Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.
This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula
... Show MoreWireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s
... Show MoreThrough an experimental program of eighteen specimens presented in this paper, the bond strength between reinforcing bar and rubberized concrete was produced by adding waste tire rubber instead of natural aggregate. The fine and coarse aggregate was replaced in 0%, 25%, and 50% with the small pieces of a waste tire. Natural aggregate replacement ratio, rebar size, embedded rebar length, the rebar yield stress of rebar, cover, and concrete compressive strength were studied in this investigation. Ultimate bond stress, bond stress-slip response, and failure modes were presented. The experimental results reported that a reduction of 19% in bond strength was noticed in 50% replaced rubberized concrete compared with convention
... Show MoreThe performance of drug treatment and assessments of different drugs' side effects both can be affected by the interaction between food additives and drugs. Organic compounds such as food colorants dyes are utilized as additives in a wide range of foods. In this study, the adsorption interaction behavior between the colorant food dye sunset yellow (SY) and the drug loratadine was examined. The adsorption procedure is conducted at different drug dosages, various SY dye concentrations, and different temperature (288-318K). The equilibrium data were explained by using Freundlich and Langmuir adsorption isotherms, but Langmuir offering the best fit model. Kinetics adsorptive behavior of sunset yellow on loratadine matched pseudo-second order
... Show MoreModern asphalt technology has adopted nanomaterials as an alternative option to assert that asphalt pavement can survive harsh climates and repeated heavy axle loading during service life and prolong pavement life. This work aims to elucidate the behavior of the modified asphalt mixture fracture model and assess the fatigue and Rutting performance of Hot Mix Asphalt (HMA) mixes using the outcomes of indirect Tensile Strength (IDT), Semicircular bend (SCB) and rutting resistance; for this, a single PG (64−16) nanomodified asphalt binder with 5 % SiO2 and TiO2 have been investigated through a series of laboratory tests, including: Resilient modulus, Creep compliance, and tensile strength, SCB, and Flow Number (FN) to study their potential
... Show MoreThe effect of air injection angle on the performance of airlift pump used for water pumping has been studied analytically and experimentally. An airlift pump of dimensions 42mm diameter and 2200 mm length with conventional and modified air injection device was considered. A modification on conventional injection device (normal air-jacket type) was carried out by changing injection angle from 90 (for conventional) to 45 and 22.5 (for modified). Continuity and one-dimensional momentum balance for the flow field with basic principle of two-phase flow and expressions of slip ratio and friction factor as function of flow rates were formulated. The analytical and experimental investigations were carried out f
... Show MoreA field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.
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