UWB-MIMO Triple Notched Antenna for Isolation Reduction

Wireless Personal Communications - In this article compact multiple input multiple output (MIMO) antenna with triple notch at the ultra-wideband application having two identical monopole antennas...     

A method for functional magnetic resonance imaging of olfaction

A method for generating olfactory stimuli for humans within a functional magnetic resonance imaging (fMRI) experimental design is described. The system incorporates a nasal-mask in which the change from odorant to no-odorant conditions occurs in less than 500 ms and is not accompanied by visual, auditory, tactile, or thermal cues. The mask provides an ordorant-free environment following prolonged ordorant presence. Specific imaging parameters that are conducive to the study of the human olfactory system are described. In a pilot study performed using these methods, the specific patterns of activation observed converged with published experimental and clinical findings.     

Synchronization models for multimedia presentation with user participation

This paper addresses the key issue of providingflexible multimedia presentation with user participation and suggests synchronization models that can specify the user participation during the presentation. We study models like the Petrinet-based hypertext model and the object composition Petri nets (OCPN). We suggest adynamic timed Petri nets structure that can model pre-emptions and modifications to the temporal characteristics of the net. This structure can be adopted by the OCPN to facilitate modeling of multimedia synchronization characteristics with dynamic user participation. We show that the suggested enhancements for the dynamic timed Petri nets satisfy all the properties of the Petri net theory. We use the suggested enhancements to model typical scenarios in a multimedia presentation with user inputs.     

Point-based manifold harmonics

This paper proposes an algorithm to build a set of orthogonal Point-Based Manifold Harmonic Bases (PB-MHB) for spectral analysis over point-sampled manifold surfaces. To ensure that PB-MHB are orthogonal to each other, it is necessary to have symmetrizable discrete Laplace-Beltrami Operator (LBO) over the surfaces. Existing converging discrete LBO for point clouds, as proposed by Belkin et al. [CHECK END OF SENTENCE], is not guaranteed to be symmetrizable. We build a new point-wisely discrete LBO over the point-sampled surface that is guaranteed to be symmetrizable, and prove its convergence. By solving the eigen problem related to the new operator, we define a set of orthogonal bases over the point cloud. Experiments show that the new operator is converging better than other symmetrizable discrete Laplacian operators (such as graph Laplacian) defined on point-sampled surfaces, and can provide orthogonal bases for further spectral geometric analysis and processing tasks.     

Motion fault detection and isolation in Body Sensor Networks

Significant amount of research and development is being directed on monitoring activities of daily living of senior citizens who live alone as well as those who have certain motion disorders such as Alzheimer’s and Parkinson’s. A combination of sophisticated inertial sensing, wireless communication and signal processing technologies has made such a pervasive and remote monitoring possible. Due to the nature of the sensing and communication mechanisms, these monitoring sensors are susceptible to errors and failures. In this paper, we address the issue of identifying and isolating faulty sensors in a Body Sensor Network that is used for remote monitoring of daily living activities. We identify three different types of faults in a Body Sensor Network and propose fault isolation strategies using history-based and non-history based approaches. The contributions of this paper are: (i) faulty sensor node identification in a small number of deployed body sensors (accelerometers); and (ii) identification of a faulty sensor node using a statically or dynamically bound group of sensor nodes that is sharing similar sensor signal patterns.     

Multi-Objective Optimization Model for QoS-Enabled Web Service Selection in Service-Based Systems

Nowadays, the web service has become the emerging communication technology where the interaction of each user is performed through the World Wide Web. However, the performance of the web service mechanism is degraded due to security flaws that occur throughout the Internet.. The user or service requester may not attain the relevant web service for their requirement. To overcome this problem, the newly developed multi-objective based Cuckoo Search (MCS) algorithm is proposed in this article. Initially, the input query model was built by the query keyword that is provided by the service requester. Then, the given query is matched with the database that hosts the web services that relates to input query. Among the various services, the user has to select the appropriate web service using the proposed algorithm. The MCS algorithm is newly designed by combining the Cuckoo Search algorithm and the QoS parameter based multiple objectives. Additionally, the new mathematical model of fitness is evaluated by the multi-objective parameters. Finally, the proposed algorithm exploits the fitness value to select the relevant web service for the user query. The experimental results are validated and performance is analyzed by the parameters of precision, recall, and F-measure. Thus, 86.6% of precision value was obtained by the proposed method, which ensured provision of the appropriate web service.     

Synthesis of Nanocrystalline Lanthanum Strontium Manganite Powder by the Urea–Formaldehyde Polymer Gel Combustion Route

Nanocrystalline lanthanum strontium manganite (LSM) powder has been synthesized by combustion of a transparent gel obtained by the polymerization of methylol urea and urea in a solution containing La³⁺, Sr²⁺, and Mn²⁺ (LSM ions). Chemistry of the transparent urea–formaldehyde (UF) polymer gel formation and structure of the gel have been proposed such that the LSM ions act in between the growing UF polymer chains by interacting through NH, OH, and CO groups by co-ordination and prevent polymer self-assembly through inter-chain hydrogen bonding as evidenced from infrared spectrum. Thermally stable structures formed by the decomposition of UF polymer below 300°C undergo combustion in the presence of nitrate oxidant in a temperature range from 350°–450°C. A perovskite LSM phase has been formed by self-sustained combustion of the dried gel initiated with little kerosene. The powder obtained after deagglomeration and calcination at 600°C for 2 h has a D ₅₀ value of 0.19 μm, and the particles are aggregates of crystallites 10–25 nm in size.     

Hybridization of stochastic reduced basis methods with polynomial chaos expansions

We propose a hybrid formulation combining stochastic reduced basis methods with polynomial chaos expansions for solving linear random algebraic equations arising from discretization of stochastic partial differential equations. Our objective is to generalize stochastic reduced basis projection schemes to non-Gaussian uncertainty models and simplify the implementation of higher-order approximations. We employ basis vectors spanning the preconditioned stochastic Krylov subspace to represent the solution process. In the present formulation, the polynomial chaos decomposition technique is used to represent the stochastic basis vectors in terms of multidimensional Hermite polynomials. The Galerkin projection scheme is then employed to compute the undetermined coefficients in the reduced basis approximation. We present numerical studies on a linear structural problem where the Youngs modulus is represented using Gaussian as well as lognormal models to illustrate the performance of the hybrid stochastic reduced basis projection scheme. Comparison studies with the spectral stochastic finite element method suggest that the proposed hybrid formulation gives results of comparable accuracy at a lower computational cost.     

The Role of the Prefrontal Cortex in the Maintenance of Verbal Working Memory: An Event-Related fMRI Analysis.

Neuroimaging studies have been inconclusive in characterizing the role of the prefrontal cortex (PFC) for maintaining increasingly larger amounts of information in working memory (WM). To address this question, the authors collected event-related functional MRI data while participants performed an item-recognition task in which the number of to-be-remembered letters was parametrically modulated. During maintenance of information in WM, the dorsolateral and the ventrolateral PFC exhibited linearly increasing activation in response to increasing WM load. Prefrontal regions could not be distinguished from one another on the basis of load sensitivity, but the dorsolateral PFC had stronger functional connectivity with the parietal and motor cortex than the ventrolateral PFC. These results suggest an increasingly important role for the PFC in actively maintaining information as the amount of that information increases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)