Polynomial-Time Approximation Schemes for Subset-Connectivity Problems in Bounded-Genus Graphs

We present the first polynomial-time approximation schemes (PTASes) for the following subset-connectivity problems in edge-weighted graphs of bounded-genus: Steiner tree, low-connectivity survivable-network design, and subset TSP. The schemes run in $\mathcal{O}(n \log n)$ time for graphs embedded on both orientable and nonorientable surfaces. This work generalizes the PTAS framework from planar graphs to bounded-genus graphs: any problem that is shown to be approximable by the planar PTAS framework of Borradaile et al. (ACM Trans. Algorithms 5(3), 2009) will also be approximable in bounded-genus graphs by our extension.     

Geometry and topology optimization of geodesic domes using charged system search

Dome structures provide cost-effective solutions for covering large areas without intermediate supports. In this article, simple procedures are developed to reach the configuration of the geodesic domes. A new definition of dome optimization problems is given which consists of finding optimal sections for elements (size optimization), optimal height for the crown (geometry optimization) and the optimum number of elements (topology optimization) under determined loading conditions. In order to find the optimum design, the recently developed meta-heuristic algorithm, known as the Charged System Search (CSS), is applied to the optimum design of geodesic domes. The CSS takes into account the nonlinear response of the domes. Using CSS, the optimum design of the geodesic domes is efficiently performed.     

Vocal-based emotion recognition using random forests and decision tree

This paper proposes a new vocal-based emotion recognition method using random forests, where pairs of the features on the whole speech signal, namely, pitch, intensity, the first four formants, the first four formants bandwidths, mean autocorrelation, mean noise-to-harmonics ratio and standard deviation, are used in order to recognize the emotional state of a speaker. The proposed technique adopts random forests to represent the speech signals, along with the decision-trees approach, in order to classify them into different categories. The emotions are broadly categorised into the six groups, which are happiness, fear, sadness, neutral, surprise, and disgust. The Surrey Audio-Visual Expressed Emotion database is used. According to the experimental results using leave-one-out cross-validation, by means of combining the most significant prosodic features, the proposed method has an average recognition rate of \(66.28\%\), and at the highest level, the recognition rate of \(78\%\) has been obtained, which belongs to the happiness voice signals. The proposed method has \(13.78\%\) higher average recognition rate and \(28.1\%\) higher best recognition rate compared to the linear discriminant analysis as well as \(6.58\%\) higher average recognition rate than the deep neural networks results, both of which have been implemented on the same database.     

Predicting Interfacial Loads between the Prosthetic Socket and the Residual Limb for Below-Knee Amputees – A Case Study

Abstract:  In this study, an artificial neural network (ANN) was deployed as a tool to determine the internal loads between the residual limb and prosthetic socket for below-knee amputees. This was achieved by using simulated load data to validate the ANN and captured clinical load data to predict the internal loads at the residual limb–socket interface. Load/pressure was applied to 16 regions of the socket, using loading pads in conjunction with a load applicator, and surface strains were collected using 15 strain gauge rosettes. A super-position program was utilised to generate training and testing patterns from the original load/strain data collected. Using this data, a back-propagation ANN, developed at the University of the West of England, was trained. The input to the trained network was the surface strains and the output the internal loads/pressure. The system was validated and the mean square error (MSE) of the system was found to be 8.8% for 1000 training patterns and 8.9% for 50 testing patterns, which was deemed an acceptable error. Finally, the validated system was used to predict pressure-sensitive/-tolerant regions at the limb–socket interface with great success.     

Investigating the effect of nano-silica on efficiency of the foam in enhanced oil recovery

Due to the vast production of crude oil and consequent pressure drops through the reservoirs, secondary and tertiary oil recovery processes are highly necessary to recover the trapped oil. Among the different tertiary oil recovery processes, foam injection is one of the most newly proposed methods. In this regard, in the current investigation, foam solution is prepared using formation brine, C₁₉TAB surfactant and air concomitant with nano-silica (SiO₂) as foam stabilizer and mobility controller. The measurements revealed that using the surfactant-nano SiO₂ foam solution not only leads to formation of stable foam, but also can reduce the interfacial tension mostly considered as an effective parameter for higher oil recovery. Finally, the results demonstrate that there is a good chance of reducing the mobility ratio from 1.12 for formation brine and reservoir oil to 0.845 for foam solution prepared by nanoparticles.     

Fabricating Janus membranes via physicochemical selective chemical vapor deposition

Membranes with asymmetric wettability-Janus membranes-have recently received considerable attention for a variety of critical applications. Here, we report on a simple approach to introduce asymmetric wettability into hydrophilic porous domains. Our approach is based on the physicochemical-selective deposition of polytetrafluoroethylene (PTFE) on hydrophilic polymeric substrates. To achieve selective deposition of PTFE, we inhibit the polymerization reaction within the porous domain. We prefill the substrates with glycerol, containing a known amount of free radical inhibitor, and utilize initiated chemical vapor deposition (iCVD) for the polymerization of PTFE. We show that the glycerol/inhibitor mixture hinders the deposition of PTFE within the membrane pores. As a result, the surface of the substrates remains open and porous. The fabricated Janus membranes show stable wetting-resistant properties, evaluated through sessile drop contact angle measurements and direct contact membrane distillation (DCMD).     

Dynamic mechanical behavior and nanostructure morphology of hyperbranched‐modified polypropylene blends

Polypropylene (PP) was modified utilizing two types of polyesteramide‐based hyperbranched polymers (amphiphilic PS and hydrophilic PH). A maleicanhydride‐modified PP (PM) was used as a reactive dispersing agent to enhance the modification by grafting the hyperbranched polymers onto the PP chains. Pure PP, two different non‐reactively modified samples, i.e. excluding PM, and two different reactively modified samples, i.e. including PM, were studied. Investigating the morphology of the samples was performed by scanning electron microscopy. To follow the effect of the modification on the dynamic mechanical properties, dynamic mechanical analysis experiments both in the melt (rheometric mechanical spectrometry) and in solid state (dynamic mechanical thermal analysis) were carried out. In the next step, the nanocrystalline structure of the samples was studied by small angle X‐ray scattering (SAXS) in two different modes, i.e. static and recrystallization. Hundreds of SAXS patterns were analyzed automatically using procedures written in PV‐WAVE image‐processing software. The chord distribution function (CDF) was calculated and the long period (l_p) of the crystal lamellae was extracted from the CDFs. The rheometric mechanical spectrometry results show that both hyperbranched polymers decrease complex viscosity η^* and enhance liquid‐like behavior. This happens more significantly when PM is included. The dynamic mechanical thermal analysis results reveal that T_g decreases when PS and PH are added. In the reactively modified samples this reduction is compensated most probably because of the crosslinked structure formed through the grafting reaction between the hyperbranched polymers and PM. Such structure is confirmed by SAXS data and calculated CDFs in the recrystallization mode. Static SAXS data also show enhancement in the crosshatched morphology of the crystalline lamellae of PP for reactively modified samples compared with non‐reactively modified samples. © 2013 Society of Chemical Industry     

Modification of poly(propylene) by grafted polyester‐amide‐based dendritic nanostructures with the aim of improving its dyeability

Fiber‐graded poly(propylene) was modified by polyester‐amide‐based dendritic nanostructures with the aim of improving its dyeability. Two different dendritic polymers were used and the dendritic nanostructures were formed in situ via reactive blending with maleic anhydride‐modified poly(propylene). Samples were chosen exploiting a 4‐component mixture design. Thermal, morphological, and rheological characterizations showed domains with different size and distribution were formed and primary properties of the dendritics determined the characteristics of the resulted domains. Morphological parameters were quantified by digital analysis of scanning electron microscope images. Thermal and rheological behavior also demonstrated good agreements with the inferred morphology of the formed dendritic domains. The modified samples were then dyed with dispersed dyestuffs. A variety of substantivities were obtained, and some of the modified samples showed a significant enhancement in dyeing properties. A predictive model was developed for K/S ratio, where K and S are absorption and scattering coefficients of the Kubelka‐Munk one constant theory, respectively. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012