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1. |
Record Nr. |
UNINA9910494743203321 |
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Titolo |
Dual diagnosis during pregnancy, prenatally and into motherhood / / Joana Sharpen, editor |
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Pubbl/distr/stampa |
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Bradford, West Yorkshire : , : Emerald Publishing Limited, , [2020] |
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©2020 |
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ISBN |
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Descrizione fisica |
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1 online resource (57 pages) |
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Disciplina |
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Soggetti |
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Pregnancy - Nutritional aspects |
Motherhood - Psychological aspects |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Cover -- Guest editorial -- A review of factors associated with patterns of drinking during pregnancy -- Profiles of mothers who seek treatment for substance use disorders in a clinical centre -- Factors associated with the severity of IPV perpetrated by substance using men towards current partner -- How to capture the experience of mothers with alcohol problems involved in English family court proceedings - lessons from the field. |
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2. |
Record Nr. |
UNINA9910142396003321 |
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Titolo |
Guidelines for improving plant reliability through data collection and analysis [[electronic resource]] |
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Pubbl/distr/stampa |
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New York, : American Institute of Chemical Engineers, c1998 |
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ISBN |
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1-282-78326-2 |
9786612783265 |
0-470-93524-3 |
0-470-93526-X |
1-59124-625-3 |
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Descrizione fisica |
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1 online resource (210 p.) |
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Collana |
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Disciplina |
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620.00452 |
660.2815 |
660/.2815 |
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Soggetti |
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Chemical process control - Statistical methods |
Reliability (Engineering) - Statistical methods |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Guideline for Improving Plant Reliability through Data Collection and Analysis; Contents; Preface; Acknowledgments; 1 Introduction; 1.1. Background; 1.2. Taxonomy; 1.3. Data Aggregation/Sharing; 2 Definitions; 2.1. Introduction; 2.2. Discussion of Key Reliability Terms; 2.3. Glossary of Terms; 3 Methods of Analysis; 3.1. Introduction; 3.2. Basic Concepts of Data Analysis; 3.2.1. Failure Data; 3.2.2. Need for Correct Failure Modes; 3.2.3. Types of Systems-Repairable or Nonrepairable; 3.2.4. Reliability versus Availability; 3.2.5. Types of Data-Censoring; 3.2.6. Definitions |
3.2.7. Dealing with Censored Data3.2.8. Common Cause Failures; 3.2.9. Predictive versus Descriptive Methods; 3.3. Data Manipulation Examples; 3.3.1. Methods of Analysis; 3.4. Cyclical Service; 3.5. Batch Service; 3.6. Standby Service; 3.7. Failures Following a Repair; 3.8. Selecting an Operating Mode; 3.9. Analysis Based on Statistical Inferences; 3.9.1. Modeling Reliability Parameters for the Population; |
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3.9.2. The Weibull Distribution; 3.9.3. Graphical Method for Estimating the Weibull Parameters; 3.9.4. The Exponential Distribution; 3.9.5. Confidence Limits for Reliability Parameters |
References4 Example Applications; 4.1. Introduction; 4.2. Conducting a Reliability Analysis-Pump Example; 4.3. Right-Censoring; 4.4. MTTF by Numerical Integration; 4.5. Reliability Calculations for Repaired Items; 4.6. Calculation of MTTR by Numerical Integration; 4.7. Fitting a Weibull Distribution; 4.8. Combinations of Failure Distributions; 4.9. System Performance-Compressor Example; 4.10. Life-Cycle Costs-Compressor Example (continued); 4.11. Maintenance Budgeting-Compressor Example (continued); 4.12. Throughput Targets-Compressor Example (continued); 4.13. Summary; References |
5 Data Structure5.1. Data Structure Overview; 5.2. General Taxonomy; 5.2.1. Taxonomy Levels 14 (Industry, Site, Plant, Process Units); 5.2.2. Taxonomy Levels 5-7 (System, Component, Part); 5.2.3. Treatment of Subordinate Systems in the CCPS Database; 5.3. Database Structure; 5.3.1. Inventory Tables; 5.3.2. Event Tables; 5.3.3. Failure Logic Data; 6 Quality Assurance of Data; 6.1. Introduction; 6.2. Basic Principles of Quality as Applied to Equipment Reliability Data; 6.3. Quality Management; 6.4. Quality Principles; 6.5. Verification of Data Quality |
6.5.1. Quality Plan for Database Administrator (DA)6.5.2. Quality Plan for Data Subscribers; 6.5.3. Certification of Data Subscribers; 6.5.4. Internal Verification of Data Quality; 6.5.5. Verification of Data Prior to Acceptance; 6.5.6. Recertification of Data Contributors; 6.5.7. Appeal Process; 6.5.8. Audits of Work Process; APPENDIX I Guidelines for Data Collection and Submission; I.1. Introduction; I.1.1. Data Types; I.1.2. Subscriber Data; I.1.3. Inventory Data; I.1.4. Event Data; I.1.5. Data Analysis; I.1.6. Database Limitations; I.1.7. Goals of the Equipment Reliability Process |
I.1.8. Certification of a Subscriber |
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Sommario/riassunto |
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Written by reliability data experts, the book gives plant managers and supervisors the guidance they need to collect, and use with confidence, process equipment reliability data for risk-based decisions. Focusing on the process industries, it provides the protocol and techniques to collect and organize high quality plant performance, maintenance, and repair data from your own operations, and includes methods and examples on how the data can be converted into useful information for engineering, maintenance, safety, and loss prevention. This data can be used for: facility reliability/availabilit |
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