Wavefront reduction using graphs,neural networks and genetic algorithm

This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.     

Maximizing learning without sacrificing the fun: Stealth assessment,adaptivity and learning supports in educational games

In this study, we investigated the validity of a stealth assessment of physics understanding in an educational game, as well as the effectiveness of different game-level delivery methods and various in-game supports on learning. Using a game called Physics Playground, we randomly assigned 263 ninth- to eleventh-grade students into four groups: adaptive, linear, free choice and no-treatment control. Each condition had access to the same in-game learning supports during gameplay. Results showed that: (a) the stealth assessment estimates of physics understanding were valid—significantly correlating with the external physics test scores; (b) there was no significant effect of game-level delivery method on students' learning; and (c) physics animations were the most effective (among eight supports tested) in predicting both learning outcome and in-game performance (e.g. number of game levels solved). We included student enjoyment, gender and ethnicity in our analyses as moderators to further investigate the research questions.     

Design,Facile Synthesis and Characterization of Porphyrin-Zirconium-Ferrite@SiO2 Core-Shell and Catalytic Application in Cyclohexane Oxidation

Silicon - In this study, a new magnetic ZrFe2O4@SiO2-TCPP nanocatalyst with high efficiency was used for the oxidation of cyclohexane to cyclohexanone (Ke) and cyclohexanol (Al). The mesoporous...     

Experimental determination of gas holdup and volumetric mass transfer coefficient in a jet bubbling reactor

The hydrodynamics and mass transfer characteristics of a lab-scale jet bubbling reactor(JBR) including the gas holdup, volumetric mass transfer coefficient and specific interfacial area were assessed experimentally investigating the influence of temperature, p H and superficial gas velocity. The reactor diameter and height were 11 and 30 cm,respectively. It was equipped with a single sparger, operating at atmospheric pressure, 20 and 40℃, and two p H values of 3 and 6. The height of the liquid was 23 cm, while the superficial gas velocity changed within 0.010–0.040 m·s~(-1) range. Experiments were conducted with pure oxygen as the gas phase and saturated lime solution as the liquid phase. The liquid-side volumetric mass transfer coefficient was determined under unsteady-state oxygen absorption in a saturated lime solution. The gas holdup was calculated based on the liquid height change, while the specific interfacial area was obtained by a physical method based on the bubble size distribution(BSD) in different superficial gas velocities. The results indicated that at the same temperature but different p H, the gas holdup variation was negligible, while the liquid-side volumetric mass transfer coefficient at the p H value of 6 was higher than that at the p H = 3. At a constant p H but different temperatures, the gas holdup and the liquid-side volumetric mass transfer coefficients at 40℃ were higher than that of the same at 20℃. A reasonable and appropriate estimation of the liquid-side volumetric mass transfer coefficient(kla) in a pilot-scale JBR was provided which can be applied to the design and scale-up of JBRs.     

Synthesis and characterization of hydrophilic nanocomposite coating on glass substrate

Hydrophilic coatings based on 3‐glicidoxy propyl trimethoxy silane (GPTMS) and polyethylene glycol (PEG) were prepared with the incorporation of tetramethoxysilane (TMOS) and silica nanoparticle colloidal suspension by a sol–gel process. Characterization of the coatings has been performed by Fourier Transform Infrared (FTIR) and Attenuated Total Reflectance Infrared (ATR‐IR) techniques. Morphological properties were characterized by Scanning Electron Microscopy (SEM). The distribution of Si atoms in the hybrid system was obtained by Si mapping. The particle size in sol solution of the coating was measured by light scattering analyzer. Optical properties were characterized by using UV–vis spectrophotometer. The hydrophilicity of the coating was determined by contact angle measurements, and also the results have been confirmed by surface energy and water uptake investigations. The obtained results indicate that the surfactants affected the contact angles remarkably but did not change the transparency. It has been found that applying silica nano particles leads to coatings with different properties than those using TMOS, while siloxane contents were the same in these two set of coatings. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102: 5322–5329, 2006     

Learning to transform time series with a few examples

We describe a semi-supervised regression algorithm that learns to transform one time series into another time series given examples of the transformation. This algorithm is applied to tracking, where a time series of observations from sensors is transformed to a time series describing the pose of a target. Instead of defining and implementing such transformations for each tracking task separately, our algorithm learns a memoryless transformation of time series from a few example input-output mappings. The algorithm searches for a smooth function that fits the training examples and, when applied to the input time series, produces a time series that evolves according to assumed dynamics. The learning procedure is fast and lends itself to a closed-form solution. It is closely related to nonlinear system identification and manifold learning techniques. We demonstrate our algorithm on the tasks of tracking RFID tags from signal strength measurements, recovering the pose of rigid objects, deformable bodies, and articulated bodies from video sequences. For these tasks, this algorithm requires significantly fewer examples compared to fully-supervised regression algorithms or semi-supervised learning algorithms that do not take the dynamics of the output time series into account.     

The role of metacognitive listening strategies awareness and podcast-use readiness in using podcasting for learning English as a foreign language

The aim of this study was to investigate the role of English as Foreign Language (EFL) learners’ metacognitive listening strategies awareness and podcast-use readiness in using podcasting technology for learning English as a foreign language. One hundred and forty-one EFL students completed Metacognitive Awareness Listening Questionnaire (MALQ) that assessed their awareness and perceived use of listening strategies in five components including planning-evaluation, directed attention, person knowledge, mental translation, and problem solving. They also completed a questionnaire that assessed their readiness to use podcasting in terms of familiarity, attitude, and experience. Information on participants’ frequency of podcast use for learning English, frequency of the internet use, and digital device ownership was also obtained. The result of the analysis revealed that podcasting use was significantly related to metacognitive listening strategies awareness in general and its entire components except mental translation strategies while the strongest correlation was found with problem solving strategies (r = .49, p < 0.01). Podcasting use was also found to be significantly related to perceived podcast-use readiness and internet use hours. Further, multiple regressions showed that perceived podcast-use readiness, problem solving, and person knowledge -in order of power prediction- were good predictors of podcasting use for learning English as a foreign language.     

Influence of surface roughness on flotation kinetics of quartz

Surface roughness of quartz particles was determined by measuring the specific surface area of particles. The wettability characteristics of particles were determined by measuring the flotation rate using a laboratory flotation cell. Experimental results show that the rod mill product has higher roughness than the ball mill product. For the particles with larger surface roughness, the flotation kinetics constant is also higher. Finally, empirical relationships between surface roughness (r) and the flotation kinetics constant (k) of quartz particles as k=A+Br+Cr ^0.5lnr+D/lnr+E/r and k=A+Br are presented, in which A, B, C, D and E are constants related to experimental conditions and mineralogical properties of mineral.     

Mathematical Modeling and Genetic Algorithm Optimization of Reactive Absorption of H2S

A rate‐based mathematical model was developed for the reactive absorption of H₂S in NaOH, with NaOCl or H₂O₂ as the chemical oxidant solutions in a packed column. A modified mass transfer coefficient in the gas phase was obtained by genetic algorithm and implemented in the model to correct the assumption of instantaneous reactions. The effects of different operating variables including the inlet H₂S concentration, inlet gas mass flux, initial NaOH, concentrations of the chemical oxidants in the scrubbing solutions, and liquid‐to‐gas ratio on the H₂S removal efficiency were studied. A genetic algorithm was employed to optimize the operating variables in order to obtain maximum removal efficiency of H₂S. The model results were in good agreement with the experimental data.