Il diritto come istituzione / Neil MacCormick, Ota Weinberger ; a cura di Massimo La Torre

• Record Nr.: UNISA990000753840203316
• Autore: MacCORMICK, Neil
• Pubbl/distr/stampa: Milano : Giuffrè, 1990
• ISBN: 88-14-02301-8
• Descrizione fisica: XII, 435 p ; 24 cm
• Collana: Seminario giuridico della Università di Bologna , Miscellanee ; 8; Legal philosophical library
• Altri autori (Persone): WEINBERGER, Ota
• Disciplina: 340.1
• Soggetti: Diritto - Teorie
• Collocazione: XXX.A. Coll. 5/ 5 (X 2 XIV 8)
• Lingua di pubblicazione: Italiano
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Food and urbanism : the convivial city and a sustainable future / / Susan Parham

• Record Nr.: UNINA9910797926403321
• Autore: Parham Susan
• Pubbl/distr/stampa: London : , : Bloomsbury Academic, , 2015
• ISBN: 1-4725-2096-3; 0-85785-474-7
• Descrizione fisica: 1 online resource (362 pages) : illustrations
• Classificazione: SOC055000ARC010000SOC026000SOC015000
• Disciplina: 307.1416
• Soggetti: Sustainable urban development; Food - Social aspects; Sociology, Urban
• 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 (pages 279-351) and index.
• Nota di contenuto: Machine generated contents note: -- DedicationPrefaceAcknowledgementsList of IllustrationsIntroduction: Food and Urbanism: the Convivial City and Sustainable FuturePart One: Food, Domesticity and DesignThe Paradoxical Kitchen and the Death of DiningThe Garden and Gastronomy Part Two: Gastronomy and Public SpaceFood's Outdoor Room The Gastronomic Townscape Ambivalent SuburbiaConvivial Green Space Part Three: Food Space on the EdgeThe Productive Periphery The Megalopolitan Food RealmDesigning the Critical Food Region Food and Urbanism in a Global Context Conclusion: Food and Urbanism - Making a Resilient City BibliographyIndex.
• Sommario/riassunto: "Cities are now home to over fifty per cent of the world's population, but the contribution of food to shaping cities is often overlooked. Food matters in designing and planning cities because how it is grown, transported, bought, cooked, eaten, cleaned up and disposed of has significant effects on creating a sustainable, resilient and convivial urban future. The book explores methods for extending the gastronomic possibilities of urban space - from the scale of the table to the metropolis. Using a wealth of examples from cities worldwide, the book explores how physical design and socio-spatial arrangements ; focused on food can help maintain socially rich, productive and sustainable urban space. Underpinning the book's analysis of food and cities is the view that decisions about a hyper-urban future should recognise the fundamental role of food. Food and Urbanism provides an original and new contribution to food scholarship; exploring some intriguing research questions about the ways that food, urbanism and sustainable conviviality interconnect"--; "Cities are now home to over fifty per cent of the world's population, but the contribution of food to shaping cities is often overlooked. Food matters in designing and planning cities because how it is grown, transported, bought, cooked, eaten, cleaned up and disposed of has significant effects on creating a sustainable, resilient and convivial urban future. The book explores methods for extending the gastronomic possibilities of urban space - from the scale of the table to the metropolis. Using a wealth of examples from cities worldwide, the book explores how physical design and socio-spatial arrangements focused on food can help maintain socially rich, productive and sustainable urban space. Underpinning the book's analysis of food and cities is the view that decisions about a hyper-urban future should recognise the fundamental role of food. Food and Urbanism provides an original and new contribution to food scholarship; exploring some intriguing research questions about the ways that food, urbanism and sustainable conviviality interconnect"--

Artificial Intelligence in Process Fault Diagnosis : Methods for Plant Surveillance

• Record Nr.: UNINA9910830640803321
• Autore: Fickelscherer Richard J
• Pubbl/distr/stampa: Newark : , : John Wiley & Sons, Incorporated, , 2024; ©2024
• ISBN: 1-119-82592-X; 1-119-82590-3
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (436 pages)
• Disciplina: 670.427
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: COVER -- TITLE PAGE -- COPYRIGHT PAGE -- DEDICATION PAGE -- CONTENTS -- LIST OF CONTRIBUTORS -- FOREWORD -- PREFACE -- ACKNOWLEDGMENTS -- CHAPTER 1 MOTIVATIONS FOR AUTOMATING PROCESS FAULT ANALYSIS -- OVERVIEW -- CHAPTER HIGHLIGHTS -- 1.1 INTRODUCTION -- 1.2 THE CHANGING ROLE OF THE PROCESS OPERATORS IN PLANT OPERATIONS -- 1.3 TRADITIONAL METHODS FOR PERFORMING PROCESS FAULT MANAGEMENT -- 1.4 LIMITATIONS OF HUMAN OPERATORS IN PERFORMING PROCESS FAULT MANAGEMENT -- 1.5 THE ROLE OF AUTOMATED PROCESS FAULT ANALYSIS -- REFERENCES -- CHAPTER 2 VARIOUS PROCESS FAULT DIAGNOSTIC METHODOLOGIES -- OVERVIEW -- CHAPTER HIGHLIGHTS -- 2.1 INTRODUCTION -- 2.2 VARIOUS ALTERNATIVE DIAGNOSTIC STRATEGIES OVERVIEW -- 2.2.1 Fault Tree Analysis -- 2.2.2 Alarm Analysis -- 2.2.3 Decision Tables -- 2.2.4 Sign-Directed Graphs -- 2.2.5 History-Based Statistical Methods -- 2.2.6 Diagnostic Strategies Based upon Qualitative Models -- 2.2.7 Diagnostic Strategies Based upon Quantitative Models -- 2.2.8 Artificial Neural Network Strategies -- 2.2.9 Artificial Immune System Strategies -- 2.2.10 Knowledge-Based System Strategies -- 2.2.11 Role of the Process Operators in Automated Fault Detection and Diagnosis -- 2.3 DIAGNOSTIC METHODOLOGY CHOICE CONCLUSIONS -- REFERENCES -- CHAPTER 2.A FAILURE MODES AND EFFECTS ANALYSIS -- 2.A.1 Introduction -- 2.A.; 2 FMEA Procedure -- 2.A.3 Conclusion -- CHAPTER 3 ALARM MANAGEMENT AND FAULT DETECTION -- CHAPTER HIGHLIGHTS -- ABBREVIATIONS USED -- 3.1 INTRODUCTION -- 3.2 APPLICABLE DEFINITIONS AND GUIDELINES -- 3.3 THE ALARM MANAGEMENT LIFE CYCLE -- 3.3.1 Introduction -- 3.3.2 Life Cycle Model -- 3.3.3 Alarm Philosophy -- 3.3.4 Alarm Identification -- 3.3.5 Alarm Rationalization -- 3.3.6 Alarm Design -- 3.3.7 Implementation -- 3.3.8 Operation -- 3.3.9 Maintenance -- 3.3.10 Monitoring and Assessment -- 3.3.11 Management of Change -- 3.3.12 Audit.; 3.4 GENERATION OF DIAGNOSTIC INFORMATION -- 3.4.1 Introduction -- 3.4.2 As Part of the Basic Process Control System -- 3.4.3 As a Separate Application -- 3.5 PRESENTATION OF THE DIAGNOSTIC INFORMATION -- 3.5.1 Introduction -- 3.5.2 As Part of the Alarm Text -- 3.5.3 As a Link to the Diagnostic Application -- 3.5.4 As an Indication in the HMI -- 3.6 INFORMATION RATES -- 3.6.1 Introduction -- 3.6.2 Nuisance Alarms -- REFERENCES -- CHAPTER 4 OPERATOR PERFORMANCE: SIMULATION AND AUTOMATION -- CHAPTER HIGHLIGHTS -- 4.1 BACKGROUND -- 4.2 AUTOMATION -- 4.2.1 Smart Alarming -- 4.2.2 Safe Park Applications -- 4.3 SIMULATION -- 4.4 RESEARCH -- 4.4.1 Method -- 4.4.2 Testing and Results -- 4.4.3 Operator Performance -- 4.4.4 Implications -- 4.5 AI INTEGRATION -- 4.5.1 Pattern Recognition -- 4.5.2 Training -- 4.6 CASE STUDY: TURBO EXPANDERS OVER-SPEED -- 4.7 HUMAN-CENTERED AI -- 4.7.1 Case Study: Boeing 737 MAX -- 4.7.2 AI Mental Models -- REFERENCES -- CHAPTER 5 AI AND ALARM ANALYTICS FOR FAILURE ANALYSIS AND PREVENTION -- OVERVIEW -- 5.1 INTRODUCTION -- 5.2 POST-ALARM ASSESSMENT AND ANALYSIS -- 5.2.1 Alarm Configuration Database -- 5.3 REAL-TIME ALARM ACTIVITY DATABASE AND OPERATOR ACTION JOURNAL -- 5.4 PRE-ALARM ASSESSMENT AND ANALYSIS -- 5.5 UTILIZING ALARM ASSESSMENT INFORMATION -- 5.6 EXAMINING THE ALARM SYSTEM TO RESOLVE FAILURES ON A WIDER SCALE -- 5.6.1 Sequence of Events (SOE) Module -- 5.6.2 Use of First Principles to Determine Likely Root Causes -- 5.6.3 Use of Simple Data Analytics to Identify Redundant/Repetitive Alarms -- 5.6.4 Use of Data Analytics to Identify Problem Areas with Upsets Related to Transitions, out of Service, and out of Suppression States -- 5.6.5 Use of Data Analytics to Identify Problem Areas with Chronic Alarm Shelving -- 5.7 EMERGING METHODS OF ALARM ANALYSIS -- 5.7.1 Use of Advanced Modeling Methods to Determine Remediation.; 5.7.2 Use of Automated Machine Learning to Determine Causes and Assess Interventions -- 5.8 DEEP REINFORCEMENT LEARNING FOR ALARMING AND FAILURE ASSESSMENT -- 5.9 SOME TYPICAL AI AND MACHINE LEARNING EXAMPLES FOR FURTHER STUDY -- 5.9.1 Boolean Logic Tables -- 5.9.2 Statistical Regression and Variance -- 5.9.3 Artificial Neural Networks (ANNs) -- 5.9.4 Expert Systems -- 5.9.5 Sensitivity Analysis -- 5.9.6 Fuzzy Logic -- 5.9.7 Bayesian Networks -- 5.9.8 Genetic Algorithms -- 5.9.9 SmartSignal, PRiSM (AVEVA), and PPCL -- 5.9.10 Control System Effectiveness Study -- 5.10 WRAP-UP -- CHAPTER 5.A PROCESS STATE TRANSITION LOGIC EMPLOYED BY THE ORIGINAL FMC FALCONEER KBS -- 5.A.1 INTRODUCTION -- 5.A.2 POSSIBLE PROCESS OPERATING STATES -- 5.A.3 SIGNIFICANCE OF PROCESS STATE IDENTIFICATION AND TRANSITION DETECTION -- 5.A.4 METHODOLOGY FOR DETERMINING PROCESS STATE IDENTIFICATION -- 5.A.4.1 Present Value States of all Key Sensor Data -- 5.A.4.2 Predicted Next Value States of all Key Sensor Data -- 5.A.5 PROCESS STATE IDENTIFICATION AND TRANSITION LOGIC PSEUDO-CODE -- 5.A.5.1 Attributes of the Current Data Vector -- 5.A.; 5.2 Method that is Applied to Each Updated Data Vector -- 5.A.6 SUMMARY -- APPENDIX 5.A REFERENCES -- CHAPTER 5.B PROCESS STATE TRANSITION LOGIC AND ITS ROUTINE USE IN FALCONEER™ IV -- 5.B.1 TEMPORAL REASONING PHILOSOPHY -- 5.B.2 INTRODUCTION -- 5.B.3 STATE IDENTIFICATION ANALYSIS CURRENTLY USED IN FALCONEER™ IV -- 5.B.4 STATE IDENTIFICATION ANALYSIS SUMMARY -- APPENDIX 5.B REFERENCES -- CHAPTER 6 PROCESS FAULT DETECTION BASED ON TIME-EXPLICIT KIVIAT DIAGRAM -- OVERVIEW -- CHAPTER HIGHLIGHTS -- 6.1 INTRODUCTION -- 6.2 TIME-EXPLICIT KIVIAT DIAGRAM -- 6.3 FAULT DETECTION BASED ON THE TIME-EXPLICIT KIVIAT DIAGRAM -- 6.4 CONTINUOUS PROCESSES -- 6.5 BATCH PROCESSES -- 6.6 PERIODIC PROCESSES -- 6.7 CASE STUDIES -- 6.8 CONTINUOUS PROCESSES.; 6.9 BATCH PROCESSES -- 6.10 PERIODIC PROCESSES -- 6.11 CONCLUSIONS -- ACKNOWLEDGMENT -- REFERENCES -- ACKNOWLEDGMENTS -- APPENDIX 6.A REFERENCES -- CHAPTER 6.A VIRTUAL STATISTICAL PROCESS CONTROL ANALYSIS -- 6.A.1 OVERVIEW -- 6.A.2 INTRODUCTION -- 6.A.3 EWMA CALCULATIONS AND SPECIFIC VIRTUAL SPC ANALYSIS CONFIGURATIONS -- 6.A.3.1 Controlled Variables -- 6.A.3.2 Uncontrolled Variables and Performance Equation Variables -- 6.A.4 VIRTUAL SPC ALARM TRIGGER SUMMARY -- 6.A.5 VIRTUAL SPC ANALYSIS CONCLUSIONS -- ACKNOWLEDGMENTS -- APPENDIX 6.A REFERENCES -- CHAPTER 7 SMART MANUFACTURING AND REAL-TIME CHEMICAL PROCESS HEALTH MONITORING AND DIAGNOSTIC LOCALIZATION -- CHAPTER HIGHLIGHTS -- 7.1 INTRODUCTION TO PROCESS OPERATIONAL HEALTH MODELING -- 7.2 DIAGNOSTIC LOCALIZATION - KEY CONCEPTS -- 7.2.1 Qualitative Modeling and Symptomaticand Topographic Search -- 7.2.2 Functional Representation as a Qualitative Modeling Construct -- 7.2.3 Causal Link Assessment for Combined Topographical and Symptomatic Assessment -- 7.3 TIME -- 7.3.1 Discretization and Single Time-Step Analysis -- 7.3.2 Dynamics in an Individual Functional Representation -- 7.3.3 Time Window and Feature Extraction -- 7.4 THE WORKFLOW OF DIAGNOSTIC LOCALIZATION -- 7.5 DL-CLA USE CASE IMPLEMENTATION: NOVA CHEMICAL ETHYLENE SPLITTER -- 7.5.1 CPP Generation -- 7.5.2 CPP Interpretation -- 7.5.3 Diagnostic Localization -- 7.6 ANALYZING POTENTIAL MALFUNCTIONS OVER TIME -- 7.7 ANALYSIS OF VARIOUS OPERATIONAL SCENARIOS -- 7.7.1 Event Manifestation, Sensor Reliability/Sensor Malfunctions -- 7.7.2 Hypothetical and Function-Only Devices -- 7.7.3 Unaccounted Malfunctions, Graceful Degradation, Multiple Malfunctions, Etc. -- 7.7.4 Sensor Availability and Reliability -- 7.7.5 Process Complexity -- 7.8 DL-CLA INTEGRATION WITH SMART MANUFACTURING (SM) -- 7.9 AN FR MODEL LIBRARY -- 7.9.1 Reusing FR Device Models.; 7.9.2 Complex FR Models -- 7.9.3 Analysis and Results -- 7.10 CONCLUSIONS -- REFERENCES -- CHAPTER 8 OPTIMAL QUANTITATIVE MODEL-BASED PROCESS FAULT DIAGNOSIS -- OVERVIEW -- CHAPTER HIGHLIGHTS -- 8.1 INTRODUCTION -- 8.2 PROCESS FAULT ANALYSIS CONCEPT TERMINOLOGY -- 8.3 MOME QUANTITATIVE MODELS OVERVIEW -- 8.4 MOME QUANTITATIVE MODEL DIAGNOSTIC STRATEGY -- 8.5 MOME SV&amp -- PFA DIAGNOSTIC RULES' LOGIC COMPILER MOTIVATIONS -- 8.6 MOME FUZZY LOGIC ALGORITHM OVERVIEW -- 8.6.1 MOME Fuzzy Logic Algorithm Details -- 8.6.2 Single Fault Fuzzy Logic SV&amp -- PFA Diagnostic Rule -- 8.6.3 Multiple Fault Fuzzy Logic SV&amp -- PFA Diagnostic Rule -- 8.7 SUMMARY OF THE MOME DIAGNOSTIC STRATEGY -- 8.8 ACTUAL PROCESS SYSTEM KBS APPLICATION PERFORMANCE RESULTS -- 8.9 CONCLUSIONS -- ACKNOWLEDGMENTS -- REFERENCES -- CHAPTER 8.; A FALCONEERTM IV FUZZY LOGIC ALGORITHM PSEUDO-CODE -- 8.A.1 Introduction -- 8.A.2 Single and Non-Interactive Multiple Faults -- 8.A.3 Pairs of Interactive Multiple Faults -- 8.A.4 Summary -- CHAPTER 8.B MOME CONCLUSIONS -- 8.B.1 Overview -- 8.B.2 Summary of the Mome Diagnostic Strategy -- 8.B.3 Falconeer™ IV KBS Application Project Procedure -- 8.B.4 Optimal Automated Process Fault Analysis Conclusions -- CHAPTER 9 FAULT DETECTION USING ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING -- CHAPTER HIGHLIGHTS -- ABBREVIATIONS USED -- 9.1 INTRODUCTION -- 9.2 ARTIFICIAL INTELLIGENCE -- 9.3 MACHINE LEARNING -- 9.4 ENGINEERED FEATURES -- 9.4.1 Fast Fourier Transformation and Signal Processing -- 9.4.2 Principal Component Analysis -- 9.5 MACHINE LEARNING ALGORITHMS -- 9.5.1 Decision Trees and Ensemble Trees -- 9.5.2 Artificial Neural Networks -- 9.5.3 Bayesian Networks -- 9.5.4 High-Density Clustering -- 9.5.5 Large Language Models and the Future AI-Driven Factories -- REFERENCES -- CHAPTER 10 KNOWLEDGE-BASED SYSTEMS -- CHAPTER HIGHLIGHTS.; ABBREVIATIONS USED.