Design of a multiple-beam forming network using CORPS optimized for cellular systems

The design of beam-forming networks (BFNs) for a multibeam-steerable antenna array using Coherently Radiating Periodic Structures (CORPS) in cellular mobile communication systems is presented. In this paper, the CORPS technology is introduced and applied to the design of beam-forming networks in cellular systems for the first time. The CORPS-BFNs proposed show improved performance over the common way to feed antenna arrays used in mobile systems. In this design, the input ports of the feeding network design are optimized using the particle swarm optimization (PSO) algorithm. Two 2-beam design configurations of CORPS-BFN for a multibeam-steerable linear array on a cellular scenario are proposed and analyzed. Simulation results show the benefits of BFNs based on CORPS on a cellular mobile scenario based on the array factor response, in terms of side lobe level (SLL) and signal-to-interference (SIR) improvement capability. Furthermore, results for average SIR improvement, signal to interference plus noise power ratio (SINR) and BER are discussed.     

Influence of flow pattern on the parameter estimates of a simplebreathing mechanics model

The first-order model of breathing mechanics is widely used in clinical practice to assess the viscoelastic properties of the respiratory system. Although simple, this model takes the predominant features of the pressure-flow relationship into account but gives highly systematic residuals between measured and model-predicted variables. To achieve a better fit of the entire data set, an approach hypothesizing deterministic time-variations of model parameters, summarized by information-weighted histograms was recently proposed by Bates and Lauzon (1992). The present study uses flow and pressure data measured in intensive care patients to evaluate the real potential of this approach in clinical practice. Information-weighted histograms of the model parameters, estimated by an on-line identification algorithm, were first constructed by taking into account the parameter percentage standard deviations. Then, the influence of the respiratory flow pattern on the calculated histograms was evaluated by the Kolmogorov-Smirnov statistical test. The results show that the method gives good reproducibility under stable experimental conditions. In addition, for a given airflow waveform; an increase in respiratory frequency shifts the histograms representing time-varying viscous properties strongly versus lower values, whereas it shifts the histograms representing time-varying elastic properties slightly versus higher values. On the other hand, the same histograms were highly dependent on the airflow waveform, especially for the viscous properties. Even in a limited experimental work, in all the conditions considered, the method provides results which agree well with the physiological knowledge of nonlinear and multicompartment behavior of respiratory mechanics     

Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

Fast and accurate tissue elasticity imaging is essential in studying dynamic tissue mechanical properties. Various ultrasound shear elasticity imaging techniques have been developed in the last two decades. However, to reconstruct a full field-of-view 2-D shear elasticity map, multiple data acquisitions are typically required. In this paper, a novel shear elasticity imaging technique, comb-push ultrasound shear elastography (CUSE), is introduced in which only one rapid data acquisition (less than 35 ms) is needed to reconstruct a full field-of-view 2-D shear wave speed map (40 × 38 mm). Multiple unfocused ultrasound beams arranged in a comb pattern (comb-push) are used to generate shear waves. A directional filter is then applied upon the shear wave field to extract the left-to-right (LR) and right-to-left (RL) propagating shear waves. Local shear wave speed is recovered using a time-of-flight method based on both LR and RL waves. Finally, a 2-D shear wave speed map is reconstructed by combining the LR and RL speed maps. Smooth and accurate shear wave speed maps are reconstructed using the proposed CUSE method in two calibrated homogeneous phantoms with different moduli. Inclusion phantom experiments demonstrate that CUSE is capable of providing good contrast (contrast-to-noise ratio ≥ 25 dB) between the inclusion and background without artifacts and is insensitive to inclusion positions. Safety measurements demonstrate that all regulated parameters of the ultrasound output level used in CUSE sequence are well below the FDA limits for diagnostic ultrasound.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Transmission Fiber Chromatic Dispersion Dependence on Temperature: Implications on 40 Gb/s Performance

In this letter, we will evaluate the performance degradation of a 40 km high‐speed (40 Gb/s) optical system, induced by optical fiber variations of the chromatic dispersion induced by temperature changes. The chromatic dispersion temperature sensitivity will be estimated based on the signal quality parameters.     

Towards a Sustainable Green Design for Next-Generation Networks

Recently distributed real-time database systems are intended to manage large volumes of dispersed data. To develop distributed real-time data processing, a reality and stay competitive well defined protocols and algorithms must be required to access and manipulate the data. An admission control policy is a major task to access real-time data which has become a challenging task due to random arrival of user requests and transaction timing constraints. This paper proposes an optimal admission control policy based on deep reinforcement algorithm and memetic algorithm which can efficiently handle the load balancing problem without affecting the Quality of Service (QoS) parameters. A Markov decision process (MDP) is formulated for admission control problem, which provides an optimized solution for dynamic resource sharing. The possible solutions for MDP problem are obtained by using reinforcement learning and linear programming with an average reward. The deep reinforcement learning algorithm reformulates the arrived requests from different users and admits only the needed request, which improves the number of sessions of the system. Then we frame the load balancing problem as a dynamic and stochastic assignment problem and obtain optimal control policies using memetic algorithm. Therefore proposed admission control problem is changed to memetic logic in such a way that session corresponds to individual elements of the initial chromosome. The performance of proposed optimal admission control policy is compared with other approaches through simulation and it depicts that the proposed system outperforms the other techniques in terms of throughput, execution time and miss ratio which leads to better QoS.

     

A Dynamic Harmonic Regression Approach to Power System Modal Identification and Prediction

Abstract—Time series models provide a powerful tool to extract nonstationary features from measured data. In this article, a statistical framework based upon a dynamic harmonic regression model for examining modal behavior is provided. In this model, temporal patterns in measured data are modeled within a stochastic state space setting. Estimates of the states or time-varying parameters are then obtained using an optimal estimation method based on the Kalman filter. Techniques to estimate future values of the unobserved signal are also analyzed. The widely applicable technique is illustrated on both simulated and measured data. Factors that affect the performance of the method are discussed, including the effects of non-linear trends, data quality, and sampling design. Connections with other modal identification methods are also investigated.     

Property specification patterns at work: verification and inconsistency explanation

Innovations in Systems and Software Engineering - Property specification patterns (PSPs) have been proposed to ease the formalization of requirements, yet enable automated verification thereof. In...     

Periodic Copula Autoregressive Model Designed to Multivariate Streamflow Time Series Modelling

Water Resources Management - It is a challenge to develop models that can represent the stochastic behaviour of rivers and basins. Currently used streamflow models were constructed under rigid...     

The direct catalytic asymmetric mannich reaction

The direct catalytic asymmetric addition of unmodified carbonyl compounds to preformed or in situ-generated imines has emerged as a promising new route to optically enriched alpha- and beta-amino acid derivatives, beta-lactams, and 1,2- and gamma-amino alcohols. The direct catalytic asymmetric Mannich reactions are mediated by small organometallic and organic amine catalysts that can achieve levels of selectivity similar to those possible with natural enzymes. The different small-molecule catalysts described here are complementary in their applications. They also complement each other in syn or anti selectivity of the direct asymmetric Mannich reaction. In this Account, we highlight the recent developments in and contributions to this research.