Correlation between lattice strain and magnetic properties enhancement of nanocrystalline cobalt ferrite with controlled annealing

Journal of Materials Science: Materials in Electronics - Spinel cobalt ferrite (CoFe2O4) has been prepared using the citrate precursor sol–gel method. The synthesized samples have been...     

An advanced fingerprint matching using minutiae-based indirect local features

Multimedia Tools and Applications - Biometric systems examine the uniqueness of an individual based on physical and behavioral characteristics. Among the known traits, fingerprint is the most...     

Assessment of Shear Stress Distribution in Meandering Compound Channels with Differential Roughness Through Various Artificial Intelligence Approach

Water Resources Management - Accurate prediction of shear stress distribution along the boundary in an open channel is the key to solving numerous critical engineering problems such as flood...     

Increasing ionic conductivity and mechanical strength of a plastic electrolyte by inclusion of a polymer

In this contribution we present a soft matter solid electrolyte which was obtained by inclusion of a polymer (polyacrylonitrile, PAN) in LiClO₄/LiTFSI-succinonitrile (SN), a semi-solid organic plastic electrolyte. Addition of the polymer resulted in considerable enhancement in ionic conductivity as well as mechanical strength of LiX-SN (X = ClO₄, TFSI) plastic electrolyte. Ionic conductivity of 92.5%-[1 M LiClO₄-SN]:7.5%-PAN (PAN amount as per SN weight) composite at 25 °C recorded a remarkably high value of 7 × 10⁻³ Ω⁻¹ cm⁻¹, higher by few tens of order in magnitude compared to 1 M LiClO₄-SN. Composite conductivity at sub-ambient temperature is also quite high. At −20 °C, the ionic conductivity of (100 − x)%-[1 M LiClO₄-SN]:x%-PAN composites are in the range 3 × 10⁻⁵-4.5 × 10⁻⁴ Ω⁻¹ cm⁻¹, approximately one to two orders of magnitude higher with respect to 1 M LiClO₄-SN electrolyte conductivity. Addition of PAN resulted in an increase of the Young's modulus (Y) from Y → 0 for LiClO₄-SN to a maximum of 0.4 MPa for the composites. Microstructural studies based on X-ray diffraction, differential scanning calorimetry and Fourier transform infrared spectroscopy suggest that enhancement in composite ionic conductivity is a combined effect of decrease in crystallinity and enhanced trans conformer concentration.     

Multi-objective particle swarm optimization algorithm using adaptive archive grid for numerical association rule mining

Neural Computing and Applications - The most challenging issues in association rule mining are dealing with numerical attributes and accommodating several criteria to discover optimal rules without...     

Machine learning approach to recognize ventricular arrhythmias using VMD based features

The occurrence of life-threatening ventricular arrhythmias (VAs) such as Ventricular tachycardia (VT) and Ventricular fibrillation (VF) leads to sudden cardiac death which requires detection at an early stage. The main aim of this work is to develop an automated system using machine learning tool for accurate prediction of VAs that may reduce the mortality rate. In this paper, a novel method using variational mode decomposition (VMD) based features and C4.5 classifier for detection of ventricular arrhythmias is presented. The VMD model was used to decompose the electrocardiography (ECG) signals to extract useful informative features. The method was tested for ECG signals obtained from PhysioNet database. Two standard databases i.e. CUDB (Creighton University Ventricular Tachyarrhythmia Database) and VFDB (MIT-BIH Malignant Ventricular Ectopy Database) were considered for this work. A set of time–frequency features were extracted and ranked by the gain ratio attribute evaluation method. The ranked features are subjected to support vector machine (SVM) and C4.5 classifier for classification of normal, VT and VF classes. The best detection was obtained with sensitivity of 97.97%, specificity of 99.15%, and accuracy of 99.18% for C4.5 classifier with a 5 s data analysis window. These results were better than SVM classifier result having an average accuracy of 86.87%. Hence, the proposed method demonstrates the efficiency in detecting the life-threatening VAs and can serve as an assistive tool to clinicians in the diagnosis process.

     

Degradation Kinetics and Storage Stability of Vacuum Spray-Dried Micro Wet-Milled Orange Juice (<Emphasis Type="Italic">Citrus unshiu</Emphasis>) Powder

The aim of this work was to evaluate the degradation kinetics and stability of micro wet milled orange juice powders obtained by vacuum spray drying, using maltodextrin as a carrier agent. Powders were produced with four combinations of orange juice solids/maltodextrin solids 60:40, 50:50, 40:60, and 30:70 by weight. Ascorbic acid degradation, color, and antioxidant activity of powders were evaluated throughout 90 days. Powders were stored at 10, 25, and 35 °C and relative humidity of 33%. Temperature and storage time negatively influenced the stability of ascorbic acid and color, whereas antioxidant activity increased at the beginning of storage at a higher temperature then decreased slightly after 60 days. For stability study, powders were stored at different water activities (0.11 to 0.84) in order to determine the plasticizing effects of water on glass transition temperature. Both water activity and glass transition temperature were used to predict the critical conditions for storage. Vacuum spray dried powder produced with a ratio of 30:70 (orange juice solids/maltodextrin solids) was considered as the most stable, since it showed highest critical water activity (a_w?=?0.61) and lowest moisture content (0.11 g water/g of dry solid) among the four powders. Vacuum spray drying using superheated steam as the heating medium was proven to be an effective way of producing orange juice powders with minimum loss of nutrients.     

Eye ultrastructure in the pollen-feeding beetle, Xanthochroa luteipennis (Coleoptera: Cucujiformia: Oedemeridae)

The pollen-consuming beetle Xanthochroa luteipennis, which belongs to the family Oedemeridae, possesses a nearly spherical eye of approximately 400 microm in diameter. The eye contains 750-800, mostly hexagonal ommatidia, which are of the acone apposition type and have an open rhabdom. A well-developed pupil mechanism controls the light flux to the rhabdom. The pupil is formed with the help of screening pigment translocations, involving primary and secondary (accessory) pigment cells. Cross-sections of rhabdoms reveal that they are developed as ring-like structures, made up of the rhabdomeres of six retinula cells, surrounding a rod-like inner column of two fused rhabdomeres. Rhabdoms of ommatidia in the middle of the eye differ somewhat from those in more peripheral areas. In the former the central rhabdom is circular in cross-section, while in the latter it is spindle-shaped. The rhabdom organization in combination with the distal pupil mechanism is seen as an adaptation to maximize photon capture under a variety of ambient light intensities, for Oedemerid beetles are commonly active during the day as well as the night.     

Comparative analysis and robustness study of logic styles

Microsystem Technologies - This paper explores design of various components that are extensively used in digital circuits namely AND gate, OR gate, NAND gate, NOR gate and Full Adder using GDI...