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 Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

ABSTRACT The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro. In minimal medium, Cells were treated with 32 ug/ml of penicillin G, carbencillin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementations. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and cephalotin Deletion of methionine or asparagine abolished the protec- tion against carbencillin and to a less extent ce

The role of specific amino acids namely cysteine, methionine, threonine and asparagine in the protection provided by vamin solution against B-lactam inhibition to E. coli was evaluated in vitro In minimal medium, cells were treated with 32 ug/ml of penicillin G, carbenciLlin, hostacillin, cloxacillin and cephalotin in the presence of specific amino acid supplementation. Deletion of specific amino acids from the media abolished the protection provided by vamin. Threonine was essential for the protection of cells against all tested antibiotics, while cysteine was essential for protection against carbencillin and sephalotin. Deletion of methionine or asparagine abolished the protection against carbencillin and to a less extent cephalotin.

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Diversity the terms and practice the organizational filed with different concepts and environment, which Iraqi environment part from them. Some organizational in Iraqi environment leave its basic oriented to agreement with the leader desire, their fore this research focus tow basic variable (organizational citizenship behavior & transparence), we supposition which is dependent to explanation the response variable (strategic leadership). The results justification in part and not justification in another part. For example the organizational citizenship behavior effect on some parte of the strategic leadership. The transparence have faraway to fly from the relation with organizational citizenship behavior and strategic leadershi