Non-prismatic reinforced concrete (RC) beams are widely used for various practical purposes, including enhancing architectural aesthetics and increasing the overall thickness in the support area above the column, which gives high assurance to services that this will not result in the distortion of construction features and can reduce heights. The hollow sections (recess) can also be used for the maintenance of large structural sections and the safe passage of utility lines of water, gas, telecommunications, electricity, etc. They are generally used in large and complex civil engineering works like bridges. This study conducted a numerical study using the commercial finite element software ANSYS version 15 for analysing RC beams, hol

The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

This study investigates the impact of varying glass fiber-reinforced polymer (GFRP) stirrup spacing on the performance of doubly GFRP-reinforced concrete beams. The research focuses on assessing the behavior of GFRP-reinforced concrete beams, including load-carrying capacity, cracking, and deformability. It explores the feasibility and effectiveness of GFRP bars as an alternative to traditional steel reinforcement in concrete structures. Six concrete beams with a cross-section of 300 mm (wide) × 250 mm (deep), simply supported on a 2100 mm span, were tested. The beams underwent four-point bending with two concentrated loads applied symmetrically at one-third of the span length, resulting in a shear span (a)-to-depth (h) ratio of 2.

In this study, the effect of fire flame on the punching shear strength of steel fiber reinforced concrete flat plates was experimentally investigated using nine half-scale specimens with dimensions of 1500×1500 mm and a total thickness of 100 mm. The main investigated variables comprised the steel fiber volume fraction 0, 1, and 1.5% and the burning steady state temperature 500 and 600 °C. The specimens were divided into three groups, each group consists of three specimens. The specimens in the first group were tested with no fire effect to be the reference specimens, while the others of the second and third groups were tested after being exposed to fire-flame effect. The adopted characteristics of the fire test were; (one hour) b

A steganography hides information within other information, such as file, message, picture, or video. A cryptography is the science of converting the information from a readable form to an unreadable form for unauthorized person. The main problem in the stenographic system is embedding in cover-data without providing information that would facilitate its removal. In this research, a method for embedding data into images is suggested which employs least significant bit Steganography (LSB) and ciphering (RSA algorithm) to protect the data. System security will be enhanced by this collaboration between steganography and cryptography.

This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.