Intelligent wavelet fuzzy brain emotional controller using dual function-link network for uncertain nonlinear control systems

This study aims to propose a more efficient hybrid algorithm to achieve favorable control performance for uncertain nonlinear systems. The proposed algorithm comprises a dual function-link network-based multilayer wavelet fuzzy brain emotional controller and a sign(.) functional compensator. The proposed algorithm estimates the judgment and emotion of a brain that includes two fuzzy inference systems for the amygdala network and the prefrontal cortex network via using a dual-function-link network and three sub-structures. Three sub-structures are a dual-function-link network, an amygdala network, and a prefrontal cortex network. Particularly, the dual-function-link network is used to adjust the amygdala and orbitofrontal weights separately so that the proposed algorithm can efficiently reduce the tracking error, follow the reference signal well, and achieve good performance. A Lyapunov stability function is used to determine the adaptive laws, which are used to efficiently tune the system parameters online. Simulation and experimental studies for an antilock braking system and a magnetic levitation system are presented to verify the effectiveness and advantage of the proposed algorithm.

     

Monitoring the Ratio of Two Normal Variables Using EWMA Type Control Charts

In many fields, there is the need to monitor quality characteristics defined as the ratio of two random variables. The design and implementation of control charts directly monitoring the ratio stability is required for the continuous surveillance of these quality characteristics. In this paper, we propose two one‐sided exponentially weighted moving average (EWMA) charts with subgroups having sample size n > 1 to monitor the ratio of two normal random variables. The optimal EWMA smoothing constants, control limits, and ARLs have been computed for different values of the in‐control ratio and correlation between the variables and are shown in several figures and tables to discuss the statistical performance of the proposed one‐sided EWMA charts. Both deterministic and random shift sizes have been considered to test the two one‐sided EWMA charts' sensitivity. The obtained results show that the proposed one‐sided EWMA control charts are more sensitive to process shifts than other charts already proposed in the literature. The practical application of the proposed control schemes is discussed with an illustrative example. Copyright © 2015 John Wiley & Sons, Ltd.     

Mechanical property enhancement of aligned multi-walled carbon nanotube sheets and composites through press-drawing process

A solid-state drawing and winding process was done to create thin aligned carbon nanotube (CNT) sheets from CNT arrays. However, waviness and poor packing of CNTs in the sheets are two main weaknesses restricting their reinforcing efficiency in composites. This report proposes a simple press-drawing technique to reduce wavy CNTs and to enhance dense packing of CNTs in the sheets. Non-pressed and pressed CNT/epoxy composites were developed using prepreg processing with a vacuum-assisted system. Effects of pressing on the mechanical properties of the aligned CNT sheets and CNT/epoxy composites were examined. Pressing with distributed loads of 147, 221, and 294 N/m showed a substantial increase in the tensile strength and the elastic modulus of the aligned CNT sheets and their composites. The CNT sheets under a press load of 221 N/m exhibited the best mechanical properties found in this study. With a press load of 221 N/m, the pressed CNT sheet and its composite, respectively, enhanced the tensile strength by 139.1 and 141.9%, and the elastic modulus by 489 and 77.6% when compared with non-pressed ones. The pressed CNT/epoxy composites achieved high tensile strength (526.2 MPa) and elastic modulus (100.2 GPa). Results show that press-drawing is an important step to produce superior CNT sheets for development of high-performance CNT composites.     

Phonon Scattering in Thin Silica Films Below 1 K

A method is described for studying thermal phonon scattering in thin films on dielectric substrates below a few Kelvin. It is used to study silica films on silicon substrates. Using Monte Carlo simulations with no free parameters, we find that thermally grown silica films 0.1 to 1.0 m thick scatter the phonons as strongly as bulk silica, and hence, have the same thermal conductivity as bulk silica, while a 0.1 m thick e-beam evaporated silica film has a thermal conductivity five times smaller than bulk silica, indicative of additional defects.     

Integratable non-clogging microconcentrator based on counter-flow principle for continuous enrichment of CaSki cells sample

This study addresses the need to reduce the risk of clogging when preparing samples for cell concentration, i.e., the CaSki Cell-lines (epidermoid cervical carcinoma cells). Aiming to develop a non-clogging microconcentrator, we proposed a new counter-flow concentration unit characterized by the directions of penetrating flows being at an obtuse angle to the main flow, due to employment of streamlined turbine blade-like micropillars. Based on the optimization results of the counter-flow unit profile, a fractal arrangement for the counter-flow concentration unit was developed. A counter-flow microconcentrator chip was then designed and fabricated, with both the processing layer and collecting layer arranged in terms of the honeycomb structure. Visualized experiments using CaSki cell samples on the microconcentrator chip demonstrated that no cell-clogging phenomena occurred during the test and that no cells were found in the final filtrate. The test results show an excellent concentration performance for the microconcentrator chip, while a concentrating ratio of >4 with the flow rate being below 1.0 ml/min. As only geometrical structure is employed in the passive device, the counter-flow microconcentrator can be easily integrated into advanced microfluidic systems. Owing to the merit of non-clogging and continuous processing ability, the counter-flow microconcentrator is not only suitable for the sample preparation within biomedical field, but also applicable in water-particle separation.     

Combination of convex theories: Modularity,deduction completeness,and explanation

Decision procedures are key components of theorem provers and constraint satisfaction systems. Their modular combination is of prime interest for building efficient systems, but their effective use is often limited by poor interface capabilities, when such procedures only provide a simple “sat/unsat” answer. In this paper, we develop a framework to design cooperation schemas between such procedures while maintaining modularity of their interfaces. First, we use the framework to specify and prove the correctness of classic combination schemas by Nelson–Oppen and Shostak. Second, we introduce the concept of deduction complete satisfiability procedures, we show how to build them for large classes of theories, then we provide a schema to modularly combine them. Third, we consider the problem of modularly constructing explanations for combinations by re-using available proof-producing procedures for the component theories.