This paper presents a proposed neural network algorithm to solve the shortest path problem (SPP) for communication routing. The solution extends the traditional recurrent Hopfield architecture introducing the optimal routing for any request by choosing single and multi link path node-to-node traffic to minimize the loss. This suggested neural network algorithm implemented by using 20-nodes network example. The result shows that a clear convergence can be achieved by 95% valid convergence (about 361 optimal routes from 380-pairs). Additionally computation performance is also mentioned at the expense of slightly worse results.

Abstract

 This study investigated the optimization of wear behavior of AISI 4340 steel based on the Taguchi method under various testing conditions. In this paper, a neural network and the Taguchi design method have been implemented for minimizing the wear rate in 4340 steel. A back-propagation neural network (BPNN) was developed to predict the wear rate. In the development of a predictive model, wear parameters like sliding speed, applying load and sliding distance were considered as the input model variables of the AISI 4340 steel. An analysis of variance (ANOVA) was used to determine the significant parameter affecting the wear rate. Finally, the Taguchi approach was applied to determine

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In

Optimized Link State Routing Protocol (OLSR) is an efficient routing protocol used for various Ad hoc networks. OLSR employs the Multipoint Relay (MPR) technique to reduce network overhead traffic. A mobility model's main goal is to realistically simulate the movement behaviors of actual users. However, the high mobility and mobility model is the major design issues for an efficient and effective routing protocol for real Mobile Ad hoc Networks (MANETs). Therefore, this paper aims to analyze the performance of the OLSR protocol concerning various random and group mobility models. Two simulation scenarios were conducted over four mobility models, specifically the  Random Waypoint model (RWP), Random Direction model (RD), Nomadic Co

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

The aim of the research is to shed light on identifying the extent of the university professor's competencies and their roles in managing and training participants in e-training workshops as a pedagogical point view. The research sample consisted of a group of (30) university professors (lecturers) in the training workshops, in scientific,humanitarian and social disciplines, including (12) a university professor (holding a trainer certificate), , the research methodology is descriptive, and the community is a group of trained participants. (115) participated in (40) e-training workshops organized by the Center for Continuing Education at the University of Baghdad (and the selection of workshops within the researcher's specialization in the

      Storing, transferring, and processing high-dimensional electroencephalogram (EGG) signals is a critical challenge. The goal of EEG compression is to remove redundant data in EEG signals. Medical signals like EEG must be of high quality for medical diagnosis. This paper uses a compression system with near-zero Mean Squared Error (MSE) based on Discrete Cosine Transform (DCT) and double shift coding for fast and efficient EEG data compression. This paper investigates and compares the use or non-use of delta modulation, which is applied to the transformed and quantized input signal. Double shift coding is applied after mapping the output to positive as a final step. The system performance is tested using EEG data files from the C

Omentin (or intelectin) is a main visceral fat secretory adipokine.  There is a growing interest to link omentin, obesity and co-morbidity factors. The aim of the present study is to evaluate serum omentin and its association to insulin resistance biomarkers, lipid profile and atherogenic indies. This cross – sectional study was conducted in Obesity Research and Therapy Unit-Alkindy College of Medicine by recruiting (115) individuals; 49 males /66 females. Subjects between (20 to 60) years of age were selected and classified into two groups according to their Body mass index (BMI). Group1 involved healthy lean volunteers (25 male/ 36 female; BMI 18.5 - 24.9). Group2 involved obese subjects; (24 male / 36 female with BMI ≥ 30). The s

Background: COVID-19 has caused a considerable number of hospital admissions in China since December 2019. Many COVID-19 patients experience signs of acute respiratory distress syndrome, and some are even in danger of dying. Objective: to measure the serum levels of D-dimer, Neutrophil-Lymphocyte count ratio (NLR), and neopterin in patients hospitalized with severe COVID-19 in Baghdad, Iraq. And to determine the cut-off values (critical values) of these markers for the distinction between the severe patients diagnosed with COVID‐19 and the controls. Materials and methods: In this case-control study, we collect blood from 89 subjects, 45 were severe patients hospitalized in many Baghdad medical centers who were diagnosed with COVID

The research aimed to prepare muscle elongation exercises for the arms with high intensity in which the training methods for young blind fencers vary, and to identify the effect of the diversity of muscle elongation exercises for the arms with high intensity on the cellular basal efficiency (lactic acid and sodium bicarbonate) and pulmonary respiration for young blind weapon fencers in terms of sports technology, and the experimental approach was adopted by designing the experimental and equal control groups, and the limits of the research community were represented by young fencers with shish weapon under the age of (20) years in the Army Sports Club, whose number is Total (15) swordsmen, continuing their training for the sports season (20