Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
Measuring the efficiency of postgraduate and undergraduate programs is one of the essential elements in educational process. In this study, colleges of Baghdad University and data for the academic year (2011-2012) have been chosen to measure the relative efficiencies of postgraduate and undergraduate programs in terms of their inputs and outputs. A relevant method to conduct the analysis of this data is Data Envelopment Analysis (DEA). The effect of academic staff to the number of enrolled and alumni students to the postgraduate and undergraduate programs are the main focus of the study.
To determine the association between cigarette smoking and oxidative stress, a study was conducted in the period from January 2020 to April 2021, at College of Medicine, Al-Nahrain University, Baghdad, Iraq. The Enzyme-linked immunosorbent assay (ELISA) technique was utilized for measurement the antioxidant enzymes including: Glutathione superoxide (GPX) and catalase (CAT) and the biomarker of lipid peroxidation Malondialdehyde (MDA). Also, the gene expression of Nrf2 and HO-1were determined by using RT-PCR technique. The results indicate lower level of both GPX and CAT (p ≤ 0.001) in smokers compared with non-smokers. While the result of MDA indicate higher level in smokers (p≤0.001) compared with nonsmokers. The Nrf2 and HO-1 gene exp
... Show MorePhotovoltaic (PV) devices are widely used renewable energy resources and have been increasingly manufactured by many firms and trademarks. This condition makes the selection of right product difficult and requires the development of a fast, accurate and easy setup that can be implemented to test available samples and select the cost effective, efficient, and reliable product for implementation. An automated test setup for PV panels using LabVIEW and several microcontroller-based embedded systems were designed, tested, and implemented. This PV testing system was fully automated, where the only human intervention required was the instalment of PV panel and set up of required testing conditions. The designed and implemented system was
... Show MoreThe study presents the test results of Completely Decomposed Granite (CDG) soil tested under drained triaxial compression, direct shear and simple shear tests. Special attention was focused on the modification of the upper halve of conventional Direct Shear Test (DST) to behave as free
head in movement along with vertical strain control during shear stage by using Geotechnical Digital System (GDS). The results show that Free Direct Shear Test (FDST) has clear effect on the measured shear stress and vertical strain during the test. It has been found that shear strength
parameters measured from FDST were closer to those measured from simple shear and drained triaxial compression test. This study also provides an independent check on
Background: The bonded orthodontic retainer constructed from multistrand wire and composite is an efficient esthetic retainer, which can be maintained long-term. Clinical failures of bonded orthodontic retainers, most commonly at the wire/composite interface, have been reported. This in vitro investigation aimed to evaluate the tensile forces of selected multistrand wires and composite materials that are available for use in the construction of bonded fixed retainers. Materials and Methods: The study sample includes 120 wires with three types of retainer wires (3 braided strands\ Orthotechnology, 8 braided strands\ G&H Orthodontics, 6 coaxial strands\ Orthoclassic wires), two types of adhesive (flowable\ Orthotechnology, non flowable\ G&H O
... Show MoreIndicators of government debt is of extreme importanse in economic activity through knowledge of the economic impact of government debt, if the phenomenon is accepted or prepared to dangerous stage by stage, and there fore it can Through these indicators to measure the degree of indebtedness in relation to the economic activity of the Government on the one hand, the governments ability to repay the other hand.
Due to this it inferred that the degree of indebtedness in Iraq specificratio has exceed 60% during the period 1990 – 2002 ntejh lack of political and economic stability of the government, which led to the governments inability to repay the ma
... Show MoreThis work bases on encouraging a generous and conceivable estimation for modified an algorithm for vehicle travel times on a highway from the eliminated traffic information using set aside camera image groupings. The strategy for the assessment of vehicle travel times relies upon the distinctive verification of traffic state. The particular vehicle velocities are gotten from acknowledged vehicle positions in two persistent images by working out the distance covered all through elapsed past time doing mollification between the removed traffic flow data and cultivating a plan to unequivocally predict vehicle travel times. Erbil road data base is used to recognize road locales around road segments which are projected into the commended camera
... Show MoreDeep 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 mod
... Show MorePurpose This study was design to investigate of Purpose This study was design to investigate of P. aeruginosa, an example of Gram-negative bacteria, in seven primary and secondary schools of Baghdad city, and the effects of Ethanol and Dettol of P. aeruginosa biofilm. Design/methodology/approach Seventy swabs were collected from seven primary and secondary schools of Baghdad city, Iraq, during November -December 2022. Swabs were collected from classes desk, doors handles, students hands and water taps. Standard microbiological testing methods were used on the samples for isolation and identification. The ability of bacteria to form biofilm and the effects of Ethanol and Dettol on “preformed” biofilms was examined by microtiter plate wi
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