Special issue : Computational intelligence models for image processing and information reasoning

Computational Intelligence (CI) models comprise robust computing methodologies with a high level of machine learning quotient. CI models, in general, are useful for designing computerized intelligent systems/machines that possess useful characteristics mimicking human behaviors and capabilities in solving complex tasks, e.g., learning, adaptation, and evolution. Examples of some popular CI models include fuzzy systems, artificial neural networks, evolutionary algorithms, multi-agent systems, decision trees, rough set theory, knowledge-based systems, and hybrid of these models. This special issue highlights how different computational intelligence models, coupled with other complementary techniques, can be used to handle problems encountered in image processing and information reasoning.

Facile preparation and thermoelectric properties of Bi₂Te₃ based alloy nanosheet/PEDOT:PSS composite films

Bi2Te3 based alloy nanosheet (NS)/poly(3,4-ethylenedioxythiophene):poly(4-styrenesulfonate) (PEDOT:PSS) composite films were prepared separately by spin coating and drop casting techniques. The drop cast composite film containing 4.10 wt % Bi2Te3 based alloy NSs showed electrical conductivity as high as 1295.21 S/cm, which is higher than that (753.8 S/cm) of a dimethyl sulfoxide doped PEDOT:PSS film prepared under the same condition and that (850-1250 S/cm) of the Bi2Te3 based alloy bulk material. The composite film also showed a very high power factor value, ∼32.26 μWm(-1) K(-2). With the content of Bi2Te3 based alloy NSs increasing from 0 to 4.10 wt %, the electrical conductivity and Seebeck coefficient of the composite films increase simultaneously.

Performance enhancement of single-walled nanotube-microwave exfoliated graphene oxide composite electrodes using a stacked electrode configuration

We report the development of a stacked electrode supercapacitor cell using stainless steel meshes as the current collectors and optimised single walled nanotubes (SWNT)-microwave exfoliated graphene oxide (mw rGO) composites as the electrode material. The introduction of mw rGO into a SWNT matrix creates an intertwined porous structure that enhances the electroactive surface area and capacitive performance due to the 3-D hierarchical structure that is formed. The composite structure was optimised by varying the weight ratio of the SWNTs and mw rGO. The best performing ratio was the 90% SWNT-10% mw rGO electrode which achieved a specific capacitance of 306 F g-1 (3 electrode measurement calculated at 20 mV s-1). The 90% SWNT-10% mw rGO was then fabricated into a stacked electrode configuration (SEC) which significantly enhanced the electrode performance per volume (1.43 mW h cm-3, & 6.25 W cm-3). Device testing showed excellent switching capability up to 10 A g-1, and very good stability over 10000 cycles at 1.0 A g-1 with 93% capacity retention. © the Partner Organisations 2014.

Research of a new type rectifier and voltage-multiplier piezoelectric energy harvester circuit

Traditional rectifier circuit can convert AC to DC, but some disadvantages can't be avoided, such as small output current, high power consumption, low conversion efficiency. This paper designs a new type of rectifier voltage-multiplier circuit named MR MOS circuit. It uses a low let-through resistance MOS tube to replace the conventional rectifier diode, and adds the voltage-multiplying factor to the synchronous input port. Therefore, it can improve the rectifier effect and increase the output voltage. By the simulation result of Synopsys Saber Platform, it shows that the new type circuit can implement the rectification and voltage-multiplying by the simulating output pulse voltage of nano fiber made in Deakin University as the source of excitation. It can provide the basic theoretical of the piezoelectric energy harvester (PEH) development, and has certain reference significance to the development of piezoelectricity technology. © (2014) Trans Tech Publications.

Testing for error correction in panel data

This paper proposes new error correction-based cointegration tests for panel data. The limiting distributions of the tests are derived and critical values provided. Our simulation results suggest that the tests have good small-sample properties with small size distortions and high power relative to other popular residual-based panel cointegration tests. In our empirical application, we present evidence suggesting that international healthcare expenditures and GDP are cointegrated once the possibility of an invalid common factor restriction has been accounted for. © 2007 Blackwell Publishing Ltd.