Manganese ferrite-polyaniline hybrid materials: Electrical and magnetic properties

Magnetic MnFe₂O₄ nanopowders were synthesized by an original solvothermal method in the absence and in the presence of tetra-n-butylammonium bromide (TBAB) and Tween 80 (TW) as surfactants. Manganese ferrite/polyaniline (PANI) hybrid materials were synthesized by in situ polymerization of aniline on the surface of MnFe₂O₄ using ammonium persulfate as oxidant. The purpose of the study was to investigate the influence of the two surfactants on the properties of the MnFe₂O₄ powders and of their composites with PANI. The specific surface area, the cumulative surface area of pores and the cumulative volume of pores are influenced by the nature of surfactant in case of MnFe₂O₄ powders and are higher by comparison to those of the MnFe₂O₄/PANI hybrid materials. The values of saturation magnetization in case of MnFe₂O₄ powders are higher than those of the hybrid materials and are not influenced by the surfactant nature. These features revealed that MnFe₂O₄ powders can be efficiently used as adsorbents for the purification of wastewaters. The values of the electrical conductivity of the composites exhibit a significant increase in comparison to the MnFe₂O₄ powders and depend on the surfactant nature. The highest value of electrical conductivity was achieved by the composite obtained using Tween 80 as surfactant (σ_DC = 54.5·10^?5S?m^?1) which was close to that of PANI (σ_DC = 61.2·10^?5 S?m^?1). The fact that the magnetic and electric properties of the synthesized MnFe₂O₄/PANI composites can be changed by design, demonstrate the high potential of these materials to be used in magneto-electric applications.     

Static and free vibration analysis of functionally graded plates based on a new quasi-3D and 2D shear deformation theories

In this study, two dimensional (2D) and quasi three-dimensional (quasi-3D) shear deformation theories are presented for static and free vibration analysis of single-layer functionally graded (FG) plates using a new hyperbolic shape function. The material of the plate is inhomogeneous and the material properties assumed to vary continuously in the thickness direction by three different distributions; power-law, exponential and Mori–Tanaka model, in terms of the volume fractions of the constituents. The fundamental governing equations which take into account the effects of both transverse shear and normal stresses are derived through the Hamilton's principle. The closed form solutions are obtained by using Navier technique and then fundamental frequencies are found by solving the results of eigenvalue problems. In-plane stress components have been obtained by the constitutive equations of composite plates. The transverse stress components have been obtained by integrating the three-dimensional stress equilibrium equations in the thickness direction of the plate. The accuracy of the present method is demonstrated by comparisons with the different 2D, 3D and quasi-3D solutions available in the literature.     

Ion beam induced evolution of surface morphology and optical properties of SnO2–ZnO nanocomposite thin films

SnO₂–ZnO nanocomposite thin films, prepared by a simple carbothermal reduction based vapor deposition method, were irradiated with 8 MeV Si³⁺ ions for engineering the morphological and optical properties. The surface morphology of the nanocomposites was studied by atomic force microscopy (AFM), while the optical properties were investigated by photoluminescence spectroscopy (PL) and Raman spectroscopy. AFM studies on the irradiated samples revealed growth of nanoparticles at lower fluence and a significant change in surface morphology leading to the formation of nanosheets and their aggregates at higher fluences. A tentative mechanism underlying the observed ion induced evolution of surface morphology of SnO₂–ZnO nanocomposite is proposed. PL studies revealed strong enhancement in the UV emissions from the nanocomposite thin film at lower fluence, while a drastic decrease in the UV emissions along with a significant enhancement in the defect emissions has been observed at higher fluences.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

Improvement of adhesion and paint ability of EVA copolymers with different vinyl acetate contents by treatment with UV-ozone

The surface modifications produced by UV-ozone treatment of two ethylene-vinyl acetate (EVA) copolymers containing 12 and 20 wt% vinyl acetate (EVA12 and EVA20 respectively) were studied. The treatment with UV-ozone improved the wettability of both EVAs due to the creation of new carbon–oxygen moieties. The extent of these modifications increased with increasing length of the treatment and the modifications produced in EVA20 were produced for shorter lengths of treatment. The UV-ozone treatment also created roughness and heterogeneities on the EVA surfaces. Whereas roughness formation prevailed on the UV-ozone treated EVA12, important ablation was dominant on the treated EVA20. T-peel strength values in joints made with polychloroprene adhesive increased when the EVAs were treated with UV-ozone. Short length of UV-ozone treatment (1 min) produced higher T-peel strength in joints made with EVA20 whereas higher T-peel strength values in joints made with EVA12 were obtained after treatment for 5–7.5 min in which a cohesive failure into a weak boundary layer on the treated EVA surface was found. Furthermore, the adhesion of UV-ozone treated EVA20 to acrylic paint increased. Finally, the ageing resistance of the treated EVA/polychloroprene adhesive joints was good and the surface modifications on the UV-ozone treated EVAs lasted for 24 h after treatment at least.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Anti‐Sway Crane Control Considering Wind Disturbance and Container Mass

A method for estimating the sway angle using an observer has already been proposed. The state observer estimates the sway angle accurately and must use the detected sway angle value. However, the estimated sway angle has an error owing to rope length error, friction force, and wind. Moreover, the container mass cannot be determined, and therefore the observer parameter is not suitable. We already proposed robust antisway control for overcoming rope length error without adding a new sensor. Further, we designed a friction disturbance observer to cancel out the influence of the friction force. In this paper, we first propose a container mass estimation method when a crane system performs rolling up control. The observer parameter can be selected using the estimated mass value. Second, in crane parallel shift control, we propose a robust antisway control even when there is a wind disturbance. We design a wind disturbance observer and propose a wind disturbance estimator to separate the friction observer output from the wind disturbance observer output. We confirm through experiments that the proposed method can reduce vibration.     

A conceptualization of intended learning outcomes supporting self‐regulated learners in indicating learning paths

Intended learning outcomes (ILOs) indicate what learners will be able to achieve after they are taught. Traditionally, ILOs are expressed as plain text or unstructured documents. What if all ILOs of a specific course of study can be conceptualized through a structured diagrammatic technique? It was hypothesized that learners can benefit from this conceptualization in learning, especially in self‐regulated learning. The aim of this study was to investigate whether the ILOs represented in unstructured or structured formats can facilitate learners to identify learning paths. The results revealed that the mean ratings of all learning paths were statistically significantly higher with structured ILOs.