A metaheuristic analysis of heat transfer rates through porous fins of tapered and step profiles: a comparative study

Neural Computing and Applications - The advanced high-end gadgets and sophisticated machines require effective mechanism of transferring heat away from the sources. In a large number of...     

Nonlinear static and dynamic analysis of circular plates and shallow spherical shells using the collocation method

The present work investigates the efficacy and applicability of interior global orthogonal point collocation method to the axisymmetric nonlinear analysis of elastic circular plates and shallow spherical shells subjected to uniformly distributed transverse load. Spacewise discretisation has been carried out using a polynomial expansion with the zeros of a Chebyshev polynomial as collocation points. Timewise integration has been carried out with Newmark k-β scheme corresponding to average acceleration method. The static response and snap-through buckling results, as well as, the dynamic response and dynamic buckling results under a uniformly distributed step load have been obtained and found to agree closely with the available results.     

An efficient clustering scheme using support vector methods

Support vector clustering involves three steps—solving an optimization problem, identification of clusters and tuning of hyper-parameters. In this paper, we introduce a pre-processing step that eliminates data points from the training data that are not crucial for clustering. Pre-processing is efficiently implemented using the R*-tree data structure. Experiments on real-world and synthetic datasets show that pre-processing drastically decreases the run-time of the clustering algorithm. Also, in many cases reduction in the number of support vectors is achieved. Further, we suggest an improvement for the step of identification of clusters.     

Non-darcy natural convection from a heated vertical plate in saturated porous media with mass transfer

The nonsimilar and self-similar flows for the steady natural convection over a vertical heated surface in a saturated porous medium with mass transfer using non-Darcy model have been studied under boundary layer approximations. The differential equations governing both the nonsimilar and self-similar flows have been solved numerically using an implicit finite-difference scheme developed by Keller. The results indicate that both heat transfer and velocity field are appreciably affected by the modified Grashof number and mass transfer except that the effect of the modified Grashof number on the heat transfer for large suction is very small. It is found that the maximum velocity occurs at the wall and it increases as the modified Grashof number or injection increases.     

Effect of Calcium Lactate, 4-Hexyl Resorcinol and Vacuum Packing on Physico-chemical, Sensory and Microbiological Qualities of Minimally Processed Litchi (Litchi chinensis Sonn.)

Litchi (Litchi chinensis Sonn.) fruits are very susceptible to pericarp browning which adversely affects consumer acceptability even though the aril portion remains in excellent condition. Litchi arils (litchis) were treated with a solution containing 0–2% (w/v) calcium lactate (CL), 0–0.02% (w/v) 4‐hexyl resorcinol (4‐HR) and 1% potassium sorbate. The pH of solution was adjusted to 4.0 with citric acid. Treated litchis were packed in polystyrene trays, over‐wrapped with polypropylene film, vacuum‐packed (0, 47409.3, 94831.9 Pa) and stored at 4 ± 2 °C. Drip losses, pH, total soluble solids (TSS), sensory attributes and microbiological quality of stored samples were estimated. A four‐factor, three‐level experimental design (D₆ Hokes design) with 19 experiments was chosen. Mathematical models were developed to analyse and predict the effect of CL, 4‐HR, in‐package vacuum and storage time on the responses. TSS, pH and sensory scores decreased significantly (P 0.01), whereas drip losses and microbial count increased significantly (P 0.01) with time. Drip loss was significantly (P 0.1) reduced by addition of CL. 4‐HR prevented browning and changes in colour score during storage were significantly less. Vacuum in packages exerted significant (P 0.01) effect over pH, TSS, sensory and microbiological qualities of minimally processed litchis.     

Fluorescence in situ hybridization (FISH): DNA probe production and hybridization criteria

We describe methods for the production of fluorescence in situ hybridization (FISH) probes and the utilization of these probes for the detection of complementary DNA sequences with accuracy and sensitivity for application in both basic research and clinical diagnosis. Due to the frequent use of FISH in many laboratories, it is important to apply the most convenient and reproducible approach. This review describes some of the most recent techniques, and includes versatile, effective and simple methods of probe production and fluorescence in situ hybridization. We also describe methods for the production of region-specific and chromosome-specific DNA probes and hybridization techniques for the visualization of these probes.     

An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.