The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Video steganography has become a popular option for protecting secret data from hacking attempts and common attacks on the internet. However, when the whole video frame(s) are used to embed secret data, this may lead to visual distortion. This work is an attempt to hide sensitive secret image inside the moving objects in a video based on separating the object from the background of the frame, selecting and arranging them according to object's size for embedding secret image. The XOR technique is used with reverse bits between the secret image bits and the detected moving object bits for embedding. The proposed method provides more security and imperceptibility as the moving objects are used for embedding, so it is difficult to notice the

The unstable and uncertain nature of natural rubber prices makes them highly volatile and prone to outliers, which can have a significant impact on both modeling and forecasting. To tackle this issue, the author recommends a hybrid model that combines the autoregressive (AR) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models. The model utilizes the Huber weighting function to ensure the forecast value of rubber prices remains sustainable even in the presence of outliers. The study aims to develop a sustainable model and forecast daily prices for a 12-day period by analyzing 2683 daily price data from Standard Malaysian Rubber Grade 20 (SMR 20) in Malaysia. The analysis incorporates two dispersion measurements (I

Preserving the Past and Building the Future: A Sustainable Urban Plan for Mosul, Iraq

In this paper thermo-hydrodynamic characteristics were investigated experimentally for a new type shell-helical coiled tube heat exchanger used as a storage tank of closed loop solar water heater system. Triple concentric helical coils were made of copper tubes of (12.5mm OD and 10mm ID) with coils diameter of (207, 152.2, 97mm) for outer, middle and inner coils respectively. The experiments were carried out during a clear sky days of (March and April 2012). The parameters studied in this work are: history of average temperature of shell side of the storage tank, collector heat gain, heat rejected from coils to shell side of the storage tank, collector efficiency, thermal effectiveness of the heat exchanger (storage tank), and pressure d

Objective: This experiment was conducted to study the effects of ionized water on certain egg quality traits and the levels of proteins and enzymes in the blood of the Japanese quail Coturnix japonica . Materials and Methods: One hundred 42-day-old quail were randomly distributed among five treatment groups with four replicates for each group. The following treatments were used: T1 (control): The birds were provided normal water, T2: The birds were provided alkaline water (pH = 8), T3: The birds were provided alkaline water (pH = 9), T4: The birds were provided acidic water (pH = 6) and T5: The birds were provided acidic water (pH = 5). A Complete Randomized Design (CRD) was used to investigate the effects of the studied treatments on diffe

Ziegler and Nichols proposed the well-known Ziegler-Nichols method to tune the coefficients of PID controller. This tuning method is simple and gives fixed values for the coefficients which make PID controller have weak adaptabilities for the model parameters variation and changing in operating conditions. In order to achieve adaptive controller, the Neural Network (NN) self-tuning PID control is proposed in this paper which combines conventional PID controller and Neural Network learning capabilities. The proportional, integral and derivative (K_P, K_I, K_D) gains are self tuned on-line by the NN output which is obtained due to the error value on the desired output of the system under control. The conventio