Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

On the capacity of the state‐dependent interference relay channel

This paper considers the state‐dependent interference relay channel (SIRC) in which one of the two users may operate as a secondary user and the relay has a noncausal access to the signals from both users. For discrete memoryless SIRC, we first establish the achievable rate region by carefully merging Han‐Kobayashi rate splitting encoding technique, superposition encoding, and Gelfand‐Pinsker encoding technique. Then, based on the achievable rate region that we derive, the capacity of the SIRC is established in many different scenarios including (a) the weak interference regime, (b) the strong interference regime, and (c) the very strong interference regime. This means that our capacity results contain all available known results in the literature. Next, the achievable rate region and the associated capacity results are also evaluated in the case of additive Gaussian noise. Additionally, many numerical examples are investigated to show the value of our theoretical derivations.     

Effect of ZnO layer thickness upon optoelectrical properties of NiO/ ZnO heterojunction prepared at room temperature

In this work, p-NiO/n-ZnO heterostructures were successfully prepared at room temperature using RF sputtering technique. The influence of ZnO layer thickness on the performance of the heterojunction was investigated. The deposited ZnO layers have a hexagonal Wurtzite structure with preferable growth orientations along (002) and (103) for thinner films. Increasing the thickness results in more crystallographic orientation randomness. The current–voltage measurements of the realized heterojunctions showed a clear rectifying behavior. The measured ideality factor varies from 2.5 to 1.6 according to the thickness of ZnO layer. The series resistance of the device is enlarged with increasing ZnO thickness. The deduced parameters from the I–V characteristics suggest that 200 nm is the optimal thickness of the ZnO layer according to our experimental conditions. We attribute the relatively better performance of this thickness to achieving reasonable compensation between serial resistance and ideality factor. The best heterojunction was tested and successfully used as a UV detector.     

Object segmentation and labeling by learning from examples

We propose a system that employs low-level image segmentation followed by color and two-dimensional (2-D) shape matching to automatically group those low-level segments into objects based on their similarity to a set of example object templates presented by the user. A hierarchical content tree data structure is used for each database image to store matching combinations of low-level regions as objects. The system automatically initializes the content tree with only "elementary nodes" representing homogeneous low-level regions. The "learning" phase refers to labeling of combinations of low-level regions that have resulted in successful color and/or 2-D shape matches with the example template(s). These combinations are labeled as "object nodes" in the hierarchical content tree. Once learning is performed, the speed of second-time retrieval of learned objects in the database increases significantly. The learning step can be performed off-line provided that example objects are given in the form of user interest profiles. Experimental results are presented to demonstrate the effectiveness of the proposed system with hierarchical content tree representation and learning by color and 2-D shape matching on collections of car and face images.     

Effect of postoperative mydriatics on the iris

PURPOSE: To assess the role postoperative mydriatics play after extracapsular cataract extraction (ECCE) and posterior chamber intraocular lens (IOL) implantation in causing iris modifications and in controlling inflammation. SETTING: Outpatients Department, Ninewells Hospital, Dundee, Scotland. METHODS: The prospective study comprised 136 patients who had standardized ECCE. Half the patients used a mydriatic for 2 weeks postoperatively. Anterior chamber activity, pain, and eye redness were evaluated at 2 weeks postoperatively; pupil shape, peripheral anterior synechias, IOL position, and iris adhesions, at 6 weeks. RESULTS: Iris-lens adhesions were significantly more common in the group using a mydriatic. There was no difference between the two groups in postoperative inflammation. CONCLUSION: Mydriatics should not be used routinely after ECCE with posterior chamber IOL implantation.     

Stereoselectivity in cutaneous hydrolysis and transdermal transport of propranolol prodrug

This review is written to evaluate the stereoselectivity in cutaneous hydrolysis and transdermal transport of propranolol prodrug. This discussion will be useful in the development of knowledge about stereoselective cutaneous hydrolysis and its influence on stereoselective transdermal transport of many other chiral prodrugs and drugs. Propranolol prodrugs undergo stereoselective hydrolysis in hairless mouse skin homogenate and in excised skin samples during permeation; the stereoselectivity is markedly biased towards hydrolysis of the (R) isomer. Unlike the liver, the esterase activity of the skin is high in its cytosolic fraction. Most of the lipophilic propranolol prodrugs cause stereoselective permeation across hairless mouse skin. A mechanism of stereoselective permeation of propranolol prodrug across the skin has been proposed, which indicates that the stereoselectivity in permeation is resulted from the stereoselective hydrolysis of lipophilic prodrug during permeation.