Profiling drivers based on driver dependent vehicle driving features

This work addresses the problem of profiling drivers based on their driving features. A purpose-built hardware integrated with a software tool is used to record data from multiple drivers. The recorded data is then profiled using clustering techniques. k-means has been used for clustering and the results are counterchecked with Fuzzy c-means (FCM) and Model Based Clustering (MBC). Based on the results of clustering, a classifier, i.e., an Artificial Neural Network (ANN) is trained to classify a driver during driving in one of the four discovered clusters (profiles). The performance of ANN is compared with that of a Support Vector Machine (SVM). Comparison of the clustering techniques shows that different subsets of the recorded dataset with a diverse combination of attributes provide approximately the same number of profiles, i.e., four. Analysis of features shows that average speed, maximum speed, number of times brakes were applied, and number of times horn was used provide the information regarding drivers’ driving behavior, which is useful for clustering. Both one versus one (SVM) and one versus rest (SVM) method for classification have been applied. Average accuracy and average mean square error achieved in the case of ANN was 84.2 % and 0.05 respectively. Whereas the average performance for SVM was 47 %, the maximum performance was 86 % using RBF kernel. The proposed system can be used in modern vehicles for early warning system, based on drivers’ driving features, to avoid accidents.     

A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture

The Journal of Supercomputing - A multimedia-based medical decision-making system is an ultimate requirement in the medical imaging domain. In the healthcare sector, achieving quick and efficient...     

Effect of fortification on physico-chemical and microbiological stability of whole wheat flour

Stability of fortified whole wheat flour (WWF) was evaluated using NaFeEDTA, elemental iron, ZnSO₄ and ZnO as fortificants. Fortified WWF was stored in tin boxes and polypropylene bags for 60 days under ambient storage condition (ASC) and controlled storage condition (CSC). Fortification significantly (p ? 0.05) decreased moisture and protein content and increased ash content to 5.44%, 6% and 23%, as compared to control. Fortified WWF, assayed periodically for mould contamination manifested a significant inhibition (∼1 log reduction) in flours containing elemental iron. Low storage temperature and relative humidity (RH) indicated lower level of mould count during extended storage time. Tin boxes, as storage material, exhibited a better protection against mould attack, acting as an effective barrier for moisture. Fortificants exerted a slight deteriorative effect on texture characteristics of the chapattis made of these flours but chapattis were still accepted by the judges. Zinc fortificants seemed like having little or no effect on the quality of the flours and chapattis, made of such flours. Shelf life of fortified flour may be extended by using elemental iron as fortificant and storing the product in tin boxes under relatively low temperature and RH.     

Investigating Schizocarp morphology as a taxonomic tool in study of Apiaceae family by utilizing LM and SEM techniques

In present study, the schizocarp morphology of 14 species belonging to Apiaceae family has been investigated. Light microscopy (LM) and scanning electron microscopy (SEM) have been utilized to highlight qualitative and quantitative features of studied species. Variations have been observed in macro‐ and micro‐morphological features such as color, shape, symmetry, length, width, apex, epicuticular projections, surface patterns, anticlinal, and periclinal wall patterns. Schizocarp shapes observed were oval, round, triangular, linear, elliptic, and globose. Fruit was either homomorphic or heteromorphic. Crystalloids, stellate hair, multicellular spines, and platelets were mostly observed epicuticular projections. Surface patterns on the fruit surface were striate, rugulate‐striate, reticulate, and striato‐knotted. Both macro‐ and micro‐morphological characters can serve as an important tool in classifying Apiaceae family at various taxonomic ranks. Substantial variations observed can assist as useful constraints at various taxonomic levels as they provide reliable and constant details. Disparities observed in schizocarp features can pave a path for Apiaceae family classification based on phylogenetic and molecular studies.     

Removal and recovery of zirconium from its aqueous solution by Candida tropicalis

Removal and recovery of zirconium from dilute aqueous solutions by Candida tropicalis used as biosorbent, was studied by performing biosorption-desorption tests. This biosorbent was selected after screening a range of microbial species. The process was found to be highly dependent on initial pH and concentration of metal solution. At optimized experimental parameters, the maximum zirconium biosorption capacity of C. tropicalis was 179 mg Zr g(-1) dry weight of biosorbent. The adsorption distribution coefficient value of 3968 ml g(-1) was obtained for zirconium biosorption by C. tropicalis. Different theoretical thermodynamic models governing the adsorption behavior of zirconium were also tested. Zirconium biosorption was found to closely follow the Langmuir model. At low biomass concentrations it was found to follow pseudo-first-order kinetics. However when higher biomass concentrations were used kinetics was changed to pseudo-second-order. The zirconium bound to the biomass was stripped out (60.2% at S/L of 1.0 g of zirconium loaded biomass/l of eluent) using sodium bicarbonate and the biomass could be used for multiple sorption-desorption cycles.     

Nanocomposite BaZr0.7Sm0.1Y0.2O3−δ–La0.8Sr0.2Co0.2Fe0.8O3−δ materials for single layer fuel cell

Single layer fuel cell (SLFC) is a novel breakthrough in energy conversion technology. This study is to realize the physical-electrochemical co-driving mechanism of a single component device composed of mixed ionic and semiconductor material. This paper is focused on investigating the mechanism and characterization of synthesized nanocomposite BaZr_0.7Sm_0.1Y_0.2O_3?δ (BZSY)–La_0.8Sr_0.2Co_0.2Fe_0.8O_3?δ (LSCF) in proportion 1:1 and 3:7 for SLFC. The crystallographic structure and morphology is studied with X-ray diffraction (XRD) and scanning electron microscopy (SEM). The nano-particles lie in the range of 100–210 nm. Ultraviolet (UV) and electrochemical impedance spectroscopy (EIS) is used to analyze the semiconducting nature of nanocomposite (BZSY–LSCF). The performance of SLFC was carried out at different temperatures ranging between 400 and 650 °C. The mixed conductivity of the synthesized material was about 2.3 S cm^?1. The synergic effect of junction and energy band gap towards charge separation as well as the promotion of ion transport by junction built in field contributes to the working principle and high power output in the SLFC.     

New EWMA charts for process variance

The EWMA chart is effective in detecting small shifts in the process mean or process variance. Numerous EWMA charts for the process variance have been suggested in the literature. In this article, new one-sided and two-sided EWMA charts are developed for monitoring the variance of a normal process. In developing these new EWMA charts, first, new unbiased estimators of the process variance are developed, followed by incorporating the developed estimators into the new EWMA charts' statistics. The Monte Carlo simulation method is adopted to evaluate the zero-state and steady-state run-length performances of the proposed EWMA variance charts, in comparison with that of three existing EWMA variance charts and the weighted adaptive CUSUM variance chart. The findings reveal that the proposed charts generally perform better than the existing charts. An example of application is given to show the implementation of the proposed and existing charts in detecting increases or decreases in the process variance.     

Physico-chemical study for zinc removal and recovery onto native/chemically modified Aspergillus flavus NA9 from industrial effluent

Zinc biosorption characteristic of locally isolated Aspergillus flavus NA9 were examined as a function of pH, temperature, pulp density, contact time and initial metal ion concentration. The maximum zinc uptake was found to be 287.8 ± 11.1 mg g^?1 with initial metal concentration 600 mg L^?1 at initial pH 5.0 and temperature 30 °C. The equilibrium data gave good fits to Freundlich and Florry models with correlation coefficient value of 0.98. The contribution of the functional groups and lipids to zinc biosorption as identified by chemical pretreatment was in the order: carboxylic acids > hydroxyl > amines > lipids. The mechanism of biosorption was also studied using Fourier transform infrared (FTIR) spectrometry, scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDX). The biosorbent was regenerated using 0.01 M HCl with 83.3% elution efficiency and was reused for five sorption–desorption cycles with 23.5% loss in biosorption capacity. The order of co-cations showing increased inhibitions of zinc uptake by A. flavus NA9 was Pb > Cu > Mn > Ni. The biosorption assays conducted with actual paint industry effluents revealed efficiency of 88.7% for Zn (II) removal by candidate biomass.     

Kinetic studies for Ni(II) biosorption from industrial wastewater by Cassia fistula (Golden Shower) biomass

The present study explores the ability of Cassia fistula waste biomass to remove Ni(II) from industrial effluents. C. fistula biomass was found very effective for Ni(II) removal from wastewater of Ghee Industry (GI), Nickel Chrome Plating Industry (Ni-Cr PI), Battery Manufacturing Industry (BMI), Tanner Industry: Lower Heat Unit (TILHU), Tannery Industry: Higher Heat Unit (TIHHU), Textile Industry: Dying Unit (TIDU) and Textile Industry: Finishing Unit (TIFU). The initial Ni(II) concentration in industrial effluents was found to be 34.89+/-0.01, 183.56+/-0.08, 21.19+/-0.01, 43.29+/-0.03, 47.26+/-0.02, 31.38+/-0.01 and 31.09+/-0.01mg/L in GI, Ni-Cr PI, BMI, TILHU, TIHHU, TIDU and TIFU, respectively. After biosorption the final Ni(II) concentration in industrial effluents was found to be 0.05+/-0.01, 17.26+/-0.08, 0.03+/-0.01, 0.05+/-0.01, 0.1+/-0.01, 0.07+/-0.01 and 0.06+/-0.01mg/L in GI, Ni-Cr PI, BMI, TILHU, TIHHU, TIDU and TIFU, respectively. The % sorption Ni(II) ability of C. fistula from seven industries included in present study tend to be in following order: TILHU (99.88)>GI (99.85) approximately BMI (99.85)>TIFU (99.80)>TIHHU (99.78)>TIDU (99.77)>Ni-Cr PI (90.59). Sorption kinetic experiments were performed in order to investigate proper sorption time for Ni(II) removal from wastewater. Batch metal ion uptake capacity experiments indicated that sorption equilibrium reached much faster in case of industrial wastewater samples (480min) in comparison to synthetic wastewater (1440min) using same biosorbent. The kinetic data were analyzed in term of pseudo-first-order and pseudo-second-order expressions. Pseudo-second-order model described well the sorption kinetics of Ni(II) onto C. fistula biomass from industrial effluents in comparison to pseudo-first-order kinetic model. Due to unique high Ni(II) sorption capacity of C. fistula waste biomass it can be concluded that it is an excellent biosorbent for Ni(II) uptake from industrial effluents.