Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “INTERNET”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,711 records · Page 95
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Parallel Heuristics for Scalable Community Detection

Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability to problems that can be solved on desktops. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose multiple heuristics that are designed to break the sequential barrier. Our heuristics are agnostic to the underlying parallel architecture. For evaluation purposes, we implemented our heuristics on shared memory (OpenMP) and distributed memory (MapReduce-MPI) machines, and tested them over real world graphs derived from multiple application domains (internet, biological, natural language processing). Experimental results demonstrate the ability of our heuristics to converge to high modularity solutions comparable to those output by the serial algorithm in nearly the same number of iterations, while also drastically reducing time to solution.

clustering, graph algorithms↗
DOE OSTI2015

SBIR Phase II Final Report - Multi-Protocol Energy Management Gateway for Home-Area Networks

Significant amounts of electricity, natural gas, and heating oil are wasted by homeowners due to inefficient operation and inadequate maintenance of heating, ventilation, and air conditioning (HVAC) equipment. Coincident’s work under this award reduces energy waste, saves consumers money, and reduces carbon emissions. It does so in three ways: First, Coincident’s approach replaces the traditional thermostat with a wireless network of sensors and controllers that measure temperature, humidity and occupancy in multiple rooms in the house. The “Internet of Things” is a technology trend holding the promise of ubiquitous inexpensive sensors. The reality, however, is that energy and HVAC monitoring and management is a patchwork of incompatible protocols and expensive proprietary technologies. Coincident’s multi-protocol architecture, developed in part under this award tackles this problem and brings low cost interoperable sensor and control devices to market. Second, the Coincident system eliminates hard-to-program and rigid thermostat schedules and instead provides automatic operation of heating and cooling by combining individual temperature and comfort preferences with energy-saving targets, real-time utility use information, weather data, and room utilization patterns. Energy efficiency technology must be appealing to consumers otherwise it will not be used. The Coincident user interface has engaging features such as remote control from any smart phone or web browser and per-room performance breakdowns. Expected energy savings resulting from more efficient operation of heating and air conditioning equipment are in the range of 10-20%. Third, the Coincident system provides heating and air-conditioning contractors with fine-grained performance data for every residence they support (subject to customer privacy controls). This data is integrated from diverse networks within the residence and includes HVAC performance and fuel use data. This information allows the partner to validate energy savings and identify potential system faults (whether from installation problems or maintenance issues). When combined with professional installation as part of high-efficiency HVAC upgrade, energy savings levels of 20-30% can be achieved. Economic feasibility of energy efficiency technology is one of the key challenges addressed in this award. The Coincident system is engineered to be delivered at a disruptive price point, making the system financially feasible for new and retrofit homes of all types and sizes. The Coincident system is intended to be sold through the HVAC professional—the industry most capable of improving HVAC efficiency. Providing HVAC contractors with detailed home performance data motivates them to sell the product, provides them with maintenance and upgrade revenue opportunities, and therefore delivers customer savings and environmental benefits. Having demonstrated technical and financial feasibility, Coincident has won additional grants and awards, participated in pilot projects, started partnership discussions with several HVAC equipment vendors, and has lined up several large channel partners ready to participate in large pilot rollouts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Performance Monitoring of Residential Hot Water Distribution Systems

Current water distribution systems are designed such that users need to run the water for some time to achieve the desired temperature, wasting energy and water in the process. We developed a wireless sensor network for large-scale, long time-series monitoring of residential water end use. Our system consists of flow meters connected to wireless motes transmitting data to a central manager mote, which in turn posts data to our server via the internet. This project also demonstrates a reliable and flexible data collection system that could be configured for various other forms of end use metering in buildings. The purpose of this study was to determine water and energy use and waste in hot water distribution systems in California residences. We installed meters at every end use point and the water heater in 20 homes and collected 1s flow and temperature data over an 8 month period. For a typical shower and dishwasher events, approximately half the energy is wasted. This relatively low efficiency highlights the importance of further examining the energy and water waste in hot water distribution systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Frequent Subgraph Discovery in Large Attributed Streaming Graphs

The problem of finding frequent subgraphs in large dynamic graphs has so far only consid- ered a dynamic graph as being represented by a series of static snapshots taken at various points in time. This representation of a dynamic graph does not lend itself well to real time processing of real world graphs like social networks or internet traffic which consist of a stream of nodes and edges. In this paper we propose an algorithm that discovers the frequent subgraphs present in a graph represented by a stream of labeled nodes and edges. Our algorithm is efficient and consists of tunable parameters that can be tuned by the user to get interesting patterns from various kinds of graph data. In our model updates to the graph arrive in the form of batches which contain new nodes and edges. Our algorithm con- tinuously reports the frequent subgraphs that are estimated to be found in the entire graph as each batch arrives. We evaluate our system using 5 large dynamic graph datasets: the Hetrec 2011 challenge data, Twitter, DBLP and two synthetic. We evaluate our approach against two popular large graph miners, i.e., SUBDUE and GERM. Our experimental re- sults show that we can find the same frequent subgraphs as a non-incremental approach applied to snapshot graphs, and in less time.

Dynamic graph, Frequent subgraph mining, pattern d↗
DOE OSTI2015

Rapid deployable global sensing hazard alert system

A rapid deployable global sensing hazard alert system and associated methods of operation are provided. An exemplary system includes a central command, a wireless backhaul network, and a remote monitoring unit. The remote monitoring unit can include a positioning system configured to determine a position of the remote monitoring unit based on one or more signals received from one or more satellites located in Low Earth Orbit. The wireless backhaul network can provide bidirectional communication capability independent of cellular telecommunication networks and the Internet. An exemplary method includes instructing at least one of a plurality of remote monitoring units to provide an alert based at least in part on a location of a hazard and a plurality of positions respectively associated with the plurality of remote monitoring units.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

EXAMINING THE ROLE AND RESEARCH CHALLENGES OF SOCIAL MEDIA AS A TOOL FOR NONPROLIFERATION AND ARMS CONTROL TREATY VERIFICATION

Traditional arms control treaty verification activities typically involve a combination of technical measurements via physical and chemical sensors, state declarations, political agreements, and on-site inspections involving international subject matter experts. However, the ubiquity of the internet, and the electronic sharing of data that it enables, has made available a wealth of open source information with the potential to benefit verification efforts. Open source information is already being used by organizations such as the International Atomic Energy Agency to support the verification of state-declared information, prepare inspectors for in-field activities, and to maintain situational awareness . The recent explosion in social media use has opened new doors to exploring the attitudes, moods, and activities around a given topic. Social media platforms, such as Twitter, Facebook, and YouTube, offer an opportunity for individuals, as well as institutions, to participate in a global conversation at minimal cost. Social media data can also provide a more data-rich environment, with text data being augmented with images, videos, and location data. The research described in this paper investigates the utility of applying social media signatures as potential arms control and nonproliferation treaty verification tools and technologies, as determined through a series of case studies. The treaty relevant events that these case studies touch upon include detection of undeclared facilities or activities, determination of unknown events recorded by the International Monitoring System (IMS), and the global media response to the occurrence of an Indian missile launch. The case studies examine how social media can be used to fill an information gap and provide additional confidence to a verification activity. The case studies represent, either directly or through a proxy, instances where social media information may be available that could potentially augment the evaluation of an event. The goal of this paper is to instigate a discussion within the verification community as to where and how social media can be effectively utilized to complement and enhance traditional treaty verification efforts. In addition, this paper seeks to identify areas of future research and development necessary to adapt social media analytic tools and techniques, and to form the seed for social media analytics to aid and inform arms control and nonproliferation policymakers and analysts. While social media analysis (as well as open source analysis as a whole) will not ever be able to replace traditional arms control verification measures, they do supply unique signatures that can augment existing analysis.

nonproliferation, arms control, social media↗
DOE OSTI2015

Personalized professional content recommendation

A personalized content recommendation system includes a client interface configured to automatically monitor a user's information data stream transmitted on the Internet. A hybrid contextual behavioral and collaborative personal interest inference engine resident to a non-transient media generates automatic predictions about the interests of individual users of the system. A database server retains the user's personal interest profile based on a plurality of monitored information. The system also includes a server programmed to filter items in an incoming information stream with the personal interest profile and is further programmed to identify only those items of the incoming information stream that substantially match the personal interest profile.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2012

DNSViz

The Domain Name System Security Extensions (DNSSEC) add authentication to the DNS. However, analyzing and troubleshooting a DNSSEC deployment is difficult in part because of the protocol complexity and in part because authentication involves retrieving dependent components from a number of different Internet locations. DNSViz was written to bring all these DNSSEC components together into a single graph, so they can be represented visually, and nuances can be highlighted for easy identification. DNSViz includes functionality for both analyzing a domain name using active probing and visual representation of the domain name, available currently through a Web interface.

Deccio, Casey↗
DOE OSTI2013

Detecting and Analyzing Multiple Moving Objects in Crowded Environments with Coherent Motion Regions

Understanding the world around us from large-scale video data requires vision systems that can perform automatic interpretation. While human eyes can unconsciously perceive independent objects in crowded scenes and other challenging operating environments, automated systems have difficulty detecting, counting, and understanding their behavior in similar scenes. Computer scientists at ORNL have a developed a technology termed as "Coherent Motion Region Detection" that invloves identifying multiple indepedent moving objects in crowded scenes by aggregating low-level motion cues extracted from moving objects. Humans and other species exploit such low-level motion cues seamlessely to perform perceptual grouping for visual understanding. The algorithm detects and tracks feature points on moving objects resulting in partial trajectories that span coherent 3D region in the space-time volume defined by the video. In the case of multi-object motion, many possible coherent motion regions can be constructed around the set of trajectories. The unique approach in the algorithm is to identify all possible coherent motion regions, then extract a subset of motion regions based on an innovative measure to automatically locate moving objects in crowded environments.The software reports snapshot of the object, count, and derived statistics ( count over time) from input video streams. The software can directly process videos streamed over the internet or directly from a hardware device (camera).

Cheriyadat, Anil M.↗
DOE OSTI2014

Introduction to Cyber Technologies exercise environment

Exercise environment for Introduction to Cyber Technologies class. This software is essentially a collection of short scripts, configuration files, and small executables that form the exercise component of the Sandia Cyber Technologies Academy's Introduction to Cyber Technologies class. It builds upon other open-source technologies, such as Debian Linux and minimega, to provide comprehensive Linux and networking exercises that make learning these topics exciting and fun. Sample exercises: a pre-built set of home directories the student must navigate through to learn about privilege escalation, the creation of a virtual network playground designed to teach the student about the resiliency of the Internet, and a two-hour Capture the Flag challenge for the final lesson. There are approximately thirty (30) exercises included for the students to complete as part of the course.

Source record↗
DOE OSTI2015

Stonix, Version 0.x

STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.

Source record↗
DOE OSTI2016

The Password Problem

Passwords are an ubiquitous, established part of the Internet today, but they are also a huge security headache. Single sign-on, OAuth, and password managers are some of the solutions to this problem. OAuth is a new, popular method that allows people to use large, common authentication providers for many web applications. However, it comes at the expense of some privacy: OAuth makes users easy to track across websites, applications, and devices. Password managers put the power in the hands of the users, but this vulnerability survey reveals that you have to be extremely careful which program you choose. All in all, password managers are the solution of choice for home users and small organizations, but large companies will probably want to invest in their own SSO solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Current Trends in the Detection of Sociocultural Signatures: Data-Driven Models

The harvesting of behavioral data and their analysis through evidence-based reasoning enable the detection of sociocultural signatures in their context to support situation awareness and decision making. Harvested data are used as training materials from which to infer computational models of sociocultural behaviors or calibrate parameters for such models. Harvested data also serve as evidence input that the models use to provide insights about observed and future behaviors for targets of interest. The harvested data is often the result of assembling diverse data types and aggregating them into a form suitable for analysis. Data need to be analyzed to bring out the categories of content that are relevant to the domain being addressed in order to train or run a model. If, for example, we are modeling the intent of a group to engage in violent behavior using messages that the group has broadcasted, then these messages need to be processed to extract and measure indicators of violent intent. The extracted indicators and the associated measurements (e.g. rates or counts of occurrence) can then be used to train/calibrate and run computational models that assess the propensity for violence expressed in the source message. Ubiquitous access to the Internet, mobile telephony and technologies such as digital photography and digital video have enabled social media application platforms such as Facebook, YouTube, and Twitter that are altering the nature of human social interaction. The fast increasing pace of online social interaction introduces new challenges and opportunities for gathering sociocultural data. Challenges include the development of harvesting and processing techniques tailored to new data environments and formats (e.g. Twitter, Facebook), the integration of social media content with traditional media content, and the protection of personal privacy. As these and other challenges are addressed, a new wealth of behavioral data and data analysis methods becomes available that are shaping social computing as a strongly data-driven experimental discipline with an increasingly stronger impact on the decision-making process of groups and individuals alike. In this chapter, we review current advances and trends in the detection of sociocultural signatures. Specific embodiments of the issues discussed are provided with respect to the assessment of violent intent and sociopolitical contention. We begin by reviewing current approaches to the detection of sociocultural signatures in these domains. Next, we turn to the review of novel data harvesting methods for social media content. Finally, we discuss the application of sociocultural models to social media content, and conclude by commenting on current challenges and future developments.

Sanfilippo, Antonio P.↗
DOE OSTI2016

Expanding geothermal resource utilization through directed research, education, and public outreach: Final Technical Report

The University of Nevada, Reno (UNR) conducts research and outreach activities that will lead to increased utilization of geothermal resources in the western US. The Great Basin Center for Geothermal Energy (GBCGE) is working in partnership with US industry to establish geothermal energy as a sustainable, environmentally sound, economically competitive contributor to energy supply in the western US. Task 1 involves conducting geoscience and engineering research and developing technology to improve the assessment, exploration, and stimulation of geothermal resources. Subtask projects were selected based on peer review of proposals submitted to the GBCGE from Nevada System of High Education (NSHE) institutions for short project development and seed awards intended to develop background and establish viability of approaches for future activities. Task 2 includes project management and organization of workshops periodically requested by DOE and others to satisfy other mission goals of the GBCGE and the DOE geothermal program. GBCGE supports interaction with national and international geothermal organizations, with brochures, presentations, and materials describing GBCGE accomplishments and current research. We continue to maintain and develop an internet-based information system that makes geothermal data and information available to industry, government, and academic stakeholders for exploration and development of geothermal resources. This award also partially supported post-doctoral scholar Drew Siler and research scientist Betsy Littlefield Pace whose effort is included under developing future research projects. Task 2 also focuses on education and outreach through a competitive graduate fellowship program. The budget is for two-year stipends for three graduate students to work collaboratively with GBCGE faculty on Master’s or PhD degrees in geoscience and engineering fields. This grant supported three MS students in full for two years toward the degree and contributed bridge money for four other students to finish their degrees. In total, eight graduate degrees were supported by this grant, either through the faculty seed grants or the fellowship program.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Low-cost scalable quartz crystal microbalance array for environmental sensing

Proliferation of environmental sensors for internet of things (IoT) applications has increased the need for low-cost platforms capable of accommodating multiple sensors. Quartz crystal microbalance (QCM) crystals coated with nanometer-thin sensor films are suitable for use in high-resolution (~1 ng) selective gas sensor applications. We demonstrate a scalable array for measuring frequency response of six QCM sensors controlled by low-cost Arduino microcontrollers and a USB multiplexer. Gas pulses and data acquisition were controlled by a LabVIEW user interface. We test the sensor array by measuring the frequency shift of crystals coated with different compositions of polymer composites based on poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) while films are exposed to water vapor and oxygen inside a controlled environmental chamber. Our sensor array exhibits comparable performance to that of a commercial QCM system, while enabling high-throughput 6 QCM testing for under $1,000. We use deep neural network structures to process sensor response and demonstrate that the QCM array is suitable for gas sensing, environmental monitoring, and electronic-nose applications.

Anazagasty, Cristain↗
DOE OSTI2015

A Literature Review and Compilation of Nuclear Waste Management System Attributes for Use in Multi-Objective System Evaluations.

The purpose of this work was to compile a comprehensive initial set of potential nuclear waste management system attributes. This initial set of attributes is intended to serve as a starting point for additional consideration by system analysts and planners to facilitate the development of a waste management system multi-objective evaluation framework based on the principles and methodology of multi-attribute utility analysis. The compilation is primarily based on a review of reports issued by the Canadian Nuclear Waste Management Organization (NWMO) and the Blue Ribbon Commission on America's Nuclear Future (BRC), but also an extensive review of the available literature for similar and past efforts as well. Numerous system attributes found in different sources were combined into a single objectives-oriented hierarchical structure. This study provides a discussion of the data sources and the descriptions of the hierarchical structure. A particular focus of this study was on collecting and compiling inputs from past studies that involved the participation of various external stakeholders. However, while the important role of stakeholder input in a country's waste management decision process is recognized in the referenced sources, there are only a limited number of in-depth studies of the stakeholders' differing perspectives. Compiling a comprehensive hierarchical listing of attributes is a complex task since stakeholders have multiple and often conflicting interests. The BRC worked for two years (January 2010 to January 2012) to "ensure it has heard from as many points of view as possible." The Canadian NWMO study took four years and ample resources, involving national and regional stakeholders' dialogs, internet-based dialogs, information and discussion sessions, open houses, workshops, round tables, public attitude research, website, and topic reports. The current compilation effort benefited from the distillation of these many varied inputs conducted by the previous studies.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Method and system to discover and recommend interesting documents

Disclosed are several examples of systems that can read millions of news feeds per day about topics (e.g., your customers, competitors, markets, and partners), and provide a small set of the most relevant items to read to keep current with the overwhelming amount of information currently available. Topics of interest can be chosen by the user of the system for use as seeds. The seeds can be vectorized and compared with the target documents to determine their similarity. The similarities can be sorted from highest to lowest so that the most similar seed and target documents are at the top of the list. This output can be produced in XML format so that an RSS Reader can format the XML. This allows for easy Internet access to these recommendations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Turbo FRMAC 2016 Version 7.1.0

The Turbo FRMAC (TF) software program is the software implementation of the science and methodologies utilized in the Federal Radiological Monitoring and Assessment Center (FRMAC). The software automates the calculations described in volumes 1 of "The Federal Manual for Assessing Environmental Data during a Radiological Emergency" (2015 version). In the event of the intentional or accidental release of radioactive material, the software is used to guide and govern the response of the Federal, State, Local, and Tribal governments. The manual, upon which the software is based, is unclassified and freely available on the Internet.

Fulton, John↗