The semiempirical (PM3) and DFT quantum mechanical methods were used to investigate the theoretical degradation of Indigo dye. The chemical reactivity of the Indigo dye was evaluated by comparing the potential energy stability of the mean bonds. Seven transition states were suggested and studied to estimate the actually starting step of the degradation reaction. The bond length and bond angle calculations indicate that the best active site in the Indigo dye molecule is at C10=C11. The most possible transition states are examined for all suggested paths of Indigo dye degradation predicated on zero-point energy and imaginary frequency. The first starting step of the reaction mechanism is proposed. The change in enthalpy, Gibbs free energy and change in entropy of the overall reaction are equal to -548268.223 kcal/mol, 30831.951 kcal/mol and 48.552 cal/mol.deg, respectively. The activation energy is 46176.405 kcal/mol. The reaction rate is equal to .
Biodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–
... Show MorePorous materials play an important role in creating a sustainable environment by improving wastewater treatment's efficacy. Porous materials, including adsorbents or ion exchangers, catalysts, metal–organic frameworks, composites, carbon materials, and membranes, have widespread applications in treating wastewater and air pollution. This review examines recent developments in porous materials, focusing on their effectiveness for different wastewater pollutants. Specifically, they can treat a wide range of water contaminants, and many remove over 95% of targeted contaminants. Recent advancements include a wider range of adsorption options, heterogeneous catalysis, a new UV/H2O
Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc
... Show MoreAssessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,
... Show MoreWith the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev
... Show MoreThe esterification reaction of ethyl alcohol and acetic acid catalyzed by the ion exchange resin, Amberlyst 15, was investigated. The experimental study was implemented in an isothermal batch reactor. Catalyst loading, initial molar ratio, mixing time and temperature as being the most effective parameters, were extensively studied and discussed. A maximum final conversion of 75% was obtained at 70°C, acid to ethyl alcohol mole ratio of 1/2 and 10 g catalyst loading. Kinetic of the reaction was correlated with Langmuir-Hanshelwood model (LHM). The total rate constant and the adsorption equilibrium of water as a function of the temperature was calculated. The activation energies were found to be as 113876.9 and -49474.95 KJ per Kmol of ac
... Show MoreThe denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing. Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds. This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin
... Show MoreInstitutions and companies are looking to reduce spending on buildings and services according to scientific methods, provided they reach the same purpose but at a lower cost. On this basis, this paper proposes a model to measure and reduce maintenance costs in one of the public sector institutions in Iraq by using performance indicators that fit the nature of the work of this institution and the available data. The paper relied on studying the nature of the institution’s work in the maintenance field and looking at the type of data available to know the type and number of appropriate indicators to create the model. Maintenance data were collected for the previous six years by reviewing the maintenance and financial dep
... Show MoreData mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the most effective parameter, particularly when Age<49.5. Whereas Ki67 appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu
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