Scheduling Timetables for courses in the big departments in the universities is a very hard problem and is often be solved by many previous works although results are partially optimal. This work implements the principle of an evolutionary algorithm by using genetic theories to solve the timetabling problem to get a random and full optimal timetable with the ability to generate a multi-solution timetable for each stage in the collage. The major idea is to generate course timetables automatically while discovering the area of constraints to get an optimal and flexible schedule with no redundancy through the change of a viable course timetable. The main contribution in this work is indicated by increasing the flexibility of generating optimal timetable schedules with different copies by increasing the probability of giving the best schedule for each stage in the campus with the ability to replace the timetable when needed. The Evolutionary Algorithm (EA) utilized in this paper is the Genetic Algorithm (GA) which is a common multi-solution metaheuristic search based on the evolutionary population that can be applied to solve complex combinatorial problems like timetabling problems. In this work, all inputs: courses, teachers, and time acted by one array to achieve local search and combined this acting of the timetable by using the heuristic crossover to ensure that the essential conditions are not broken. The result of this work is a flexible scheduling system, which shows the diversity of all possible timetables that can be created depending on user conditions and needs.
This research seeks to shed light on what you add intangible assets of benefit to the company and this antagonize pause for consideration because it makes the company in a good competitive position stimulates the rest of the companies to acquire those assets.
That many companies have achieved competitive advantages in the market do not even achieved monopolies increased the value and reaped extraordinary profits as a result of those assets which requires the need to be measured to determine the extent to which contribution in the emergence of the value added to the value of the company on the one hand and to make the presentatio
... Show MoreAbstract. Geographical and remote sensing, which gave a picture of the change in the area of agricultural land in the study area for selected years (1980, 1990, 2000, 2010, 2020). In particular and Iraq in general, as this led to a reduction in the areas of agricultural lands and in return an increase in arid lands and their desertifica- tion and the loss of their productive value, which as a result leads to the migration of the population, the change of land sex, the failure to achieve food security and dependence on the import of the food basket.
Computer simulations were carried out to investigate the dependence of the main perturbation parameters (Sun and Moon attractions, solar radiation pressure, atmosphere drag, and geopotential of Earth) on the orbital behavior of satellite. In this simulation, the Cowell method for accelerations technique was adopted, the equation of motion with perturbation was solved by 4th order Runge-Kutta method with step (1/50000) of period to obtain the state vectors for position and velocity. The results of this simulation have been compared with data that available on TLEs (NORD data in two line elements). The results of state vectors for satellites (Cartosat-2B, Gsat-14 an
Background: Most prevalent chronic liver disease in developed and developing nations is non-alcoholic fatty liver disease. From fatty liver, which often has benign, non-progressive clinical history, to non-alcoholic steatohepatitis, a more serious variant of fatty liver that can lead to cirrhosis and end-stage liver disease, non-alcoholic fatty liver disease encompasses broad spectrum of diseases. The gold standard for determining extent of hepatic fibrosis is still liver biopsy; however, number of noninvasive tests have been established to make diagnosis and assess effectiveness of treatment.
Objective: Aim of study was to assess effectiveness of the combination of fibroscan and
... Show MoreThe tetradentate N2O2 Schiff base ligand, which is produced via the condensation reaction of 2-hydroxynaphthaldehyde with phthalohydrazide, is prepared in this work with a fair yield. The prepared ligand was characterized using a microanalysis technique (C.H.N), UV-vis, FTIR, 1H-,13C-NMR, mass spectrometry, and thermal gravimetric analysis (TGA). New complexes were synthesized by a reaction between ligand (N'1E,N'2Z)-N'1,N'2-bis((1-hydroxynaphthalen-2yl)methylene)phthalohydrazide and metal chloride of Co+2, Ni+2, and Zn+2 ions in absolute ethanol. The present complexes are also characterized by techniques such as C.H.N, UV-vis, FTIR, TGA, molar conductivity, atomic absorption, and magnetic moment measurements. The in vitro antimicro
... Show MoreThis paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient
In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden
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