Dependence of Electrodynamics on the Models of the Electromagnetic Medium
Issue:
Volume 6, Issue 6, November 2021
Pages:
83-87
Received:
26 February 2021
Accepted:
22 March 2021
Published:
5 November 2021
Abstract: This article traces the influence of physical models of the electromagnetic medium on electrodynamics. The connection between the ability of the electrodynamic equations to describe the processes under study and the adequacy of the model of the electromagnetic medium used in their derivation to the known data is shown. It is revealed that the assumption of the absence of the existence of the electromagnetic medium leads to certain methodological difficulties in deriving the electrodynamic equations. The paper highlights the main milestones in the evolution of the physical model of electromagnetic medium. As a rule, the existence of electromagnetic medium in physics has been denied up to the present time due to the lack of its consistent model. A new physical model of the electromagnetic medium is developed and based on it a system of electrodynamic equations is derived that agree with the known data of physical experiments and astronomical observations. On the basis of the proposed physical model, a mathematical description of the method of detecting the electromagnetic medium is obtained. The developed physical model made it possible not only to explain the data of known electromagnetic phenomena and experiments, but also to propose the Galilean relativity principle within the framework of classical mechanics. Possible consequences of detection of the electromagnetic medium are discussed.
Abstract: This article traces the influence of physical models of the electromagnetic medium on electrodynamics. The connection between the ability of the electrodynamic equations to describe the processes under study and the adequacy of the model of the electromagnetic medium used in their derivation to the known data is shown. It is revealed that the assum...
Show More
Advanced Mathematical Formulas to Calculate Prime Numbers
Issue:
Volume 6, Issue 6, November 2021
Pages:
88-91
Received:
4 March 2021
Accepted:
3 November 2021
Published:
10 November 2021
Abstract: Prime numbers are the core of mathematics and specifically of number theory. The application of prime numbers in modern science, especially in computer science, is very wide. The importance of prime numbers has increased especially in the field of information technology, i.e., in data security algorithms. It is easy to generate the product of two prime numbers but extremely difficult and a laborious to decompose prime factors combined together. The RSA system in cryptography uses prime numbers widely to calculate the public and the private keys. Diffie-Hellman Key Exchange in cryptography uses prime numbers in a similar way and in computing hash codes also we use Prime numbers. Since prime numbers can only divisible by 1 and themselves, they are not factored any further like whole numbers. Their appearance within the infinite string of numbers in random fasion that devising a functional equation to correctly predict them, infinitely, has been belived by many mathematician as impossible task. The problem to calculate prime number using a formula posed for long periods. Though different formulae to calculate prime number were developed by Euler, Fermat and mersenne, the formulae work for limited natural numbers and calculate limited prime numbers. However, on this paper the author wants to show how prime number calculated for all values of integers(x).
Abstract: Prime numbers are the core of mathematics and specifically of number theory. The application of prime numbers in modern science, especially in computer science, is very wide. The importance of prime numbers has increased especially in the field of information technology, i.e., in data security algorithms. It is easy to generate the product of two p...
Show More
A Character Segmentation Method to Increase Character Recognition Accuracy for Turkish License Plates
Gulsum Cigdem Cavdaroglu,
Mehmet Gokmen
Issue:
Volume 6, Issue 6, November 2021
Pages:
92-104
Received:
19 September 2021
Accepted:
16 October 2021
Published:
31 December 2021
Abstract: Automatic License Plate Recognition is a computer vision technology that provides a way to recognize the vehicle's license plates without direct human intervention. Developing Automatic License Plate Recognition methodologies is a widely studied topic among the computer vision community to increase the accuracy rates. Automatic License Plate Recognition systems include image acquisition and character segmentation phases. Although there are many studies, the research in character segmentation and improving recognition accuracy remains limited. The lack of an international standard for license plates and the misinterpretation of ambiguous characters are challenging problems for Automatic License Plate Recognition systems. Several academic works have shown that the ambiguous character problem can be overcome by using a second model that contains only these characters. In this study, we propose a new methodology to reduce the character recognition errors of Automatic License Plate Recognition systems. One of the reasons for the low accuracy rates is the problem of ambiguous characters. In most studies using OCR, it was observed that a single model was used for alphanumeric characters during the recognition phase. Instead of using a single model, using separate models for letters and digits will improve the recognition process and increase accuracy. Therefore, we determined whether the characters are letters or numbers, and we expressed the license plates in the form of letters - digits. The method suggested for segmenting blobs worked with an accuracy of 96.12% on the test dataset. The method recommended for generating letter-digit expressions for the license plates worked with an accuracy of 99.28% on the test dataset. The proposed methodology can work only on Turkish license plates. In future studies, we will expand our method by using the license plate dataset of a different country.
Abstract: Automatic License Plate Recognition is a computer vision technology that provides a way to recognize the vehicle's license plates without direct human intervention. Developing Automatic License Plate Recognition methodologies is a widely studied topic among the computer vision community to increase the accuracy rates. Automatic License Plate Recogn...
Show More
