A bolted–welded hybrid demountable shear connector for use in deconstructable steel–concrete composite buildings and bridges was proposed. The hybrid connector consisted of a partially threaded stud, which was welded on the flange of a steel section, and a machined steel tube with compatible geometry, which was bolted on the stud. Four standard pushout tests according to Eurocode 4 were carried out to assess the shear performance of the hybrid connector. The experimental results show that the initial stiffness, shear resistance, and slip capacity of the proposed connector were higher than those of traditional welded studs. The hybrid connector was a ductile connector, according to Eurocode 4, with slip capacity higher than 6 mm. A nonli

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

Background: Giant middle cerebral artery (MCA) aneurysms are surgically challenging lesions. Because of the complexity and variability of these aneurysms, a customized surgical technique is often needed for each case. In this article, we present a modified clip reconstruction technique of a ruptured complex giant partially thrombosed middle cerebral artery aneurysm.

Case description: The aneurysm was exposed using the pterional approach. Following proximal control, the aneurysm sac was decompressed. Then, we applied permanent clips to reconstruct the aneurysm neck. The configuration of the aneurysm mandated a tailored clipping pattern to account for resi

Photovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was

In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,