On stochastic comparisons of finite mixtures for some semiparametric families of distributions

In this paper, we consider the classical finite mixture model, which is an effective tool for modeling lifetime distributions for random samples from heterogeneous populations. We discuss new results on stochastic comparison for two finite mixtures when each of them is drawn from one of the following semiparametric families, i.e., proportional hazards, accelerated lifetime and proportional reversed hazards.     

Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

Synthesis, Characterization and Catalytic Properties of Mesoporous Cobalt Aluminophosphate Molecular Sieves

Isomorphously substituted cobalt(II) hexagonal mesoporous aluminophosphate (CoHMA) molecular sieves were synthesized hydrothermally and characterized by various analytical and spectroscopic techniques. It was deduced that cobalt ions exhibit a divalent oxidation state in tetrahedral coordination in mesoporous aluminophosphates. Further, unlike cobalt-containing microporous aluminophosphate molecular sieves, Co(II) ions remain in a tetrahedral geometry even after calcination. The catalytic activity of CoHMA was tested for the cyclohexane oxidation reaction under mild conditions. Remarkable substrate conversion and product (cyclohexanol) selectivity were obtained compared to several previously reported heterogeneous catalysts.     

Porous Titania Thin Films Grown by Anodic Oxidation for Hydrogen Sensors

Porous titanium dioxide (Titania) thin films were grown by anodic oxidation using high purity (99.7%) titanium foil in a dilute sulphuric acid (1 M) medium. The anodization process was carried out for 30 minutes with 20 mA/cm² and 50 mA/cm² current densities. The samples were characterized by XRD, SEM, and AFM techniques. It was found that the grown porous titania films were less sensitive to 500 ppm hydrogen in air ambient below 300°C; however, the sensitivity and response behavior of the film at 300°C are very much dependent on the growth conditions. Particularly, the films grown at current density 50 mA/cm² and 1 M acid concentration exhibited the lowest response time of 151 sec at 300°C.     

Studies on the Reduction of Coefficient of Variation: A Case Study

In a spinning mill, yarn is the final product. Linear density expressed in terms of count is one of the important characteristics of yarn. Because variability of textile strands increases as the linear density increases, the variability in the count is often measured in terms of coefficient of variation (CV)%. The yarn with a high CV% of count leads to a higher end breakage rate during the spinning and subsequent weaving/knitting operations, and consequently, results in lesser productivity and poorer appearance quality of the woven/knitted fabric. When this woven/knitted fabric is dyed, uneven shades are generated. Because the production of yarn involves processing of raw cotton in multimachines at multistages, possible sources that lead to a high CV% of count are many. Enrick's (1960) analysis procedure, which is based on the modification of the range method for analysis of variance, is used conventionally for detecting the stages where excessive “between-machine” differences are present. When the CV% of count is inflated due to the generation of systematic variation in any machine or introduction of high variability by any machine, this inflation remains undetected when using Enrick's procedure. The case study presented here demonstrates that a step-by-step analysis of linear densities of different stage-outputs starting from yarn to card sliver, using appropriate nested design models along with Duncan's multiple range test, is very useful in detecting all possible sources of a high CV% of count of yarn.     

QOS aware channel and power allocation scheme for D2D enabled cellular networks

Telecommunication Systems - Device-to-device (D2D) communication enabled cellular system is capable of enhancing the spectrum utilization and throughput performance of the system. However, D2D...     

Synthesis of nanocrystalline hydroxyapatite using surfactant template systems: Role of templates in controlling morphology

Hydroxyapatite (HA) nanopowder was synthesized by reverse microemulsion technique using calcium nitrate and phosphoric acid as starting materials in aqueous phase. Cyclohexane, hexane, and isooctane were used as organic solvents, and Dioctyl sulfosuccinate sodium salt (AOT), dodecyl phosphate (DP), NP5 (poly(oxyethylene)₅ nonylphenol ether), and NP12 (poly(oxyethylene)₁₂ nonylphenol ether) as surfactants to make the emulsion. Effect of synthesis parameters, such as type of surfactant, aqueous to organic ratio (A/O), pH and temperature on powder characteristics were studied. It was found that the surfactant templates played a significant role in regulating the morphology of the nanoparticle. Hydroxyapatite nanoparticle of different morphologies such as spherical, needle shape or rod-like were obtained by adjusting the conditions of the emulsion system. Synthesized powder was characterized using X-ray diffraction (XRD), BET surface area and transmission electron microscopy (TEM). Phase pure HA nanopowder with highest surface area of 121 m²/g were prepared by this technique using NP5 as a surfactant. Densification studies showed that this nanoparticle can give about 98% of their theoretical density. In vitro bioactivity of the dense HA compacts was confirmed by excellent apatite layer formation after 21 days in SBF solution. Cell material interaction study showed good cell attachment and after 5 days cells were proliferated on HA compacts in OPC1 cell culture medium. The results imply this to be a versatile approach for making hydroxyapatite nanocrystals with controlled morphology and excellent biocompatibility.