Expected Outputs. 2.4.1 What is the expected output of the student’s research? Mark with X Research assignment (for structured programmes) Thesis (for research masters programmes) Dissertation (for doctoral programmes)
Expected Outputs. 1. A first draft of report 2. A final report of no more than 20 pages, without annex with: An executive summary stating key findings A list of recommendations related to the functioning of the JFA in terms of efficiency, effectiveness and impact A review of good practices related to JFA
Expected Outputs. What are the expected outputs the candidate needs to deliver through the course of his or her candidature and thereafter? Examples: The candidate is expected to write at least xxx journal article(s) and submit for publication to a peer reviewed journal during the course / after completion of his or her candidature. The candidate is expected to present at least xxx academic paper(s) at an international/local academic conference during the course / after completion of his or her candidature. The candidate is expected to register at least xxx patent(s) during the course / after completion of his or her candidature. Should the candidate not complete the task(s) within the time agreed upon, SU reserves the right to appoint a writer to prepare the project for publication – in such a way so as not to disadvantage the candidate.
Expected Outputs. 4.1 The following outputs are required from this project (the delivery timetable is set out below): Agreed plan of work. Regular project board meetings (possibly monthly) and progress updates by phone/email (at least every 2 weeks), including progress against milestones and issues arising (format and content to be agreed at the project inception meeting). Research tools, including questionnaires, discussion guides, sampling frames etc. Presentation of interim findings, including answers to key questions identified by the steering group. Presentations of final results to DECC and stakeholder groups. All underpinning data including quantitative data tables in Excel / SPSS accessible format and/or CSV or tab delimited files. Draft interim report covering delivery costs and other agreed issues. Draft final evaluation report. Final evaluation report. A presentation in power point setting out main findings, for use by DECC. Assistance with dissemination of report findings, including presentations to DECC staff and stakeholders.
Expected Outputs. The Service provider will prepare and submit specific stage reports and documents to the satisfaction of the contracting Authority. The content of the reports will be guided by the detailed scope shown in the terms of reference. Reports shall be written in English. The metric system will be used and the British standard codes applied. The service provider shall have sole responsibility for all the information gathered and conclusions presented in the reports. The service provider will take into account all comments from the contracting authority parties regarding each stage submission and modify submitted reports accordingly.
Expected Outputs. Software and documentation for the two new consensus models into the crowd analysis framework. • New consensus models case study in a citizen science project. • Algorithm for numerical simulations useful to evaluate the efficacy of the consensus models considered in crowd analysis. • Report of the results of simulations, with suggestions to improve the consensus models. Actual Outputs: • Crowdanalysis, (program/code), URL: xxxxx://xxxx.xxx/project/crowdnalysis/ • Cerquides, J.; Mülâyim, M.O.; Xxxxxxxxx-Xxxxxxxx, J.; Xxxx Xxxxxxx, A.; Xxxxxxxxx-Xxxxxxx, X.X. A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data. Mathematics 2021, 9, 875., (publication), URL: xxxxx://xxx.xxx/10.3390/math9080875 • Xxxxxxx-Xxxxx, B.; Cerquides, J. On the Convergence of Stochastic Process Convergence Proofs. Mathematics 2021, 9, 1470., (publication), URL: xxxxx://xxx.xxx/10.3390/math9131470 • Xxxxxxxxx-Xxxxxxxx, J.; Cerquides, J. A Robust Solution to Variational Importance Sampling of Minimum Variance. Entropy 2020, 22, 1405., (publication), URL: xxxxx://xxx.xxx/10.3390/e22121405 • Xxxxx Xxxxxxxxx (2021). Parametrization invariant interpretation of priors and posteriors. arXiv:2105.08304 [cs, math, stat]., (publication), URL: xxxxx://xxx.xxx/http://xxxxx.xxx/abs/2105.08304 Connection of Results to Work Package Objectives: Crowdsourcing can be applied to quickly obtain accurate information in different domains, including disaster management scenarios. This requires the computation of the consensus among the different annotators. Probabilistic graphical models can be used to build interpretable consensus models. These models can answer questions such as “Who is the more competent annotator for this task?”, or “How many annotators do I need for this task?” which provide a clear example of machine learning with human-in-the-loop, and fully related to T1.3 Continuous & incremental learning in joint human/AI systems in WP2. The evolutionary results will help to understand the best way to proceed in the research, suggesting new theoretical and experimental studies to address the topic. Therefore, they make it possible to evaluate the interplay between human acting and AI learning in crowdsourcing tasks, connected with T3.2 Human-AI Interaction/collaboration paradigms
Expected Outputs. Software: an interface between nat.lang. parsing software (IRL) and reasoning software (knowledge graphs) Actual Outputs: • Web-Services library, (program/code), URL: xxxxx://xxxxxx.xxx/SonyCSLParis/Catasto Connection of Results to Work Package Objectives: Natural language processing and understanding in machines often relies on statistical pattern recognition. What is missing here is the ability of a machine to describe in a human understandable way how it came to a certain interpretation. This would allow humans to take part in a machine’s reasoning process, thereby facilitating human-computer interaction and collaboration. By using IRL, the interpretation of an utterance is transparently expanded, and ambiguous entities are resolved until a single interpretation is found. At the same time, large datasets with semantic knowledge about the world exist in open repositories on the web. These repositories could be used in a similar way as we humans use our semantic memory, to disambiguate entities that cannot be resolved using the context of a dialogue alone.
Expected Outputs. 1 Conference/Journal Paper • 1 Prototype • Dataset Samples
Expected Outputs. Submission to one of the following: International Journal of Social Robotics, Behaviour & Information Technology, AAMAS, or CHI. Submission to be sent by the end of August 2021. • Release of the game developed for the study on the AI4EU platform to allow other researchers to use it and extend it • Educational component on the Ethical aspect of AI, giving a concrete example on how AI can “manipulate” a human Actual Outputs: • The Pest Control Game experimental platform, (program/code), URL: will be released after the study is completed International Journal of Social Robotics or Behaviour & Information Technology, (publication) • Educational component on ethical aspect of AI, (other) Connection of Results to Work Package Objectives: This project contributes to WP3 and WP4. The study carried during the micro-project will give insight on how an artificial agent may influence a human's behavior in a social dilemma context, thus allowing for informed design and development of such artificial agent. In addition, the platform developed will be made available publicly, allowing future researchers to experiment on other configurations and other types of feedback. By using a well-development and consistent platform, the results of different studies will be more easily comparable.
Expected Outputs. 1 conference paper containing the description of the ontology and guidelines for its usages • 1 ontology artifact
