This study investigates the impact of agricultural investment policy—represented by agricultural loans and investment allocations—on rice crop production in Iraq over the period 2003–2023, employing the Autoregressive Distributed Lag (ARDL) model. Using time-series econometric analysis, the study confirms a short-term positive and statistically significant effect of financial support on rice output, while revealing statistically insignificant long-term effects. The presence of a cointegration relationship suggests long-term equilibrium between agricultural policy variables and rice production. However, the absence of causality in the Yamamoto-Toda test implies that structural and institutional inefficiencies may dilute the long-term i

Presupposition is the background belief that is known by both the speaker and the addressee, it is tied to particular words and aspects of the surface structure that act as linguistic triggers. The present study aims at investigating whether Iraqi fourth -year university students are able to recognize the English presuppositions through the meaning of these linguistic triggers .To fulfil the basic requirements of the study, the researcher has conducted a test . The results of the study have validated the hypothesis of the work and it is found that the linguistic triggers are important tools in recognizing presuppositions.    

This experiment was conducted to evaluate the effect of foliar spraying with gibberellic acid concentrations (0,50,100)mg.L­¹ and proline acid concentrations (0, 25, 50)mg.L­¹ and their interactions on some growth parameters of pea plant using clay pots in the botanical garden of Biology Department College of Education for pure science Ibn –Al-Haitham ,Baghdad University, for the growing season 2012-2013 the experiment involved the studing of some growth parameters as plant?s height, dry weight, wt. of pods.plant­¹, biology yield and the concentration of some major elements (nitrogen, phosphorus and calcium) in plant?s seeds. The experiment was designed according to Completely Randomized Desig(CRD) with three replications. R

A lab-scale packed Bio film reactor was used for ethanol production by fermentation of sugar solution using a local
isolated yeast saccharomyces cerevisia and glutaraldelryde on gelating as a covalent bounding agent. In this study four
types of packing in the reactor were used. They are; polypropylene mesh, glass rashig rings, ceramic rashig rings and
glass beads. Glucose solutions were used as substrate with four concentrations; (5, I 0, I 5, 20 g/l). Results show that the
ethanol productivity was increase with increasing sugar concentration. Also it was found that polypropylene mesh
packing give the highest productivity while glass beads gives the lowest productivity. The experiments were conducted at
three temperatur

Quality control charts are limited to controlling one characteristic of a production process, and it needs a large amount of data to determine control limits to control the process. Another limitation of the traditional control chart is that it doesn’t deal with the vague data environment. The fuzzy control charts work with the uncertainty that exists in the data. Also, the fuzzy control charts investigate the random variations found between the samples. In modern industries, productivity is often of different designs and a small volume that depends on the market need for demand (short-run production) implemented in the same type of machines to the production units. In such cases, it is difficult to determine the contr

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition