Two novel demountable shear connectors for precast steel-concrete composite bridges are presented. The connectors use high-strength steel bolts, which are fastened to the steel beam with the aid of a special locking configuration that prevents slip of bolts within their holes. Moreover, the connectors promote accelerated construction and overcome typical construction tolerances issues of precast structures. Most importantly, the connectors allow bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (3) steel beams can be replaced, while precast decks and shear connectors can be reused. A series of push-out tests and a beam test were conducted to assess the behavior of the connectors and quantify the effect of important parameters. The experimental results showed that shear resistance and slip capacity can reach 2.5 and 2.7 times respectively of those of welded shear studs along with superior stiffness and strength against slab uplift. Additionally, shear stiffness of M16 mm LNSC was equal to that of M19 mm welded studs. Identical tests reveal negligible scatter in the shear load – slip displacement behavior. Design equations are proposed to predict the shear resistance with minimum deviations.
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
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Background: Currently there are four general approaches to correct refractive errors: refractive corneal surgery, crystalline lens surgery and implantation of an intraocular lens in anterior or posterior chamber. Aim: To evaluate the predictability, safety and stability of toric phakic implantable collamer lens implantation to correct moderate to high myopic astigmatism. Methods: Sixty eyes of 40 patients underwent implantation of a toric implantable collamer lens (V4c design) in the Eye Specialty Private Hospital, Baghdad, Iraq were studied. The mean spherical refraction was -11.32±3.17 diopter (D) with a range of -6.00 to -18.00 D and a mean cylinder of -2.61±1.16 with range of -1.00 to -5.50 D. The outcome measures that evaluat
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Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking rob
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