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.
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In the present work a comparative study for thermal and electrical performance of different hybrid photovoltaic/thermal collectors designs for Iraq climate conditions have been carried out. Four different types of air based hybrid PV/T collectors have been manufactured and tested. Three collectors consist of four main parts namely, channel duct, glass cover, axial fan to circulate air and two PV panels in parallel connection. The measured parameters are, the temperature of the upper and the lower surfaces of the PV panels, air temperature along the collector, air flow rate, pressure drop, power produced by solar cell, and climate conditions such as wind speed, solar radiation and ambient temperature. The thermal and hydraulic performances o
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
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Capacitive–resistive humidity sensors based on polythiophene (P3HT) organic semiconductor as an active material hybrid with three types of metallic nanoparticles (NP) (Ag, Al, and Cu) were synthesized by pulsed laser ablation (PLA). The hybrid P3HT/metallic nanoparticles were deposited on indium-tin-oxide (ITO) substrate at room temperature. The surface morphology of theses samples was studied by using field emission scanning electron micrographs (FE-SEM), which indicated the formation of nanoparticles with grain size of about 50nm. The electrical characteristics of the sensors were examined as a function of the relative humidity levels. The sensors showed an increase in the capacitance with variation in the humidity level. Whil
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The need for participants’ performance assessments in academia and industry has been a growing concern. It has attendance, among other metrics, is a key factor in engendering a holistic approach to decision-making. For institutions or organizations where managing people is an important yet challenging task, attendance tracking and management could be employed to improve this seemingly time-consuming process while keeping an accurate attendance record. The manual/quasi-analog approach of taking attendance in some institutions could be unreliable and inefficient, leading to inaccurate computation of attendance rates and data loss. This work, therefore, proposes a system that employs embedded technology and a biometric/ w
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
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This paper presents a numerical simulation of the flow around elliptic groynes by using CFD software. The flow was simulated in a flume with 4m long, 0.4m wide, and 0.175m high with a constant bed slope. Moreover, the first Groyne placed at 1m from the flow inlet with a constant the Groyne height of 10cm and a 1cm thickness, and the width of Groynes equals 7cm. A submergence ratio of the elliptic Groynes of 75% was assumed, corresponding to a discharge of 0.0057m3/sec. The CFD model showed a good ability to simulate the flow around Groynes with good accuracy. The results of CFD software showed that when using double elliptic Groy
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International trade in services is becoming increasingly important as it is an economic activity that deals with invisible trade, which has become increasingly important in the balance of international trade. The establishment of the WTO is a starting point in international trade relations. It is responsible for all aspects of international trade, , And in view of the continued increase in international trade in services, the need for more internationally recognized rules has become more urgent, especially as it has been increasingly proven that the traditional framework of public services is inadequate to operate some of the most dynamic and innovative sectors of the economy. (GATS) to be the regulatory framework for this sector
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The current research aims to identify the effect of the study hand-on strategy on the achievement of the chemistry subject at the first grade students in the government day schools. The Umm al-Mu 'mineen school was chosen by appointment the intentional, so that its student is the research sample of the second Rusafa Directorate for the academic year (2021-2022). Then, two divisions were randomly selected for the first average out of 6 divisions to represent the experimental group that is studying according to the strategy of the thinker hand and the other the control group that is studying according to the usual method. The equivalence of the two research groups was verified by a set of variables represented by (chronological age, previous
... Show MoreThe current research aims to identify the effect of the hands_on strategy on the life effectiveness skills of the first grade students in the government's daytime middle schools. The Umm al-Mu 'minin school was intentionally chosen to be the research sample of the second Rusafa Directorate for the academic year 2021-2022. Then, two divisions were randomly chosen for the first of the six divisions to represent the experimental group that is studying according to the strategy of the hands_on and the other the control group that is studying according to the usual method. The equivalence of the two research groups was verified by a set of variables. The two groups were found to be equivalent. As for the research tool, the life effectiveness sca
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