Numbers Of Actors Research Articles

Asymptotic theory in bipartite graph models with a growing number of parameters

AbstractAffiliation networks contain a set of actors and a set of events, where edges denote the affiliation relationships between actors and events. Here, we introduce a class of affiliation network models for modelling the degree heterogeneity, where two sets of degree parameters are used to measure the activeness of actors and the popularity of events, respectively. We develop the moment method to infer these degree parameters. We establish a unified theoretical framework in which the consistency and asymptotic normality of the moment estimator hold as the numbers of actors and events both go to infinity. We apply our results to several popular models with weighted edges, including generalized ‐, Poisson and Rayleigh models. Simulation studies and a realistic example that involves the Poisson model provide concrete evidence that supports our theoretical findings.

Comparison of Methods for Imputing Social Network Data

Social network data often contain missing values because of the sensitive nature of the information collected and the dependency among the network actors. As a response, network imputation methods including simple ones constructed from network structural characteristics and more complicated model-based ones have been developed. Although past studies have explored the influence of missing data on social networks and the effectiveness of imputation procedures in many missing data conditions, the current study aims to evaluate a more extensive set of eight network imputation techniques (i.e., null-tie, Reconstruction, Preferential Attachment, Constrained Random Dot Product Graph, Multiple Imputation by Bayesian Exponential Random Graph Models or BERGMs, k-Nearest Neighbors, Random Forest, and Multiple Imputation by Chained Equations) under more practical conditions through comprehensive simulation. A factorial design for missing data conditions is adopted with factors including missing data types, missing data mechanisms, and missing data proportions, which are applied to generated social networks with varying numbers of actors based on 4 different sets of coefficients in ERGMs. Results show that the effectiveness of imputation methods differs by missing data types, missing data mechanisms, the evaluation criteria used, and the complexity of the social networks. More complex methods such as the BERGMs have consistently good performances in recovering missing edges that should have been present. While simpler methods like Reconstruction work better in recovering network statistics when the missing proportion of present edges is low, the BERGMs work better when more present edges are missing. The BERGMs also work well in recovering ERGM coefficients when the networks are complex and the missing data type is actor non-response. In conclusion, researchers analyzing social networks with incomplete data should identify the network structures of interest and the potential missing data types before selecting appropriate imputation methods.

Multi-Agent Deep Q Network to Enhance the Reinforcement Learning for Delayed Reward System

This study examines various factors and conditions that are related with the performance of reinforcement learning, and defines a multi-agent DQN system (N-DQN) model to improve them. N-DQN model is implemented in this paper with examples of maze finding and ping-pong as examples of delayed reward system, where delayed reward occurs, which makes general DQN learning difficult to apply. The implemented N-DQN shows about 3.5 times higher learning performance compared to the Q-Learning algorithm in the reward-sparse environment in the performance evaluation, and compared to DQN, it shows about 1.1 times faster goal achievement speed. In addition, through the implementation of the prioritized experience replay and the implementation of the reward acquisition section segmentation policy, such a problem as positive-bias of the existing reinforcement learning models seldom or never occurred. However, according to the characteristics of the architecture that uses many numbers of actors in parallel, the need for additional research on light-weighting the system for further performance improvement has raised. This paper describes in detail the structure of the proposed multi-agent N_DQN architecture, the contents of various algorithms used, and the specification for its implementation.

Power across the global health landscape: a network analysis of development assistance 1990-2015.

Power distribution across the global health landscape has undergone a fundamental shift over the past three decades. What was once a system comprised largely of bilateral and multilateral institutional arrangements between nation-states evolved into a varied landscape where these traditional actors were joined by a vast assemblage of private firms, philanthropies, non-governmental organizations and public–private partnerships. Financial resources are an explicit power source within global health that direct how, where and to whom health interventions are delivered, which health issues are (de)prioritized, how and by whom evidence to support policies and interventions is developed and how we account for progress. Financial resource allocations are not isolated decisions but rather outputs of negotiation processes and dynamics between actors who derive power from a multiplicity of sources. The aims of this paper are to examine the changes in the global health actor landscape and the shifts in power using data on disbursements of development assistance for health (DAH). A typology of actors was developed from previous literature and refined through an empirical analysis of DAH. The emergent network structure of DAH flows between global health actors and positionality of actors within the network were analysed between 1990 and 2015. The results reflect the dramatic shift in the numbers of actors, relationships between actors, and funding dispersal over this time period. Through a combination of the massive influx of new funding sources and a decrease in public spending, the majority control of financial resources in the DAH network receded from public entities to a vast array of civil society organizations and public–private partnerships. The most prominent of these was the Bill and Melinda Gates Foundation and the Global Fund for AIDS, TB and malaria, which rose to the third and fourth most central positions within the DAH network by 2015.

Comparing Complexity in Watershed Governance: The Case of California

Environmental governance scholars argue that optimal environmental performance can be achieved by matching the scale of governance to the scale of the resource being managed. In the case of water, this means managing at the scale of the watershed. However, many watersheds lack a single watershed-scale organization with authority over all water resources and instead rely on cross-jurisdiction coordination or collaboration among diverse organizations. To understand what “watershed governance” looks like fully, this paper maps organizations with rights to use, regulate, or manage water in four subwatersheds in California (the American, Cosumnes, and Kings Rivers in the Sacramento-San Joaquin watershed and the Shasta River in the Klamath watershed). We assemble datasets of water organizations, water rights holders, and water management plans and use content analysis and social network analysis to explore what water management looks like in the absence of a single basin authority. We describe the institutional complexity that exists in each watershed, compare the physical and institutional interconnections between actors in the watersheds, and then ask to what extent these connections map onto watershed boundaries. We find that the ways in which water management is complex takes very different forms across the four watersheds, despite their being located in a similar political, social, and geographic context. Each watershed has drastically different numbers of actors and uses a very different mix of water sources. We also see very different levels of coordination between actors in each watershed. Given these differences, we then discuss how the institutional reforms needed to create watershed-scale management are unique for each watershed. By building a stronger comparative understanding of what watershed governance actually entails, this work aims to build more thoughtful recommendations for building institutional fit.

Influences of executive and memory functioning on memory for the sources of actions.

This research provides evidence for similarities and differences between the results of traditional source memory paradigms and results from the Person-Action Conjunction (PAC) test. In the PAC test, participants view actions performed by different actors and are later tested on their memory for which actor performed each action. The PAC test can be construed as a source memory test, with actions serving as target information and actors representing the sources of those actions. Unlike traditional source memory tests, which involve a many-to-few relation of targets to sources, the PAC test involves a many-to-many relation, typically with equal numbers of actors and actions. To test whether the relation of targets to sources influences the cognitive mechanisms underlying memory for the sources of actions, young and older participants in two experiments (N = 217) took part in the PAC test, either in the context of many actors or just two actors. Participants also received Glisky and Kong's (2008) battery of tests of executive and memory functioning. Executive functioning predicted source memory performance in older adults tested in the context of just two actors, whereas memory functioning predicted young adult performance in this context. Moreover, memory functioning predicted the performance of both age groups when tested in the context of many actors, even after controlling for memory for those actors in isolation. Both young and older adults may thus rely on basic associative mechanisms to remember the sources of actions when each actor is only encountered once in the context of performing an individual action. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Longitudinal multiple case study on effectiveness of network-based dementia care towards more integration, quality of care, and collaboration in primary care

Introduction : The rising incidence and policies to keep dementia patients in their own homes are increasingly putting pressure on primary care systems and budgets. The DementiaNet program stimulates development of primary care networks of medical, nursing and welfare professionals for community-dwelling dementia patients through practice facilitation. This study aimed to provide insight into the merits and drawbacks of this program, mechanisms and which contextual factors influenced them. Methods : In this longitudinal mixed methods multiple case study, primary care professionals with shared caseloads of dementia patients, were enrolled to form networks in the DementiaNet program. Data collection consisted of continuously kept logs, yearly structured interviews to rate the network maturity score (range 0-24), yearly quality of care assessment through a sum score of quality indicators (range 0-100), and in-depth interviews regarding experiences and perceived effects. Quantitative data were analyzed through mixed models; qualitative data with thematic analysis. Results were integrated by combined interpretation. Results : Thirteen networks were successfully initiated in the program, consisting of a median of 9 professionals. Overall, the networks showed an average yearly increase of 2.03 (95% CI 1.20-2.96) on network maturity and 8.45 (95% CI 2.80-14.69) on quality indicator sum scores. Mixed methods interpretation revealed patterns regarding network and contextual factors enabling the transition towards more mature networks and better quality of care. Discussion : Time trends in network maturity and quality of care indicators showed overall improvements. Several enabling factors for the transition to network-based care were identified including strong and adequate leadership (preferably with leaders from primary care practice), high involvement of motivated primary care physicians, high acquaintanceship with other network members, and network seize with a compact network that operates in a relatively small geographical area. Conclusions : Participation in the DementiaNet program was associated with increased network maturity and subsequent beneficial effects on quality of care. Adaptation towards a more mature network seemed to favour quality of care improvements. Lesson learned : The multiple case study design demonstrated its value in the evaluation of DementiaNet as example of a complex health care innovation by incorporating interactions and contextual dependency. Limitations : The main limitation of the study was the limited follow-up. The DementiaNet approach demands considerable changes in behaviour and practice from large numbers of actors; such adaptations require time and will be different per network. Indeed, networks work different in speed of change and improvement goals. Nonetheless, these initial results show improvements even over one and two year timeframes. Suggestions for future research : A succeeding study will be initiated to ensure longer follow-up of existing networks, while simultaneously expanding the number of networks.

Confidence Intervals for Assessing Sizes of Social Network Centralities

This research uses random networks as benchmarks for inferential tests of network structures. Specifically, we develop formulas for expected values and confidence intervals for four frequently employed social network centrality indices. The first study begins with analyses of stylized networks, which are then perturbed with increasing levels of random noise. When the indices achieve their values for fully random networks, the indices reveal systematic relationships that generalize across network forms. The second study then delves into the relationships between numbers of actors in a network and the density of a network for each of the centrality indices. In doing so, expected values are easily calculated, which in turn enable chi-square tests of network structure. Furthermore, confidence intervals are developed to facilitate a network analyst’s understanding as to which patterns in the data are merely random, versus which are structurally significantly distinct.

Mobile based application for prediction of diabetes mellitus: FHIR Standard

Presently physicians providing clinical decision along clinical guidelines manually on basis of manual query to patients that involve documentation files of lab reports, medication description etc., that make practice sluggish and arduous. With development of mobile based application provide assistance to physician in providing quick decision in appropriate manner as patient data available any-time from any-where that will enhance quality of care in field of healthcare. HL7 standard promotes FHIR(Fast Health Interoperability Resource) standard and health information technology for mobile-health. Mobile health is not a vertical field, but a kind of horizontal field that has cut various impact of healthcare domains. This application provide the effective health management of patient's electronic health record with ease of user friendly interface, that can be accessed on role based authentication by numbers of actors like patient, physician, clinic staff and patient's family etc. Basically this study projected decision support system for prediction of chronic disease-Diabetic- Mellitus using FHIR(Fast Health Interoperability Resource) as standard for interoperability among hospital information system. Application provide physician's structured series of symptoms/signs as uploaded by patients, laboratory and staff. Series of questioner along with outcomes are formed, all outcomes appraised and tested by team of medical domain experts.

Confidence Intervals for Assessing Sizes of Social Network Centralities

This research uses random networks as benchmarks for inferential tests of network structures. Specifically, we develop formulas for expected values and confidence intervals for four frequently employed social network centrality indices. The first study begins with analyses of stylized networks, which are then perturbed with increasing levels of random noise. When the indices achieve their values for fully random networks, the indices reveal systematic relationships that generalize across network forms. The second study then delves into the relationships between numbers of actors in a network and the density of a network for each of the centrality indices. In doing so, expected values are easily calculated, which in turn enable chi-square tests of network structure. Furthermore, confidence intervals are developed to facilitate a network analyst’s understanding as to which patterns in the data are merely random, versus which are structurally significantly distinct.

Affiliation discrete weighted networks with an increasing degree sequence

ABSTRACTAffiliation network is one kind of two-mode social network with two different sets of nodes (namely, a set of actors and a set of social events) and edges representing the affiliation of the actors with the social events. The connections in many affiliation networks are only binary weighted between actors and social events that can not reveal the affiliation strength relationship. Although a number of statistical models are proposed to analyze affiliation binary weighted networks, the asymptotic behaviors of the maximum likelihood estimator (MLE) are still unknown or have not been properly explored in affiliation weighted networks. In this paper, we study an affiliation model with the degree sequence as the exclusively natural sufficient statistic in the exponential family distributions. We derive the consistency and asymptotic normality of the maximum likelihood estimator in affiliation finite discrete weighted networks when the numbers of actors and events both go to infinity. Simulation studies and a real data example demonstrate our theoretical results.

Affiliation networks with an increasing degree sequence

ABSTRACTAffiliation network is one kind of two-mode social network with two different sets of nodes (namely, a set of actors and a set of social events) and edges representing the affiliation of the actors with the social events. Although a number of statistical models are proposed to analyze affiliation networks, the asymptotic behaviors of the estimator are still unknown or have not been properly explored. In this article, we study an affiliation model with the degree sequence as the exclusively natural sufficient statistic in the exponential family distributions. We establish the uniform consistency and asymptotic normality of the maximum likelihood estimator when the numbers of actors and events both go to infinity. Simulation studies and a real data example demonstrate our theoretical results.

Expanding boundaries: Nongovernmental organizations as supply chain members

Abstract Using a social movement perspective, we propose a framework that includes nonprofit actors as members of supply chains in a context that we call sustainable supply chain facilitation, particularly within multi-stakeholder supply chain sustainability initiatives. In this framework, certain nongovernmental organizations (NGOs) work alongside other supply chain firms, going beyond technical roles to serve as coordinators, conveners, organizers, brokers, and negotiators who facilitate multiparty agreement on sustainability issues within and across supply chains. We describe a set of roles consisting of third-party facilitators (3PF), fourth-party facilitators (4PF), and fifth-party facilitators (5PF) serving in increasingly strategic roles with increasing numbers of actors, and with increasing potential for co-creation of value in global supply chains. Reframing nongovernmental organizations as members of supply chains instead of outsiders provides a dramatically different perspective. This explicit acknowledgement of membership can help business and NGO managers to rethink their own roles and motivations and to find collaborative solutions in the steady transition to more sustainable supply chains.

Sum Product Networks for Activity Recognition.

This paper addresses detection and localization of human activities in videos. We focus on activities that may have variable spatiotemporal arrangements of parts, and numbers of actors. Such activities are represented by a sum-product network (SPN). A product node in SPN represents a particular arrangement of parts, and a sum node represents alternative arrangements. The sums and products are hierarchically organized, and grounded onto space-time windows covering the video. The windows provide evidence about the activity classes based on the Counting Grid (CG) model of visual words. This evidence is propagated bottom-up and top-down to parse the SPN graph for the explanation of the video. The node connectivity and model parameters of SPN and CG are jointly learned under two settings, weakly supervised, and supervised. For evaluation, we use our new Volleyball dataset, along with the benchmark datasets VIRAT, UT-Interactions, KTH, and TRECVID MED 2011. Our video classification and activity localization are superior to those of the state of the art on these datasets.

Leverging Knowledge and Networks: A Creative Projects Perspective on Entrepreneurial Action

This paper extends tertius iungens social network dynamics to theorize the micro-social level of entrepreneurial activity – the social dynamics of relatively small numbers of actors surrounding the formation and early growth of new ventures. We animate these ideas with a focus a project-based view of entrepreneurship that emphasizes the collective action in which initial entrepreneurial groups define emergent goals and aggregate people and resources toward realizing them. This theoretical framework has as its central conceptual components tertius iungens connecting activity and creative project action trajectories. Our perspective offers insights into the social processes associated with new venture formation while integrating and extending key elements from a growing body of work on entrepreneurial action. By illuminating the initial stages of emergent entrepreneurial action, our study clarifies social processes surrounding new venture initiatives while suggesting ways to advance entrepreneurship theory ...

Public policy and media frames: the debate over migration in Brazil

The main goal of this article is to provide a good basis to assess the way media frames are embedded in a wider social scenario, and how public and political preferences can be researched through media debate. The methodology adopted allows for an analysis of newspaper articles that can show broader trends of the debate and serve as a thermometer to measure public debate. It can further highlight details and enable in-depth analyses of media discourse. The article explores the interconnectedness of media debate and policy-making process by means of the analysis of articles published in a Brazilian newspaper between 2009 and 2010. Quantitative and qualitative methodologies are employed to identify the frames used in media and to offer insights of their relationship with the political debate. The ongoing political debate has raised attention to the issue of migration, with a great numbers of actors expressing very diverse points of view. A broader public debate has been initiated and some portions of it find voice in different means of communication. The paper argues that changes in the public and in the media debate are a response to changes in the political debate, while at the same time the first two also help to outline the latter.

Collective Action at Local and Global Scales: The Next Collaborative Agenda

As we approach the twenty-year anniversary of Keohane and Ostrom’s Local Commons and Global Interdependence, I assess their agenda for collaboration between scholars working in the local and global domains. I use the case of global climate change - a challenge that intrinsically spans local to global collective action - to emphasize what scholars working at the intersection of these two domains have learned over the last two decades and what we might do next. Issues that were ripe twenty years ago - such as studying the effects of numbers of actors and their heterogeneity - have seen substantial progress. New topics for cross-domain research include a more careful look at how collective action affects technological innovation. They also include the study of how fragmented institutions affect collective action; fragmentation has grown as a research topic in both domains yet described with different terms of “polycentrism” and “regime complexes.” This paper is part of a panel at APSA aimed at reviving the Keohane-Ostrom; I suggest that a shift to these new topics is as important as a revival of interest in collaboration in these two domains.

The Challenges of Planetary Bandwagoning

This article explores a paradox at the heart of climate bandwagoning. Numerous actors have hitched their efforts to climate policy formation in an effort either to advance their own interests or genuinely contribute to addressing this most urgent global dilemma or both. At the same time, the large number of stakeholders complicates climate negotiations as exceeding numbers of actors bring related but tangential issues into discussions and demand to be heard. The international community is thus faced with an almost existential situation: to address climate change in an effective manner requires nearly everyone in the room (regime bandwagoning); with everyone in the room, however, less is accomplished (regime sclerosis). This article explains such a paradox by stepping back from the cases presented in this special issue, and bringing into high relief the lineaments of regime congestion as they manifest in global climate affairs, and outlining the promises and perils involved.

A SELF-ADAPTIVE MODEL OF ACTOR-COLLABORATION NETWORK

We suggest a self-adaptive model for a description of actor-collaboration. Suppose that the numbers of actors and directors increase as time progresses (with different velocity). Each of the people is randomly given a style coefficient and a famousness coefficient, which vary on time according to his achievements in every year. A director can conduct more films and an actor can be invited to perform in more films in condition they have a higher famousness coefficient. Our numerical simulation results show that the actor-collaboration network described by this model is both small-world network and scaling-free network. All the important statistical parameters obtained by the simulation are in a good agreement with the statistical results. We also suggest a new parameter, which is addressed as "degree of connexity". Its distribution shows a new power law.

Evaluation of Preparedness and Response to Hurricanes Georges and Mitch: Conclusions and Recommendations

Mr. Chairman, Ladies and Gentlemen, first let me thank you for coming to this meeting that has been organized by us in close collaboration with UYDP, OCHA, UNIGEF and IDNOR with generous support from the Canadian, UK, and USA development agencies. It always is a pleasure to recognize our partners.We have with us here today representatives of a large number of agencies, institutions, NGOs, and private individuals. This cross section of interests is a manifestation of a growing and irreversible trend. The important issues of our time cannot be dealt with solely by nations, agencies, or individuals, even the most powerful ones. The phenomenon of globalization no longer is restricted to economic or financial matters: it is now evoking the wide participation of ranges and numbers of actors that would have been unthinkable a few decades ago. In almost all aspects of our work, we are looking to find the partners and interests that can bring value to the management of the issue or the search for solutions, if definitive solutions ever can be found to the really important human challenges.