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Showing papers by "Rajasthan Technical University published in 2020"


Journal ArticleDOI
TL;DR: A novel Support Vector Regression method is proposed to analysis five different tasks related to novel coronavirus to get better classification accuracy and the promising results demonstrate its superiority in both efficiency and accuracy.
Abstract: In this paper, we are working on a pandemic of novel coronavirus (COVID-19). COVID-19 is an infectious disease, it creates severe damage in the lungs. COVID-19 causes illness in humans and has killed many people in the entire world. However, this virus is reported as a pandemic by the World Health Organization (WHO) and all countries are trying to control and lockdown all places. The main objective of this work is to solve the five different tasks such as I) Predicting the spread of coronavirus across regions. II) Analyzing the growth rates and the types of mitigation across countries. III) Predicting how the epidemic will end. IV) Analyzing the transmission rate of the virus. V) Correlating the coronavirus and weather conditions. The advantage of doing these tasks to minimize the virus spread by various mitigation, how well the mitigations are working, how many cases have been prevented by this mitigations, an idea about the number of patients that will recover from the infection with old medication, understand how much time will it take to for this pandemic to end, we will be able to understand and analyze how fast or slow the virus is spreading among regions and the infected patient to reduce the spread based clear understanding of the correlation between the spread and weather conditions. In this paper, we propose a novel Support Vector Regression method to analysis five different tasks related to novel coronavirus. In this work, instead of simple regression line we use the supported vectors also to get better classification accuracy. Our approach is evaluated and compared with other well-known regression models on standard available datasets. The promising results demonstrate its superiority in both efficiency and accuracy.

107 citations


Journal ArticleDOI
TL;DR: This paper introduces a novel exponential spider monkey optimization which is employed to fix the significant features from high dimensional set of features generated by SPAM and demonstrates that the selected features by Exponential SMO effectively increase the classification reliability of the classifier in comparison to the considered feature selection approaches.

95 citations


Journal ArticleDOI
TL;DR: A mathematical model considering susceptible, exposed, infected, asymptotic, quarantine/isolation and recovered classes as in case of COVID-19 disease is developed and Elasticity and sensitivity analysis indicates that model is more sensitive towards the transmission rate from exposed to infected classes rather than Transmission rate from susceptible to exposed class.
Abstract: In this article, we develop a mathematical model considering susceptible, exposed, infected, asymptotic, quarantine/isolation and recovered classes as in case of COVID-19 disease. The facility of quarantine/isolation have been provided to both exposed and infected classes. Asymptotic individuals either recovered without undergo treatment or moved to infected class after some duration. We have formulated the reproduction number for the proposed model. Elasticity and sensitivity analysis indicates that model is more sensitive towards the transmission rate from exposed to infected classes rather than transmission rate from susceptible to exposed class. Analysis of global stability for the proposed model is studied through Lyapunov's function.

71 citations


Journal ArticleDOI
TL;DR: The proposed optimization techniques outperform the existing methods with promising exploration and exploitation abilities to solve engineering optimization problems and significantly improve the system performance.

46 citations


Journal ArticleDOI
01 Mar 2020
TL;DR: In this paper, the modal analysis of an axially functionally graded material beam under hygrothermal effect is presented, where the material constants of the beam are supposed to be graded smoothly.
Abstract: This investigation focuses on the modal analysis of an axially functionally graded material beam under hygrothermal effect. The material constants of the beam are supposed to be graded smoothly alo...

45 citations


Journal ArticleDOI
TL;DR: Comparison of RRF based spot price forecasts with existing non-parametric machine learning models reveal that RRFs based forecast accuracy outperforms other models.
Abstract: Spot instances were introduced by Amazon EC2 in December 2009 to sell its spare capacity through auction based market mechanism. Despite its extremely low prices, cloud spot market has low utilization. Spot pricing being dynamic, spot instances are prone to out-of bid failure. Bidding complexity is another reason why users today still fear using spot instances. This work aims to present Regression Random Forests (RRFs) model to predict one-week-ahead and one-day-ahead spot prices. The prediction would assist cloud users to plan in advance when to acquire spot instances, estimate execution costs, and also assist them in bid decision making to minimize execution costs and out-of-bid failure probability. Simulations with 12 months real Amazon EC2 spot history traces to forecast future spot prices show the effectiveness of the proposed technique. Comparison of RRFs based spot price forecasts with existing non-parametric machine learning models reveal that RRFs based forecast accuracy outperforms other models. We measure predictive accuracy using MAPE, MCPE, OOB Error and speed. Evaluation results show that $MAPE M A P E = 10 % for 66 to 92 percent and $MCPE M C P E = 15 % for 35 to 81 percent of one-day-ahead predictions with prediction time less than one second. $MAPE M A P E = 15 % for 71 to 96 percent of one-week-ahead predictions.

40 citations


Proceedings ArticleDOI
15 Jul 2020
TL;DR: Detect or segmentation techniques are used to detect and segment the brain-tumor region from the MRI images of brain and it is very useful method in recent days.
Abstract: The brain tumor is a disease that affects or harms the brain with unwanted tissues. This is very difficult to detect brain tumor tissue from whole brain. Early detection of tumor is very important to save patient's life. Detection or segmentation techniques are used to detect and segment the brain-tumor region from the MRI images of brain and it is very useful method in recent days. In medical, magnetic-resonance-imaging is a tough field in image processing because accuracy percentage must be very high so doctors could get proper idea about diseases to save patient's life. Some MRI images have been taken as inputs data. The brain-tumor segmentation process is performed for separating brain-tumor tissues from brain MRI images, The MRI images should be filtering such as with the median filtering technique and skull stripping should be done in pre-processing, the thresholding process is being done on the given MRI images with using the watershed segmentation method. Then at last the segmented tumor region is obtained. And then in other phase features extracted by GLCM methods using MATLAB software. Then, the some images have been classified using support vector machine (SVM), this system obtained with the average accuracy of 93.05%. Which is quite better than other conventional models.

36 citations


Journal ArticleDOI
TL;DR: A novel Ultra-wideband–Multi-Input-Multi-Output Antenna Sensor (UMAS) probe is designed for the detection of the malignant cells in the breast and it exhibits clear detection of normal and malignant breast phantoms.
Abstract: In this work, a novel Ultra-wideband-Multi-Input-Multi-Output Antenna Sensor (UMAS) probe is designed for the detection of the malignant cells in the breast. The Sensor probe has four radiating elements and it is operated within the 2.8 GHz to 20 GHz ultra-wide band range. Isolation between the radiating element is more than 20 dB. Further, three kinds of the breast phantoms (i.e. normal phantom, phantom with single and multiple tumors) are fabricated using tissue mimicking material. The electrical characteristics of the malignant cells are different from non-malignant cells of the breast. The S-parameter and Specific Absorption Rate (SAR) analysis are best approaches to detect the malignant cells in the breast. The UMAS sensing probe is embedded on the phantoms and S-parameters of the probe are recorded from the Vector Network Analyzer (VNA). Measured S-parameters of the probe for normal and malignant phantoms are differ from each other. The statistical machine learning concept of Principal Component Analysis (PCA) is also applied on the measured S-Parameters. Which exhibits clear detection of normal and malignant breast phantoms. Further verification is done by using Simulation based specific absorption rate (SAR) study of the phantom models for tumor detection. The obtained maximum SAR results are well differentiating the normal phantom.

32 citations


Journal ArticleDOI
TL;DR: A novel FT approach named node-link failure fault tolerance model (NLFFT Model) in WSN is presented, to handle the faults that occur either by link or node failure during data transmission from the sensor to the sink or base station.
Abstract: A wireless sensor network (WSN) is a collection of various tiny devices known as sensor nodes, which are also called motes. Due to high-energy consumption, the possibility of hardware, link or node failure, and some malicious attacks, sensor networks are considered error-prone networks. Hence, fault tolerance (FT) in WSN is one of the prominent issues. This article presents a novel FT approach named node-link failure fault tolerance model (NLFFT Model) in WSN, to handle the faults that occur either by link or node failure during data transmission from the sensor to the sink or base station. The NLFFT model consists of an improved quadratic minimum spanning tree (Imp-QMST) approach. This approach helps in finding the alternate link whenever it fails due to various situations and also an improved-handoff (Imp-Handoff) algorithm to support the node failure to the fault tolerance. Improved QMST presents a novel mechanism to find an alternate edge in place of the broken or failed edge in the spanning tree, to improve the fault tolerance in WSN. Imp-Handoff suggests a novel way to find the faulty node owing to less battery power and replaces a defective node by an appropriate neighbor to shift the tasks performed by a faulty node in WSN. Simulation results clearly state that as compared to the basic techniques i.e. Q-MST and Handoff algorithm, the proposed NLFFT model improvises the performance of WSN around by 7%. The results prove that the Imp-QMST gives about 6% improved throughput, 5% less end-to-end delay, and 6% less power consumption than the QMST algorithm. Similarly, Imp-Handoff improves about 4% throughput, 6% less end-to-end delay, and utilizes 7% less power consumption.

31 citations


Proceedings ArticleDOI
01 Dec 2020
TL;DR: In this paper, the authors analyzed the tweets regarding COVID-19 from November, 2019 to May, 2020 in India and its affect, all tweets are categorized into three categories (Positive, Negative and Neutral).
Abstract: Corona Virus or COVID-19 first appeared in December, 2019 in Wuhan, China. People tweeted aggressively on twitter at that time. This paper analysed the tweets regarding COVID-19 from November, 2019 to May, 2020 in India and its affect. All tweets are categorized into 3 categories(Positive, Negative and Neutral). Multiple datasets are created State-wise, Month-wise, combined of all states to analyze the people's reactions towards Lockdown in June, 2020 and about everything related to COVID-19. Most people started having Negative tweets but with increasing time people shifted towards positive and neutral comments. In April, 2020 most comments were Positive and about winning against Corona virus.

24 citations


Book ChapterDOI
01 Jan 2020
TL;DR: In this article, a novel dispersion compensation model has been presented with chirped fiber Bragg grating (CFBG) for longhaul transmission system, which has been designed for 20 Gbps non-return to zero (NRZ) transmission system over 210 km long singlemode fiber (SMF).
Abstract: In this work, a novel dispersion compensation model has been presented with chirped fiber Bragg grating (CFBG) for long-haul transmission system. The proposed model has been designed for 20 Gbps non-return to zero (NRZ) transmission system over 210 km long single-mode fiber (SMF). The proposed model is applied to Dense Wavelength Division Multiplexing (DWDM) also. Performance of the model is optimized through linear-chirped CFBG having 90 mm short grating length and it plays a significant role as a module of dispersion compensation. The proposed model enhance/improves the performance in terms of bit error rate (BER) and quality factor is ≥18 at the receiver end of systems. Further, it has also been compared with existing reported work on the basis of quality factor, BER, and eye-diagrams. The simulations of the proposed model have been carried out through OptiSystem 7.

Journal ArticleDOI
TL;DR: The proposed TSGWO outperformed other methods with maximal average Residual energy of 2.161 J, maximal link lifetime of 0.075 s, maximal PDR of 96.38%, and maximal throughput of429.49 Kbps.
Abstract: Internet of Things (IoTs) have become popular for connected people as well as objects for collecting and exchanging data based on embedded sensors. In IoT-assisted Wireless sensor Networks (WSN), the nodes are considered as the resource parameters in several ways, like computing resources, energy resources, and storage resources such that the robust multipath routing protocols are needed for maintaining long network lifetime and for achieving higher energy utilization. Hence, this paper presents the multipath routing protocol using the proposed optimization method, named Tunicate swarm Grey Wolf optimization (TSGWO) algorithm in the IoT assisted WSN network. By multipath routing protocol, the multipath is designed by multipath source node to several destinations. The multipath source node forwarding packet to multiple destinations simultaneously. At first, the nodes in IoT-assisted WSN network is simulated together and performs the cluster head selection using Fractional Gravitational Search algorithm (FGSA), and then the multipath routing process is done on the basis of proposed TSGWO in which the routing path is selected by considering the fitness parameters, like QoS parameters and trust factors. The QoS parameters include the delay, energy, link lifetime, as well as distance. The path with the minimum distance is selected as optimal path using fitness parameter. The proposed optimization algorithm effectively performs the multipath routing mechanism by integrating the parametric features from both the optimization algorithm. After that, the route maintenance process is carried out in the simulated IoT network to recover the link breakage based on DRINA. The proposed TSGWO outperformed other methods with maximal average Residual energy of 2.161 J, maximal link lifetime of 0.075 s, maximal PDR of 96.38%, and maximal throughput of429.49 Kbps.

Journal ArticleDOI
TL;DR: A compact and computationally optimized MIMO antenna for UWB applications that provides extended ultra-wide impedance bandwidth of 3–25 GHz (fractional bandwidth 157%), enhanced isolation S 21 ≤ − 27 dB envelope correlation coefficient (ECC = 0.002), good pattern diversity, and constant group delay.
Abstract: Isolation and bandwidth are the two important performance parameters of the multiple-input-multiple-output (MIMO) antenna. A small footprint of an antenna with enhanced isolation and extended bandwidth is highly desirable for space-limited UWB applications. In this paper, we present a compact and computationally optimized MIMO antenna for UWB applications. The proposed antenna consists of two micro-strip-fed semicircular radiating elements. The inverted prism-shaped ground stub is used to enhance isolation. A truncated-shaped partial ground plane with two ground slots is used for impedance matching over the extended UWB. The circular monopole radiating elements of the reference antenna (RA) are converted into semicircular radiating elements for efficient utilization of the available space. The initial design parameters are obtained from the RA. In the next step, the initial design parameters are optimized by a fast and accurate surrogate-assisted optimization model. Using the optimized design parameters, the final design of the antenna is simulated using a computer simulation tool. The prototype of the antenna is fabricated on a Roger substrate (substrate height ‘h’ = 0.8 mm) with a dielectric constant of 3. The manufactured prototype with the size of 31 × 18 mm2 is experimentally evaluated and validated using vector network analyser and anechoic chamber. The proposed MIMO antenna provides extended ultra-wide impedance bandwidth of 3–25 GHz (fractional bandwidth 157%), enhanced isolation S21 ≤ − 27 dB envelope correlation coefficient (ECC = 0.002), good pattern diversity, and constant group delay. Finally, the obtained results are compared with the existing literature.

Proceedings ArticleDOI
13 May 2020
TL;DR: The pest diseases specifically with their impact on the current production of the crop are illustrated and the image detection technique emerges as an effective measurement tool in order to fight the infestation.
Abstract: Agriculture is an essential source of sustenance In India, this sector has tremendous opportunities of large-scale employment for villagers A survey report illustrated the dependency of the Indian population on agriculture ie nearly 70% Here, agriculture consist of the composition of several crops depending on the climatic nature However, most of the Indian farmers are still unaware of technical knowledge such as what kind of crop suits their farmland Numerous heterogeneous diseases affect the production of crops and result as a profitable loss This paper illustrates the pest diseases specifically with their impact on the current production of the crop In addition, it shows the survey reports based on several detection techniques of image detection It is important to search and develop more techniques in order to identify the pest disease before it creates a serious loss in crop production The current method for the reduction of pest disease is to spray pesticides However, this process severely affects the health of humans directly or indirectly The pest detection techniques at the early stages can provide less need for spraying pesticides The image detection technique emerges as an effective measurement tool in order to fight the infestation This technique offers better crop management with production as it delivers the maximum protection to crops Such techniques also minimize human errors and efforts as providing the feature of automatic monitoring over large fields

Journal ArticleDOI
TL;DR: In this paper, a direct injection VCR diesel engine was used in experimental investigations for determining the combustion characteristics of D-NM-DEE blends at different compression ratios, and a significant improvement in engine performance, and reduction in emission and fuel cost was achieved.
Abstract: Research in the field of alternative, clean and renewable bio-fuels has increased dramatically in recent years for performance improvement, emission control and running cost reduction in internal combustion engines due to continuously increasing prices of conventional fuels, depletion of fossil fuels and environmental protection. In this work, a direct injection VCR diesel engine was used in experimental investigations for determining the combustion characteristics of D–NM–DEE blends at different compression ratios. By exhaust emission and performance analysis of the diesel engine at peak load and standard compression ratio (18.5), D–NM2.5–DEE7.5 (nitromethane 2.5%, diethyl ether 7.5% and diesel 90%) blend was identified as the best fuel blend among all fuel blends and pure diesel. Furthermore, all the considered fuels with different CR at peak load were ranked by the Entropy–TOPSIS method. From the analysis, D–NM2.5–DEE7.5 at CR–19.5 (ranked first with RC i - 0.922231) was found as the best fuel blend among all fuel blends and different compression ratios considered with similar experimental conditions. By the comparison of the best fuel blend (D–NM2.5–DEE7.5 at CR 19.5) with pure diesel (at standard CR 18.5), a significant improvement in engine performance, and reduction in emission and fuel cost was achieved.

Proceedings ArticleDOI
01 Feb 2020
TL;DR: DAB dc-dc converter has been simulated and analyzed in MATLAB Simulink environment as an application ofSolid State Transformer and a single-phase shifting technique (SPS) has been used to minimize the large Dc link capacitor for obtaining a stable output voltage.
Abstract: Solid State Transformer (SST) is a popular device in the present scenario. Power electronics-based SST has many advantages over the conventional transformer likewise; high switching frequency, less weight, low losses. It is a multi-stage transformer composed of different stages of converters likewise; rectifier, inverter and dual active bridge (DAB) for the desired output. It has been evident that stand-alone SST is not able to provide a stable output without any control technique. For SST, the DAB DC-DC converter plays an important role; it provides constant power with a better range at higher efficiency and minimizes the number of passive components. The proposed converter consists of eight semiconductor switches that are isolated through a transformer of high-frequency. In this paper, DAB dc-dc converter has been simulated and analyzed in MATLAB Simulink environment as an application of SST. Here, a single-phase shifting technique (SPS) has been used to minimize the large Dc link capacitor for obtaining a stable output voltage.

Journal ArticleDOI
TL;DR: Performance of presented work has been tested both quantitatively and qualitatively by using different fidelity parameters like; peak signal-to-noise ratio, structural similarity index and normalized correlation coefficient.
Abstract: Need of trusted and highly secured copyright protection techniques to prevent the illegal copying and sharing of digital data are highly required in recent years due to rapid development in internet technology. Here, lossless robust color image watermarking scheme using lifting scheme with grey wolf optimization (GWO) for copyright protection has been proposed. The insertion of color watermark has been done into the host image by changing the singular values of the host/cover image using optimized strength factor; alpha. To increase the security and robustness, scrambling of watermark has also been carried out by using Arnold transform along with GWO optimization technique in the presented work. Performance of presented work has been tested both quantitatively and qualitatively by using different fidelity parameters like; peak signal-to-noise ratio, structural similarity index and normalized correlation coefficient. The presented work has also been tested against various artificial attacks along with comparison with considered image watermarking techniques.

Journal ArticleDOI
TL;DR: In this paper, the Sumudu and Laplace transforms were used to find the solutions of the fractional kinetic equation related with the - Mathieu-type series through the procedure of sumudu.
Abstract: In this paper, our aim is to finding the solutions of the fractional kinetic equation related with the - Mathieu-type series through the procedure of Sumudu and Laplace transforms. The outcomes of fractional kinetic equations in terms of the Mittag-Leffler function are presented.

Journal ArticleDOI
TL;DR: In this study, RSC-MLI configurations have been analysed and Modified selective harmonic elimination technique has been presented to control the magnitude of input DC-link and optimal switching angles.
Abstract: Multilevel inverters (MLIs) have been recognised to generate the voltage for power quality applications. Presently number of topological improvements have been reported in literature. In higher lev...

Journal ArticleDOI
TL;DR: In this article, the displacement and stress analysis and design optimization of the automobile vehicle frontal bumper beam is achieved by designing eight different cross sections with the help of mechanical modeling based software Creo.

Journal ArticleDOI
TL;DR: This work fulfils the literature gap of critical analysis of FPGA implementation of FFA architecture using different multiplier and adder topologies and implements the proposed designs in VHDL.
Abstract: Parallel FIR filter is the prime block of many modern communication application such as MIMO, multi-point transceivers etc. But hardware replication problem of parallel techniques make the system more bulky and costly. Fast FIR algorithm (FFA) gives the best alternative to traditional parallel techniques. In this paper, FFA based FIR structures with different topologies of multiplier and adder are implemented. To optimize design different multiplication technique like add and shift method, Vedic multiplier and booth multiplier are used for computation. Various adders such as carry select adder, carry save adder and Han-Carlson adder are analyzed for improved performance of the FFA structure. The basic objective is to investigate the performance of these designs for the tradeoffs between area, delay and power dissipation. Comparative study is carried out among conventional and different proposed designs. The advantage of presented work is that; based on the constraints, one can select the suitable design for specific application. It also fulfils the literature gap of critical analysis of FPGA implementation of FFA architecture using different multiplier and adder topologies. Xilinx Vivado HLS tool is used to implement the proposed designs in VHDL.

Journal ArticleDOI
01 Jan 2020
TL;DR: To performed enhanced operation of PV cells and maximize the solar energy extraction an incremental conductance based maximum power point tracking scheme is used and selected harmonic elimination based genetic algorithm method is consider for control the gating pulse of PV based RS MLI.
Abstract: Multilevel inverters (MLIs) are developed to meet medium voltage and high power applications in flexible power systems. The conventional configuration of multilevel inverter requires more switches and has limitation to its wide range application. This paper reports the performed work on 1-phase 7-level reduced switch multilevel inverter (RS MLI) in photovoltaic (PV) system. RS MLI configuration integration with PV system which uses less number of switching components for specified number of voltage output levels as compared to that of conventional multilevel inverter topology. To performed enhanced operation of PV cells and maximize the solar energy extraction an incremental conductance based maximum power point tracking scheme is used. To improve the quality of RS MLI output parameters mainly total harmonic distortion and switching losses, selected harmonic elimination based genetic algorithm method is consider for control the gating pulse of PV based RS MLI. This work is performed using MATLAB/SIMULINK software.

Journal ArticleDOI
TL;DR: This paper deals with the analysis and processing aspects of raw data and cleaned data in big data applications and also deals with data cleaning and its implementation concepts.
Abstract: Data analysis and processing is playing an important role because of the large amount of data generated through various sources of big data. It is an important component in big data-based applicati...

Journal ArticleDOI
TL;DR: In this paper, several interesting properties of the incomplete I-functions associated with the Marichev-Saigo-Maeda (MSM) fractional operators are studied and investigated.
Abstract: In this article, several interesting properties of the incomplete I-functions associated with the Marichev–Saigo–Maeda (MSM) fractional operators are studied and investigated. It is presented that the order of the incomplete I-functions increases about the utilization of the above-mentioned operators toward the power multiple of the incomplete I-functions. Further, the Caputo-type MSM fractional order differentiation for the incomplete I-functions is studied and investigated. Saigo, Riemann–Liouville, and Erdelyi–Kober fractional operators are also discussed as specific cases.

Journal ArticleDOI
TL;DR: This paper deals with the data life cycle with different steps and various works are done for data management in different sectors and benefits of the datalife cycle for industrial and healthcare applications including challenges, conclusions, and future scope.

Journal ArticleDOI
TL;DR: In this article, an experimental study for the heat transfer coefficient (HTC) of water-based TiO2 and Al2O3 nanofluids flowing in an annulus has been carried out at 1 bar.
Abstract: A nanofluid is a suspension of nanometer-sized particles in a base fluid. In the last decade, flow boiling of nanofluid has gained much attention. However, only a few correlations on flow boiling are available. In this paper, an experimental study for HTC (heat transfer coefficient) of water-based TiO2 and Al2O3 nanofluids flowing in an annulus has been carried out at 1 bar. The volumetric concentration of the nanofluid was varied from 0.05 to 0.20%, and heat flux and the mass flux were varied from 6.25 to 143.2 kW m−2 and 338 to 1014 kg m−2 s−1, respectively. It was observed that HTC for both the nanofluids was greater than that of the base fluid water, and it increased with increase in the concentration of the nanoparticles, the heat flux and the mass flux. The highest HTC was obtained for Al2O3 nanofluid at 0.20% concentration for the heat flux of 143.2 kW m−2 and mass flux of 1014 kg m−2 s−1. It was found that nanofluid made from Al2O3 nanoparticles had better HTC than nanofluid made from TiO2 nanoparticles. The HTC ratios, i.e., the ratio of HTC of the nanofluid to the HTC of the base fluid, also increased with the increase in concentration, heat flux and mass flux. In the later part of the paper, new correlations were developed for predicting HTC for TiO2 and Al2O3 nanofluids. Finally, an ANN model was developed to predict the heat transfer coefficient. Experimental values were found to be in good agreement with ANN predictions.

Journal ArticleDOI
TL;DR: In this article, the image formulas associated with the fractional calculus operators with Appell function in the kernel and Caputo-type fractional differential operators involving Srivastava polynomials and extended Mittag-Leffler function are established.
Abstract: This article aims to establish certain image formulas associated with the fractional calculus operators with Appell function in the kernel and Caputo-type fractional differential operators involving Srivastava polynomials and extended Mittag-Leffler function. The main outcomes are presented in terms of the extended Wright function. In addition, along with the noted outcomes, the implications are also highlighted.

Journal ArticleDOI
TL;DR: In this paper, a mathematical model is proposed to characterize the anomalous subdiffusion of cytosolic calcium incorporating conformable derivative with respect to the time variable and fractal derivative in terms of the space variable.
Abstract: In the present work, we investigate the calcium signaling in cardiac myocytes. On the basis of the concept of anomalous diffusion, a mathematical model is proposed to characterize the anomalous subdiffusion of cytosolic calcium incorporating conformable derivative with respect to the time variable and fractal derivative with respect to the space variable. Problem has been solved using the Crank-Nicolson finite difference scheme for numerical approximation. The numerical simulation for the solution of the developed model is presented graphically for the various values of the fractal dimension and order of the fractional derivative.

Journal ArticleDOI
TL;DR: In this paper, negative torque reduction and flow augmentation are used to improve the performance of the Savonius turbine, which is a drag-type vertical-axis wind turbine.
Abstract: Savonius turbine is a drag-type vertical axis wind turbine. Negative torque reduction and flow augmentation are common methods which consequently improve its performance. The present research is to...

Journal ArticleDOI
TL;DR: This paper presents a designing of dual-coated miniaturized metamaterial inspired quad band antenna for wireless standards with gain enhancement and shows good agreement between the simulated and measured results.
Abstract: This paper presents a designing of dual-coated miniaturized metamaterial inspired quad band antenna for wireless standards with gain enhancement. Proposed design has compactness in size with electrical dimension of 0.239 × 0.351 × 0.0127 λ (30 × 44 × 1.6 mm3), at lower frequency of 2.39 GHz. The antenna consist a double printed slotted hexagonal shape radiating section with implementation of metamaterial rectangular split ring resonator. Antenna achieve quad bands for wireless standards WLAN (2.4/5.8 GHz), WiMAX (3.5 GHz), IEEE 802.11P (WAVE-5.9 GHz), ITU assigned X bands (7.25–7.75, 7.9–8.4 GHz) and satellite communication systems operating bands (C-band: 7.4–8.9 GHz and X-band: 8–10 GHz for satellite TV). An acceptable gain, stable radiation characteristics and good impedance matching are observed at all the resonant frequencies of the proposed structure. By application of proposed frequency selective surface an average enhancement of gain is about 4–5 dB over the operating band. Antenna fabricated and tested represent good agreement between the simulated and measured results.