Dynamic Time Slice Calculation for Round Robin Process Scheduling Using NOC

Process scheduling means allocating a certain amount of CPU time to each of the user processes.  One of the popular scheduling algorithms is the “Round Robin” algorithm, which allows each and every process to utilize the CPU for short time duration.  Processes which finish executing during the time slice are removed from the ready queue.  Processes which do not complete execution during the specified time slice are removed from the front of the queue, and placed at the rear end of the queue. This paper presents an improvisation to the traditional round robin scheduling algorithm, by proposing a new method. The new method represents the time slice as a function of the burst time of the waiting process in the ready queue. Fixing the time slice for a process is a crucial factor, because it subsequently influences many performance parameters like turnaround time, waiting time, response time and the frequency of context switches.  Though the time slot is fixed for each process, this paper explores the fine-tuning of the time slice for processes which do not complete in the stipulated time allotted to them

Effect of β/α Strength Ratio on the Stress-Strain Curve of Beta Titanium Alloy by Finite Element Modelling

A systematic study was undertaken to determine the effect of the β/α strength ratio on the stress-strain behavior of near beta titanium alloy by the finite element method where the volume percent of the second phase was constant at 16 vol.%. The β/α strength ratio of the harder β phase to the softer α phase was varied from approximately 4 to 5 where the a phase strength (0.2% YS) was kept constant at 296 MPa. It was found that the flow stress did not vary linearly with the strength ratio. Stress gradients were found in both α and β phases and the nature of the stress gradient was found to depend on α particle shape. In some locations higher stresses were found in near the interface. In β, the stresses were generally higher near the interfaces

Classification of skin disease using deep learning neural networks with mobilenet V2 and LSTM

Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. This study proposed a computerized process of classifying skin disease through deep learning-based MobileNet V2 and Long Short Term Memory (LSTM). The MobileNet V2 model proved to be efficient with a better accuracy that can work on lightweight computational devices. The proposed model is efficient in maintaining stateful information for precise predictions. A grey-level co-occurrence matrix is used for assessing the progress of diseased growth. The performance has been compared against other state-of-the-art models such as Fine-Tuned Neural Networks (FTNN), Convolutional Neural Network (CNN), Very Deep Convolutional Networks for Large-Scale Image Recognition developed by Visual Geometry Group (VGG), and convolutional neural network architecture that expanded with few changes. The HAM10000 dataset is used and the proposed method has outperformed other methods with more than 85% accuracy. Its robustness in recognizing the affected region much faster with almost 2x lesser computations than the conven-tional MobileNet model results in minimal computational efforts. Furthermore, a mobile application is designed for instant and proper action. It helps the patient and dermatologists identify the type of disease from the affected region’s image at the initial stage of the skin disease. These findings suggest that the proposed system can help general practitioners efficiently and effectively diagnose skin conditions, thereby reducing further complications and morbidity

Critical current densities of high pressure oxygen sputtered thin films of YBa<SUB>2</SUB>Cu<SUB>3</SUB>O<SUB>7-x</SUB> by non-resonant rf absorption method

The critical current densities (Jc) have been measured at 77K in high pressure oxygen sputtered thin films of YBa2Cu3O7-x superconductor using the non-resonant rf absorption technique. High values of Jc (~ 105A/cm2) are observed in these relatively large area (~ 1.2 cm2) films

Molecular interaction in binary mixtures of 1,4-butanediol+picolines: Viscometric approach

The viscosity (h) of {1,4-butanediol (i) + α-, or β-, or γ-picoline (j)}binary mixtures have been measured and reported at 303.15, 308.15, 313.15 and 318.15 K over the entire range of composition. Viscosity deviation (∆h) and excess Gibbs energy of activation of viscous flow (∆G*E) based on Eyring’s theory have been evaluated and the results fitted to the Redlich-Kister equation. The ∆h values are observed to be negative over the entire range of composition for (1,4-butanediol+α-picoline), (1,4-butanediol+β-picoline) and (1,4-butanediol+γ-picoline) systems. The experimental viscosity data have been compared with some well-known equations of Frenkel, modified Frenkel approach and predictive ones like McAllister, Grunberg-Nissan, Hind et al., Tamura Kurata and Katti-Chaudhri. The effects of molecular sizes and shapes of the component molecules on the molecular interactions present thereof in the mixtures have been discussed.

Biochemical Composition and Disease Resistance in Newly Synthesized Amphidiploid and Autotetraploid Peanuts

Genetic diversity in peanut (Arachishypogaea L.) is narrow due to its evolution and domestication processes. Amphidiploids and autotetraploids (newly synthesized tetraploids) were created to broaden its genetic base. Molecular analysis has shown that the newly synthesized tetraploids had broader genetic base; and were genetically divergent when compared to cultivated peanut. Nutritional composition relative to oil, fatty acid composition, O/L ratio, protein, iodine value and presence of plant proteinase inhibitors such as trypsin and chymotrypsin inhibitors were studied in the synthesized tetraploids. Some of the newly synthesized tetraploids had higher amounts of proteinase inhibitors. Evaluation of newly synthesized tetraploids revealed several lines resistant to late leaf spot (LLS) and peanut bud necrosis disease (PBND)

Enhanced Microwave Absorption Properties of Intrinsically Core/shell Structured La0.6Sr0.4MnO3Nanoparticles

The intrinsically core/shell structured La0.6Sr0.4MnO3nanoparticles with amorphous shells and ferromagnetic cores have been prepared. The magnetic, dielectric and microwave absorption properties are investigated in the frequency range from 1 to 12 GHz. An optimal reflection loss of −41.1 dB is reached at 8.2 GHz with a matching thickness of 2.2 mm, the bandwidth with a reflection loss less than −10 dB is obtained in the 5.5–11.3 GHz range for absorber thicknesses of 1.5–2.5 mm. The excellent microwave absorption properties are a consequence of the better electromagnetic matching due to the existence of the protective amorphous shells, the ferromagnetic cores, as well as the particular core/shell microstructure. As a result, the La0.6Sr0.4MnO3nanoparticles with amorphous shells and ferromagnetic cores may become attractive candidates for the new types of electromagnetic wave absorption materials

An assessment of the Indian Ocean mean state and seasonal cycle in a suite of interannual CORE-II simulations

We present an analysis of annual and seasonal mean characteristics of the Indian Ocean circulation and water masses from 16 global ocean–sea-ice model simulations that follow the Coordinated Ocean-ice Reference Experiments (CORE) interannual protocol (CORE-II). All simulations show a similar large-scale tropical current system, but with differences in the Equatorial Undercurrent. Most CORE-II models simulate the structure of the Cross Equatorial Cell (CEC) in the Indian Ocean. We uncover a previously unidentified secondary pathway of northward cross-equatorial transport along 75 °E, thus complementing the pathway near the Somali Coast. This secondary pathway is most prominent in the models which represent topography realistically, thus suggesting a need for realistic bathymetry in climate models. When probing the water mass structure in the upper ocean, we find that the salinity profiles are closer to observations in geopotential (level) models than in isopycnal models. More generally, we find that biases are model dependent, thus suggesting a grouping into model lineage, formulation of the surface boundary, vertical coordinate and surface salinity restoring. Refinement in model horizontal resolution (one degree versus degree) does not significantly improve simulations, though there are some marginal improvements in the salinity and barrier layer results. The results in turn suggest that a focus on improving physical parameterizations (e.g. boundary layer processes) may offer more near-term advances in Indian Ocean simulations than refined grid resolution

Stability and aromaticity of nH2@B12N12 (n=1–12) clusters

Standard ab initio and density functional calculations are carried out to determine the structure, stability, and reactivity of B12N12 clusters with hydrogen doping. To lend additional support, conceptual DFT-based reactivity descriptors and the associated electronic structure principles are also used. Related cage aromaticity of this B12N12 and nH2@B12N12 are analyzed through the nucleus independent chemical shift values