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

KE Sharquie, AA Noaimi, AF Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 11

Background: Clinicians and investigators consider the normal range of bowel habit and frequency as between 3 to 21 motions per week . Stool frequency out side the normal range may be unusual but may not be abnormal in the sense of a disease . And according to the consistency, the normal stool ranges from porridge like to hard and pellety .Objectives: To establish a basic data about the bowel habits (consistency and frequency) in a sample of healthy Iraqi population; in addition to learn about their definition of constipation and diarrhea.Methods: Prospective study from Jan 2000- Jun 2000 at Al-Yarmouk teaching hospital, Baghdad. Questionnaires were distributed to 950 healthy persons of different age group .The questionnaire included: Det

Clinicians and investigators consider the normal range of bowel habit and frequency as between 3 to 21 motions per week. Stool frequency outside the normal range may be unusual but may not be abnormal in the sense of a disease, and according to the consistency, the normal stool ranges from porridge like to hard and pellety.
Objectives: To establish a basic data about the bowel habits (consistency and frequency) in a sample of healthy Iraqi population; in addition to learn about their definition of constipation and diarrhea.
Methods: Prospective study from Jan 2000- Jun 2000 at Al-Yarmouk teaching hospital, Baghdad. Questionnaires were distributed to 950 healthy persons of different age group .The questionnaire included: Detailed hi

Background: The risk of antibiotics resistance (AR) increases due to excessive of antibiotics either by health care provider or by the patients.

Objective: The assessment of the self-medication Practice of over the counter drugs and other prescription drugs and its associated risk factor.

Subjects and Methods: Study design: A descriptive study was conducted from “20th December 2019 to 08th January 2021”. A pre validated and structured questionnaire in English and Urdu language was created to avoid language barrier including personal detail, reasons and source and knowledge about over the counter drugs and Antibiotics. Sample of the study was randomly selected.

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

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification