Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor the removal of brain sections can be addressed in the subsequent steps, resulting in an unfixed mistake during further analysis. Therefore, accurate skull stripping is necessary for neuroimaging diagnostic systems. This paper proposes a system based on deep learning and Image processing, an innovative method for converting a pre-trained model into another type of pre-trainer using pre-processing operations and the CLAHE filter as a critical phase. The global IBSR data set was used as a test and training set. For the system's efficacy, work was performed based on the principle of three dimensions and three sections of MR images and two-dimensional images, and the results were 99.9% accurate.
This article presents a new cascaded extended state observer (CESO)-based sliding-mode control (SMC) for an underactuated flexible joint robot (FJR). The control of the FJR has many challenges, including coupling, underactuation, nonlinearity, uncertainties and external disturbances, and the noise amplification especially in the high-order systems. The proposed control integrates the CESO and SMC, in which the CESO estimates the states and disturbances, and the SMC provides the system robustness to the uncertainty and disturbance estimation errors. First, a dynamic model of the FJR is derived and converted from an underactuated form to a canonical form via the Olfati transformation and a flatness approach, which reduces the complexity of th
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
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Incorporating waste byproducts into concrete is an innovative and promising way to minimize the environmental impact of waste material while maintaining and/or improving concrete’s mechanical characteristics and strength. The proper application of sawdust as a pozzolan in the building industry remains a significant challenge. Consequently, this study conducted an experimental evaluation of sawdust as a fill material. In particular, sawdust as a fine aggregate in concrete offers a realistic structural and economical possibility for the construction of lightweight structural systems. Failure under four-point loads was investigated for six concrete-filled steel tube (CFST) specimens. The results indicated that recycled lightweight co
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
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In this work we fabrication holographic optical element diffraction grating thickness 40?m and mirror90?m by using dichromated gelatin,to perform that we have to use the Nd-yaG laser doubling frequency of wavelenght (532)nm and its powers of (80)mWatt.we have studyed the thickness and concentration dichromat effect in mirror reflaction ,effect of angle of reconstruction beam in band width and diffraction efficiency ,study effect gelatin hardener of the diffraction efficiency.
As the banking sector is a strong influence on the country's economic growth,The solid financial well-being of anybank does not mean only a guarantee for its investors, It is also important for both owners and workers and for theeconomy in all its joints.The elements of capital adequacy and quality of assets are important to the functioning of thebanking business.In this study, the research sample included four private banks. Quarterly data were used for the period(2011 - 2018).Moreover, data is also collected from articles, papers, the World Wide Web (the Internet) and specializedinternational journals.In this research, an effort was made to try to find out the effect of (the ratio of the capital owned todeposits on the value of the bank),
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Anew mathematical formula was proposed to describe the behavior of the extinction coefficient as a function of ambient temperature and wavelengths for some of infrared materials. This formula was derived depending on some experimental data of transmittance spectrum versus wavelengths for many ambient temperatures. The extensive study of the spectrum characteristics and depending on Bose-Einstein distribution led to derive an equation connecting the extinction coefficient or the absorption coefficient with the ambient temperature and wavelengths of the incident rays. The basic assumption in deriving process is the decreasing in transmittance value with the increasing temperature which is only due to the changing in extinction coeffi
... Show MoreIn this research, we studied the effect of (β-rays) on the optical properties of pure (PMMA) films prepared by using casting technique, and the optical properties for these films was studied before and after irradiation by recording the Absorption and Transmission spectra for a range of wavelength range (190-1100) nm. and then the absorption and Transmission and the reflectivity, extinction coefficient, refractive index, and real and imaginary parts of dielectric constant was studied
The process of discovering pharmaceuticals is of great importance in our contemporary life, in a way that without life becomes almost impossible, as this process is the first building block in the field of pharmaceutical industries to search for new methods and means of treatment and treatment. But in fact, the fact that talking about this process is not that simple and easy, because this process is complicated and difficult in a way that makes it take a time range that in some cases reaches what is permissible ten years to reach a chemical formula that can be used later in the manufacturing process Pharmacokinetics, and during this long period of time, this process will have a set of effects, some of which are specific to the researcher di
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