Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreLifestyle Medicine is the application of evidence-based lifestyle approaches for the prevention, treatment, and even the reversal of lifestyle-related chronic diseases such as diabetes, hypertension, heart disease, obesity, polycystic ovarian diseases, dementia, arthritis, and cancers
A tunable band pass filter based on fiber Bragg grating sensor using an in-fiber Mach-Zender interferometer with dual micro-cavities is presented. The micro-cavity was formed by splicing together a conventional single-mode fiber and a solid core photonic crystal fiber (SCPCF) with simple arc discharge technique. Different parameters such as arc power, length of the SCPCF and the overlap gap between samples were considered to control the fabrication process. The ellipsoidal air-cavity between the two fibers forms Fabry-Perot cavity. The diffraction loss was very low due to short cavity length. Ellipsoidal shape micro-cavities were experimentally achieved parallel to the propagation axis having dimensions of (24.92 – 62.32) μm of width
... Show More<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in
... Show MoreIn this paper, three tool paths strategies; iso-planar, helical and adaptive have been implemented to investigates their effect on the mechanical properties of Brass 65-35 formed by single point incremental sheet metal forming process. To response this task, a fully digital integrated system from CAD modeling to finished part (CAD/CAM) for SPIF process has been developed in this paper.
The photo-micrographs shows an identical grain formation due to the plastic deformation of the incremental forming process, change in the grain shape and size was observed. It's found that the adaptive tool path play a significant role to increase the hardness of the formed specimen from (48 to 90 HV) and the grain texture of the formed specimen found a
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This study presents experimental and numerical investigations on seven one-way, reinforced concrete (RC) slabs with a new technique of slab weight reduction using polystyrene-embedded arched blocks (PEABs). All slabs had the same dimensions, steel reinforcement, and concrete compressive strength. One of these slabs was a solid slab, which was taken as a control slab, while the other six slabs were cast with PEABs. The main variables were the ratio of the length of the PEABs to the length of the slab (lp/L) and the ratio of the height of the PEABs to the total slab depth (hP/H). The minimum decrease in the ultimate load capacity was about 6% with a minimum reduction in the slab weight of 15%. In contrast, the maximum decrease in the
... Show MoreThe present work presents design and implementation of an automated two-axis solar tracking system using local materials with minimum cost, light weight and reliable structure. The tracking system consists of two parts, mechanical units (fixed and moving parts) and control units (four LDR sensors and Arduino UNO microcontroller to control two DC servomotors). The tracking system was fitted and assembled together with a parabolic trough solar concentrator (PTSC) system to move it according to information come from the sensors so as to keep the PTSC always perpendicular to sun rays. The experimental tests have been done on the PTSC system to investigate its thermal performance in two cases, with tracking system (case 1) and without trackin
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