This work aims to analyze a three-dimensional discrete-time biological system, a prey-predator model with a constant harvesting amount. The stage structure lies in the predator species. This analysis is done by finding all possible equilibria and investigating their stability. In order to get an optimal harvesting strategy, we suppose that harvesting is to be a non-constant rate. Finally, numerical simulations are given to confirm the outcome of mathematical analysis.
This research examines the use of time in Hebrew children's literature and how historical narratives about the biblical period and beyond formed an arena for narrative conflict between the 1960s and the mid-1980s. The research clarifies the nature of narrative time: the time of events within the story itself (the sequence of events، the rhythm، and the occasional shifts between past and present)، as well as the framing time، which is the historical period the narrator perceives as the backdrop to the narrative. It also explores the time of memory and the use of flashbacks، evocations، or temporal allusions that connect young readers to a collective past. Our research also addresses how Zionist narratives began to lose credibility afte
... Show MoreAging of asphalt pavements typically occurs through oxidation of the asphalt and evaporation of the lighter maltenes from the binder. The main objective of this study is to evaluate influence of aging on performance of asphalt paving materials.nAsphalt concrete mixtures, were prepared, and subjected to short term aging (STA) procedure which involved heating the loose mixtures in an oven for two aging period of (4 and 8) hours at a temperature of 135 o C. Then it was subject to Long term aging (LTA) procedure using (2 and 5) days aging periods at 85 o C for Marshall compacted specimens. The effect of aging periods on properties of asphalt concrete at optimum asphalt content such as Marshall Properties, indirect tensile strength at 25 o C,
... Show MoreIn this paper, a time–space fractional order inverse source problem to determine the temperature solution and the time‐dependent source term from heat moment to the time–space fractional heat equation with an initial condition, homogeneous Dirichlet boundary conditions, and integral overdetermination condition is investigated. Two unconditionally stable finite difference schemes are proposed to find a numerical solution of the direct problem. Namely, method I is based on the approximation of the time‐fractional derivative via Laplace transformation, whereas method II is based on finite difference approximation. The inverse problem is solved iteratively
This Paper aims to plan the production of the electrical distribution converter (400 KV/11) for one month at Diyala Public Company and with more than one goal for the decision-maker in a fuzzy environment. The fuzzy demand was forecasting using the fuzzy time series model. The fuzzy lead time for raw materials involved in the production of the electrical distribution converter (400 KV/11) was addressed using the fuzzy inference matrix through the application of the matrix in Matlab, and since the decision-maker has more than one goal, so a mathematical model of goal programming was create, which aims to achieve two goals, the first is to reduce the total production costs of the electrical distribution converter (400 KV/11) and th
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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