Communicable disease pandemic: a simulation model based on community transmission and social distancing.

Communicable disease pandemic is a severe disease outbreak all over the countries and continents. Swine Flu, HIV/AIDS, corona virus disease-19 (COVID-19), etc., are some of the global pandemics in the world. The major cause of becoming pandemic is community transmission and lack of social distancing. Recently, COVID-19 is such a largest outbreak all over the world. This disease is a communicable disease which is spreading fastly due to community transmission, where the affected people in the community affect the heathy people in the community. Government is taking precautions by imposing social distancing in the countries or state to control the impact of COVID-19. Social distancing can reduce the community transmission of COVID-19 by reducing the number of infected persons in an area. This is performed by staying at home and maintaining social distance with people. It reduces the density of people in an area by which it is difficult for the virus to spread from one person to other. In this work, the community transmission is presented using simulations. It shows how an infected person affects the healthy persons in an area. Simulations also show how social distancing can control the spread of COVID-19. The simulation is performed in GNU Octave programming platform by considering number of infected persons and number of healthy persons as parameters. Results show that using the social distancing the number of infected persons can be reduced and heathy persons can be increased. Therefore, from the analysis it is concluded that social distancing will be a better solution of prevention from community transmission.

Optimal control of a fractional order model for granular SEIR epidemic with uncertainty.

In this study, we present a general formulation for the optimal control problem to a class of fuzzy fractional differential systems relating to SIR and SEIR epidemic models. In particular, we investigate these epidemic models in the uncertain environment of fuzzy numbers with the rate of change expressed by granular Caputo fuzzy fractional derivatives of order ß ∈ (0, 1]. Firstly, the existence and uniqueness of solution to the abstract fractional differential systems with fuzzy parameters and initial data are proved. Next, the optimal control problem for this fractional system is proposed and a necessary condition for the optimality is obtained. Finally, some examples of the fractional SIR and SEIR models are presented and tested with real data extracted from COVID-19 pandemic in Italy and South Korea.

ITFDS: Channel-Aware Integrated Time and Frequency-Based Downlink LTE Scheduling in MANET.

One of the crucial problems in Industry 4.0 is how to strengthen the performance of mobile communication within mobile ad-hoc networks (MANETs) and mobile computational grids (MCGs). In communication, Industry 4.0 needs dynamic network connectivity with higher amounts of speed and bandwidth. In order to support multiple users for video calling or conferencing with high-speed transmission rates and low packet loss, 4G technology was introduced by the 3G Partnership Program (3GPP). 4G LTE is a type of 4G technology in which LTE stands for Long Term Evolution, followed to achieve 4G speeds. 4G LTE supports multiple users for downlink with higher-order modulation up to 64 quadrature amplitude modulation (QAM). With wide coverage, high reliability and large capacity, LTE networks are widely used in Industry 4.0. However, there are many kinds of equipment with different quality of service (QoS) requirements. In the existing LTE scheduling methods, the scheduler in frequency domain packet scheduling exploits the spatial, frequency, and multi-user diversity to achieve larger MIMO for the required QoS level. On the contrary, time-frequency LTE scheduling pays attention to temporal and utility fairness. It is desirable to have a new solution that combines both the time and frequency domains for real-time applications with fairness among users. In this paper, we propose a channel-aware Integrated Time and Frequency-based Downlink LTE Scheduling (ITFDS) algorithm, which is suitable for both real-time and non-real-time applications. Firstly, it calculates the channel capacity and quality using the channel quality indicator (CQI). Additionally, data broadcasting is maintained by using the dynamic class-based establishment (DCE). In the time domain, we calculate the queue length before transmitting the next packets. In the frequency domain, we use the largest weight delay first (LWDF) scheduling algorithm to allocate resources to all users. All the allocations would be taken placed in the same transmission time interval (TTI). The new method is compared against the largest weighted delay first (LWDF), proportional fair (PF), maximum throughput (MT), and exponential/proportional fair (EXP/PF) methods. Experimental results show that the performance improves by around 12% compared with those other algorithms.

Linear quadratic regulator problem governed by granular neutrosophic fractional differential equations.

Quadratic cost functions estimation in the linear optimal control systems governed by differential equations (DEs) or partial differential equations (PDEs) has a well-established discipline in mathematics with many interfaces to science and engineering. During its development, the impact of uncertain phenomena to objective function and the complexity of the systems to be controlled have also increased significantly. Many engineering problems like magnetohydromechanical, electromagnetical and signal analysis for the transmission and propagation of electrical signals under uncertain environment can be dealt with. In this paper, we study the optimal control problem with operating a fractional DEs and PDEs at minimum quadratic objective function in the framework of neutrosophic environment and granular computing. However, there has been no studies appeared on the neutrosophic calculus of fractional order. Hence, we will introduce some derivatives of fractional order, including the neutrosophic Riemann-Liouville fractional derivatives and neutrosophic Caputo fractional derivatives. Next, we propose a new setting of two important problems in engineering. In the first problem, we investigate the numerical and exact solutions of some neutrosophic fractional DEs and neutrosophic telegraph PDEs. In the second problem, we study the optimality conditions together with the simulation of states of a linear quadratic optimal control problem governed by neutrosophic fractional DEs and PDEs. Some key applications to DC motor model and one-link robot manipulator model are investigated to prove the effectiveness and correctness of the proposed method.

A New Approach for Construction of Geodemographic Segmentation Model and Prediction Analysis.

Customer retention is invariably the top priority of all consumer businesses, and certainly it is one of the most critical challenges as well. Identifying and gaining insights into the most probable cause of churn can save from five to ten times in terms of cost for the company compared with finding new customers. Therefore, this study introduces a full-fledged geodemographic segmentation model, assessing it, testing it, and deriving insights from it. A bank dataset consisting 11,000 instances, which consists of 10,000 instances for training and 10,000 instances for testing, with 14 attributes, has been used, and the likelihood of a person staying with the bank or leaving the bank is computed with the help of logistic regression. Base on the proposed model, insights are drawn and recommendations are provided. Stepwise logistic regression methods, namely, backward elimination method, forward selection method, and bidirectional model are constructed and contrasted to choose the best among them. Future forecasting of the models has been done by using cumulative accuracy profile (CAP) curve analysis.