The new sustainable development goals set by the UN include a goal of making cities inclusive, safe, sustainable, and resilient. Cities are growing at huge rates, and conditions of deteriorating QOL̛s are increasing in the form of poor access to services, and slums are remarkable, especially in the cities of the Middle East; hence, the research problem can arise from a lack of knowledge regarding the in determination of a way to assess the resilience of cities to develop mechanisms that will improve the quality of urban life. In this study, a tool called CRF has been applied for the assessment of the city's resilience principles of health and quality of life, economics and social, infrastructure and environmental systems, and the principle

Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

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                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

In this paper, two of the local search algorithms are used (genetic algorithm and particle swarm optimization), in scheduling number of products (n jobs) on a single machine to minimize a multi-objective function which is denoted as  (total completion time, total tardiness, total earliness and the total late work). A branch and bound (BAB) method is used for comparing the results for (n) jobs starting from (5-18). The results show that the two algorithms have found the optimal and near optimal solutions in an appropriate times.

In this work we experimentally investigated SWCNTs and MWCNTs to increase their thermal conductivity and electrically functionalization process using different reagents ((nitric acid, HNO3 followed by acid treatment with H2SO4), then washed with deionized water (DW) and then treated with H2O2 via ultrasonic technique. Then repeated the steps with MWCNTs and compare their results in an effort to improve experimental conditions that efficiently differentiate the surface of the single walled carbon nanotubes (SWCNTs) and multi walled carbon nanotubesi(MWCNTs) that less nanotubes destroy and to enhance the properties of them and also to reduce aggregation in liquid. the results were prove by XRD, and infrared spectroscopy (FTIR). The FTIR sp

In real world, almost all networks evolve over time. For example, in networks of friendships and acquaintances, people continually create and delete friendship relationship connections over time, thereby add and draw friends, and some people become part of new social networks or leave their networks, changing the nodes in the network. Recently, tracking communities encountering topological shifting drawn significant attentions and many successive algorithms have been proposed to model the problem. In general, evolutionary clustering can be defined as clustering data over time wherein two concepts: snapshot quality and temporal smoothness should be considered. Snapshot quality means that the clusters should be as precise as possible durin

     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s

In this work, polyvinylpyrrolidone (PVP), multi-walled carbon nanotubes (MWCNTs) nanocomposite was prepared and hybridized with Graphene (Gr) by the solution casting method.  The morphological and electrical properties were investigated by field effect scanning electron microscopy (FESEM) images, portraying a uniform dispersion of graphene within the PVP-MWCNT nanocomposite. The AC conductivity increased from (1.45552) to (2.34812) (Ω cm)^-1 with the use of nanocomposite. The increasing continues for the AC conductivity after hybridized with graphene up to (7.20641) (Ω cm)^-1. In addition, the performances of the prepared samples for gas sensor application have been investigated.