LEADER 02690oam 2200421 450 001 9910831072303321 005 20230629234147.0 010 $a1-119-64007-5 010 $a1-119-64006-7 010 $a1-119-64005-9 035 $a(CKB)4100000011248699 035 $a(MiAaPQ)EBC6382208 035 $a(EXLCZ)994100000011248699 100 $a20210417d2021 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExplosion vented equipment system protection guide /$fRobert Charles Comer 210 1$aHoboken, New Jersey :$cWiley,$d[2021] 210 4$d©2021 215 $a1 online resource (211 pages) 311 $a1-119-64003-2 330 $a"The U.S. Chemical Safety Board reports 316 dust explosions over the last 30 years that caused 145 workers killed and 846 injured with extensive damage to facilities. Fines by OSHA have totaled more than $100,000,000. According to the independent 2019 (mid-year) combustible dust incident report from Dustex Research, Ltd, there were 80 dust related fires, 19 dust related explosions, 72 injuries and one fatality in the U.S. from January through July 2019. There are more than 130,000 establishments in the U.S., many with more than one facility, with many dust collection systems per facility. The new National Fire Protection Agency directive, NFPA 652, "Standard on the Fundamentals of Combustible Dust", requires all facilities to complete a DHA (Dust Hazard Analysis) by September 2020. Required is a systematic review to identify and evaluate potential dust fire, flash fire and explosion hazards in a process or facility where combustible or explosive material is handled or processed. The result of these analyses will disclose dust collection systems that present a risk of catastrophic failure that will require mitigation. Most facilities do not have a licensed structural engineer or stress analyst on staff that has the experience to perform the analysis to make the equipment safe. This book provides the information required to mitigate equipment, facilities and personnel at risk"--$cProvided by publisher. 606 $aDust control$xEquipment and supplies 606 $aFire prevention$xEquipment and supplies 615 0$aDust control$xEquipment and supplies. 615 0$aFire prevention$xEquipment and supplies. 676 $a628.922 700 $aComer$b Robert Charles$f1934-$01605694 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bUtOrBLW 906 $aBOOK 912 $a9910831072303321 996 $aExplosion vented equipment system protection guide$93931090 997 $aUNINA LEADER 09922nam 2200505 450 001 9910830908903321 005 20230916032655.0 010 $a1-394-17513-2 010 $a1-394-17512-4 035 $a(MiAaPQ)EBC30726183 035 $a(Au-PeEL)EBL30726183 035 $a(EXLCZ)9928128870400041 100 $a20230916d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aFuzzy logic applications in computer science and mathematics /$fedited by Rahul Kar [and four others] 205 $a1st ed. 210 1$aHoboken, NJ :$cJohn Wiley & Sons, Inc.,$d[2023] 210 4$d©2023 215 $a1 online resource (300 pages) 311 08$aPrint version: Kar, Rahul Fuzzy Logic Applications in Computer Science and Mathematics Newark : John Wiley & Sons, Incorporated,c2023 9781394174539 320 $aIncludes bibliographical references and index. 327 $aCover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Decision Making Using Fuzzy Logic Using Multicriteria -- 1.1 Introduction -- 1.2 Fuzzy Logic -- 1.3 Decision Making -- 1.4 Literature Review -- 1.5 Conclusion -- Acknowledgment -- References -- Chapter 2 Application of Fuzzy Logic in the Context of Risk Management -- 2.1 Introduction -- 2.2 Objectives of Risk Management -- 2.3 Improved Risk Estimation -- 2.3.1 Point-Wise Calculations on a Curve -- 2.3.2 Estimation of a Curve -- 2.3.3 Accuracy in Quantification is Raised -- 2.3.4 The Problems with the Basic Quantification Approach -- 2.4 Threat at Quantification Matrix -- 2.4.1 Qualitative Matrix -- 2.4.2 Errors in Scaling -- 2.4.3 Band Width at Various Scales -- 2.5 Fundamental Definitions -- 2.5.1 Positioning Statement -- 2.5.2 Risk Under the Level of Tolerance -- 2.5.3 Risk Elimination -- 2.6 Fuzzy Logic -- 2.7 Risk Related to Fuzzy Matrix -- 2.8 Conclusion -- Bibliography -- Chapter 3 Use of Fuzzy Logic for Controlling Greenhouse Environment: A Study Through the Lens of Web Monitoring -- 3.1 Introduction -- 3.2 Design (Hardware) -- 3.2.1 Sensor for Measuring Soil Moisture -- 3.2.2 Sensor for Measuring Humidity and Temperature -- 3.3 Programming Arduino Mega Board -- 3.3.1 Fuzzification -- 3.3.2 Fuzzy Inference -- 3.3.3 Communication via Remote Connections and a Web Server -- 3.4 Implementation of a Prototype -- 3.5 Results -- 3.6 Conclusion -- Bibliography -- Chapter 4 Fuzzy Logics and Marketing Decisions -- 4.1 Introduction -- 4.2 Literature -- 4.2.1 Fuzzy Logic (FL) -- 4.2.2 FL Application in Marketing -- 4.2.2.1 Communication and Advertising -- 4.2.2.2 Customer Service and Satisfaction -- 4.2.2.3 Customer Segmentation -- 4.2.2.4 CRM -- 4.2.2.5 Pricing -- 4.2.2.6 Evaluation of a Product -- 4.2.2.7 Uncertainty in the Development of New Products. 327 $a4.2.2.8 Decision Making -- 4.2.2.9 Consumer Nation Identity (CNI) -- 4.2.2.10 Quality of Service -- 4.3 Conclusion -- 4.4 Further Studies -- References -- Chapter 5 A Method for Ranking Fuzzy Numbers Based on Their Value, Ambiguity, Fuzziness, and Vagueness -- 5.1 Introduction -- 5.2 Preliminaries -- 5.2.1 Definitions and Concepts -- 5.3 The Designed Method -- 5.4 Validate the Reasonableness of the Suggested Ranking Algorithm -- 5.5 Comparative Analysis and Numerical Examples -- 5.6 Application -- 5.7 Conclusions -- References -- Chapter 6 Evacuation of Attributes to Translucent TNSET in Mathematics Using Rough Topology -- 6.1 Introduction -- 6.2 Basic Concepts of Rough Topology -- 6.2.1 Conditional Attribute -- 6.2.2 Decision Attribute -- 6.2.3 Rough Topology -- 6.2.4 Lower Approximation -- 6.2.5 Upper Approximation -- 6.2.6 Boundary Region -- 6.2.7 Basis -- 6.2.8 Information System -- 6.2.9 Core -- 6.3 Algorithm -- 6.4 Information System -- 6.5 Working Procedure -- 6.6 Conclusion -- References -- Chapter 7 Design of Type-2 Fuzzy Controller for Hybrid Multi-Area Power System -- 7.1 Introduction -- 7.2 Plant Model -- 7.3 Controller Design -- 7.3.1 Proportional Integral Derivative (PID) Controller -- 7.3.2 Fractional Order Proportional Integral Derivative (FOPID) Controller -- 7.3.3 Type-2-Fuzzy Logic -- 7.4 Levenberg-Marquardt Algorithm -- 7.5 Optimization of Controller Parameters Using CASO Algorithm -- 7.6 Result and Analysis -- 7.6.1 Without Disturbances -- 7.6.2 With Disturbances -- 7.7 Conclusion -- Appendix -- References -- Chapter 8 Alzheimer's Detection and Classification Using Fine-Tuned Convolutional Neural Network -- 8.1 Introduction -- 8.2 Literature Review -- 8.3 Methodology -- 8.3.1 Dataset -- 8.3.2 Pre-Processing -- 8.4 Implementation and Results -- 8.5 Conclusion -- References. 327 $aChapter 9 Design of Fuzzy Logic-Based Smart Cars Using Scilab -- 9.1 Introduction -- 9.2 Literature Survey -- 9.2.1 Fuzzy Logic for Automobile Industry -- 9.2.2 Fuzzy Logic for Smart Cars -- 9.2.3 Fuzzy Logic for Driver Behavior Detection -- 9.2.4 Fuzzy Logic Applications for Common Industry -- 9.3 Proposed Fuzzy Inference System for Smart Cars -- 9.3.1 Fuzzification -- 9.3.2 Membership Functions -- 9.3.3 Rule Base -- 9.3.4 Example Rules -- 9.3.5 Defuzzification -- 9.4 Implementation Details and Results -- 9.5 Conclusion and Future Work -- References -- Chapter 10 Financial Planning and Decision Making for Students Using Fuzzy Logic -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 System Architecture -- 10.3.1 Input -- 10.3.2 Fuzzification -- 10.3.3 Membership Function -- 10.3.3.1 Necessity -- 10.3.3.2 Cost Percentage -- 10.3.3.3 Quality -- 10.3.4 Fuzzy Rule Base -- 10.3.5 Fuzzy Output -- 10.3.6 Defuzzification -- 10.4 Conclusion and Future Scope -- References -- Chapter 11 A Novel Fuzzy Logic (FL) Algorithm for the Automatic Detection of Oral Cancer -- 11.1 Introduction -- 11.1.1 Significance of Pre-Processing -- 11.2 Image Enhancement -- 11.3 Gabor Transform -- 11.4 Image Transformation -- 11.5 Adaptive Networks: Architecture -- 11.5.1 Classification of Images -- 11.6 Results and Discussions -- 11.7 Conclusion -- Bibliography -- Chapter 12 A Study on Decision Making of Difficulties Faced by Indian Workers Abroad by Using Rough Topology -- 12.1 Introduction -- 12.1.1 Problems Faced by the Indian Workers -- 12.2 Fundamental Idea of Rough Topology -- 12.2.1 Conditional Attribute -- 12.2.2 Decision Attribute -- 12.2.3 Rough Topology -- 12.2.4 Lower Approximation -- 12.2.5 Upper Approximation -- 12.2.6 Boundary Region -- 12.2.7 Basis -- 12.2.8 Information System -- 12.2.9 Core -- 12.3 Algorithm -- 12.4 Information System -- 12.5 Working Procedure. 327 $a12.6 Conclusion -- References -- Chapter 13 Case Study on Fuzzy Logic: Fuzzy Logic-Based PID Controller to Tune the DC Motor Speed -- 13.1 Introduction -- 13.1.1 DC Motor -- 13.1.2 DC Motor Speed Control Methods -- 13.1.2.1 PID Controller -- 13.1.2.2 Fuzzy-Based PID Controller -- 13.1.2.3 Micro Controller-Based PID Controller -- 13.1.2.4 Genetic Algorithm-Based PID Controller -- 13.2 Literature Review -- 13.2.1 Common Findings -- 13.2.2 Comparative Analysis of Research Works Reviewed -- 13.2.3 Strengths in the Literature Reviewed -- 13.2.4 Weaknesses in the Literature Reviewed -- 13.2.5 Findings in the Literature Reviewed -- 13.3 Design of Fuzzy-Based PID Controller -- 13.3.1 Fuzzy Controller -- 13.3.2 Flowchart for Fuzzy Controller -- 13.3.3 Fuzzy Logic Controller Membership Function and FAM Table -- 13.3.4 Rules for the Fuzzy Controller -- 13.3.5 Simulation Diagram of FLC -- 13.3.6 Fuzzy-Based PID Controller -- 13.3.6.1 Fuzzy Block Design -- 13.3.6.2 Flowchart for Fuzzy-PID Controller -- 13.3.6.3 Simulation Diagram of Fuzzy-PID Controller -- 13.4 Experimental Work and Results Analysis -- 13.5 Conclusion and Future Scope -- References -- Chapter 14 Application of Intuitionistic Fuzzy Network Using Efficient Domination -- 14.1 Introduction -- 14.2 Efficient Domination in Intuitionistic Fuzzy Graph (IFG) -- 14.3 Main Frame Work -- 14.3.1 Construction of IFN from Sub IFN -- 14.4 Secret Key -- 14.4.1 Encryption Algorithm -- 14.4.2 Decryption Algorithm -- 14.5 Illustration -- 14.5.1 Construction of IFN from Sub IFN -- 14.5.2 Secret Key -- 14.5.3 Encryption Algorithm -- 14.5.4 Decryption Algorithm -- 14.6 Conclusion -- References -- Chapter 15 Analysis of Parameters Related to Malaria with Comparative Study on Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps -- 15.1 Introduction -- 15.2 Parameters of Malaria -- 15.3 Fuzzy Cognitive Map. 327 $a15.3.1 Matrix Representation of FCM -- 15.4 Neutrosophic Cognitive Map -- 15.4.1 Matrix Representation of NCM -- 15.5 Comparison and Discussion -- 15.6 Conclusion -- References -- Chapter 16 Applications of Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps on Analysis of Dengue Fever -- 16.1 Introduction -- 16.2 Parameters of Dengue -- 16.3 Fuzzy Cognitive Maps -- 16.3.1 Matrix Representation of FCM -- 16.4 Neutrosophic Cognitive Map -- 16.4.1 Matrix Representation of NCM -- 16.5 Comparison and Discussion -- 16.6 Conclusion -- References -- Chapter 17 A Comprehensive Review and Analysis of the Plethora of Branches of Medical Science and Bioinformatics Based on Fuzzy Logic -- 17.1 Introduction -- 17.2 Previous Work -- 17.3 Fuzzy Logic in Medical Fields and Bioinformatics -- 17.3.1 Applied Fuzzy Logic in Medical Areas -- 17.3.2 Applied Fuzzy Logic in Bioinformatics -- 17.4 Review of Published Work and In-Depth Analysis -- 17.5 Conclusion -- References -- Index -- EULA. 606 $aFuzzy mathematics 606 $aFuzzy systems 606 $aSystem analysis 615 0$aFuzzy mathematics. 615 0$aFuzzy systems. 615 0$aSystem analysis. 676 $a510 702 $aKar$b Rahul 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830908903321 996 $aFuzzy logic applications in computer science and mathematics$94052536 997 $aUNINA