The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies analysed using R.Is accessible to anyone with a basic knowledge of statistics or data analysis.Includes an extensive bibliography and pointers to further reading within the text.Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies analysed using R.Is accessible to anyone with a basic knowledge of statistics or data analysis.Includes an extensive bibliography and pointers to further reading within the text.Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text.

Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers' attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers’ attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers' attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

Shareholder inspection rights form an important tool for shareholder protection. They offer shareholders seeking information private access to specific books and records of the company that are otherwise not publicly available. While there has been a discourse on the topic in some jurisdictions such as Delaware (USA), it has not received scholarly treatment at an international level. This Research Handbook seeks to alter that, and signifies the first endeavor to engage in a comprehensive and comparative analysis of shareholder inspection rights across 19 different jurisdictions representing five continents.Themes emerging from the study include the historical evolution of inspection rights, the statutory design of the inspection regime, how inspection rights interact with disclosure norms under securities regulation, and the manner in which inspection rights are actually utilized by shareholders. While there is some commonality among jurisdictions, the larger story is one of divergence, which is understandable since local needs tend to drive the design and operation of the regime.The Research Handbook on Shareholder Inspection Rights is invaluable to academics, scholars, and students working in the area of corporate law and governance, legal practitioners working in corporate law and, in particular, shareholder litigation and regulators and government bodies overseeing the corporate sector, including corporate and securities regulators.

Shareholder inspection rights form an important tool for shareholder protection. They offer shareholders seeking information private access to specific books and records of the company that are otherwise not publicly available. While there has been a discourse on the topic in some jurisdictions such as Delaware (USA), it has not received scholarly treatment at an international level. This Research Handbook seeks to alter that, and signifies the first endeavor to engage in a comprehensive and comparative analysis of shareholder inspection rights across 19 different jurisdictions representing five continents.

Themes emerging from the study include the historical evolution of inspection rights, the statutory design of the inspection regime, how inspection rights interact with disclosure norms under securities regulation, and the manner in which inspection rights are actually utilized by shareholders. While there is some commonality among jurisdictions, the larger story is one of divergence, which is understandable since local needs tend to drive the design and operation of the regime.

The Research Handbook on Shareholder Inspection Rights is invaluable to academics, scholars, and students working in the area of corporate law and governance, legal practitioners working in corporate law and, in particular, shareholder litigation and regulators and government bodies overseeing the corporate sector, including corporate and securities regulators.

The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​

The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

Vinegars can be considered as acidic products of special importance for the enri- ment of our diet, and resulting from the desired or controlled oxidation of ethanol containing (liquid) substrates. The traditional use and integration of vinegars in numerous cultures can be traced back to ancient times. In fact, the cultural heritage of virtually every civilization includes one or more vinegars made by the souring action (of micro-organisms) following alcoholic fermentation. It has been do- mented that the Egyptians, Sumerians and Babylonians had experience and tech- cal knowledge in making vinegar from barley and any kind of fruit. Vinegar was very popular both in ancient Greece and Rome, where it was used in food prepa- tions and as remedy against a great number of diseases. In Asia, the first records about vinegar date back to the Zhou Dynasty (1027-221 BC) and probably China’s ancient rice wines may have originally been derived from fruit, for which (malted) rice was substituted later. The historical and geographical success of vinegars is mainly due to the low technology required for their production, and to the fact that several kinds of raw materials rich in sugars may easily be processed to give vinegar. In addition, vi- gars are well-known and accepted as safe and stable commodities that can be c- sumed as beverages, health drinks or added to food as preservatives or as flavo- ing agents.

Vinegars can be considered as acidic products of special importance for the enri- ment of our diet, and resulting from the desired or controlled oxidation of ethanol containing (liquid) substrates. The traditional use and integration of vinegars in numerous cultures can be traced back to ancient times. In fact, the cultural heritage of virtually every civilization includes one or more vinegars made by the souring action (of micro-organisms) following alcoholic fermentation. It has been do- mented that the Egyptians, Sumerians and Babylonians had experience and tech- cal knowledge in making vinegar from barley and any kind of fruit. Vinegar was very popular both in ancient Greece and Rome, where it was used in food prepa- tions and as remedy against a great number of diseases. In Asia, the first records about vinegar date back to the Zhou Dynasty (1027-221 BC) and probably China’s ancient rice wines may have originally been derived from fruit, for which (malted) rice was substituted later. The historical and geographical success of vinegars is mainly due to the low technology required for their production, and to the fact that several kinds of raw materials rich in sugars may easily be processed to give vinegar. In addition, vi- gars are well-known and accepted as safe and stable commodities that can be c- sumed as beverages, health drinks or added to food as preservatives or as flavo- ing agents.

More volumes on 'Deleuze and Artistic Research':Machinic Assemblages of DesireAberrant NuptialsDeleuze’s and Guattari’s philosophy in the field of artistic researchGilles Deleuze’s intriguing concept of the dark precursor refers to intensive processes of energetic flows passing between fields of different potentials. Fleetingly used in Difference and Repetition, it remained underexplored in Deleuze’s subsequent work. In this collection of essays numerous contributors offer perspectives on Deleuze’s concept of the dark precursor as it affects artistic research, providing a wide-ranging panorama on the intersection between music, art, philosophy, and scholarship.The forty-eight chapters in this publication present a kaleidoscopic view of different fields of knowledge and artistic practices, exposing for the first time the diversity and richness of a world situated between artistic research and the philosophy of Gilles Deleuze and Félix Guattari. Within different understandings of artistic research, the authors—composers, architects, performers, philosophers, sculptors, film-makers, painters, writers, and activists—map practices and invent concepts, contributing to a creative expansion of horizons, materials, and methodologies.This publication is GPRC-labeled (Guaranteed Peer-Reviewed Content).ContributorsVOLUME 1: Paulo de Assis, Arno Böhler, Edward Campbell, Diego Castro-Magas, Pascale Criton, Zornitsa Dimitrova, Lois Fitch, Mike Fletcher, Paolo Galli, Lindsay Gianoukas, Keir GoGwilt, Oleg Lebedev, Jimmie LeBlanc, Nicolas Marty, Frédéric Mathevet, Vincent Meelberg, Catarina Pombo Nabais, Tero Nauha, Gabriel Paiuk, Martin Scherzinger, Einar Torfi Einarsson, Steve Tromans, Toshiya Ueno, Susanne Valerie, Audronė ŽukauskaitėVOLUME 2: Éric Alliez, Manola Antonioli, Jūratė Baranova, Zsuzsa Baross, Anna Barseghian, Ian Buchanan, Elena del Río, Luis de Miranda, Lucia D’Errico, Lilija Duoblienė, Adreis Echzehn, Jae Emerling, Verina Gfader, Ronny Hardliz, Rahma Khazam, Stefan Kristensen, Erin Manning, John Miers, Elfie Miklautz, Marc Ngui, Andreia Oliveira, Federica Pallaver, Andrej Radman, Felix Rebolledo, Anne Sauvagnargues, Janae Sholtz, Mhairi Vari, Mick Wilson, Elisabet Yanagisawa

This book is the first practical book on AI risk assessment and management. It will enable you to evaluate and implement safe and accurate AI models and applications. The book features risk assessment frameworks, statistical metrics and code, a risk taxonomy curated from real-world case studies, and insights into AI regulation and policy, and is an essential tool for AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities. The centerpiece of this book is a risk management and assessment framework titled “Safe Human-centered AI (SAFE-HAI),” which highlights AI risks across the following Responsible AI principles: accuracy, sustainability and robustness, explainability, transparency and accountability, fairness, privacy and human rights, human-centered AI, and AI governance. Using several statistical metrics such as Area Under Curve (AUC), Rank Graduation Accuracy, and Shapley values, you will learn to apply Lorenz curves to measure risk and inequality across the different principles and will be equipped with a taxonomy/scoring rubric to identify and mitigate identified risks.  This book is a true practical guide and covers a real-world case study using the proposed SAFE-HAI framework. The book will help you adopt standards and voluntary codes of conduct in compliance with AI risk and safety policies and regulations, including those from the NIST (National Institute of Standards and Technology) and EU AI Act (European Commission). What You Will LearnKnow the key principles behind Responsible AI and associated risksBecome familiar with risk assessment frameworks, statistical metrics, and mitigation measures for identified risksBe aware of the fundamentals of AI regulations and policies and how to adopt themUnderstand AI governance basics and implementation guidelines Who This Book Is ForAI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities

This book is the first practical book on AI risk assessment and management. It will enable you to evaluate and implement safe and accurate AI models and applications. The book features risk assessment frameworks, statistical metrics and code, a risk taxonomy curated from real-world case studies, and insights into AI regulation and policy, and is an essential tool for AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities.

 

The centerpiece of this book is a risk management and assessment framework titled “Safe Human-centered AI (SAFE-HAI),” which highlights AI risks across the following Responsible AI principles: accuracy, sustainability and robustness, explainability, transparency and accountability, fairness, privacy and human rights, human-centered AI, and AI governance. Using several statistical metrics such as Area Under Curve (AUC), Rank Graduation Accuracy, and Shapley values, you will learn to apply Lorenz curves to measure risk and inequality across the different principles and will be equipped with a taxonomy/scoring rubric to identify and mitigate identified risks. 

 

This book is a true practical guide and covers a real-world case study using the proposed SAFE-HAI framework. The book will help you adopt standards and voluntary codes of conduct in compliance with AI risk and safety policies and regulations, including those from the NIST (National Institute of Standards and Technology) and EU AI Act (European Commission).

 

What You Will Learn

Know the key principles behind Responsible AI and associated risksBecome familiar with risk assessment frameworks, statistical metrics, and mitigation measures for identified risksBe aware of the fundamentals of AI regulations and policies and how to adopt themUnderstand AI governance basics and implementation guidelines

 

Who This Book Is For

AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities

Aberrant Nuptials explores the diversity and richness of the interactions between artistic research and Deleuze studies. "Aberrant nuptials" is the expression Gilles Deleuze uses to refer to productive encounters between systems characterised by fundamental difference. More than imitation, representation, or reproduction, these encounters foster creative flows of energy, generating new material configurations and intensive experiences. Within different understandings of artistic research, the contributors to this book--architects, composers, film-makers, painters, performers, philosophers, sculptors, and writers--map current practices at the intersection between music, art, and philosophy, contributing to an expansion of horizons and methodologies. Written by musicians and artists who have been reflecting Deleuzian and Post-Deleuzian discourses in their artworks, and by established Deleuze scholars who have been working on interferences between art and philosophy, this volume reflects the current relevance of artistic research and Deleuze studies for the arts.This publication is GPRC-labeled (Guaranteed Peer-Reviewed Content).Contributors: Suzie Attiwill (RMIT University), Sara Baranzoni (Universidad de las Artes of Guayaquil), Zsuzsa Baross (Trent University), Terri Bird (Monash University), Ronald Bogue (University of Georgia), Barbara Bolt (VCA University of Melbourne), Peter Burleigh (University of Basel / HGK, Basel), Edward Campbell (University of Aberdeen / Centre for Modern Thought), Marianna Charitonidou (University of Paris West Nanterre / National Technical University of Athens), Jean-Marc Chouvel (Paris-Sorbonne University), Guillaume Collett (University of Kent), Zornitsa Dimitrova (University of Munster), Lilija Duobliene (University of Vilnius), Lucia D'Errico (Orpheus Institute), Bracha L. Ettinger (artist, painter, theorist), Henrik Frisk (Royal Academy of Music Malmoe), jan jagodzinski (University of Alberta), Oleg Lebedev (Universite Catholique de Louvain), Gustavo Penha (University of Sao Paulo), Katie Pleming (King's College London), Liana Psarologaki (University of Suffolk), Emilia Marra (University of Trieste), Tero Nauha (Helsinki Collegium), Stefan OEstersjoe (Orpheus Institute), Simon O'Sullivan (theorist, artist), Antonia Pont (Deakin University), Elisabeth Presa (University of Melbourne), Spencer Roberts (University of Huddersfield), Jonas Rutgeerts (dramaturge, performance theorist), Anne Sauvagnargues (University of Paris Ouest Nanterre La Defense), Janae Sholtz (Alvernia University), Steve Tromans (musician, independent researcher), Kamini Vellodi (University of Edinburgh), Paolo Vignola (Universidad de las Artes of Guayaquil), Audrone Zukauskaite (Lithuanian Culture Research Institute).In collaboration with Orpheus Institute

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies analysed using R.Is accessible to anyone with a basic knowledge of statistics or data analysis.Includes an extensive bibliography and pointers to further reading within the text.Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications.Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods.Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining.Features detailed case studies based on applied projects within industry.Incorporates discussion of data mining software, with case studies analysed using R.Is accessible to anyone with a basic knowledge of statistics or data analysis.Includes an extensive bibliography and pointers to further reading within the text.Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text.

Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers' attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers’ attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

This Research Handbook provides a critical examination of the landscape of EU securities law, including crypto-markets, financial innovation and the Capital Markets Union. It explores the enforcement of EU securities regulation ies and related instruments, such as the EU Takeover Regulation.Leading specialists discuss the full length and breadth of the subject, from the history and theory of securities regulation to emerging challenges such as those posed by crypto-assets and crypto-markets. They consider mandatory disclosure, short-selling regulation and growth markets, shedding light on the regulatory framework governing the investment and disclosure requirements of environmental, social and governance assets. The Research Handbook also stands back and considers lawmakers' attempts to establish coherent regulation that enables financial innovation in an increasingly technology-driven industry, alongside discussions about the value of shareholder activism and the debate between public and private enforcement mechanisms. The Research Handbook on EU Securities Law is an essential reference for scholars and students of financial law and European law. Its forward-thinking insights will also greatly benefit practising lawyers and industry stakeholders in the field of securities.

Shareholder inspection rights form an important tool for shareholder protection. They offer shareholders seeking information private access to specific books and records of the company that are otherwise not publicly available. While there has been a discourse on the topic in some jurisdictions such as Delaware (USA), it has not received scholarly treatment at an international level. This Research Handbook seeks to alter that, and signifies the first endeavor to engage in a comprehensive and comparative analysis of shareholder inspection rights across 19 different jurisdictions representing five continents.Themes emerging from the study include the historical evolution of inspection rights, the statutory design of the inspection regime, how inspection rights interact with disclosure norms under securities regulation, and the manner in which inspection rights are actually utilized by shareholders. While there is some commonality among jurisdictions, the larger story is one of divergence, which is understandable since local needs tend to drive the design and operation of the regime.The Research Handbook on Shareholder Inspection Rights is invaluable to academics, scholars, and students working in the area of corporate law and governance, legal practitioners working in corporate law and, in particular, shareholder litigation and regulators and government bodies overseeing the corporate sector, including corporate and securities regulators.

Shareholder inspection rights form an important tool for shareholder protection. They offer shareholders seeking information private access to specific books and records of the company that are otherwise not publicly available. While there has been a discourse on the topic in some jurisdictions such as Delaware (USA), it has not received scholarly treatment at an international level. This Research Handbook seeks to alter that, and signifies the first endeavor to engage in a comprehensive and comparative analysis of shareholder inspection rights across 19 different jurisdictions representing five continents.

Themes emerging from the study include the historical evolution of inspection rights, the statutory design of the inspection regime, how inspection rights interact with disclosure norms under securities regulation, and the manner in which inspection rights are actually utilized by shareholders. While there is some commonality among jurisdictions, the larger story is one of divergence, which is understandable since local needs tend to drive the design and operation of the regime.

The Research Handbook on Shareholder Inspection Rights is invaluable to academics, scholars, and students working in the area of corporate law and governance, legal practitioners working in corporate law and, in particular, shareholder litigation and regulators and government bodies overseeing the corporate sector, including corporate and securities regulators.

The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​

The papers in this book cover issues related to the development of novel statistical models for the analysis of data. They offer solutions for relevant problems in statistical data analysis and contain the explicit derivation of the proposed models as well as their implementation. The book assembles the selected and refereed proceedings of the biannual conference of the Italian Classification and Data Analysis Group (CLADAG), a section of the Italian Statistical Society. ​

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

This book offers a clear description of all the balsamic vinegars and/or similar products produced in the world, their differences in composition, quality and use. This encompasses all the steps for the production of Traditional Balsamic Vinegar: grape composition, crushing, concentration of the must, alcoholic and acetic fermentation, ageing, sensorial properties and quality of the final product. This book covers extensively all the balsamic vinegars, especially the industrial ones that have a really large market and diffusion.

Vinegars can be considered as acidic products of special importance for the enri- ment of our diet, and resulting from the desired or controlled oxidation of ethanol containing (liquid) substrates. The traditional use and integration of vinegars in numerous cultures can be traced back to ancient times. In fact, the cultural heritage of virtually every civilization includes one or more vinegars made by the souring action (of micro-organisms) following alcoholic fermentation. It has been do- mented that the Egyptians, Sumerians and Babylonians had experience and tech- cal knowledge in making vinegar from barley and any kind of fruit. Vinegar was very popular both in ancient Greece and Rome, where it was used in food prepa- tions and as remedy against a great number of diseases. In Asia, the first records about vinegar date back to the Zhou Dynasty (1027-221 BC) and probably China’s ancient rice wines may have originally been derived from fruit, for which (malted) rice was substituted later. The historical and geographical success of vinegars is mainly due to the low technology required for their production, and to the fact that several kinds of raw materials rich in sugars may easily be processed to give vinegar. In addition, vi- gars are well-known and accepted as safe and stable commodities that can be c- sumed as beverages, health drinks or added to food as preservatives or as flavo- ing agents.

Vinegars can be considered as acidic products of special importance for the enri- ment of our diet, and resulting from the desired or controlled oxidation of ethanol containing (liquid) substrates. The traditional use and integration of vinegars in numerous cultures can be traced back to ancient times. In fact, the cultural heritage of virtually every civilization includes one or more vinegars made by the souring action (of micro-organisms) following alcoholic fermentation. It has been do- mented that the Egyptians, Sumerians and Babylonians had experience and tech- cal knowledge in making vinegar from barley and any kind of fruit. Vinegar was very popular both in ancient Greece and Rome, where it was used in food prepa- tions and as remedy against a great number of diseases. In Asia, the first records about vinegar date back to the Zhou Dynasty (1027-221 BC) and probably China’s ancient rice wines may have originally been derived from fruit, for which (malted) rice was substituted later. The historical and geographical success of vinegars is mainly due to the low technology required for their production, and to the fact that several kinds of raw materials rich in sugars may easily be processed to give vinegar. In addition, vi- gars are well-known and accepted as safe and stable commodities that can be c- sumed as beverages, health drinks or added to food as preservatives or as flavo- ing agents.

More volumes on 'Deleuze and Artistic Research':Machinic Assemblages of DesireAberrant NuptialsDeleuze’s and Guattari’s philosophy in the field of artistic researchGilles Deleuze’s intriguing concept of the dark precursor refers to intensive processes of energetic flows passing between fields of different potentials. Fleetingly used in Difference and Repetition, it remained underexplored in Deleuze’s subsequent work. In this collection of essays numerous contributors offer perspectives on Deleuze’s concept of the dark precursor as it affects artistic research, providing a wide-ranging panorama on the intersection between music, art, philosophy, and scholarship.The forty-eight chapters in this publication present a kaleidoscopic view of different fields of knowledge and artistic practices, exposing for the first time the diversity and richness of a world situated between artistic research and the philosophy of Gilles Deleuze and Félix Guattari. Within different understandings of artistic research, the authors—composers, architects, performers, philosophers, sculptors, film-makers, painters, writers, and activists—map practices and invent concepts, contributing to a creative expansion of horizons, materials, and methodologies.This publication is GPRC-labeled (Guaranteed Peer-Reviewed Content).ContributorsVOLUME 1: Paulo de Assis, Arno Böhler, Edward Campbell, Diego Castro-Magas, Pascale Criton, Zornitsa Dimitrova, Lois Fitch, Mike Fletcher, Paolo Galli, Lindsay Gianoukas, Keir GoGwilt, Oleg Lebedev, Jimmie LeBlanc, Nicolas Marty, Frédéric Mathevet, Vincent Meelberg, Catarina Pombo Nabais, Tero Nauha, Gabriel Paiuk, Martin Scherzinger, Einar Torfi Einarsson, Steve Tromans, Toshiya Ueno, Susanne Valerie, Audronė ŽukauskaitėVOLUME 2: Éric Alliez, Manola Antonioli, Jūratė Baranova, Zsuzsa Baross, Anna Barseghian, Ian Buchanan, Elena del Río, Luis de Miranda, Lucia D’Errico, Lilija Duoblienė, Adreis Echzehn, Jae Emerling, Verina Gfader, Ronny Hardliz, Rahma Khazam, Stefan Kristensen, Erin Manning, John Miers, Elfie Miklautz, Marc Ngui, Andreia Oliveira, Federica Pallaver, Andrej Radman, Felix Rebolledo, Anne Sauvagnargues, Janae Sholtz, Mhairi Vari, Mick Wilson, Elisabet Yanagisawa

This book is the first practical book on AI risk assessment and management. It will enable you to evaluate and implement safe and accurate AI models and applications. The book features risk assessment frameworks, statistical metrics and code, a risk taxonomy curated from real-world case studies, and insights into AI regulation and policy, and is an essential tool for AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities. The centerpiece of this book is a risk management and assessment framework titled “Safe Human-centered AI (SAFE-HAI),” which highlights AI risks across the following Responsible AI principles: accuracy, sustainability and robustness, explainability, transparency and accountability, fairness, privacy and human rights, human-centered AI, and AI governance. Using several statistical metrics such as Area Under Curve (AUC), Rank Graduation Accuracy, and Shapley values, you will learn to apply Lorenz curves to measure risk and inequality across the different principles and will be equipped with a taxonomy/scoring rubric to identify and mitigate identified risks.  This book is a true practical guide and covers a real-world case study using the proposed SAFE-HAI framework. The book will help you adopt standards and voluntary codes of conduct in compliance with AI risk and safety policies and regulations, including those from the NIST (National Institute of Standards and Technology) and EU AI Act (European Commission). What You Will LearnKnow the key principles behind Responsible AI and associated risksBecome familiar with risk assessment frameworks, statistical metrics, and mitigation measures for identified risksBe aware of the fundamentals of AI regulations and policies and how to adopt themUnderstand AI governance basics and implementation guidelines Who This Book Is ForAI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities

This book is the first practical book on AI risk assessment and management. It will enable you to evaluate and implement safe and accurate AI models and applications. The book features risk assessment frameworks, statistical metrics and code, a risk taxonomy curated from real-world case studies, and insights into AI regulation and policy, and is an essential tool for AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities.

 

The centerpiece of this book is a risk management and assessment framework titled “Safe Human-centered AI (SAFE-HAI),” which highlights AI risks across the following Responsible AI principles: accuracy, sustainability and robustness, explainability, transparency and accountability, fairness, privacy and human rights, human-centered AI, and AI governance. Using several statistical metrics such as Area Under Curve (AUC), Rank Graduation Accuracy, and Shapley values, you will learn to apply Lorenz curves to measure risk and inequality across the different principles and will be equipped with a taxonomy/scoring rubric to identify and mitigate identified risks. 

 

This book is a true practical guide and covers a real-world case study using the proposed SAFE-HAI framework. The book will help you adopt standards and voluntary codes of conduct in compliance with AI risk and safety policies and regulations, including those from the NIST (National Institute of Standards and Technology) and EU AI Act (European Commission).

 

What You Will Learn

Know the key principles behind Responsible AI and associated risksBecome familiar with risk assessment frameworks, statistical metrics, and mitigation measures for identified risksBe aware of the fundamentals of AI regulations and policies and how to adopt themUnderstand AI governance basics and implementation guidelines

 

Who This Book Is For

AI governance teams, AI auditors, AI ethicists, machine learning (ML) practitioners, Responsible AI practitioners, and computer science and data science students building safe and trustworthy AI systems across businesses, organizations, and universities

Aberrant Nuptials explores the diversity and richness of the interactions between artistic research and Deleuze studies. "Aberrant nuptials" is the expression Gilles Deleuze uses to refer to productive encounters between systems characterised by fundamental difference. More than imitation, representation, or reproduction, these encounters foster creative flows of energy, generating new material configurations and intensive experiences. Within different understandings of artistic research, the contributors to this book--architects, composers, film-makers, painters, performers, philosophers, sculptors, and writers--map current practices at the intersection between music, art, and philosophy, contributing to an expansion of horizons and methodologies. Written by musicians and artists who have been reflecting Deleuzian and Post-Deleuzian discourses in their artworks, and by established Deleuze scholars who have been working on interferences between art and philosophy, this volume reflects the current relevance of artistic research and Deleuze studies for the arts.This publication is GPRC-labeled (Guaranteed Peer-Reviewed Content).Contributors: Suzie Attiwill (RMIT University), Sara Baranzoni (Universidad de las Artes of Guayaquil), Zsuzsa Baross (Trent University), Terri Bird (Monash University), Ronald Bogue (University of Georgia), Barbara Bolt (VCA University of Melbourne), Peter Burleigh (University of Basel / HGK, Basel), Edward Campbell (University of Aberdeen / Centre for Modern Thought), Marianna Charitonidou (University of Paris West Nanterre / National Technical University of Athens), Jean-Marc Chouvel (Paris-Sorbonne University), Guillaume Collett (University of Kent), Zornitsa Dimitrova (University of Munster), Lilija Duobliene (University of Vilnius), Lucia D'Errico (Orpheus Institute), Bracha L. Ettinger (artist, painter, theorist), Henrik Frisk (Royal Academy of Music Malmoe), jan jagodzinski (University of Alberta), Oleg Lebedev (Universite Catholique de Louvain), Gustavo Penha (University of Sao Paulo), Katie Pleming (King's College London), Liana Psarologaki (University of Suffolk), Emilia Marra (University of Trieste), Tero Nauha (Helsinki Collegium), Stefan OEstersjoe (Orpheus Institute), Simon O'Sullivan (theorist, artist), Antonia Pont (Deakin University), Elisabeth Presa (University of Melbourne), Spencer Roberts (University of Huddersfield), Jonas Rutgeerts (dramaturge, performance theorist), Anne Sauvagnargues (University of Paris Ouest Nanterre La Defense), Janae Sholtz (Alvernia University), Steve Tromans (musician, independent researcher), Kamini Vellodi (University of Edinburgh), Paolo Vignola (Universidad de las Artes of Guayaquil), Audrone Zukauskaite (Lithuanian Culture Research Institute).In collaboration with Orpheus Institute