Evolving an Accurate Decision Tree-Based Model for Predicting Carbon Dioxide Solubility in Polymers

Solubility is one of the most indispensable physicochemical properties determining the compatibility of components of a blending system. Research has been focused on the solubility of carbon dioxide in polymers as a significant application of green chemistry. To replace costly and time-consuming experiments, a novel solubility prediction model based on a decision tree, called the stochastic gradient boosting algorithm, was proposed to predict CO₂ solubility in 13 different polymers, based on 515 published experimental data lines. The results indicate that the proposed ensemble model is an effective method for predicting the CO₂ solubility in various polymers, with highly satisfactory performance and high efficiency. It produces more accurate outputs than other methods such as machine learning schemes and an equation of state approach.     

Correction to: Cloud-based vehicular networks: a taxonomy,survey, and conceptual hybrid architecture

Wireless Networks - The original version of this article unfortunately contained a mistake in the title. The correct title has been published with this erratum.     

Selectivity Enhancement to the Exclusive Formation of Ethyltoluenes and Hydrogen During Dehydroalkylation of Toluene with Ethane

The dehydroalkylation of toluene with ethane to the isomeric ethyltoluenes was studied on 0.4Pt/H-ZSM-5 at varying contact times (1/WHSV). At a high contact time of 1.0 h, toluene disproportionation and hydrogenolysis reactions dominate, resulting in low selectivity to the desired ethyltoluenes via the alkylation reaction. However, at a low contact time of 0.12 h side reactions are eliminated, resulting in maximum selectivities to the kinetically favored ethyltoluenes and hydrogen. Results at high selectivities to ethyltoluenes provide significant insight into reaction pathways.     

Motion Perception Using Analog VLSI

Motion perception is arguably a fundamental mechanism used by natural species to accomplish a number of tasks, such as navigating freely in an unknown environment. Traditional motion perception methods tend to be computationally intensive, requiring powerful computers and large memories. However, by copying biological mechanisms, such as elementary motion discrimination at the early stages of the visual processing paths, it should be possible to build small and efficient motion perception systems. This paper describes the manner in which a simple motion perception model based on the insect visual system has been implemented using mixed analog/digital VLSI. The device has been fabricated in a 2 micron double metal, double polysilicon process, and comprises 61 photo-detectors, and associated analog and digital circuitry. While not entirely successful in that component mismatches hamper the detection of dark-to-bright changes in contrast, the results clearly show the feasibility of using such a device in autonomous control systems.     

Prediction of liquid–liquid phase diagrams of aqueous salt+PEG systems using a thermodynamic model

In this study a thermodynamic model for the phase behavior of aqueous salt+polymer solutions is developed. The model is based on the solution theory of Hill, which included scaling laws for the polymer molecular mass dependence and Pitzer–Debye–Hückel theory. This model was tested for systems composed of two different molecular mass of polyethylene glycols (PEG) and five different inorganic salts. All the model parameters were determined from independent measurements. The agreement between the experimental and predicted phase diagrams by this model is good.     

Photocatalytic degradation of methyl tert‐butyl ether (MTBE) in contaminated water by ZnO nanoparticles

BACKGROUND: Over the past several decades methyl tert‐butyl ether (MTBE) as additive to gasoline, intended to either boost ratings of fuel or to reduce air pollution, has been accepted worldwide. Since MTBE has high water solubility, the occurrence of fuel spills or leaks from underground storage tanks or transferring pipeline has led to the contamination of natural waters. In this study the degradation of aqueous MTBE at relatively high concentrations was investigated by a UV‐visible/ZnO/H₂O₂ photocatalytic process. The effects of important operational parameters such as pH, amount of H₂O₂, catalyst loading and irradiation time were also investigated. Concentration of MTBE and intermediates such as tert‐butyl formate and tert‐butyl alcohol were measured. RESULTS: Time required for complete degradation increased from 20 to 150 min when the initial concentration was increased from 10 to 500 mg L^?1. The first‐order rate constants for degradation of MTBE were estimated to be 0.183–0.022 min^?1 as the concentration increased from 10 to 500 mg L^?1. Study of the overall mineralization monitored by total organic carbon analysis showed that at an initial concentration of 100 mg L^?1 MTBE complete mineralization was obtained after 100 min under UV‐visible/ZnO/H₂O₂ photocatalysis. CONCLUSION: The data presented in this paper clearly indicated that UV‐visible/ZnO/O₂ as an advanced oxidation process provides an efficient treatment alternative for the remediation of MTBE‐contaminated waters. Copyright © 2008 Society of Chemical Industry     

Robust control of polytopic systems by convex optimization

Robust control synthesis of linear time-invariant SISO polytopic systems is investigated using the polynomial approach. A convex set of all stabilizing controllers for a polytopic system is given over an infinite-dimensional space. A finite-dimensional approximation of this set is obtained using the orthonormal basis functions and represented by a set of LMIs thanks to the KYP lemma. Then, an LMI based convex optimization problem for robust pole placement with sensitivity function shaping in two- and infinity-norm is proposed. The simulation results show the effectiveness of the proposed method.     

Consistency of robust estimators in multi-structural visual data segmentation

A theoretical framework is presented to study the consistency of robust estimators used in vision problems involving extraction of fine details. A strong correlation between asymptotic performance of a robust estimator and the asymptotic bias of its scale estimate is mathematically demonstrated where the structures are assumed to be linear corrupted by Gaussian noise. A new measure for the inconsistency of scale estimators is defined and formulated by deriving the functional forms of four recent high-breakdown robust estimators. For each estimator, the inconsistency measures are numerically evaluated for a range of mutual distances between structures and inlier ratios, and the minimum mutual distance between the structures, for which each estimator returns a non-bridging fit, is calculated.