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In this paper, an improved energy balance method has been presented to obtain an analytical approximate solution to investigate a conservative non-linear oscillator having inertia and static non-linearity. The method is valid for both small and large amplitudes of oscillation. Although the trial solution of the present paper is the same as Khan and Mirzabeigy (2014), the solution procedure is different. Moreover, the algebraic equations appeared in the present technique are solved analytically. The results obtained in this paper are compared with other existing results. The present method not only gives better result than other existing result but also gives perfect agreement with the numerical result (considered to be exact result). [ABSTRACT FROM AUTHOR]

Calculus is the subject of evaluating derivatives and integrals of non-integer orders of a given function, fractional differential equations is the subject of studying the solution of differential equations of fractional order is considered in this paper, which contain initial conditions. The general form of a fractional differentia equation is supported by: y(s) = k(c, u), y(stk) (c0) = u. Where k = 1, 2, ... , n + 1, n < q < n + 1, and n is an integer number. The solution of fractional differential equations has so many difficulties in their analytic solution, therefore numerical methods may be in most cases be the suitable method of solution. This paper introduces and study a numerical solution by ADI methods for solving fractional differential equations. We used the matrix obtained from this solution as a key matrix for cryptography the plain text and transform it to cipher text by using the method of Hill matrix system the quantity demand and investment in research and development, while the other model focuses on a more realistic relationship between the quantity demand and the price. [ABSTRACT FROM AUTHOR]

Recently cryptography is one of the essence areas of study. There are two types of cryptography, this paper is concerned with the simplest and fastest which is "Symmetric Key Cryptography". Symmetric encryption text information is widely known as an effective and secure method for the purpose of secure transmission. In this paper, we present a new symmetric encryption scheme for text encryption and decryption based on Karhunen Loeve transform, where Karhunen Loeve transform is a reversible linear transform. The time complexity of the proposed scheme is calculated for both encryption and decryption. The proposed scheme has an has efficiency according to the security measures. [ABSTRACT FROM AUTHOR]

In this paper; we study the relationship between two modules in module theory namely injective and pseudo valuation modules. We investigated that every module has three properties which are noetherian, cyclic and regular is pseudo valuation modules. Also, if R is an Artinian ring and E is finitely generated regular module, it implies that E is (P.V.M). We proved that for an R-module E, if R is a commutative ring with E is a Noetherian, Artinian and regular module, then E is P.V.M. Finally, some definitions and new results have introduced in this paper. [ABSTRACT FROM AUTHOR]

An edge labeling of a connected graph G = (V, E) is said to be local antimagic if it is a bijection f : E → {1, ... ,|E|} such that for any pair of adjacent vertices x and y, f+(x) ≠ f+(y), where the induced vertex label f+(x) = ∑f(e), with e ranging over all the edges incident to x. The local antimagic chromatic number of G, denoted by χla(G), is the minimum number of distinct induced vertex labels over all local antimagic labelings of G. Let χ(G) be the chromatic number of G. In this paper, sharp upper and lower bounds of χla(G) for G with pendant vertices, and sufficient conditions for the bounds to equal, are obtained. Consequently, for k ≥ 1, there are infinitely many graphs with k ≥ χ(G) - 1 pendant vertices and χla(G) = k + 1. The work of this paper leads to conjecture and problem on graphs with pendant(s). [ABSTRACT FROM AUTHOR]

Let T = (V, E) be a tree of order n. Let f : E → {1, 2, 3, ... } be an injective edge labeling of T. The weight of a path P is the sum of the labels of the edges of P and is denoted by w(P). If the set of weights of the paths in T is , then f is called a Leech labeling of T and a tree which admits a Leech labeling is called a Leech tree. In this paper, we introduce a new parameter called Leech index which gives a measure of how close a tree is towards being a Leech tree. Let f : E → {1, 2, 3, ... } be an edge labeling of T such that both f and w are injective. Let S denote the set of all weights of the paths in T. Let kf be the positive integer such that {1, 2, 3, ... , k f } ⊆ S and kf + 1 ∉ S. Then k(T) = max kf, where the maximum is taken over all such edge labelings f is called the Leech index of T. In this paper, we determine the Leech index of several families of trees and obtain bounds for this parameter. [ABSTRACT FROM AUTHOR]

This paper focuses on the mathematical model based on the input output realization with a view to analyzing the time-invariant dynamical behaviour of the blood flow through carotid artery. The entire system's characteristic is governed by the Navier-Stokes equation which is represented in this paper as differential-algebraic matrix representation. This mathematical representation is commonly known as state space model that is extracted from the Taylor-hood finite element discretization of the physical model. Later, for computational convenient, this model is divided into different sub-blocks studying the sparsity patterns of the matrices each of which contains the system's parameters responsible for any dynamical changes. This form is well-known as index-II descriptor data model representing the relationship between the input external force applying to the artery's boundary and the output measuring the changes in the blood velocity and the pressure. Based on the input-output realization, MATLAB interface is used to carry out numerical experiments and the results illustrate the numerical behaviour of the generated state space model for analyzing the blood flow nature through carotid artery. [ABSTRACT FROM AUTHOR]

Cloud computing is the on-demand availability of a group of networked elements providing services, especially data storage and computing power, without actual management and addressing by the user. In lieu, the entire suite of hardware and software is managed by a provider and have functions dispersed over various location, each location being a data center. Since cloud computing users rely on sharing resources and may request multiple cloud services concurrently, a dynamic provision must be there so that all the resources are available to the user in a competent manner. However, despite abundantly available benefits, many organizations are still skeptical about using the cloud computing service model because of security concerns associated with the service. The paper also discusses different types of cloud security, controls of cloud security and algorithms used for emanating the privacy of the client's data. In this paper, a CNN and SVM model is also applied for detection Anti-Spoofing images for identification on images on cloud. [ABSTRACT FROM AUTHOR]

Sharing information from one device to another is gradually replacing hand-to-hand paper work in this connected digital age. Digital, modern technology are used to control the data communication. Because of this, the pace of a device's cyber security is presently fast increasing. DDoS(Distributed Denial-of-Service), is one such phenomenon. TCP (Transmission Control Protocol) Half-open attacks include an SYN(Synchronization) flood attacks. It is a form of distributed denial of service attack that seeks to block all valid communication to a server in order to available server resources. This paper aims to protect the communication from DDoS TCP SYN flood attack. There are many research papers which can detect the attack after the attack take place and the prevention percentage is low. In this research paper this attack can be prevented much well than other model because a flood attack can detect before hampering the server and deny the connection attempt. There will be two cases studied and solved here that SYN-ACK(Synchronization-Acknowledgement) lost (no destination), SYN-ACK—no response. [ABSTRACT FROM AUTHOR]

In the number theory, the law of quadratic reciprocity is a theorem about modular arithmetic that gives conditions for the solvability of quadratic equations modulo prime numbers. It noticed by Euler and Legendre and proved by Gauss. In this paper, we will study the quadratic reciprocity law theorem where the Euler Criterion and Legendre Symbol are involved. The application of quadratic reciprocity law theorem is given in cryptography, where the Quadratic Residuosity Problem considered as a hard mathematical problem for Goldwasser Micali Randomized Public Key Cryptosystem. This system will be discussed with the details in this paper. [ABSTRACT FROM AUTHOR]

The current stage in the development of cryptography is characterized by attention of researchers to the methods of many-valued logic. Of particular importance are the methods of three-valued logic, which are used in quantum cryptography, as well as in three-valued cryptographic algorithms with an increased level of cryptographic strength, implemented on binary computers. This circumstance leads to the need for further improvement of methods for constructing of high-quality cryptographic primitives. This paper is devoted to the generalization of definition of the correlation immunity of three-valued logic functions in the context of the properties of matrices of correlation coefficients of S-boxes built on their basis. The paper proposes methods for the synthesis of complete classes of 3-functions of length N = 9, the output of which does not depend on the input variable x1 or x2, as well as the full set of correlation immune 3-functions. The relationship between the introduced criterion of the correlation immunity of 3-functions and the criterion for the absence of a correlation interconnection between the output and input vectors of S-boxes of length N = 9 is also established. [ABSTRACT FROM AUTHOR]

In this paper, authors defined a conical open set's characterization. As a consequence, they introduced the (- space and - space)-open subdigraph in graph theory. Their interrelationships were investigated. As a result, several theorems have been proven. The aim of this paper, is to find graph theory applications due to the difficulty in finding applications in topological spaces, which are pure mathematics branches. We defined a conical open set's characterization. As a consequence, we introduced the (space and - space)-open subdigraph in graph theory. Their interrelationships were investigated. As a result, several theorems have been proven. [ABSTRACT FROM AUTHOR]

We were able to classify all 1-error correcting [5, 3] codes over GF(5) in paper [1] and [5, 2] ternary codes in paper [2]. Now, our focus is an equivalence based classification of error correcting linear codes of length 6 over GF(5). In paper [3], we investigated the equivalence of [6,3,4] codes of length 6 and dimension 3 over GF(4). In this paper we classify the [6,3,4] codes over GF(5). We explore the weight distribution of these codes as well as their duals. [ABSTRACT FROM AUTHOR]

Multimedia data including text, audio, image, and video are increasingly transmitted over networks or stored in digital format. Therefore, secure transmission and storage are required to preserve it. This is why the utilization of cryptography has become imperative to establish new approaches for rising security. The cryptographic systems rely on cellular automata (CA) and chaotic systems, which are fundamental in various cryptographic applications such as key generation and image encryption. Some of them are complex and others have little key space. In this paper, a novel research work based on cellular automata and chaotic logistic mapping is proposed. Overall, the paper aims to propose a new cryptographic system that produces encrypted data with random characteristics. A novel technique is adopted to develop the evolution of configurations in elementary cellular automata (ECA) which makes the obtained result more random. Simulation results demonstrate that the proposed approach has a high level of security and resists various attacks. In addition, it outperforms some existing image encryption algorithms. [ABSTRACT FROM AUTHOR]

Lightweight cryptography is essential for securing resource-limited devices like smart card, RFID (radio-frequency identification)tags, sensor network and embedded system. In this paper, we present a survey of lightweight block ciphers from both software and hardware perspectives. This paper show the analysis of lightweight block ciphers on the basis of block size, key size, number of rounds, area in gate equivalent, speed, logic process as metrics for comparison purpose. Also, this comprehensive survey highlights the strengths and some of the security related issues in terms of key length and attacks in lightweight cryptography. [ABSTRACT FROM AUTHOR]

In modern times individuals are facing an important social challenge in the form of stress. Combining sensor devices that capture physiological, and brain waves data, this study develops a machine learning technique using cloud computing to recognize stress in people in social contexts. In this paper, we are comparing several classifiers, including Random Forest, Support Vector Machine, k-nearest neighbor and AdaBoost, and also inventing a method that uses sensor data in day-to-day life. It detects stress levels with high accuracy. Our results show that by combining data from all the sensors, we are able to accurately differentiate between the stressful and normal situations of humans. In addition, this paper also evaluates the individual capabilities of each sensor modality and its applicability for stress detection in real-time situations. Methods: We have provided unique technology to incorporate sensor signals using cloud computing. It monitors the user's sweat level, temperature, heart rate variation, and EEG under various motion estimations and also chooses the best model to detect the anxiety level based on the user's motion conditions. Results: Evaluation of algorithms using sample data reveals an overall concern detection accuracy of 94% along with a significant reduction in false positives compared to the ultramodern techniques. [ABSTRACT FROM AUTHOR]

Short text is rapidly expanding, and it is critical to understand why. Unlike traditional documents, short text is short and sparse, making machine learning and text mining algorithms difficult to apply. The process of identifying and categorizing ideas expressed in a text into positive, negative, and neutral polarities is referred to as sentiment analysis. The selection of features for machine learning is critical. The evaluation of search engines is a critical topic in the field of information retrieval. Researchers can determine whether their new algorithms add value or should be scrapped by effectively evaluating their algorithms. Organizations create cutting-edge methods for assessing their performance. Social tags have become an important source of information in web 2.0 for making personalized recommendations by identifying user interests and preferences. The purpose of this research is to systematically represent the actual topics of tags, the content of items, and user interest in specific topics via popular tags based on the content of the tags, items, and topics. The goal of this paper is to propose an innovative method for identifying user topic interests using popular tags. This paper proposes a method for extracting the main features of short text at various granularity levels. One aspect of how the content of items is represented in this paper is through the use of popular tags, but the representation of user interests is also discussed. By analysing a small dataset of short text classifications, we were able to compare our proposed method to a state-of-the-art baseline. We reduced the classification error by 20% using two different analysis methods, while the other method reduced it by 16.68%. The original tags of users are used to generate topic interests, from which we identify popular tags. The popular tags are then used to generate topic interests using an autoencoder approach. [ABSTRACT FROM AUTHOR]

Pen pressure is an important individual characteristic of the handwriting examination whose potential has not been fully utilized. Most of the times it is overlooked by experts because they do not think it has substantial value to be of forensic significance. Generally, it is thought to be of relevance in cases involving simple and traced forgery. One of the reasons behind pen pressure being ignored by the document examiners may be a lack of technique to calculate the absolute value of pen pressure. The existing methods require specialized setup, training, and are expensive in nature and can only be used to measure relative value of pen pressure. The aim of this paper is to discuss various methodologies used by document experts and researchers in past with an attempt to quantify pen pressure and critically analyze them to bring the reader's and researcher's focus on their advantages and disadvantages. The paper also discusses prospects of future works which may include techniques that can be used more routinely in handwriting examination and can also give an absolute measure of pen pressure. In this aspect, mathematical approaches can be further explored. [ABSTRACT FROM AUTHOR]

Due to insufficiency of parking space, people face many problems in finding a vacant slot to park their vehicles in the parking area. This problem is giving rise to many other problems such as traffic congestion, wastage of fuel, money and time. Therefore, there is a need to develop an intelligent parking management system for better utilization of the resources. The main objective of the paper is to design an efficient parking system to search for the vacant slots in the parking area. In this paper, experiments have been conducted on standard dataset "PKLot" which consists of 695,899 images of two different parking lots. These images were captured from three different camera views under different climatic conditions like rainy, sunny and cloudy. Various machine learning (ML) techniques like Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) with different parameters have been applied on the dataset. Further, an ensemble model for classification of occupied and vacant slots in the parking area has been developed which improves the performance of the system as compared with other state-of-the-art systems. [ABSTRACT FROM AUTHOR]

Fog computing is defined as the distribution of computing resources between the data devices and the cloud or any other data centre in a distributed computing infrastructure or process. This paper briefly reviews the various definitions, applications, architecture and fog simulators proposed by researchers over the years. In this paper, a comparison table is presented which highlights the key features of simulators available like FogtorchII, iFogSim, Fogbus, MyiFogSim etc. [ABSTRACT FROM AUTHOR]

A graph G is s -Hamiltonian-connected if the deletion of any vertex subset with at most s vertices results in a Hamiltonian-connected graph. In this paper, for positive integer s, a graph G is s-trail-connected if for any vertex subset X with |X|≤ s, G − X is trail-connected; a graph G is s-edge-trail-connected if for any edge subset Y with|Y|≤ s, G \ Y is trailconnected. The main purpose of this paper is to depict the structure of 1-trail-connected and 1-edge-trail-connected square tree. [ABSTRACT FROM AUTHOR]

Gait of post-stroke patients have been analyzed and classified in this paper. Data pertaining to gait of both post-stroke patients and healthy people of the same age group were obtained and analyzed. Xsens motion capture system was used for obtaining this data from 40 people belonging to both categories. Advanced modern machine learning techniques such as Logistic Regression, Multilayer Perceptron (MLP), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) were employed for classifying the data obtained. Accurate spatiotemporal parameters values for gait were obtained. Amongst the different machine learning techniques, XGBoost gave the most accurate classification result of about 96%. The walking patterns of the patients who had undergone a stroke attack were analyzed. severity of abnormal gait patterns was a key factor that was taken into consideration and points were given accordingly. The data presented in this paper can be used to develop diagnostic tools for gait rehabilitation of stroke survivors, to evaluate and estimate their way of walking in order to understand their progress. It can be used to understand the different types of walking disorders post-stroke and thereafter select the right kind of treatment that needs to be implemented for proper recovery. [ABSTRACT FROM AUTHOR]

All graph in this paper is connected and simple graph. Let d(u, v) be a distance between any vertex u and v in graph G = (V, E). A function l : V(G) → {1, 2,..., k} is called vertex irregular k-labelling and w : V(G) → N where w(u) = ΣvϵN(u)l(v). If for every uv ϵ E(G), w(u) ≠ w(v) and opt(l) = min(max(li); li vertex irregular labelling) is called a local irregularity vertex coloring. The minimum cardinality of the largest label over all such local irregularity vertex coloring is called chromatic number local irregular, denoted by χlis(G). In this paper, we study about local irregularity vertex coloring of families graphs, namely triangular book graph, square book graph, pan graph, subdivision of pan graph, and grid graphs. [ABSTRACT FROM AUTHOR]

In this paper, we study both strong and weak rate of convergence of Euler-Maruyama scheme for one-dimensional stochastic differential equations involving the local time (SDELT) of the unknown process, whose the solution corresponds to divergence form operator with a discontinuous coefficients at point ξ ∈ ℝ. The paper is concerned with stochastic differential equation with local time of type, where is the local time of X in {ξ}. The main idea of this paper is to use a space transform in order to transform the original SDELT to a new auxiliary equation with discontinuous coefficients but without local time. Then, we apply the Euler-Maruyama scheme to this new equation. Finally, we obtain an approximation of the original SDELT by transforming the approximation of the auxiliary equation. [ABSTRACT FROM AUTHOR]

With the improvement of IoT functions, number of devices connecting to Internet of Things (IoT) is expected to grow globally in future and those devices may have to generate a big bulk of data for processing in limited time. Under such environment, Data management should serve as a link between objects and data generating devices, as well as data consumer apps for analysis and action. IoT interacts with all communication devices and permits global access of data generated by devices. Cloud computing is playing a vital role in computing, network management and storing data but all these activities are being done in centralized data-centers. The centralized cloud computing can lead to some kind of risks like limited capacity issues, high latency and network failure, with the exponential growth of IoT. Cloud and fog computing has the answer for all such risks, as it does all computation or storage of IoT items locally instead of sending to cloud and thus this helps to provide quick results and improves Quality of service (QoS) for healthcare system. Cloud and fog is considered to be safest and quickest approach to ensure IoT delivers expected results in healthcare system where delay can lead to criticality for the patients. Fog computing becomes important as it manages data and computation at the network edge closest to the end user which makes it super & quick reactive. Despite its compelling advantages, the characteristics of fog computing arise new security and privacy challenges. This paper investigates the various QoS parameters and discusses different security issues along with possible solutions in fog system. The paper also proposes an approach to enhance the quality of service in integrated cloud-fog environment. [ABSTRACT FROM AUTHOR]

Hard-hats are the most essential safety gear on construction sites. Accidents happen due to the ignorance to wear a hard hat properly. To prevent construction accidents due to the non-usage of hard hats, automatic non-hardhat usage detection techniques have been observed to be more efficient. This paper analyses the usage of deep learning algorithms in detecting construction workers who fail to wear their hard hats properly. The accuracy of the 3 deep learning algorithms, i.e. YOLO v4, v5 and YOLACT++ have been tested using a set of data of Hard-hats collected from the crowdsourcing and web mining. These vision-based deep learning methods and algorithms have been applied and compared in terms of accuracy, scalability, and robustness. The research evaluated the different frames of construction site workers and classified image frames into different categories. The frames were input into the deep learning algorithm as per their visual categories. The objective of the paper is to analyze the present deep learning approaches for the real-time detection of the hardhat on the construction site in a way that the hardhat could be recognized efficiently without any failure and would be able to distinguish the workers who are not wearing their Hard-hats suitably and introduce a new access control system using deep learning methods to solve the problem of efficiently identifying Hard-hats for site workers. The experimental results demonstrate that the high score of precision, recall, and fast speed of the techniques, which would effectively detect non-usage of Hard-hats by site workers at different construction site conditions. This will help improve safety and supervision on construction sites. [ABSTRACT FROM AUTHOR]

Mental disorder is defined as psychological disorders that involve instabilities in brain function. This paper aims to provide an overview of photoplethysmogram (PPG) for detecting early symptoms of mental disorders encompassing physiology using different stimuli. This paper discusses mental disorder studies that have been highlighted in the previous literature. The contribution of the PPG is summarized through feature extraction and its accuracy classified using machine learning. Moreover, research challenges and recommendations in the field are discussed. In conclusion, there were significant changes against the early signs of mental disorders through emotional and stress levels from PPG signal morphology. [ABSTRACT FROM AUTHOR]

The majorize modelling of the modified Newton method (MNM) is an effective tool for concluding the existence and uniqueness of the solution of nonlinear operator equations. In this paper, we consider MNM together with a new majorant function (MF) that needed weak conditions to solve a nonlinear algebraic system (NLAS). The main advantage of this method is that you only require to establish the inverse of the Jacobian matrix (JM) at the initial guess (IG) and there is no need to compute it at the other iterations. The proposed strategy in this paper is logical and easy to execute. The theorems of MF and convergence are established for the method. Numerical results show that the strategy is efficient and promising. [ABSTRACT FROM AUTHOR]

HC-128 is a strong candidate of eSTREAM Project. The resistance of this algorithm against cryptanalytic attacks has been analyzed by several researchers. We analyze its security in terms of its variability and non-linearity. A strong crypto-algorithm should have full variability. By 'variability of an algorithm' we mean the number of distinct sequences, the algorithm can produce. Full variability means that the algorithm produces as many distinct sequences as there are key-IV pairs. There are research papers which indicate that the algorithm may have the full variability. However, no concrete proof is given. In this paper we present a deterministic proof of full variability of HC-128. Non-linearity plays an important role in determining the security of a crypto-algorithm. Because of the complicated nature of the algorithm, determining the exact degree of the HC- 128 function is quite difficult. In this paper, we demonstrate that the degree of non-linearity of key and IV setup function of HC-128 is very high and it is computationally hard to invert the cipher with the knowledge of key stream only. [ABSTRACT FROM AUTHOR]

In this paper, we obtained sandwich theorem for new condition of analytic univalent functions which is defined by the generalized salageon integro-differential operator. [ABSTRACT FROM AUTHOR]

Through our paper, we intent to study the influence of Eyring-Powell liquid oscillatory flow with dangerous heated convective and (MHD) form. It is with the association of liquid movement equations by exhausting the technique ''Perturbation Technique" in relationship of (ϵ << 1 Weissenberg number to get perfect principles for the rate field. All the results of mental factors of the (Re) Reynold's number, (M) Hypnotic parameter, Peclt number (Pr) and Darisi parameter (Da) are conversed below the dissimilar principles, as displayed in popular designs. [ABSTRACT FROM AUTHOR]

In this paper, using Bianchini-Grandolfi gauge functions, we define a new notion of BG-contraction mapping and proximal BG-contraction mapping. After that, we prove some best proximity point results. Hence, we generalize and improve results existing in the literature such as [12]. Also, we provide nontrivial example to demonstrate the effectiveness of our result. Finally, we give an existence and uniqueness result for the solution of nonlinear Freldhom and Volterra integral equations via our result. [ABSTRACT FROM AUTHOR]

In this paper, we first obtain some q-Hermite-Hadamard type inequalities for the product of two convex functions. Then by using the product of two co-ordinated convex functions, we establish new q-Hermite-Hadamard type inequalities. The results in this work generalize several results obtained in earlier studies. [ABSTRACT FROM AUTHOR]

This paper is devoted to introduce a new kind of topological vector spaces called strongly α-topological vector space and study their relationship with other types of topological vector spaces. The α-bounded and totally α-bounded sets are defined by using α-open in strongly α-topological vector space and some of their characterizations are established. [ABSTRACT FROM AUTHOR]

The aim of the present paper is to introduce and study the notions of -set and -continuity via biopeation. We discuss some properties of these notions. [ABSTRACT FROM AUTHOR]

The aim of this paper is to present a new algorithm for solving some decision-making problems of fuzzy soft sets over semigroups based on the Minkowski distance. Furthermore, some examples show that the new algorithm is practical for solving decision-making problems. [ABSTRACT FROM AUTHOR]

Our main goal in this paper is to propose a mathematical model in order to use it to study the historical achievements of a particular team in order to stand on the evolutionary behavior of the team and to be able to predict the future results of the team by measuring the team's performance through the total number of victories, losses and draws in official matches approved. Our main idea is to use a Markov model to find the results of matches, so that the outcome of each match is one of the specified cases: win or lose or draw. [ABSTRACT FROM AUTHOR]

In this paper, a definition of a special type of function based on the concept of proximity relation is presented in conjunction with central set theory to find a special definition of continuity between center topological spaces and the transfer of topological properties, which we call sharing central continuous function. [ABSTRACT FROM AUTHOR]

This paper aims to introduce a new form of orthogonality in the real normed space. This new orthogonality depends on a norm derivative concept. Some of its substantial characteristics are present, also we use this relation to define -angular property. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to show some interesting properties of hyperbolic univalent convex differential functions in the case of estimating the real and imaginary parts of a hyperbolic univalent convex function using the definition of invariant differential operator of the first and second-order as stated in theorems (2.1) and (2.2). In addition, the same differential operator has been analyzed through an estimation of the differential operator when to be be a holomorphic function for each , except some poles z, and also in case of being a locally univalent function defined in the unit disk. [ABSTRACT FROM AUTHOR]

In this paper we develop the concept of local function via - ω open. We also study the densities and their properties with respect to - ω open in the ideal topological spaces. We also defined - Iω hyper , - Iω resolvable and - ω condense by expanding the definition of ideal topological space and associating it with set - ω open. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a new class of operators on separable Hilbert space called poly. normal operator. An operator is called poly. normal if there exists a polynomial ℙ, where such that , where * is the adjoint operator of. We investigated some basic properties and new results were discussed in this research. [ABSTRACT FROM AUTHOR]

The notion of picture fuzzy soft sets (PFSSs) was first introduced by Yang et al. [26] in 2015, which is merging the notion of picture fuzzy sets (PFSs) and soft sets. We used the notion of PFSSs over UP-algebras to present eight new notions of PFSSs using a special type in this paper. In addition, we describe the eight new notions of PFSSs over UP-algebras and their necessary and sufficient conditions. [ABSTRACT FROM AUTHOR]

In this paper, some properties of linear functionals are studied, which are used in functional analysis, optimization theory, numerical analysis, approximation theory, various applications, etc. [ABSTRACT FROM AUTHOR]

Let (X, D) be a complete metric space and H, F be single and multivalued mappings on X respectively. In this paper, we investigate two new types of fixed point theorems from a set of single and multivalued mappings in a complete metric spaces endowed with a graph G such that the set of vertices of G, V(G) = X and the set of edges of G, E(G) ⊆ X × X. [ABSTRACT FROM AUTHOR]

The whole world is suffering from a pandemic virus known as COVID-19 nowadays. This virus is also known as novel corona virus. There are various statements coming out regarding its generation but till now one thing is coming is that its origin place seems to be a lab somewhere in Wuhan city of China. It is also said off and on the record that covid-19 virus came into existence near November 2019 but on record, the WHO office (China) reported on 31st December 2019 that an unknown virus is detected in Wuhan city. On 7th January 2020, Chinese authorities announced about the existence of this virus. At the initial stage, it was supposed that this virus might be bat-origin but after that several other statements are coming day by day. Authors are not going to discuss about the causes of its origin. But since this virus has become the pandemic around the world so it is necessary to study this virus and its nature to predict the future outbreaks and also control strategies by using mathematical modeling. In this paper, we are going to study the model by using Atangana-Baleanu fractional operator. Also we calculated the numeric results with graphical representation. [ABSTRACT FROM AUTHOR]