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Numerical approach to generalized coupled fractional Ramani equations
The main goal of this study is to find solutions for the generalized coupled Ramani equation with the fractional order using the fractional natural decomposition method (FNDM). Four distinct cases are chosen to illustrate and validate the effectiveness of the considered method. The simulations in terms of numeric have been illustrated to confirm the reliability and proficiency of the projected scheme. Moreover, the behavior of the obtained results is captured for distinct fractional order. The comparison study is illustrated to verify the accuracy of the projected procedure. The achieved results exemplify that the projected solution procedure offers a simple algorithm and is also very efficient to analyze the nature of the coupled differential equations with arbitrary order situated in associated areas of Science and Engineering. 2022 World Scientific Publishing Company. -
Numerical and sensitivity analysis of MHD bioconvective slip flow of nanomaterial with binary chemical reaction and Newtonian heating
The impact of Stefan blowing on the MHD bioconvective slip flow of a nanofluid towards a sheet is explored using numerical and statistical tools. The governing partial differential equations are nondimensionalized and converted to similarity equations using apposite transformations. These transformed equations are solved using the RungeKuttaFehlberg method with the shooting technique. Graphical visualizations are used to scrutinize the effect of the controlling parameters on the flow profiles, skin friction coefficient, local Nusselt, and Sherwood number. Moreover, the sensitivities of the reduced Sherwood and Nusselt number to the input variables of interest are explored by adopting the response surface methodology. The outcomes of the limiting cases are emphatically in corroboration with the outcomes from preceding research. It is found that the heat transfer rate has a positive sensitivity towardsthe haphazard motion of the nanoparticles and a negative sensitivity towardsthe thermomigration. The thermal field is enhanced by the Stefan blowing aspect. Moreover, the fluid velocity can be controlled by the applied magnetic field. 2021 Wiley Periodicals LLC -
Numerical analysis and finite element simulation of axial stiffness of overhead transmission line conductor
Cables, overhead electrical conductors, and ropes are flexible structural assemblies made out of a central core and number of wires which are twisted together to form a complex helical structure. In the majority, cables are subjected to axial loading primarily, followed by the associated twisting. Depending upon the application, they are additionally loaded in bending also. The mechanical behavior of the cables can be predicted by various mathematical models reported in the literature. The mathematical model can predict the overall global behavior of the cable well. However, the local behavior of the cable must be included to have intricate realistic studies. In this paper, an attempt is made to predict the response of the cable considering all the local effects under axial loading. A core with a single layer of six wires is modelled using the helical rod concept and its mechanical behavior is investigated by means of Finite Element Analysis (FEA). The effect of axial loading on the cable is proposed to be studied as a function of various cable axial strains. The core-wire and the wire-wire contact mode of the cable assembly have been considered with due consideration of the contact forces and the associated frictional effects. The reduction in cable stiffness has been studied under various slip modes. The analytical and FEA results are validated with experimental tests on a single-layered transmission line conductor. TJPRC Pvt. Ltd. -
Nudges and choice architecture in public policy: A bibliometric analysis
In recent years, nudges and choice architecture have gained significant attention amongst researchers, particularly in the domain of public policymaking. This study contributes to the existing literature on the application of nudges and choice architecture in public policy through a bibliometric analysis. A total of 419 documents from the Web of Science database from 2010 to 2021 were analysed, identifying the most prolific authors, foundational works, and sources, along with primary research themes. The study identifies keywords and themes that shape the current research trends and visualizes the intellectual structure of empirical works. The findings show an increasing focus on this subject area over the past decade, with a growing interest in themes such as dietary habits, healthcare, effectiveness of behavioral interventions, and sustainable choices. The application of nudges and choice architecture in policies related to health, food consumption, and diet management has also become increasingly prevalent as evidenced by the exponential growth in publications on these topics. 2023 Elsevier Inc. -
NSS-ML: a Novel spectrum sensing framework using machine learning for cognitive radio IoT networks
A key component of cognitive radio systems is spectrum sensing, which reduces coexistence problems and maximises spectrum efficiency. However, the introduction of multiple situations with distinct characteristics brought about by 5G communication presents problems for spectrum sensing to support a wide range of applications with high performance and flexible implementation. Inspired by these difficulties, a new method with a multi-layer extreme learning machine optimised for bats is presented in this study. This technique makes use of a variety of input vectors, such as channel ID, energy, distance, and received signal intensity, to enhance user categorization and sensing capabilities. Moreover, we compare the proposed method with the state-of-the-art spectrum sensing approaches in order to evaluate its effectiveness in 5G situations, especially in healthcare applications. Evaluation metrics including channel detection probability, sensitivity, and selectivity are carefully examined. The findings unequivocally prove the suggested spectrum sensing approachs superiority over current methods and highlight its potential for smooth incorporation into a variety of 5G applications. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Novel task assignment policies using enhanced hyper-heuristic approach in cloud
Cloud computing plays a vital role in all fields of todays business. The processor sharing server farm is one of the most used server farms in the cloud environment. The key challenge for the mentioned server farms is to provide an optimal scheduling policy to process the computational jobs in the cloud. Many scheduling policies were introduced and deployed by the existing approaches to build an optimal cloud environment. The existing approaches of the heuristic algorithms such as meta-heuristic and hyper-heuristic approaches were the most frequently used scheduling algorithms for the past years. These approaches work well only in the limited types of tasks and resources in a processor sharing server farms in the cloud environment. In the proposed system, novel task assignment policies have been proposed by enhancing the hyper-heuristic approach for the type low task and high resource in the cloud environment. The results of the proposed approach are compared with the existing approaches and the performance evaluation of the proposed approach is also done. As a result, the proposed enhanced hyper-heuristic approach performs well for processor sharing server farms in the cloud environment. Copyright 2023 Inderscience Enterprises Ltd. -
Novel system for mental health state analysis using machine learning and methods thereof /
Patent Number: 202041044754, Applicant: Prof.Santosh Kumar J.
Systems and methods are provided to understand mental health state of an individual by audio sensors, video sensors and log data of mobile devices. To get more accurate and reliable data machine learning module is also integrated with three input forms of data provided to the system. Once any abnormality is observed, it is reported to the caretakers with a coping strategy to solve the illness at initial stages. -
Novel system for mental health state analysis using machine learning and methods thereof /
Patent Number: 202041044754, Applicant: Prof.Santosh Kumar J.
Systems and methods are provided to understand mental health state of an individual by audio sensors, video sensors and log data of mobile devices. To get more accurate and reliable data machine learning module is also integrated with three input forms of data provided to the system. Once any abnormality is observed, it is reported to the caretakers with a coping strategy to solve the illness at initial stages. -
Novel synthesis and dft calculations of 3-PHENYL-2-(1H-TETRAZOL-5-YL)acrylamdes under catalyst-free, one-pot cascade reaction /
Patent Number: 202141023459, Applicant: Jyothis Devasia.
The present invention offers a novel method for the synthesis of 3-phenyl-2-(1H-tetrazol-5-yl)acrylamides 4(a-g) under catalyst-free conditions. All the reactions were carried out in an one-pot cascade process starting with various aromatic/heteroaryl aldehydes, 2-cyanoacetamide and sodium azide at 110 oC using dimethylformamide (DMF) as a solvent. In addition, the reaction conditions were screened for optimization conditions towards solvent, catalyst, temperature and equivalence of sodium azide. -
Novel super stack passivation in AlGaN/GaN HEMT for power electronic applications
A super-stack passivation technique is proposed for an AlGaN/GaN HEMT in order to improve the breakdown voltage and cutoff frequency. The performance of the proposed technique is benchmarked against a conventional GaN HEMT. The analysis and investigation are carried out using Technology Computer-Aided Design (TCAD). The simulation results are validated with experimental data. It is observed that the breakdown voltage of the conventional and proposed devices is 356V and 449V, respectively. In contrast to the conventional device, the breakdown voltage of the proposed device is improved by 21%. This is the manifestation of the suppression of the electric field by the super-stack passivation technique in the proposed device. Furthermore, it is also observed that the Johnsons figure of merit in the proposed GaN-HEMT is also improved. 2024 The Author(s). Published by IOP Publishing Ltd. -
Novel splitring resonator antennas for biomedical application
Our paper presents the design and development of split ring resonator based metamaterial antenna for biomedical i.e., Industrial, Scientific and Medical(ISM-2.45GHz) applications and also used in biosensors. Now a day the biological changes in the human body such as glucose content in blood, heart rate, respiratory rate, brain tumor are monitored by the use of wireless body area networks. In such networks the main part of the system is antenna with compactness and wider bandwidth. We have designed gain enhanced and wide bandwidth antennas with size reduction of more than 95% compared to the conventional patch antenna. The design methodology is based on Metamaterial which is an emerging technology uses split ring resonators for size reduction. We have designed double square split ring shape superstrate antenna and circular ring resonator antenna with stub for 2.48GHz. Also they have better return loss (>12dB). Our antennas are fed with microstrip feeding and Coplanar Waveguide (CPW) feeding for better impedance matching and easy fabrication. The fabricated antennas are tested using Network analyzer. The measured results are good in agreement with simulated results. 2015, Journal of Pure and Applied Microbiology. All rights reserved. -
Novel soliton solutions of four sets of generalized (2+1)-dimensional Boussinesq-Kadomtsev-Petviashvili-like equations
In this paper, we examined four different forms of generalized (2+1)-dimensional Boussinesq-Kadomtsev-Petviashvili (B-KP)-like equations. In this connection, an accurate computational method based on the Riccati equation called sub-equation method and its Bklund transformation is employed. Using this method, numerous exact solutions that do not exist in the literature have been obtained in the form of trigonometric, hyperbolic, and rational. These solutions are of considerable importance in applied sciences, coastal, and ocean engineering, where the B-KP-like equations modeled for some significant physical phenomenon. The graph of the bright and dark solitons is presented in order to demonstrate the influence of different physical parameters on the solutions. All of the findings prove the stability, effectiveness, and accuracy of the proposed method. 2022 World Scientific Publishing Company. -
Novel quantum inspired approaches for automatic clustering of gray level images using Particle Swarm Optimization, Spider Monkey Optimization and Ageist Spider Monkey Optimization algorithms
This paper is intended to identify the optimal number of clusters automatically from an image dataset using some quantum behaved nature inspired meta-heuristic algorithms. Due to the lack of sufficient information, it is difficult to identify the appropriate number of clusters from a dataset, which has enthused the researchers to solve the problem of automatic clustering and to open up a new era of cluster analysis with the help of several natures inspired meta-heuristic algorithms. In this paper, three quantum inspired meta-heuristic techniques, viz., Quantum Inspired Particle Swarm Optimization (QIPSO), Quantum Inspired Spider Monkey Optimization (QISMO) and Quantum Inspired Ageist Spider Monkey Optimization (QIASMO), have been proposed. A comparison has been outlined between the quantum inspired algorithms with their corresponding classical counterparts. The efficiency of the quantum inspired algorithms has been established over their corresponding classical counterparts with regards to fitness, mean, standard deviation, standard errors of fitness, convergence curves (for benchmarked mathematical functions) and computational time. Finally, the results of two statistical superiority tests, viz., t- test and Friedman test have been provided to prove the superiority of the proposed methods. The superiority of the proposed methods has been established on five publicly available real life image datasets, five Berkeley image datasets of different dimensions and four benchmark mathematical functions both visually and quantitatively. 2019 Elsevier B.V. -
Novel PAPR Reduction in UFMC system for 5G Wireless Networks Using Precoding Algorithm
The Universal Filtered Multi-carrier (UFMC) system is promising alternative multicarrier modulation scheme for fifth generation (5G) cellular networks. UFMC systems offer many advantages such as larger spectral efficiency, robustness, lower latency and minimizing out of band emission. However, the most serious problem in the UFMC system is high peak to average power ratio (PAPR). This high peak signal is seriously harmed by the high power amplifier (HPA). Therefore, this research presents a novel Square Root raised Cosine function (SRC)-Precoding method introduced to reduction of PAPR. A performance analysis of various methods being examined upon in terms of CCDF of PAPR and the BER. The Simulation result shows that the proposed approach can effectively reduce the PAPR 6dB compared to standard UFMC. Moreover, the bit error rate (BER) study of the UFMC model indicates that the proposed approach significantly improves 15 dB compared with conventional UFMC systems. 2022 IEEE. -
Novel magnetic nanocomposites and their environmental applications
Environmental contamination by numerous emerging pollutants including pharmaceuticals, microplastics, and pesticides residues is one of the greatest problems facing the world today. The release of these pollutants into the air, water, and soil causes serious threat to plants and animals. These contaminants enter the food chain through contaminated agricultural produce and animals, posing a threat to human health. Therefore, there is an urgent need to develop novel methods to detect, degrade, and remove toxic environmental pollutants. Recently, nanomaterials have been widely used in various applications as catalysts, sensors, and adsorbents due to their unique outstanding properties. This chapter, therefore, focuses on the recent application of magnetic nanoparticles and their respective nanocomposites as degradation catalysts, adsorbents, and electrochemical sensors for detection and removal of environmental pollutants. 2024 Elsevier Ltd. All rights reserved. -
Novel hybrid metamaterial to improve the performance of a beamforming antenna
This paper investigates the design and implementation of a novel hybrid metamaterial unit cell to improve a beamforming Wi-Fi antenna's performance. The proposed metamaterial unit cell is created on an FR-4 substrate (?? = 4.4) and a thickness of 1.6 mm. The metallization height of the unit cell is maintained at 0.035 mm. The designed metamaterial unit cell is simulated using HFSS Ver. 18.2 to verify the double negative behaviour. The unit cell consists of five Split Ring Resonators (SRR's) at the bottom and a hexagonal ring of six triangles. Initially, a conventional inset fed microstrip patch antenna is designed then an array of the proposed unit cell is created and used as a superstrate to study the performance. A Three Element Antenna Array (TEAA) is designed to operate at 2.4 GHz Wi-Fi band, and the superstrate created out of the proposed unit cell is used to study its effect. Metamaterial superstrate improved the conventional Single Element Antenna (SEA) gain by approximately 2 dB. Superstrate with TEAA exhibited an improved gain of 1 dB over TEAA. Published under licence by IOP Publishing Ltd. -
Novel HGDBO: A Hybrid Genetic and Dung Beetle Optimization Algorithm for Microarray Gene Selection and Efficient Cancer Classification; [Nuevo HGDBO: Un Algoritmo Hrido de Optimizaci Genica y de Escarabajos Peloteros para la Selecci de Genes en Microrrays y la Clasificaci Eficiente del Ccer]
Introduction: ovarian cancer ranked as the seventh most common cancer and the eighth leading cause of cancer-related mortality among women globally. Early detection was crucial for improving survival rates, emphasizing the need for better screening techniques and increased awareness. Microarray gene data, containing numerous genes across multiple samples, presented both opportunities and challenges in understanding gene functions and disease pathways. This research focused on reducing feature selection time in large gene expression datasets by applying a hybrid bio-inspired method, HGDBO. The goal was to enhance classification accuracy by optimizing gene subsets for improved gene expression analysis. Method: the study introduced a novel hybrid feature selection method called HGDBO, which combined the Dung Beetle Optimization (DBO) algorithm with the Genetic Algorithm (GA) to improve microarray data analysis. The HGDBO method leveraged the exploratory strengths of DBO and the exploitative capabilities of GA to identify relevant genes for disease classification. Experiments conducted on multiple microarray datasets showed that the hybrid approach offered superior classification performance, stability, and computational efficiency compared to traditional methods. Ovarian cancer classification was performed using Nae Bayes (NB) and Random Forest (RF) algorithms. Results and Discussion: the Random Forest model outperformed the Nae Bayes model across all metrics, achieving higher accuracy (0,96 vs. 0,91), precision (0,95 vs. 0,91), recall (0,97 vs. 0,90), F1 score (0,95 vs. 0,91), and specificity (0,97 vs. 0,86). Conclusions: these results demonstrated the effectiveness of the HGDBO method and the Random Forest classifier in improving the analysis and classification of ovarian cancer using microarray gene data. 2024; Los autores. -
Novel heterocyclic thiosemicarbazones derivatives as colorimetric and "turn on" fluorescent sensors for fluoride anion sensing employing hydrogen bonding
(Chemical Equation Presented) Two novel heterocyclic thiosemicarbazone derivatives have been synthesized, and characterized, by means of spectroscopic and single crystal X-ray diffraction methods. Their chromophoric-fluorogenic response towards anions in competing solvent dimethyl sulfoxide (DMSO) was studied. The receptor shows selective recognition towards fluoride anion. The binding affinity of the receptors with fluoride anion was calculated using UV-visible and fluorescence spectroscopic techniques. 2013 Elsevier B.V. All rights reserved. -
Novel electrochemical biosensor key significance of smart intelligence (IoMT & IoHT) of COVID-19 virus control management
Recent outbreak of COVID-19 pandemic has led to the different possibilities of the development of treatment against corona virus. To know the phylogenicity of SARS-CoV, various studies have been conducted with the outcome of the results showing virulence is caused due to spike protein. Various detection techniques with clinical approach like imaging technology, RT-PCR etc. are comparatively expensively than the use of biosensors. Nano-biosensors have an excellent way of approach to track the conditions of individual and public providing information about the existing condition and treatment status. Electrochemical nano-biosensors are referred as an excellent way of detection. The use of graphene based electrochemical nano-biosensors are most advantageous due to its elevated properties. Fluorescence investigation is one of the precise ways of sensing, optical biosignals that helps in obtaining real time results with high accuracy and negligible changes. The potential application of nano-biosensors are very wide, improvised and advanced Nanotechnology helps in the use of nano-biosensors detect all possible biosignals. Significant ubiquitous IoT-enabled novel sensor technologies that can be potentially utilized to respond various facets the growing COVID-19 pandemic from diagnostic and therapeutics to the prevention stage. 2022 Elsevier Ltd -
Novel dioxidomolybdenum complexes containing ONO chelators: Synthesis, physicochemical properties, crystal structures, Hirshfeld surface analysis, DNA binding/cleavage studies, docking, and in vitro cytotoxicity
A series of dioxidomolybdenum (VI) complexes, [MoO2(ESB)H2O]DMF (1), [MoO2(ESB)MeOH] (2), and [MoO2(ESB)H2O]EtOH (3), containing 3-ethoxysalicylaldehyde benzoylhydrazone have been synthesized and analysed using various spectral and analytical techniques such as elemental analyses, IR spectra, UVVis absorption spectra, X-ray crystallography, and Hirshfeld surface analysis. Based on the elemental and spectral analysis, six-coordinate geometry was assigned for these complexes wherein the hydrazone ligand binds to the metal centre in its dianionic enolate form through ONO donor set. Distorted octahedral geometry of complexes 1 and 2 was evidenced from their crystal structures, which is typical for many cis-dioxido complexes of MoVI. The proligand and the new complexes were examined for their DNA binding, DNA cleavage, and cytotoxic properties. The DNA binding efficiency of the compounds in terms of their binding constants (Kb) of the metal complexes was observed to be 1.3727 105 M?1, 3.0194 104 M?1, and 1.13206 104 M?1 for [MoO2(ESB)H2O]DMF (1), [MoO2(ESB)MeOH] (2), and [MoO2(ESB)H2O]EtOH (3), respectively, indicating that these complexes strongly bind to DNA. To determine the binding interactions of the complexes with DNA and protein (BSA), molecular docking studies were carried out. Gel electrophoresis study reveals the fact that the complexes cleaved supercoiled pUC-18 DNA to nicked form (Form II) in the presence and absence of H2O2. The complexes showed significantly high cytotoxicity against MCF-7 (breast cancer cells). 2021 John Wiley & Sons, Ltd.