Bayesian Cluster Finder: Clusters in the CFHTLS Archive Research Survey

The detection of galaxy clusters in present and future surveys enables measuring mass-to-light ratios, clustering properties, galaxy cluster abundances and therefore, constraining cosmological parameters. We present a new technique for detecting galaxy clusters, which is based on the Matched Filter Algorithm from a Bayesian point of view. The method is able to determine the position, redshift and richness of the cluster through the maximization of a filter depending on galaxy luminosity, density and photometric redshift combined with a galaxy cluster prior that accounts for color-magnitude relations and BCG-redshift relation. We tested the algorithm through realistic mock galaxy catalogs, revealing that the detections are 100% complete and 80% pure for clusters up to z $$20 (Abell Richness $\sim$0, M$\sim4\times10^{14} M_{\odot}$). The completeness and purity remains approximately the same if we do not include the prior information, implying that this method is able to detect galaxy cluster with and without a well defined red sequence. We applied the algorithm to the CFHTLS Archive Research Survey (CARS) data, recovering similar detections as previously published using the same or deeper data plus additional clusters which appear to be real.Comment: Accepted for publication in MNRAS; 17 pages, 38 figure

Edge Computing Research Survey

In this paper, we present a survey in edge computing research

Office of Research Survey Instrument

Researchers frequently face the daunting task of locating appropriate funding to support their research. A survey by University of Michigan (U-M) Medical School Office of Research (OoR) found that the majority of respondents expressed frustration with the time and effort it takes to search for new funding opportunities. This is the survey instrument that was used.http://deepblue.lib.umich.edu/bitstream/2027.42/115473/1/Office of Research Survey Instrument.pdfDescription of Office of Research Survey Instrument.pdf : U-M Medical School Office of Research Surve

Research Survey Questionnaire and Results

Prior to the development of the Visual Toolkit, a questionnaire was sent to all full and part-time faculty in the Pilon School of Business to gather information about the current use of visual tools among the faculty. Among the 10 questions asked were inquiries into faculty and student level of comfort with visuals, whether faculty was aware of the use of visual tools in business today and whether they believe teaching visual thinking (learning and processing with visuals) will better prepare students for the current business environment. The full questionnaire and survey results are included herehttps://source.sheridancollege.ca/business_visual_toolkit_survey/1000/thumbnail.jp

Public Impact-Focused Research Survey Results

The Association of Public and Land Grant Universities (APLU) Council on Research (COR) led an initiative to define, identify, and develop a recommended path forward for public impact research (PIR). A survey was conducted of APLU institution in order to: To characterize the extent of public impact research (PIR) occurring at APLU institutions. To understand how institutions (or leaders within institutions) think about, define, and communicate about this type of work. To provide perspectives about the challenges, opportunities, and rewards that may be associated with this type of scholarship. Responses were received from a diverse set of seventy public and land grant universities (APLU total membership was 239 universities at the time of this survey). Research expenditures at responding institutions ranged from $5 million to over$1 billion in FY 2017, and respondents included Hispanic-serving institutions, historically black universities, IEP-designated universities, and were received from 26 US states and one Canadian province. This document contains the complete set of de-identified responses to the survey. The intent is to make this broadly available and accessible to individuals or groups who may want to further analyze or use these results

Open Research Survey Report 2017

Providing Research Data Management (RDM) support has many challenges. The different types of data, the volume storied on various media, the differences across disciplines, all contribute to the complexity of supporting RDM in a diverse institution such as Birkbeck. Another part of the challenge of delivering an RDM service is the varying attitudes toward data management. Staff are often unclear of what “Research Data” means to them, and have often have mixed levels of previous support or training. Without knowing what our academics already understand of RDM, it would be very hard to meet their needs in the correct way. Many institutions have run these types of surveys in the past few years, yielding useful results. Recently UCL, SOAS, and a consortium led by Jisc have run very similar surveys, which we hoped to be able to compare our results to. Open Access was also included in the survey; so as to compare attitudes to a previous survey which ran in 2011. Same questions were deliberately the same, while we added some extra questions about the Research Excellence Frame work to gauge current staff attitudes

Commercialization of Government Funded R&D : Follow-up Research Survey on NEDO Research Projects

Drawing on data obtained from the questionnaire survey for the 242 private R&D projects supported by NEDO (New Energy and Industrial Technology Development Organization), Japan’s public management organization promoting R&D, this paper explores how the private R&D projects’ dependence on public supports affects their R&D processes and, in turn, projects’ performance and the commercialization of developed technologies. Our analyses show that dependence on government resources gives rise to some —isolation. of the projects from the other parts of companies that they belong to. Such isolation, mainly derived from projects’ unique positions in —double dependence. structures, negatively affects R&D performance especially related to commercialization. First, high dependence on public resources prevents project members from interacting with people outside the projects within the company. This precludes the projects to effectively leverage internal resources in overcoming technological problems. Secondly, high dependence weakens governance or control on project’s activities by internal management. This deters development of commercialization technologies and makes it difficult for the projects to acquire legitimacy for further investment towards commercialization. Our findings suggest that both companies and public funding agencies should promote projects to keep intimate relationships with the other parts of their organization for successful R&D leading to commercialization.