The third part of the collection of poems on affairs of state [[electronic resource] ] : containing Esquire Marvel's Further instructions to a painter, and the late Lord Rochester's Farewel

• Record Nr.: UNISA996392673903316
• Pubbl/distr/stampa: London, : [s.n.], 1689
• Descrizione fisica: [2], 30 p
• Altri autori (Persone): MarvellAndrew <1621-1678.>
• Soggetti: Political poetry, English; Political satire, English; Great Britain History Restoration, 1660-1688 Poetry
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Contributions by Marvell and others.; Reproduction of original in Huntington Library.
• Sommario/riassunto: eebo-0113

Codice delle leggi tributarie : terzo fascicolo di aggiornamento con i provvedimenti pubblicati fino al 31 agosto 1953 / A. D. Giannini, S. Scoca, G. Buzzetti

• Record Nr.: UNINA9910907900803321
• Autore: Italia
• Pubbl/distr/stampa: Milano, : Giuffre, 1953
• Edizione: [2. ed.]
• Descrizione fisica: 327 p. ; 17 cm
• Collana: Collezione legislativa
• Locazione: DEC
• Collocazione: DPR 2 138.4
• Lingua di pubblicazione: Italiano
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Artificial Intelligence and the Rule of Law : The Age of Legal Tech and Digital Governance in a Fractured Digital World / / edited by Armando Aliu

• Record Nr.: UNINA9911035042603321
• Autore: Aliu Armando
• Pubbl/distr/stampa: Cham : , : Springer Nature Switzerland : , : Imprint : Palgrave Macmillan, , 2025
• ISBN: 9783031973895; 9783031973888
• Edizione: [1st ed. 2025.]
• Descrizione fisica: 1 online resource (348 pages)
• Collana: Law and Criminology Series
• Disciplina: 303.483
• Soggetti: Science - Social aspects; Artificial intelligence; Political sociology; Technology - Moral and ethical aspects; International law; Science and Technology Studies; Artificial Intelligence; Political Sociology; Ethics of Technology; Sociology of Science; Public International Law
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Chapter 1. Introduction: AI Interdisciplinarity and the Rule of Law – The Age of Legal Tech and Digital Governance Shaped by Digital Ethics, Responsible AI, and AI4People (Armando Aliu & Dorian Aliu) -- Chapter 2. The Role of the Arts and Humanities in Thinking about AI (John Tasioulas) -- Chapter 3. The Trio of Computational Jurisprudence: History, Present, and Future (Surong Zhu & Guoyang Ma) -- Chapter 4. Contribution to an Algorithm for the Rule of Law (Mohamed Ben Achour) -- Chapter 5. From Procedural Fetishism to Substantive Due Process in AI Governance and Digital Constitutionalism (Monika ; Zalnieriute) -- Chapter 6. The Right to Be Forgotten Meets Machine Learning: Evaluating the Legal Feasibility of Unlearning Methods (Liane Rose Colonna & Tobıas Oechterıng) -- Chapter 7. Towards a General Principle of Vulnerability: Is Private Law Ready for the Digital Age? (Begoña Gonzalez Otero) -- Chapter 8. International Law between Enhanced Anthropocentrism and Post-Anthropocentrism: The Need for an International Treaty on Bio-Technological Ethics (Themistoklis Tzimas) -- Chapter 9. The EU AI Act and the Future of AI Governance: Implications for U.S. Firms and Policymakers (David Krause) -- Chapter 10. Conclusion: Future of AI and the Rule of Law – Ethics and Regulatory Framework in Legal Tech and Digital Governance (Armando Aliu, Rūta Liepiņa, Sofia Klymchuk, Ikran Abdirahman, Beatrice Panattoni, Josh Lee Kok Thong & Hellen Van Der Kroef).
• Sommario/riassunto: “Artificial Intelligence and the Rule of Law is a timely, richly textured guide to the fast-converging worlds of legal tech, governance, and ethics. The book integrates doctrinal analysis with empirical benchmarks and even includes executable code. The book is a resource for courts, regulators, and builders alike. Each chapter offers a clear entry-point, whether you are tracking the EU AI Act, designing compliance tools, or re-thinking judicial accountability in the LLM era. It is a valuable addition to the AI-and-law shelf.” - Kevin P. Lee, Intel Chair, Social Justice and Racial Equity Professor, Faculty of Law, North Carolina Central University, Durham, North Carolina, United States “Artificial intelligence holds great promise to improve access to justice and strengthen the rule of law. At the same time, technology challenges the traditional ways of making, applying and understanding the law. This book investigates both chances and risks and offers novel and thoughtful solutions. I very much recommend engaging with it.” - Felix Steffek, Professor of Law and Deputy Faculty Chair, Faculty of Law, University of Cambridge, Cambridge, UK; Global Distinguished Professor of Law, University of Notre Dame, Notre Dame, Indiana, United States This book explores the most pressing challenges in AI technologies and practices and digitally transformed fracturing world that is shaped by digital governance and digital ethics. It draws attention to unraveling the legal labyrinth of regulatory frameworks on AI and the rule of law, and how these AI regulations intervene in the digital transformation of LegalTech across the world. The book scrutinizes the issues, risks, and opportunities of AI to uphold the rule of law, promote human rights, improve access to justice, and protect people’s rights and fundamental freedoms. The book sheds light on the impact of AI use on the development of the rule of law and digital transformation in legal systems. Armando Aliu is Assistant Professor at the University of Wrocław and Jagiellonian University in Poland. He is a member of the Association for the Advancement of Artificial Intelligence (AAAI), Max Planck Alumni Association, and Academic Council on the United Nations System (ACUNS).

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

• Record Nr.: UNINA9910512188503321
• Pubbl/distr/stampa: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021
• ISBN: 3-030-92238-3
• Edizione: [1st ed. 2021.]
• Descrizione fisica: 1 online resource (724 pages)
• Collana: Theoretical Computer Science and General Issues, , 2512-2029 ; ; 13110
• Disciplina: 006.32
• Soggetti: Pattern recognition systems; Machine learning; Education - Data processing; Computer engineering; Computer networks; Social sciences - Data processing; Automated Pattern Recognition; Machine Learning; Computers and Education; Computer Engineering and Networks; Computer Application in Social and Behavioral Sciences
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Cognitive Neurosciences -- A Novel Binary BCI Systems Based on Non-oddball Auditory and Visual Paradigms -- A Just-In-Time Compilation Approach for Neural Dynamics Simulation -- STCN-GR: Spatial-Temporal Convolutional Networks for Surface-Electromyography-Based Gesture Recognition -- Gradient descent learning algorithm based on spike selection mechanism for multilayer spiking neural networks -- Learning to Coordinate via Multiple Graph Neural Networks -- A Reinforcement Learning Approach for Abductive Natural Language Generation -- DFFCN: Dual Flow Fusion Convolutional Network for ; Micro Expression Recognition -- AUPro: Multi-label Facial Action Unit Proposal Generation for Sequence-level Analysis -- Deep kernelized network for fine-grained recognition -- Semantic Perception Swarm Policy with Deep Reinforcement Learning -- Reliable, Robust, and Secure Machine Learning Algorithms Open-Set Recognition with Dual Probability Learning -- How Much Do Synthetic Datasets Matter In Handwritten Text Recognition -- PCMO: Partial Classification from CNN-Based Model Outputs -- Multi-branch Fusion Fully Convolutional Network for Person Re-Identification -- Fast Organization of Objects Spatial Positions in Manipulator Space from Single RGB-D Camera -- EvoBA: An Evolution Strategy as a Strong Baseline for Black-Box Adversarial Attacks -- A Novel Oversampling Technique for Imbalanced Learning Based on SMOTE and Genetic Algorithm -- Dy-Drl2Op: Learning Heuristics for TSP on the Dynamic Graph via Deep Reinforcement Learning -- Multi-label classification of hyperspectral images based on label-specific feature fusion -- A Novel Multi-Scale Key-Point Detector Using Residual Dense Block and Coordinate Attention -- Alleviating Catastrophic Interference in Online Learning via Varying Scale of Backward Queried Data -- Construction and Reasoning for Interval-Valued EBRB Systems -- Theory and Applications of Natural Computing Paradigms -- Brain-mimetic Kernel: A Kernel Constructed from Human fMRI Signals Enabling aBrain-mimetic Visual Recognition Algorithm -- Predominant Sense Acquisition with a Neural Random Walk Model -- Processing-response dependence on the on-chip readout positions in spin-wave reservoir computing -- Advances in deep and shallow machine learning algorithms for biomedical data and imaging -- A Multi-Task Learning Scheme for Motor Imagery Signal Classification -- An End-to-End Hemisphere Discrepancy Network for Subject-Independent Motor Imagery Classification -- Multi-domain Abdomen Image Alignment Based on Joint Network of Registration and Synthesis -- Coordinate Attention Residual Deformable U-Net for Vessel Segmentation -- Gated Channel Attention Network for Cataract Classification on AS-OCT Image -- Overcoming Data Scarcity for Coronary Vessel Segmentation Through Self-Supervised Pre-Training -- Self-Attention Long-Term Dependency Modelling in Electroencephalography Sleep Stage Prediction -- ReCal-Net: Joint Region-Channel-Wise Calibrated Network for Semantic Segmentation in Cataract Surgery Videos -- Enhancing Dermoscopic Features Classification in Images Using Invariant Dataset Augmentation and Convolutional Neural Networks -- Ensembles of Randomized Neural Networks for Pattern-based Time Series Forecasting -- Grouped Echo State Network with Late Fusion for Speech Emotion Recognition -- Applications -- MPANet: Multi-level Progressive Aggregation Network for Crowd Counting -- AFLLC: A Novel Active Contour Model based on Adaptive Fractional Order Differentiation and Local Linearly Constrained Bias Field -- DA-GCN: A Dependency-Aware Graph Convolutional Network for Emotion Recognition in Conversations -- Semi-Supervised Learning with Conditional GANs for Blind Generated Image Quality Assessment -- Uncertainty-Aware Domain Adaptation for Action Recognition -- Free-Form Image Inpainting with Separable Gate Encoder-decoder Network -- BERTDAN: Question-Answer Dual Attention Fusion Networks With Pre-trained Models for Answer Selection -- Rethinking the Effectiveness of Selective Attention in Neural Networks -- An Attention Method to Introduce Prior Knowledge in Dialogue State Tracking -- Effect of Input Noise Dimension in GANs -- Wiper Arm Recognition using YOLOv4 -- Context Aware Joint Modeling of Domain Classification, Intent Detection and Slot Filling with Zero-shot Intent Detection Approach -- Constrained Generative Model ; for EEG Signals Generation -- Top-Rank Learning Robust to Outliers -- Novel GAN Inversion Model with Latent Space Constraints for Face Reconstruction -- Edge Guided Attention Based Densely Connected Network for Single Image Super-Resolution -- An Agent-Based Market Simulator for Back-testing Deep Reinforcement Learning Based Trade Execution Strategies -- Looking beyond the haze: A Pyramid Fusion Approach -- DGCN-rs: a Dilated Graph Convolutional Networks Jointly Modelling Relation and Semantic for Multi-Event Forecasting -- Training Graph Convolutional Neural Network against Label Noise -- An LSTM-based Plagiarism Detection via Attention Mechanism anda Population-based Approach for Pre-Training Parameters with imbalanced Classes.
• 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.