The aim of this research is to construct a three-dimensional maritime transport model to transport nonhomogeneous goods (k) and different transport modes (v) from their sources (i) to their destinations (j), while limiting the optimum quantities v ijk x to be transported at the lowest possible cost v ijk c and time v ijk t using the heuristic algorithm, Transport problems have been widely studied in computer science and process research and are one of the main problems of transport problems that are usually used to reduce the cost or times of transport of goods with a number of sources and a number of destinations and by means of transport to meet the conditions of supply and demand. Transport models are a key tool in logistics and supply chain management to reduce costs, times or improve services, In this study Three algorithms were proposed to solve the transport matrix (Range(R), Arithmetic Mean(AM), Cost Slop(CO)), and this algorithm must meet the requirements of problem restrictions and goals to reach good solutions, and may sometimes be the optimal solutions so we will adopt any solutions that are the best and optimal through our findings in the application of heuristic algorithms and based on the final results can be based on the heuristic method., The research concluded that the best reasoning method is the (arithmetic mean(AM)) because it gave the best results in reducing the total (cost and time) before and after the optimization method (MODI), It also gave the cost inclination method less total costs and time higher than the method of arithmetic mean After conducting the optimization method(MODI)
This approach was developed to achieve an accurate, fast, economic and sensitivity to estimation of diphenhydramine Hydrochloride. The dye that produced via reaction between diphenhydramine HCl with thymol blue in acidic medium pH ≈ 4.0. The ion pair method include an optimization study to formed yellowcolored that extraction by liquid – liquid method. The product separated of complexes by using by chloroform solution measured spectrophotometry at 400 nm. The analysis data at optimum conditions showed that linearity concentration in a range of calibration curve 1.0 – 50 μg /mL, limit of detectionand limit of quantification 0.0786 and 0.2358 μg/mL respectively. The molar absorptivity and Sandell’s sensitivity were 1.8 × 10 -4 L/mo
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In the present study, 1-ethyl -3-methyllimidazolium acetate ionic liquid is introduced for extractive desulfurization of Iraqi kerosene (1622ppm) and compared with 1-ethyl -3- methyllimidazolium tetrafloroborate. The effect of ionic liquid/ fuel ratio (1/9, 1/4, 1/2), temperature (25, 30,40oC), stirring speed (300,450rpm) and time (10, 30, 90, 180, 360 min) were studied. Sulfur compound analysis was performed using X-Ray fluorescence. The ionic liquid with acetate anion (OAc) showed better performance than tetrafloborate (BF4). The maximum extraction efficiency was 32% achieved at 1/2 IL/Fuel and 40oC after 90min. The oxidation step using hydrogen peroxide (8ml/200ml), catalyzed by acetic acid (2ml) and followed by ionic liquid extraction h
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreFour rapid, accurate and very simple derivative spectrophotometric techniques were developed for the quantitative determination of binary mixtures of estradiol (E2) and progesterone (PRG) formulated as a capsule. Method I is the first derivative zero-crossing technique, derivative amplitudes were detected at the zero-crossing wavelength of 239.27 and 292.51 nm for the quantification of estradiol and 249.19 nm for Progesterone. Method II is ratio subtraction, progesterone was determined at λmax 240 nm after subtraction of interference exerted by estradiol. Method III is modified amplitude subtraction, which was established using derivative spectroscopy and mathematical manipulations. Method IIII is the absorbance ratio technique, absorba
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