University of Leeds Sample Clauses

University of Leeds. Living allowance (1) Mobility allowance (2) Contribution to the research/training/transfer of knowledge programme expenses (3) Management activities (including audit certification) (4) Contribution to overheads (5) Total 306,432.00 82,252.80 129,600.00 373,257.00 89,154.17 980,695.97 Party 2 – Imperial College of Science, Technology and Medicine Living allowance (1) Mobility allowance (2) Contribution to the research/training/transfer of knowledge programme expenses (3) Management activities (including audit certification) (4) Contribution to overheads (5) Total 153,216.00 41,126.40 64,800.00 2,000.00 26,114.24 287,256.64 Party 3 - Universiteit Utrecht Living allowance (1) Mobility allowance (2) Contribution to the research/training/transfer of knowledge programme expenses (3) Management activities (including audit certification) (4) Contribution to overheads (5) Total 121,797.00 21,236.40 43,200.00 2,000.00 18,823.34 207,056.74 Party 4 – Universitair Medisch Centrum Utrecht Living allowance (1) Mobility allowance (2) Contribution to the research/training/transfer of knowledge programme expenses (3) Management activities (including audit certification) (4) Contribution to overheads (5) Total 118,674.00 31,854.60 64,800.00 2,000.00 21,732.86 239,061.46 Party 5 – Stichting Het Nederland Kanker Institut – Xxxxxx xxx Xxxxxxxxxxx Ziekenhuis Living allowance (1) Mobility allowance (2) Contribution to the research/training/transfer of knowledge programme expenses (3) Management activities (including audit certification) (4) Contribution to overheads (5) Total 118,674.00 31,854.60 64,800.00 2,000.00 21,732.86 239,061.46 Party 6 – Deutsches Krebsforschungszentrum
Sample 1
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University of Leeds. The University of Leeds is one of the largest higher education institutions in the UK, with more than 31,000 students from 147 different countries, and a member of the Xxxxxxx Group research-­‐intensive universities. We are a top 10 university for research and impact power in the UK, according to the 2014 Research Excellence Framework, and positioned as one of the top 100 best universities in the world in the 2014 QS World University Rankings. xxx.xxxxx.xx.xx This information is provided by RNS The company news service from the London Stock Exchange
Sample 1
University of Leeds. The School of Physics and Astronomy at the University of Leeds has expertise in photo-detector development, electronics systems design and physics analysis. The foreseen contributions to the KM3NeT-PP project are in WPB (participation in the political process), WPD (study of staged and/or distributed facilities) and in WPN (data dissemination).
Sample 1
University of Leeds. There are four clear directions for University of Leeds future work that arise out of SUBITO, each of which they have started to explore. The first is to replace the hand-crafting of rules within SUBITO by automatic learning of the behaviour patterns that characterise critical events. We had already made progress in learning simple events in a related EU project (Co-Friend) given video clips depicting examples of these target events, and optionally a spatio-temporal window within the video delineating examples more precisely. In this, we do not use the predominant approach of classifying spatial-temporal distributions of local image/video features and instead focus on the spatial and temporal relations between the objects depicted within a video. This mirrors the representation used in SUBITO. The challenge is to augment this representation to deal with the additional richness of hand-crafted relational models used in SUBITO, such as the critical metrical constraints based on proximity and time that define an abandonment (e.g. person must be out of range of the bag for a prescribed time). We have started by generalising the qualitative spatial and temporal relations in our current work to become learnt relations, thereby allowing adaptation to critical time delays and spatial displacements. This work is on-going within EU project COGNITO. A greater challenge would be to learn the movement models that characterise social groups. In SUBITO, the logical inference mechanism we used treats visual observations and hand-crafted rules as certain. A natural extension is to associate uncertainty with both the observations and the rules, leading to the inference of critical events with associated uncertainties. We started to do this for rules using Markov Logic Networks (within project Co-Friend) but have yet to extend this to the observations, although there are probabilistic logics that will do this. The implication would be that two incompatible but plausible hypotheses on who introduced a bag into the scene could be explored side by side - this kind of uncertainty was common for the scenarios in SUBITO. This also leads to quantitative assessment of the degree of threat in any given situation, depending on the uncertainty of the facts and rules used in inferring this assessment. A third direction arising out of SUBITO is to detect anomalous behaviours instead of pre- defined critical events. This would again be achieved by learning, but now within an unsupervised ...
Sample 1

Related to University of Leeds

  • University Any notice may be served upon the University by delivering it, in writing, to the University at the address set forth on the last page of this Agreement, by depositing it in a United States Postal Service deposit box with the postage fully prepaid and with the notice addressed to the University at the aforementioned address, or by sending a facsimile of it to the University facsimile number set forth on the last page of this Agreement.

  • Research Use The Requester agrees that if access is approved, (1) the PI named in the DAR and (2) those named in the “Senior/Key Person Profile” section of the DAR, including the Information Technology Director and any trainee, employee, or contractor1 working on the proposed research project under the direct oversight of these individuals, shall become Approved Users of the requested dataset(s). Research use will occur solely in connection with the approved research project described in the DAR, which includes a 1-2 paragraph description of the proposed research (i.e., a Research Use Statement). Investigators interested in using Cloud Computing for data storage and analysis must request permission to use Cloud Computing in the DAR and identify the Cloud Service Provider (CSP) or providers and/or Private Cloud System (PCS) that they propose to use. They must also submit a Cloud Computing Use Statement as part of the DAR that describes the type of service and how it will be used to carry out the proposed research as described in the Research Use Statement. If the Approved Users plan to collaborate with investigators outside the Requester, the investigators at each external site must submit an independent DAR using the same project title and Research Use Statement, and if using the cloud, Cloud Computing Use Statement. New uses of these data outside those described in the DAR will require submission of a new DAR; modifications to the research project will require submission of an amendment to this application (e.g., adding or deleting Requester Collaborators from the Requester, adding datasets to an approved project). Access to the requested dataset(s) is granted for a period of one (1) year, with the option to renew access or close-out a project at the end of that year. Submitting Investigator(s), or their collaborators, who provided the data or samples used to generate controlled-access datasets subject to the NIH GDS Policy and who have Institutional Review Board (IRB) approval and who meet any other study specific terms of access, are exempt from the limitation on the scope of the research use as defined in the DAR.

  • Research, Science and Technology Cooperation 1. The aims of cooperation in research, science and technology, carried out in the mutual interest of the Parties and in compliance with their policies, will be: (a) to build on existing agreements already in place for cooperation on research, science and technology; (b) to encourage, where appropriate, government agencies, research institutions, universities, private companies and other research organizations in the Parties to conclude direct arrangements in support of cooperative activities, programs or projects within the framework of this Agreement, specially related to trade and commerce; and (c) to focus cooperative activities towards sectors where mutual and complementary interests exist, with special emphasis on information and communication technologies and software development to facilitate trade between the Parties. 2. The Parties will encourage and facilitate, as appropriate, the following activities including, but not limited to:

  • Commercial Driver’s License As a result of recent Federal statutory requirements, the State of Michigan enacted Act 346 of 1988. The parties agree that as a result of these statutory requirements some employees within the Technical Bargaining Unit may be required to obtain and retain a Commercial Drivers License (CDL) to continue to perform certain duties for the State. Whenever a CDL is referred to in this Section, it is understood to mean the CDL and any required endorsements. In order to implement this provision, the parties agree to the following:

  • Xxxxx, Haldimand, Norfolk (a) An employee shall be granted five working days bereavement leave with pay upon the death of the employee’s spouse, child, stepchild, parent, stepparent, legal guardian, grandchild or step-grandchild.

  • University Obligations (a) The University must, and must ensure its Personnel:

  • PROFESSORS, TEACHERS AND RESEARCHERS 1. An individual who is a resident of a Contracting State immediately before making a visit to the other Contracting State, and who, at the invitation of any university, college, school or other similar educational institution which is recognized by the competent authority in that other Contracting State, visits that other Contracting State for a period not exceeding two years solely for the purpose of teaching or research or both at such educational institution shall be exempt from tax in that other Contracting State on any remuneration for such teaching or research.

  • Science and Technology 1. Member States shall:

  • Return of University Records Contractor agrees that within thirty (30) days after the expiration or termination of this Agreement, for any reason, all University Records created or received from or on behalf of University will be (1) returned to University, with no copies retained by Contractor; or (2) if return is not feasible, destroyed. Twenty (20) days before destruction of any University Records, Contractor will provide University with written notice of Contractor’s intent to destroy University Records. Within five (5) days after destruction, Contractor will confirm to University in writing the destruction of University Records.

  • ACKNOWLEDGEMENT AND PROTECTION OF INTELLECTUAL PROPERTY RIGHTS 9.1 The Institution acknowledges that all copyrights, patent rights, trade marks, database rights, trade secrets and other intellectual property rights relating to the Licensed Material are the sole and exclusive property of Publisher or are duly licensed to the Publisher and that this Licence does not assign or transfer to the Institution any right, title or interest therein except for the right to use the Licensed Material in accordance with the terms and conditions of this Licence.

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