5,998 research outputs found
Visual Detection of Structural Changes in Time-Varying Graphs Using Persistent Homology
Topological data analysis is an emerging area in exploratory data analysis
and data mining. Its main tool, persistent homology, has become a popular
technique to study the structure of complex, high-dimensional data. In this
paper, we propose a novel method using persistent homology to quantify
structural changes in time-varying graphs. Specifically, we transform each
instance of the time-varying graph into metric spaces, extract topological
features using persistent homology, and compare those features over time. We
provide a visualization that assists in time-varying graph exploration and
helps to identify patterns of behavior within the data. To validate our
approach, we conduct several case studies on real world data sets and show how
our method can find cyclic patterns, deviations from those patterns, and
one-time events in time-varying graphs. We also examine whether
persistence-based similarity measure as a graph metric satisfies a set of
well-established, desirable properties for graph metrics
Options for Securing RTP Sessions
The Real-time Transport Protocol (RTP) is used in a large number of
different application domains and environments. This heterogeneity
implies that different security mechanisms are needed to provide
services such as confidentiality, integrity, and source
authentication of RTP and RTP Control Protocol (RTCP) packets
suitable for the various environments. The range of solutions makes
it difficult for RTP-based application developers to pick the most
suitable mechanism. This document provides an overview of a number
of security solutions for RTP and gives guidance for developers on
how to choose the appropriate security mechanism
Comparison of Interactive Visualization Techniques for Origin-Destination Data Exploration
Origin-Destination (OD) data is a crucial part of price estimation in the aviation industry, and an
OD flight is any number of flights a passenger takes in a single journey. OD data is a complex set
of data that is both flow and multidimensional type of data.
In this work, the focus is to design interactive visualization techniques to support user exploration
of OD data. The thesis work aims to find which of the two menu designs suit better for OD data
visualization: breadth-first or depth-first menu design. The two menus follow Schneiderman’s Task
by Data Taxonomy, a broader version of the Information Seeking Mantra.
The first menu design is a parallel, breadth-first menu layout. The layout shows the variables in
an open layout and is closer to the original data matrix. The second menu design is a hierarchical,
depth-first layout. This layout is derived from the semantics of the data and is more compact in
terms of screen space.
The two menu designs are compared in an online survey study conducted with the potential end
users. The results of the online survey study are inconclusive, and therefore are complemented
with an expert review. Both the survey study and expert review show that the Sankey graph
is a good visualization type for this work, but the interaction of the two menu designs requires
further improvements. Both of the menu designs received positive and negative feedback in the
expert review. For future work, a solution that combines the positives of the two designs could be
considered.
ACM Computing Classification System (CCS):
Human-Centered Computing → Visualization → Empirical Studies in Visualization
Human-centered computing → Interaction design → Interaction design process and methods →
Interface design prototypin
Stochastic methods for measurement-based network control
The main task of network administrators is to ensure that their network functions properly. Whether they manage a telecommunication or a road network, they generally base their decisions on the analysis of measurement data. Inspired by such network control applications, this dissertation investigates several stochastic modelling techniques for data analysis. The focus is on two areas within the field of stochastic processes: change point detection and queueing theory. Part I deals with statistical methods for the automatic detection of change points, being changes in the probability distribution underlying a data sequence. This part starts with a review of existing change point detection methods for data sequences consisting of independent observations. The main contribution of this part is the generalisation of the classic cusum method to account for dependence within data sequences. We analyse the false alarm probability of the resulting methods using a large deviations approach. The part also discusses numerical tests of the new methods and a cyber attack detection application, in which we investigate how to detect dns tunnels. The main contribution of Part II is the application of queueing models (probabilistic models for waiting lines) to situations in which the system to be controlled can only be observed partially. We consider two types of partial information. Firstly, we develop a procedure to get insight into the performance of queueing systems between consecutive system-state measurements and apply it in a numerical study, which was motivated by capacity management in cable access networks. Secondly, inspired by dynamic road control applications, we study routing policies in a queueing system for which just part of the jobs are observable and controllable
Highlighting in information visualization: A survey
Highlighting was the basic viewing control mechanism in computer graphics and visualization to guide users' attention in reading diagrams, images, graphs and digital texts. As the rapid growth of theory and practice in information visualization, highlighting has extended its role that acts as not only a viewing control, but also an interaction control and a graphic recommendation mechanism in knowledge visualization and visual analytics. In this work, we attempt to give a formal summarization and classification of the existing highlighting methods and techniques that can be applied in Information Visualization, Visual Analytics and Knowledge Visualization. We propose a new three-layer model of highlighting. We discuss the responsibilities of each layer in the different stage of the visual information processing. © 2010 IEEE
Visualization Techniques for the Analysis of Neurophysiological Data
In order to understand the diverse and complex functions of the Human brain, the temporal relationships
of vast quantities of multi-dimensional spike train data must be analysed. A number of statistical
methods already exist to analyse these relationships. However, as a result of expansions in recording
capability hundreds of spike trains must now be analysed simultaneously.
In addition to the requirements for new statistical analysis methods, the need for more efficient data
representation is paramount. The computer science field of Information Visualization is specifically
aimed at producing effective representations of large and complex datasets. This thesis is based on
the assumption that data analysis can be significantly improved by the application of Information
Visualization principles and techniques.
This thesis discusses the discipline of Information Visualization, within the wider context of visualization.
It also presents some introductory neurophysiology focusing on the analysis of multidimensional
spike train data and software currently available to support this problem. Following this,
the Toolbox developed to support the analysis of these datasets is presented. Subsequently, three case
studies using the Toolbox are described. The first case study was conducted on a known dataset in
order to gain experience of using these methods. The second and third case studies were conducted
on blind datasets and both of these yielded compelling results
From Social Simulation to Integrative System Design
As the recent financial crisis showed, today there is a strong need to gain
"ecological perspective" of all relevant interactions in
socio-economic-techno-environmental systems. For this, we suggested to set-up a
network of Centers for integrative systems design, which shall be able to run
all potentially relevant scenarios, identify causality chains, explore feedback
and cascading effects for a number of model variants, and determine the
reliability of their implications (given the validity of the underlying
models). They will be able to detect possible negative side effect of policy
decisions, before they occur. The Centers belonging to this network of
Integrative Systems Design Centers would be focused on a particular field, but
they would be part of an attempt to eventually cover all relevant areas of
society and economy and integrate them within a "Living Earth Simulator". The
results of all research activities of such Centers would be turned into
informative input for political Decision Arenas. For example, Crisis
Observatories (for financial instabilities, shortages of resources,
environmental change, conflict, spreading of diseases, etc.) would be connected
with such Decision Arenas for the purpose of visualization, in order to make
complex interdependencies understandable to scientists, decision-makers, and
the general public.Comment: 34 pages, Visioneer White Paper, see http://www.visioneer.ethz.c
A unified ontology-based data integration approach for the internet of things
Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cloud-based IoT platforms to build a schema for data generated from diverse sources. We tested the proposed model on real data consisting of approximately 160,000 readings from various sources in different formats like CSV, JSON, raw data, and XML. The data were collected through the file transfer protocol (FTP) and generated 960,000 resource description framework (RDF) triples. We evaluated the proposed approach by running different queries on different machines on SPARQL protocol and RDF query language (SPARQL) endpoints to check query processing time, validation of integration, and performance of the unified ontology model. The average response time for query execution on generated RDF triples on the three servers were approximately 0.144 seconds, 0.070 seconds, 0.062 seconds, respectively
Cycling as Reading a Cityscape: A Phenomenological Approach to Interface-Shaped Perception
This essay attempts to assess whether the perceptual issues posed by the contemporary interface culture, and the constant attitude shift demanded by the new media between the “natural” and the “as if” modes, might be considered a significant challenge for phenomenological aesthetics as understood in terms of Merleau-Ponty’s phenomenology of perception. To demonstrate how the use of a particular interface profoundly shapes the form and structure of an activity as well as enabling perception of a particular kind, the author does not focus directly on the state-of-the-art smart interfaces, but describes the experience of cycling in a large city, with the interface in the form of the bicycle upgraded with an imagined ride simulator. While the former enables a very particular entrance into the world of perception, shaped by its moderate speed and detachment from the ground, the latter enables techno-shaped perception in the “as if” screenic mode. The experience described raises questions concerning the kinaesthetic, proprioceptive and motor features contributing to the cyclist’s mobile perception, as well as pointing to issues related to the reading of the city’s network as a particular spatial configuration generated by the cyclist’s realtime activity. This is the space-time-event-ridescape maintained and modified by the corporeal act
of cycling. The spatiality of such a ride does not presume the notion of a space that contains the cyclist, but builds on notions of being-in-the-ridescape (as a kind of cityscape), in terms not only of full corporeal and mental engagement, but also of bodily literacy. The reading of the cityscape enabled by the combination of two interfaces, the bicycle and the ride simulator, is discussed in relation to de Certeau’s account of pedestrian (walking) experience in a big city, his distinction between strategies and tactics, and the notion that each cyclist contributes a novel story to ridetext, which is viewed not as an aesthetic object but as the production of puzzles for the rider to solve. The paper cocludes by questioning the capacity of phenomenology to accommodate the contemporary phenomenon of a “mixed” or “augmented reality” either in concept or in relation to the demands of the phenomenological reduction and the ends of the epoché.
Indo-Pacific Journal of Phenomenology, Volume 10, Edition 2, October 2010: 61-7
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