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At least 73 records · Page 4

Cross-boundary collaboration in waste management research: A network analysis

Highlights: • No core scholars stood out from cross-boundary research collaboration networks. • No institution occupied a critical position. • Old-line developed countries stay in the center of research than developing ones. • More research has focused on “hard” technologies than “soft” measures. • CBRC from different perspectives were limited but increasing steadily over time. - Abstract: This paper aims to illustrate the cross-boundary research collaboration (CBRC) landscape of waste management (WM) by various collaboration networks. Through a set of rigorous procedures, a total of 15,396 research papers were extracted from eight subject-related journals published between 1981 and 2016. The authors utilized CiteSpace, a Java programme that helps visualize and dissect patterns in scientific literature, to evaluate the content through individual, institutional, national, and disciplinary perspectives. The evaluations of three former perspectives revealed a steady rise in CBRC within WM over the last thirty-five years, although the overall intensities proved fairly low. Inter-individual collaboration groups were limited to their respective regions and only loosely connected, but as more and more academic institutions and universities engaged in WM research, the number and quality of the collaborations increased. Developed countries, chiefly in North America and Western Europe, comprised the bulk of the WM research, whilst the mounting contributions from developing countries, China in particular, forecasts greater diversity in the future. The analysis also suggested that the intensity of the interdisciplinary collaboration network declined slightly, however, the intensity proved low to begin with. Previous WM research focused more on “hard” technologies than “soft” measures. Future endeavors to encourage CBRC in WM should promote more innovative research to tackle waste challenges globally in a sustainable way.

54 ENVIRONMENTAL SCIENCES↗

An Integrated Platform for Collaborative Data Analytics

While collaboration among data scientists is a key to organizational productivity, data analysts face significant barriers to achieving this end, including data sharing, accessing and configuring the required computational environment, and a unified method of sharing knowledge. Each of these barriers to collaboration is related to the fundamental question of knowledge management “how can organizations use knowledge more effectively?”. In this paper, we consider the problem of knowledge management in collaborative data analytics and present ShareAL, an integrated knowledge management platform, as a solution to that problem. The ShareAL platform consists of three core components: a full stack web application, a dashboard for analyzing streaming data and a High Performance Computing (HPC) cluster for performing real time analysis. Prior research has not applied knowledge management to collaborative analytics or developed a platform with the same capabilities as ShareAL. ShareAL overcomes the barriers data scientists face to collaboration by providing intuitive sharing of data and analytics via the web application, a shared computing environment via the HPC cluster and knowledge sharing and collaboration via a real time messaging application.

Oesch, T↗

XSIM Final Report: Modelling the Past and Future of Identity Management for Scientific Collaborations

The eXtreme Science Identity Management (XSIM1) research project: collected and analyzed real world data on virtual organization (VO) identity management (IdM) representing the last 15+ years of collaborative DOE science; constructed a descriptive VO IdM model based on that data; used the model and existing trends to project the direction for IdM in the 2020 timeframe; and provided guidance to scientific collaborations and resource providers that are implementing or seeking to improve IdM functionality. XSIM conducted over 20 semi­structured interviews of representatives from scientific collaborations and resource providers, both in the US and Europe; the interviewees supported diverse set of scientific collaborations and disciplines. We developed a definition of “trust,” a key concept in IdM, to understand how varying trust models affect where IdM functions are performed. The model identifies how key IdM data elements are utilized in collaborative scientific workflows, and it has the flexibility to describe past, present and future trust relationships and IdM implementations. During the funding period, we gave more than two dozen presentations to socialize our work, encourage feedback, and improve the model; we also published four refereed papers. Additionally, we developed, presented, and received favorable feedback on three white papers providing practical advice to collaborations and/or resource providers.

97 MATHEMATICS AND COMPUTING↗

International Collaboration Activities in Geologic Disposal Research: FY2021 Progress

This report describes the FY21 status of international collaboration regarding geologic disposal research in the Spent Fuel and Waste Disposition (SFWD) Campaign. Since 2012, in an effort coordinated by Lawrence Berkeley National Laboratory, SFWD has advanced active collaboration with several international geologic disposal programs across the world. Such collaboration has allowed the SFWD Campaign to benefit from a deep knowledge base in regards to alternative repository environments developed over decades and has provided a framework for active peer-to-peer research participation in international groups which conduct, analyze, and model performance-relevant processes. Via international collaboration, the SFWD Campaign also benefits from substantial international investments in research facilities (such as underground research laboratory testing and modeling) and achieves cost savings via joint funding of expensive field experiments. To date, SFWD’s International Disposal R&D Program has established formal collaboration agreements with multiple international initiatives and various international partners, and national lab scientists associated with SFWD have conducted a large number of specific collaborative R&D activities that align well with its R&D priorities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Collaboration Website for Muon Catalyzed Fusion and Muon Beam Production

This project sets up a website to support the nascent Muon Catalyzed Fusion collaboration including development of particle accelerators and transport beamlines for muon beams. The website is envisioned as having the general public information pages and private pages for collaboration members. Multimedia elements like images, text animations, and video lectures, covering a broad spectrum of topics will populate the educational site, covering muon facilities, to comprehensive explorations and seminal documents that define the science of Muon Catalyzed Fusion, Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes. Ensuring compatibility across devices and operating systems, it also features integration with Google Docs for collaboration, a code repository (GitHub), a blog platform with comments (WordPress), the potential for ChatGPT integration and interactive graph plotting with Python Plotty to enhance data visualization. This project will maintain public and protected private pages, due to the proprietary nature of the work or research in progress. The public sections will be built to foster dissemination of information and highlight recent work within the NK Labs collaboration, including lectures, published papers, and regular blog posts with open commenting. The private section will support unpublished or nonpublic research, by facilitating collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. Ultimately, this project strives to make complex scientific knowledge more accessible to the public, foster enhanced collaboration, and serve as a platform for sharing cutting-edge research in Muon Catalyzed Fusion and Accelerators.

43 PARTICLE ACCELERATORS↗

The role of international collaboration in the United States geologic disposal research program

Abstract. More than a decade ago, the United States disposal program discontinued all research activities focused on the unsaturated fractured tuff formation at Yucca Mountain as the geologic disposal site for spent fuel and high-level radioactive waste. A new research and development (R&D) program was initiated to provide a sound technical basis for alternative disposal options across clay, crystalline, and salt rocks. The goals of this broad program were (and still are) to (1) increase confidence in the robustness of generic disposal concepts, (2) develop the science and engineering tools needed to support disposal concept implementation, and (3) conduct R&D on the direct disposal of existing dual-purpose (storage and transportation) canisters. Recognizing the benefits of international collaboration toward the common goal of safely and efficiently managing the back end of the nuclear fuel cycle, the program emphasized international cooperation as an effective strategy for sharing information and knowledge. In a multi-laboratory effort coordinated by Lawrence Berkeley National Laboratory, the United States Department of Energy (DOE) program established formal and informal cooperation partnerships with several international initiatives and institutions and developed a number of collaborative R&D activities in important research areas, such as engineered barrier integrity, near-field perturbations, radionuclide transport, performance assessment, and methods for characterization and monitoring of engineered and natural barriers. This presentation gives an overview of these R&D activities, with a specific focus on activities that improve our current understanding of the coupled thermal–hydrological–mechanical–chemical (THMC) processes occurring in engineered and natural barriers. We start with a brief review of selected international collaboration initiatives and then describe a few specific collaboration projects. We focus specifically on such studies that use experimental data sets provided by international research cooperation for joint modeling work to increase confidence in performance-relevant predictions of coupled processes. Overall, the focus on international collaboration has allowed deep engagement of US researchers with the international waste management R&D community in terms of best practices, new scientific advances, state-of-the-art simulation tools, new monitoring and performance confirmation approaches, and lessons learned. The joint R&D with international researchers, worldwide sharing of knowledge and experience, and access to relevant data and experiments from a variety of host rocks have helped our researchers to significantly improve their understanding of the current technical basis for disposal in a range of potential host rock environments. International collaboration also provides ample opportunity for training and educating junior staff that are well suited to move the United States disposal research program forward into the next decades, a promising avenue for developing a next-generation workforce of disposal scientists.

Birkholzer, Jens T.↗

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g., manufacturing and systems operation). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost, risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographical distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across Agency.

Monell, Donald W.↗

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g. manufacturing and systems operations). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographically distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across the Agency.

Monell, Donald W.↗

Sensor Authentication in Collaborating Sensor Networks

In this thesis, we address a new security problem in the realm of collaborating sensor networks. By collaborating sensor networks, we refer to the networks of sensor networks collaborating on a mission, with each sensor network is independently owned and operated by separate entities. Such networks are practical where a number of independent entities can deploy their own sensor networks in multi-national, commercial, and environmental scenarios, and some of these networks will integrate complementary functionalities for a mission. In the scenario, we address an authentication problem wherein the goal is for the Operator O i of Sensor Network S i to correctly determine the number of active sensors in Network Si. Such a problem is challenging in collaborating sensor networks where other sensor networks, despite showing an intent to collaborate, may not be completely trustworthy and could compromise the authentication process. We propose two authentication protocols to address this problem. Our protocols rely on Physically Unclonable Functions, which are a hardware based authentication primitive exploiting inherent randomness in circuit fabrication. Our protocols are light-weight, energy efficient, and highly secure against a number of attacks. To the best of our knowledge, ours is the first to addresses a practical security problem in collaborating sensor networks.

42 ENGINEERING↗

Text and Graph Based Approach for Analyzing Patterns of Research Collaboration: An Analysis of the TrueImpactDataset

Patterns of scientific collaboration and their effect on scientific production have been the subject of many studies. In this paper, we analyze the nature of ties between co-authors and study collaboration patterns in science from the perspective of semantic similarity of authors who wrote a paper together and the strength of ties between these authors (i.e. how frequently have they previously collaborated together). These two views of scientific collaboration are used to analyze publications in the TrueImpactDataset (Herrmannova et al., 2017) (Herrmannova et al., 2017), a new dataset containing two types of publications – publications regarded as seminal and publications regarded as literature reviews by field experts. We show there are distinct differences between seminal publications and literature reviews in terms of author similarity and the strength of ties between their authors. In particular, we find that seminal publications tend to be written by authors who have previously worked on dissimilar problems (i.e. authors from different fields or even disciplines), and by authors who are not frequent collaborators. On the other hand, literature reviews in our dataset tend to be the result of an established collaboration within a discipline. This demonstrates that our method provides meaningful information about potential future impacts of a publication which does not require citation information.

Herrmannova, Dasha↗

Sensitivity analysis of synergistic collaborative scenarios towards sustainable nuclear energy systems

The paper presents results of the study on the role of collaboration among countries towards sustainable global nuclear energy systems. The study explores various market shares for nuclear fuel cycle services, possible scale of collaboration among countries and assesses benefits and issues relevant for collaboration between suppliers and users of nuclear fuel cycle services. The approach used in the study is based on a heterogeneous world model with grouping of the non-personified nuclear energy countries according to different nuclear fuel cycle policies. The methodology applied in the analysis allocates a fraction of future global nuclear energy generation to each of such country-groups as a function of time. The sensitivity studies performed show the impacts of the group shares on the scope of collaboration among countries and on the resulting possible reactor mix and nuclear fuel cycle infrastructure versus time. The study quantitatively demonstrates that the synergistic approach to nuclear fuel cycle has a significant potential for offering a win-win collaborative strategy to both, technology holders and technology users on their joint way to future sustainable nuclear energy systems. The study also highlights possible issues on such a collaborative way. (authors)

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Shopping For Danger: E-commerce techniques applied to collaboration in cyber security

Collaboration among cyber security analysts is essential to a successful protection strategy on the Internet today, but it is uncommonly practiced or encouraged in operating environments. Barriers to productive collaboration often include data sensitivity, time and effort to communicate, institutional policy, and protection of domain knowledge. We propose an ambient collaboration framework, Vulcan, designed to remove the barriers of time and effort and mitigate the others. Vulcan automated data collection, collaborative filtering, and asynchronous dissemination, eliminating the effort implied by explicit collaboration among peers. We instrumented two analytic applications and performed a mock analysis session to build a dataset and test the output of the system.

99 GENERAL AND MISCELLANEOUS↗

Universal Collaboration Strategies for Signal Detection: A Sparse Learning Approach

Here, this paper considers the problem of high-dimensional signal detection in a large distributed network whose nodes can collaborate with their one-hop neighboring nodes (spatial collaboration). We assume that only a small subset of nodes communicate with the fusion center (FC). We design optimal collaboration strategies which are universal for a class of deterministic signals. By establishing the equivalence between the collaboration strategy design problem and sparse principal component analysis (PCA), we solve the problem efficiently and evaluate the impact of collaboration on detection performance.

97 MATHEMATICS AND COMPUTING↗

What Composition of High-Energy Physics Collaborations is Epistemically Optimal?

Computer simulations have recently come to the fore as a crucial tool for studying epistemic dynamics of scientific collectives. One pressing issue in big-ticket, long-term, and crowded particle physics research is the optimal organization of collaborations. This research developed a computation model of collaborations in high-energy physics and performed simulations to investigate the epistemic efficiency of groups and its dependence on the size of such groups and their composition: namely, percentages of pure, partially theoretically competent, and fully theoretically competent experimentalists. The present study reveals that in both small (100-member) and large (3000-member) groups, epistemic payoff as the measure of epistemic efficiency of collaborations is, generally, positively correlated with an increase in both the number of theoretically fully competent and pure (incompetent) experimentalists. Here, we are less certain of such conclusion in the case of the small collaborations. Although the subcommunity of experimentalists who are partially expert is not found to be immediately epistemically beneficial for collaborations, nevertheless they also crucially serve as a transitional community between the theorists and the experimentalists. Predicated on the toy model simulations, I suggest that institutions should provide measures to assist members of the latter subgroup in progressing toward developing a full theoretical expertise.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Not just for programmers: How GitHub can accelerate collaborative and reproducible research in ecology and evolution

Abstract Researchers in ecology and evolutionary biology are increasingly dependent on computational code to conduct research. Hence, the use of efficient methods to share, reproduce, and collaborate on code as well as document research is fundamental. GitHub is an online, cloud‐based service that can help researchers track, organize, discuss, share, and collaborate on software and other materials related to research production, including data, code for analyses, and protocols. Despite these benefits, the use of GitHub in ecology and evolution is not widespread. To help researchers in ecology and evolution adopt useful features from GitHub to improve their research workflows, we review 12 practical ways to use the platform. We outline features ranging from low to high technical difficulty, including storing code, managing projects, coding collaboratively, conducting peer review, writing a manuscript, and using automated and continuous integration to streamline analyses. Given that members of a research team may have different technical skills and responsibilities, we describe how the optimal use of GitHub features may vary among members of a research collaboration. As more ecologists and evolutionary biologists establish their workflows using GitHub, the field can continue to push the boundaries of collaborative, transparent, and open research.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Mixed Presence Collaboration using Scalable Visualizations in Heterogeneous Display Spaces

Mixed presence collaboration involves remote collaboration between multiple collocated groups. This paper presents the design and results of a user study that focused on mixed presence collaboration using large-scale tiled display walls. The research was conducted in order to compare data synchronization schemes for multi-user visualization applications. Our study compared three techniques for sharing data between display spaces with varying constraints and affordances. The results provide empirical evidence that using data sharing techniques with continuous synchronization between the sites lead to improved collaboration for a search and analysis task between remotely located groups. We have also identified aspects of synchronized sessions that result in increased remote collaborator awareness and parallel task coordination. It is believed that this research will lead to better utilization of large-scale tiled display walls for distributed group work.

data-conferencing↗

Framework For Human-Automation Collaboration: Project Status Report

The Human-Automation Collaboration (HAC) research project within the Department of Energy’s Advanced Small Modular Reactor (AdvSMR) program is investigating how advanced technologies that are planned for AdvSMRs might affect the performance and the reliability of the plant from a human factors and human performance perspective. The HAC research effort investigates the consequences of allocating functions between the operators and automated systems. More specifically, the research team is addressing 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. As one step to accomplish this goal, the research team reviewed available information on AdvSMR designs and identified plant functions and operator tasks that might impact the design of the HAC. The identified functions and tasks will later be vetted against insights learned from the current fleet of Light Water Reactors (LWR), other industries where humans are collaborating with highly automated systems, and the results from the activities in the AdvSMR Concepts of Operations project to inform a high-level generic design model. This generic model will be used as a basis for experimental studies to study the effects of different HAC concepts as well as evaluating new human-system interface (HSI) solutions to support a well-functioning HAC. Another important part needed to accomplish the research goal is a model of the collaboration between the human operator and the automated system. The team has developed a model of HAC that defines: (1) the important design dimensions of automation that impact automation’s use by personnel and integrated human-automation performance, (2) what aspects of human cognition, behavior, and performance mediate automation’s use by personnel, and (3) when and how the above factors affect the use of automation and the overall performance of the HAC system. The HAC model is utilized to identify areas in need of additional research, which forms the basis for planned HAC research activities. By detailing the relationships between characteristics of HAC, automation, and human cognition, the HAC model identifies what aspects of the human-automation interaction are important to consider in developing automation for AdvSMR systems. Three analytical studies have been initiated to address questions related to the HAC model. These studies are 1) Models of Teamwork, 2) Standardized HAC Performance Measurement Battery, and 3) Initiators and Triggering Conditions for Adaptive Automation. Additionally, a number of field studies have been identified and are in progress, and a set of experimental studies that are on schedule to be conducted later in the project to address the main research question. This report consists of three main parts: the preliminary identification of AdvSMR functions and tasks, a description of the updates and extensions to the HAC model, and a description of ongoing and planned analytical, field, and experimental research efforts that the research team has developed to accomplish the project’s overall goal of establishing a technical basis for designing the collaboration of personnel and automation.

99 GENERAL AND MISCELLANEOUS↗

Model for Collaboration among Carriers to Reduce Empty Container Truck Trips

In recent years, intermodal transport has become an increasingly attractive alternative to freight shippers. However, the current intermodal freight transport is not as efficient as it could be. Oftentimes an empty container needs to be transported from the empty container depot to the shipper, and conversely, an empty container needs to be transported from the receiver to the empty container depot. These empty container movements decrease the freight carrier’s profit, as well as increase traffic congestion, decrease roadway safety, and add unnecessary emissions to the environment. To this end, our study evaluates a potential collaboration strategy to be used by carriers for domestic intermodal freight transport based on an optimization approach to reduce the number of empty container trips. A binary integer-linear programming model is developed to determine each freight carrier’s optimal schedule while minimizing its operating cost. The model ensures that the cost for each carrier with collaboration is less than or equal to its cost without collaboration. It also ensures that average savings from the collaboration are shared equally among all participating carriers. Additionally, two stochastic models are provided to account for uncertainty in truck travel times. The proposed collaboration strategy is tested using empirical data and is demonstrated to be effective in meeting all of the shipment constraints.

42 ENGINEERING↗