The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

   With increasing population and development, the resources of fossil fuels decreased, leading to the need to find alternative sources of energy. Furthermore, the use of fossil fuels is accompanied by several downsides including environmental fatality associated with toxic gas emissions from diesel engines and continuous increase of the price of diesel fuel. Biodiesel is one of the most important types of renewable energy that replaces the fossil fuel requirement (mineral diesel) and maintains eco-friendly sustainability. Calcium is an essential plant nutrient as it plays an important role in the formation of plant cell walls and membranes. Therefore, the fallen leaves of mango tree can be utilized to produce nano calcium oxide a

The purpose of this research is to analyze the relationship between the emotional intelligence and the leadership personality of the managers . the research was tested at the college of administration and economics – university of Baghdad through applying it on a sample of (67) members and units of the college. a questionnaire was used as a major tool for collecting data and information . for the purpose of researching to conclusion, the research aimed to test two main hypotheses related to the correlation coefficient and the effect correlation between the two main variable of the research, some statistical techniques such as (the mean, student deviation, percentages, correlation coefficient spearman, simple regression) were us

The following list comprises sixty-one species and subspecies of coccine¬llid beetles belonging to twenty-two genera distributed among six tribes in three subfamilies. All the species and subspecies have been recorded for Iraq. The categories have been arranged systematically according to Korschefsky's (1931) catalogue.

The aim of this paper is to estimate a nonlinear regression function of the Export of the crude oil Saudi (in Million Barrels) as a function of the number of discovered fields.

 Through studying the behavior of the data we show that its behavior was not followed a linear pattern or can put it in a known form so far there was no possibility to see a general trend resulting from such exports.

We use different nonlinear estimators to estimate a regression function, Local linear estimator, Semi-parametric as well as an artificial neural network estimator (ANN).

The results proved that the (ANN) estimator is the best nonlinear estimator am

Tigris River water that comes from Turkey represents the main water resource of this river in Iraq. The expansion in water river implementations has formed a source of trouble for the workers in the water resources management field in Iraqi. Unfortunately, there is no agreement between Iraq and Turkey till now to share the water of this international river. Consequently, the optimal operation of water resources systems, particularly a multi-objective, multi-reservoir, is of the most necessity at the present time.

 In this research two approaches, were used the dynamic programming (DP) approach and simulation model to find the optimal monthly operation of Ilisu Dam (from an Iraqi point of view) through a comp

A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp