Data Structures and Algorithms

1707 Submissions

[5] viXra:1707.0371 [pdf] submitted on 2017-07-28 06:39:26

Storing Data in DNA

Authors: George Rajna
Comments: 43 Pages.

Over millennia, nature has evolved an incredible information storage medium – DNA. It evolved to store genetic information, blueprints for building proteins, but DNA can be used for many more purposes than just that. [23] Based on early research involving the storage of movies and documents in DNA, Microsoft is developing an apparatus that uses biology to replace tape drives, researchers at the company say. [22] Our brains are often compared to computers, but in truth, the billions of cells in our bodies may be a better analogy. The squishy sacks of goop may seem a far cry from rigid chips and bundled wires, but cells are experts at taking inputs, running them through a complicated series of logic gates and producing the desired programmed output. [21] At Caltech, a group of researchers led by Assistant Professor of Bioengineering Lulu Qian is working to create circuits using not the usual silicon transistors but strands of DNA. [20] Researchers have introduced a new type of "super-resolution" microscopy and used it to discover the precise walking mechanism behind tiny structures made of DNA that could find biomedical and industrial applications. [19] Genes tell cells what to do—for example, when to repair DNA mistakes or when to die—and can be turned on or off like a light switch. Knowing which genes are switched on, or expressed, is important for the treatment and monitoring of disease. Now, for the first time, Caltech scientists have developed a simple way to visualize gene expression in cells deep inside the body using a common imaging technology. [18] Researchers at The University of Manchester have discovered that a potential new drug reduces the number of brain cells destroyed by stroke and then helps to repair the damage. [17]
Category: Data Structures and Algorithms

[4] viXra:1707.0247 [pdf] submitted on 2017-07-18 07:46:50

A Neutrosophic Image Retrieval Classifier

Authors: A. A. Salama, Mohamed Eisa, A. E. Fawzy
Comments: 6 Pages.

In this paper, we propose a two-phase Content-Based Retrieval System for images embedded in the Neutrosophic domain. In this first phase, we extract a set of features to represent the content of each image in the training database. In the second phase, a similarity measurement is used to determine the distance between the image under consideration (query image), and each image in the training database, using their feature vectors constructed in the first phase. Hence, the N most similar images are retrieved.
Category: Data Structures and Algorithms

[3] viXra:1707.0239 [pdf] replaced on 2017-08-13 18:09:20

The Backward Differentiation of the Bordering Algorithm for an Indefinite Cholesky Factorization

Authors: Stephen P. Smith
Comments: 19 Pages.

The bordering method of the Cholesky decomposition is backward differentiated to derive a method of calculating first derivatives. The result is backward differentiated again and an algorithm for calculating second derivatives results. Applying backward differentiation twice also generates an algorithm for conducting forward differentiation. The differentiation methods utilize three main modules: a generalization of forward substitution for calculating the forward derivatives; a generalization of backward substitution for calculating the backward derivatives; and an additional module involved with the calculation of second derivatives. Separating the methods into three modules lends itself to optimization where software can be developed for special cases that are suitable for sparse matrix manipulation, vector processing and/or blocking strategies that utilize matrix partitions. Surprisingly, the same derivative algorithms fashioned for the Cholesky decomposition of a positive definite matrix can be used again for matrices that are indefinite. The only differences are very minor adjustments involving an initialization step that leads into backward differentiation and a finalization step that follows forward differentiation.
Category: Data Structures and Algorithms

[2] viXra:1707.0091 [pdf] submitted on 2017-07-06 04:33:07

Chip Combines Computing and Data Storage

Authors: George Rajna
Comments: 54 Pages.

Now, researchers at Stanford University and MIT have built a new chip to overcome this hurdle. [28] In the quest to make computers faster and more efficient, researchers have been exploring the field of spintronics—shorthand for spin electronics—in hopes of controlling the natural spin of the electron to the benefit of electronic devices. [27] When two researchers from the Swiss Federal Institute of Technology (ETH Zurich) announced in April that they had successfully simulated a 45-qubit quantum circuit, the science community took notice: it was the largest ever simulation of a quantum computer, and another step closer to simulating "quantum supremacy"—the point at which quantum computers become more powerful than ordinary computers. [26] Researchers from the University of Pennsylvania, in collaboration with Johns Hopkins University and Goucher College, have discovered a new topological material which may enable fault-tolerant quantum computing. [25] The central idea of TQC is to encode qubits into states of topological phases of matter (see Collection on Topological Phases). [24] One promising approach to building them involves harnessing nanometer-scale atomic defects in diamond materials. [23] Based on early research involving the storage of movies and documents in DNA, Microsoft is developing an apparatus that uses biology to replace tape drives, researchers at the company say. [22] Our brains are often compared to computers, but in truth, the billions of cells in our bodies may be a better analogy. The squishy sacks of goop may seem a far cry from rigid chips and bundled wires, but cells are experts at taking inputs, running them through a complicated series of logic gates and producing the desired programmed output. [21] At Caltech, a group of researchers led by Assistant Professor of Bioengineering Lulu Qian is working to create circuits using not the usual silicon transistors but strands of DNA. [20] Researchers have introduced a new type of "super-resolution" microscopy and used it to discover the precise walking mechanism behind tiny structures made of DNA that could find biomedical and industrial applications. [19] Genes tell cells what to do—for example, when to repair DNA mistakes or when to die—and can be turned on or off like a light switch. Knowing which genes are switched on, or expressed, is important for the treatment and monitoring of disease. Now, for the first time, Caltech scientists have developed a simple way to visualize gene expression in cells deep inside the body using a common imaging technology. [18]
Category: Data Structures and Algorithms

[1] viXra:1707.0074 [pdf] replaced on 2017-07-11 13:15:48

Fractality and Coherent Structures in Satisfiability Problems

Authors: Theophanes Raptis
Comments: 47 Pages. Typo correction in eq. (29a-b) and (35a-b)

We utilize a previously reported methodological framework [5], to find a general set of mappings for any satisfiability (SAT) problem to a set of arithmetized codes allowing a classification hierarchy enumerable via integer partition functions. This reveals a unique unsatisfiability criterion via the introduction of certain universal indicator functions associating the validity of any such problem with a mapping between Mersenne integers and their complements in an inclusive hierarchy of exponential intervals. Lastly, we present means to reduce the complexity of the original problem to that of a special set of binary sequences and their bit block analysis via a reduction of any expression to a type of a Sequential Dynamical System (SDS) using the technique of clause equalization. We specifically notice the apparent analogy of certain dynamical properties behind such problems with resonances and coherencies of multi-periodic systems leading to the possibility of certain fast analog or natural implementations of dedicated SAT-machines. A Matlab toolbox is also offered as additional aid in exploring certain simple examples.
Category: Data Structures and Algorithms