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 determine a trace amount of the colored product in the first method, followed by measuring with a UV-vis spectrophotometer. The linearity of the calibration curve was above the range of 5–14 μg mL−1, and the R2 was 0.9988. The LOD and LOQ were found to be 0.0318 and 0.1059 μg mL−1, respectively. The recovery was between 99.49–99.82%, the %RSD was 0.67–2.00% and the molar absorptivity was 4.724 × 103 L mol−1 cm−1. This method was successfully employed for 3-aminophenol detection in several wastewater samples from Rustamiya, under the Al Doura and Diyala bridge.
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
... Show MoreImage 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
... Show MoreThis study included the determination of mercury level in twelve samples of skin whitening cream available in local market in Baghdad by atomic absorption spectrophotometer ,all the samples analyzed was contained a detectable amount of mercury. The lowest concentration of mercury in the sample C (Top Shirley) was 0.482 μg/g, and the higher concentration was 29.54 μg/g in the sample J (Norseen) .It was also noted that the samples H (whitening speckle removing day cream) and K (whitening speckle removing night cream) did not mention in the label significance the name of the country of origin and date of the validity of the product.
Abstract The current research aimed at analyzing the content of the chemistry book for the third intermediate grade according to environmental ethics. The two researchers adopted the descriptive analytical approach, as the research community and its sample of the chemistry book for the third intermediate grade, approved by the Iraqi Ministry of Education for the academic year (2021-2022). The two researchers built a list ( +- standard) of environmental ethics, which included three main areas ( ethics of protecting the environment from pollution, ethics of protecting environmental resources from consumption (rationalization of consumption) and protecting living organisms, and the ethics of environmental literacy), and then derived from it (
... Show MoreThe extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.