Data Encryption and Hashing Schemes for Multimedia Protection

There are millions of people using social networking sites like Facebook, Google+, and Youtube every single day across the entire world for sharing photos and other digital media. Unfortunately, sometimes people publish content that does not belong to them. As a result, there is an increasing demand for quality software capable of providing maximum protection for copyrighted material. In addition, confidential content such as medical images and patient records require high level of security so that they can be protected from unintended disclosure, when transferred over the Internet. On the other hand, decreasing the size of an image without significant loss in quality is always highly desirable. Hence, the need for efficient compression algorithms. This thesis introduces a robust method for image compression in the shearlet domain. Motivated by the outperformance of the Discrete Shearlet Transform (DST) compared to the Discrete Wavelet Transform (DWT) in encoding the directional information in images, we propose a DST-based compression algorithm that provides not only a better quality in terms of image approximation and compression ratio, but also increases the security of images via the Advanced Encryption Standard. Experimental results on a slew of medical images illustrate an improved performance in image quality of the proposed approximation approach in comparison to DWT, and also demonstrate its robustness against a variety of tests, including randomness, entropy, key sensitivity, and input sensitivity. We also present a 3D mesh hashing technique using spectral graph theory. The main idea is to partition a 3D model into sub-meshes, followed by the generation of the Laplace-Beltrami matrix of each sub-mesh, and the application of eigen-decomposition. This, in turn, is followed by the hashing of each sub-mesh using Tsallis entropy. The experimental results using a benchmark 3D models demonstrate the effectiveness of the proposed hashing scheme

Dynamical Systems

Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...

A precise bare simulation approach to the minimization of some distances. Foundations

In information theory -- as well as in the adjacent fields of statistics, machine learning, artificial intelligence, signal processing and pattern recognition -- many flexibilizations of the omnipresent Kullback-Leibler information distance (relative entropy) and of the closely related Shannon entropy have become frequently used tools. To tackle corresponding constrained minimization (respectively maximization) problems by a newly developed dimension-free bare (pure) simulation method, is the main goal of this paper. Almost no assumptions (like convexity) on the set of constraints are needed, within our discrete setup of arbitrary dimension, and our method is precise (i.e., converges in the limit). As a side effect, we also derive an innovative way of constructing new useful distances/divergences. To illustrate the core of our approach, we present numerous examples. The potential for widespread applicability is indicated, too; in particular, we deliver many recent references for uses of the involved distances/divergences and entropies in various different research fields (which may also serve as an interdisciplinary interface)

Text Similarity Between Concepts Extracted from Source Code and Documentation

Context: Constant evolution in software systems often results in its documentation losing sync with the content of the source code. The traceability research field has often helped in the past with the aim to recover links between code and documentation, when the two fell out of sync. Objective: The aim of this paper is to compare the concepts contained within the source code of a system with those extracted from its documentation, in order to detect how similar these two sets are. If vastly different, the difference between the two sets might indicate a considerable ageing of the documentation, and a need to update it. Methods: In this paper we reduce the source code of 50 software systems to a set of key terms, each containing the concepts of one of the systems sampled. At the same time, we reduce the documentation of each system to another set of key terms. We then use four different approaches for set comparison to detect how the sets are similar. Results: Using the well known Jaccard index as the benchmark for the comparisons, we have discovered that the cosine distance has excellent comparative powers, and depending on the pre-training of the machine learning model. In particular, the SpaCy and the FastText embeddings offer up to 80% and 90% similarity scores. Conclusion: For most of the sampled systems, the source code and the documentation tend to contain very similar concepts. Given the accuracy for one pre-trained model (e.g., FastText), it becomes also evident that a few systems show a measurable drift between the concepts contained in the documentation and in the source code.</p

In Limbo, or, The Protracted Death of the Novel: William Gaddis’s J R and the Precarious State of Postmodern Literature

Postponed access: the file will be accessible after 2021-05-15Eksperimentell postmodernistisk litteratur blir framleis møtt med skepsis og skuldingar om irrelevans, også av tonegjevande litteraturkritikarar som Fredric Jameson, som rangerer litteratur under resterande kunstarter i postmoderniteten. Denne masteroppgåva tek for seg dei særeigne kvalitetane til eksperimentell postmodernistisk litteratur med utgangspunkt i romanen J R (1975) av William Gaddis. Denne romanen særmerkast av å være skriven som ein samanhengande dialog, med berre sjeldne innslag av ei narrativ stemme som att på til forsømer den tradisjonelle deskriptive rolla til fordel for å berre være endå ei stemme i samtalemylderet. Dette gjenspeiler Jean-François Lyotards idear om den aukande ugyldigheita til metanarrativ. Med omsyn til dette illustrerer J R korleis romanen, som på det mest konservative presenterast i form av eit strukturert narrativ formidla av ein allvitande forteljar, kan fornyast til auka fleksibilitet for å holde relevans ved lag i postmoderniteten. Ved å presentere teksten så upartisk som mogleg, opnar den seg for ei rekke tolkingar slik at lesaren bidrar til kunstverkets skaparhandling. Lesehandlinga, som i dei mest tradisjonelle tilfella er ei passiv oppleving der forfattaren formidlar eit fullbyrda produkt til lesaren, skiftast her ut med ein dialektisk, aktiv prosess der lesaren og teksta inngår i eit gjensidig forhold. Vidare opnar den ekskluderande autoriteten til ei narrativ stemme for at mindre narrativ i teksten kan nærstuderast, mens større, meir eksplisitte narrativ kan sidestillast, ettersom dialogen ofte består av lange, tilsynelatande trivielle tema. Sjølve oppgåva er delt inn i fire deler. Første del giv ein oversikt over romanens kontekst, postmodernistiske preg og narratologiske særtrekk. Andre del tek for seg entropi, eit dominerande tema i romanen, samt dei ekstralitterære implikasjonane dette inneberer. Tredje del tek for seg dei filmatiske parallellane i romanen. Fjerde del tek for seg den singulære posisjonen til J R i litteraturhistoria; til tross for at Gaddis i aukande grad blir betrakta som ein av dei leiande postmodernistiske forfattarane, har han aldri fått merksemd hos eit større publikum utanom akademiske kretsar i motsetning til forfattarar som Don DeLillo og Thomas Pynchon. Eg vil derfor undersøke arven etter J R, om der er nokon, og parallellane mellom J R og Pynchons hovudverk, Gravity’s Rainbow (1973). Sjølv om J R tilbyr eit alternativ til den dominerande romanstilen, kan det være at romanen berre er eit unntak til regelen, noko som understrekast av romanens avgrensa lesekrets og den snarare indirekte enn direkte innverknaden til Gaddis.Engelsk mastergradsoppgåveMAHF-LÆFRMAHF-ENGENG35

Machine Learning Assisted Discovery of Shape Memory Polymers and Their Thermomechanical Modeling

As a new class of smart materials, shape memory polymer (SMP) is gaining great attention in both academia and industry. One challenge is that the chemical space is huge, while the human intelligence is limited, so that discovery of new SMPs becomes more and more difficult. In this dissertation, by adopting a series of machine learning (ML) methods, two frameworks are established for discovering new thermoset shape memory polymers (TSMPs). Specifically, one of them is performed by a combination of four methods, i.e., the most recently proposed linear notation BigSMILES, supplementing existing dataset by reasonable approximation, a mixed dimension (1D and 2D) input model and a type of dual-convolutional-neural-network model. The framework is able to predict the recovery stress and glass transition temperature for TSMP and screen 14 new TSMPs from a large chemical space. The other leverages transfer learning, variational autoencoder and weighted vector combination method, and the developed ML framework can design ultraviolet (UV) curable TSMPs with desired properties. With new SMPs discovered by ML, as well as other new SMPs continuously developed in the labs, there is an urgent need to develop thermomechanical models so that the new SMPs can be used in structural design. Through the framework of solid mechanics, three different constitutive models are presented for classical one-way thermoset shape memory polymer (TSMP), two-way semi-crystalline SMP and enthalpy-driven four-chain SMP with large recovery stress, respectively. Among them, a new two-phase sphere model based on the physical growth process of the frozen phase from nuclei is proposed, which tends to bring more underly physical mechanism for the classical storage strain-based phase transition model. By introducing Gibbs energy and a transition of the molecule deformation mechanism, a enthalpy-driven thermomechanical model with new representative unit cell is developed, which could reasonably elucidates the large recovery stress for a new branch of TSMPs. Multiple mechanisms, involving phase transition law, damage evolution, and relaxation are introduced into the model for two-way semi-crystalline SMP, which is able to reveal the mechanisms of three different 2W-SMEs

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described