Nonlinear modelling has a significant role in different disciplines of sciences such as behavioral,social,physical and biological sciences.The structural properties are also needed for such types of disciplines,as dyn...Nonlinear modelling has a significant role in different disciplines of sciences such as behavioral,social,physical and biological sciences.The structural properties are also needed for such types of disciplines,as dynamical consistency,positivity and boundedness are the major requirements of the models in these fields.One more thing,this type of nonlinear model has no explicit solutions.For the sake of comparison its computation will be done by using different computational techniques.Regrettably,the aforementioned structural properties have not been restored in the existing computational techniques in literature.Therefore,the construction of structural preserving computational techniques are needed.The nonlinearmodel for cervical cancer is constructed by parametric perturbation technique.Well-known computer methods are considered for the computation of cervical cancer dynamics.The well-known existing methods in literature are Euler Maruyama,Euler and Runge Kutta.Nonstandard finite difference method or Implicitly driven explicit method is first time considered for aforesaid model under the assumptions given byMickens in a stochastic way.Unfortunately,the aforementioned existing methods did not reinstate structural properties of cervical cancer dynamics in the human population.Our plannedmethod is structural preserving and a powerful tool for all nonlinear models of biomedical engineering problems.We have verified that existing computational methods do not preserve dynamical properties.But,the implicitly driven explicit method is a good device for dynamical properties.In the support of assertions,convergence analysis of implicitly driven explicit method is presented.展开更多
Since the end of 2019,the world has suffered from a pandemic of the disease called COVID-19.WHO reports show approximately 113M confirmed cases of infection and 2.5 M deaths.All nations are affected by this nightmare ...Since the end of 2019,the world has suffered from a pandemic of the disease called COVID-19.WHO reports show approximately 113M confirmed cases of infection and 2.5 M deaths.All nations are affected by this nightmare that continues to spread.Widespread fear of this pandemic arose not only from the speed of its transmission:a rapidly changing“normal life”became a fear for everyone.Studies have mainly focused on the spread of the virus,which showed a relative decrease in high temperature,low humidity,and other environmental conditions.Therefore,this study targets the effect of weather in considering the spread of the novel coronavirus SARS-CoV-2 for some confirmed cases in Iraq.The eigenspace decomposition technique was used to analyze the effect of weather conditions on the spread of the disease.Our theoretical findings showed that the average number of confirmed COVID-19 cases has cyclic trends related to temperature,humidity,wind speed,and pressure.We supposed that the dynamic spread of COVID-19 exists at a temperature of 130 F.The minimum transmission is at 120 F,while steady behavior occurs at 160 F.On the other hand,during the spread of COVID-19,an increase in the rate of infection was seen at 125%humidity,where the minimum spread was achieved at 200%.Furthermore,wind speed showed the most significant effect on the spread of the virus.The spread decreases with a wind speed of 45 KPH,while an increase in the infectious spread appears at 50 KPH.展开更多
Cloud computing is an Information Technology deployment model established on virtualization.Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment.H...Cloud computing is an Information Technology deployment model established on virtualization.Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment.However,task scheduling challenges such as optimal task scheduling performance solutions,are addressed in cloud computing.First,the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm.This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies,task priorities,and length.Second,a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is proposed to solve the task execution delay problem in DWRR based task scheduling.In the end,a fuzzy logic system is designed for HPSPACO that expands task scheduling in the cloud environment.A fuzzy method is proposed for the inertia weight update of the PSO and pheromone trails update of the PACO.Thus,the proposed Fuzzy Hybrid Particle Swarm Parallel Ant Colony Optimization on cloud computing achieves improved task scheduling by minimizing the execution and waiting time,system throughput,and maximizing resource utilization.展开更多
Physical health plays an important role in overall well-being of the human beings.It is the most observed dimension of health among others such as social,intellectual,emotional,spiritual and environmental dimensions.D...Physical health plays an important role in overall well-being of the human beings.It is the most observed dimension of health among others such as social,intellectual,emotional,spiritual and environmental dimensions.Due to exponential increase in the development of wireless communication techniques,Internet of Things(IoT)has effectively penetrated different aspects of human lives.Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications.IoT can be leveraged through several health service offerings such as remote health and monitoring services,aided living,personalized treatment,and so on.In this scenario,Deep Learning(DL)models are employed in proficient disease diagnosis.The current research work presents a new IoT-based physical health monitoring and management method using optimal Stacked Sparse Denoising Autoencoder(SSDA)technique i.e.,OSSDA.The proposed model utilizes a set of IoT devices to collect the data from patients.Imbalanced class problem poses serious challenges during disease diagnosis process.So,the OSSDA model includes Synthetic Minority Over-Sampling Technique(SMOTE)to generate artificial minority class instances to balance the class distribution.Further,the hyperparameter settings of the OSSDA model exhibit heavy influence upon the classification performance of SSDA technique.The number of hidden layers,sparsity,and noise count are determined by Sailfish Optimizer(SFO).In order to validate the effectiveness and performance of the proposed OSSDA technique,a set of experiments was conducted on diabetes and heart disease datasets.The simulation results portrayed a proficient diagnostic outcome from OSSDA technique over other methods.The proposed method achieved the highest accuracy values i.e.,0.9604 and 0.9548 on the applied heart disease and diabetes datasets respectively.展开更多
DNA tetrahedro n nano structure (DTN) is one of the simplest DNA nano structures and has bee n successfully applied for biose nsin g, imagi ng, and treatment of can cer. To facilitate its biomedical applications and p...DNA tetrahedro n nano structure (DTN) is one of the simplest DNA nano structures and has bee n successfully applied for biose nsin g, imagi ng, and treatment of can cer. To facilitate its biomedical applications and pote ntial clinical tran slation, fun dame ntal un derstandi ng of DTN's transportation among major organs in living organisms becomes increasingly important. Here, we describe the efficient renal clearanee of DTN in healthy mice by using positron emission tomography (PET) imaging. The kidney elimination of DTN was later applied for renal function evaluation in murine models of unilateral ureteral obstruction (UUO). We further established a mathematical program of DTN to validate its changes of transportation pattern in healthy and UUO mice. We believe the establishment of pharmacokinetic profiles and mathematical model of DTN may provide in sight for future optimization of DNA nano structures for biomedical applications.展开更多
The reduced density matrices of a many-body quantum system form a convex set, whose three-dimensional projection is convex in R3. The boundary of may exhibit nontrivial geometry, in particular ruled surfaces. T...The reduced density matrices of a many-body quantum system form a convex set, whose three-dimensional projection is convex in R3. The boundary of may exhibit nontrivial geometry, in particular ruled surfaces. Two physical mechanisms are known for the origins of ruled surfaces： symmetry breaking and gapless. In this work, we study the emergence of ruled surfaces for systems with local Hamiltonians in infinite spatial dimension, where the reduced density matrices are known to be separable as a consequence of the quantum de Finetti＇s theorem. This allows us to identify the reduced density matrix geometry with joint product numerical range II of the Hamiltonian interaction terms. We focus on the case where the interaction terms have certain structures, such that a ruled surface emerges naturally when taking a convex hull of ∏. We show that, a ruled surface on sitting in ∏ has a gapless origin, otherwise it has a symmetry breaking origin. As an example, we demonstrate that a famous ruled surface, known as the oloid, is a possible shape of , with two boundary pieces of symmetry breaking origin separated by two gapless lines.展开更多
In this article, we apply the first elliptic function equation to find a new kind of solutions of nonlinear partial differential equations （PDEs） based on the ho- mogeneous balance method, the Jacobi elliptic expans...In this article, we apply the first elliptic function equation to find a new kind of solutions of nonlinear partial differential equations （PDEs） based on the ho- mogeneous balance method, the Jacobi elliptic expansion method and the auxiliary equation method. New exact solutions to the Jacobi elliptic functions of a nonlinear PDE describing pulse narrowing nonlinear transmission lines are given with the aid of computer program, e.g. Maple or Mathematica. Based on Kirchhoff＇s current law and Kirchhoff＇s voltage law, the given nonlinear PDE has been derived and can be reduced to a nonlinear ordinary differential equation （ODE） using a simple transformation. The given method in this article is straightforward and concise, and can be applied to other nonlinear PDEs in mathematical physics. Further results may be obtained.展开更多
文摘Nonlinear modelling has a significant role in different disciplines of sciences such as behavioral,social,physical and biological sciences.The structural properties are also needed for such types of disciplines,as dynamical consistency,positivity and boundedness are the major requirements of the models in these fields.One more thing,this type of nonlinear model has no explicit solutions.For the sake of comparison its computation will be done by using different computational techniques.Regrettably,the aforementioned structural properties have not been restored in the existing computational techniques in literature.Therefore,the construction of structural preserving computational techniques are needed.The nonlinearmodel for cervical cancer is constructed by parametric perturbation technique.Well-known computer methods are considered for the computation of cervical cancer dynamics.The well-known existing methods in literature are Euler Maruyama,Euler and Runge Kutta.Nonstandard finite difference method or Implicitly driven explicit method is first time considered for aforesaid model under the assumptions given byMickens in a stochastic way.Unfortunately,the aforementioned existing methods did not reinstate structural properties of cervical cancer dynamics in the human population.Our plannedmethod is structural preserving and a powerful tool for all nonlinear models of biomedical engineering problems.We have verified that existing computational methods do not preserve dynamical properties.But,the implicitly driven explicit method is a good device for dynamical properties.In the support of assertions,convergence analysis of implicitly driven explicit method is presented.
文摘Since the end of 2019,the world has suffered from a pandemic of the disease called COVID-19.WHO reports show approximately 113M confirmed cases of infection and 2.5 M deaths.All nations are affected by this nightmare that continues to spread.Widespread fear of this pandemic arose not only from the speed of its transmission:a rapidly changing“normal life”became a fear for everyone.Studies have mainly focused on the spread of the virus,which showed a relative decrease in high temperature,low humidity,and other environmental conditions.Therefore,this study targets the effect of weather in considering the spread of the novel coronavirus SARS-CoV-2 for some confirmed cases in Iraq.The eigenspace decomposition technique was used to analyze the effect of weather conditions on the spread of the disease.Our theoretical findings showed that the average number of confirmed COVID-19 cases has cyclic trends related to temperature,humidity,wind speed,and pressure.We supposed that the dynamic spread of COVID-19 exists at a temperature of 130 F.The minimum transmission is at 120 F,while steady behavior occurs at 160 F.On the other hand,during the spread of COVID-19,an increase in the rate of infection was seen at 125%humidity,where the minimum spread was achieved at 200%.Furthermore,wind speed showed the most significant effect on the spread of the virus.The spread decreases with a wind speed of 45 KPH,while an increase in the infectious spread appears at 50 KPH.
文摘Cloud computing is an Information Technology deployment model established on virtualization.Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment.However,task scheduling challenges such as optimal task scheduling performance solutions,are addressed in cloud computing.First,the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm.This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies,task priorities,and length.Second,a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is proposed to solve the task execution delay problem in DWRR based task scheduling.In the end,a fuzzy logic system is designed for HPSPACO that expands task scheduling in the cloud environment.A fuzzy method is proposed for the inertia weight update of the PSO and pheromone trails update of the PACO.Thus,the proposed Fuzzy Hybrid Particle Swarm Parallel Ant Colony Optimization on cloud computing achieves improved task scheduling by minimizing the execution and waiting time,system throughput,and maximizing resource utilization.
基金This research work was funded by Institution Fund projects under Grant No.(IFPHI-051-130-2020.)Therefore,authors gratefully acknowledge technical and financial support from the Ministry of Education and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘Physical health plays an important role in overall well-being of the human beings.It is the most observed dimension of health among others such as social,intellectual,emotional,spiritual and environmental dimensions.Due to exponential increase in the development of wireless communication techniques,Internet of Things(IoT)has effectively penetrated different aspects of human lives.Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications.IoT can be leveraged through several health service offerings such as remote health and monitoring services,aided living,personalized treatment,and so on.In this scenario,Deep Learning(DL)models are employed in proficient disease diagnosis.The current research work presents a new IoT-based physical health monitoring and management method using optimal Stacked Sparse Denoising Autoencoder(SSDA)technique i.e.,OSSDA.The proposed model utilizes a set of IoT devices to collect the data from patients.Imbalanced class problem poses serious challenges during disease diagnosis process.So,the OSSDA model includes Synthetic Minority Over-Sampling Technique(SMOTE)to generate artificial minority class instances to balance the class distribution.Further,the hyperparameter settings of the OSSDA model exhibit heavy influence upon the classification performance of SSDA technique.The number of hidden layers,sparsity,and noise count are determined by Sailfish Optimizer(SFO).In order to validate the effectiveness and performance of the proposed OSSDA technique,a set of experiments was conducted on diabetes and heart disease datasets.The simulation results portrayed a proficient diagnostic outcome from OSSDA technique over other methods.The proposed method achieved the highest accuracy values i.e.,0.9604 and 0.9548 on the applied heart disease and diabetes datasets respectively.
基金University of Wisconsin-Madison, the National Institutes of Health (NIBIB/NCI P30CA014520, T32CA009206)the American Cancer Society (125246-RSG-13- 099-01-CCE), the National Natural Science Foundation of China (Nos. 51573096, 51703132, 31771036, and 81630049)+2 种基金the Basic Research Program of Shenzhen (Nos. JCYJ20170412111100742 and JCYJ20160422091238319)the Guangdong Province Natural Science Foundation of Major Basic Research and Cultivation Project (No. 2018B030308003)Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China (No. 161032).
文摘DNA tetrahedro n nano structure (DTN) is one of the simplest DNA nano structures and has bee n successfully applied for biose nsin g, imagi ng, and treatment of can cer. To facilitate its biomedical applications and pote ntial clinical tran slation, fun dame ntal un derstandi ng of DTN's transportation among major organs in living organisms becomes increasingly important. Here, we describe the efficient renal clearanee of DTN in healthy mice by using positron emission tomography (PET) imaging. The kidney elimination of DTN was later applied for renal function evaluation in murine models of unilateral ureteral obstruction (UUO). We further established a mathematical program of DTN to validate its changes of transportation pattern in healthy and UUO mice. We believe the establishment of pharmacokinetic profiles and mathematical model of DTN may provide in sight for future optimization of DNA nano structures for biomedical applications.
基金supported by the Natural Sciences and Engineering Research Council of Canada,Canadian Institute for Advanced Research,Perimeter Institute for Theoretical PhysicsResearch at Perimeter Institute was supported by the Government of Canada through Industry Canada and by the Province of Ontario through the Ministry of Economic Development&Innovation
文摘The reduced density matrices of a many-body quantum system form a convex set, whose three-dimensional projection is convex in R3. The boundary of may exhibit nontrivial geometry, in particular ruled surfaces. Two physical mechanisms are known for the origins of ruled surfaces： symmetry breaking and gapless. In this work, we study the emergence of ruled surfaces for systems with local Hamiltonians in infinite spatial dimension, where the reduced density matrices are known to be separable as a consequence of the quantum de Finetti＇s theorem. This allows us to identify the reduced density matrix geometry with joint product numerical range II of the Hamiltonian interaction terms. We focus on the case where the interaction terms have certain structures, such that a ruled surface emerges naturally when taking a convex hull of ∏. We show that, a ruled surface on sitting in ∏ has a gapless origin, otherwise it has a symmetry breaking origin. As an example, we demonstrate that a famous ruled surface, known as the oloid, is a possible shape of , with two boundary pieces of symmetry breaking origin separated by two gapless lines.
文摘In this article, we apply the first elliptic function equation to find a new kind of solutions of nonlinear partial differential equations （PDEs） based on the ho- mogeneous balance method, the Jacobi elliptic expansion method and the auxiliary equation method. New exact solutions to the Jacobi elliptic functions of a nonlinear PDE describing pulse narrowing nonlinear transmission lines are given with the aid of computer program, e.g. Maple or Mathematica. Based on Kirchhoff＇s current law and Kirchhoff＇s voltage law, the given nonlinear PDE has been derived and can be reduced to a nonlinear ordinary differential equation （ODE） using a simple transformation. The given method in this article is straightforward and concise, and can be applied to other nonlinear PDEs in mathematical physics. Further results may be obtained.
