Browsing by Author "Cieza Altamirano, Gilder"

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A Cloud-Based Machine Learning Approach to Reduce Noise in ECG Arrhythmias for Smart Healthcare Services.
(Hindawi Limited, 2022-01) Jain, Paras; F. Alsanie, Walaa Fahad; Oseda Gago, Dulio; Cieza Altamirano, Gilder; Sandoval Núñez, Rafaél Artidoro; Rizwan, A.; Asakipaam, Simon Atuah
ECG (electrocardiogram) identi es and traces targets and is commonly employed in cardiac disease detection. It is necessary for monitoring precise target trajectories. Estimations of ECG are nonlinear as the parameters TDEs (time delays) and Doppler shifts are computed on receipt of echoes where EKFs (extended Kalman thlters) and electrocardiogram have not been examined for computations. ECG, certain times, results in poor accuracies and low SNRs (signal-to-noise ratios), especially while encountering complicated environments. This work proposes to track online lter performances while using optimization techniques to enhance outcomes with the removal of noise in the signal. The use of cost functions can assist state corrections while lowering costs. A new parameter is optimized using IMCEHOs (Improved Mutation Chaotic Elephant Herding Optimizations) by linearly approximating system nonlinearity where multiiterative function (Optimized Iterative UKFs) predicts a target’s unknown parameters. To obtain optimal solutions theoretically, multiiterative function takes less iteration, resulting in shorter execution times. De proposed multiiterative function provides numerical approximations, which are derivative-free implementations. Signals are updated in the cloud environment; the updates are received by the patients from home. The simulation evaluation results with estimators show better performances in terms of reduced NMSEs (normalized mean square errors), RMSEs (root mean squared errors), SNRs, variances, and better accuracies than current approaches. Machine learning algorithms have been used to predict the stages of heart disease, which is updated to the patient in the cloud environment. The proposed work has a 91.0% accuracy rate with an error rate of 0.05% by reducing noise levels.
Aggregation-Based Dynamic Channel Bonding to Maximise the Performance of Wireless Local Area Networks (WLAN)
(Hindawi Limited, 2022-06) Parashar, Vivek; Kashyap, Ramgopal; Rizwan, A.; Karras, Dimitrios Alexios; Cieza Altamirano, Gilder; Dixit, Ekta; Ahmadi, Fardin
Channel bonding is considered by the IEEE 802.11ac amendment to improve wireless local area network (WLAN) performance. In this article, the channel bonding and aggregation method were proposed to increase wireless local area network performance (WLANs). It combines many channels (or lanes) to boost the capacity of modem traffic. Channel bonding is the combination of two neighbouring channels within a certain frequency band to increase wireless device throughput. Wi-Fi employs channel bonding, also known as Ethernet bonding. Channel bandwidth is equal to the uplink/downlink ratio multiplied by the operational capacity. A single 20 MHz channel is divided into two, four, or eight power channels. At 80 MHz, there are more main and smaller channels. Performance of short-range WLANs is determined through graph-based approach. The twochannel access techniques including channel bonding proposed for the IEEE 802.11ac amendment are analysed and contrasted. The novel channel sizing algorithm based on starvation threshold is proposed to expand the channel size to improve WLAN performance. Second-cycle throughput is estimated at 20 Mbps, much beyond the starvation threshold. Our test reveals access points (AP) 1, 2, and 4 have enough throughput. A four-AP WLAN with a 5-Mbps starvation threshold is presented. C160 = 1 since there is only one 160 MHz channel. MIR (3, 160 (a, a, a)) =0, indicating that AP 3’s predicted throughput is 0. The algorithm rejects the 160 MHz channel width since ST is larger than 0. The channel width in MHz is given by B =0,1 MIR. The MIR was intended to maximise simultaneous broadcasts in WLANs. The authors claim that aggregation with channel bonding outperforms so all WLAN APs should have a single-channel width. It usually outperforms fairness-based measures by 15% to 20%. Wi-Fi standards advise “channel bonding,” or using higher frequency channels. Later standards allow channel bonding by increasing bands and channel lengths. Wider channels enhance average WLAN AP throughput, but narrower channels reduce appetite. Finally, it is concluded that APs are more useful than STAs.
An Internet of Things (IoT) Based Block Chain Technology to Enhance the Quality of Supply Chain Management (SCM)
(Hindawi Limited, 2022-07) Rizwan, A.; Karras, Dimitrios Alexios; Mohan Kumar, Jitendra K.; Sánchez-Chero, Manuel Jesus; Mogollón Taboada, Marlon Martin; Cieza Altamirano, Gilder
Recent technological developments indicate possible advancements in supply chain management (SCM). ese innovations have attracted a lot of interest from industries including logistics, manufacturing, packaging, and transportation. e conventional systems, however, use centralised servers to control all operations, including the exchange of raw materials, making orders, dealing with buyers and sellers, and updating orders. e network’s supply chain may thus be insecure as a result of every activity being routed via centralised servers. e danger is additionally increased by a number of di culties, including scalability, data integrity, security, and availability. Block chain technology may be used in these circumstances to decentralise transaction processing and eliminate the need for a centralised controller. In this approach, the performance of the resource-constrained supply chain network is improved by the e ective use of edge computing and priority data access. e Intelligent K-Means (IKM) clustering algorithm is suggested across the edge nodes in the current research to categorise the priority level of each piece of data. is classi er determines if the edge node has received data that is high priority or low priority. Low priority data is recorded in the log les for future data analysis. en, to allow safe data ow in the open block chain while excluding outside parties, the High Priority Access based Smart Contract (HPASC) technique is deployed. e whole experiment was conducted in a Python environment, and variables including scalability, reaction time, throughput, and accuracy were studied. Current systems’ constrained block sizes and fork creation lengthen the time transactions must wait before being processed. e suggested methodology is quicker and uses less storage space than current block chain systems. e results show that the suggested approach works better than current blockchain technology to raise the standard of supply chain management.
Analytical Solution to the Generalized Complex Duffing Equation.
(Hindawi Limited, 2022-11) Salas S., Alvaro H.; Cieza Altamirano, Gilder; Martínez H, Lorenzo J.
Future scientifc and technological evolution in many areas of applied mathematics and modern physics will necessarily depend on dealing with complex systems. Such systems are complex in both their composition and behavior, namely, dealing with complex dynamical systems using diferent types of Dufng equations, such as real Dufng equations and complex Dufng equations. In this paper, we derive an analytical solution to a complex Dufng equation. We extend the Krylov–Bogoli´ubov–Mitropolsky method for solving a coupled system of nonlinear oscillators and apply it to solve a generalized form of a complex Dufng equation.
Artificial intelligent investigations for the dynamics of the bone transformation mathematical model.
(Elsevier, 2022-10) Cholamjiak, Watcharaporn; Sabir, Zulqurnain; Zahoor Raja, Muhammad Asif; Sánchez-Chero, Manuel Jesus; Oseda Gago, Dulio; Sánchez-Chero, José Antonio; Seminario-Morales, Maria Veronica; Oseda Gago, Marco Antonio; Agurto Cherre, Cesar Augusto; Cieza Altamirano, Gilder
In this study, the stochastic numerical solutions of the fractional myeloma bone disease system (FMBDS) have been presented. The fractional order investigation provides more accurate solutions of the FMBDS. The FMBDS is classified into three dynamics and the solution of each class is presented by using the artificial neural network enhanced by the scale conjugate gradient procedures (ANN-SCGPs). Three different fractional order performances have been used to present the solutions of the FMBDS by applying the ANN-SCGPs. The statics is chosen as 11%, 12% and 77% for training, testing and verification. Twelve number of hidden neurons with input and output layers have been proposed for the FMBDS. The comparison of proposed and reference solutions is performed that shows the accuracy of the ANN-SCGPs. The consistency, validity, precision, and capability of the ANN-SCGPs can be judged based on the state transitions values, regression actions, correlation behaviors, error histograms, and mean square error data.
Case study of autocatalysis reactions on tetra hybrid binary nanofluid flow via Riga wedge: Biofuel thermal application.
(Elsevier, 2023-05) Sajid, Tanveer; Gari, Abdullatif Abdulhadi; Jamshed, Wasim; Eid, Mohamed R.; Abdulhafiz, Nazrul Islam; Irshad, Kashif; Cieza Altamirano, Gilder; M Tag El Din, El Sayed
Ethanol and biodiesel, which both belong to the first generation of biofuel technology, are the two most popular forms of biofuels now in use. In order to create next-generation biofuels using waste, cellulosic biomass, and algae-based resources, the Bioenergy Technologies Office (BETO) is working with business. The present article is designed to study the effect of tetra hybrid nanoparticles with the utilization of the novel Hamilton and Crosser model and catalytic reaction on binary fluid with the consideration of ethanol biofuel as a base fluid. Ethanol comprising tetra hybrid nanoparticles and heterogeneous catalytic reaction amplifies thermal conductivity and significantly increases brake thermal efficiency and reduces brake-specific fuel consumption in diesel engines. Therefore, the aim of this article is a theoretical checkup that is related to heat and mass transport of biofuel flow considering binary fluid accompanied with autocatalysis reaction and novel tetra hybrid nanoparticles on biofluid flow subjected to a Riga wedge. Transportation of heat via nonuniform heat source/sink, thermal radiation, and thermal conductivity are in our consideration. The mathematics of the assumed problem generates the system of non-linear partial differential equations from basic equations of momentum, energy, and mass. The usage of non-dimensional variables gave a system of non-linear ODEs with boundary conditions which are further dealt with in the Lobatto111A scheme. The results are obtained for stretching/shrinking wedge with several parameters. From obtained results, it is observed that the velocity field diminishes owing to magnification in Weissenberg number and Casson fluid parameter. The temperature field diminishes by amplifying heat generation, thermal radiation, and variable thermal conductivity parameter. Concentration distribution escalates by rising homogeneous reaction parameters.
Catalysis reaction influence on 3D tetra hybrid nanofluid flow via oil rig solar panel sheet: Case study towards oil extraction.
(Elsevier, 2023-07) Sajid, Tanveer; Jamshed, Wasim; Algarni, Salem A.; Alqahtani, Talal; Mohamed R. Eid; Irshad, Kashif; Cieza Altamirano, Gilder; M Tag El Din, El Sayed; Nahar Tajer, Khadiga Wadi
The power that comes from renewable sources is made back faster than it is used. Infinitely renewable examples include solar and wind energy. There are many sources of clean energy all around us. Motive behind current study: A framework has now been developed throughout this research to investigate the impact of the sun’s rays on novel Xue tetra hybrid magnetized cross nano-liquid as it moves through an expanding sheet inside that PV sheet of a solar module installed on top of such an offshore solar oil field. A novel Xue tetra hybrid nanofluid model has been developed and utilized to explore the impact of tetrahybrid nanoparticles on liquid flowing in order to investigate heat transport analysis. By directing the liquid’s motion through a magnetic field, we may examine its velocity impact. The concentration aspect of nanofluid has been examined by including homogeneous and heterogeneous chemical processes, and indeed, the temperature accessibility of cross-nanofluid is obtained by taking into consideration effects like thermal conductivity and thermal radiation. Technique: The PDEs derived from the working prototype are then subjected to the resemblance factors, yielding the ODEs. The bvp4c scheme is used to get numerical results. The procedure is an ODE solver that belongs to the Runge-Kutta family. In order to provide precise answers in the fourth and fifth orders, it performs six function evaluations. The discrepancy between them is therefore interpreted as the solution’s (fourth-order) inaccuracy. Adaptive stepsize integration techniques greatly benefit from this error estimation. Fehlberg’s (RKF) integration strategy is quite similar to Cash and Carp technique. Significant finding: From obtained results, it is detected that the addition of novel tetrahybrid nanoparticles in the conventional liquid (Xue tetrahybrid nanofluid) enhances heat transfer rate and temperature profile more quickly in contrast to conventional ternary hybrid nanofluid and dihybrid nanofluid available in the existing literature. The thing which makes the present work novel and one step ahead in contrast to existing available literature is the development and implementation of a tetrahybrid nanofluid model in contrast to conventional ternary hybrid and dihybrid nanofluid models. Tetra m hybridity nanoliquid generates extra heat in distinction to already existing ternary hybridity and dihybrid nanofluid models and more heat is absorbed by PV sheets in the existence of tetrahybrid nanoparticles. Conclusions: When the nanomaterials are submerged inside this liquid, their temperature increases throughout both the shear thinning and shear thickening cases. This is because the homogeneous chemical reaction mimics the migration of nanoparticles within the liquid. The increased magnetic force, in addition to an enhancement of Lorentz’s force, slows down the nanofluid motion. The increased volume percentage of tetrahybrid nanoparticles, thermal radiation, and thermal conductivity boost the heat that’s captured by a PV sheet, and that heat is utilized for other functions, such as drilling or navigation, on that solar offshore rig. Cost analysis: Cost analysis has also been presented in terms of Pakistan offshore oil rigs in terms of solar panels and diesel generators and it is observed that 49% cost is reduced if we replaced offshore oil rigs with solar-powered energy.
Conocimiento sobre el consumo de ácido fólico en gestantes atendidas en el Centro de Salud Paccha, Chota – 2024.
(Universidad Nacional Autónoma de Chota, 2024-03-21) Herrera Tapia, Ana; Rivera Fernandez, Clever Enrique; Tenorio Carranza, Jorge Romain; Cieza Altamirano, Gilder
La investigación tuvo como objetivo describir el nivel de conocimiento sobre el consumo de ácido fólico en gestantes atendidas en el Centro de Salud Paccha, Chota 2024. Estudio descriptivo, observacional y trasversal. La muestra fueron 36 gestantes. La técnica una encuesta y el instrumento un cuestionario sobre el conocimiento del consumo de ácido fólico. Resultados: Las características sociodemográficas más frecuentes fueron que, 88,9% eran casadas o convivientes, 77,8% amas de casa, 44,4% tenían educación primaria y 41,7% entre 18 y 29 años. El mayor conocimiento se presentó en el 100% de gestantes que respondieron correctamente a preguntas como ¿Qué es ácido fólico? y ¿Dónde se brinda información correcta sobre suplementación?; mientras que se registró 83,3% en la pregunta ¿Al consumir ácido fólico, qué enfermedades o complicaciones se puede prevenir en el bebé?; y 80,6% en ¿Qué tipo de alimentos, además del suplemento que recibe en el Puesto de Salud se puede encontrar el ácido fólico? Por otro lado, se observó un desconocimiento del 66,7% en cuanto a ¿En qué momento se recomienda finalizar el consumo de ácido fólico?, un 63,9% en ¿Por qué es importante el consumo de ácido fólico?, y 52,8% en ¿Cuál es el momento ideal para iniciar el consumo de ácido fólico? En la dimensión consumo de ácido fólico 50% presentaron conocimiento medio, 27,8% medio y 22,2% alto; en la dimensión complicaciones al no consumir ácido fólico, 38,9% conocimiento bajo, 33,3% medio y 27,8% alto; mientras que en el conocimiento global 50% conocimiento medio, 36,1% bajo y 13,9% alto. Conclusión: El conocimiento sobre ácido fólico es mayormente de nivel medio.
Cubic Chemical Autocatalysis and Oblique Magneto Dipole Effectiveness on Cross Nanofluid Flow via a Symmetric Stretchable Wedge.
(MDPI, 2023-05) Mohd Nasir, Nor Ain Azeany; Sajid, Tanveer; Jamshed, Wasim; Cieza Altamirano, Gilder; Eid, Mohamed R.; Abdel Aziz ElSeabee, Fayza
Exploration related to chemical processes in nanomaterial flows contains astonishing features. Nanoparticles have unique physical and chemical properties, so they are continuously used in almost every field of nanotechnology and nanoscience. The motive behind this article is to investigate the Cross nanofluid model along with its chemical processes via auto catalysts, inclined magnetic field phenomena, heat generation, Brownian movement, and thermophoresis phenomena over a symmetric shrinking (stretching) wedge. The transport of heat via nonuniform heat sources/sinks, the impact of thermophoretic diffusion, and Brownian motion are considered. The Buongiorno nanofluid model is used to investigate the impact of nanofluids on fluid flow. Modeled PDEs are transformed into ODEs by utilizing similarity variables and handling dimensionless ODEs numerically with the adoption of MATLAB’s developed bvp4c technique. This software performs a finite difference method that uses the collocation method with a three-stage LobattoIIIA strategy. Obtained outcomes are strictly for the case of a symmetric wedge. The velocity field lessens due to amplification in the magneto field variable. Fluid temperature is amplified through the enhancement of Brownian diffusion and the concentration field improves under magnification in a homogeneous reaction effect.
Dynamics of Fractional Differential Model for Schistosomiasis Disease.
(Tech Science Press, 2022-03) Botmart, Thongchai; Weera, Wajaree; Zahoor Raja, Muhammad Asif; Sabir, Zulqurnain; Hiader, Qusain; Cieza Altamirano, Gilder; Muro Solano, Plinio Junior; Tesén Arroyo, Alfonso
In the present study, a design of a fractional order mathematical model is presented based on the schistosomiasis disease. To observe more accurate performances of the results, the use of fractional order derivatives in the mathematical model is introduce based on the schistosomiasis disease is executed. The preliminary design of the fractional order mathematical model focused on schistosomiasis disease is classified as follows: uninfected with schistosomiasis, infected with schistosomiasis, recovered from infection, susceptible snail unafflicted with schistosomiasis disease and susceptible snail afflicted with this disease. The solutions to the proposed system of the fractional order mathematical model will be presented using stochastic artificial neural network (ANN) techniques in conjunction with the LevenbergMarquardt backpropagation (LMBP), referred to as ANN-LMBP. To illustrate the preciseness of the ANN-LMBP method, mathematical presentations of three different values focused on fractional order will be performed. These statics performances are taken in these investigations are 78% and 11% for both learning and certification. The accuracy of the ANN-LMBP method is determined by comparing the values obtained by the database Adams-Bash forth-Moulton scheme. The simulation-based error histograms (EHs), MSE, recurrence, and state transitions (STs) will be offered to achieve the capability,m accuracy, steadiness, abilities, and finesse of the ANN-LMBP method.
Endo/exothermic chemical processes influences of tri-hybridity nanofluids flowing over wedge with convective boundary constraints and activation energy.
(Elsevier, 2023-06) Sajid, Tanveer; Al Mesfer, Mohammed Khaloofah Mola; Jamshed, Wasim; Eid, Mohamed R.; Danish, Mohammad; Irshad, Kashif; Ibrahim, Rabha W.; Batool, Sawera; M Tag El Din, El Sayed; Cieza Altamirano, Gilder
Prandtl Eyring fluid and stretchable wedge have multiple usages in many industries. The present study aims to investigate the impact of modified Buongiorno trihybrid nanofluid on Prandtl Eyring fluid past a wedge with the addition of various influences like endothermic/exothermic reactions, thermal radiation, and thermal conductivity, Cattaneo-Christov double diffusion. Aluminium alloys (AA7072), Aluminium alloys (AA7075) and Silver (Ag) are used as nanocomponents. Prandtl Eyring fluid is employed as a conventional liquid in the preparation of nanofluids by blending nano components into the base fluid. Further, the flow model is imposed with Modified Buongiorno nanofluid. By using the similarity approach, the proposed mathematical flow model of partial differential equations (PDEs) is turned into highly nonlinear ordinary differential equations (ODEs). Throughout the whole range of material parameters, the solution for the ensuing nonlinear boundary value issue is given by employing the finite element method (FEM). The numerical results of Prandtl Eyring ternary HNF motion, thermal and solute profiles are performed through graphical amassment on the collected data and discussed in detail. The numerical significances of material sections, such as the frictional force, local Nusselt quantity, and local Sherwood number requirements, are supplied in tabular form. Further, it also presents the validation and performance characteristics of the proposed device with previously published work and found excellent accuracy. In comparison to hybrid nanoparticles, the consequences reveal that heat transmission is amplified in the case of tri-hybrid nanoparticles. The numerical consequences show that the heat transfer amount reduces in the situation of exothermic reactions parameter Ω < 1 and rises due to magnification in the status of endothermic reactions parameter Ω > 1.
Nivel de estrés en gestantes atendidas en el Centro de Salud Virgen del Carmen Bambamarca, 2024.
(Universidad Nacional Autónoma de Chota, 2025-02-03) Blanco Llamo, José Luis; Vásquez Idrogo, Edey Magna; Tenorio Carranza, Jorge Romain; Cieza Altamirano, Gilder
El objetivo del estudio fue contrastar el nivel de estrés en gestantes atendidas en el Centro de Salud Virgen del Carmen, Bambamarca 2024. Estudio de enfoque cuantitativo, nivel descriptivo, diseño no experimental trasversal, realizado con 78 gestantes; se utilizó como técnica una encuesta y como instrumento un cuestionario de recolección de datos. Resultados: las características sociodemográficas predominantes fueron: el 26,9% están entre 15 - 20 años, el 79,5% son convivientes, el 26,9% tienen secundaria completa, el 83,3% son ama de casa, el 43,6% se encuentran en el III trimestre de embarazo. Respecto al nivel de estrés el 82,1% presentan estrés moderado y el 17,9% severo; en la dimensión fisiológica el 89,7 % presenta estrés moderado, 9,0% severo y el 1,3% leve; mientras que en la dimensión psicológica el 76,9% presenta estrés moderado y el 23,1% severo. Se concluye que el nivel de estrés en las gestantes atendidas en el Centro de Salud Virgen del Carmen Bambamarca, es diferente al nivel de estrés en gestantes del Hospital de Chota por tener un p-valor significativo (p = 0,000).
Solution to a Damped Duffing Equation Using He's Frequency Approach
(Hindawi Limited, 2022-07) Salas S., Alvaro H.; Cieza Altamirano, Gilder; Sánchez-Chero, Manuel Jesus
In this paper, we generalize He’s frequency approach for solving the damped Du ng equation by introducing a time varying amplitude. We also solve this equation by means of the homotopy method and the Lindstedt–Poincar´e method. High accurate formulas for approximating the Jacobi elliptic function cn are formally derived using Chebyshev and Pade approximation techniques.
Spectral Relaxation Methodology for Chemical and Bioconvection Processes for Cross Nanofluid Flowing around an Oblique Cylinder with a Slanted Magnetic Field Effect.
(Multidisciplinary Digital Publishing Institute, 2022-10) Rasool, Ghulam; Hussain Shah, Syed Zahir; Sajid, Tanveer; Jamshed, Wasim; Cieza Altamirano, Gilder; Keswani, Bright; Sandoval Núñez, Rafaél Artidoro; Sánchez-Chero, Manuel Jesus
The current investigation explains the chemical reaction and bioconvection process for an inclined magnetized Cross nanofluid over an inclined cylinder using a spectral relaxation approach. Additionally, the facts concerning swimming gyrotactic microorganisms, non-uniform thermal conductivity, and variable decrease or increase in heat sources are taken together. Each profile is checked for inclined and orthogonal magnetic impact. Appropriate transformations made for conversion of nonlinear PDEs into systems of ODEs. For obtaining numerical results, a spectral relaxation approach is utilized, and graphs are plotted with each physical parameter attached. It is well established that the temperature field intensifies owing to an amplification of thermal conduction and Brownian diffusivity phenomena. The heat transfer rate amplifies owing to a magnification in magnetic parameter and thermal conductivity, but the velocity field diminishes as a result of magnification in the Weissenberg number and power law index. Amplification in the reaction rate constant parameter diminishes the concentration field. Activation energy is the key factor responsible for magnification in the concentration field. Furthermore, smooth agreement is found during comparison with the existing literature. Statistical analysis is also conducted for physical quantities.
Stochastic Computational Heuristic for the Fractional Biological Model Based on Leptospirosis.
(Tech Science Press, 2022-10) Sabir, Zulqurnain; Sánchez-Chero, Manuel Jesus; Zahoor Raja, Muhammad Asif; Cieza Altamirano, Gilder; Seminario-Morales, Maria Veronica; Fernández Vásquez, José Arquímedes; Purihuamán Leonardo, Celso Nazario; Thongchai Botmart; Wajaree Weera
The purpose of these investigations is to find the numerical outcomes of the fractional kind of biological system based on Leptospirosis by exploiting the strength of artificial neural networks aided by scale conjugate gradient, called ANNs-SCG. The fractional derivatives have been applied to get more reliable performances of the system. The mathematical form of the biological Leptospirosis system is divided into five categories, and the numerical performances of each model class will be provided by using the ANNs-SCG. The exactness of the ANNs-SCG is performed using the comparison of the reference and obtained results. The reference solutions have been obtained by using the Adams numerical scheme. For these investigations, the data selection is performed at 82% for training, while the statics for both testing and authentication is selected as 9%. The procedures based on the,recurrence, mean square error, error histograms, regression, state transitions, and correlation will be accomplished to validate the fitness, accuracy, and reliability of the ANNs-SCG scheme.
Swarming Computational Techniques for the Influenza Disease System
(Tech Science Press, 2022-05) Noinang, Sakda; Sabir, Zulqurnain; Cieza Altamirano, Gilder; Zahoor Raja, Muhammad Asif; Sánchez-Chero, Manuel Jesus; Seminario-Morales, Maria Veronica; Weera, Wajaree; Botmart, Thongchai
Abstract: The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using the differential form of each class of the IDS and then optimized by the PSOIPA. The correctness and accuracy of the scheme are observed to perform the comparative analysis of the obtained IDS results with the Adams solutions (reference solutions). An absolute error in suitable measures shows the precision of the proposed ANNs procedures and the optimization efficiency of the PSOIPA. Furthermore, the reliability and competence of the proposed computing method are enhanced through the statistical performances
Thermal case classification of solar-powered cars for binary tetra hybridity nanofluid using Cash and Carp method with Hamilton-Crosser model.
(Elsevier, 2023-06) Sajid, Tanveer; Jamshed, Wasim; Katbar, Nek Muhammad; Eid, Mohamed R.; Abd-Elmonem, Assmaa; Abdalla, Nesreen Sirelkhtam Elmki; M Tag El Din, El Sayed; Cieza Altamirano, Gilder
Solar energy is the most important source of thermal energy that comes from the sun. This kind of energy has enormous potential applications in fields of technology such as photovoltaic panels, renewable power, solar light poles, and solar pumps used for water extraction. The era in which we are living is all about the applications of solar energy in industrial sectors most importantly in solar sports car manufacturing. This article presents a new way of thinking about the heat transport analyses of photovoltaic hybrid vehicles, by factoring Casson-Sutterby liquid with the inclusion of various effects like variable thermal conduction, thermal radiation, heat generation, and tetrahybrid nanoparticles. To solve the modelled equations in regards to both momentum and energy, another well-computational approach known as the Cash and Carp method was used. The effects of a wide variety of factors on temperature, shear stress, and velocity fields, as well as the surface drag coefficient and Nusselt number, are briefly described and illustrated in the form of tables and figures. It then found that the thermal radiation, heat production, and thermal conductivity parameters and insertion of agglomerative tetrhybrid nanoparticles in the base fluid amplify heat transfer rate, it has been shown that the performance of the solar car increases in terms of heat transition. In comparison to standard nanofluid, tetrahybrid nanofluid is the most effective medium for the transmission of heat. From the regression analysis, it is observed that the error in terms of Nusselt number is smaller 0.0151 for the case ε = 1.5, and increases to 0.0151 in the case of ε = 2.5. Relative percentage error is smaller 4.62% in the case of heat generation Q= 0.7 but a maximum of 15.8% in the case of thermal radiation Rd = 2.
Thermal transport and characterized flow of trihybridity Tiwari and Das Sisko nanofluid via a stenosis artery: A case study.
(Elsevier, 2023-05) Fangfang, Fu; Sajid, Tanveer; Jamshed, Wasim; Eid, Mohamed R.; Cieza Altamirano, Gilder; Altaf, Imran; Abd-Elmonem, Assmaa; M Tag El Din, El Sayed
The improvement of heat transfer is the focus of this paper’s innovative theoretical ternary hybridity nanofluid (HNF) prototype. In this examination, blood is employed as the conventional liquid, and the tri-hybrid nanomolecules Au, Ag, and TiO2 are submerged in it. The extension has been made in the conventional Tiwari and Das hybrid nanofluid model to transform it for the case of a trihybrid nanofluid. By consuming resemblance variables and the Keller box methodology (KBM) to resolve the ordinary differential equations (ODEs) resulting from the conversion of the liquid flowing and temperature formulas. The results are graphed, and it is shown that the trihybridity nanofluid (THNF) has greater thermal conductance than the HNF. The heat transference rate increases in the situation of an augmentation in thermal conduction and radiation effect which helps remove the toxic plaque from the blood flowing through arteries. This additional heat produced because of amplification in thermal radiative fluxing is used to open rigid arteries through which the blood is flow.
Time for a New Player in Business Analytics: An MCDM Scheme Based on One-Dimensional Uncertain Linguistic Interval-Valued Neutrosophic Fuzzy Data.
(University of New Mexico, 2023-12) Darvesh, Adil; Naeem, Khalid; Bukhari, Syeda Mifzalah; Sánchez-Chero, Manuel Jesus; Cieza Altamirano, Gilder; Sandoval Núñez, Rafaél Artidoro; Pozo-Suclupe, Luis Antonio; Coronado Zuloeta, Iván Pedro
Abstract: Pooling the opinions of the decision makers about premier alternative from a list of given choices is the most crucial phenomenon theory of decision making. The MSM operator is an effective approach and can identify the collective connection among various input viewpoints. So, tacking the fully benefit of MSM operator, this paper presents a new novel in depth investigation of MSM in context of Neutrosophic fuzzy variables. Initially we developed the structure of One-dimension uncertain linguistic interval valued neutrosophic fuzzy variables, deliberate their fundamental properties along with meaningful laws. Moreover, we encompass the MSM operator to the extent of one dimensional uncertain-linguistic Neutrosophic fuzzy variables and introduced some novel aggregations operators including one-dimensional uncertain linguistic interval-valued Neutrosophic fuzzy, weighted fuzzy and ordered weighted fuzzy McLaurin symmetric mean operator. The practical utilization of the proposed aggregation operators in business analytic are also included in the paper. In last comparison is made between current vs old studies which proved solidity and reliability of the new operator’s vs existing operators in the literature.