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

Corrosion occurs in all sectors including oil pipelines, drinking water and sewerage in the majority of cases linked to corrosion of steel. Good corrosion management includes optimising corrosion control actions and minimising lifecycle corrosion costs whilst meeting environmental goals. The toxicity of commonly used synthetic inhibitors are the subject of recent legislations (REACH and PARCOM) have led to search on more eco-friendly corrosion inhibitors. Extensive research is conducted to assess the corrosion inhibition rate of diverse green inhibitors. However, it was not adequately

In this study, we propose the possibility of generating several parallel and independent random bitstreams from the time-varying optical emission spectra of an atmospheric pressure air microplasma system. This is achieved by splitting the plasma arc emission into discrete wavelengths using an optical spectrometer and then monitoring the fluctuating intensities of each wavelength as an independent time series. As a proof of concept, we considered eight wavelengths centered at 377.8, 389.1, 425.8, 591.4, 630.5, 673.0, 714.2, and 776.4 nm corresponding to atomic emissions lines from species

Complex systems are pervasive in many areas of science. With the increasing requirement for high levels of system performance, complex systems has become an important area of research due to its role in many industries. Advances in System Dynamics and Control provides emerging research on the applications in the field of control and analysis for complex systems, with a special emphasis on how to solve various control design and observer design problems, nonlinear systems, interconnected systems, and singular systems. Featuring coverage on a broad range of topics, such as adaptive control

Doubly Fed Induction Generator (DFIG) based on wind turbines demand a high degree of reliability and availability and they are characterized by expensive and safety critical maintenance work. This paper deals with a new strategy for detection and estimation of current sensor faults in the stator and rotor of a DFIG. First, a state space model of a DFIG is developed based on voltages and flux equations, which can be used in order to estimate states and to generate residuals by using a Luenberger observer. Then, the residuals results are exploited for faults detection and estimation. Finally

New hybrid Eulerian/Lagrangian model is presented accounting for the two-way coupling between the pulsating blood flow and the artery deformability. The Streamline-Upwind/Petrove--Galerkin (SUPG) finite element technique is used to treat for the convective nature of the momentum equation. The deformability of the artery walls is accounted for by treating the wall as an elastic beam under transverse unsteady distributed load, namely the fluid pressure. The results of the present contribution compare well against the available published data. © 2019, Isfahan University of Technology.

Inflatable structures are characterized by being light and easy to manufacture and deploy. Hence, they find many applications in aerospace and aeronautical engineering. In this paper, an inflatable segment with a The National Advisory Committee for Aeronautics (NACA) 0021 airfoil cross-section is designed, fabricated, and tested. The geometrical accuracy of the manufactured inflatable segment is measured using laser scanning. Measurements show that the average normalized error of the chord length and thickness are 2.97% and 0.554%, respectively. The aerodynamic behavior of the inflatable

Recently, unmanned aerial vehicles (UAVs), also known as drones, have gained widespread interest in civilian and military applications, which has led to the development of novel UAVs that can perform various operations. UAVs are aircraft that can fly without the need of a human pilot onboard, meaning they can fly either autonomously or be remotely piloted. They can be equipped with multiple sensors, including cameras, inertial measurement units (IMUs), LiDAR, and GPS, to collect and transmit data in real time. Due to the demand for UAVs in various applications such as precision agriculture

This paper presents a real-time vision framework that detects and tracks vehicles from stationary camera. It can be used to calculate statistical information such as average traffic speed and flow as well as in surveillance tasks. The framework consists of three main stages. Vehicles are first detected using Haar-like features. In the second phase, an adaptive appearance-based model is built to dynamically keep track of the detected vehicles. This model is also used in the third phase of data association to fuse the detection and tracking results. The use of detection results to update the

In this work, we are proposing a silicon (Si) based concentric tube broadband absorber. The proposed broadband absorber is composed of consecutive concentric tubes of intrinsic Si and doped-Si (D-Si) layers. The structure exhibits a broadband performance within a wide range of mid-IR wavelength spectrum extending from 3 to 7 µm with an absorption peak that varies between 0.88 and 0.97 in the case of S-polarized incident light. We report that light coupling to the proposed concentric tube metamaterial absorber structure over a broad wavelength range is a result of exhibiting multiple resonance