Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)
The application of pultruded (GFRP) composite has become increasingly prominent in civil infrastructure projects. This study provides a comprehensive analysis of experimental and numerical studies conducted on the mechanical characteristics of (GFRP) composites across various temperature conditions, encompassing ambient and fire scenarios. The compilation comprises over 100 scholarly articles that examine the mechanical behavior of (GFRP) materials, specifically emphasizing their tensile and compressive strengths, showed the mechanical properties of (GFRP) materials are commonly compromised when exposed to high temperatures that approach or surpass the resin's glass transition temperature (Tg). In contrast, temperatures that are low
... Show MoreEco-friendly materials are increasingly used in civil engineering to support sustainable development. Conventional concrete relies heavily on Ordinary Portland Cement (OPC), the production of which contributes significantly to the carbon dioxide (CO₂) emissions. Ground Granulated Blast Furnace Slag (GGBFS) and fly ash can partially replace OPC, thereby reducing the environmental impact. This study investigates the effect of basalt fiber incorporation on the mechanical properties of geopolymer lightweight concrete. The concrete mixtures consisted of fly ash, slag, pumice aggregate, sand, and an alkaline activator prepared by combining sodium hydroxide and sodium silicate. The mix design included an activator-to-binder ratio of 0.45
... Show MoreConveyor belt systems facilitate the movement of goods and materials, making them an essential part of various fields. Deep learning control methods are therefore indispensable to assure their energy efficiency and optimal motor speed. Here, training is conducted via a convolutional neural network with transfer learning using VGG16 base net. Feature extraction layers are fixed, whilst fully connected layers are replaced. Thirty-three appropriate object classes are considered for classification, and images are acquired using an overhead camera. The obtained weight values are transmitted to Arduino that uses these data to control the stepper motor speed for optimal performance and minimum energy consumption, achieving approximate esti
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