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  1. Data Science and Knowledge Discovery
    Contributor: Portela, Filipe (Herausgeber)
    Published: 2022
    Publisher:  MDPI - Multidisciplinary Digital Publishing Institute, Basel

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    Source: Union catalogues
    Contributor: Portela, Filipe (Herausgeber)
    Language: Undetermined
    Media type: Ebook
    Format: Online
    ISBN: 9783036543154
    Other identifier:
    10.3390/books978-3-0365-4315-4
    Other subjects: crisis reporting; chatbots; journalists; news media; COVID-19; textbook research; digital humanities; digital infrastructures; data analysis; content base image retrieval; semantic information retrieval; deep features; multimedia document retrieval; data science; open government data; governance and social institutions; economic determinants of open data; geoinformation technology; fractal dimension; territorial road network; box-counting framework; script Python; ArcGIS; internet of things; LoRaWAN; ICT; The Things Network; ESP32 microcontroller; decision systems; rule based systems; databases; rough sets; prediction by partial matching; spatio-temporal; activity recognition; smart homes; artificial intelligence; automation; e-commerce; machine learning; big data; customer relationship management (CRM); distracted driving; driving behavior; driving operation area; data augmentation; feature extraction; authorship; text mining; attribution; neural networks; deep learning; forensic intelligence; dashboard; WebGIS; data analytics; SARS-CoV-2; Big Data; Web Intelligence; media analytics; social sciences; humanities; linked open data; adaptation process; interdisciplinary research; media criticism; classification; information systems; public health; data mining; ioCOVID19; n/a; Information technology industries; Computer science
    Scope: 1 electronic resource (254 pages)
  2. Data Science and Knowledge Discovery
    Contributor: Portela, Filipe (Herausgeber)
    Published: 2022
    Publisher:  MDPI - Multidisciplinary Digital Publishing Institute, Basel ; OAPEN FOUNDATION, The Hague

    Data Science (DS) is gaining significant importance in the decision process due to a mix of various areas, including Computer Science, Machine Learning, Math and Statistics, domain/business knowledge, software development, and traditional research.... more

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    Data Science (DS) is gaining significant importance in the decision process due to a mix of various areas, including Computer Science, Machine Learning, Math and Statistics, domain/business knowledge, software development, and traditional research. In the business field, DS's application allows using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data to support the decision process. After collecting the data, it is crucial to discover the knowledge. In this step, Knowledge Discovery (KD) tasks are used to create knowledge from structured and unstructured sources (e.g., text, data, and images). The output needs to be in a readable and interpretable format. It must represent knowledge in a manner that facilitates inferencing. KD is applied in several areas, such as education, health, accounting, energy, and public administration. This book includes fourteen excellent articles which discuss this trending topic and present innovative solutions to show the importance of Data Science and Knowledge Discovery to researchers, managers, industry, society, and other communities. The chapters address several topics like Data mining, Deep Learning, Data Visualization and Analytics, Semantic data, Geospatial and Spatio-Temporal Data, Data Augmentation and Text Mining.

     
    Export to reference management software   RIS file
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    Source: Union catalogues
    Contributor: Portela, Filipe (Herausgeber)
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9783036543154; 9783036543161
    Subjects: Information technology industries; Computer science
    Other subjects: crisis reporting; chatbots; journalists; news media; COVID-19; textbook research; digital humanities; digital infrastructures; data analysis; content base image retrieval; semantic information retrieval; deep features; multimedia document retrieval; data science; open government data; governance and social institutions; economic determinants of open data; geoinformation technology; fractal dimension; territorial road network; box-counting framework; script Python; ArcGIS; internet of things; LoRaWAN; ICT; The Things Network; ESP32 microcontroller; decision systems; rule based systems; databases; rough sets; prediction by partial matching; spatio-temporal; activity recognition; smart homes; artificial intelligence; automation; e-commerce; machine learning; big data; customer relationship management (CRM); distracted driving; driving behavior; driving operation area; data augmentation; feature extraction; authorship; text mining; attribution; neural networks; deep learning; forensic intelligence; dashboard; WebGIS; data analytics; SARS-CoV-2; Big Data; Web Intelligence; media analytics; social sciences; humanities; linked open data; adaptation process; interdisciplinary research; media criticism; classification; information systems; public health; data mining; ioCOVID19; n/a
    Scope: 1 Online-Ressource (254 p.)
  3. Strengthening the results chain
    synthesis of case studies of results-based management by providers
    Author: Zwart, Rosie
    Published: [2017]
    Publisher:  OECD Publishing, [Paris, France]

    This paper presents an analysis of evidence from seven case studies of results-based management by development co-operation providers. Analysis of themes from the case studies reveal six interrelated challenges which providers face in their efforts... more

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    This paper presents an analysis of evidence from seven case studies of results-based management by development co-operation providers. Analysis of themes from the case studies reveal six interrelated challenges which providers face in their efforts to manage for the results of development co-operation. The six challenges are: linking results to development goals, ensuring the purpose of results systems is well-defined, weighing up the benefits of aggregating and attributing results from standard indicators, enabling country ownership, using performance information alongside results information, and building and embedding a results culture. Providers continue to adopt a range of approaches to pursue a focus on results and there are many examples of good practice. The case studies suggest that in a complex development landscape some providers are prioritising the use of aggregated results information for domestic accountability, communication, and performance management over their use for learning and policy direction. In this context, the paper argues that in agency-wide results frameworks development co-operation results are often detached (or de-contextualised) from development results and discusses the implications of this, including the use of standard indicators to measure aggregated outputs. The paper uses case study evidence to discuss and suggest practical ways providers can build and maintain a strong results focus which enables analysis, insights and learning, and has achievement of development outcomes as its objective.

     
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    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Series: OECD development policy papers ; no. 7 (August 2017)
    Subjects: Results; results-based management; results frameworks; development co-operation; data; evidence-based; SDGs; Agenda 2030; standard indicators; aggregation; attribution; performance measurement; Development
    Scope: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  4. Data Science and Knowledge Discovery
    Contributor: Portela, Filipe (Herausgeber)
    Published: 2022
    Publisher:  MDPI - Multidisciplinary Digital Publishing Institute, Basel

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    Export to reference management software   RIS file
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    Source: Union catalogues
    Contributor: Portela, Filipe (Herausgeber)
    Language: 0|e
    Media type: Ebook
    Format: Online
    ISBN: 9783036543154
    Subjects: Information technology industries; Computer science
    Other subjects: crisis reporting; chatbots; journalists; news media; COVID-19; textbook research; digital humanities; digital infrastructures; data analysis; content base image retrieval; semantic information retrieval; deep features; multimedia document retrieval; data science; open government data; governance and social institutions; economic determinants of open data; geoinformation technology; fractal dimension; territorial road network; box-counting framework; script Python; ArcGIS; internet of things; LoRaWAN; ICT; The Things Network; ESP32 microcontroller; decision systems; rule based systems; databases; rough sets; prediction by partial matching; spatio-temporal; activity recognition; smart homes; artificial intelligence; automation; e-commerce; machine learning; big data; customer relationship management (CRM); distracted driving; driving behavior; driving operation area; data augmentation; feature extraction; authorship; text mining; attribution; neural networks; deep learning; forensic intelligence; dashboard; WebGIS; data analytics; SARS-CoV-2; Big Data; Web Intelligence; media analytics; social sciences; humanities; linked open data; adaptation process; interdisciplinary research; media criticism; classification; information systems; public health; data mining; ioCOVID19; n/a
    Scope: 1 electronic resource (254 pages)
  5. Strengthening the results chain
    synthesis of case studies of results-based management by providers
    Author: Zwart, Rosie
    Published: [2017]
    Publisher:  OECD Publishing, [Paris, France]

    This paper presents an analysis of evidence from seven case studies of results-based management by development co-operation providers. Analysis of themes from the case studies reveal six interrelated challenges which providers face in their efforts... more

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    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
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    Universität Potsdam, Universitätsbibliothek
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    This paper presents an analysis of evidence from seven case studies of results-based management by development co-operation providers. Analysis of themes from the case studies reveal six interrelated challenges which providers face in their efforts to manage for the results of development co-operation. The six challenges are: linking results to development goals, ensuring the purpose of results systems is well-defined, weighing up the benefits of aggregating and attributing results from standard indicators, enabling country ownership, using performance information alongside results information, and building and embedding a results culture. Providers continue to adopt a range of approaches to pursue a focus on results and there are many examples of good practice. The case studies suggest that in a complex development landscape some providers are prioritising the use of aggregated results information for domestic accountability, communication, and performance management over their use for learning and policy direction. In this context, the paper argues that in agency-wide results frameworks development co-operation results are often detached (or de-contextualised) from development results and discusses the implications of this, including the use of standard indicators to measure aggregated outputs. The paper uses case study evidence to discuss and suggest practical ways providers can build and maintain a strong results focus which enables analysis, insights and learning, and has achievement of development outcomes as its objective.

     
    Export to reference management software   RIS file
      BibTeX file
    Content information
    Volltext (lizenzpflichtig)
    Volltext (lizenzpflichtig)
    Source: Staatsbibliothek zu Berlin
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    Series: OECD development policy papers ; no. 7 (August 2017)
    Subjects: Results; results-based management; results frameworks; development co-operation; data; evidence-based; SDGs; Agenda 2030; standard indicators; aggregation; attribution; performance measurement; Development
    Scope: 1 Online-Ressource (circa 32 Seiten), Illustrationen
  6. Self-regulated Learning, Locus of Control, and Reading Comprehension
    A new window to teach reading comprehension
    Author: Nejabati, Najva
    Published: 2018
    Publisher:  LAP LAMBERT Academic Publishing, Saarbrücken

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    Source: Union catalogues
    Language: English
    Media type: Ebook
    Format: Online
    ISBN: 9783659641671; 3659641677
    Other identifier:
    9783659641671
    Edition: 1. Auflage
    Other subjects: (Produktform)Electronic book text; reading comprehension; attribution; locus of control; EFL Learners; Self-regualated learning; (VLB-WN)1564: Englische Sprachwissenschaft, Literaturwissenschaft
    Scope: Online-Ressource, 188 Seiten
    Notes:

    Lizenzpflichtig. - Vom Verlag als Druckwerk on demand und/oder als E-Book angeboten
  7. The affordability of the Sustainable Development Goals
    a myth or reality?
    Author: Chongcharoentanawat, Patima; Haile, Kaleab K.; Kleine Deters, Bart; Kool, Tamara Antoinette; Osei Kwadwo, Victor
    Published: 2016
    Publisher:  Maastricht Economic and Social Research Institute on Innovation and Technology (UNU‐MERIT), Maastricht, the Netherlands

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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Series: Working paper series / United Nations University, UNU-MERIT ; #2016, 027
    Subjects: Sustainable Development Goals; Millennium Development Goals; attribution; monitoring; fiscal stress; fiscal capacity; health; education; poverty; Cambodia; El Salvador; Ethiopia; Indonesia; Senegal
    Scope: 1 Online-Ressource (circa 34 Seiten), Illustrationen
  8. Mistaking noise for bias
    victimhood and Hutu-Tutsi reconciliation in East Africa
    Author: Blouin, Arthur; Mukand, Sharun W.
    Published: July 2022
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    The difficulty in resurrecting inter-ethnic cooperation in the aftermath of violence and genocide is one of the biggest challenges facing post-conflict societies. Using experimental data from post-genocide Rwanda and Burundi, this paper shows that an... more

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    The difficulty in resurrecting inter-ethnic cooperation in the aftermath of violence and genocide is one of the biggest challenges facing post-conflict societies. Using experimental data from post-genocide Rwanda and Burundi, this paper shows that an unwarranted tendency to blame others for negative outcomes is a behavioural barrier that makes reconciliation difficult. We show that individuals systematically (and mistakenly) blame accidental negative shocks (noise) to the deliberate intent of individuals (bias). This "victimhood bias" wherein individuals ascribe noise to bias is much larger for (a) individuals for whom ethnic identity is salient; (b) for those who have had greater exposure to inter-ethnic violence. Further, we observe that both inter-ethnic contact and economic development are associated with a decline in this victimhood bias. Finally, those with a lower victimhood bias are more likely to behave cooperatively in inter-ethnic rela-tionships. Our results suggest that insurance agreements that limit negative shocks and reduce noise, can encourage reconciliation by mitigating feelings of victimhood.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/263784
    Series: CESifo working paper ; no. 9854 (2022)
    Subjects: noise; bias; victim; conflict; reconciliation; attribution
    Scope: 1 Online-Ressource (circa 38 Seiten), Illustrationen
  9. Social inequalities in climate change-attributed impacts of hurricane harvey
    Author: Smiley, Kevin T.; Noy, Ilan; Wehner, Michael; Frame, Dave; Sampson, C. Michael; Wing, Oliver E.
    Published: November 2021
    Publisher:  CESifo, Center for Economic Studies & Ifo Institute, Munich, Germany

    Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But no research to date investigates if, and to what extent, there are social inequalities in current climate change-attributed flood... more

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    Climate change is already increasing the severity of extreme weather events such as with rainfall during hurricanes. But no research to date investigates if, and to what extent, there are social inequalities in current climate change-attributed flood impacts. Here, we use climate change attribution science paired with hydrological flood models to estimate climate change-attributed flood depths and damages during Hurricane Harvey in Harris County, Texas. We then combine this information with detailed land-parcel and census tract socio-economic data to describe the socio-spatial characteristics of these climate change-induced impacts. Our findings show that 30 to 50% of the flooded properties would not have flooded without climate change. These climate change-attributed impacts were particularly felt in Latinx neighborhoods, and especially so in Latinx neighborhoods that were low-income and among those located outside of FEMA's 100-year floodplain (and therefore less likely to be insured). An important implication is the need to focus on pressing climate justice challenges that not only concern future climate change-induced risks, but are already affecting vulnerable populations disproportionately now.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
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    hdl: 10419/248957
    Series: CESifo working paper ; no. 9412 (2021)
    Subjects: Hurricane Harvey; attribution; climate change; poverty; flood insurance
    Scope: 1 Online-Ressource (circa 31 Seiten), Illustrationen
  10. Illuminating the e-commerce marketing mix
    framework development, marketing tool effects on online patronage, and impact of brand equity
    Author: Klink, Benjamin
    Published: [2023]

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