This research intends to develop a method based on the Artificial Neural Network (ANN) to predict permanent earthquake-induced deformation of the earth dams and embankments. For this purpose, data sets of observations from 152 published case histories on the performance of the earth dams and embankments, during the past earthquakes, was used. In order to predict earthquake-induced deformation o...

Abstract. Various machine learning methods were attempted in the global mapping of surface ocean partial pressure CO2 (pCO2) to reduce uncertainty sink estimate due undersampling pCO2. In previous research, predictors pCO2 usually selected empirically based on theoretic drivers pCO2, and same combination was applied all areas except where there a lack coverage. However, differences between diff...

This paper presents a feed forward back-propagation neural network model to predict the retained tensile strength and design chart in order to estimation of the strength reduction factors of nonwoven geotextiles due to installation process. A database of 34 full-scale field tests were utilized to train, validate and test the developed neural network and regression model. The results show that t...

Groundwater is an essential resource for drinking and agricultural purposes in the Al-Jouf region, Saudi Arabia. The main objective of this study to assess groundwater quality irrigation region. Physicochemical characteristics were determined, including total dissolved solids (TDS), pH, electric conductivity (EC), hardness, various anions cations. index (WQI) was calculated determine suitabilit...

In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as  amount  of  flow  intensity  ratio,  temperature,  residence  time,  and  pH  are  used  as  input  variables  of  the network,  whereas  the  extraction  yield  is  considere...

accommodation of mechanism with human being’s physical characteristics creates the possibility of safe and efficient interaction between human being and robot. regarding the fact that amputation of a limb in human beings causes several mental, economical and social difficulties and problems, need to a substitute limb which has the most efficiency for the person after amputation is a vital need....

non-invasive ultrasound surgeries such as high intensity focused ultrasound have been developed to treat tumors or to stop bleeding. in this technique, incorporation of a suitable imaging modality to monitor and control the treatments is essential so several imaging methods such as x-ray, magnetic resonance imaging and ultrasound imaging have been proposed to monitor the induced thermal lesions...

Background and objective: Blood pressure (BP) is one of the crucial indicators that contains valuable medical information about cardiovascular activities. Developing photoplethysmography (PPG)-based cuffless BP estimation algorithms with enough robustness accuracy clinically useful in practice, due to its simplicity noninvasiveness. In this paper, we have developed tested two frameworks for art...

Abstract Assessing the stability of stopes is essential in open stope mine design as unstable hangingwalls and footwalls lead to sloughing, unplanned dilution, safety concerns compromising profitability mine. Over past few decades, numerous empirical tools have been developed dimension connection with its stability, using graph method. However, one principal limitations method objectively deter...

This paper proposes a new architecture — Attentive Tensor Product Learning (ATPL) — to represent grammatical structures in deep learning models. ATPL is a new architecture to bridge this gap by exploiting Tensor Product Representations (TPR), a structured neural-symbolic model developed in cognitive science, aiming to integrate deep learning with explicit language structures and rules. The key ...