Nowadays, most of the on-chip plasmonic single-photon sources emit an unpolarized stream of single photons that demand a subsequent polarizer stage in a practical quantum cryptography system. In this paper, we numerically demonstrated the coupling of the light emitted from a quantum emitter (QE) at 700 nm wavelength to the propagation mode supported by an on-chip hybrid plasmonic waveguide (HPW) polarization rotator. Our results proved that the light emitted is linearly polarized at 0º, 45º/−45º, and 90º with propagation lengths of 5 μm, 3.3 μm, and 3.9 μm, respectively. Moreover, high power-conversion efficiency was obtained from an applied transverse magnetic (TM) mode (0º-polarization) to a transverse electric (TE) (90º-polari

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

In the last few years, the Internet of Things (IoT) is gaining remarkable attention in both academic and industrial worlds. The main goal of the IoT is laying on describing everyday objects with different capabilities in an interconnected fashion to the Internet to share resources and to carry out the assigned tasks. Most of the IoT objects are heterogeneous in terms of the amount of energy, processing ability, memory storage, etc. However, one of the most important challenges facing the IoT networks is the energy-efficient task allocation. An efficient task allocation protocol in the IoT network should ensure the fair and efficient distribution of resources for all objects to collaborate dynamically with limited energy. The canonic

One of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed

The main objective of the present work is to find a method increases the efficiency of the airfoil that is used for blade in wind turbine, wing in aircraft, propeller and helicopter (like NACA 4412). By overcoming the separation of flow at high angle of attacks, a slotted airfoil had been used and solved numerically through connecting the pressure side in the bottom surface with the suction side in the top surface of the airfoil to energize the separated flow. Slot exit, width and slope were considered as a parameters of slot configuration to determine the effective design of consideration. Reynolds number was taken as [1.6 x106 ] and the angle of attacks were ranged from (0o - 20o ). The numerical solution with Ansys Fluent commercial prog

This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce