The planning, designing, construction of excavations and foundations in soft to very soft clay soils are always difficult. They are problematic soil that caused trouble for the structures built on them because of the low shear strength, high water content, and high compressibility. This work investigates the geotechnical behavior of soft clay by using tyre ash material burnt in air. The investigation contains the following tests: physical tests, chemical tests, consolidation test, Compaction tests, shear test, California Bearing Ratio test CBR, and model tests. These tests were done on soil samples prepared from soft clay soil; tyre ash was used in four percentages (2, 4, 6, and 8%). The results of the tests were; The soil samples which

Association rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.

This paper is concerned with introducing and studying the first new approximation operators using mixed degree system and second new approximation operators using mixed degree system which are the core concept in this paper. In addition, the approximations of graphs using the operators first lower and first upper are accurate then the approximations obtained by using the operators second lower and second upper sincefirst accuracy less then second accuracy. For this reason, we study in detail the properties of second lower and second upper in this paper. Furthermore, we summarize the results for the properties of approximation operators second lower and second upper when the graph G is arbitrary, serial 1, serial 2, reflexive, symmetric, tra

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Nanotechnology has shown a lot of promise in the oil and gas sectors, including nanoparticle-based drilling fluids. This paper aims to explore and assess the influence of various nanoparticles on the performance of drilling fluids to make the drilling operation smooth, cost effective and efficient. In order to achieve this aim, we exam the effect of Multi Wall Carbon Nanotube and Silicon Oxide Nanoparticles as Nanomaterial to prepare drilling fluids samples.

Anew method for mixing of drilling fluids samples using Ultra sonic path principle will be explained. Our result was drilling fluids with nano materials have high degree of stability.

   The results of using Multiwall Carbon Nanotube and Silicon Oxide show t

Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

The frequent and widespread use of medicines and personal care products, particularly in the residential environment, tends to raise concerns about environmental and human health impacts. On the other hand, carbon dioxide accumulation in the atmosphere is a problem with numerous environmental consequences. Microalgae are being used to bioremediate toxins and capture CO2. The current study aimed to confirm the possibility of removing pharmaceutical contaminant (Ranitidine) at different concentrations by using the Chlorella Sorokiniana MH923013 microalgae strain during the growth time. As part of the experiment, carbon dioxide was added to the culture medium three times per week. Explanatory results revealed that gas doses directly affect

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a