The rise of the Internet of Things (IoT) has led to a numerous and diverse amount of products and real life implementations for smart cities in the last few years. With the many opportunities and challenges, the academic and industrial field has come up with many hardware and middleware platforms. We categorise these different IoT applications and solutions into different domains and present an application for each. This survey aims at defining the state-of-the-art major and common technologies, frameworks, and applications used to open doors to drive future research and to spark new ideas for

Meta-heuristics and nature inspired algorithms have been prominent solvers for highly complex, nonlinear and hard optimization problems. The Gaining-Sharing Knowledge algorithm (GSK) is a recently proposed nature-inspired algorithm, inspired by human and their tendency towards growth and gaining and sharing knowledge with others. The GSK algorithm have been applied to different optimization problems and proved robustness compared to other nature-inspired algorithms. The GSK algorithm has two main control parameters kfand kr which controls how much individuals gain and share knowledge with

For the past decade, Internet of Things (IoT) had an important role in our lives. It connects a large number of embedded devices. These devices fulfill very difficult and complicated tasks, which facilitate our work. Till now the security of IoT faces many challenges such as privacy, authentication, confidentiality, trust, middleware security, mobile security and policy enforcement. In order to provide a secure environment for IoT, this paper proposes a framework for IoT devices. © 2017 IEEE.

Ad hoc networks are peer mobile nodes that self configure to form a network. In these types of networks there is no routing infrastructure, and usually nodes have limited resources. This imposes a serious problem due to some nodes' selfishness and willingness to preserve their resources. Many approaches have been proposed to deal with this problem and mitigate the selfishness; amongst these approaches are reputation systems. This paper proposes a reputation system scheme that helps isolating misbehaving nodes and decreasing their ability to launch an attack on the network. The idea of this

Numerous commercial tools like Xamarin, React Native and PhoneGap utilize the concept of cross-platform mobile applications development that builds applications once and runs it everywhere opposed to native mobile app development that writes in a specific programming language for every platform. These commercial tools are not very efficient for native developers as mobile applications must be written in specific language and they need the usage of specific frameworks. In this paper, a suggested approach in TCAIOSC tool to convert mobile applications from Android to iOS is used to develop the

In the field of pattern recognition multiple classifier systems based on the combination of outputs from different classifiers have been proposed as a method of high performance classification systems. The objective of this work is to develop a fuzzy Gaussian classifier for combining multiple learners, we use a fuzzy Gaussian model to combine the outputs obtained from K-nearest neighbor classifier (KNN), Fuzzy K-nearest neighbor classifier and Multi-layer Perceptron (MLP) and then compare the results with Fuzzy Integral, Decision Templates, Weighted Majority, Majority Naïve Bayes, Maximum

Purpose - The purpose of this paper is to present a dynamic model to measure the degree of system's leanness under dynamic demand conditions using a novel integrated metric. Design/methodology/approach - The multi-stage production system model is based on a system dynamics approach. The leanness level is measured using a new developed integrated metric that combines efficiency,WIP performance as well as service level. The analysis includes design of experiment technique at the initial analysis to examine the most significant parameters impacting the leanness score and then followed by

In the era of digital transformation, a mass disruption in the global industries have been detected. Big data, the Internet of Things (IoT) and Artificial Intelligence (AI) are just examples of technologies that are holding such digital disruptive power. On the other hand, retailing is a high-intensity competition and disruptive industry driving the global economy and the second largest globally in employment after the agriculture. AI has large potential to contribute to global economic activity and the biggest sector gains would be in retail. AI is the engine that is poised to drive the

Background: Lung cancer is a leading cause of cancer-related death worldwide and is the most commonly diagnosed cancer. Like other cancers, it is a complex and highly heterogeneous disease involving multiple signaling pathways. Identifying potential therapeutic targets is critical for the development of effective treatment strategies. Methods: We used a systems biology approach to identify potential key regulatory factors in smoking-induced lung cancer. We first identified genes that were differentially expressed between smokers with normal lungs and those with cancerous lungs, then integrated

Fractional-order spiking neuron models can enrich model flexibility and dynamics due to the extra degrees of freedom. This paper aims to study the effects of applying four different numerical methods to two fractional-order spiking neuron models: the Fractional-order Leaky integrate-and-fire (FO-LIF) model and the Fractional-order Hodgkin–Huxley (FO-HH) model. Furthermore, some adjustments to these models are proposed, and the effect of reducing the memory size is investigated. We first propose a new realistic formulation for Fo-LIF model to better describe its functionality that is aligned