This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6^th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

In this paper, the C̆ech fuzzy soft closure spaces are defined and their basic properties are studied. Closed (respectively, open) fuzzy soft sets is defined in C̆ech fuzzy-soft closure spaces. It has been shown that for each C̆ech fuzzy soft closure space there is an associated fuzzy soft topological space. In addition, the concepts of a subspace and a sum are defined in C̆ech fuzzy soft closure space. Finally, fuzzy soft continuous (respectively, open and closed) mapping between C̆ech fuzzy soft closure spaces are introduced. Mathematics Subject Classification: 54A40, 54B05, 54C05.

Any design subject to a set of forces contributing to the establishment of relations working to strengthen the internal elements of the design; any imbalance in these elements can make a fragmented and weak design, thus preventing it from achieving the goal or performance. Poor performance can be attributed to various factors: the extent and function of the elements and principles in the design, realization of the idea, especially in fashion design.
Moreover, there are many aspects of a design that go into achieving the realization of the designer’s idea. The design utilizes a lot of stimulants by drawing attention to its design, which is consistent with the need for psychological and material individuals. In this research, we will

Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

Fabrication of a photodetector consists of the conjugated polymer "MEH-PPV"- poly (2-methoxy-5-(2'-ethylhexyloxy)-1,4-phenlenevinylene) and MEH-PPV:MWCNT nanocomposite thin film. The volume ratio investigated was 0.75:0.25. MEH-PPV was dissolved in chloroform solvent and doped with MWCNTs. The spin coating method was used to achieve a facile and low cost photodetector. The absorption spectrum decreases by adding the CNTs. The PL spectrum detected recombination curve results by doping the polymer with CNTs, and AFM measurement showed an increase of roughness average from (0.168 to 2.43nm) of "MEH-PPV" and "MEH-PPV:CNTs", respectively. The doping ratio 0.25, which has a higher photoresponsivity, was evaluated at 1.70 A/W and 2.14 A/W of th