Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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.

Background: The Covid-19 pandemic changed the world; its most important achievement for education was changing the approach from traditional to virtual education. The present study aimed to investigate the role of virtual education networks on mental health of students including personality, beliefs, scientific, and cultural dimensions, in selected countries.Methods: This was an exploratory and applied study. According to the phenomenology strategy, theoretical saturation occurred after 24 semi-structured and targeted qualitative interviews with teachers from Iran, Iraq, Syria and Lebanon, in 2023. Quantitative data was collected through a researcher-made online questionnaire with 423 participants. Teachers with at least a Bachelor’s degr

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

Diarrhea is one of the most commonly encountered minor ailments in the community pharmacies. It is associated with significant morbidity and mortality. However, the majority of pharmacists in Iraq did not manage diarrheal cases in a proper way. Therefore, the current study aimed to evaluate the benefit of a new mobile application (diarrhea management step by step) to improve the pharmacist's role in the management of diarrhea. The study was conducted from 21th September to 21th October 2021 using a pre-post design via a simulated patient (SP) technique. A validated diarrhea scenario was presented to each pharmacist by the SP twice, once before and the other after giving the mobile application to the pharmacist. Furthermore, pharmaci

In this research, has been to building a multi objective Stochastic Aggregate Production Planning model for General al Mansour company Data with Stochastic  demand under changing of market and uncertainty environment in aim to draw strong production plans.  The analysis to derive insights on management issues regular and extra labour costs and the costs of maintaining inventories and good policy choice under the influence medium and optimistic adoption of the model of random has adoption form and had adopted two objective functions total cost function (the core) and income and function for a random template priority compared with fixed forms with objective function and the results showed that the model of two phases wit

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of