scholarly journals Fractal fractional derivative on chemistry kinetics hires problem

2021 ◽  
Vol 7 (1) ◽  
pp. 1155-1184
Author(s):  
Muhammad Aslam ◽  
◽  
Muhammad Farman ◽  
Hijaz Ahmad ◽  
Tuan Nguyen Gia ◽  
...  
Keyword(s):  
Chemical Kinetics ◽  
Chemical Reactions ◽  
Transfer Problem ◽  
Nonlinear Models ◽  
Real Life ◽  
Numerical Results ◽  
Actual Behavior ◽  
Caputo Fractional Derivatives ◽  
Home Heating ◽  
Life Problems

<abstract> <p>In this work, we construct the fractional order model for chemical kinetics issues utilizing novel fractal operators such as fractal fractional by using generalized Mittag-Leffler Kernel. To overcome the constraints of the traditional Riemann-Liouville and Caputo fractional derivatives, a novel notion of fractional differentiation with non-local and non-singular kernels was recently presented. Many scientific conclusions are presented in the study, and these results are supported by effective numerical results. These findings are critical for solving the nonlinear models in chemical kinetics. These concepts are very important to use for real life problems like brine tank cascade, recycled brine tank cascade, pond pollution, home heating and biomass transfer problem. Many scientific results are presented in the paper also prove these results by effective numerical results. These results are very important for solving the nonlinear model in chemistry kinetics which will be helpful to understand the chemical reactions and its actual behavior; also the observation can be developed for future kinematic chemical reactions with the help of these results.</p> </abstract>

scholarly journals Fractal fractional derivative on chemistry kinetics hires problem

2021 ◽  
Vol 7 (1) ◽  
pp. 1155-1184
Author(s):  
Muhammad Aslam ◽  
◽  
Muhammad Farman ◽  
Hijaz Ahmad ◽  
Tuan Nguyen Gia ◽  
...  
Keyword(s):  
Chemical Kinetics ◽  
Chemical Reactions ◽  
Transfer Problem ◽  
Nonlinear Models ◽  
Real Life ◽  
Numerical Results ◽  
Actual Behavior ◽  
Caputo Fractional Derivatives ◽  
Home Heating ◽  
Life Problems

<abstract> <p>In this work, we construct the fractional order model for chemical kinetics issues utilizing novel fractal operators such as fractal fractional by using generalized Mittag-Leffler Kernel. To overcome the constraints of the traditional Riemann-Liouville and Caputo fractional derivatives, a novel notion of fractional differentiation with non-local and non-singular kernels was recently presented. Many scientific conclusions are presented in the study, and these results are supported by effective numerical results. These findings are critical for solving the nonlinear models in chemical kinetics. These concepts are very important to use for real life problems like brine tank cascade, recycled brine tank cascade, pond pollution, home heating and biomass transfer problem. Many scientific results are presented in the paper also prove these results by effective numerical results. These results are very important for solving the nonlinear model in chemistry kinetics which will be helpful to understand the chemical reactions and its actual behavior; also the observation can be developed for future kinematic chemical reactions with the help of these results.</p> </abstract>

scholarly journals Some High-Order Iterative Methods for Nonlinear Models Originating from Real Life Problems

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1249
Author(s):  
Malik Zaka Ullah ◽  
Ramandeep Behl ◽  
Ioannis K. Argyros
Keyword(s):  
Nonlinear Models ◽  
Real Life ◽  
Systems Of Equations ◽  
Type Method ◽  
Life Problems ◽  
Similar Information ◽  
Large Systems ◽  
Computable Error Bounds ◽  
Theoretical Results ◽  
High Order Iterative Methods

We develop a sixth order Steffensen-type method with one parameter in order to solve systems of equations. Our study’s novelty lies in the fact that two types of local convergence are established under weak conditions, including computable error bounds and uniqueness of the results. The performance of our methods is discussed and compared to other schemes using similar information. Finally, very large systems of equations (100×100 and 200×200) are solved in order to test the theoretical results and compare them favorably to earlier works.

Optimizing the Curriculum in Thermodynamics and Heat Transfer With Better Labs, In-Class Demonstrations and Interesting Realistic Problems to Enhance Learning

2015 ◽  
Author(s):  
K. Larsen ◽  
A. Hossain ◽  
M. Weiser
Keyword(s):  
Heat Transfer ◽  
Transfer Problem ◽  
Real Life ◽  
Primary Objective ◽  
Theoretical Understanding ◽  
Text Book ◽  
Life Problems ◽  
Class Room ◽  
Realistic Problem ◽  
Eastern Washington

The primary objective of a thermodynamic/heat transfer course is to provide the fundamental knowledge necessary to understand the behavior of thermal systems. A thermodynamic/heat transfer course provides a detailed calculus-based analysis of energy, entropy, exergy, conduction, convection, and radiation using these concepts to calculate the behavior and efficiencies of different processes and cycles. Proper conceptual and theoretical understanding of thermodynamics/heat transfer is very important to solve real life problems. In order to understand and properly use the concepts, it is necessary that there be effective labs and in-class demonstrations, as well as realistic problems to serve this purpose. Most thermodynamic/heat transfer courses have some labs and some courses use in-class demonstrations that attempt to apply what is being learned in the class room. How effective these labs and demonstrations are in helping the students understanding of the thermodynamic/heat transfer principles is questionable. To facilitate theoretical learning, instructors need to also solve a variety of interesting problems in thermodynamics/heat transfer, besides solving the conventional problems from the text book. Solving these realistic problems helps students to also enhance their conceptual understanding, and, motivate students to continue their learning. This paper describes an example of an interesting heat transfer problem that compares an analytical solution with that of an FEA solution to help engage the students in learning how to apply both approaches to a realistic problem. Furthermore, this paper discusses a series of labs that are currently used at Eastern Washington University (EWU) to help students apply what they are learning in a thermodynamic/heat transfer course. The labs at EWU are compared to a survey conducted at 25 universities to find other possible labs and in-class demonstrations. From this study, the best labs and in-class demonstrations will be discussed, explored, and implementation recommendations will be given.

The Psychologist in the Medical School: An Example of Solving Real-Life Problems

1970 ◽  
Author(s):  
Matisyohu Weisenberg ◽  
Carl Eisdorfer ◽  
C. Richard Fletcher ◽  
Murray Wexler
Keyword(s):  
Medical School ◽  
Real Life ◽  
Life Problems

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

scholarly journals Formulating Modes of Cooperative Leaning for Education for Sustainable Development

2021 ◽  
Vol 13 (6) ◽  
pp. 3465
Author(s):  
Jordi Colomer ◽  
Dolors Cañabate ◽  
Brigita Stanikūnienė ◽  
Remigijus Bubnys
Keyword(s):  
Sustainable Development ◽  
Real Life ◽  
Education For Sustainable Development ◽  
Professional Life ◽  
Global Challenges ◽  
Life Problems ◽  
The Face ◽  
Contemporary Education ◽  
The Impact

In the face of today’s global challenges, the practice and theory of contemporary education inevitably focuses on developing the competences that help individuals to find meaningfulness in their societal and professional life, to understand the impact of local actions on global processes and to enable them to solve real-life problems [...]

scholarly journals Derivative-Free King’s Scheme for Multiple Zeros of Nonlinear Functions

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1242
Author(s):  
Ramandeep Behl ◽  
Sonia Bhalla ◽  
Eulalia Martínez ◽  
Majed Aali Alsulami
Keyword(s):  
Iterative Methods ◽  
Fourth Order ◽  
Order Of Convergence ◽  
Real Life ◽  
Multiple Roots ◽  
Computational Results ◽  
Nonlinear Functions ◽  
First Order ◽  
Life Problems ◽  
Derivative Free

There is no doubt that the fourth-order King’s family is one of the important ones among its counterparts. However, it has two major problems: the first one is the calculation of the first-order derivative; secondly, it has a linear order of convergence in the case of multiple roots. In order to improve these complications, we suggested a new King’s family of iterative methods. The main features of our scheme are the optimal convergence order, being free from derivatives, and working for multiple roots (m≥2). In addition, we proposed a main theorem that illustrated the fourth order of convergence. It also satisfied the optimal Kung–Traub conjecture of iterative methods without memory. We compared our scheme with the latest iterative methods of the same order of convergence on several real-life problems. In accordance with the computational results, we concluded that our method showed superior behavior compared to the existing methods.

scholarly journals ACO with Intuitionistic Fuzzy Pheromone Updating Applied on Multiple-Constraint Knapsack Problem

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1456
Author(s):  
Stefka Fidanova ◽  
Krassimir Todorov Atanassov
Keyword(s):  
Decision Making ◽  
Knapsack Problem ◽  
Propositional Logic ◽  
Optimization Problems ◽  
Real Life ◽  
Combinatorial Optimization Problems ◽  
Intuitionistic Fuzzy ◽  
Life Problems ◽  
Multiple Constraint

Some of industrial and real life problems are difficult to be solved by traditional methods, because they need exponential number of calculations. As an example, we can mention decision-making problems. They can be defined as optimization problems. Ant Colony Optimization (ACO) is between the best methods, that solves combinatorial optimization problems. The method mimics behavior of the ants in the nature, when they look for a food. One of the algorithm parameters is called pheromone, and it is updated every iteration according quality of the achieved solutions. The intuitionistic fuzzy (propositional) logic was introduced as an extension of Zadeh’s fuzzy logic. In it, each proposition is estimated by two values: degree of validity and degree of non-validity. In this paper, we propose two variants of intuitionistic fuzzy pheromone updating. We apply our ideas on Multiple-Constraint Knapsack Problem (MKP) and compare achieved results with traditional ACO.

scholarly journals Calculators as Facilitators of Understanding Computational and Mathematical Contexts

2019 ◽  
Vol 1 (1) ◽  
pp. 177-183
Author(s):  
Jan Guncaga ◽  
Lilla Korenova ◽  
Jozef Hvorecky
Keyword(s):  
Soft Skills ◽  
Real Life ◽  
Theoretical Background ◽  
Learning Processes ◽  
Complex Phenomenon ◽  
Learning To Learn ◽  
Life Problems ◽  
The Subject ◽  
The Relationship

AbstractLearning is a complex phenomenon. Contemporary theories of education underline active participation of learners in their learning processes. One of the key arguments supporting this approach is the learner’s simultaneous and unconscious development of their ability of “learning to learn”. This ability belongs to the soft skills highly valued by employers today.For Mathematics Education, it means that teachers have to go beyond making calculations and memorizing formulas. We have to teach the subject in its social context. When the students start understanding the relationship between real-life problems and the role of numbers and formulas for their solutions, their learning becomes a part of their tacit knowledge. Below we explain the theoretical background of our approach and provide examples of such activities.

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