A novel elephant herd optimization model with a deep extreme Learning machine for solar radiation prediction using weather forecasts

The Journal of Supercomputing - In recent times, the exploitation of solar resources has remained a major issue due to increasing energy utilization globally. For effective solar resource...     

Acute renal failure in a patient with mantle cell lymphoma

Mantle cell lymphoma is a rare form of B‐cell lymphoma. We present a 54‐year‐old gentleman with mantle cell lymphoma. It was diagnosed based on the demonstration of B‐cell antigens CD20 and CD5. It was further confirmed by demonstration of overexpression of cyclin D1 on these atypical lymphocytes in the immunohistochemical staining. He also had acute renal failure and proteinuria. Renal biopsy revealed crescents and lymphomatous infiltration of tubulointerstitium. The presence of infiltrating cells with similar markers in both the lymph node and the kidney confirmed the infiltration of kidney with lymphomatous cells. Our present patient, after a thorough literature search, is found to be the second one with a glomerular lesion and tubulointerstitial infiltration by malignant lymphoma cells.     

Selection of machining parameters for constrained machining problem using evolutionary computation

In this paper, the optimization of cutting parameters for constrained machining operations is reported. Modified genetic algorithm (MGA) is an evolutionary computation technique that has been proposed in this paper to solve the machining problem. Additional constraints have been incorporated to the multipass turning model. The optimization of drilling and facing parameters have also been carried out. To demonstrate the procedure and performance of the approach, an illustrative example is discussed. The results of the proposed algorithm are compared with other traditional and non-traditional techniques such as Newton’s method, hill climbing and ants colony technique.     

Enhanced photovoltaic performance of a dye sensitized solar cell with Cu/N Co-doped TiO<Subscript>2</Subscript> nanoparticles

Pure and Copper/Nitrogen (Cu/N)-codoped TiO₂ photoanodes with various Cu concentrations are prepared via sol–gel route for the photoanode application in dye-sensitized solar cells (DSSCs). All the prepared samples are characterized by X-Ray Diffraction (XRD), X-Ray Photoelectron Spectroscopy (XPS), Scanning Electron Microscope (SEM), Transmission Electron Microscopy (TEM), UV–Vis spectroscopy (UV–VIS) and Electrochemical Impedance Spectroscopy (EIS). Addition of suitable amount of Cu and N content in TiO₂ can alter its optical and electrical properties by extending absorption in the visible region and band gap reduction. The results show that some of the Ti sites are replaced by Cu atoms while O sites are occupied by N atoms. Upon adequate addition of Cu/N could lead to smaller particle size, higher specific surface area, increased dye adsorption and retarded charge carrier recombination. A significant improvement in the power conversion efficiency is observed in case of optimized 0.3 mol% Cu/N-doped TiO₂ nanoparticles (NPs) based DSSC. This optimized 0.3 mol% Cu/N-doped photoanode accomplished a best power conversion efficiency of 11.70% with a short circuit current density of 23.41 mA cm^?2 which is 41% higher than that of the pure TiO₂ photoanode based DSSC (6.82%).     

Efficient Resource Allocation in Fog Computing Using QTCS Model

Infrastructure of fog is a complex system due to the large number of heterogeneous resources that need to be shared. The embedded devices deployed with the Internet of Things (IoT) technology have increased since the past few years, and these devices generate huge amount of data. The devices in IoT can be remotely connected and might be placed in different locations which add to the network delay. Real time applications require high bandwidth with reduced latency to ensure Quality of Service (QoS). To achieve this, fog computing plays a vital role in processing the request locally with the nearest available resources by reduced latency. One of the major issues to focus on in a fog service is managing and allocating resources. Queuing theory is one of the most popular mechanisms for task allocation. In this work, an efficient model is designed to improve QoS with the efficacy of resource allocation based on a Queuing Theory based Cuckoo Search (QTCS) model which will optimize the overall resource management process.     

Solution combustion synthesis of iron tungstate nanoparticles for photoelectrochemical water splitting towards oxygen evolution

Journal of Materials Science: Materials in Electronics - Iron tungstate (FeWO4) nanoparticles were prepared by simple solution combustion technique. The preparation method discloses the first...     

Application of local error method to SSSF simulation of vector propagation in dispersion compensated optical links

A local error method based on an analytical scheme previously developed for the scalar optical fiber channel is applied to the second-order symmetrized split-step Fourier simulation of polarization multiplexed signal propagation through dispersion compensated optical fiber links. It is found that the global simulation accuracy for the vector propagation can be satisfied using the local error bound from a scalar propagation model for the same global error over a large range of simulation accuracy, chromatic dispersion, and differential group delay. Furthermore, carefully designed numerical simulations are used to show that similar local simulation error are obtained for vector simulations and that the similar local error leads to higher computational efficiency compared to other prevalent step-size selection schemes. The scaling of the global simulation error with respect to the number of optical fiber spans is demonstrated, and global error control for multi-span simulations is proposed. Combining the local error and global error control, the developed simulation scheme can significantly speed up the time-consuming simulations in coherent optical fiber communication system analysis and design.     

On minimizing the system information age in vehicular ad-hoc networks via efficient scheduling and piggybacking

Recent advances in vehicular networks have enforced researchers to focus on various information dissemination techniques. Exchanging information among the vehicles is imperative due to the ever-changing network topology in vehicular networks. However, random transmitter selection in traditional CSMA based channel access mechanism limits the delay performance. Data, such as state information, is often time critical, and hence, efficient information dissemination techniques to improve delay performance are essential. In this work, we aim to minimize the average system age which is the mean number of time slots old a vehicle’s information is at all other vehicles in the network. To achieve this, we explore the benefits of simultaneous transmission along with piggybacking of information for multi-hop communication. While allowing simultaneous transmission guarantees faster dissemination of information, piggybacking facilitates dissemination of more information per transmission, thereby keeping the network more updated. We have also analysed the relationship between piggybacked information and number of vehicles in the network. Simulation results show improvement in network performance. Our analytical results are in good agreement with the simulation results.     

Sequential separation of lanthanides, thorium and uranium using novel solid phase extraction method from high acidic nuclear wastes

A novel grafted polymer for selective extraction and sequential separation of lanthanides, thorium and uranium from high acidic wastes has been developed by grafting Merrifield chloromethylated (MCM) resin with octyl(phenyl)-N,N-diisobutylcarbamoyl-methylphosphine oxide (CMPO) (MCM-CMPO). The grafting process is well characterized using FT-IR spectroscopy, (31)P and (13)C CPMAS (cross-polarized magic angle spin) NMR spectroscopy and CHNPS elemental analysis. The influence of various physico-chemical parameters during metal ion extraction by the resin phase are studied and optimized by both static and dynamic methods. The resin shows very high sorption capacity values of 0.960mmolg(-1) for U(VI), 0.984mmolg(-1) for Th(IV), 0.488mmolg(-1) for La(III) and 0.502mmolg(-1) for Nd(III) under optimum HNO(3) medium, respectively. The grafted polymer shows faster rate exchange kinetics (<5min is sufficient for 50% extraction) and greater preconcentration ability, with reusability exceeding 20 cycles. During desorption process, sequential separation of the analytes is possible with varying eluting agents. The developed grafted resin has been successfully applied in extracting Th(IV) from high matrix monazite sand, U(VI) and Th(IV) from simulated nuclear spent fuel mixtures. All the analytical data is based on triplicate analysis and measurements are within 3.5% rsd reflecting the reproducibility and reliability of the developed method.