Enhancement of Exon Regions Recognition in Gene Sequences Using a Radix -4 Multi-valued Logic with DSP Approach

Numerous levels of concepts perform logical designand logical representations in an efficient manner. In typical and quantum theories of computation, Binary logic and Boolean algebra occupies an imperative place. But they havethe limitation of representing signals or sequences by using either binary ‘1’ or ‘0’. This has major drawbacks that the neutralities or any intermediate values are ignored which are essential in most of the applications. Because of the occurrence of such situations it is the need of the hour to look into other alternative logics in order to fulfill the necessities of the user in their respective applications. The binary logic can be replaced by Multi-Valued Logic (MVL), which grabs the positions of the major applications because of the ability to provide representation by using more than two values.As most of the significant applications are based on the logical sequences, the multi-valued logic shines because of its thriving feature. Genomic signal processing, a novel research area in bioinformatics,is one of the foremost applications which involve the operations of logical sequences. It is concerned with the digital signal representations and analysis of genomic data.Determination of the coding region in DNA sequence is one of the genomic operations.This leads to the identification of the characteristics of the gene which in turn finds out an individual’s behavior. In order to extract the coding regions on the basis of logical sequences a number of techniques have been proposed by researchers. But most of the works utilized binary logic, which lead to the problem of losing some of the coding regions and incorrectly recognizing non-coding regions as the coding regions. Hereby,we are proposing an approach for recognizing the exon regions from a gene sequence based on the multi-valued logic. In this approach, we have utilized fourlevel logical system, termed as quaternary logic for the representation of gene sequences and so that we recognize theexon regions from the DNA sequence

Statically-analyzed stream monitoring for cyber-physical Systems

Cyber-physical systems are digital systems interacting with the physical world. Even though this induces an inherent complexity, they are responsible for safety-critical tasks like governing nuclear power plants or controlling autonomous vehicles. To preserve trust into the safety of such systems, this thesis presents a runtime verification approach designed to generate trustworthy monitors from a formal specification. These monitors are responsible for observing the cyber-physical system during runtime and ensuring its safety. As underlying language, I present the asynchronous real-time specification language RTLola. It contains primitives for arithmetic properties and grants precise control over the timing of the monitor. With this, it enables specifiers to express properties relevant to cyber-physical systems. The thesis further presents a static analysis that identifies inconsistencies in the specification and provides insights into the dynamic behavior of the monitor. As a result, the resource consumption of the monitor becomes predictable. The generation of the monitor produces either a hardware description synthesizable onto programmable hardware, or Rust code with verification annotation. These annotations allow for proving the correctness of the monitor with respect to the semantics of RTLola. Last, I present the construction of a conservative hybrid model of the underlying system using information extracted from the specification. This model enables further verification steps.Cyber-physische Systeme sind digitale Systeme, die mit der physischen Welt interagieren. Obwohl das zu einer inhärenten Komplexität führt, sind sie verantwortlich für sicherheitskritische Aufgaben wie der Steuerung von Kernkraftwerken oder autonomen Fahrzeugen. Umdas Vertrauen in deren Sicherheit zu wahren, präsentiert diese Doktorarbeit einen Ansatz zur Laufzeitverifikation, konzipiert, um vertrauenswürdige Monitore aus einer formalen Spezifikation zu generieren. Diese Monitore sind dafür verantwortlich, das cyber-physische System zur Laufzeit zu überwachen und dessen Sicherheit zu gewährleisten. Als zugrundeliegende Sprache präsentiere ich die asynchrone Echtzeit-Spezifikationssprache RTLola. Sie enthält Primitiven für arithmetische Eigenschaften und gewährt präzise Kontrolle über das Timing des Monitors. Damit wird es Spezifizierenden ermöglicht Eigenschaften auszudrücken, die für Cyber-physische Systeme relevant sind. Weiterhin präsentiert diese Doktorarbeit eine statische Analyse, die Unstimmigkeiten in der Spezifikation identifiziert und Einblicke in das dynamische Verhalten des Monitors liefert. Aufgrund dessen wird der Ressourcenverbrauch des Monitors vorhersehbar. Die Generierung des Monitors erzeugt entweder eine Hardwarebeschreibung, die auf programmierbarer Hardware synthetisiert werden kann, oder Rust Code mit Verifikationsannotationen. Diese Annotationen erlauben es, die Korrektheit des Monitors bezogen auf die Semantik von RTLola zu beweisen. Abschließend präsentiere ich die Konstruktion von einem konservativen hybriden Modell des zugrundeliegenden Systems anhand von Informationen, die aus der Spezifikation gewonnen wurden. Dieses Modell ermöglicht weitere Verifikationsschritte

Realization of Multi-Valued Logic Using Optical Quantum Computing

Quantum computing is a paradigm of computing using physical systems, which operate according to quantum mechanical principles. Since 2017, functioning quantum processing units with limited capabilities are available on the cloud. There are two models of quantum computing in the literature: discrete variable and continuous variable models. The discrete variable model is an extension of the binary logic of digital computing with quantum bits |0⟩ and |1⟩ . In the continuous variable model, the quantum state space is infinite-dimensional and the quantum state is expressed with an infinite number of basis elements. In the physical implementation of quantum computing, however, the quantized energy levels of the electromagnetic field come in multiple values, naturally realizing the multi-valued logic of computing. Hence, to implement the discrete variable model (binary logic) of quantum computing, the temperature control is needed to restrict the energy levels to the lowest two to express the binary quantum states |0⟩ and |1⟩. The physical realization of the continuous variable model naturally implements the multi-valued logic of computing because any physical system always has the highest level of quantized energy observed i.e., the quantum state space is always finite dimensional. In 2001, Knill, Laflamme, and Milburn proved that linear optics realizes universal quantum computing in the qubit-based model. Optical quantum computers by Xanadu, under the phase space representation of quantum optics, naturally realizes the multi-valued logic of quantum computing at room temperature. Optical quantum computers use optical signals, which are most compatible with the fiber optics communication network. They are easily fabricable for mass production, robust to noise, and have low latency. Optical quantum computing provides flexibility to the users for determining the dimension of the computational space for each instance of computation. Additionally, nonlinear quantum optical effects are incorporated as nonlinear quantum gates. That flexibility of user-defined dimension of the computational space and availability of nonlinear gates lead to a faithful implementation of quantum neural networks in optical quantum computing. This dissertation provides a full description of a multi-class data quantum classifier on ten classes of the MNIST dataset. In this dissertation, I provide the background information of optical quantum computing as an ideal candidate material for building the future classical-quantum hybrid internet for its numerous benefits, among which the compatibility with the existing communications/computing infrastructure is a main one. I also show that optical quantum computing can be a hardware platform for realizing the multi- valued logic of computing without the need to encode and decode computational problems in binary logic. I also derive explicit matrix representation of optical quantum gates in the phase space representation. Using the multi-valued logic of optical quantum computing, I introduce the first quantum multi-class data classifier, classifying all ten classes of the MNIST dataset

Protein microenvironments for topology analysis

Previously held under moratorium from 1st December 2016 until 1st December 2021Amino Acid Residues are often the focus of research on protein structures. However, in a folded protein, each residue finds itself in an environment that is defined by the properties of its surrounding residues. The term microenvironment is used herein to refer to these local ensembles. Not only do they have chemical properties but also topological properties which quantify concepts such as density, boundaries between domains and junction complexity. These quantifications are used to project a protein’s backbone structure into a series of scores. The hypothesis was that these sequences of scores can be used to discover protein domains and motifs and that they can be used to align and compare groups of 3D protein structures. This research sought to implement a system that could efficiently compute microenvironments such that they can be applied routinely to large datasets. The computation of the microenvironments was the most challenging aspect in terms of performance, and the optimisations required are described. Methods of scoring microenvironments were developed to enable the extraction of domain and motif data without 3D alignment. The problem of allosteric site detection was addressed with a classifier that gave high rates of allosteric site detection. Overall, this work describes the development of a system that scales well with increasing dataset sizes. It builds on existing techniques, in order to automatically detect the boundaries of domains and demonstrates the ability to process large datasets by application to allosteric site detection, a problem that has not previously been adequately solved.Amino Acid Residues are often the focus of research on protein structures. However, in a folded protein, each residue finds itself in an environment that is defined by the properties of its surrounding residues. The term microenvironment is used herein to refer to these local ensembles. Not only do they have chemical properties but also topological properties which quantify concepts such as density, boundaries between domains and junction complexity. These quantifications are used to project a protein’s backbone structure into a series of scores. The hypothesis was that these sequences of scores can be used to discover protein domains and motifs and that they can be used to align and compare groups of 3D protein structures. This research sought to implement a system that could efficiently compute microenvironments such that they can be applied routinely to large datasets. The computation of the microenvironments was the most challenging aspect in terms of performance, and the optimisations required are described. Methods of scoring microenvironments were developed to enable the extraction of domain and motif data without 3D alignment. The problem of allosteric site detection was addressed with a classifier that gave high rates of allosteric site detection. Overall, this work describes the development of a system that scales well with increasing dataset sizes. It builds on existing techniques, in order to automatically detect the boundaries of domains and demonstrates the ability to process large datasets by application to allosteric site detection, a problem that has not previously been adequately solved

Infrared Spectroscopy

This informative and state-of-the-art book on Infrared Spectroscopy is addressed to Researchers in Medicine as well as to Pharmaceutical Industry and Agriculture. It features 7 specialized chapters of MIRS and NIRS covering applications in proteins and biopolymers; food quality research and food safety applications; and medical applications, such as Down syndrome disorders of tooth, probing of brain oxygen, the role of CO2 in blood pressure and diagnosis of metastatic cancer. This book highlights the span of modern Infrared applications