The rapid growth of cities and their inflation is a big problem, especially in the last years. this growth is accompanied by such problems like population growth, housing need, low level of services, random expansion, traffic congestion as well as pollution of the environment, which leads to a decline in the quality of life in Baghdad, the population are concentration in Baghdad therefore that leads to imbalance of development among cities and productive concentration for service projects in a mega cities, causing migration from other provinces In search of a better life. The main objective of the new cities is to relieve pressure on major cities and guide the growth of cities. Basmaya city it’s a new city project adopted f

The current study had investigated how specific physiological parameters and the endurance of offensive skills of elite Iraqi badminton players are influenced using preparatory phase training. The study used a systematic experimental research design to determine the impact of high-intensity interval exercise (HIIE) on technical accuracy and movement efficiency. Maximal oxygen uptake (VO 2 max), blood lactate levels, and other salient physiological variables were taken before and after training. The results indicated that VO 2 max was significantly increased and lactate was reduced which indicated an increase in aerobic and anaerobic capacity. There was also an increased offensive physical endurance among the participants, increased shot eff

Despite all the possibilities held by Iraq for the production of poultry , but there is low and clear in the level of production and a rise in costs and a decline in per capita consumption is due to a number of reasons, including poor investment , stop government subsides , dumping policies , market Bolmottagat imported , the contribution of the merchant squandering of national capacity , weak base material for the growth of this sector , the security situation and the crisis of energy and others .

Despite all this research has shown that there are great investment opportunities in this very sector of the market size and absorptive capacity of his and the growth of per capita income  and level of cul

The research aims to identify the impact of the visual teaching strategy by using infographics mathematics achievement for intermediate grade students. The experimental research method was adopted, as the experimental design of two independent and equal groups with a post test was used, whereas the experiment was applied on a sample consisting of (52) male students from first- intermediate grade students in (Al-Haq Al-Mubin intermediate school for Boys) of the General Directorate in Anbar Governorate - Department Education in Fallujah for the academic year (2021-2022), and the research sample was distributed equally on the two research groups, and Division (B) was chosen randomly to be the experimental group, while Division (A) was the cont

            This research aims to explore the impact of strategic  intelligence by his dimensions (Foresight , system thinking, vision, motivation and partnership) on decision making styles which represented by ( rational, intuitive, dependent, Spontaneous and  Avoidant style) for a sample of the administrative leaders in the center of  Reconstruction &Housing Ministry and Some its formations which are companies of (Sa'ad, Al Mansour, al Farouq, Assyria, al-Mu'tasim, al- Rasheed, and Public Authority for Housing).  So to achieve the  research objectives and to test hypotheses, it has been relying

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

This paper introduces a novel nonparametric hybrid cyber-intelligence-based statistical process control and anomaly detection framework in time series data. It is developed to overcome the shortcomings of the classical control schemes in dealing with complex, abnormal, and noisy input data, especially when it is autocorrelated. The proposed methodology combines three technical pillars: First, it utilizes a bidirectional long-short-term memory architecture (Bi-LSTM) to capture long-term time dependency and learn nonlinear patterns, leaving only true deviations as residuals that remove trends and noises from the market. Second, it adopts the Golden Eagle Optimizer (GEO) algorithm for optimal parameter selection. This intelligent algor

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

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm