Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

In the present work the performance of semifluidized bed adsorber was evaluated for removal of phenolic compound from wastewater using commercial activated carbon as adsorbent. P-chlorophenol (4-Chlorophenol) and o-cresol (2-methylphenol) was selected as a phenolic compound for that purpose. The phenols percent removal, in term of breakthrough curves were studied as affected by hydrodynamics limitations which include minimum and maximum semifluidization velocities and packed bed formation in the column by varying various parameters such as inlet liquid superficial velocity (from U_minsf to 8U_minsf m/s), and retaining grid (sometimes referred to as adsorbent loading) to initial static bed height ratio (from 3-4.5). In

Due to the exceedingly high integration density of VLSI circuits and the resulting high power density, thermal integrity became a major challenge. One way to tackle this problem is Dark silicon. Dark silicon is the amount of circuitry in a chip that is forced to switch off to insure thermal integrity of the system and prevent permanent thermal-related faults. In many-core systems, the presence of Dark Silicon adds new design constraints, in general, and on the communication fabric of such systems, in particular. This is due to the fact that system-level thermal-management systems tend to increase the distance between high activity cores to insure better thermal balancing and integrity. Consequently, a designing dilemma is created wh

This article presents an improvement in the properties of environmentally friendly, inexpensive, and readily available surfaces for use in addressing a significant environmental problem: pollution from dyes generated by various industrial processes. The surface of Iraqi flint clay was acidically activated and used to adsorb methyl orange dye from its aqueous solutions. The clay surface was characterized before and after acid activation using several techniques, including Fourier transform infrared spectroscopy, X-ray diffraction spectroscopy, X-ray disperse energy spectroscopy, and field-emission scanning electron microscopy. The adsorption of methyl orange dye using flint clay before and after activation was performed in batch system under

This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w