This paper presents an experimental study for the structural performance of reinforced concrete (RC) exterior beam–column joints rehabilitated using carbon-fiber-reinforced polymer (CFRP). The present experimental program consists of testing 10 half-scale specimens divided into three groups covering three possible defects in addition to an adequately detailed control specimen. The considered defects include the absence of the transverse reinforcement within the joint core, insufficient bond length for the beam main reinforcement and inadequate spliced implanted column on the joint. Three different strengthening schemes were used to rehabilitate the defected beam–column joints including externally bonded CFRP strips and sheets in addition to near surface mounted (NSM) CFRP strips. The failure criteria including ultimate capacity, mode of failure, initial stiffness, ductility and the developed ultimate strain in the reinforcing steel and CFRP were considered and compared for each group for the control and the CFRP-strengthened specimens. The test results showed that the proposed CFRP strengthening configurations represented the best choice for strengthening the first two defects from the viewpoint of the studied failure criteria. On the other hand, the results of the third group showed that strengthening the joint using NSM strip technique enabled the specimen to outperform the structural performance of the control specimen while strengthening the joints using externally bonded CFRP strips and sheets failed to restore the strengthened joints capacity.

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A smart vehicle should be able to monitor the actions and behaviors of the human driver to provide critical warnings or intervene when necessary. Recent advancements in deep learning and computer vision have shown great promise in monitoring human behavior and activities. While these algorithms work well in a controlled environment, naturalistic driving conditions add new challenges such as illumination variations, occlusions, and extreme head poses. A vast amount of in-domain data is required to train models that provide high performance in predicting driving related tasks to effectively monitor driver actions and behaviors. Toward building the required infrastructure, this paper presents the multimodal driver monitoring (MDM) dataset, which was collected with 59 subjects that were recorded performing various tasks. We use the Fi-Cap device that continuously tracks the head movement of the driver using fiducial markers, providing frame-based annotations to train head pose algorithms in naturalistic driving conditions. We ask the driver to look at predetermined gaze locations to obtain accurate correlation between the driver's facial image and visual attention. We also collect data when the driver performs common secondary activities such as navigation using a smart phone and operating the in-car infotainment system. All of the driver's activities are recorded with high definition RGB cameras and a time-of-flight depth camera. We also record the controller area network-bus (CAN-Bus), extracting important information. These high quality recordings serve as the ideal resource to train various efficient algorithms for monitoring the driver, providing further advancements in the field of in-vehicle safety systems.

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This paper presents the experimental findings for different strengthening techniques applied on defected reinforced-concrete cantilever slabs to restore lost flexural capacities owing to insufficient bond length of the main tensile steel. The restoration technique was based on compensation of the main tensile steel by near-surface mounted steel bars, externally bonded steel plates or externally bonded carbon fibre-reinforced polymer sheets. In addition, new hybrid techniques are presented, which merge the traditional techniques with a 20 mm thick ultra-high-performance strain-hardening cementitious composites (UHP-SHCC) layer. It was found that the strengthening technique based on the embedded steel bars on the UHP-SHCC overlay enabled the strengthened slab to restore its lost capacity and outperformed it by about 5% compared to that of the properly detailed slab. Nevertheless, this restoration was at the expense of the exhibited ductility. Conversely, the strengthening technique based on the application of externally bonded steel plates on a transition layer of the UHP-SHCC material enabled the strengthened slab to restore the lost capacity by about 96% as well as to outperform its ductility by more than 29% compared to those of the properly detailed slab.

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Impact loading could impair the entire structure or a part of it, thus making the human life at stake. In this study, to improve the impact resistance of reinforced concrete slabs under drop-weight loading, a thin layer of strain-hardening cementitious composites was added at either tension or compression side of the slab. The main parameter of this study was the three contact surface conditions, namely grinding, grinding plus steel dowels, and grinding plus epoxy adhesive, between the substrate slab and the strain-hardening cementitious composites layer. Therefore, 63 reinforced concrete slabs were prepared and tested under the effect of drop-weight falling from three different heights: 1, 1.5, and 2 m. In addition, for comparison purposes, additional seven slabs were tested under central incremental static loading until failure is presented. It was found that the strain-hardening cementitious composites–strengthening layer enhanced the impact and static response of the strengthened slabs when added at either tension or compression side. Besides, to achieve the outermost impact resistance showing ductile performance, it is better to provide a thin layer of the strain-hardening cementitious composites at the tension side of the slab connected to the substrate slab by epoxy resin applied on pre-prepared grinded surface.