Models of Restoration Probability in WDM Networks Employing Active Restoration

The ever-increasing demand for network bandwidth makes network survivability an issue of great concern. Lightpath restoration is a valuable approach to guaranteeing an acceptable level of survivability in WDM optical networks with better resource utilization than that of its protection counterpart. Active restoration (AR) is a newly proposed lightpath restoration scheme [M. Mostafa et al. OSA Journal of Optical Networking, vol. 3, no. 4, pp. 247–260] that combines the best of protection and reactive restoration while avoiding their shortcomings. In this paper, we conduct detailed performance analysis on the restoration probability of AR-based WDM networks. In particular, analytical models of restoration probability are developed respectively for networks with full-wavelength conversion capability and for networks without wavelength conversion capability under different backup path searching schemes. Based on the new models, we investigate the effects of wavelength availability, wavelength conversion capability, path length as well as backup path seeking methods on the restoration probability.     

A Combined Antenna Array and Multi-User Detection DS-CDMA Receiver in Single-Path and Multi-Path Fading Channels

An adaptive antenna array is incorporated into a decorrelatingmulti-user detector to effectively increase the DS-CDMA system capacity.Capacity improvement is due to beamforming gain, spatial diversity gain(assuming large angle spread), and the decorrelating effect. Thereceiver has been analyzed for the cases of sufficiently andinsufficiently spaced receiving antennas. The receiver consists of afront-end beamformer for every user in the cell and has knowledge of allusers' signature sequences. The beamformer estimates the desired userchannel vector, enhancing its signal and reducing the co-channelinterference from other directions. The multi-user detection, exploitingknowledge of other users, rejects those interferers whose arrival anglesare close to that of the desired user. The average uncoded Bit ErrorRate (BER) as a function of the number of in-beam active users, theaverage antenna Signal-to-Noise Ratio (SNR), and the number of receivingantennas is examined in both single-path and multi-path Rayleigh fadingchannels. Analysis shows an increase in system capacity proportional tothe number of receiving antennas.     

Study of features based on nonlinear dynamical modeling in ECG arrhythmia detection and classification

We present a study of the nonlinear dynamics of electrocardiogram (ECG) signals for arrhythmia characterization. The correlation dimension and largest Lyapunov exponent are used to model the chaotic nature of five different classes of ECG signals. The model parameters are evaluated for a large number of real ECG signals within each class and the results are reported. The presented algorithms allow automatic calculation of the features. The statistical analysis of the calculated features indicates that they differ significantly between normal heart rhythm and the different arrhythmia types and, hence, can be rather useful in ECG arrhythmia detection. On the other hand, the results indicate that the discrimination between different arrhythmia types is difficult using such features. The results of this work are supported by statistical analysis that provides a clear outline for the potential uses and limitations of these features.     

Détermination des perturbations induites aux extrémités d’une ligne blindée soumise à une excitation ponctuelle de courant

This article allows the determination of the induced perturbations at the ends of the coaxial line in wide frequency band enough. The perturbation source is a current direct point injection into the cable screen in any position. For this, we have applied the theory of the state variables, with foundation of the quasi-TEM approximation, in order to simulate the coaxial line above a ground level that has a finished conductivity. This allows us to supply the current and voltage expressions at the ends of the line as their analytic forms for any conditions of charge. Next, the elaborate objective is to verify experimentally on concrete applications if the test obtained results confirm the theoretical expectations supplied by calculation code finalizing.     

Cooperative Q‐learning techniques for distributed online power allocation in femtocell networks

In this paper, we address the problem of distributed interference management of femtocells that share the same frequency band with macrocells using distributed multi‐agent Q‐learning. We formulate and solve two problems representing two different Q‐learning algorithms, namely, femto‐based distributed and sub‐carrier‐based distributed power controls using Q‐learning (FBDPC‐Q and SBDPC‐Q). FBDPC‐Q is a multi‐agent algorithm that works on a global basis, for example, deals with the aggregate macrocell and femtocell capacities. Its complexity increases exponentially with the number of sub‐carriers in the system. Also, it does not take into consideration the sub‐carrier macrocell capacity as a constraint. To overcome these problems, SBDPC‐Q is proposed, which is a multi‐agent algorithm that works on a sub‐carrier basis, for example, sub‐carrier macrocell and femtocell capacities. Each of FBDPC‐Q and SBDPC‐Q works in three different learning paradigms: independent (IL), cooperative (CL), and weighted cooperative (WCL). IL is considered the simplest form for applying Q‐learning in multi‐agent scenarios, where all the femtocells learn independently. CL and WCL are the proposed schemes in which femtocells share partial information during the learning process in order to strike a balance between practical relevance and performance. We prove the convergence of the CL paradigm when used in the FBDPC‐Q algorithm. We show via simulations that the CL paradigm outperforms the IL paradigm in terms of the aggregate femtocell capacity, especially in networks with large number of femtocells and large number of power levels. In addition, we propose WCL to address the CL limitations. Finally, we evaluate the robustness and scalability of both FBDPC‐Q and SBDPC‐Q, against several typical dynamics of plausible wireless scenarios (fading, path loss, random activity of femtocells, etc.). We show that the CL paradigm is the most scalable to large number of femtocells and robust to the network dynamics compared with the IL and WCL paradigms. Copyright © 2014 John Wiley & Sons, Ltd.     

Resistivity dependence of minority carrier lifetime and cell performance in p-type dendritic web silicon ribbon

This study shows that the bulk lifetime in 95 μm thick p-type dendritic web silicon solar cells is a strong function of bulk resistivity. The higher the resistivity, the greater the bulk lifetime. This behavior is explained on the basis of dopant–defect interaction, which increases the lifetime limiting trap concentration with the addition of dopant atoms. Model calculations show that in the absence of doping dependence of bulk lifetime (τ), 2 Ω cm web should give the best cell efficiency for bulk lifetimes below 30 μs. However, strong doping dependence of bulk lifetime in p-web cells shifts the optimum resistivity from 2 to 15 Ω cm. Bulk lifetime in the as-grown web material was found to be less than 1 μs for all the resistivities. After the cell processing which involves phosphorus gettering, aluminum gettering, and SiN induced hydrogen passivation of defects, the bulk lifetime increased to 6.68, 11, 31 and 68.9 μs in 0.62, 1.37, 6.45 and 15 Ω cm p-type web material, respectively. Therefore, cell process induced recovery of lifetime in web is doping dependent, which favors high resistivity. Solar cells fabricated on 95 μm thick web silicon by a manufacturable process involving screen-printing and belt-line processing gave 14.5% efficient 4 cm² cells on 15 Ω cm resistivity. This represents a record efficiency for such a thin manufacturable screen-printed cell on a low-cost PV grade Si ribbon that requires no wafering or etching.     

A framework for predictive modeling of anatomical deformations

A framework for modeling and predicting anatomical deformations is presented, and tested on simulated images. Although a variety of deformations can be modeled in this framework, emphasis is placed on surgical planning, and particularly on modeling and predicting changes of anatomy between preoperative and intraoperative positions, as well as on deformations induced by tumor growth. Two methods are examined. The first is purely shape-based and utilizes the principal modes of co-variation between anatomy and deformation in order to statistically represent deformability. When a patient's anatomy is available, it is used in conjunction with the statistical model to predict the way in which the anatomy will/can deform. The second method is related, and it uses the statistical model in conjunction with a biomechanical model of anatomical deformation. It examines the principal modes of co-variation between shape and forces, with the latter driving the biomechanical model, and thus predicting deformation. Results are shown on simulated images, demonstrating that systematic deformations, such as those resulting from change in position or from tumor growth, can be estimated very well using these models. Estimation accuracy will depend on the application, and particularly on how systematic a deformation of interest is.     

Face Recognition Through Different Facial Expressions

Face recognition has become an accessible issue for experts as well as ordinary people as it is a focal non-interfering biometric modality. In this paper, we introduced a new approach to perform face recognition under varying facial expressions. The proposed approach consists of two main steps: facial expression recognition and face recognition. They are two complementary steps to improve face recognition across facial expression variation. In the first step, we selected the most expressive regions responsible for facial expression appearance using the Mutual Information technique. Such a process helps not only improve the facial expression classification accuracy but also reduce the features vector size. In the second step, we used the Principal Component Analysis (PCA) to build EigenFaces for each facial expression class. Then, a face recognition is performed by projecting the face onto the corresponding facial expression Eigenfaces. The PCA technique significantly reduces the dimensionality of the original space since the face recognition is carried out in the reduced Eigenfaces space. An experimental study was conducted to evaluate the performance of the proposed approach in terms of face recognition accuracy and spatial-temporal complexity.

     

啤酒酵母和乳酸菌发酵棕榈粕渣饲料制备工艺的响应面优化

通过单因素实验和响应面法对啤酒酵母和乳酸菌发酵棕榈粕渣饲料制备工艺进行研究。结果表明:基料制备最佳发酵条件为发酵时间5 d、棕榈仁渣目数70目、菌料比1∶103、发酵温度30℃、含水量36%,该条件下基料中总菌落数为7.20×10~(10)个/g;发酵产物最佳发酵条件为发酵温度30℃、棕榈果渣与空果串配比1∶2、棕榈果渣及空果粉碎长度4 cm、配料比1∶10(基料与棕榈果渣和空果串质量比)、含水量35%、发酵时间36 d,该条件下发酵产物营养成分OD值为0.966。对发酵饲料主要成分进行分析,其粗蛋白、粗脂肪、粗纤维、粗灰分、钙、磷、含水量分别为7.20%、7.61%、26.20%、5.20%、0.38%、0.26%、16.20%,总菌落数为9.0×10~7个/g。该发酵方法工艺简单,具有良好的工业化生产前景。