The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
The wastewater arising from pulp and paper mills is highly polluted and has to be treated before discharged into rivers. Coagulation-flocculation process using natural polymers has grown rapidly in wastewater treatment. In this work, the performance of alum and Polyaluminum Chloride (PACl) when used alone and when coupled with Fenugreek mucilage on the treatment of pulp and paper mill wastewater were studied. The experiments were carried out in jar tests with alum, PACl and Fenugreek mucilage dosages range of 50-2000 mg/L, rapid mixing at 200 rpm for 2 min, followed by slow mixing at 40 rpm for 15 min and settling time of 30 min. The effectiveness of Fenugreek mucilage was measured by the reduction of turbidity and Chemical Oxygen Demand
... Show MoreThe spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the 
In present work, new tetra-dentate ligand, titled 3,5-bis ((E)-5-Bromo-2-hydroxy benzylidene amino) benzoic acid (H3L), was prepared via an acid-catalyzed condensation process. New four metallic ligand complexes with Co(II), Ni(II), Cu(II) and Zn(II) ions, were also prepared from the refluxing of equivalent moles. Ligand's structure and its complexes; were confirmed by numerous characterization methods, including Ultraviolet-Visible, Infrared, Mass Spectrometer, 1H and 13C Nuclear Magnetic Resonance spectra, atomic absorption, magnetic moments, and molar conductivity measurements. The results of the spectroscopic analyzes proved that the prepared ligand acts as tetradentate bi-ionic ligand and it was bond
... Show MoreIn this paper, the fuzzy logic and the trapezoidal fuzzy intuitionistic number were presented, as well as some properties of the trapezoidal fuzzy intuitionistic number and semi- parametric logistic regression model when using the trapezoidal fuzzy intuitionistic number. The output variable represents the dependent variable sometimes cannot be determined in only two cases (response, non-response)or (success, failure) and more than two responses, especially in medical studies; therefore so, use a semi parametric logistic regression model with the output variable (dependent variable) representing a trapezoidal fuzzy intuitionistic number.
the model was estimated on simulati
... Show MoreOne of the most significant elements influencing weather, climate, and the environment is vegetation cover. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI) over the years 2019–2022 were estimated based on four Landsat 8 TIRS’s images covering Duhok City. Using the radiative transfer model, the city's land surface temperature (LST) during the next four years was calculated. The aim of this study is to compute the temperature at the land's surface (LST) from the years 2019-2022 and understand the link, between LST, NDVI, and NDBI and the capability for mapping by LANDSAT-8 TIRS's. The findings revealed that the NDBI and the NDVI had the strongest correlation with the
... Show MoreABSTRACT
This study aimed to choose top stocks through technical analysis tools specially the indicator called (ratio of William index), and test the ability of technical analysis tools in building a portfolio of shares efficient in comparison with the market portfolio. These one technical tools were used for building one portfolios in 21 companies on specific preview conditions and choose 10 companies for the period from (March 2015) to (June 2017). Applied results of the research showed that Portfolio yield for companies selected according to the ratio of William index indicator (0.0406) that
... Show MoreMicrobial Desalination Cell (MDC) is capable of desalinating seawater, producing electrical power and treating wastewater. Previously, chemical cathodes were used, which were application restrictions due to operational expenses are quite high, low levels of long-term viability and high toxicity. A pure oxygen cathode was using, external resistance 50 and 150 k Ω were studied with two concentrations of NaCl in the desalination chamber 15-25 g/L which represents the concentration of brackish water and sea water. The highest energy productivity was obtained, which amounted to 44 and 46 mW/m3, and the maximum limit for desalination of saline water was (31% and 26%) for each of 25 g / L and 15 g / L, respectively, when using an ex
... Show MoreAmputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte
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