Here we present the univariate quantitative approximation of Banach space valued continuous functions on a compact interval or all the real line by quasi-interpolation Banach space valued neural network operators. We perform also the related Banach space valued fractional approximation.
Herein, we continue to summarise a set of fundamental results of various random polynomials including orthogonal polynomials.Also we outline how Kac-Rice formula is generalised in various dimensions.This paper contains the second part of survey of selected results on the real/complex zeros of random polynomials and asymptotic results of expected number of zeros of random polynomials in higher dimensions.Expected number of zeros of random orthogonal polynomials is methodologically presented to initiate further research.
An epidemic disease caused by coronavirus has spread all over the world with a strong contagion rate.We implement an SIR model to study the evolution of the infected population and the number of infected recovered and dead because of this epidemic in South Carolina consistent with available data.We perform an analysis of the results of the model by varying the parameters and initial conditions, in particular transmission and recovery rates.We use data covering the period December 1, 2020, to June 1, 2021.The models and results are consistent with the observations.The models developed using data help us understand the recovery rates.The infection and recovery increasing in South Carolina do not show improvement.The number of dead people tends to increase although by small amount.Models were developed based on the available data.Initially neural networks and machine learning methodology were used to come up with transmission rates.Later, direct calculation and optimal control methodology were used to deduce transmission parameters.For the period December to June there were no available data on recovered populations and we have to determine them as well as transmission and recovery rates based on data of infected populations and dead population using neural networks and optimal control methodologies where transmission, recovery, relapsation immunity and death rates from infection are considered as decision variables.From the data from CDC we see that the number of infected population is increasing.We have also data for the number of dead population due to the virus.Our models are consistent with the data we have available for the infected and dead population.However, there were no data for recovered population in South Carolina for the entire period December 1 to June 1.We have to use our model to come up with recovered population number.One thing we observe is that the number of infected population was increasing.One of the control measures that are believed to be reliable methods of curbing the spread of the virus is quarantine.We include a model that includes quarantine in our work.In our quarantine we see that if 100,000 susceptible people in the whole state were quarantined there would have been a considerable decrease in the number of infected population.
Recently, store and retrieve data in the cloud architecture is an attractive cloud computing research.In addition to these, the utilization of economic resources and security of data transmission by the company, additional constraints such as Google, Microsoft, Yahoo, IBM and Amazon in various internet services.Data and structure management is the biggest concern of cloud computing strategy, as they evolved into custody, and provide new service mode via the Internet.Cloud service provider (CSP), the owner To calculate the data of the resource pool, it is the main component of containing clouds.Maintenance of the data center of a large movement with the CSP application software.Cloud service, down scale-up, and has easy access performance.Consumers, the cloud computing model, you must have the integrity to ensure the confidentiality, privacy, availability and data access management.Cloud computing is promising as had been efficient, there are many challenges, because the user does not know the location of the data, there was a data security.Address security software industry is an important factor in cloud data processing applications.Therefore, this study focused create cloud security and vulnerability level constraint data transfer mode.In cloud computing, data maintenance CSP is thus used for data storage security and trust is dependent on third-party suppliers authorized person.The rise of password encryption and decryption mechanisms to ensure the privacy of cloud data protection deposition.An important process before the encryption mechanism is to understand the security, storage and data access vulnerability levels.Niubi The purpose of this article is to provide security and privacy challenges of analyzing significant cloud computing and create policy challenges derived from observation.Encryption and decryption mechanisms to cloud computing model provides a number of enhanced security attributes involved in lead-based encryption (ABE)
Cloud data security needs have become an ongoing issue that needs to be addressed urgently.The data encryption cloud is a valuable tool to ensure data security.The existing proxy server system allows many users to perform search operations to find the problem time lag and encryption of data that is not overflowing with cloud storage.Many researchers have been inspired by this work under the single data owner system and the multi-owner data system.As Protected Data Encryption Algorithm (PDEA), this algorithm is used to store data in a database provided by a single cloud service provider and cloud server to conduct data access with no actual data volume.Use simple data recovery and access procedures.Cloud storage, for companies to store data locally during this process.PDEA stores prefer active cloud storage services to lower prices and use a large amount of data to store.Cloud computing is based on rapid development and builds a secure search code from information recovery.Therefore, dual outsourcing of data in the cloud is cheaper, minimizing long-term storage and maintenance complexity.There are data integrity, reliability, security, and minimum guarantees available on the cloud server.
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As vehicle self-organizing networks (in VANETs) know, this has to be an essential area of research in recent years.As the most advanced VANET in this country, this research will introduce the issue of relationship.Reliable transport protocols are offered based on arbitrary unicast routes.The method with route optimization request response is minimized to control the overhead of the proposed contract-the fall detection system.A task is to predict the energy from the nodes of the data transmission path to the near-robust destination and use the algorithmic process traffic detection and avoidance to improve packet transmission.Crash Detection Defect-Free Algorithm (CDFA) Consumption Cost is not a data metric that achieves communication speed.The route optimization request-response method is minimized to control the overhead of the proposed protocol.Fast routing protocols use the fast dynamic communication algorithm (FDCA), which is intended to guarantee multi-hop wireless links between sources and destinations.At the peer node, use a multi-hop routing method for the urgent forwarding of data packets to the recipient.To avoid hitting the Fast Dynamic Obstacle Detection Algorithm (FDFDA), the long delay of the vehicle is due to unknown traffic conditions or the possibility of traffic congestion.This method has proven to be very fast with reliable and efficient multi-hop established by supervisors: high-speed packet loss message distribution and the consequences of routing protocols to reduce redundancy need to be cut.
In the cloud environment, the implementation of resource management requires a processing resource to a higher ratio.Since there are different number of alternative computer capacity, resource scheduling is a complex task in a cloud computing environment.Program is one of the most important issues in the cloud computing environment.We will analyze the diversity of the scheduling algorithm, shows the various parameters.We, the management of disk space, please note that is an important issue in a virtual environment.In order to provide high-high-throughput and cost-effective, the scheduling algorithm, existing, however, they do not take into account the reliability and availability.Therefore, we are, there is a need to improve the removal of the filter algorithm (RDFRA) in the cloud duplicate data availability and reliability of the algorithm are repeated in the data transmission rate of the proposed method of calculating the filter is removed and the environmental data.Using this method reserved resources are reserved to deal with any sudden or unexpected traffic task.In order to verify the measurement method using Similar delays, lead time, energy efficiency, yield, variety etc. downtime.From the results section, this method is, it is clear that you are better than the existing research.
Diabetic retinopathy (DR) is derived from diabetes is a serious eye disease and in the most common cause of blindness.DR is an eye disease that is a result of chronic disease of diabetes.A microaneurysm is a small red spot in the retina that raises from the fragile part of the blood vessel, hard exudates, and abnormal growth of blood vessels are the diabetic retinopathy.Predicting the presence of microaneurysms as an early indication of fundus imaging and diabetic retinopathy has been a major challenge for decades.DR is suffering from a person's chronic high blood sugar levels, microvascular problems, and irreversible vision loss leads.To solve this problem, the rapid advancement of Deep Learning (DL) makes it an effective technique for providing interesting solutions to analytical problems in medicine.The proposed system DL algorithms are Retinal Hidden Linear Selection (RHLS) algorithm and Quick Convolutional Diagnosis (QCD) algorithm.Retinal Hidden Linear Selection (RHLS) algorithm used to pre-process to remove noise from the fundus image, and excessiveperformance.Then, a quick convolution diagnosis (QCD) algorithm is a classification to determine whether the fundus image is subjected to a normal or influence.The results obtained are the proposed method, from a very effective and color fundus image shows a successful diabetic retinopathy diagnosis.
Vehicular Ad-hoc Networks (VANETs) is a wireless network that provides communication between vehicles and roadside infrastructure.It has been gaining high attention in the field mainly by researchers recently.It can provide various services, ranging from security-related early warning systems, enhanced navigation mechanisms, and information and entertainment applications.In VANET systems, some confidential data and contact information leakage can cause a severe loss of property.After that, it is a need for a higher level of security VANET system.Therefore, in VANET is the urgent priority need for security of privacy protection protocol.The proposed method Elliptic Homomorphic signature (EHS) the critical requirement is to allow VANETs privacy protection protocol to ensure its authenticity for the use of trademarks.When the user signs data, the signature is generated using the secret key, which is kept secure by the signer, and it encrypts the data.No one can create any signature items other than legitimate users.Destination to receive data using the public key confirms has not been modified in transit.The attacker can neither find the correct signature nor steal the data.The simulation results, when used in VANET, confirmed the level of effectiveness and security.
Machine learning methods become more and more popular.The purpose of using these methods is to become more and more popular network security components such as firewalls and anti-virus software such as machine learning methods expected to rise.Data machine learning systems provided by well-trained users can be vulnerable to attacks, poisoning data where malicious users inject fake training data, and damage the learning model.Data poisoning attacks can damage the integrity of the machine learning model by introducing malicious training models that affect results during testing.Distributed machine learning (DML) and Semi-DML is training that can be realized from a large database when any node is able to work out accurate results at an acceptable time.Compared to this inevitably diverse environment the attack will still expose potential targets.In this proposed method, we introduced the method for data detection poisoning, Data Poison Detection Program, Resource Schemes Multi-Linear Regression (RSMLR) to provide better learning protection and assistance from central sources.Proper allocation of resources in RSMLR can reduce resource waste.The application of modifying the data poison detection program can extend the system even more dynamically according to the environment and attack intensity.In addition, many of the components will increase the resource consumption of the system due to training.
Department of Mathematics, University of Louisiana at Lafayette. Abstract: It is known that Caputo fractional differential equations play an important role in modeling physical situation. The models represented by Caputo fractional differential equation in general are better and efficient models than its counterpart with integer derivative models. In this work, we consider nonlinear Caputo impulsive fractional differential equations with initial conditions. Further, the impulses occur in the nonhomogeneous term. Initially, we have computed the solution of the linear Caputo impulsive fractional differential equation explicitly using the method of mathematical induction. We have developed comparison results in terms of coupled lower and upper solutions when the nonlinear terms are sums of an increasing and decreasing functions of the unknown function. Finally, we have developed generalized monotone method for the Nonlinear Caputo Impulsive Fractional Differential Equations with initial conditions. This proves the existence coupled minimal and maximal solutions of the nonlinear problem. Finally, under uniqueness condition, we prove the existence of the unique solution of the nonlinear Caputo fraction impulsive differential equation with initial condition. We have also presented some numerical results.
