Poverty and social impact analysis by the IMF [[electronic resource] ] : review of methodology and selected evidence / / Robert Gillingham, editor

• Record Nr.: UNINA9910455118203321
• Pubbl/distr/stampa: Washington, D.C., : International Monetary Fund, c2008
• ISBN: 1-4552-7611-1; 1-4527-9574-6; 1-283-53379-0; 9786613846242; 1-4519-4924-3
• Descrizione fisica: 1 online resource (270 p.)
• Altri autori (Persone): GillinghamRobert
• Disciplina: 305.5/69091724
• Soggetti: Economic assistance - Social aspects; Poverty - Social aspects; Electronic books.; Developing countries Social conditions; Developing countries Economic conditions; Developing countries Economic policy
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references (p. 115-132).
• Nota di contenuto: Introduction -- Review of macro-micro approaches for evaluating the distributional impacts of macroeconomic reforms / [Moataz El-Said] -- Distributional impacts of indirect tax and public pricing reforms: a review of methods and empirical evidence / [David Coady] -- Analyzing the impact of trade liberalization and devaluation on poverty / [Alejandro Simone] -- Distributional impact of agricultural sector reforms in Africa: a review of past experience / [David Newhouse].
• Sommario/riassunto: The Poverty Reduction and Growth Facility (PRGF) is used by the IMF to provide support for countries' implementation of their poverty reduction and growth strategies. A key requirement in the design of PRGF programs is understanding the effects of reform program measures on vulnerable groups-particularly the poor-and how to ; devise measures to mitigate any negative effects. Poverty and social impact analysis (PSIA) is a critical instrument for pursuing this goal. The IMF has therefore established a small group of staff economists to facilitate the integration of PSIA into PRGF-supported prog

Holding the shop together : German industrial relations in the postwar era / / Stephen J. Silvia

• Record Nr.: UNINA9910814811303321
• Autore: Silvia Stephen J
• Pubbl/distr/stampa: Ithaca, New York ; ; New York : , : Cornell University Press, , 2013; ©2013
• ISBN: 0-8014-6965-1; 1-322-52330-4; 0-8014-6966-X
• Descrizione fisica: 1 online resource (297 p.)
• Disciplina: 331.80943/09045
• Soggetti: Industrial relations - Germany; Labor unions - Germany; Labor policy - Germany
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Front matter -- Contents -- Preface -- Abbreviations -- Introduction -- 1. The Enduring Resilience of the Law and the State in German Industrial Relations -- 2. Codetermination: Pillar of Postwar German Industrial Relations -- 3. A Quantitative Analysis of Membership Developments in the Postwar German Trade Union Movement: Milieu Matters -- 4. Trade Unions in Germany: The Two Postwar Movements -- 5. Employers Associations: From Regaining Credibility to Retaining Relevance -- Conclusion: Integrating the Pieces and Looking toward the Future -- Notes -- Index
• Sommario/riassunto: Since the onset of the Great Recession, Germany's economy has been praised for its superior performance, which has been reminiscent of the "economic miracle" of the 1950's and 1960's. Such acclaim is surprising ; because Germany's economic institutions were widely dismissed as faulty just a decade ago. In Holding the Shop Together, Stephen J. Silvia examines the oscillations of the German economy across the entire postwar period through one of its most important components: the industrial relations system. As Silvia shows in this wide-ranging and deeply informed account, the industrial relations system is strongest where the German economy is strongest and is responsible for many of the distinctive features of postwar German capitalism. It extends into the boardrooms, workplaces and government to a degree that is unimaginable in most other countries. Trends in German industrial relations, moreover, influence developments in the broader German economy and, frequently, industrial relations practice abroad. All these aspects make the German industrial relations regime an ideal focal point for developing a deeper understanding of the German economy as a whole. Silvia begins by presenting the framework of the German industrial relations system-labor laws and the role of the state-and then analyzes its principal actors: trade unions and employers' associations. He finds the framework sound but the actors in crisis because of membership losses. Silvia analyzes the reasons behind the losses and the innovative strategies German labor and management have developed in their efforts to reverse them. He concludes with a comprehensive picture and then considers the future of German industrial relations.

Neural Information Processing : 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8–12, 2021, Proceedings, Part I / / edited by Teddy Mantoro, Minho Lee, Media Anugerah Ayu, Kok Wai Wong, Achmad Nizar Hidayanto

• Record Nr.: UNINA9910512185403321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• ISBN: 3-030-92185-9
• Edizione: [1st ed. 2021.]
• Descrizione fisica: 1 online resource (719 pages)
• Collana: Theoretical Computer Science and General Issues, , 2512-2029 ; ; 13108
• Disciplina: 006.32
• Soggetti: Pattern recognition systems; Machine learning; Computer vision; Computer engineering; Computer networks; Education - Data processing; Automated Pattern Recognition; Machine Learning; Computer Vision; Computer Engineering and Networks; Computers and Education
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Theory and Algorithms -- Metric Learning Based Vision Transformer for Product Matching -- Stochastic Recurrent Neural Network for Multistep Time Series Forecasting -- Speaker Verification with Disentangled Self-Attention -- Multi Modal Normalization -- A Focally Discriminative Loss for Unsupervised Domain Adaptation -- Automatic Drum Transcription with Label Augmentation using Convolutional Neural Networks -- Adaptive Curriculum Learning for Semi-Supervised Segmentation of 3D CT-Scans -- Genetic Algorithm and Distinctiveness Pruning in the Shallow Networks for VehicleX -- Stack Multiple Shallow Autoencoders ; into A Strong One: A New Reconstruction-based Method to Detect Anomaly -- Learning Discriminative Representation with Attention and Diversity for Large-scale Face Recognition -- Multi-task Perceptual Occlusion Face Detection with Semantic Attention Network -- RAIDU-Net: Image Inpainting via Residual Attention Fusion and Gated Information Distillation -- Sentence Rewriting with Few-Shot Learningfor Document-Level Event Coreference Resolution -- A Novel Metric Learning Framework for Semi-supervised Domain Adaptation -- Generating Adversarial Examples by Distributed Upsampling -- CPSAM: Channel and Position Squeeze Attention Module -- A Multi-Channel Graph Attention Network for Chinese NER -- GSNESR: A Global Social Network Embedding Approach for Social Recommendation -- Classification Models for Medical Data with Interpretative Rules -- Contrastive Goal Grouping for Policy Generalization in Goal-Conditioned Reinforcement Learning -- Global Fusion Capsule Network with Pairwise-Relation Attention Graph Routing -- MA-GAN: A Method Based on Generative Adversarial Network for Calligraphy Morphing -- One-Stage Open Set Object Detection with Prototype Learning -- Aesthetic-aware Recommender System for Online Fashion Products -- DAFD: Domain Adaptation Framework for Fake News Detection -- Document Image Classification Method based on Graph Convolutional Network -- Continual Learning of 3D Point Cloud Generators -- Attention-Based 3D ResNet for Detection of Alzheimer's Disease Process -- Generation of a Large-Scale Line Image Dataset with Ground Truth Texts from Page-Level Autograph Documents -- DAP-BERT: Differentiable Architecture Pruning of BERT -- Trash Detection On Water Channels -- Tri-Transformer Hawkes Process: Three Heads are better than one -- PhenoDeep: A deep Learning-based approach for detecting reproductive organs from digitized herbarium specimen images -- Document-level Event Factuality Identification using Negation and Speculation Scope -- Dynamic Network Embedding by Time-Relaxed Temporal Random Walk -- Dual-band Maritime Ship Classification based on Multi-layer Convolutional Features and Bayesian Decision -- Context-Based Anomaly Detection via Spatial Attributed Graphs in Human Monitoring -- Domain-Adaptation Person Re-Identification via Style Translation and Clustering -- Multimodal Named Entity Recognition Via Co-attention-based Method with Dynamic Visual Concept Expansion -- Ego Networks -- Cross-modal based Person Re-Identification via Channel Exchange and adversarial Learning -- SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs -- Deep Neuroevolution: Training Neural Networks using a Matrix-free Evolution Strategy -- Weighted P-Rank: A Weighted Article Ranking Algorithm Based on a Heterogeneous Scholarly Network -- Clustering Friendly Dictionary Learning -- Understanding Test-Time Augmentation -- SphereCF: Sphere Embedding for Collaborative Filtering -- Concordant Contrastive Learning for Semi-supervised Node Classification on Graph -- Improving Shallow Neural Networks via Local and Global Normalization -- Underwater Acoustic Target Recognition with Fusion Feature -- Evaluating Data Characterization Measures for Clustering Problems in Meta-learning -- ShallowNet: An Efficient Lightweight Text Detection Network Based on Instance Count-aware Supervision Information -- Image Periodization for Convolutional NeuralNetworks -- BCN-GCN: A Novel Brain Connectivity Network Classification Method via Graph Convolution Neural Network for Alzheimer's Disease -- Triplet Mapping for Continuously Knowledge Distillation -- A Prediction-Augmented AutoEncoder for Multivariate Time Series Anomaly Detection.
• Sommario/riassunto: The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 ; constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.