Industries copper a craft that requires precision and patience great in the processes of industrialization and execution of product launches brass designs and a variety of forms , and the goal of research into the possibility of the use of modern technologies in the development of industries copper local , and identifies research study models of industries copper local to the city of Baghdad , and are available in the markets for the period from (200 - 2011) , Chapter II Multi industries copper local and technical in the copper industry , and after analysis models the sample was the most important conclusions : can work forms a multi- product copper formations deep or window using the technique work motifs and patterns. - formations deco

The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

The efficiency of Nd:YAG laser radiation in removing debris and smear layer from prepared root
canal walls was studied. Fifty-seven human extracted single rooted anterior teeth were divided into three
groups. A group that was not lased is considered as a control group. The remaining teeth were exposed to
different laser parameters regarding laser energy, repetition rate and exposure time. For the case of the set of
parameters of 7 mJ laser energy, the cleaning was maximum at 3 p.p.s. repetition rate for 3 seconds exposure
time for, the coronal, middle and apical thirds. Above and below this energy level, there was an overdose
(melting) or under dose (no effect). Nevertheless for 10mJ laser energy case, the cleaning effi

The propagation of laser beam in the underdense deuterium plasma has been studied via computer simulation using the fluid model. An appropriate computer code “HEATER” has been modified and is used for this purpose. The propagation is taken to be in a cylindrical symmetric medium. Different laser wavelengths (1 = 10.6 m, 2 = 1.06 m, and 3 = 0.53 m) with a Gaussian pulse type and 15 ns pulse widths have been considered. Absorption energy and laser flux have been calculated for different plasma and laser parameters. The absorbed laser energy showed maximum for  = 0.53 m. This high absorbitivity was inferred to the effect of the pondermotive force.

The exponential growth of audio data shared over the internet and communication channels has raised significant concerns about the security and privacy of transmitted information. Due to high processing requirements, traditional encryption algorithms demand considerable computational effort for real-time audio encryption. To address these challenges, this paper presents a permutation for secure audio encryption using a combination of Tent and 1D logistic maps. The audio data is first shuffled using Tent map for the random permutation. The high random secret key with a length equal to the size of the audio data is then generated using a 1D logistic map. Finally, the Exclusive OR (XOR) operation is applied between the generated key and the sh

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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