State of the aRt personality research: A tutorial on network analysis of personality data in R

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks. In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.

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Performance indicators for public transit connectivity in multi-modal transportation networks

With the purpose of measuring and monitoring systemic risk, some topological properties of the interbank exposures and the payments system networks are studied. We propose non-topological measures which are useful to describe the individual behavior of banks in both networks. The evolution of such networks is also studied and some important conclusions from the systemic risks perspective are drawn. A unified measure of interconnectednessis also created. The main findings of this study are: the payments system network is strongly connected in contrast to the interbank exposures network; the type of exposures and payment size reveal different roles played by banks; behavior of banks in the exposures network changed considerably after Lehman's failure; interconnectedness of a bank, estimated by the unified measure, is not necessarily related with its assets size.

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An Empirical Study of the Mexican Banking System's Network and Its Implications for Systemic Risk

Agroecology is a promising alternative to industrial agriculture, with the potential to avoid the negative social and ecological consequences of input-intensive production. Transitioning to agroecological production is, however, a complex project that requires diverse contributions from the outside of scientific institutions. Agroecologists therefore collaborate with traditional producers and agroecological movements. Permaculture is one such agroecological movement, with a broad international distribution and a unique approach to system design. Despite a high public profile, permaculture has remained relatively isolated from scientific research. Though the potential contribution of permaculture to agroecological transition is great, it is limited by this isolation from science, as well as from oversimplifying claims, and the lack of a clear definition. Here, we review scientific and popular permaculture literature. A systematic review discusses quantitative bibliometric data, including keyword analysis. A qualitative review identifies and assesses major themes, proposals, and claims. The manuscript follows a stratified definition of permaculture as design system, best practice framework, worldview, and movement. The major points of our analysis are as follows: (1) Principles and topics largely complement and even extend principles and topics found in the agroecological literature. (2) Distinctive approaches to perennial polyculture, water management, and the importance of agroecosystem configuration exceed what is documented in the scientific literature and thus suggest promising avenues of inquiry. (3) Discussions of practice consistently underplay the complexity, challenges, and risks that producers face in developing diversified and integrated production systems. (4) The movement is mobilizing diverse forms of social support for sustainability, in geographically diverse locations. (5) And scholarship in permaculture has always been a diverse marginal sector, but is growing.

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Permaculture for agroecology: design, movement, practice, and worldview. A review

GPUs have become popular recently to accelerate general-purpose data-parallel applications. However, most existing work has focused on GPU-friendly applications with regular data structures and access patterns. While a few prior studies have shown that some irregular workloads can also achieve speedups on GPUs, this domain has not been investigated thoroughly. Graph applications are one such set of irregular workloads, used in many commercial and scientific domains. In particular, graph mining -as well as web and social network analysis- are promising applications that GPUs could accelerate. However, implementing and optimizing these graph algorithms on SIMD architectures is challenging because their data-dependent behavior results in significant branch and memory divergence. To address these concerns and facilitate research in this area, this paper presents and characterizes a suite of GPGPU graph applications, Pannotia, which is implemented in OpenCL and contains problems from diverse and important graph application domains. We perform a first-step characterization and analysis of these benchmarks and study their behavior on real hardware. We also use clustering analysis to illustrate the similarities and differences of the applications in the suite. Finally, we make architectural and scheduling suggestions that will improve their execution efficiency on GPUs.

/pdf/pannotia-understanding-irregular-gpgpu-graph-applications-4aqnrykk6z.pdf

Ulrik

Papers

A faster algorithm for betweenness centrality