Low-latency, query-driven analytics over voluminous multidimensional, spatiotemporal datasets

2017 Summer.Includes bibliographical references.Ubiquitous data collection from sources such as remote sensing equipment, networked observational devices, location-based services, and sales tracking has led to the accumulation of voluminous datasets; IDC projects that by 2020 we will generate 40 zettabytes of data per year, while Gartner and ABI estimate 20-35 billion new devices will be connected to the Internet in the same time frame. The storage and processing requirements of these datasets far exceed the capabilities of modern computing hardware, which has led to the development of distributed storage frameworks that can scale out by assimilating more computing resources as necessary. While challenging in its own right, storing and managing voluminous datasets is only the precursor to a broader field of study: extracting knowledge, insights, and relationships from the underlying datasets. The basic building block of this knowledge discovery process is analytic queries, encompassing both query instrumentation and evaluation. This dissertation is centered around query-driven exploratory and predictive analytics over voluminous, multidimensional datasets. Both of these types of analysis represent a higher-level abstraction over classical query models; rather than indexing every discrete value for subsequent retrieval, our framework autonomously learns the relationships and interactions between dimensions in the dataset (including time series and geospatial aspects), and makes the information readily available to users. This functionality includes statistical synopses, correlation analysis, hypothesis testing, probabilistic structures, and predictive models that not only enable the discovery of nuanced relationships between dimensions, but also allow future events and trends to be predicted. This requires specialized data structures and partitioning algorithms, along with adaptive reductions in the search space and management of the inherent trade-off between timeliness and accuracy. The algorithms presented in this dissertation were evaluated empirically on real-world geospatial time-series datasets in a production environment, and are broadly applicable across other storage frameworks

Director's Discretionary Fund Report for Fiscal Year 1996

Topics covered include: Waterproofing the Space Shuttle tiles, thermal protection system for Reusable Launch Vehicles, computer modeling of the thermal conductivity of cometary ice, effects of ozone depletion and ultraviolet radiation on plants, a novel telemetric biosensor to monitor blood pH on-line, ion mobility in polymer electrolytes for lithium-polymer batteries, a microwave-pumped far infrared photoconductor, and a new method for measuring cloud liquid vapor using near infrared remote sensing. Also included: laser-spectroscopic instrument for turbulence measurement, remote sensing of aircraft contrails using a field portable imaging interferometer, development of a silicon-micromachined gas chromatography system for determination of planetary surface composition, planar Doppler velocimetry, chaos in interstellar chemistry, and a limited pressure cycle engine for high-speed output

Autonomous, Collaborative, Unmanned Aerial Vehicles for Search and Rescue

Search and Rescue is a vitally important subject, and one which can be improved through the use of modern technology. This work presents a number of advances aimed towards the creation of a swarm of autonomous, collaborative, unmanned aerial vehicles for land-based search and rescue. The main advances are the development of a diffusion based search strategy for route planning, research into GPS (including the Durham Tracker Project and statistical research into altitude errors), and the creation of a relative positioning system (including discussion of the errors caused by fast-moving units). Overviews are also given of the current state of research into both UAVs and Search and Rescue

Computational Frameworks for Multi-Robot Cooperative 3D Printing and Planning

This dissertation proposes a novel cooperative 3D printing (C3DP) approach for multi-robot additive manufacturing (AM) and presents scheduling and planning strategies that enable multi-robot cooperation in the manufacturing environment. C3DP is the first step towards achieving the overarching goal of swarm manufacturing (SM). SM is a paradigm for distributed manufacturing that envisions networks of micro-factories, each of which employs thousands of mobile robots that can manufacture different products on demand. SM breaks down the complicated supply chain used to deliver a product from a large production facility from one part of the world to another. Instead, it establishes a network of geographically distributed micro-factories that can manufacture the product at a smaller scale without increasing the cost. In C3DP, many printhead-carrying mobile robots work together to print a single part cooperatively. While it holds the promise to mitigate issues associated with gantry-based 3D printers, such as lack of scalability in print size and print speed, its realization is challenging because existing studies in the relevant literature do not address the fundamental issues in C3DP that stem from the amalgamation of the mobile nature of the robots, and continuous nature of the manufacturing tasks. To address this challenge, this dissertation asks two fundamental research questions: RQ1) How can the traditional 3D printing process be transformed to enable multi-robot cooperative AM? RQ2) How can cooperative manufacturing planning be realized in the presence of inherent uncertainties in AM and constraints that are dynamic in both space and time? To answer RQ1, we discretize the process of 3D printing into multiple stages. These stages include chunking (dividing a part into smaller chunks), scheduling (assigning chunks to robots and generating print sequences), and path and motion planning. To test the viability of the approach, we conducted a study on the tensile strength of chunk-based parts to examine their mechanical integrity. The study demonstrates that the chunk-based part can be as strong as the conventionally 3D-printed part. Next, we present different computational frameworks to address scheduling issues in C3DP. These include the development of 1) the world-first working strategy for C3DP, 2) a framework for automatic print schedule generation, evaluation, and validation, and 3) a resource-constrained scheduling approach for C3DP that uses a meta-heuristic approach such as a modified Genetic Algorithm (MGA) and a new algorithm that uses a constraint-satisficing approach to obtain collision-free print schedules for C3DP. To answer RQ2, a multi-robot decentralized approach based on a simple set of rules is used to plan for C3DP. The approach is resilient to uncertainties such as variation in printing times and can even outperform the centralized approach that uses MGA with a conflict-based search for large-scale problems. By answering these two fundamental questions, the central objective of the research project to establish computational frameworks to enable multi-robot cooperative manufacturing was achieved. The search for answers to the RQs led to the development of novel concepts that can be used not only in C3DP, but many other manufacturing tasks, in general, requiring cooperation among multiple robots

TransFormers for Extreme Environments: Projecting Favorable Micro-Environments Around Robots and Areas of Interest

Surviving Extreme Space Environments (EE) is one of NASAs Space Technology Grand Challenges; we propose a paradigm shift in addressing this challenge. TransFormers (TFs) transform a region of an extreme environment into a favorable micro-environment, projecting energy at the precise location where robots or humans operate. TFs often use shape transformation to control the energy projection

2005 Annual Research Symposium Abstract Book

2005 annual volume of abstracts for science research projects conducted by students at Trinity College

Sustainable Development, Ecological Complexity, and Environmental Values

Sustainable Development, Ecological Complexity, and Environmental Values contributes to expanding the idea of sustainability by integrating different thematic issues related to sustainable development in its threefold consideration (economic, social, and environmental) with regard to the case of the Basque Country. On the global scale, changes have clearly accelerated; ecological and social sustainability are two facets of the same changing reality. First, social sustainability depends on ecological sustainability. If we continue degrading nature's capacity to produce the ecosystems' services (water filtration, climate stabilization, etc) and resources (food, materials), both individuals and nations will be affected by growing pressures and increasing conflicts, as well as by threats to public health and personal safety. Second, ecological sustainability depends on social sustainability, a socially unjust and unfair system wiht an ever-increasing population that is not able to have its needs met will necessarily lead to environmental collapse. In addition, human behavior and the social dynamic often lie at the heart of social and ecological problems. It must be, therefore, assumed that there will not be sustainable development if sustainable societies do not first exist. A sustainable society has the challenge of developing human capital. In this book, these global questions are treated as they relate to specific place and context, the Basque Country and its modern institutions.This book was published with generous financial support from the Basque Government.Introduction—Ignacio Ayestarán and Miren Onaindia ? 1. An Evaluation of Ecosystem Services as a Base for the Sustainable Management of a Region by Miren Onaindia and Gloria Rodríguez-Loinaz ? 2. An Evaluation of Millennium Ecosystems from the Basque Country by Igone Palacios, Izaskun Casada-Arzuaga, Iosu Madariaga, and Xabier Arana ? 3. Climate Change: Activities of the EOLO Group at the University of the Basque Country by Agustín Ezcurra, Jon Sáenz, and Gabriel Ibarra-Berastegi ? 4. The Environmental Value of the Karstic Landscape of the Urdaibai Biosphere Reserve: The Asnarre Promontory (Bizkaia) by Arantza Aranburu, Laura Damas-Mollá, Patxi García-Garmilla, Iñaki Yusta, M. Arriolabengoa, Peru Iridoy, and Eneko Iriarte ? 5. Recent Environmental Transformation of the Bilbao Estuary: Natural and Anthropogenic Processes by Alejandro Cearreta, Maria Jesús Irabien, and Eduardo Leorri ? 6. The Landscape of the Autonomous Community of the Basque Country: The Evolution of Forest Systems by Lorena Peña and Ibone Amezaga ? 7. Critical Theories of Sustainable Development by Eguzki Urteaga ? 8. Bases for the Transition toward a Sustainable Economy by Roberto Bermejo, David Hoyos, and Eneko Garmendia ? 9. Environmental Values, the Epistemology of Complex Problems, and Postnormal Science in the Face of Global Change by Ignacio Ayestáran ? 10. Science, Gender, and Sustainable Development by Teresa Nuño Angós ? 11. Environmental Education as Training: A Case Study at the University of the Basque Country by Araitz Uskola Ibarluzea ? 12. Social Values and Sustainable Practices among Basque Inshore Fishermen by Pío Pérez Aldasoro ? 13. Sustainable Development and the Values of Well-Being and Globalization by Eduardo Rubio Ardanaz, Juan Antonio Rubio-Ardanaz, and Xiao Fang ? Index ? List of Contributor

Approximate Computing Survey, Part II: Application-Specific & Architectural Approximation Techniques and Applications

The challenging deployment of compute-intensive applications from domains such Artificial Intelligence (AI) and Digital Signal Processing (DSP), forces the community of computing systems to explore new design approaches. Approximate Computing appears as an emerging solution, allowing to tune the quality of results in the design of a system in order to improve the energy efficiency and/or performance. This radical paradigm shift has attracted interest from both academia and industry, resulting in significant research on approximation techniques and methodologies at different design layers (from system down to integrated circuits). Motivated by the wide appeal of Approximate Computing over the last 10 years, we conduct a two-part survey to cover key aspects (e.g., terminology and applications) and review the state-of-the art approximation techniques from all layers of the traditional computing stack. In Part II of our survey, we classify and present the technical details of application-specific and architectural approximation techniques, which both target the design of resource-efficient processors/accelerators & systems. Moreover, we present a detailed analysis of the application spectrum of Approximate Computing and discuss open challenges and future directions.Comment: Under Review at ACM Computing Survey

Index to 1986 NASA Tech Briefs, volume 11, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1986 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences