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Anthropological Information About a Message Variability
George Losik,
Igor Boyko,
Vadim Tkachenko,
Boris Potapov,
Yury Vilchuk
Issue:
Volume 5, Issue 1, January 2020
Pages:
1-9
Received:
6 December 2019
Accepted:
30 December 2019
Published:
30 January 2020
Abstract: The article represents a particular case in the field of the theory of a message encoding and decoding when the message is transmitted from a transmitter to a receiver. In this case human plays a role of the transmitter and receiver. From the positions of the theory of coding and the theory of pattern recognition, considers the phenomenon of anthropological similarity in the anatomical structure of the human sensory-motor system. There is illustration of the importance of the topological similarity of the transmitter and receiver as a source of additional information on the example of an anthropological (species) similarity of the auditory and articulation systems. The results of experiments support the idea the receiver receives additional information or anthropological information about the message, which is decoded not from the message, but from a physical structure of the receiver. Such a transfer is possible with reference to information about human means, articulations, facial expressions and pantomimic poses. It is concluded, in order to convey the knowledge, the physical structure of the information carrier about this knowledge must be the same for the transmitter of the message and the receiver; in other cases, genesis of this additional information a priori impossible.
Abstract: The article represents a particular case in the field of the theory of a message encoding and decoding when the message is transmitted from a transmitter to a receiver. In this case human plays a role of the transmitter and receiver. From the positions of the theory of coding and the theory of pattern recognition, considers the phenomenon of anthro...
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Graphic Coding and Decoding Methods Using Relative Coordinates
Issue:
Volume 5, Issue 1, January 2020
Pages:
10-13
Received:
1 January 2020
Accepted:
10 January 2020
Published:
31 January 2020
Abstract: There are many processes in PCB production. In order to facilitate management and problem tracing, PCB monitoring is required in each production process. The production process of PCB is very different from that of common products. Barcode, QR code or electronic label can be pasted on common products, but not on PCB. Because corrosive chemical solution is used in many PCB production processes. In order to solve this problem, a coding method based on relative coordinates and a graphic decoding method combining Hough transform and projection transformation are proposed. This method takes into account that the most commonly used NC drilling machine in PCB manufacturing enterprises. The graphic coding method uses the relative coordinates of holes drilled on the PCB. The relative coordinates of the holes centers represent the encoding information. The image decoding method uses the Hough transform and the projection transformation. First, the captured image is transformed by Hough transform, and the center coordinates of the image are detected. Secondly, the image is projective transformed by the centers of the most lateral four holes as the feature points. The distortion image is transformed into a regular image. Then, the image decoding is realized by calculating the relative coordinates of the centers. The practicability of the method and the correctness of the algorithm are verified by experiments. This method has been used in the PCB production line of an enterprise.
Abstract: There are many processes in PCB production. In order to facilitate management and problem tracing, PCB monitoring is required in each production process. The production process of PCB is very different from that of common products. Barcode, QR code or electronic label can be pasted on common products, but not on PCB. Because corrosive chemical solu...
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Towards Cryptanalysis of a Variant Prime Numbers Algorithm
Bashir Kagara Yusuf,
Kamil Ahmad Bin Mahmood
Issue:
Volume 5, Issue 1, January 2020
Pages:
14-30
Received:
10 January 2020
Accepted:
31 January 2020
Published:
13 February 2020
Abstract: A hallmark of prime numbers (primes) that both characterizes it away from other natural numbers and makes it a challenging preoccupation, is its staunch defiance to be expressed in terms of composites or as a formula listing all its sequence of elements. A classification approach, was mapped out, that fragments a prime into two: its last digit (trailer - reduced set of residue {1, 3, 7 and 9}) and the other digits (lead) whose value is incremented by either 1, 2 or 3 thus producing a modulo-3 arithmetic equation. The algorithm tracked both Polignac’s and modified Goldbach’s coefficients in order to explore such an open and computationally hard problem. Precisely 20,064,735,430 lower primes of digits 2 to 12 were parsed through validity test with the powers of 10 primes of Sloane's A006988. Adopting at most cubic terms of predictors (as the next logical step of Euler’s quadratic formula for primes) in multiple linear regression analysis, the generated outputs were analyzed to aid in building Akaike Information Criterion (AIC) best model with forward selection strategy. The main task was fragmented into atomic units of similar instances and types (an atom is a table of length 4,493,869 integer sequences where a database contains 30 relational tables with facilities for further reprocessing). A node, that supports parallel processing, stores 30 contiguous databases, and explores 4,044,482,100 successive integers. 513,649,226,700 lower natural numbers were explored by 127 hypothetical nodes yielding primes stored in 114,300 tables spread across 3,810 databases. Veriton S6630G computer system with 7.86GB usable memory and processor Intel(R) Core(TM) i7-4790 CPU @ 3.60GHz were amongst the remarkable resources. Contrary to the apparent chaotic camouflage of primes as a bundle, the partitioned sample spaces reveal some remarkable patterns in terms of intervals of both sequence numbers and distances of separation from their immediate neighborhoods.
Abstract: A hallmark of prime numbers (primes) that both characterizes it away from other natural numbers and makes it a challenging preoccupation, is its staunch defiance to be expressed in terms of composites or as a formula listing all its sequence of elements. A classification approach, was mapped out, that fragments a prime into two: its last digit (tra...
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A Survey of Generative Adversarial Networks Based on Encoder-Decoder Model
Yi Yin,
Lin Ouyang,
Zhixiang Wu,
Shuifang Yin
Issue:
Volume 5, Issue 1, January 2020
Pages:
31-41
Received:
17 January 2020
Accepted:
11 February 2020
Published:
10 March 2020
Abstract: The generative model is a very important type of model in the field of artificial intelligence in recent years. Such models can comprehend the data through the neural network, and then create data according to the probability distribution of the input data, predict the results according to the data characteristics. The whole processing process is "intelligent". At present, two typical applications of generative model are Generative Adversarial Networks (GAN) model and Encoder-Decoder model, which have strong ability to generate image data. In the model of GAN, the generator simulates real data, and the discriminator judges the authenticity of the samples. Its goal is to train a generator to fit the real data perfectly, so that the discriminator cannot distinguish. In the Encoding-Decoding model, it can be understood as a process of "Encoding→intermediate vector→Decoding", It is suitable for processing one kind of data to generate another kind of data with the same probability distribution as the original data. Since most of the data features are intermingled, they are encoded in a complex and disorderly way. But if these features are extractable, it shows that these features are interpretable, and it will be easier to use these features for coding. Based on this situation, some research results have been produced by incorporating the Encoder- Decoder into GAN. This paper systematically analyzes and summarizes the basic concepts and theories of GAN and Encoder-Decoder, as well as their respective advantages and disadvantages. On this basis, by combing the related work of the two types of models, the main technical routes of the three types of GAN based on the Encoder Decoder are summarized, the techniques and theories including variational inference, energy function and correlation transformation of different distribution data are summarized. Finally, the GAN based on the Encoder-Decoder is summarized.
Abstract: The generative model is a very important type of model in the field of artificial intelligence in recent years. Such models can comprehend the data through the neural network, and then create data according to the probability distribution of the input data, predict the results according to the data characteristics. The whole processing process is "...
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