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Summary: In this paper, a modified consensus protocol algorithm is proposed for controlling a group of identical unmanned aerial vehicles (UAVs), which have been subjected to interfering signals during coordinate information exchange, using an unknown parameter in the consensus protocol. The maximum levels of interfering signals in the proposed protocol were adjusted by incorporating a hysteresis function with a dead zone consistent with the initial coordinates and the interfering signal levels. An adaptation algorithm is proposed to address a priori uncertainty regarding the consensus parameters, involving the correction of an unknown parameter by eliminating control signals exhibiting false sign changes. This correction relies on the coordinates in the phase plane, indicating that the delay in maneuver execution occurs at the beginning of the maneuver. Furthermore, by modeling synchronized motion, UAV group consensus is demonstrated for an ideal case devoid of a priori uncertainty regarding control protocol parameters, interfering signals, or consequences. The convergence of the adaptation algorithm was assessed by defining a vector function to track parameter changes during tuning. The monotonically decreasing nature of the resulting curve, along with the finite duration of the tuning process, provides confirmation of the convergence of the adaptation algorithm. [ABSTRACT FROM AUTHOR]

A key challenge in crisis management is maintaining an adequate information position to support coherent decision‐making between a range of actors. Such distributed decision‐making is often supported by a common operational picture that not only conveys factual information but also attempts to codify a dynamic and vibrant crisis management process. In this paper, we explain why it is so difficult to move from information sharing towards support for distributed decision‐making. We argue that two key processes need to be considered: supporting both the translation of meaning and the transformation of interests between those on the front line and those in the remote response network. Our analysis compares the information‐sharing processes in three large‐scale emergency response operations in the Netherlands. Results indicate that on several occasions the collaborative decision‐making process was hampered because actors limited themselves to factual information exchange. The decision‐making process only succeeds when actors take steps to resolve their varying interpretations and interests. This insight offers important lessons for improving information management doctrines and for supporting distributed decision‐making processes. [ABSTRACT FROM AUTHOR]

We are witnessing a growing gap separating primary research data from derived data products presented as knowledge in publications. Although journals today more often require the underlying data products used to derive the results as a prerequisite for a publication, the important link to the primary data is lost. However, documenting the postprocessing steps of data linking, the primary data with derived data products has the potential to increase the accuracy and the reproducibility of scientific findings significantly. Here, we introduce the rBEFdata R package as companion to the collaborative data management platform BEFdata. The R package provides programmatic access to features of the platform. It allows to search for data and integrates the search with external thesauri to improve the data discovery. It allows to download and import data and metadata into R for analysis. A batched download is available as well which works along a paper proposal mechanism implemented by BEFdata. This feature of BEFdata allows to group primary data and metadata and streamlines discussions and collaborations revolving around a certain research idea. The upload functionality of the R package in combination with the paper proposal mechanism of the portal allows to attach derived data products and scripts directly from R, thus addressing major aspects of documenting data postprocessing. We present the core features of the rBEFdata R package along an ecological analysis example and further discuss the potential of postprocessing documentation for data, linking primary data with derived data products and knowledge. [ABSTRACT FROM AUTHOR]

SUMMARY: The learning automaton (LA) team model has been proposed as one method for modeling multi‐agent systems. It is modeled as a noncooperative game of learning automata. In this model, each LA operates independently from each other, and there exists a Nash equilibrium, that is, the existence of an optimal mixed strategy in the mixed strategy space of the game has been proven. However, for modeling multi‐agent systems more generally, the information exchange among agents and the acquisition of cooperative behaviors such as the formation of autonomous community are required. In this paper, in order to complement the LA team model, we propose a new LA team model with some fully or partially collaborative learning behaviors. In this new model, each automaton performs reinforcement learning process in order to identify random environments exchanging information with its adjacent automata. Several computer simulations indicate the availability of the proposed model. [ABSTRACT FROM AUTHOR]

ABSTRACT As there are a number of high-profile public inquiries into child death tragedies, 'information sharing' has now become a moral and political imperative across England and Wales for improving the welfare and protection of children. This paper discusses multi-agency information practices, at the stage of referral, which were observed and documented in the day-to-day practice of child protection work. Drawing on transcribed, professional narrative accounts, a 'jigsaw' metaphor is used to describe the process of piecing information together to ascertain a 'full' picture of children and families lives. However, these accounts highlight that there is something of a mismatch between the jigsaw, as articulated in the conceptual abstract accounts, and jigsaw practices operating on the ground. It is argued that abstracting professional information practices from situated contexts creates impoverished understandings of these practices. Thus, reported findings in this paper highlight the inherent complexities of jigsaw practices in the 'everyday' of child protection work, which challenges objectivist assumptions about a stability of meaning, and further highlight that the 'endpoint' of reaching a 'full' picture of a child's life is not fixed, nor does it have the same meaning for all professionals, but rather it is a complex process involving sense-making, translation in context and organizational relevance. [ABSTRACT FROM AUTHOR]

This paper proposes a distributed edge event-triggered (DEET) scheme of multi-agent systems via a communication buffer to reduce unnecessary update of controllers induced by fast information transmission. This edge scheme avoids a synchronous phenomenon in node event-triggered mechanism, in which the triggering of one agent activates information transmission of all edges linked with this agent. Hence, the node event-triggered scheme leads to unnecessary update of control protocols while the DEET provides a new approach without constrains on synchronous phenomenon of edge information exchange. That is, the communication on each edge is independent with other edges. In addition, we investigate another case where edge information transmission is subject to quantization and a quantized edge event-triggered control protocol is proposed. Note that such a quantized protocol guarantees asymptotical consensus instead of bounded consensus in most of the existing literature. Meanwhile, both DEET and quantized edge event-triggered schemes have nontrivial properties of excluding Zeno behavior. Furthermore, an algorithm is provided to avoid continuous event detection; hence, the communication traffic of the whole network is reduced significantly. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Improving health care delivery is a pressing societal goal, and information scientists have a role in effecting change. Information science research has led to understanding theories and practices of information use within the informing professions, but information science and one of its subspecialties, Knowledge Management (KM), also have the potential to influence and enhance other professional disciplines. This concept paper makes the argument that KM is a beneficial framework to help health care clinicians manage their practices and ultimately administer quality care to their patients. The central argument is predicated on the assumption that medicine is a knowledge-based profession and that finding, sharing, and developing clinicians' knowledge is necessary for effective primary health care practice. The authors make the case that in an environment of a burgeoning body of health care research and the adoption of technology tools, physicians can benefit from understanding effective KM practice. The model as presented here borrows from recent information science scholarship in KM and is intended to inform intervention protocols for effective KM to improve quality of care. [ABSTRACT FROM AUTHOR]

Data are becoming an essential product of scholarship, complementing the roles of journal articles, papers, and books. Research data can be reused to ask new questions, to replicate studies, and to verify research findings. Data become even more valuable when linked to publications and other related resources to form a value chain. Types and uses of data vary widely between disciplines, as do the online availability of publications and the incentives of scholars to publish their data. Publishers, scholars, and librarians each have roles to play in constructing a new scholarly information infrastructure for e-research. Technical, policy, and institutional components are maturing; the next steps are to integrate them into a coherent whole. Achieving a critical mass of datasets in public repositories, with links to and from publisher databases, is the most promising solution to maintaining and sustaining the scholarly record in digital form. [ABSTRACT FROM AUTHOR]

Construction project control aims to effectively obtain real-time information and enhance dynamic control by utilizing information sharing and connecting involved participants of the projects to reduce construction conflicts and project delays. However, extending the construction project control system to job sites is not considered efficient because using notebooks in a harsh environment like a construction site is not particularly a conventional practice. Meanwhile, paper-based documents of the site processes are ineffective and cannot get the quick response from the office and project control center. Integrating promising information technologies such as personal digital assistants (PDA), bar code scanning, and data entry mechanisms, can be extremely useful in improving the effectiveness and convenience of information flow in construction supply chain control systems. Bar code scanning is appropriate for several construction applications, providing cost savings through increased speed and accuracy of data entry. This article demonstrates the effectiveness of a bar-code-enabled PDA application, called the mobile construction supply chain management (M-ConSCM) System, that responds efficiently and enhances the information flow between offices and sites in a construction supply chain environment. The advantage of the M-ConSCM system lies not only in improving the efficiency of work for on-site engineers, but also providing the Kanban-like visual control system for project participants to control the whole project. Moreover, this article presents a generic system architecture and its implementation. [ABSTRACT FROM AUTHOR]