Decentralized adaptive recurrent neural control structure

This paper presents a novel decentralized variable structure neural control approach for large-scale uncertain systems, which is developed using recurrent high-order neural networks (RHONN). It is assumed that each subsystem belongs to a class of block-controllable nonlinear systems whose vector fields includes interconnection terms, which are bounded by nonlinear functions. A decentralized RHONN structure and the respective learning law are proposed in order to approximate online the dynamical behavior of each nonlinear subsystem. The control law, which is able to regulate and to track the desired reference signals, is designed using the well-known variable structure theory. The stability of the whole system is analyzed via the Lyapunov methodology. The applicability of the proposed decentralized identification and control algorithm is illustrated via simulations as applied to an interconnected double inverted pendulum.     

Investigation of temperature-dependent polarization, dielectric, and magnetization behavior of multiferroic layered nanostructure

The PbZr_0.53Ti_0.47O₃(PZT)/CoFe₂O₄(CFO) layered nanostructures show lowering of dielectric constant and polarization, and an enhanced magnetization with a decrease in temperature from 400 K to 100 K. The temperature dependence of the real part of the dielectric constant illustrates a step-like behavior, whereas the imaginary part gives a relaxation peak near the step maxima temperature. A slow decrease in the polarization was observed from 300 K to 200 K, with an eventual collapse of polarization at ~ 100 K, and a complete polarization recovery with heating, these phenomena is reproducible over cycles of experiment. Remanent magnetization of the layered nanostructure was found to be three times higher at 100 K than that at room temperature. There is a slow enhancement in remanent (internal) magnetization with lowering of temperature, resulting in slow polarization switch and finally the collapse. The temperature-dependent dielectric, polarization and magnetization were different from the parent layer, indicating a kind of dynamic magneto-electric coupling in the layered nanostructures.     

Dielectric relaxation phenomena in the compound: LiCo<Subscript>3/5</Subscript>Mn<Subscript>1/5</Subscript>Cu<Subscript>1/5</Subscript>VO<Subscript>4</Subscript>

Solution-based chemical method has been used to produce LiCo_3/5Mn_1/5Cu_1/5VO₄ ceramics. The formation of the compound is checked by X-ray diffraction analysis and it reveals an orthorhombic unit cell structure with lattice parameters of a = 9.8262 Å, b = 3.0706 Å, c = 14.0789 Å. Field emission scanning electron micrograph indicates a polycrystalline texture of the material with grains of unequal sizes (~0.2 to 3 μm). Complex impedance spectroscopy technique is used to study the dielectric properties. Temperature dependence of dielectric constant (ε _r) at various frequencies exhibits the dielectric anomalies in ε _r at T _c (transition temperature) = 245, 255, 260 and 265 °C with (ε_r)_max. ~458, 311, 214 and 139 for 50, 100, 200 and 500 kHz, respectively. Frequency dependence of tangent loss at various temperatures shows the presence of dielectric relaxation in the material.     

Analysis of normal and epileptic seizure EEG signals using empirical mode decomposition

Epilepsy is one of the most common neurological disorders characterized by transient and unexpected electrical disturbance of the brain. The electroencephalogram (EEG) is an invaluable measurement for the purpose of assessing brain activities, containing information relating to the different physiological states of the brain. It is a very effective tool for understanding the complex dynamical behavior of the brain. This paper presents the application of empirical mode decomposition (EMD) for analysis of EEG signals. The EMD decomposes a EEG signal into a finite set of bandlimited signals termed intrinsic mode functions (IMFs). The Hilbert transformation of IMFs provides analytic signal representation of IMFs. The area measured from the trace of the analytic IMFs, which have circular form in the complex plane, has been used as a feature in order to discriminate normal EEG signals from the epileptic seizure EEG signals. It has been shown that the area measure of the IMFs has given good discrimination performance. Simulation results illustrate the effectiveness of the proposed method.     

A Time-Domain Digital-Intensive Built-In Tester for Analog Circuits

To solve test challenges in nanometer CMOS technologies, a time-domain digital-intensive built-in tester for analog circuits is proposed. The compact tester allows characterizations of AC response and DC gain for various analog circuits which have a low-pass frequency characteristic. By applying ramp signals to stimulate the circuit under test and measuring slopes and time delays of its responses, the testing can be simple and robust over process-voltage-temperature variations. Also, it is well suited for nanometer technologies because of its digital-intensive implementation. The tester was fabricated in 65 nm standard CMOS process and occupies 0.026 mm².     

Component-based technique for determining the effects of acupuncture for fighting migraine using SPECT images

In this work, SPECT brain images are analyzed automatically in order to determine the effects of acupuncture applied for fighting migraine. For this purpose, two different groups of patients are randomly collected and received verum and sham acupuncture, respectively. Changes in the brain perfusion patterns can be measured quantitatively by dealing with the images in a classification context. A classification scheme consisting of a component-based feature extraction technique in combination with Support Vector Machines allows us to accurately determine the regions of interest (ROIs) where acupuncture produced more intense effects, and whether these effects are correlated with a decrease or an increase of the brain activity. Effects produced by verum and sham acupuncture are studied, and the best method for intensity normalization is discussed. The result is a complete, objective system which can be used for general purposes in the visual assessment of perfusion images.     

Binary ant colony optimization applied to variable screening in the Mahalanobis–Taguchi System

This work presents the application of the Mahalanobis–Taguchi System (MTS) to a dimensional problem in the automotive industry. The combinatorial optimization problem of variable selection is solved by the application of a recent version of binary ant colony optimization algorithm. Moreover, a comparison with respect to binary particle swarm optimization algorithm is also presented and a discussion regarding the numerical results is given.     

A multidimensional data model using the fuzzy model based on the semantic translation

With the rapid development of Web 2.0 sites such as Blogs and Wikis users are encouraged to express opinions about certain products, services or social topics over the web. There is a method for aggregating these opinions, called Opinion Aggregation, which is made up of four steps: Collect, Identify, Classify and Aggregate. In this paper, we present a new conceptual multidimensional data model based on the Fuzzy Model based on the Semantic Translation to solve the Aggregate step of an Opinion Aggregation architecture, which allows exploiting the measure values resulting from integrating heterogeneous information (including unstructured data such as free texts) by means of traditional Business Intelligence tools. We also present an entire Opinion Aggregation architecture that includes the Aggregate step and solves the rest of steps (Collect, Identify and Classify) by means an Extraction, Transformation and Loading process. This architecture has been implemented in an Oracle Relational Database Management System. We have applied it to integrate heterogeneous data extracted from certain high end hotels websites, and we show a case study using the collected data during several years in the websites of high end hotels located in Granada (Spain). With this integrated information, the Data Warehouse user can make several analyses with the benefit of an easy linguistic interpretability and a high precision by means of interactive tools such as the dashboards.