Searching for Smallest Grammars on Large Sequences and Application to DNA

International audienceMotivated by the inference of the structure of genomic sequences, we address here the smallest grammar problem. In previous work, we introduced a new perspective on this problem, splitting the task into two different optimization problems: choosing which words will be considered constituents of the final grammar and finding a minimal parsing with these constituents. Here we focus on making these ideas applicable on large sequences. First, we improve the complexity of existing algorithms by using the concept of maximal repeats when choosing which substrings will be the constituents of the grammar. Then, we improve the size of the grammars by cautiously adding a minimal parsing optimization step. Together, these approaches enable us to propose new practical algorithms that return smaller grammars (up to 10\%) in approximately the same amount of time than their competitors on a classical set of genomic sequences and on whole genomes of model organisms

A Review of Subsequence Time Series Clustering

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies

Master of Music in Composition

This portfolio of compositions involved the creation of multimedia works within the context of collaborative artistic practice. This interest has resulted from my increasing participation in multidisciplinary collaborative projects in recent years as a composer and singer. In the portfolio of works I have drawn on a range of theoretical texts from the fields of cognitive science, psychology, sociology and spirituality to develop a supportive discourse with which to reflect on the creative intersection of activities. Five collaborative compositions were created and realised. These range from a self-generative installation to a traditional film score. To examine the creative process, I have constructed a continuum that situates each piece between polarities of product or process-driven work. On one side of this continuum is Beads, a generative sound/video installation which explores video tracking as a compositional agent. At the opposite pole is The Old Woman in the Woods, a typical cinematic film score. Situated between these two extreme points are Terroir, Let It Go, and Aspects of Trees. Aspects of Trees is a hyperimprovisational system for visual projections, live cello, and software application. Let it Go explores the balance between improvisation, composition and “composed” instruments. Terroir is a fixed media experimental film which uses a single data source collected from an old cell phone

A holistic view of the creative potential of performance practice in contemporary music

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityThe creative potential and work of the performer in new music extends from the moment of conceptualising a concert to the moment of presenting it on stage and comprises many areas between and around those two points. In this thesis I explore the nature of this activity, from the act of playing itself to the commissioning and creating of new pieces, curatorial and collaborative tasks, and the actual concert presentation. I deliberately include interrelations between performer and music promoters, composers and the audience. This leads me to further areas of investigation, namely the question of the performer’s leadership, the charismatic bond with the audience and the creation of what I call “concert aura”. I do not strive to offer all-purpose formulae for the “perfect concert” or for the ideal collaboration. I investigate performance practice not as an absolute art but rather as something embedded in and shaped by social relations and society. Accordingly I understand this thesis as an empirically based study of the questions performers could ask, as well as processes in which they might want to engage, to find meaningful solutions for each new situation. Not all of the questions I raise will be new to each performer, but in their collaborative and concert practice many performers rely on a random, unsystematic, empirical understanding that has been gained by chance. In contrast, I attempt to draw a theoretical basis for my investigation from the fields of psychology, philosophy, media science and sociology, together with the evaluation of my own and other artists’ performance practice. In this way I hope to develop an academic foundation and a comprehensive, systematic approach that can be applied to different collaboration and concert situations. Part 1 of my thesis is concerned with theories and concepts relating to creativity, collaboration and presentation (concert aura and charisma) and aims to establish a firm theoretical basis for application in practice. Part 2 presents, discusses and analyses a selection of case studies from my own practice, considered in relation to the theories discussed in the first part. I conclude by offering guidelines to collaboration and giving a model example of how one might plan a future performance, aiming to create a Gesamtkunstwerk through the totality of the preparation and presentation, its social and psychological connotations. The thesis includes two DVDs with Quicktime Movies and two CDs with recordings of the compositions, commissioned as part of this research and discussed throughout the thesis. The Appendix contains three sample-CDs with an accompanying commentary which give an introduction to contemporary playing techniques for the acoustic and electronic violin and acoustic viola. This CD is intended as a guide for composers to get acquainted with the instruments and was given to each composer involved in this research

Outward-Orientation and Development: Are Revisionists Right

The costs of import substitution (IS) as a strategy for industrialization, which was deemed synonymous with economic development by many development economists of the fifties and sixties, were shown to be substantial in the influential and nuanced studies of the seventies and eighties under the auspices of OECD, NBER and World Bank. These studies played a critical role in shifting policies in several developing countries away from the IS strategy. Recently there has been a proliferation of cross country regressions as a methodology of analysis of issues relating to growth, trade and other issues. Both proponents (e.g. Sachs and Warner (1995)) and opponents (Rodriguez and Rodrik (1999)) of the view that openness to trade is linked to higher growth have relied on such regressions. The paper systematically reviews the theoretical and empirical studies on such linkage. It rejects the cross-country regression methodology for reasons of their weak theoretical foundation, poor quality of their data base and their inappropriate econometric methodologies. It argues that the most compelling evidence on this issue can come only from careful case studies of policy regimes of individual entries such as those of OECD, NBER and World Bank. It concludes that the virtues of openness established in these nuanced in-depth studies remain unrefuted.Developing Countries, Economic Development, Economic Growth, International Trade, Openness, Import Substitution, Export Promotion, Cross-Country Regressions

AIDIS: Detecting and Classifying Anomalous Behavior in UbiquitousKernel Processes

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Targeted attacks on IT systems are a rising threat against the confidentiality, integrity, and availability of critical information and infrastructures. With the rising prominence of advanced persistent threats (APTs), identifying and under-standing such attacks has become increasingly important. Current signature-based systems are heavily reliant on fixed patterns that struggle with unknown or evasive applications, while behavior-based solutions usually leave most of the interpretative work to a human analyst.In this article we propose AIDIS, an Advanced Intrusion Detection and Interpretation System capable to explain anomalous behavior within a network-enabled user session by considering kernel event anomalies identified through their deviation from a set of baseline process graphs. For this purpose we adapt star-structures, a bipartite representation used to approximate the edit distance be-tween two graphs. Baseline templates are generated automatically and adapt to the nature of the respective operating system process.We prototypically implemented smart anomaly classification through a set of competency questions applied to graph template deviations and evaluated the approach using both Random Forest and linear kernel support vector machines.The determined attack classes are ultimately mapped to a dedicated APT at-tacker/defender meta model that considers actions, actors, as well as assets and mitigating controls, thereby enabling decision support and contextual interpretation of ongoing attack

Advanced Threat Intelligence: Interpretation of Anomalous Behavior in Ubiquitous Kernel Processes

Targeted attacks on digital infrastructures are a rising threat against the confidentiality, integrity, and availability of both IT systems and sensitive data. With the emergence of advanced persistent threats (APTs), identifying and understanding such attacks has become an increasingly difficult task. Current signature-based systems are heavily reliant on fixed patterns that struggle with unknown or evasive applications, while behavior-based solutions usually leave most of the interpretative work to a human analyst. This thesis presents a multi-stage system able to detect and classify anomalous behavior within a user session by observing and analyzing ubiquitous kernel processes. Application candidates suitable for monitoring are initially selected through an adapted sentiment mining process using a score based on the log likelihood ratio (LLR). For transparent anomaly detection within a corpus of associated events, the author utilizes star structures, a bipartite representation designed to approximate the edit distance between graphs. Templates describing nominal behavior are generated automatically and are used for the computation of both an anomaly score and a report containing all deviating events. The extracted anomalies are classified using the Random Forest (RF) and Support Vector Machine (SVM) algorithms. Ultimately, the newly labeled patterns are mapped to a dedicated APT attacker–defender model that considers objectives, actions, actors, as well as assets, thereby bridging the gap between attack indicators and detailed threat semantics. This enables both risk assessment and decision support for mitigating targeted attacks. Results show that the prototype system is capable of identifying 99.8% of all star structure anomalies as benign or malicious. In multi-class scenarios that seek to associate each anomaly with a distinct attack pattern belonging to a particular APT stage we achieve a solid accuracy of 95.7%. Furthermore, we demonstrate that 88.3% of observed attacks could be identified by analyzing and classifying a single ubiquitous Windows process for a mere 10 seconds, thereby eliminating the necessity to monitor each and every (unknown) application running on a system. With its semantic take on threat detection and classification, the proposed system offers a formal as well as technical solution to an information security challenge of great significance.The financial support by the Christian Doppler Research Association, the Austrian Federal Ministry for Digital and Economic Affairs, and the National Foundation for Research, Technology and Development is gratefully acknowledged

The measurement, evolution, and neural representation of action grammars of human behavior

Human behaviors from toolmaking to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Testing this idea will require objective, generalizable methods for measuring the structural complexity of real-world behavior. Here we present a data-driven approach for extracting action grammars from basic ethograms, exemplified with respect to the evolutionarily relevant behavior of stone toolmaking. We analyzed sequences from the experimental replication of ~ 2.5 Mya Oldowan vs. ~ 0.5 Mya Acheulean tools, finding that, while using the same “alphabet” of elementary actions, Acheulean sequences are quantifiably more complex and Oldowan grammars are a subset of Acheulean grammars. We illustrate the utility of our complexity measures by re-analyzing data from an fMRI study of stone toolmaking to identify brain responses to structural complexity. Beyond specific implications regarding the co-evolution of language and technology, this exercise illustrates the general applicability of our method to investigate naturalistic human behavior and cognition

Phrase based browsing for simulation traces of network protocols

Most discrete event simulation frameworks are able to out-put simulation runs as a trace. The Network Simulator 2 (NS2) is a prominent example that does so to decouple generation of dynamic behavior from its evaluation. If a modeler is interested in the specific details and confronted with lengthy traces from simulation runs, support is needed to identify relevant pieces of information. In this paper, we present a new phrase-based browser that has its roots in information retrieval, language acquisition and text com-pression which is refined to work with trace data derived from simulation models. The browser is a new navigation feature of Traviando, a trace visualizer and analyzer for sim-ulation traces. The browsing technique allows a modeler to investigate particular patterns seen in a trace, that may be of interest due to their frequent or rare occurrence. We demonstrate how this approach applies to traces generated with NS2.