Preferred Language
Articles
/
joe-1524
Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
...Show More Authors

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Radon concentration measurement in soil for some northen Iraqi's regions by using CR-39 detector
...Show More Authors

Concentrations of radon were measured in this study for twenty-four samples of soil distributed in six locations on the north part of Iraq. The radon concentrations in soil samples measured by using alpha-emitters registration that emits from Radon (222Rn) in (CR-39) track detector. The concentrations values were calculated by a comparison with standard samples. The results shows that the radon gas concentrations in Darbandikhan City varies from (16.60-34.04 Bq/m3), Halabja City (16.51-23.32 Bq/m3), Al Sulaimaniya City (17.61-32.25 Bq/m3), Koisnjaq City (22.04-35.65 Bq/m3), Shaqlaua City (21.10-29.10 Bq/m3) and Erbil City (22.30-34.63 Bq/m3). The average radon gas concentration in Al Sulaimaniya and Erbil governorate are (22.30 Bq/m3)

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Sep 01 2022
Journal Name
Computers And Electrical Engineering
Automatic illness prediction system through speech
...Show More Authors

View Publication
Scopus (12)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
...Show More Authors

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

... Show More
View Publication
Scopus (14)
Scopus Crossref
Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
...Show More Authors

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

... Show More
Scopus (14)
Scopus
Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
...Show More Authors

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

... Show More
View Publication
Scopus (11)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Mon Feb 01 2021
Journal Name
Materials Science And Engineering
Effect of magnetic water on strength properties of concrete
...Show More Authors
Abstract<p>The research’s main goal is to investigate the effects of using magnetic water in concrete mixes with regard to various mechanical properties such as compressive, flexural, and splitting tensile strength. The concrete mix investigated was designed to attain a specified cylinder compressive strength (30 MPa), with mix proportions of 1:1.8:2.68 cement to sand to crushed aggregate. The cement content was about 380 kg/m<sup>3</sup>, with a w/c ratio equal to 0.54, sand content of about 685 kg/m3, and gravel content of about 1,020 kg/m3. Magnetic water was prepared via passing ordinary water throughout a magnetic field with a magnetic intensity of 9,000 Gauss. The strength test</p> ... Show More
Crossref (6)
Crossref
Publication Date
Fri Feb 26 2021
Journal Name
Life-cycle Civil Engineering: Innovation, Theory And Practice
Shear performance of a novel demountable connector for reusable steel-concrete composite structures
...Show More Authors

A novel demountable shear connector is proposed to link a concrete slab to steel sections in a way that resulting steel-concrete composite floor is demountable, i.e. it can be easily dismantled at the end of its service life. The proposed connectors consist of two parts: the first part is a hollow steel tube with internal threads at its lower end. The second part is a compatible partially threaded bolted stud. After linking the stud to the steel section, the hollow steel tube can be fastened over the threaded stud, which create a complete demountable shear connector. The connector is suitable for use in both composite bridges and buildings, and using cast in-situ slabs, precast solid slabs, or hollow-core precast slabs. A series of push-off

... Show More
View Publication
Scopus (1)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Structures
Horizontal pushout tests and parametric analyses of a locking-bolt demountable shear connector
...Show More Authors

A ‘locking-bolt’ demountable shear connector (LBDSC) is proposed to facilitate the deconstruction and reuse of steel-concrete composite structures, in line with achieving a more sustainable construction design paradigm. The LBDSC is comprised of a grout-filled steel tube and a geometrically compatible partially threaded bolt. The latter has a geometry that ‘locks’ the bolt in compatible holes predrilled on the steel flange and eliminates initial slip and construction tolerance issues. The structural behaviour of the LBDSC is evaluated through nine pushout tests using a horizontal test setup. The effects of the tube thickness, strength of concrete slab, and strength of infilled grout on the shear resistance, initial stiffness, and du

... Show More
View Publication
Scopus (46)
Crossref (43)
Scopus Clarivate Crossref
Publication Date
Mon Jan 12 2026
Journal Name
Infrastructures
Behaviour of Shear Stress Distribution in Steel Sections Under Static and Dynamic Loads
...Show More Authors

Shear lag is the phenomenon that occurs when a supported slender member undergoes deformation from lateral loading, causing in-plane non-uniform distribution of stresses that results in reducing the member’s minimum strength capacity. This paper investigates the behaviour of shear distribution in steel I-section and box girders when subjected to both static and impact loadings. Three-dimensional finite element analysis models were prepared in Strand7 and validated against experimental results providing a basis for further comparison research into shear lagging effects. A parametric study was conducted comparing the effects of impact loading through certain specified velocities at the midspan of restrained ends. It provided new ins

... Show More
View Publication
Scopus Crossref
Publication Date
Fri Mar 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Role of using the Relative Strength Index in Making Speculation Decision in Stock: Applied Research in the Iraq Stock Exchange
...Show More Authors

 The relative strength index (RSI) is one of the best known technical analysis indicators; it provides the speculators by prior signals about the future stock’s prices, and because the speculations in shares of companies which listed in the Iraq Stock Exchange have a high degree of risk, like risk of shares prices felling, so the speculators became committed to use some methods to reduce these risks, and one of these methods is the technical analysis by using the relative strength index (RSI) which enable the speculators of choosing the right time for buy and sell the stocks and the right time to enter or leave the market by using the historical rice data. And from here the problem of the research formulated as “Is the using of

... Show More
View Publication Preview PDF
Crossref