Several previous investigations and studies utilized silica fume (SF) or (micro silica) particles as supplementary cementitious material added as a substitute to cement-based mortars and their effect on the overall properties, especially on physical properties, strength properties, and mechanical properties. This study investigated the impact of the inclusion of silica fume (SF) particles on the residual compressive strengths and microstructure properties of cement-based mortars exposed to severe conditions of elevated temperatures. The prepared specimens were tested and subjected to 25, 250, 450, 600, and 900 °C. Their residual compressive strengths and microstructure were evaluated and compared with control samples (CS) subjected to similar conditions (the same temperature category). The outcomes indicated that including silica fume particles in mortar mixtures lowered the amount and width of microcracks, upgraded the mass-loss performance, lowered crystalline calcium hydroxide, and reinforced the cement paste, which explained the improvement in residual mechanical strengths.
Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreThe behavior investigation of castellated beams with fiber-reinforced lightweight concrete deck slab as a modified choice for composite steel-concrete beams affected by harmonic load is presented in this study. The experimental program involved six fixed-supported castellated beams of 2140mm size. Three types of concrete were included: Normal Weight Concrete (NWC), Lightweight Aggregate Concrete (LWAC), and Lightweight Fiber-Reinforced Aggregate Concrete (LWACF). The specimens were divided into two groups: the first comprised three specimens tested under harmonic load effect of 30Hz operation frequency for 3 days, then the residual strength was determined through static load application. The second group included three specimens ide
... Show MoreBackground: Studying and investigating the transverse strength(Ts), impact strength(Is), hardness (Hr) and surface roughness(Ra) of conventional and modified autopolymerizing acrylic resin with different weight percentages of biopolymer kraftlignin, after curing in different water temperatures; 40°C and 80°C. Material and Methods: Standard acrylic specimens were fabricated according to ADA specification No.12 for transverse strength, ISO 179 was used for impact testing, Shore D for hardness and profilometerfor surface roughness. The material lignin first dispersed in the monomer, then the powder PMMA is immediately added. Ligninadded in different weight percentages. Then cured using pressure pot (Ivomet) in two temperatures;40°C a
... Show MoreFlying Ad hoc Networks (FANETs) has developed as an innovative technology for access places without permanent infrastructure. This emerging form of networking is construct of flying nodes known as unmanned aerial vehicles (UAVs) that fly at a fast rate of speed, causing frequent changes in the network topology and connection failures. As a result, there is no dedicated FANET routing protocol that enables effective communication between these devices. The purpose of this paper is to evaluate the performance of the category of topology-based routing protocols in the FANET. In a surveillance system involving video traffic, four routing protocols with varying routing mechanisms were examined. Additionally, simulation experiments conduct
... Show MoreUpper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin
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