Recently, a great rise in the population and fast manufacturing processes were noticed. These processes release significant magnitudes of waste. These wastes occupied a notable ground region, generating big issues for the earth and the environment. To enhance the geotechnical properties of fine-grained soil, a sequence of research projects in the lab were conducted to analyze the impacts of adding sludge waste (SW). The tests were done on both natural and mixed soil with SW at various proportions (2%, 4%, 6%, 8%, and 10%) based on the dry mass of the soil used. The experiments conducted focused on consistency, compaction, and shear strength. With the addition of 10% of SW, the values of LL and PI decreased by 29.7% and 3

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

In this work, the effect of preparing a composite of copper oxide nanoparticles with carbon on some of its optical properties was studied. The composite preparing process was carried out by exploding graphite electrodes in an aqueous suspension of copper oxide. The properties of the plasma which is formed during the explosion were studied using emission spectroscopy in order to determine the most important elements that are present in the media. The electron’s density and their energy, which is the main factor in the composite process, were determined. The particle properties were studied before and after the exploding process. The XRD showed an additional peak in the copper oxides pattern corresponding to the hexagonal graphite struct

In the present work, the feasibility of formation near-ideal ohmic behavior of In/n-Si contact efficiently by 300 s duration Nd:YAG pulsed laser processing has been recognized. Several laser pulses energy densities have been used, and the optimal energy density that gives best results is obtained. Topography of the irradiated region was extensively discussed and supported with micrographic illustrations to determine the surface condition that can play the important role in the ohmic contact quality. I-V characteristics in the forward and reverse bias and barrier height measurements have been studied for different irradiated samples to determine the laser energy density that gives best ohmic behavior. Comparing the current results with

The research includes the preparation of several complexes of the internal transition elements lanthanide (Ln = La, Nd, Er, Gd, and Dy) containing the 4f shell, with Schiff bases resulting from condensation reactions between 4-antipyrinecarboxaldehyde and 2-aminobenzothiazoles. Schiff's base was identified using FTIR spectra, UV-vis spectroscopy, elemental microanalysis CHNSO, nuclear magnetic resonance, mass spectrometry, and TGA thermal analysis. The complexes were studied and identified with elemental microanalysis CHNSO, FTIR spectroscopy, UV-vis spectroscopy, TGA thermal analysis, conductivity measurement, and magnetic sensitivity. The result showed that these complexes were classified as homogeneous bidentate complexes with th

This research aims to study the methods of reduction of dimensions that overcome the problem curse of dimensionality when traditional methods fail to provide a good estimation of the parameters So this problem must be dealt with directly . Two methods were used to solve the problem of high dimensional data, The first method is the non-classical method Slice inverse regression ( SIR ) method and the proposed weight standard Sir (WSIR) method and principal components (PCA) which is the general method used in reducing dimensions,    (SIR ) and (PCA) is based on the work of linear combinations of a subset of the original explanatory variables, which may suffer from the problem of heterogeneity and the problem of linear