Democratic Commitments : Legislatures and International Cooperation / / Lisa L. Martin

• Record Nr.: UNINA9910449950603321
• Autore: Martin Lisa L.
• Pubbl/distr/stampa: Princeton, NJ : , : Princeton University Press, , [2000]; ©2000
• ISBN: 1-282-76710-0; 9786612767104; 1-4008-2370-6
• Edizione: [Course Book]
• Descrizione fisica: 1 online resource (234 p.)
• Disciplina: 328.73/0746
• Soggetti: International cooperation; Legislative bodies; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di contenuto: Front matter -- Contents -- Preface -- CHAPTER 1. Introduction -- CHAPTER 2. Theoretical Framework: Legislatures, Executives, and Commitment -- CHAPTER 3. Institutions and Influence: Executive Agreements and Treaties -- CHAPTER 4. Economic Sanctions: Domestic Conflict of Interest and International Cooperation -- CHAPTER 5. U.S. Food-Aid Policy: The Politics of Delegation and Linkage -- CHAPTER 6. National Parliaments and European Integration: Institutional Choice in EU Member States -- CHAPTER 7. Implementing the EU's Internal Market: The Influence of National Parliaments -- CHAPTER 8. Conclusion -- References -- Index
• Sommario/riassunto: From the refusal of the U.S. Congress to approve fast-track trade authority and certain foreign aid packages to the obstacles placed by Western European parliaments in the path of economic integration, legislatures often interfere with national leaders' efforts to reach and implement predictable international agreements. This seems to give an advantage to dictators, who can bluff with confidence and make decisions without consultation, and many assume that even democratic governments would do better to minimize political dissent and speak ; foreign policy from a single mouth. In this thoughtful, empirically grounded challenge to the assumption that messy domestic politics undermine democracies' ability to conduct international relations, Lisa Martin argues that legislatures--and particularly the apparently problematic openness of their proceedings--actually serve foreign policy well by giving credibility to the international commitments that are made. Examining the American cases of economic sanctions, the use of executive agreements versus treaties, and food assistance, in addition to the establishment of the European Union, Martin concludes that--if institutionalized--even rancorous domestic conversations between executives and legislatures augment rather than impede states' international dealings. Such interactions strengthen and legitimize states' bargaining positions and international commitments, increasing their capacity to realize international cooperation. By expanding our comprehension of how domestic politics affect international dialogue, this work is a major advance in the field of international relations and critical reading for those who study or forge foreign policy.

Neural information processing : 28th International Conference, ICONIP 2021, Sanur, Bali, Indonesia, December 8-12, 2021, Proceedings, Part IV. / / Teddy Mantoro [and four others], editors

• Record Nr.: UNISA996464525103316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2021]; 2021
• ISBN: 3-030-92273-1
• Edizione: [1st ed. 2021.]
• Descrizione fisica: 1 online resource (718 pages)
• Collana: Theoretical Computer Science and General Issues, , 2512-2029 ; ; 13111
• Disciplina: 006.32
• Soggetti: Neural networks (Computer science)
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Applications -- Deep Supervised Hashing By Classification For Image ; Retrieval -- Towards Human-level Performance in Solving Double Dummy Bridge Problem -- Coarse-to-Fine Visual Place Recognition -- BFConv: Improving Convolutional Neural Networks with Butterfly Convolution -- Integrating Rich Utterance Features for Emotion Recognition in Multi-party Conversations -- Vehicle Image Generation Going Well with the Surroundings -- Scale Invariant Domain Generalization Image Recapture Detection -- Tile2Vec with Predicting Noise for Land Cover Classification -- A Joint Representation Learning Approach for Social Media Tag Recommendation -- Identity-based Data Augmentation via Progressive Sampling for One-Shot Person Re-identification -- Feature Fusion Learning Based on LSTM and CNN Networks for Trend Analysis of Limit Order Books -- WikiFlash: Generating Flashcards from Wikipedia Articles -- Video Face Recognition with Audio-Visual Aggregation Network -- WaveFuse: A Unified Unsupervised Framework for Image Fusion with Discrete Wavelet Transform -- Manipulation-invariant Fingerprints for Cross-dataset Deepfake Detection -- Low-resource Neural Machine Translation Using Fast Meta-Learning method -- Efficient, Low-Cost, Real-Time Video Super-Resolution Network -- On the Unreasonable Effectiveness of Centroids in Image Retrieval -- Few-shot Classification with Multi-task Self-supervised Learning -- Self-Supervised Compressed Video Action Recognition via Temporal-Consistent Sampling -- Stack-VAE network for Zero-Shot Learning -- TRUFM: a Transformer-guided Framework for Fine-grained Urban Flow Inference -- Saliency Detection Framework Based on Deep Enhanced Attention Network -- SynthTriplet GAN: Synthetic Query Expansion for Multimodal Retrieval -- SS-CCN: Scale Self-guided Crowd Counting Network -- QS-Hyper: A Quality-Sensitive Hyper Network for the No-Reference Image Quality Assessment -- An Efficient Manifold Density Estimator for All Recommendation Systems -- Cleora: A Simple, Strong and Scalable Graph Embedding Scheme -- STA3DCNN: Spatial-temporal Attention 3D Convolutional Neural Network for Citywide Crowd Flow Prediction -- Learning Pre-Grasp Pushing Manipulation of Wide and Flat Objects using Binary Masks -- Multi-DIP: A General Framework For Unsupervised Multi-degraded Image Restoration -- Multi-Attention Network for Arbitrary Style Transfer -- Image Brightness Adjustment with Unpaired Training -- Self-Supervised Image-to-Text and Text-to-Image Synthesis -- TextCut: A Multi-region Replacement Data Augmentation Approach for Text Imbalance Classification -- A Multi-task Model for Sentiment aided Cyberbullying Detection in Code-Mixed Indian Languages -- A Transformer-based Model for Low-resource Event Detection -- Malicious Domain Detection on Imbalanced Data with Deep Reinforcement Learning -- Designing and Searching for Lightweight Monocular Depth Network -- Improving Question Answering over Knowledge Graphs Using Graph Summarization -- Multi-Stage Hybrid Attentive Networks for Knowledge-Driven Stock Movement Prediction -- End-to-End Edge Detection via Improved Transformer Model -- Isn’t it ironic, don’t you think -- Neural Local and Global Contexts Learning for Word Sense Disambiguation -- Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification -- Paraphrase Identification with Neural Elaboration Relation Learning -- Hybrid DE-MLP-based Modeling Technique for Prediction of Alloying Element Proportions and Process Parameters -- A Mutual Information-based Disentanglement Framework for Cross-Modal Retrieval -- AGRP:A Fused Aspect-Graph Neural Network for Rating Prediction -- Classmates Enhanced Diversity-self-attention Network for Dropout Prediction in MOOCs -- A Hierarchical Graph-based Neural Network for ; Malware Classification -- A Visual Feature Detection Algorithm Inspired by Spatio-temporal Properties of Visual Neurons -- Knowledge Distillation Method for Surface Defect Detection -- Adaptive Selection of Classifiers for Person Recognition by Iris Pattern and Periocular Image -- Multi-Perspective Interactive Model for Chinese Sentence Semantic Matching -- An Effective Implicit Multi-Interest Interaction Network for Recommendation.
• 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.