Solvent effect and macrovoid formation in cellulose acetate phthalate (CAP)–polyacrylonitrile (PAN) blend hollow fiber membranes

The interactions which govern the morphology of blend hollow fiber membranes is explored in detail in the present work. A hydrophilic (cellulose acetate phthalate) and a relatively hydrophobic polymer (polyacrylonitrile, critical surface tension 47.0 mJ/m²) blend in three solvents, viz., n ‐methylpyrrolidone (NMP), dimethyl formamide (DMF), and dimethylsulfoxide (DMSO), has been selected as an example to understand the polymeric blend—solvent and nonsolvent interactions. The deviation intrinsic parameter ( ) is estimated as well as cloud point, linearized cloud point (LCP), and Fourier transform‐infrared (FT‐IR) analysis have been performed for the blend membranes. The analysis yields that is negative for both DMF and NMP indicating miscibility, whereas for DMSO it is positive indicating immiscibility. Cloud point and LCP analysis too reveal DMSO to be the poorest solvent and liquid‐liquid demixing is the governing phenomenon for the phase inversion. In depth interaction is conducted with help of FT‐IR spectra. The higher red shift of >C==O (1747 to 1665 cm^?1) after complete phase inversion indicates stronger interaction in DMF and NMP, whereas, no shift in >C==O stretching in DMSO indicates weak or no interaction. This reveals that polymer blend‐solvent interaction is weak in case of DMSO than DMF or NMP. These observations manifest in DMSO membranes being most porous, with highest permeability and molecular weight cut off with poor tensile strength. On the other hand, NMP and DMF hollow fiber membranes yields denser structure with better mechanical properties. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133 , 44366.     

Decision‐theoretic rough sets under Pythagorean fuzzy information

Decision‐theoretic rough sets (DTRSs), which provide a classical model of three‐way decisions (3WDs), play an important role in risk decision‐making problems. The risk is associated with the loss function of DTRSs, which is evaluated by the decision makers. As a new extension of fuzzy sets, Pythagorean fuzzy sets can handle uncertain information more flexibly than intuitionistic fuzzy sets in the process of decision making and it gives a new measure for the determination of loss functions of DTRSs. More specifically, we take into account the loss functions of DTRSs with Pythagorean fuzzy numbers and propose a Pythagorean fuzzy decision‐theoretic rough set (PFDTRS) model. Some properties of the expected losses are carefully investigated. Then we further design three approaches for deriving 3WDs with the PFDTRS model. The group decision making (GDM) based on the PFDTRS model is also discussed. It provides a novel interpretation for the determination of loss functions. With the aid of the Pythagorean fuzz weighted averaging operator, we aggregate the loss functions, as suggested by the all experts, which support a coherent way of designing information granules in the presence of numerics. An algorithm for 3WDs in GDM based on the PFDTRS model is designed. Then, an example is presented to elaborate on 3WDs with the PFDTRS model.     

Wigner–Yanase skew information and entanglement generation in quantum measurement

The first step of quantum measurement procedure is known as premeasurement, during which correlation is established between the system and the measurement apparatus. Such correlation may be classical or nonclassical in nature. One compelling nonclassical correlation is entanglement, a useful resource for various quantum information theoretic protocols. Quantifying the amount of entanglement, generated during quantum measurement, therefore, seeks importance from practical ground, and this is the central issue of the present paper. Interestingly, for a two-level quantum system, we obtain that the amount of entanglement, measured in term of negativity, generated in premeasurement process can be quantified by two factors: skew information, which quantifies the uncertainty in the measurement of an observable not commuting with some conserved quantity of the system, and mixedness parameter of the system’s initial state.     

Pythagorean linguistic preference relations and their applications to group decision making using group recommendations based on consistency matrices and feedback mechanism

In this paper, we introduce a new type of fuzzy set, called Pythagorean linguistic sets (PLSs), to address the preferred and nonpreferred degrees of linguistic variables. Moreover, it allows decision makers to offer effectively handle uncertain information more flexible than intuitionistic linguistic sets (ILSs) when one compares two alternatives in the process of decision making. Some of the fundamental operational laws, score, accuracy, and aggregation operators are defined, and their properties are investigated. Preference relation (PR) is a useful and efficient tool for decision making that only requires the decision makers to compare two alternatives at one time. Taking the advantages of PLSs and PRs, this paper also introduces Pythagorean linguistic preference relations (PLPRs) and studies their application. We propose an approach for group decision making using group recommendations based on consistency matrices and feedback mechanism. First, the proposed method constructs the collective consistency matrix, the weight collective PRs, and the group collective PRs. Then, it constructs a consensus relation for each expert and determines the group consensus degree (GCD) for all experts. If the GCD is smaller than a predefined threshold value, then a feedback mechanism is activated to update the PLPRs. Finally, after the GCD is greater than or equal to the predefined threshold value, we calculate the arithmetic mathematical average values of the updated group collective PR to select the most appropriate alternative.     

On robustness of radial basis function network with input perturbation

In this article, we have proposed a methodology for making a radial basis function network (RBFN) robust with respect to additive and multiplicative input noises. This is achieved by properly selecting the centers and widths for the radial basis function (RBF) units of the hidden layer. For this purpose, firstly, a set of self-organizing map (SOM) networks are trained for center selection. For training a SOM network, random Gaussian noise is injected in the samples of each class of the data set. The number of SOM networks is same as the number of classes present in the data set, and each of the SOM networks is trained separately by the samples belonging to a particular class. The weight vector associated with a unit in the output layer of a particular SOM network corresponding to a class is used as the center of a RBF unit for that class. To determine the widths of the RBF units, p-nearest neighbor algorithm is used class-wise. Proper selection of centers and widths makes the RBFN robust with respect to input perturbation and outliers present in the data set. The weights between the hidden and output layers of RBFN are obtained by pseudo inverse method. To test the robustness of the proposed method in additive and multiplicative noise scenarios, ten standard data sets have been used for classification. Proposed method has been compared with three existing methods, where the centers have been generated in three ways: randomly, using k-means algorithm, and based on SOM network. Simulation results show the superiority of the proposed method compared to those methods. Wilcoxon signed-rank test also shows that the proposed method is statistically better than those methods.

     

Tribological behaviour of hot extruded Al–Cu–Mg–Ag alloy reinforced by TiB2 particles

In the present investigation, tribological behaviour of the hot extruded Al–Cu–Mg–Ag (matrix) alloy and the effect of Ti and TiB₂ addition in matrix alloy have been studied. Hot extrusion was introduced to eliminate cast defects like porosity, voids and micro cracks. Addition of Ti and TiB₂ particles increased the hardness of the matrix by grain refinement and dispersion hardening, respectively. It has been observed that the increase in hardness had significantly improved the wear resistance of the material. Detail study of the wear surfaces and debris were carried out to understand the wear mechanism of the samples. It revealed a complex mechanism of micro-cutting, plastic deformation, abrasion and delamination of the wear samples.     

E-health monitoring system enhancement with Gaussian mixture model

Multimedia Tools and Applications - In order to enhance the healthcare system, we have designed and developed a system prototype which remotely monitors patient’s vital parameters by using...     

Force-dominated non-equilibrium oxidation kinetics of tantalum

Using a combined electrochemical and mechanical manipulation technique, we compared the equilibrium and non-equilibrium oxidation processes and states of tantalum. Experimentally, a setup was developed with an electrochemical system attached to a sliding mechanical configuration capable of friction force measurement. The surface chemistry of a sliding surface, i.e., tantalum, was modified through the electrolyte. The mechanically applied force was fixed and the dynamics of the surface was monitored in situ through a force sensor. The formation of non-equilibrium oxidation states of tantalum was found in oxidation limiting environment of acetic acid. An oxidative environment of deionized water saturated with KCl was used as comparison. We proposed a modified Arrhenius-Eyring equation in which the mechanical factor was considered. We found that the mechanical energy induced the non-stable-state reactions leading to metastable oxidation states of tantalum. This equation can be used to predict mechanochemical reactions that are important in many industrial applications.