University of Management and Technology (Pakistan)
Recent publications
Background and objective: In this work, a mathematical model based on differential equations is proposed to describe the propagation of polio in a human population. The motivating system is a compartmental nonlinear model which is based on the use of ordinary differential equations and four compartments, namely, susceptible, exposed, infected and vaccinated individuals. Methods: In this manuscript, the mathematical model is extended in order to account for spatial diffusion in one dimension. Nonnegative initial conditions are used, and we impose homogeneous Neumann conditions at the boundary. We determine analytically the disease-free and the endemic equilibria of the system along with the basic reproductive number. Results: We establish thoroughly the nonnegativity and the boundedness of the solutions of this problem, and the stability analysis of the equilibrium solutions is carried out rigorously. In order to confirm the validity of these results, we propose an implicit and linear finite-difference method to approximate the solutions of the continuous model. Conclusions: The numerical model is stable in the sense of von Neumann, it yields consistent approximations to the exact solutions of the differential problem, and that it is capable of preserving unconditionally the positivity of the approximations. For illustration purposes, we provide some computer simulations that confirm some theoretical results derived in the present manuscript.
Background and objective. We present and analyze a nonstandard numerical method to solve an epidemic model with memory that describes the propagation of Ebola-type diseases. The epidemiological system contemplates the presence of sub-populations of susceptible, exposed, infected and recovered individuals, along with nonlinear interactions between the members of those sub-populations. The system possesses disease-free and endemic equilibrium points, whose stability is studied rigorously. Methods. To solve the epidemic model with memory, a nonstandard approach based on Grünwald–Letnikov differences is used to discretize the problem. The discretization is conveniently carried out in order to produce a fully explicit and non-singular scheme. The discrete problem is thus well defined for any set of non-negative initial conditions. Results. The existence and uniqueness of the solutions of the discrete problem for non-negative initial data is thoroughly proved. Moreover, the positivity and the boundedness of the approximations is also theoretically elucidated. Some simulations confirm the validity of these theoretical results. Moreover, the simulations prove that the computational model is capable of preserving the equilibria of the system (both the disease-free and the endemic equilibria) as well as the stability of those points. Conclusions. Both theoretical and numerical results establish that the computational method proposed in this work is capable of preserving distinctive features of an epidemiological model with memory for the propagation of Ebola-type diseases. Among the main characteristics of the numerical integrator, the existence and the uniqueness of solutions, the preservation of both positivity and boundedness, the preservation of the equilibrium points and their stabilities as well as the easiness to implement it computationally are the most important features of the approach proposed in this manuscript.
Nowadays, heart disease is the leading cause of death. The high mortality rate and escalating occurrence of heart diseases worldwide warrant the requirement for a fast and efficient diagnosis of such ailments. The purpose is to design an automated system for the classification of abnormal heartbeat audio signals to assist cardiologists. To the best of our knowledge, this is the first study that uses a single neural network model for the classification of eight different types of heartbeat audio signals. The proposed recurrent neural network (RNN) model using Long short-term memory (LSTM) is developed on two publically available databases such as the PASCAL challenge and the 2017 PhysioNet challenge. Mel frequency cepstrum coefficient (MFCC) is applied to extract the dominant features, and a bandpass filter is used to remove the noise from both of the datasets. Afterward, the downsampling technique is used to fix the size of the sampling rate of each sound signal to 20KHz and 300 Hz for the Pascal and PhysioNet database, respectively. The proposed model is compared with multi-layer perceptron (MLP) in terms of different performance evaluation matrices. Furthermore, the outcomes of five machine learning (ML) models are also analyzed. The proposed model has achieved the highest classification accuracy of 0.9971 on the Pascal database, and 0.9870 accuracy on the PhysioNet challenge dataset, which is consistently superior to its competitor approaches. The proposed model provides significant assistance to the cardiac consultant in detecting heart valve diseases.
Double perovskites Rb2TlInX6 (X = Cl, I) have been simulated with the help of density functional theory to determine their structural, elastic, electronic, optical and thermal properties. The full-potential linearized augmented plane wave (FP-LAPW) method is used through the WIEN2K code. Exchange-correlation potential is described by using the well-organized modified Becke-Johnson (mBJ) with the combination of spin-orbit coupling (SOC). Structural optimization and formation energy calculations justify the stability of both compounds. The elastic parameters are calculated to measure the mechanical stuff, such as shear modulus (G), Poisson ratio (ν) and anisotropic factor (A). The studied compounds showing semiconductor nature with a bandgap of 3.51eV and 3.47eV for Rb2TlInCl6 and 1.43eV and 1.40eV for Rb2TlInI6 with mBJ and mBJ+SOC potentials, respectively. The density of states also exposes the bandgap and semiconductor nature of the materials. The optical properties of the compounds have been examined in terms of the dielectric function, refractive index, absorption, reflection, and energy loss. We also investigated the temperature-dependent transport parameters for both compounds. High electrical and low thermal conductivity with good ZT values for both materials make them potential candidates for thermoelectric applications.
Textile wastewater is ranked highly contaminated among all industrial waste. During textile processing, the consumption of dyes and complex chemicals at various stages makes textile industrial wastewater highly challenging. Therefore, conventional processes based on single-unit treatment may not be sufficient to comply with the environmental quality discharge standards and more stringent guidelines for zero discharge of hazardous chemicals (ZDHC). In this study, a novel approach was followed by recycling Poly aluminum chloride (PACl) and Alum as a catalyst for the first time in the catalytic ozonation treatment process leading to a nascent method after using them as a coagulant in Coagulation/Flocculation. In the current investigation, six different combinations were studied to remove turbidity, TSS, COD, BOD5, color, and biodegradability (BOD5/COD ratios) of wastewater. Moreover, Central Composite Design was implied using RSM in Minitab software. During the combination of treatment processes, it was found that the pre-coagulation/flocculation with coagulant PACl followed by post-catalytic ozonation with recycled PACl, a more effective treatment than others. The optimum R.E of turbidity, TSS, COD, and color were 84%, 86%, 89%, and 98%, respectively. Moreover, a decrease in toxicity and increase in biodegradability (BOD5/COD ratio from 0.29 to 0.54) was observed as well. The electrical energy demand and operational costs of treatment processes were estimated and compared with other treatment processes.
The enhancement of thermal conductivity of base fluids is desirable with the inclusion of nano-entities and bioconvection of microorganisms. The influence of the multi-slips on magnetohydrodynamic bio-convection streamline of micropolar based nanofluid across a sponge medium owing to expanding sheet is investigated in this work. The mass transpiration and activation energy with Fourier-Fick diffusion is taken into account. The leading partial differential equations are transformed into ordinary differential equations by using similarity transformations. The graphs were created by using the RK-4th order method with the shooting technique. Nusselt number, Sherwood number, skin friction factor, and motile density function are enumerated and analyzed with the variance of influenced parameters. It is observed the magnitude of the skin friction factor is enhanced with higher inputs of magnetic field and porosity parameters. Also observed that fluid speed is higher for injection than that of suction.
In this work, we use generalized form of Caputo-type fractional derivative and Riemann–Liouville fractional Integral which is known as Katugampola fractional derivative. This work deals with some results having applications of Katugampola fractional derivative. We discuss commutative and inverse property of Katugampola fractional derivative. We have also introduced Chebyshev inequalities and some other integrals inequalities applying the Katugampola fractional derivative.
Reusing the waste materials generated from demolishing existing infrastructures can play a vital role in minimizing their detrimental environmental impacts. A substantial portion of the total construction waste comprises brick wastes (B-waste). It has already been established that recycled aggregate concrete (RAC) fabricated using recycled clay brick aggregates (CBA) lacks adequate compressive strength and corresponding strain. This limits the application of RAC-CBA to mainly non-load-bearing works. External strengthening of RAC using fiber reinforced polymer (FRP) sheets has been found beneficial in terms of the improvement in ultimate compressive strength and ultimate strain. With massive costs associated with synthetic FRP sheets, this study proposes the use of Fiberglass Chopped Strand Mat (FCSM) sheets as a low-cost alternative to synthetic FRP sheets to improve compressive strength and behavior of RAC-CBA. To accomplish this, RAC was constructed with three different waste brick aggregates, mainly hollow-clay, solid-clay, and hydraulic cement-clay interlocking bricks. Typical cylinders of size 150 mm in diameter × 300 mm in height were cast and strengthened using 2, 4, and 6 layers of FCSM sheets. It was found that FCSM sheets successfully enhanced the ultimate compressive strength and strain of RAC-CBA irrespective of the type of constituting brick aggregates. Further, a correlation in the improvement of axial compressive behavior was found with the number of external FCSM sheets. The accuracy of existing ultimate strength-strain models was assessed in predicting the experimental ultimate stress and strain. In general, none of the existing models exhibited a consistent trend in predicting the axial behavior of RAC-CBA. Hence, the ultimate stress–strain models were proposed.
The intelligent manufacturing system (IMS) is a framework that improves productivity by organizing the logical features involved in manufacturing. The procedure of intelligent manufacturing owns the capability to self-control the manufacturing of the products according to the specifications of design. Different IMSs are designed to deal with continuous changes in market which can adjust to make the modified environment easier. The central idea of this research article is to select an IMS that can adapt the updated situations faster than the existing competing systems and provide higher benefits in utilizing new possibilities. To select such IMS, the applicability of multiobjective optimization on the basis of the ratio analysis (MOORA) method has been explored using Fermatean fuzzy sets. The Fermatean fuzzy aggregated weighted operators are used to construct the decision matrices. Then, the ratio analysis-based MOORA method is developed to accomplish the ranking of under consideration IMSs. Furthermore, the conversion of qualitative attributes into quantitative attributes has been performed using Fermatean fuzzy numbers (FFNs). Finally, a brief comparative analysis of the developed technique with existing models is narrated to reveal the flexibility of the Fermatean fuzzy MOORA method.
The significance of nanoparticle aggregation, Lorentz and Coriolis forces on the dynamics of spinning silver nanofluid flow past a continuously stretched surface is prime significance in modern technology, material sciences, electronics, and heat exchangers. To improve nanoparticles stability, the gyrotactic microorganisms is consider to maintain the stability and avoid possible sedimentation. The goal of this report is to propose a model of nanoparticles aggregation characteristics, which is responsible to effectively state the nanofluid viscosity and thermal conductivity. The implementation of the similarity transforQ1m to a mathematical model relying on normal conservation principles yields a related set of partial differential equations. A well-known computational scheme the FEM is employed to resolve the partial equations implemented in MATLAB. It is seen that when the effect of nanoparticles aggregation is considered, the temperature distribution is enhanced because of aggregation, but the magnitude of velocities is lower. Thus, showing the significance impact of aggregates as well as demonstrating themselves as helpful theoretical tool in future bioengineering and industrial applications.
In this article, we acquire a variety of new exact traveling wave solutions in the form of trigonometric, hyperbolic, and rational functions for the nonlinear time-fractional Clannish Random Walker’s Parabolic (CRWP) equation in the sense of beta-derivative by employing the two modified methods, namely, modified G ′ / G 2 − expansion method and modified F − expansion method. The obtained solutions are verified for aforesaid equations through symbolic soft computations. To promote the essential propagated features, some investigated solutions are exhibited in the form of 2D and 3D graphics by passing on the precise values to the parameters under the constrain conditions. The obtained solutions show that the presented methods are effective, straight forward, and reliable as compared to other methods. These methods can also be used to extract the novel exact traveling wave solutions for solving any types of integer and fractional differential equations arising in mathematical physics.
In this paper, a brushless wound rotor vernier machine (Bl-WRVM) with a single inverter configuration is proposed to achieve the brushless operation. In the proposed topology, a single inverter is connected with series-connected ABC and XYZ windings through which the current flow produces the magnetomotive force with fundamental and sub-harmonic components, respectively. The XYZ windings have similar pole pairs to the excitation windings, whereas its number of poles is different from the ABC winding. A 24-slot stator, 4-pole armature ABC winding, 2 Pole armature XYZ and excitation windings, and 44-pole field winding for the outer rotor is designed and 2D finite element analysis is carried out to determine the performance of the machine. The proposed topology makes the Bl-WRVM cost-effective by applying only a single inverter as compared to a dual-inverter Bl-WRVM and it improves its torque quality.
This study aimed to analyze anthropometrics and mechanomyography (MMG) signals as forearm flexion, pronation, and supination torque predictors. 25 young, healthy, male participants performed isometric forearm flexion, pronation, and supination tasks from 20 to 100% maximal voluntary isometric contraction (MVIC) while maintaining 90° at the elbow joint. Nine anthropometric measures were recorded, and MMG signals from the biceps brachii (BB), brachialis (BRA), and brachioradialis (BRD) muscles were digitally acquired using triaxial accelerometers. These were then correlated with torque values. Significant positive correlations were found for arm circumference (CA) and MMG root mean square (RMS) values with flexion torque. Flexion torque might be predicted using CA (r = 0.426–0.575), a pseudo for muscle size while MMGRMS (r = 0.441), an indication of muscle activation.
The concept of locating number for a connected network contributes an important role in computer networking, loran and sonar models, integer programming and formation of chemical structures. In particular it is used in robot navigation to control the orientation and position of robot in a network, where the places of navigating agents can be replaced with the vertices of a network. In this note, we have studied the latest invariant of locating number known as local fractional locating number of an antiprism based convex polytope networks. Furthermore, it is also proved that these convex polytope networks posses boundedness under local fractional locating number.
In the present work, we introduce two novel root-finding algorithms for nonlinear scalar equations. Among these algorithms, the second one is optimal according to Kung-Traub’s conjecture. It is established that the newly proposed algorithms bear the fourth- and sixth-order of convergence. To show the effectiveness of the suggested methods, we provide several real-life problems associated with engineering sciences. These problems have been solved through the suggested methods, and their numerical results proved the superiority of these methods over the other ones. Finally, we study the dynamics of the proposed methods using polynomiographs created with the help of a computer program using six cubic-degree polynomials and then give a detailed graphical comparison with similar existing methods which shows the supremacy of the presented iteration schemes with respect to convergence speed and other dynamical aspects.
In this paper, we establish the concept of controlled neutrosophic metric-like spaces as a generalization of neutrosophic metric spaces and provide several non-trivial examples to show the spuriousness of the new concept in the existing literature. Furthermore, we prove several fixed point results for contraction mappings and provide the examples with their graphs to show the validity of the results. At the end of the manuscript, we establish an application to integral equations, in which we use the main result to find the solution of the integral equation.
Knitted fleece fabrics with superior comfort characteristics are chiefly focused in winter wear. Thermal characteristics are an area of interest in selecting fleece clothing. However, environmental hazards also need to be focused. Fleece clothing is worn in cold areas having higher ultraviolet rays exposures. Hence the clothing should have the capability of combating environmental challenges. The study focuses on engineering variable fleece structures with different materials. Cotton, nylon, and polypropylene fleece patterns have been knitted using fleece 1:1, 3:1, and 2:2 patterns. The designs vary by tuck and miss stitch configurations in the fleece course. Comfort characteristics were determined through air permeability, moisture management, and thermal resistance tests. Performance criteria were evaluated in terms of pilling resistance and ultraviolet protection factor (UPF) investigation. Structures and materials owing better comfort characteristics with satisfactory UPF have been predicted as safe clothing in UV affected zones, that is, fleece 3:1 possessed the optimum comfort characteristics and UPF simultaneously; however, the mechanical performance was better for 2:1 and 1:1 fleece fabric due to less amount of miss stitch floating yarns.
In this study, we put forward the dual Maclaurin symmetric mean (DMSM) and the Maclaurin symmetric mean (MSM) operators with the context of the probabilistic dual hesitant fuzzy set (PDHFS), which can address the issues in previous probabilistic dual hesitant fuzzy aggregation operators. Some novel operators based on MSM and DMSM for aggregating PDHF information are prepared, followed by several properties and special cases. Namely, the PDHFMSM, weighted PDHFMSM (WPDHFMSM), PDHFDMSM, weighted PDHFDMSM (WPDHFDMSM) operators. Furthermore, some necessary characteristics and exceptional cases concerning different parametric values of these operators are discussed. Additionally, two new methods based on the WPDHFMSM and WPDHFDMSM operators have been developed with the help of COPRAS technique to deal with multi-attribute group decision-making problems. Lastly, the validity and effectiveness of the intended methods are demonstrated through a case study on selecting the best photovoltaic cells.
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6,409 members
Muhammad Sohail Afzal
  • Department of Life Sciences
Mudassar Abbas
  • School of Textile and Design (STD)
Tabasam Rashid
  • Department of Mathematics
Agha Kashif Arshad Khan
  • Department of Mathematics
Rana Zamin Abbas
  • School of Professional Advancement (SPA)
C-II Johar Town, 54000, Lahore, Punjab, Pakistan
Head of institution
Dr. Hassan Sohaib Murad
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