To achieve sustainability, use waste materials to make concrete to use alternative components and reduce the production of Portland cement. Lime cement was used instead of Portland cement, and 15% of the cement's weight was replaced with silica fume. Also used were eco-friendly fibers (copper fiber) made from recycled electrical. This work examines the impact of utilizing sustainable copper fiber with different aspect ratios (l/d) on some mechanical properties of high-strength green concrete. A high-strength cement mixture with a compressive strength of 65 MPa in line with ACI 211.4R was required to complete the assignment. Copper fibers of 1% by volume of concrete were employed in mixes with four different aspect ratios

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

Water supply networks are marred by serious risks of imperceptible pipeline leakage, posing ‎sustainability ‎and ‎performance ‎threats.  This article highlights the use of vibratory signal features to get around the drawbacks of traditional methods in a highly detailed framework for leak detection based on CatBoost. demonstrated excellent diagnostic performance and carried out a thorough test performance evaluation on five leakage configurations  . The expected system achieved an accuracy of 98.1% (variance (well within x/3% of expected):, beating traditional competitors such as Random Forest (97.3%) and Support Vector Machine (93.8%). ‎For example, the area under the receiver-operating characteristic curve was 0.995, in

Liquid-Liquid Extraction of Cu(II) ion in aqueous solution by dicyclohexyl-18-crown-6 as extractant in dichloroethane was studied .The extraction efficiency was investigated by a spectrophometric method. The reagent form a coloured complex which has been a quantitatively extracted at pH 6.3. The method obeys Beer`s law over range from (2.5-22.5) ppm with the correlation coefficient of 0.9989. The molar absorptivity the stoichiometry of extracted complex is found to be 1:2. the proposed method is very sensitive and selective.

Gingival crevicular fluid (GCF) may reflect the events associated with orthodontic tooth movement. Attempts have been conducted to identify biomarkers reflecting optimum orthodontic force, unwanted sequallea (i.e. root resorption) and accelerated tooth movement. The aim of the present study is to find out a standardized GCF collection, storage and total protein extraction method from apparently healthy gingival sites with orthodontics that is compatible with further high-throughput proteomics. Eighteen patients who required extractions of both maxillary first premolars were recruited in this study. These teeth were randomly assigned to either heavy (225g) or light force (25g), and their site specific GCF was collected at baseline and aft

Oil from Brassca campestris (local variety) was extracted with hexane using Soxhlet. The extracted oil was characterized and its antimicrobial activity was determined as well. The content of extracted oil was 40% with 0.5% of volatile oil .Oil was immiscible with polar solvent such as ethanol, acetone and water, while it was easily miscible with chloroform due to its hydrophobicity. The result of organoleptic tests revealed that the oil is clear yellow in color and odorless with acceptable taste. The oil was stable at 4 -25 C? for a month. Refractive index (RI) of oil was 1.4723 with density of 0.914, [both at 4-25 C?]. Boiling point 386 C?. Infra red spectroscopy (IR) indicated the presence of different chemical groups (C=C

This work reports the development of an analytical method for the simultaneous analysis of three fluoroquinolones; ciprofloxacin (CIP), norfloxacin (NOR) and ofloxacin (OFL) in soil matrix. The proposed method was performed by using microwave-assisted extraction (MAE), solid-phase extraction (SPE) for samples purification, and finally the pre-concentrated samples were analyzed by HPLC detector. In this study, various organic solvents were tested to extract the test compounds, and the extraction performance was evaluated by testing various parameters including extraction solvent, solvent volume, extraction time, temperature and number of the extraction cycles. The current method showed a good linearity over the concentration ranging from

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This work describes the development of new spectrophotometric techniques for 3-aminophenol assessment. The first technique involves using benzidine in an alkaline solution to convert 3-aminophenol into a colored complex. The produced complex has a red color with an absorbance of 462 nm. Between the concentration range 5–14 μg mL−1, Beer's law is obeyed with a correlation coefficient (R2) of 0.99781, a limit of detection (LOD) of 0.0423 μg mL−1, and a limit of quantification (LOQ) of 0.1411 μg mL−1. The recovery was between 87.2–95.43%, the relative standard deviation (%RSD) was 2.40–3.31% and the molar absorptivity was 3.545 × 103 L mol−1 cm−1. Secondly, cloud point extraction (CPE) was used to determ