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Record Nr. |
UNINA9910809953503321 |
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Titolo |
Access to and effects of social protection on workers living with HIV and their households : an analytical report / / International Labour Organization |
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Pubbl/distr/stampa |
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Geneva, Switzerland : , : International Labour Organization, , 2014 |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (134 p.) |
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Disciplina |
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Soggetti |
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Health |
Physical fitness |
Self-care, Health |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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FOREWORD; ACKNOWLEDGEMENTS; LIST OF ABBREVIATIONS; TABLE OF CONTENTS; LIST OF BOXES; LIST OF TABLES; LIST OF FIGURES; EXECUTIVE SUMMARY; INTRODUCTION; BACKGROUND TO THE STUDY AND METHODOLOGY; BACKGROUND TO THE STUDY; Box 1: Millennium Development Goal (MDG): Goal 1; OBJECTIVES OF THE STUDY; METHODOLOGICAL APPROACH; COUNTRIES AND COUNTRY CONTEXT; COUNTRY-LEVEL RESEARCH IMPLEMENTATION; Table 1: Selected statistics by country, 2012; Table 2: Research design and methods; Table 3: Sample size for quantitative and qualitative components; POPULATION CHARACTERISTICS |
Table 4: Study population by sex, gender identity, sexual orientation and othersTOOLS AND INSTRUMENTS; ANALYSIS AND REPORTING; LIMITATIONS AND CONSTRAINTS; OVERVIEW OF KEY FINDINGS; STUDY POPULATION PROFILE; Figure 1: Top sources of discrimination in Rwanda and Ukraine in previous 12 months; Table 5: Type of employment of study respondents in Indonesia; Figure 2: Type of employment by sex and sexual orientations among respondents; Table 6: Reasons for changing job by type of employment and sex in Ukraine; AVAILABILITY AND TYPE OF SOCIAL PROTECTION PROGRAMMES |
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Table 7: Types of social protection programmes for the poor in IndonesiaFigure 3: Structure of social budget expenditures in Ukraine in 2011; ACCESS TO SOCIAL PROTECTION PROGRAMMES; Figure 4: Social Protection System in Guatemala; Figure 5: Estimated Access to Social Protection / Social Assistance (excludes health); Box 2: Sources of social protection in Ukraine and their access; Table 8: Access to social protection by type of programme and sex in Rwanda; Figure 6: PLHIV coverage by type of health services; Table 9: Access to health insurance in Indonesia; BARRIERS TO SOCIAL PROTECTION ACCESS |
Table 10: Livelihood support in RwandaTable 11: Prices of antiretroviral therapy medicines in six Central American countries; Figure 7: Barriers to Social Protection for People Living with HIV; EFFECTS OF ACCESS TO SOCIAL PROTECTION; Figure 8: Access to Medical Services and Art; Table 12: Respondents who received ART, treatment for opportunistic infections and have livedfor more than 9 Years with HIV by country; Figure 9: Percentage of respondents receiving antiretroviral therapy - 95% reported having access; Table 13: Summary of effects of social protection on key indicators, by country |
CONCLUSIONSRECOMMENDATIONS; KEY SOURCES; REFERENCES; ANNEXES; ANNEX 1: EXECUTIVE SUMMARY OF GLOBAL LITERATURE REVIEW; ANNEX 2: AN OVERVIEW OF RESEARCH METHODOLOGICAL; ANNEX 3: EXECUTIVE SUMMARY - GUATEMALA COUNTRY RESEARCH; ANNEX 4: EXECUTIVE SUMMARY - INDONESIA COUNTRY RESEARCH; ANNEX 5: EXECUTIVE SUMMARY - RWANDA COUNTRY RESEARCH; ANNEX 6: EXECUTIVE SUMMARY - UKRAINE COUNTRY RESEARCH |
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Sommario/riassunto |
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This report which is the result of a process that included a global literature review, the development of a research methodology guide through consultation with experts, and research in four countries: Guatemala, Indonesia, Rwanda and Ukraine. It highlights the challenges faced by workers living with HIV and their households in accessing social protection programmes, examines the effects of such programmes on their lives and makes evidence-based recommendations. |
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2. |
Record Nr. |
UNINA9910337839003321 |
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Autore |
Meng Lei |
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Titolo |
Adaptive Resonance Theory in Social Media Data Clustering : Roles, Methodologies, and Applications / / by Lei Meng, Ah-Hwee Tan, Donald C. Wunsch II |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (200 pages) |
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Collana |
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Advanced Information and Knowledge Processing, , 1610-3947 |
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Disciplina |
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Soggetti |
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Data mining |
Algorithms |
Cognitive psychology |
Pattern perception |
Data Mining and Knowledge Discovery |
Algorithm Analysis and Problem Complexity |
Cognitive Psychology |
Pattern Recognition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Part 1: Theories -- Introduction -- Clustering and Extensions in the Social Media Domain -- Adaptive Resonance Theory (ART) for Social Media Analytics -- Part II: Applications -- Personalized Web Image Organization -- Socially-Enriched Multimedia Data Co-Clustering -- Community Discovery in Heterogeneous Social Networks -- Online Multimodal Co-Indexing and Retrieval of Social Media Data -- Concluding Remarks. |
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Sommario/riassunto |
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Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data: Basic knowledge (data & challenges) on social media analytics Clustering as a fundamental technique for unsupervised knowledge discovery and data mining A class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step |
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practices of developing unsupervised machine learning algorithms for real-world applications in social media domain Adaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction. It presents initiatives on the mathematical demonstration of ART’s learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks. Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you: How to process big streams of multimedia data? How to analyze social networks with heterogeneous data? How to understand a user’s interests by learning from online posts and behaviors? How to create a personalized search engine by automatically indexing and searching multimodal information resources? |
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