Entropy considerations in improved circuits for a biologically-inspired random pulse computer

We present five novel or modified circuits intended for building a universal computer based on random pulse computing (RPC) paradigm, a biologically-inspired way of computation in which variable is represented by a frequency of a random pulse train (RPT) rather than by a logic state. For the first time we investigate operation of RPC circuits from the point of entropy. In particular, we introduce entropy budget criterion (EBC) to reliably predict whether it is even possible to create a deterministic circuit for a given mathematical operation and show its relevance to numerical precision of calculations. Based on insights gained from the EBC, unlike in the previous art, where randomness is obtained from electronics noise or a pseudorandom shift register while processing circuitry is deterministic, in our approach both variable generation and signal processing rely on the random flip-flop (RFF) whose randomness is derived from a fundamentally random quantum process. This approach offers an advantage in higher precision, better randomness of the output and conceptual simplicity of circuits.

Fundamental Categories of Artificial Neural Networks

The new era of the world uses artificial intelligence (AI) and machine learning. The combination of AI and machine learning is called artificial neural network (ANN). Artificial neural network can be used as hardware or software-based components. Different topology and learning algorithms are used in artificial neural networks. Artificial neural network works similarly to the functionality of the human nervous system. ANN is working as a nonlinear computing model based on activities performed by human brain such as classification, prediction, decision making, visualization just by considering previous experience. ANN is used to solve complex, hard-to-manage problems by accruing knowledge about the environment. There are different types of artificial neural networks available in machine learning. All types of artificial neural networks work based of mathematical operation and require a set of parameters to get results. This chapter gives overview on the various types of neural networks like feed forward, recurrent, feedback, classification-predication.

The Triomathematics, Trithmetic, Trichometry, Triangulus & Ternary Algebra Expressions that Define the Triophysics and Triological Sciences Related to the Triscalar Mitigation of Non-Ionized Radiation via Bioharmonic Biobalancing Healthy Smart Solar Nanob

The narrative in this paper provides a detailed and descriptive mathematical model for operative Healthy Smart Solar Nanobiotechnology ™ © (Osler, 2021) designed to biobalance a non-ionized irradiated environment. The in-depth mathematics mentioned in this paper are the foundational elements for groundbreaking innovative terminologies and new pioneering scientific fields covered in detail to explicitly explain how Healthy Smart Solar Nanobiotechnology ™ © interacts with and works within the environment. These revolutionary fields of study are directly associated with the mitigating mathematical operation of Solar Smart Nanobiotechnology ™ ©. The mathematics defined in the paper also aid in the creation of new, novel, and original areas and arenas of knowledge that are designed to most accurately describe the trichotomous holistic solutions that can be used to create an all around healthy and safe environment for the well-being of all.

Simultaneous All-optical 1's Complement Cum Division-by-two Schemes

Odd and even number detection is an important mathematical operation. Generally when any number divisible by 2 then it is called even number, otherwise it is odd number. Division by 2 can be easily obtained by putting a point before least significant bit (LSB) of any binary number. As an example a number (27)10 = (11011)2 when divided by 2 its result will be (1101.1)2 = (13.5)10. Hence when we find the fractional bit as logic-1 we can say that the number is odd, otherwise it is even. This operation can be obtained by using a demultiplexer. Here we have developed an optical circuit which can divide any binary integer number by 2, apart from that its 1’s complement can also be obtained from the circuit. Both of the result can be obtained simultaneously. Terahertz optical asymmetric demultiplexer (TOAD) based generally switch assumes a vital part to plan this n-bit circuit. Numerical simulations are done to urge the exhibition of the circuit.

Comparison of modified Karnik-Mendel algorithm-based interval type-2 ANFIS and type-1 ANFIS

Purpose This study aims to propose, as the first time, the interval type-2 adaptive network-fuzzy inference system (ANFIS) structure, which is given better results compared to previously presented in the open literature. So, the ANFIS can be used effectively for training of interval type-2 fuzzy logic system (IT2FLS) parameters. Design/methodology/approach Karnik–Mendel algorithm (KMA) is modified to use in interval type-2 ANFIS. The modified Karnik–Mendel algorithm (M-KMA) is implemented to change the uncertain ANFIS parameters into known ones. In this way, the interval type-2 ANFIS removes uncertainties of IT2FLS. Therefore, the interval type-2 ANFIS is reduced to a simple one, i.e. less mathematical operation required. Only consequent parameters are trained, and the consequent parameters are chosen in the form of crisp. Findings By applying the mentioned procedure, it can be shown that interval type-2 ANFIS has generally better results compared to type-1 ANFIS. However, it was noticed that the worst results obtained in the case of interval type-2 ANFIS are equal to the best result obtained in the case of type-1 ANFIS. Therefore, users in this field can use this approach in solving nonlinear problems. Practical implications The interval type-2 ANFIS can be used as controller for highly nonlinear systems such as air vehicles. Originality/value As stated in the open literature, it is ineffective to use ANFIS for IT2FLS. In this study, the KMA is modified for IT2FLS, and it is seen that the ANFIS can be used effectively for IT2FLS.

Using marker-controlled watershed transform to detect baker’s cyst in MRI images: a pilot study

Introduction: Nowadays, Magnetic resonance imaging (MRI) has a high ability to distinguish between soft tissues because of high spatial resolution. Image processing is extensively used to extract clinical data from imaging modalities. In the medical image processing field, the knee’s cyst (especially baker) segmentation is one of the novel research areas.Material and Method: There are different methods for image segmentation. In this paper, the mathematical operation of the watershed algorithm is utilized by MATLAB software based on marker-controlled watershed segmentation for the detection of baker’s cyst in the knee’s joint MRI sagittal and axial T2-weighted images.Results: The performance of this algorithm was investigated, and the results showed that in a short time baker’s cyst can be clearly extracted from original images in axial and sagittal planes.Conclusion: The marker-controlled watershed segmentation was able to detect baker’s cyst reliable and can save time and current cost, especially in the absence of specialists it can help us for the easier diagnosis of MR images.

Performing arithmetic using a neural network trained on images of digit permutation pairs

In this paper, a neural network is trained to perform simple arithmetic using images of concatenated handwritten digit pairs. A convolutional neural network was trained with images consisting of two side-by-side handwritten digits, where the image’s label is the summation of the two digits contained in the combined image. Crucially, the network was tested on permutation pairs that were not present during training in an effort to see if the network could learn the task of addition, as opposed to simply mapping images to labels. A dataset was generated for all possible permutation pairs of length 2 for the digits 0–9 using MNIST as a basis for the images, with one thousand samples generated for each permutation pair. For testing the network, samples generated from previously unseen permutation pairs were fed into the trained network, and its predictions measured. Results were encouraging, with the network achieving an accuracy of over 90% on some permutation train/test splits. This suggests that the network learned at first digit recognition, and subsequently the further task of addition based on the two recognised digits. As far as the authors are aware, no previous work has concentrated on learning a mathematical operation in this way. This paper is an attempt to demonstrate that a network can learn more than a direct mapping from image to label, but is learning to analyse two separate regions of an image and combining what was recognised to produce the final output label.

Simultaneous All-optical 1's Complement Cum Division-by-two Schemes

Odd and even number detection is an important mathematical operation. Generally when any number divisible by 2 then it is called even number, otherwise it is odd number. Division by 2 can be easily obtained by putting a point before least significant bit (LSB) of any binary number. As an example a number (27)10 = (11011)2 when divided by 2 its result will be (1101.1)2 = (13.5)10. Hence when we find the fractional bit as logic-1 we can say that the number is odd, otherwise it is even. This operation can be obtained by using a demultiplexer. Here we have developed an optical circuit which can divide any binary integer number by 2, apart from that its 1’s complement can also be obtained from the circuit. Both of the result can be obtained simultaneously. Terahertz optical asymmetric demultiplexer (TOAD) based generally switch assumes a vital part to plan this n-bit circuit. Numerical simulations are done to urge the exhibition of the circuit.

Aсtive electro-optical system of targets detection with dynamic spectral processing of optical radiation

The issues discussed in this paper provide for further development of studies in the sphere of imaging spectroscopy and laser vision. In terms of forming the information fields (radiation fields), the electro-optical systems are subdivided into the passive and active ones. Passive electro-optical systems use the information fields formed by natural radiation sources, whereas the active ones suggest using artificial sources. Comparative analysis of mathematical and physical issues of designing the electro-optical systems with dynamic spectral processing of optical radiation of the passive and active types has been performed. It has been shown that the controlled dynamic spectral processing of optical radiation can be implemented within the passive and active electro-optical systems on the basis of the same algorithm that represents operation of the optical processor performing the mathematical operation of dot product. The authors have developed the block diagram of an active electro-optical system with dynamic spectral processing. The algorithm for optimal detection of optical signals has been developed using basics of the signal detection theory. Mathematical modeling of target detection against an inhomogeneous background has been performed. It has been shown that the optimal dynamic spectral processing of optical radiation in active electro-optical system enables to separate the desired optical signal by suppressing the background signal.

IMPLEMENTATION OF BLOM’S KEY PREDISTRIBUTION SCHEME BY USING ELLIPTIC CURVE CRYPTOGRAPHY

Cryptography, along with its various methods is used to serve the security communication purpose. Cryptography is said to be secure if the encryption key is hard to break by the attacker. Initially, Blom’s Key pre-distribution uses an integer finite field which makes this scheme easy to be intervened by attackers and criminal activists. Hence, this study suggests implementing the Elliptic Curve Cryptography to better enhance the security of the original Blom’s. In this proposed scheme, points generated from the elliptic curve will be appointed as public identifiers to be used in the original scheme. The private key and session key of each user are generated using the addition law mathematical operation with public identifiers assigned. Two users who intend to communicate with each other will obtain a common session key. Overall, the modification of Blom’s Key pre-distribution scheme will be presented in this study.