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All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Collaborative Supervised Learning for Sensor Networks

Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.

Wagstaff, Kiri L.↗
NASA NTRS2003

Designing Facilities for Collaborative Operations

A methodology for designing operational facilities for collaboration by multiple experts has begun to take shape as an outgrowth of a project to design such facilities for scientific operations of the planned 2003 Mars Exploration Rover (MER) mission. The methodology could also be applicable to the design of military "situation rooms" and other facilities for terrestrial missions. It was recognized in this project that modern mission operations depend heavily upon the collaborative use of computers. It was further recognized that tests have shown that layout of a facility exerts a dramatic effect on the efficiency and endurance of the operations staff. The facility designs (for example, see figure) and the methodology developed during the project reflect this recognition. One element of the methodology is a metric, called effective capacity, that was created for use in evaluating proposed MER operational facilities and may also be useful for evaluating other collaboration spaces, including meeting rooms and military situation rooms. The effective capacity of a facility is defined as the number of people in the facility who can be meaningfully engaged in its operations. A person is considered to be meaningfully engaged if the person can (1) see, hear, and communicate with everyone else present; (2) see the material under discussion (typically data on a piece of paper, computer monitor, or projection screen); and (3) provide input to the product under development by the group. The effective capacity of a facility is less than the number of people that can physically fit in the facility. For example, a typical office that contains a desktop computer has an effective capacity of .4, while a small conference room that contains a projection screen has an effective capacity of around 10. Little or no benefit would be derived from allowing the number of persons in an operational facility to exceed its effective capacity: At best, the operations staff would be underutilized; at worst, operational performance would deteriorate. Elements of this methodology were applied to the design of three operations facilities for a series of rover field tests. These tests were observed by human-factors researchers and their conclusions are being used to refine and extend the methodology to be used in the final design of the MER operations facility. Further work is underway to evaluate the use of personal digital assistant (PDA) units as portable input interfaces and communication devices in future mission operations facilities. A PDA equipped for wireless communication and Ethernet, Bluetooth, or another networking technology would cost less than a complete computer system, and would enable a collaborator to communicate electronically with computers and with other collaborators while moving freely within the virtual environment created by a shared immersive graphical display.

Norris, Jeffrey↗
NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗
NASA NTRS2011

The MSFC Collaborative Engineering Process for Preliminary Design and Concept Definition Studies

This paper describes a collaborative engineering process developed by the Marshall Space Flight Center's Advanced Concepts Office for performing rapid preliminary design and mission concept definition studies for potential future NASA missions. The process has been developed and demonstrated for a broad range of mission studies including human space exploration missions, space transportation system studies and in-space science missions. The paper will describe the design team structure and specialized analytical tools that have been developed to enable a unique rapid design process. The collaborative engineering process consists of integrated analysis approach for mission definition, vehicle definition and system engineering. The relevance of the collaborative process elements to the standard NASA NPR 7120.1 system engineering process will be demonstrated. The study definition process flow for each study discipline will be will be outlined beginning with the study planning process, followed by definition of ground rules and assumptions, definition of study trades, mission analysis and subsystem analyses leading to a standardized set of mission concept study products. The flexibility of the collaborative engineering design process to accommodate a wide range of study objectives from technology definition and requirements definition to preliminary design studies will be addressed. The paper will also describe the applicability of the collaborative engineering process to include an integrated systems analysis approach for evaluating the functional requirements of evolving system technologies and capabilities needed to meet the needs of future NASA programs.

Mulqueen, Jack↗
NASA NTRS2012

Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers-to-classifiers. The new capability has the potential to greatly expand the in situ analysis abilities of sensor networks. Classifiers seeking to categorize incoming data into different types of events can operate in tandem with clusterers that are sensitive to the occurrence of new kinds of events not known to the classifiers. In contrast to current approaches that treat these operations as independent components, a hybrid collaborative learning system can enable them to learn from each other.

Wagstaff, Kiri L.↗
NASA NTRS2012

Social Networking Adapted for Distributed Scientific Collaboration

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and messaging encryption; and g) Easy-to-use intuitive workflow.

Karimabadi, Homa↗
NASA NTRS2014

Public-Private Collaborations with Earth-Space Benefits

The NASA Human Health and Performance Center (NHHPC) was established in October 2010 to promote collaborative problem solving and project development to advance human health and performance innovations benefiting life in space and on Earth. The NHHPC, which now boasts over 150 corporate, government, academic and non-profit members, has convened four successful workshops and engaged in multiple collaborative projects. The virtual center facilitates member engagement through a variety of vehicles, including annual in-person workshops, webcasts, quarterly electronic newsletters, web postings, and the new system for partner engagement. NHHPC workshops serve to bring member organizations together to share best practices, discuss common goals, and facilitate development of the collaborative projects. The most recent NHHPC workshop was conducted in November 2013 on the topic of "Accelerating Innovation: New Organizational Business Models," and focused on various collaborative approaches successfully used by organizations to achieve their goals. Past workshops have addressed smart media and health applications, connecting through collaboration, microbiology innovations, and strategies and best practices in open innovation. A fifth workshop in Houston, Texas, planned for September 18, 2014, will feature "Innovation Through Co-Development: Engaging Partners". One area of great interest to NASA is mobile health applications, including mobile laboratory analytics, health monitoring, and close loop sensing, all of which also offer ground-based health applications for remote and underserved areas. Another project being coordinated by NASA and the Health and Environmental Sciences Institute is the pursuit of one to several novel strategies to increase medication stability that would enable health care in remote terrestrial settings as well as during space flight. NASA has also funded work with corporate NHHPC partner GE, seeking to develop ultrasound methodologies that will enable NASA to further understand the eye changes related to long-duration space flight. The adaptation of ultrasound to this type of eye examination could also expand the use of ultrasound in health care on the Earth in settings where MRIs are not available. To further engage NHHPC members and facilitate partnership development for NASA, the NHHPC created and deployed an engagement system in 2014 that facilitates identification and evaluation of technical needs and opportunities among all NHHPC members.

Davis, Jeffrey R.↗
NASA NTRS2017

The Importance of Earth Observations and Data Collaboration within Environmental Intelligence Supporting Arctic Research

Within the IARPC Collaboration Team activities of 2016, Arctic in-situ and remote earth observations advanced topics such as :1) exploring the role for new and innovative autonomous observing technologies in the Arctic; 2) advancing catalytic national and international community based observing efforts in support of the National Strategy for the Arctic Region; and 3) enhancing the use of discovery tools for observing system collaboration such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Arctic Environmental Response Management Application (ERMA) and the U.S. National Aeronautics and Space Administration (NASA) Arctic Collaborative Environment (ACE) project geo reference visualization decision support and exploitation internet based tools. Critical to the success of these earth observations for both in-situ and remote systems is the emerging of new and innovative data collection technologies and comprehensive modeling as well as enhanced communications and cyber infrastructure capabilities which effectively assimilate and dissemination many environmental intelligence products in a timely manner. The Arctic Collaborative Environment (ACE) project is well positioned to greatly enhance user capabilities for accessing, organizing, visualizing, sharing and producing collaborative knowledge for the Arctic.

Casas, Joseph↗
NASA NTRS2017

Benefits of International Collaboration on the International Space Station

The International Space Station is a valuable platform for research in space, but the benefits are limited if research is only conducted by individual countries. Through the e orts of the ISS Program Science Forum, international science working groups, and interagency cooperation, international collaboration on the ISS has expanded as ISS utilization has matured. Members of science teams benefit from working with counterparts in other countries. Scientists and institutions bring years of experience and specialized expertise to collaborative investigations, leading to new perspectives and approaches to scientific challenges. Combining new ideas and historical results brings synergy and improved peer-reviewed scientific methods and results. World-class research facilities can be expensive and logistically complicated, jeopardizing their full utilization. Experiments that would be prohibitively expensive for a single country can be achieved through contributions of resources from two or more countries, such as crew time, up- and downmass, and experiment hardware. Cooperation also avoids duplication of experiments and hardware among agencies. Biomedical experiments can be completed earlier if astronauts or cosmonauts from multiple agencies participate. Countries responding to natural disasters benefit from ISS imagery assets, even if the country has no space agency of its own. Students around the world participate in ISS educational opportunities, and work with students in other countries, through open curriculum packages and through international competitions. Even experiments conducted by a single country can benefit scientists around the world, through specimen sharing programs and publicly accessible \open data" repositories. For ISS data, these repositories include GeneLab, the Physical Science Informatics System, and different Earth science data systems. Scientists can conduct new research using ISS data without having to launch and execute their own experiments. Multilateral collections of research results publications, maintained by the ISS international partnership and accessible via nasa.gov, make ISS results available worldwide, and encourage new users, ideas and research. The paper explores effectiveness of international collaboration in the course of the ISS Program execution. The collaboration history, its evolution and maturation, change of focus during its different phases, and growth of its effectiveness (in accordance with the especially established criteria) are also considered in the paper in the light of benefits for the entire ISS community. With the International Space Station extended through at least 2024, more crew time becoming available and new facilities arriving on board the ISS, these benefits of international scientific collaboration on the ISS can only increase.

Robinson, Julie A.↗
DOE OSTI2015

Use of collaboration software to improve nuclear power plant outage management

Nuclear Power Plant (NPP) refueling outages create some of the most challenging activities the utilities face in both tracking and coordinating thousands of activities in a short period of time. Other challenges, including nuclear safety concerns arising from atypical system configurations and resource allocation issues, can create delays and schedule overruns, driving up outage costs. Today the majority of the outage communication is done using processes that do not take advantage of advances in modern technologies that enable enhanced communication, collaboration and information sharing. Some of the common practices include: runners that deliver paper-based requests for approval, radios, telephones, desktop computers, daily schedule printouts, and static whiteboards that are used to display information. Many gains have been made to reduce the challenges facing outage coordinators; however; new opportunities can be realized by utilizing modern technological advancements in communication and information tools that can enhance the collective situational awareness of plant personnel leading to improved decision-making. Ongoing research as part of the Light Water Reactor Sustainability Program (LWRS) has been targeting NPP outage improvement. As part of this research, various applications of collaborative software have been demonstrated through pilot project utility partnerships. Collaboration software can be utilized as part of the larger concept of Computer-Supported Cooperative Work (CSCW). Collaborative software can be used for emergent issue resolution, Outage Control Center (OCC) displays, and schedule monitoring. Use of collaboration software enables outage staff and subject matter experts (SMEs) to view and update critical outage information from any location on site or off.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

A Brief Technical History of the Large-Area Picosecond Photodetector (LAPPD) Collaboration

The Large Area Picosecond PhotoDetector (LAPPD) Collaboration was formed in 2009 to develop large-area photodetectors capable of time resolutions measured in pico-seconds, with accompanying sub-millimeter spatial resolution. During the next three and one-half years the Collaboration developed the LAPPD design of 20 x 20 cm modules with gains greater than $10^7$ and non-uniformity less than $15\%$, time resolution less than 50 psec for single photons and spatial resolution of 700~microns in both lateral dimensions. We describe the R\&D performed to develop large-area micro-channel plate glass substrates, resistive and secondary-emitting coatings, large-area bialkali photocathodes, and RF-capable hermetic packaging. In addition, the Collaboration developed the necessary electronics for large systems capable of precise timing, built up from a custom low-power 15-GigaSample/sec waveform sampling 6-channel integrated circuit and supported by a two-level modular data acquisition system based on Field-Programmable Gate Arrays for local control, data-sparcification, and triggering. We discuss the formation, organization, and technical successes and short-comings of the Collaboration. The Collaboration ended in December 2012 with a transition from R\&D to commercialization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2016

Collaborative Computer Graphics Product Development between Academia and Government: A Dynamic Model

Collaborations and partnerships between academia and government agencies are common, especially when it comes to research and development in the fields of science, engineering and technology. However, collaboration between a government agency and an art school is rather atypical. This paper presents the Collaborative Student Project, which aims to explore the following challenge: The ideation, development and realization of education and public outreach products for NASAs upcoming ICESat-2 mission in collaboration with art students.

product development with students↗
DOE OSTI2024

Cultural Shifts in High Energy Physics Collaboration from the Cold War to the Present: A Historical and Philosophical Perspective

Here, this article employs empirical history and the philosophy of science to study cultural convergences and divergences in international collaborations in high energy physics. We examine two cases: (1) E-36, an experiment on small angle proton-proton scattering conducted during the Cold War at the National Accelerator Laboratory (NAL) in the USA by Soviet and US scientists and (2) an ongoing collaborative experiment, NICA, at the Joint Institute for Nuclear Research (JINR, Dubna), which is a project devoted to heavy-ion physics. The JINR, particularly its Laboratory of High Energy Physics (formerly the “Laboratory of High Energies”) is the main mediating actor between these two cases (i.e., E-36 and NICA), as the majority of Soviet participants in E-36 were representatives of the Institute. Using empirical data collected through archival searches, field observations conducted at JINR in 2018–2019, and in-depth interviews, we tell a story of cultural differences in high energy physics by applying the concepts of ‘trading zones’ (P. Galison) and the translation of interests in actor-networks (B. Latour, M. Callon and others). We analyze three types of cultural diversity (specialization, nationality, and generational) in light of the implications of temporal context and the dichotomy between East and West, showing the roles cultural diversity plays in scientific collaboration (which is an integral part of as well as obstacle to scientific research that can nevertheless provide learning opportunities). Our study aims to demonstrate how disunity and diversity may function in scientific research and how high energy physics collaborations can remain productive despite sometimes deep divergences, including those between East and West.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Effective interdisciplinary collaboration between statisticians and other subject matter experts

Progress and innovative solutions to challenging problems often come at the intersection of multiple disciplines. Statisticians frequently are presented with opportunities to participate on or lead interdisciplinary teams, where how well their contributions are received is a function of their effectiveness as collaborators. In this article, we outline six fundamentals for effective collaboration: respect, shared common goals, trust, commitment, intercommunication, and execution. We focus on how these core aspects of a successful collaboration can be encouraged by statisticians. Through an example, we illustrate how problems can arise when some of the key components are missing and what strategies can be used to mitigate problems. Lastly, we describe how early career statisticians can work to improve their collaboration skills to improve their impact on teams with diverse backgrounds.

42 ENGINEERING↗
DOE OSTI2022

A typological framework of non-floodplain wetlands for global collaborative research and sustainable use

Non-floodplain wetlands (NFWs) are important but vulnerable inland freshwater systems that are receiving increased attention and protection worldwide. However, a lack of consistent terminology, incohesive research objectives, and inherent heterogeneity in existing knowledge hinder cross-regional information sharing and global collaboration. To address this challenge and facilitate future management decisions, we synthesized recent work to understand the state of NFW science and explore new opportunities for research and sustainable NFW use globally. Results from our synthesis show that although NFWs have been widely studied across all continents, regional biases exist in the literature. We hypothesize these biases in the literature stem from terminology rather than real geographical bias around existence and functionality. To confirm this observation, we explored a set of geographically representative NFW regions around the world and characteristics of research focal areas. We conclude that there is more that unites NFW research and management efforts than we might otherwise appreciate. Furthermore, opportunities for cross-regional information sharing and global collaboration exist, but a unified terminology will be needed, as will a focus on wetland functionality. Based on these findings, we discuss four pathways that aid in better collaboration, including improved cohesion in classification and terminology, and unified approaches to modeling and simulation. In turn, legislative objectives must be informed by science to drive conservation and management priorities. Finally, an educational pathway serves to integrate the measures and to promote new technologies that aid in our collective understanding of NFWs. Our resulting framework from NFW synthesis serves to encourage interdisciplinary collaboration and sustainable use and conservation of wetland systems globally.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Controlled environment agriculture: An opportunity to strengthen interagency research collaboration in the US government

Challenges facing food production and agricultural systems are increasingly interconnected with economic, security, health, and equity issues, among others. Threats such as extreme weather, economic volatility, and shrinking water resources and arable land, influence our ability to maintain a safe and resilient food supply. One promising solution to these threats is controlled environment agriculture (CEA). In many cases, CEA can drastically reduce the amount of water and land used in crop production while increasing productivity. Operations may be established in nearly any environment and harvests can take place year-round, supporting food system resiliency and sustainability. CEA sits at the nexus of a number of disciplines and industries, making it well suited for transdisciplinary and multi-institutional research coordination. Herein, authors from multiple US government agencies present CEA as a case study in improving cross-agency research collaboration. The federal government houses a range of scientific expertise and research capabilities, positioning scientists to lead national and global efforts in transdisciplinary, interagency approaches to complex challenges. Navigating cross-agency collaboration can be a challenge, especially coordinating across different scientific disciplines, geographic locations, and funding mechanisms. To enhance multiagency efforts, collaborators could prioritize (i) organizing personnel and resources, (ii) enhancing existing multiagency collaborations, and (iii) focusing on further opportunities for coordination. Adopting these approaches could enable federal researchers to reinforce and advance academic and industry efforts to address current CEA challenges while solidifying the United States as a leader in this arena.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Preliminary Framework for Human-Automation Collaboration

The Department of Energy’s Advanced Reactor Technologies Program sponsors research, development and deployment activities through its Next Generation Nuclear Plant, Advanced Reactor Concepts, and Advanced Small Modular Reactor (aSMR) Programs to promote safety, technical, economical, and environmental advancements of innovative Generation IV nuclear energy technologies. The Human Automation Collaboration (HAC) Research Project is located under the aSMR Program, which identifies developing advanced instrumentation and controls and human-machine interfaces as one of four key research areas. It is expected that the new nuclear power plant designs will employ technology significantly more advanced than the analog systems in the existing reactor fleet as well as utilizing automation to a greater extent. Moving towards more advanced technology and more automation does not necessary imply more efficient and safer operation of the plant. Instead, a number of concerns about how these technologies will affect human performance and the overall safety of the plant need to be addressed. More specifically, it is important to investigate how the operator and the automation work as a team to ensure effective and safe plant operation, also known as the human-automation collaboration (HAC). The focus of the HAC research is to understand how various characteristics of automation (such as its reliability, processes, and modes) effect an operator’s use and awareness of plant conditions. In other words, the research team investigates how to best design the collaboration between the operators and the automated systems in a manner that has the greatest positive impact on overall plant performance and reliability. This report addresses the Department of Energy milestone M4AT-15IN2302054, Complete Preliminary Framework for Human-Automation Collaboration, by discussing the two phased development of a preliminary HAC framework. The framework developed in the first phase was used as the basis for selecting topics to be investigated in more detail. The results and insights gained from the in-depth studies conducted during the second phase were used to revise the framework. This report describes the basis for the framework developed in phase 1, the changes made to the framework in phase 2, and the basis for the changes. Additional research needs are identified and presented in the last section of the report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

An Effective Collaborative Mobile Weighted Clustering Schemes for Energy Balancing in Wireless Sensor Networks

Collaborative strategies for mobile sensor nodes ensure the efficiency and the robustness of data processing, while limiting the required communication bandwidth. In order to solve the problem of pipeline inspection and oil leakage monitoring, a collaborative weighted mobile sensing scheme is proposed. By adopting a weighted mobile sensing scheme, the adaptive collaborative clustering protocol can realize an even distribution of energy load among the mobile sensor nodes in each round, and make the best use of battery energy. A detailed theoretical analysis and experimental results revealed that the proposed protocol is an energy efficient collaborative strategy such that the sensor nodes can communicate with a fusion center and produce high power gain.

42 ENGINEERING↗