Connectionist simulation of quantification skills

The study of numerical abilities, and how they are acquired, is being used to explore the continuity between ontogenesis and environmental learning. One technique that proves useful in this exploration is the artificial simulation of numerical abilities with neural networks, using different learning paradigms to explore development. A neural network simulation of subitization, sometimes referred to as visual enumeration, and of counting, a recurrent operation, has been developed using the so-called multi-net architecture. Our numerical ability simulations use two or more neural networks combining supervised and unsupervised learning techniques to model subitization and counting. Subitization has been simulated using networks employing unsupervised self-organizing learning, the results of which agree with infant subitization experiments and are comparable with supervised neural network simulations of subitization reported in the literature. Counting has been simulated using a multi-net system of supervised static and recurrent backpropagation networks that learn their individual tasks within an unsupervised, competitive framework. The developmental profile of the counting simulation shows similarities to that of children learning to count and demonstrates how neural networks can learn how to be combined together in a process modelling development.     

Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.      

Structural,optical and electrical properties of Cu<Subscript>2</Subscript>Zn<Subscript>1−x</Subscript>Cd<Subscript>x</Subscript>SnS<Subscript>4</Subscript> quinternary alloys nanostructures deposited on porous silicon

The Cu₂Zn_1?xCd_xSnS₄ quinternary alloy nanostructures with different Cd contents were grown using spin coating technique on porous silicon (63.93 %) substrate. The structural properties of Cu₂Zn_1?xCd_xSnS₄/PS were investigated by X-ray diffraction and field emission-scanning electron microscope (FE-SEM). The optical properties studied through photoluminescence technique, indicated that the band gap is shifted as Cd content increases from 1.84 eV at x = 0 to 1.76 eV at x = 1. The electrical characterization of the Ag/n-PS/Cu₂Zn_1?xCd_xSnS₄/Ag diode through current to voltage (I–V) characterization shows the highest photo-response of (value if any) at Cu₂Zn_0.4Cd_0.6SnS₄ composition.     

Spatial distribution and habitat characterization of schistosomiasis host snails in lake and land habitats of western Kenya

Intermediate host snails of schistosomiasis were surveyed in this study to determine their abundance and distribution in the lake and land aquatic habitats of Lake Victoria basin of Kenya. Several sites were sampled at eight locations, both in the lake and on the land. The habitat and/or vegetation type (i.e. open water, hippo grass, hyacinth, ambatch trees, other vegetation, stream, swamp, pond, dam) of the sampled aquatic sites within the locations were also differentiated, water physicochemical parameters were determined, and the abundance of different species or taxa of phytoplankton and zooplankton were enumerated and correlated with the abundance of schistosomiasis snails in the sites. The results indicated significantly more Biomphalaria sudanica snails than Bulinus africanus snails in different physical habitats on land (Student's t‐test, P < 0.05), as well as in different locations on land (Student's t‐test, P = 0.026). Regression analyses revealed that several physicochemical parameters, including dissolved oxygen (R² = ?0.659; n = 8; P = 0.014), pH (R² = 0.728; n = 8; P = 0.007) and turbulence (R² = ?0.616; n = 8; P = 0.02), were predictive of Biomphalaria spp. abundance, while pH (R² = 0.610; n = 8; P = 0.02) and turbulence (R² = ?0.578; n = 8; P = 0.028) were predictive of Bulinus spp. abundance in different locations in the lake. Cyanobacteria (R² = 0.638; n = 8; P = 0.02) and chlorophyceae (R² = ?0.50; n = 8; P = 0.05) were shown to be predictive of both Biomphalaria spp. and Bulinus spp. abundance in different locations in the lake. Zooplankton abundance varied significantly between different locations in the lake (One‐way anova , P < 0.001). Bosmina spp. were found to be predictive of both Biomphalaria spp. (R² = ?0.627; n = 8; P = 0.01) and Bulinus spp. (R² = ?0.50; n = 8; P = 0.05) in different locations in the lake. The results from this study will help inform policy regarding control measures for schistosomias and intermediate snail hosts in Lake Victoria waters, as well as in adjacent terrestrial aquatic habitats and even beyond.     

Numerical solution of second‐order,two‐point boundary value problems using continuous genetic algorithms

Second‐order, two‐point boundary‐value problems are encountered in many engineering applications including the study of beam deflections, heat flow, and various dynamic systems. Two classical numerical techniques are widely used in the engineering community for the solution of such problems; the shooting method and finite difference method. These methods are suited for linear problems. However, when solving the non‐linear problems, these methods require some major modifications that include the use of some root‐finding technique. Furthermore, they require the use of other basic numerical techniques in order to obtain the solution. In this paper, the author introduces a novel method based on continuous genetic algorithms for numerically approximating a solution to this problem. The new method has the following characteristics; first, it does not require any modification while switching from the linear to the non‐linear case; as a result, it is of versatile nature. Second, this approach does not resort to more advanced mathematical tools and is thus easily accepted in the engineering application field. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. However, being a variant of the finite difference scheme with truncation error of the order O(h²), the method provides solutions with moderate accuracy. Numerical examples presented in the paper illustrate the applicability and generality of the proposed method. Copyright © 2004 John Wiley & Sons, Ltd.     

Storage and permeation of hydrogen molecule,atom and ions (H+ and H−) through silicon carbide nanotube; a DFT approach

The barriers for the encapsulation and decapsulation of hydrogen ions (cationic hydrogen and hydride), atom, and molecule through silicon carbide nanotube are thoroughly studied. DFT method is selected to measure the kinetic barriers for the passage of hydrogen atom, ions and molecule through nanotube via scanning potential energy surface. The kinetic barriers for the passage (encapsulation and decapsulation) of hydrogen are very important to understand the mechanism of hydrogen storage and release. The barriers for the permeation of H, H⁺ and H^? across SiC nanosheet are lower compared to hydrogen molecule (H₂). The exohedral and endohedral adsorption of hydrogen ions (cation and anion), atom and exohedral hydrogen molecule on silicon carbide are exothermic in nature. Whereas the encapsulation of hydrogen molecule in silicon carbide is endothermic. Electronic properties are analyzed through measurement of energy gap between highest occupied and lowest unoccupied molecular orbitals gap (G_H-L) and the density of state (DOS) spectra. The G_H-L analysis reveals that endohedral complexes have more pronounced effect on electronic properties compared to exohedral complexes. The SiC nanotube has highly favorable properties for storage and release of hydrogen ions, and atom.     

Formal probabilistic analysis of a surgical robot control algorithm with different virtual fixtures

Surgical robots are increasingly being used in operation theaters involving normal or laparoscopic surgeries. The working of these surgical robots is highly dependent on their control algorithms, which require very rigorous analysis to ensure their correct functionality due to the safety-critical nature of surgeries. Traditionally, safety of control algorithms is ensured by simulations, but they provide incomplete and approximate analysis results due to their inherent sampling-based nature. We propose to use probabilistic model checking, which is a formal verification method, for quantitative analysis, to verify the control algorithms of surgical robots in this paper. As an illustrative example, the paper provides a formal analysis of a virtual fixture control algorithm, implemented in a neuro-surgical robot, using the PRISM model checker. In particular, we provide a formal discrete-time Markov chain-based model of the given control algorithm and its environment. This formal model is then analyzed for multiple virtual fixtures, like cubic, hexagonal and irregular shapes. This verification allowed us to discover new insights about the considered algorithm that allow us to design safer control algorithms.     

Influence of processing condition and carbon nanotube on mechanical properties of injection molded multi‐walled carbon nanotube/poly(methyl methacrylate) nanocomposites

In this work, multi‐walled carbon nanotubes (MWCNT) and poly(methyl methacrylate) (PMMA) pellets were compounded via corotating twin‐screw extruder. The produced MWCNT/PMMA nanocomposite pellets were injection molded. The effect of MWCNT concentration, injection melt temperature and holding pressure on mechanical properties of the nanocomposites were investigated. To examine the mechanical properties of the MWCNT/PMMA nanocomposites, tensile test, charpy impact test, and Rockwell hardness are considered as the outputs. Design of experiments (DoE) is done by full factorial method. The morphology of the nanocomposites was performed using scanning electron microscopy (SEM). The results revealed when MWCNT concentration are increased from 0 to 1.5 wt %, tensile strength and elongation at break were reduced about 30 and 40%, respectively, but a slight increase in hardness was observed. In addition, highest impact strength belongs to the nanocomposite with 1 wt % MWCNT. This study also shows that processing condition significantly influence on mechanical behavior of the injection molded nanocomposite. In maximum holding pressure (100 bar), the nanocomposites show highest tensile strength, elongation, impact strength and hardness. According to findings, melt temperature has a trifle effect on elongation, but it has a remarkable influence on tensile strength. In the case of impact strength, higher melt temperature is favorable. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43738.