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.
Tolerance and its impact on building society
This paper deal with the estimation of the shape parameter (a) of Generalized Exponential (GE) distribution when the scale parameter (l) is known via preliminary test single stage shrinkage estimator (SSSE) when a prior knowledge (a0) a vailable about the shape parameter as initial value due past experiences as well as suitable region (R) for testing this prior knowledge.
The Expression for the Bias, Mean squared error [MSE] and Relative Efficiency [R.Eff(×)] for the proposed estimator are derived. Numerical results about beha
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In this paper we describe several different training algorithms for feed forward neural networks(FFNN). In all of these algorithms we use the gradient of the performance function, energy function, to determine how to adjust the weights such that the performance function is minimized, where the back propagation algorithm has been used to increase the speed of training. The above algorithms have a variety of different computation and thus different type of form of search direction and storage requirements, however non of the above algorithms has a global properties which suited to all problems.
Abstract
In order to determine what type of photovoltaic solar module could best be used in a thermoelectric photovoltaic power generation. Changing in powers due to higher temperatures (25oC, 35oC, and 45oC) have been done for three types of solar modules: monocrystalline , polycrystalline, and copper indium gallium (di) selenide (CIGS). The Prova 200 solar panel analyzer is used for the professional testing of three solar modules at different ambient temperatures; 25oC, 35oC, and 45oC and solar radiation range 100-1000 W/m2. Copper indium gallium (di) selenide module has the lowest power drop (with the average percent
... Show MoreThe adhesion strength between Polyethylene (PE) film and Aluminum surface by using the adhesive material (Cyanoacrylate) has been studied. Aluminum (Al) was used as a substrate, and polyethylene (PE) was used as a film adhered to the Al surface. Standard specimens were prepared to use in the peeling test in dry condition, other specimens were immersed in water for 12 days at room temperature. the results for the specimens in the dry condition had shown that high value in the peel force and the peel energy, the peel force was 0.38*103 N/m and the peel energy was 0.605*103 N/m, peeling the film from Al surface leaves a residual of the adhesive material on both adherend, the failure for this specimen were combination of adhesive and cohesive f
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The sintering behavior of Alumina was investigated by adding TiO2. The addition of TiO2 lowered the sintering temperature of the Alumina compared with those of pure Alumina. The result suggests that TiO2 acts as an activator for sintering of Alumina. Water absorption, apparent porosity and density were examined for both pure and TiO2 added to Alumina samples. The variations of sintering behavior were discussed in terms of shrinkage, porosity, water absorption and density. Thermal shock resistance was also examined. In term of this work, the way of improving the thermal shock resistance in oxide- based materials by adding reactive Titania powder to the Alumina samples. The laboratory results showed an improvement in thermal shock resistance
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This study sought to determine malformation caused by Ochratoxin-A (OTA) on mouse embryos. Twenty adult female white Swiss mice (mus msculus) were divided into four groups, with five females per group, and with one male placed with two females in a cage. Avaginal plug was observed in the early morning and the day of mating was considered as day of pregnancy followed by the first day of pregnancy. Three sub lethal concentrations of OTA were applied to the respective groups (other than the control), 1mg/kg, 2mg/kg and 4mg/kg. The animals were given 0.1 ml per 10 gm body weight per concentration of OTA once a day during days 7-14 of pregnancy. The control group animals were given distilled water. The pregnant mice were dissected, and the embry
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In this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.
This paper deals with the F-compact operator defined on probabilistic Hilbert space and gives some of its main properties.
Relation on a set is a simple mathematical model to which many real-life data can be connected. A binary relation on a set can always be represented by a digraph. Topology on a set can be generated by binary relations on the set . In this direction, the study will consider different classical categories of topological spaces whose topology is defined by the binary relations adjacency and reachability on the vertex set of a directed graph. This paper analyses some properties of these topologies and studies the properties of closure and interior of the vertex set of subgraphs of a digraph. Further, some applications of topology generated by digraphs in the study of biological systems are cited.
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