The settlement evaluation for the jet grouted columns (JGC) in soft soils is a problematic matter, because it is influenced by the number of aspects such as soil type, effect mixture between soil and grouting materials, nozzle energy, jet grouting, water flow rate, rotation and lifting speed. Most methods of design the jet-grouting column based on experience. In this study, a prototype single and group jet grouting models (single, 1*2, and 2*2) with the total length and diameter were (2000 and 150 mm) respectively and clear spacing (3D) has been constructed in soft clay and subjected to vertical axial loads. Furthermore, different theoretical methods have been used for the estimation of (JGC) settlement. Pile load settlement analysis of the jet grout columns showed that the average settlement values were (0.41, 0.663, and 1.5 mm) for the single, group (1*2) and group (2*2) jet grouted columns respectively. While, in the theoretical methods give a higher value of the settlement (2.0, 3.48, and 5.24 mm) for the single, group (1*2) and group (2*2) jet grouted columns compared with the settlement results acquired from field pile load test data. Therefore, it is not recommended to be used for soft clay. On the other hand, Fuller and Hoy’s, Hansen’s 90%, and Butler and Hoy’s results may be considered faithful interpretation methods for the single and group (1*2 and 2*2) (JGC).
The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
Discriminant analysis is a technique used to distinguish and classification an individual to a group among a number of groups based on a linear combination of a set of relevant variables know discriminant function. In this research discriminant analysis used to analysis data from repeated measurements design. We will deal with the problem of discrimination and classification in the case of two groups by assuming the Compound Symmetry covariance structure under the assumption of normality for univariate repeated measures data.
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This paper aims to verify the existence of relationships between product innovation and the reputation of the organization. The study problem is that the State Organization for Marketing of Oil (SOMO) system is inflexible in terms of marketing procedures and needs innovative, unconventional methods in innovating its products and improving performance. The reputation of the organization. The importance of the study lies in that it is an attempt to raise the interest of SOMO in its approach to the research variables in order to enhance its competitive position in the future and improve the marketing business environment, which contributes to enhancing the reputation of the organization by product innovation. The study sample
... Show MoreThis study aims to know the role of strategic leadership to achieving competitiveness in industrial establishments by identifying the respondents’ perceptions about the level of availability of dimensions of leadership strategies (creativity and innovation, risk tolerance, available opportunities) in Bashir Al-Siksek & Partners Company for the manufacture of sanitary and plastic ware in Gaza strip
To achieve this, a questionnaire was developed and distributed to a sample of managers, auditors, accountants, and administrative employees in the study sample company. The questionnaire tool was distributed to 60 employees and employees, of which (52) were retrieved, or 86.6%, and (8) were excluded for la
... Show MoreBackground: Chronic otitis media (COM) of mucosal or squamous type is a common problem in otolaryngology practice, the active form of COM is characterized by discharge of pus and is treated by antibiotics to start with, the appropriate antibiotic should be prescribed to avoid antibiotic abuse and guarantee good outcome. Objectives:The objective of this study is to identify the causative organisms of active chronic active otitis media both (mucosal, squamous) type and test their sensitivity to various anti- microbial agents &compare with abroad studies.Methods:A prospective study was done on eighty patients, different ages and sexes were taken and carful history and examination was done, examination under microscope was done with carf
... Show MoreSoftware-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an
... Show MoreThe use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models
In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear
... Show MoreFinding the shortest route in wireless mesh networks is an important aspect. Many techniques are used to solve this problem like dynamic programming, evolutionary algorithms, weighted-sum techniques, and others. In this paper, we use dynamic programming techniques to find the shortest path in wireless mesh networks due to their generality, reduction of complexity and facilitation of numerical computation, simplicity in incorporating constraints, and their onformity to the stochastic nature of some problems. The routing problem is a multi-objective optimization problem with some constraints such as path capacity and end-to-end delay. Single-constraint routing problems and solutions using Dijkstra, Bellman-Ford, and Floyd-Warshall algorith
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