Most studies and research have tried to shed light on unemployment and employment in general, with less focus on the problems facing working women and the resulting social and economic consequences that threaten their human and professional lives. For women, working is one of the basic necessities for the sustainability of human life, and it constitutes an essential axis for both sexes and through it. It also gives a person the status and social status where the individual finds a ready opportunity to practice his intentions and desires, test his abilities and talents, and achieve his ambitions. The availability of full employment in general and the joining of women to the labor market is an important and fundamental factor in the sustai

There is a theoretical controversy in the books of Usul al-Fiqh, in the past and the present, about whether the ruling should be attached to its reason (al-Hikmah), or its apparent and stable cause (al-Illah). Looking at the practical cases of the jurists, we found them sometimes attaching rulings to its reason, and sometimes to its cause, so there is a need to know the factors that affect their choices. By extrapolation, the researcher reached at nine factors that affect referring the ruling to its cause or to its reason in jurisprudential cases.

Abstract

  Bivariate time series modeling and forecasting have become a promising field of applied studies in recent times. For this purpose, the Linear Autoregressive Moving Average with exogenous variable ARMAX model is the most widely used technique over the past few years in modeling and forecasting this type of data. The most important assumptions of this model are linearity and homogenous for random error variance of the appropriate model. In practice, these two assumptions are often violated, so the Generalized Autoregressive Conditional Heteroscedasticity (ARCH) and (GARCH) with exogenous varia

The aim of this paper is to derive a posteriori error estimates for semilinear parabolic interface problems. More specifically, optimal order a posteriori error analysis in the - norm for semidiscrete semilinear parabolic interface problems is derived by using elliptic reconstruction technique introduced by Makridakis and Nochetto in (2003). A key idea for this technique is the use of error estimators derived for elliptic interface problems to obtain parabolic estimators that are of optimal order in space and time.

Polarization manipulation elements operating at visible wavelengths represent a critical component of quantum communication sub-systems, equivalent to their telecom wavelength counterparts. The method proposed involves rotating the optic axis of the polarized input light by an angle of 45 degree, thereby converting the fundamental transverse electric (TE0) mode to the fundamental transverse magnetic (TM0) mode. This paper outlines an integrated gallium phosphide-waveguide polarization rotator, which relies on the rotation of a horizontal slot by 45 degree at a wavelength of 700 nm. This will ultimately lead to the conception of a mode hybridization phenomenon in the waveguide. The simulation results demonstrate a polarization co

The research work is "The passive voice as a grammatical phenomenon in four selected textbooks". The research deals with the grammatical phenomenon passive in German. The research consists of two parts, the theoretical and the empirical part. The present research work is divided into 3 sections:

The first section includes the definition of passive, passive types, process passive, state passive, passive with modal verbs, and other types of passive. The second section provides illustrations of the four selected textbooks. The third chapter presents the passive voice in textbooks, namely German language teaching for foreigners by Dora Schulz and Heinz Griesbach, Delfin von Aufderstrasse H. and others, Em von Balme, M. and others and

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a