Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

The investigative film is part of the documentary films and is considered one of the important films that have a high viewership by the recipient, which is of great importance in transmitting information and contributing to creating awareness of the community through the advertising function performed by the cinematic image, as the researcher addresses the concept of advertising and its development through the time stages. And advertising functions. Then the researcher dealt in his research with the cinematic technical elements that contribute to the success of the investigative advertising work, such as camera movements, music, sound effects, dialogue ... etc., which enrich the investigative picture with realism and the flow of informat

This paper deals with a central issue in the field of human communication and reveals the roaming monitoring of the incitement and hatred speech and violence in media, its language and its methods. In this paper, the researcher seeks to provide a scientific framework for the nature of the discourse of incitement, hatred speech, violence, and the role that media can play in solving conflicts with their different dimensions and in building community peace and preventing the emergence of conflicts among different parties and in different environments. In this paper, the following themes are discussed:
The root of the discourse of hatred and incitement
The nature and dimensions of the discourse of incitement and hatred speech
The n

The current work is characterized by simplicity, accuracy and high sensitivity Dispersive liquid - Liquid Micro Extraction (DLLME). The method was developed to determine Telmesartan (TEL) and Irbesartan (IRB) in the standard and pharmaceutical composition. Telmesartan and Irbesartan are separated prior to treatment with Eriochrom black T as a reagent and formation ion pair reaction dye. The analytical results of DLLME method for linearity range (0.2- 6.0) mg /L for both drugs, molar absorptivity were (1.67 × 105-    5.6 × 105) L/ mole. cm, limit of detection were (0.0242and0.0238), Limit of quantification were (0.0821and0.0711), the Distribution coefficient were

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

The aim of this paper is to investigate the effects of Nd:YAG laser shock processing (LSP) on micro-hardness and surface roughness of 86400Cu-Zn alloy. X-ray fluorescence technique was used to analyze the chemical composition of this alloy. LSP treatment was performed with a Q-switched Nd: YAG laser with a wavelength of 1064 nm. The results show that laser shock processing can significantly increase. The micro-hardness and surface roughness of the LSP-treated sample. Vickers diamond indenter was used to measure the micro-hardness of all samples with different laser pulse energy and the different number of laser pulses. It is found that the metal hardness can be significantly increased to more than 80% by increasing the laser energy and t