1,996 research outputs found
Les théories cosmologiques de M. Nys
No full textGeerts G. Les théories cosmologiques de M. Nys. In: Revue néo-scolastique. 12ᵉ année, n°48, 1905. pp. 483-487
Projections of use and supply of long-term care in Europe: Policy implications. ENEPRI Policy Brief No. 12, 12 April 2012
No full textProjections of use and supply of formal and informal care carried out in Work Package 6 of the ANCIEN project show that if current patterns of care use and supply prevail, supply of care is likely to fall behind demand. This paper discusses the key policy implications of these findings. Meeting the required care capacity poses multifarious challenges for European welfare states, namely: how to limit the growing burden of LTC expenditure on social security or government budgets, especially in countries that rely heavily on formal care, and how to avoid an increased informal caregiver burden, while at the same time ensuring adequate care for disabled older persons. Technological advances could help close the care gap, by reducing the need for care and boosting the productivity of formal and informal care workers, or by lessening the need for care. As it is impossible to assess whether these efficiency gains will suffice to bridge the care gap, policies should anticipate an increasing care burden and plan accordingly for how to deal with its consequences
A Survey of Methods and Input Data Types for House Price Prediction: Literature list
No full textGeneral file description
This xlsx document contains the literature list that forms the basis of the paper 'A Survey of Methods and Input Data Types for House Price Prediction' by Geerts, M., vanden Broucke, S. and De Weerdt, J. The Excel document contains seven sheets, relating to the phases described in the survey.
Phase3
This sheet contains the literature list for the end of Phase 2 and the start of Phase 3. It has 590 rows and 19 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title) and Algorithmic (Abstract). The latter two columns are used to indicate whether the articles describe an algorithmic approach to predict house prices based on the title and the abstract respectively. These two columns take the values 'Yes', 'No', and 'Maybe', and were completed during Phase 3.
Phase4
This sheet contains the literature list for the end of Phase 3 and the start of Phase 4. It has 116 rows and 20 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title), Algorithmic (Abstract) and Reading. All columns are the same as in the first sheet, except for the three last columns. The columns Algorithmic (Title) and Algorithmic (Abstract) now only contain the value 'Yes' as only the articles that describe an algorithm are retained in Phase 3. The column Reading describes the outcome of Phase 4. This columns is empty if the article is retained in this phase and describes the reason if it is not retained.
Phase4(end)
This sheet contains the literature list for the end of Phase 4. It has 94 rows and 20 columns. Each row contains the citation information of one article. The columns describe the ID, Authors, Title, Year, Source title, Volume, Issue, DOI, ISSN, ISBN, PubMed, Publisher, Document Type, Language, Keywords, Link, Book DOI, Algorithmic (Title), Algorithmic (Abstract) and Reading. All columns are the same as in the second sheet. The column Reading is now empty because the articles that were not retained in Phase 4 are removed from the list.
Data table
This sheet contains a table of the literature at the end of Phase 4 with indications of input data types used in the articles, the data novelty score and the cluster that the articles belong to. It has 95 rows, where each row contains the information of one article, except the last 'Total' row. It contains 21 columns :
ID: This is the same identifier as in the previous sheets.
Column1: This is a new identifier, based on an ordering on year and author.
Authors: Same as before.
Title: Same as before.
Year: Same as before.
Structural, Temporal data, Socioeconomic, Environmental, POI, Basic spatial, Location, Eucl Distances, Adv Spatial, Network Distance, Topographical data, Graphs, Images, Text: These are the different input data types. The cell is filled with 'X' if the corresponding article is using the input data type described in the column name.
Score: This column indicates the data novelty score, calculated as explained in the paper based on the sheet 'Rules Data novelty score'.
Cluster: This column indicates the cluster number as explained in the Discussion section of the paper.
Rules Data novelty score
This sheet contains 15 rows, of which the first contains the titles, and two columns. The first columns contains the input data types as in the previous sheet and the second column contains the respective novelty scores.
Model table
This sheet contains a table of the literature at the end of Phase 4 with indications of model types used in the articles, the model novelty score and the cluster that the articles belong to. It has 95 rows, where each row contains the information of one article, except the last 'Total' row. It contains 21 columns :
ID: Same as before.
Column1: Same as before
Authors: Same as before.
Title: Same as before.
Year: Same as before.
MRA, Kriging, SEM, SVC, Time Series, FL, NN, DT, RF, GBT, SVM, ANN, (Other) Ensembles, DL: These are the different model types. The cell is filled with 'X' if the corresponding article is using the model type described in the column name.
Score: This column indicates the model novelty score, calculated as explained in the paper based on the sheet 'Rules Model novelty score'.
Cluster: This column indicates the cluster number as explained in the Discussion section of the paper.
Rules Model novelty score
This sheet contains 15 rows, of which the first contains the titles, and two columns. The first columns contains the model types as in the previous sheet and the second column contains the respective novelty scores
Social TV From a Computer-Supported Cooperative Work Perspective
No full textGross T, Paul-Stueve T, Fetter M. Social TV From a Computer-Supported Cooperative Work Perspective. In: Cesar PC, Geerts D, Chorianopoulos K, eds. Social Interactive Television: Immersive Shared Experiences and Perspectives. Hershey, PA, USA: IGI Global; 2009: 50-66
Natural Resources Research Institute Technical Report
No full textHauck, Steven A; Heine, John J; Severson, Mark J; Post, Sara P; Chlebecek, Sara; Monson Geerts, Stephen D; Oreskovich, Julie A; Gordee, Sarah M. (2014). Geological and Geochemical Reconnaissance for Rare Earth Element Mineralization in Minnesota. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/187176
Comparative evaluation of the molluscicidal activity of Ambrosia maritima in Egypt and Senegal
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