A large number of researchers had attempted to identify the pattern of the functional relationship between fertility from a side and economic and social characteristics of the population from another, with the strength of effect of each. So, this research aims to monitor and analyze changes in the level of fertility temporally and spatially in recent decades, in addition to estimating fertility levels in Iraq for the period (1977-2011) and then make forecasting to the level of fertility in Iraq at the national level (except for the Kurdistan region), and for the period of (2012-2031). To achieve this goal has been the use of the Lee-Carter model to estimate fertility rates and predictable as well. As this is the form often has been familiar

Abstract

This study aims to identify the degree to which the first cycle teachers use different feedback patterns in the E-learning system, to identify the differences in the degree of use according to specialization, teaching experience, and in-service training in the field of classroom assessment as well as the interaction between them. The study sample consisted of (350) female teachers of the first cycle in the governmental schools in Muscat Governorate for the academic year 2020/2021. The study used a questionnaire containing four different feedback patterns: reinforcement, informative, corrective, and interpretive feedback. The psychometric properties of the questionnaire were verified in terms of validity

The research aims to reveal the impact of media policy in Iraqi media outlets on the level of objectivity in these outlets. A study from the communicators’ point of view where the researcher used a survey method on the communicators in media outlets to reveal the extent of media policies knowledge as well as the pressures exerted by this policy on communicators in media outlets. It also reveals the extent of their commitment to objectivity, neutrality in dealing with information and the way used to transfer it.
The research sample included (179) respondents from communicators in a range of Media outlets such as (Press, Radio, and Television), The researcher was careful with the diversity of the sample, and

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim

Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation

To damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. Double input multiband Power system stabilizers (PSSs) were used to damp out low-frequency oscillations in power system. Among dual-input PSSs, PSS4B offers superior transient performance. Power system simulator for engineering (PSS/E) software was adopted to test and evaluate the dynamic performance of PSS4B model on Iraqi national grid. The results showed

Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security