Abstract visualization of large-scale time-varying data

The explosion of large-scale time-varying datasets has created critical challenges for scientists to study and digest. One core problem for visualization is to develop effective approaches that can be used to study various data features and temporal relationships among large-scale time-varying datasets. In this dissertation, we first present two abstract visualization approaches to visualizing and analyzing time-varying datasets. The first approach visualizes time-varying datasets with succinct lines to represent temporal relationships of the datasets. A time line visualizes time steps as points and temporal sequence as a line. They are generated by sampling the distributions of virtual words across time to study temporal features. The key idea of time line is to encode various data properties with virtual words. We apply virtual words to characterize feature points and use their distribution statistics to measure temporal relationships. The second approach is ensemble visualization, which provides a highly abstract platform for visualizing an ensemble of datasets. Both approaches can be used for exploration, analysis, and demonstration purposes. The second component of this dissertation is an animated visualization approach to study dramatic temporal changes. Animation has been widely used to show trends, dynamic features and transitions in scientific simulations, while animated visualization is new. We present an automatic animation generation approach that simulates the composition and transition of storytelling techniques and synthesizes animations to describe various event features. We also extend the concept of animated visualization to non-traditional time-varying datasets--network protocols--for visualizing key information in abstract sequences. We have evaluated the effectiveness of our animated visualization with a formal user study and demonstrated the advantages of animated visualization for studying time-varying datasets

Finding My Voice: Surviving Childhood Sexual Abuse

This autobiographical study reflects experiences of surviving child sexual abuse and my journey through curriculum studies as a route to finding power through my voices. Using currere as a lead theory to frame this work, this study reveals a first-person account of sexual abuse to detail my development to empowerment and how I learned to advocate for myself and other childhood victims. Within this work, the method of currere, psychoanalytic theory, focusing, hypnosis, and healing through writing are discussed as processes for increasing self-understanding

Following (big) data in the smart city: control rooms, expertise and obligatory passage points in Santiago's public transport

Smart cities and big data have been at the forefront of urban discussions and projects over the last decade. Big data has arisen as a critical feature of the smart city to face urban challenges, usually framed by projects and policies promoting a direct relationship whereby more volume, variety, velocity and fine-detailed data will necessarily lead to better-informed decisions and, therefore, to the more effective and efficient government of cities. However, these approaches generally ignore how big data circulates and what it does. In this dissertation, I offer an alternative to previous formulations of big data in the smart city. Accordingly, I aim to analyse how data circulates in Santiago de Chile's public transport and what it does when it circulates. Drawing on the case of Santiago de Chile's public transport, I describe and analyse the emergent configurations, practices and governing techniques which enable big data to circulate. This creates what I call the data dispositif. I work with an experimental "following the data" methodology to identify how data circulation problems and their subsequent solutions emerge in Transantiago after more than ten years of implementation. Accordingly, I find that enabling big data circulation requires taking care of three emerging problems: the problem of control room fragmentation, the problem of experts and expertise, and the problem of translation. I argue that these problems are generative of specific solutions, taking the form of policies, indicators, standards, and new skills, which together produce new arrangements that allow data to circulate in ways beyond the initial operational objectives of public transport

PkCOs: synchronisation of packet-coupled oscillators in blast wave monitoring networks

Blast waves with a large amount of energy, from the use of explosive weapons, is a major cause of traumatic brain injury in armed and security forces. The monitoring of blast waves is required for defence and civil applications. The utilisation of wireless sensing technology to monitor blast waves has shown great advantages such as easy deployment and flexibility. However, due to drifting embedded clock frequency, the establishment of a common timescale among distributed blast monitoring sensors has been a challenge, which may lead to a network failing to estimate the precise acoustic source location. This work adopts a Packet-Coupled Oscillators (PkCOs) protocol to synchronise drifting clocks in a wireless blast wave monitoring network. In order to address packet collisions caused by the concurrent transmission, an anti-phase synchronisation solution is utilised to maintain clock synchronisation, and the corresponding superframe structure is developed to allow the hybrid transmission of the Sync packet and the blast wave monitoring data. As a network scales up and the hop distance grows, the packet exchange lag increases during a superframe. This, along with the drifting clock frequency, leads to the degradation of synchronisation performance while the clock frequency is usually assumed to be zero and non-drifting. Thus, a compensation strategy is proposed to eliminate the joint impacts and to improve the synchronisation precision. The theoretical performance analysis of the PkCOs algorithm in the network is presented along with verification by simulation means. Finally, the performance of the PkCOs synchronisation protocol is evaluated on an IEEE 802.15.4 hardware testbed. The experimental results show that the PkCOs algorithm provides an alternative clock synchronisation solution for blast wave monitoring networks

Proactive Retrospective Installation in Second Life: Using Currere to Explore Educational Perception, Reflection, Understanding and Development of Graduate Students Engaged in Virtual Exhibitions

This is an unprecedented study integrating of Second Life (SL) and the currere approach to develop a virtual curriculum demonstration. The overarching purposes of this study were to understand the perceptions, self-reflection, self-understanding, educational growth of graduate students in education toward teaching and learning in a virtual interdisciplinary curriculum. The three-dimensional virtual world of Second Life is a distance learning platform and multimedia combination of animations, dynamic images, embedded videos, websites, simulative worlds, slide shows and media players. The theoretical framework is based on the currere approach?a curriculum technique used to reconstruct social, intellectual, and physical systems. Data was collected in two education graduate courses in 2011 at a public university located in central Texas. After participating with SL skill trainings, the participants engaged in two virtual SL exhibitions?war and ecology?which were designed in the framework of the four currere steps?regression, progression, analysis, and synthesis. Data was collected via observations, SL reflective writings, individual currere writings, and voluntary interviews. The results revealed how SL exhibitions, based on the four-step currere approach, benefit the participants. In the regressive step, the virtual installations stimulated participants' emotions and vivid memories toward the presented topics. In the progressive step, the SL exhibitions awakened participants' awareness to educate the public on the global issues and integrate them into school subjects. In the analytic step, the exhibitions allowed participants to ruminate and re-exam the past, present and future, as well as to reflect on their own consciousness. In the synthetical stage, participants reflected and inflected their own perspectives toward the learning materials. Using the exhibitions' target knowledge, individuals were able to develop a self-understanding, which propelled them toward self-mobilization and educational reconstruction. Regarding SL curriculum development, the participants indicated SL innovative installation assisted them in extrapolating ideas for subject integration and interdisciplinary curriculum. In terms of technological utilization, SL changed the participants' perception about how integrating virtual technology into a classroom makes teaching and learning accommodating for distant students. In addition, this further motivates students to understand content more concretely and effectively. With regard to autobiographic emotional involvement, SL delivered the powerful images and videos to participants, which allowed them to understand why they possessed certain kinds of emotions toward specific events

Evaluation of Serverless Computing Frameworks Based on Kubernetes

Recent advancements in virtualization and software architectures have led to the birth of the new paradigm of serverless computing. Serverless computing, also known as function-as-a-service, allows developers to deploy functions as computing units without worrying about the underlying infrastructure. Moreover, no resources are allocated or billed until a function is invoked. Thus, the major benefits of serverless computing are reduced developer concern about infrastructure, reduced time to market and lower cost. Currently, serverless computing is generally available through various public cloud service providers. However, there are certain bottlenecks on public cloud platforms, such as vendor lock-in, computation restrictions and regulatory restrictions. Thus, there is a growing interest to implement serverless computing on a private infrastructure. One of the preferred ways of implementing serverless computing is through the use of containers. A container-based solution allows to utilize features of existing orchestration frameworks, such as Kubernetes. This thesis discusses the implementation of serverless computing on Kubernetes. To this end, we carry out a feature evaluation of four open source serverless computing frameworks, namely Kubeless, OpenFaaS, Fission and OpenWhisk. Based on predefined criteria, we select Kubeless, Fission and OpenFaaS for further evaluation. First, we describe the developer experience on each framework. Next, we compare three different modes in which OpenFaaS functions are executed: HTTP, serializing and streaming. We evaluate the response time of function invocation and ease of monitoring and management of logs. We find that HTTP mode is the preferred mode for OpenFaaS. Finally, we evaluate the performance of the considered frameworks under different workloads. We find that Kubeless has the best performance among the three frameworks, both in terms of response time and the ratio of successful responses

Summary Of The Second Army DIS Data Call: Technical Report

Report identifying user requirements, such as operational needs and corresponding functional requirements, so that effective decisions can be made regarding ongoing DIS development and use

Enabling the processing of bioinformatics workflows where data is located through the use of cloud and container technologies

>Magister Scientiae - MScThe growing size of raw data and the lack of internet communication technology to keep up with that growth is introducing unique challenges to academic researchers. This is especially true for those residing in rural areas or countries with sub-par telecommunication infrastructure. In this project I investigate the usefulness of cloud computing technology, data analysis workflow languages and portable computation for institutions that generate data. I introduce the concept of a software solution that could be used to simplify the way that researchers execute their analysis on data sets at remote sources, rather than having to move the data. The scope of this project involved conceptualising and designing a software system to simplify the use of a cloud environment as well as implementing a working prototype of said software for the OpenStack cloud computing platform. I conclude that it is possible to improve the performance of research pipelines by removing the need for researchers to have operating system or cloud computing knowledge and that utilising technologies such as this can ease the burden of moving data

A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles

While the convergence of Artificial Intelligence (AI) techniques with improved information technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it also introduced an increased amount of security and privacy threats. To ensure the security of IoVs data, privacy preservation methodologies have gained significant attention in the literature. However, these strategies also need specific adjustments and modifications to cope with the advances in IoVs design. In the interim, Federated Learning (FL) has been proven as an emerging idea to protect IoVs data privacy and security. On the other hand, Blockchain technology is showing prominent possibilities with secured, dispersed, and auditable data recording and sharing schemes. In this paper, we present a comprehensive survey on the application and implementation of Blockchain-Enabled Federated Learning frameworks for IoVs. Besides, probable issues, challenges, solutions, and future research directions for BC-Enabled FL frameworks for IoVs are also presented. This survey can further be used as the basis for developing modern BC-Enabled FL solutions to resolve different data privacy issues and scenarios of IoVs