Signal bandwidth consideration of mutual coupling effects on adaptive array performance

The effect of mutual coupling on the performance of a least mean square (LMS) adaptive array using dipole elements is analyzed in consideration of the signal bandwidth. The purpose here is to illustrate quantitatively the significance of the effect of mutual coupling. The results show that the effect in the broad-band signal cases is much greater than that in the narrow-band cases, particularly when few antenna elements are used.     

Eosinophilic cationic protein in chronic eosinophilic pneumonia and eosinophilic granuloma

We measured eosinophilic cationic protein (ECP) concentrations in the circulation and bronchoalveolar lavage (BAL) fluids from patients with chronic eosinophilic pneumonia, patients with eosinophilic granuloma, and normal control subjects. Significantly increased ECP concentrations were found in the circulation of patients with chronic eosinophilic pneumonia and with eosinophilic granuloma compared with those found in control subjects. The ECP concentrations were well correlated to eosinophil counts in the circulation of patients with chronic eosinophilic pneumonia, while they were not in patients with eosinophilic granuloma. Chronic eosinophilic pneumonia patients had prominently increased ECP concentrations in BAL fluids compared with those found in control subjects, while eosinophilic granuloma patients did not. Those concentrations in chronic eosinophilic pneumonia patients were well correlated to eosinophil counts in the BAL fluid. Corticosteroid therapy remarkably decreased circulating ECP concentrations in three patients with chronic eosinophilic pneumonia, but it had no significant effects in two patients with eosinophilic granuloma. Measurement of ECP concentrations seems to be useful to evaluate the disease activity of chronic eosinophilic pneumonia.     

Regulation of miRNA Expression by Low-Level Laser Therapy (LLLT) and Photodynamic Therapy (PDT)

Applications of laser therapy, including low-level laser therapy (LLLT), phototherapy and photodynamic therapy (PDT), have been proven to be beneficial and relatively less invasive therapeutic modalities for numerous diseases and disease conditions. Using specific types of laser irradiation, specific cellular activities can be induced. Because multiple cellular signaling cascades are simultaneously activated in cells exposed to lasers, understanding the molecular responses within cells will aid in the development of laser therapies. In order to understand in detail the molecular mechanisms of LLLT and PDT-related responses, it will be useful to characterize the specific expression of miRNAs and proteins. Such analyses will provide an important source for new applications of laser therapy, as well as for the development of individualized treatments. Although several miRNAs should be up- or down-regulated upon stimulation by LLLT, phototherapy and PDT, very few published studies address the effect of laser therapy on miRNA expression. In this review, we focus on LLLT, phototherapy and PDT as representative laser therapies and discuss the effects of these therapies on miRNA expression.     

A new control method of nonlinear systems based on impulseresponses of universal learning networks

A new control method of nonlinear dynamic systems is proposed based on the impulse responses of universal learning networks (ULNs), ULNs form a superset of neural networks. They consist of a number of interconnected nodes where the nodes may have any continuously differentiable nonlinear functions in them and each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm is derived for the ULNs, in which both the first order derivatives (gradients) and the higher order derivatives are incorporated. One of the distinguished features of the proposed control method is that the impulse response of the systems is considered as an extended part of the criterion function and it can be calculated by using the higher order derivatives of ULNs. By using the impulse response as the criterion function, nonlinear dynamics with not only quick response but also quick damping and small steady state error can be more easily obtained than the conventional nonlinear control systems with quadratic form criterion functions of state and control variables.     

Chaos control on universal learning networks

A new chaos control method is proposed which is useful for taking advantage of chaos and avoiding it. The proposed method is based on the following facts: (1) chaotic phenomena can be generated and eliminated by controlling the maximum Lyapunov exponent of the systems, and (2) the maximum Lyapunov exponent can be formulated and calculated by using higher-order derivatives of universal learning networks (ULNs). ULNs consist of a number of interconnected nodes which may have any continuously differentiable nonlinear functions in them and where each pair of nodes can be connected by multiple branches with arbitrary time delays. A generalized learning algorithm has been derived for the ULNs in which both first-order derivatives (gradients) and higher-order derivatives are incorporated. In simulations, parameters of ULNs with bounded node outputs were adjusted for the maximum Lyapunov exponent to approach the target value, and it has been shown that a fully-connected ULN with three sigmoidal function nodes is able to generate and eliminate chaotic behaviors by adjusting these parameters     

Network Intrusion Detection Using Class Association Rule Mining Based on Genetic Network Programming

Because of the expansion of the Internet in recent years, computer systems are exposed to an increasing number and type of security threats. How to detect network intrusions effectively becomes an important technique. This paper proposes a class association rule mining approach based on genetic network programming (GNP) for detecting network intrusions. This approach can deal with both discrete and continuous attributes in network‐related data. And it can be flexibly applied to both misuse detection and anomaly detection. Experimental results with KDD99Cup and DARPA98 database from MIT Lincoln Laboratory shows that the proposed method provides a competitive high detection rate (DR) compared to other machine learning techniques. © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Stock price prediction using neural networks with RasID-GA

In general, neural networks are widely used in pattern recognition, system modeling and prediction, and can model complex nonlinear systems. In the previous work, we proposed a novel training algorithm, Adaptive Random Search with Intensification and Diversification combined with Genetic Algorithm (RasID-GA), for training the multibranch recurrent neural networks recently developed. In this paper, RasID-GA has been applied to predict stock market prices using the multibranch feed forward neural networks. We predicted the next day's closing stock price with several past closing stock prices. We used the stock prices of 20 brands for 720 days in order to evaluate the generalization ability of the proposed method. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Preparation of (001)-oriented Pb(Zr,Ti)O/sub 3/ thin films and their piezoelectric applications

Preparation of (001)-oriented Pb(Zr,Ti)O₃ (PZT) thin films and their applications to a sensor and actuators were investigated. These thin films, which have a composition close to the morphotropic phase boundary, were epitaxially grown on (100)MgO single-crystal substrates by RF magnetron sputtering. These (001)-oriented PZT thin films could be obtained on various kinds of substrates, such as glass and Si, by introducing (100)-oriented MgO buffer layers. In addition, the (001)-oriented PZT thin films could be obtained on Si substrates without buffer layers by optimizing the sputtering conditions. All of these thin films showed excellent piezoelectric properties without the need for poling treatment. The PZT thin films on the MgO substrates had a high piezoelectric coefficient, d₃₁, of -100 pm/V, and an extremely low relative dielectric constant, epsiv_r, of 240. The PZT thin films on Si substrate had a very high d₃₁ of -150 pm/V and an epsiv_r = 700. These PZT thin films were applied to an angular rate sensor with a tuning fork in a car navigation system, to a dual-stage actuator for positioning the magnetic head of a high-density hard disk drive, and to an actuator for an inkjet printer head for industrial on-demand printers.