11059nam 2200517 450 99646444220331620231110223842.03-030-84340-8(CKB)4100000012027358(MiAaPQ)EBC6728977(Au-PeEL)EBL6728977(OCoLC)1268441025(PPN)258051094(EXLCZ)99410000001202735820220620d2021 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierComputer information systems and industrial Management 20th international Conference, CISIM 2021, Ełk, Poland, September 24-26, 2021 : proceedings /edited by Khalid Saeed, Jiří DvorskýCham, Switzerland :Springer,[2021]©20211 online resource (497 pages)Lecture Notes in Computer Science ;v.128833-030-84339-4 Includes bibliographical references and index.Intro -- Preface -- Organization -- Keynotes -- Toward the Automation of Security Analysis, Design and Assessment in the Development Process -- Experiments, Methods, Measurements, Instruments: A Few Details -- Logic Constructs with Information Granules: Data Analytics -- Contents -- Invited Paper -- Importance of Variables in Gearbox Diagnostics Using Random Forests and Ensemble Credits -- 1 Introduction -- 2 Methods: The Random Forest and Ensemble Credits -- 2.1 Random Forest as Composed from Binary Decision Trees -- 2.2 The `mtry' and `variables Importance' Options of RFs -- 2.3 Our Proposal: Create an Ensemble of VIPs Providing Credit Scores -- 3 Results of Calculations -- 3.1 Classification and VIPs Using RFs -- 3.2 Computing Credits Scores in an Ensemble Learning -- 3.3 Neural Networks Check the Top FIVE and Top SEVEN Variables -- 4 Summary and Concluding Remarks -- References -- Biometrics and Pattern Recognition Applications -- Typing Pattern Analysis for Fake Profile Detection in Social Media -- 1 Introduction -- 2 Background -- 3 Related Works -- 4 Proposed Work: DEEPID -- 4.1 Data Collection -- 4.2 Data Processing -- 4.3 Multi-view Multi-class Learning -- 5 Analysis -- 5.1 Fake Profile Detection -- 5.2 Social Media Profile Hijacking -- 6 Conclusions -- References -- Determination of the Most Relevant Features to Improve the Performance of RF Classifier in Human Activity Recognition -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Feature Extraction -- 3.2 Process Stages -- 4 Analysis of Results -- 5 Conclusions -- References -- Augmentation of Gait Cycles Using LSTM-MDN Networks in Person Identification System -- 1 Introduction -- 2 State-of-the-Art -- 2.1 IMU Data Augmentation -- 2.2 LSTM-MDN Data Generation -- 3 Methodology -- 3.1 Dataset -- 3.2 Gait Cycle Augmentation -- 3.3 Architecture of the Classifier.4 Identification Results -- 5 Conclusions and Future Work -- References -- Raspberry Pi-Based Device for Finger Veins Collection and the Image Processing-Based Method for Minutiae Extraction -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 The Device for Finger Veins Samples Collection -- 3.2 Image Processing for Finger Veins Feature Extraction -- 4 Experiments -- 5 Conclusions and Future Work -- References -- Identification of Humans Using Hand Clapping Sounds -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Acquisition of Clapping Sounds -- 3.2 Segmentation and Signal Conditioning -- 3.3 Feature Extraction -- 3.4 Machine Learning -- 4 Results -- 4.1 Spectral Analysis -- 4.2 Room-Dependent Versus Room-Independent Tests -- 4.3 Influence of the Number of Clap Sounds Used for Training -- 5 Discussion and Conclusions -- References -- III Computer Information Systems and Security -- Analyzing and Predicting Colombian Undergrads Performance on Saber-Pro Test: A Data Science Approach -- 1 Introduction -- 2 Materials and Methods -- 2.1 DataSet Construction -- 2.2 Dataset Appending -- 2.3 Dataset Merging -- 2.4 Dataset Cleaning -- 3 Exploratory Data Analysis (EDA) -- 4 Construction DashBoard -- 4.1 Architecture -- 4.2 General Panel -- 4.3 University Panel -- 4.4 Location Panel -- 4.5 Predict Scores Panel -- 4.6 Which Factors Matter -- 5 Results -- 6 Conclusions -- References -- Development of Digital Competences of Elementary School Teachers with a Life-Long Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Project Description -- 3.1 Basic Information -- 3.2 Project Details -- 4 Methodology -- 4.1 Pre- and Post-questionnaire Details -- 5 Results Analysis -- 6 Conclusions and Future Research -- References -- Design of Web Application with Dynamic Generation of Forms for Group Decision-Making -- 1 Introduction.2 Problem Description -- 3 Algorithm for Designing of a Web Application to Support Group Decision-Making -- 4 Numerical Testing and Discussion -- 5 Conclusions -- References -- Neural Networks as Tool to Improve the Intrusion Detection System -- 1 Introduction -- 2 Related Techniques -- 2.1 Feature Selection Techniques in IDS Systems -- 2.2 Training and Classification Techniques -- 3 Data Set Processing -- 4 Simulation Scenarios and Results -- 5 Conclusions -- References -- Anonymous Group Signature Scheme with Publicly Verifiable General Access Structure -- 1 Introduction -- 1.1 Related Works -- 1.2 Our Contribution -- 1.3 Paper Organisation -- 2 Certificate-Based Group Signature Scheme with General Access Structure -- 3 Discussion -- 3.1 Security Analysis -- 3.2 Performance Evaluation -- 4 Conclusion -- References -- A Novel Proposal of Using NLP to Analyze IoT Apps Towards Securing User Data -- 1 Introduction -- 2 Related Work -- 3 Research Gap -- 4 Proposed Framework -- 4.1 Outlier Detection with Isolation Forest Algorithm -- 5 Comparative Analysis with CHABADA -- 6 Conclusion -- References -- Addressing the Permutational Flow Shop Scheduling Problem Through Constructive Heuristics: A Statistical Comparison -- 1 Introduction -- 2 Literature Review -- 2.1 Johnson's Rule -- 2.2 Palmer Heuristic -- 2.3 Gupta Heuristic 1 -- 2.4 Gupta Heuristic 2 -- 2.5 CDS Heuristic -- 2.6 NEH Heuristic -- 2.7 PAS Heuristic -- 3 Study Case -- 4 Conclusions and Analysis of Results -- References -- ICBAKE 2021 Workshop -- Search for a Flavor Suited to Beverage by Interactive Genetic Algorithm -- 1 Introduction -- 2 Interactive Genetic Algorithm Creating Scents Suited to User's Feelings -- 2.1 Genetic Algorithm and Interactive Genetic Algorithm -- 2.2 IGA Creating Scents -- 3 Smelling Experiment -- 3.1 Experimental Procedure -- 3.2 Settings of IGA and Source Aromas.4 Results -- 4.1 Results of the Searching Experiment -- 4.2 Result of the Evaluating Experiment -- 5 Discussion -- 6 Conclusion -- References -- Investigation of Facial Preference Using Gaussian Process Preference Learning and Generative Image Model -- 1 Introduction -- 2 Gaussian Process Preference Learning -- 3 Facial Image Generation -- 3.1 StyleGAN2 -- 3.2 Construction of Latent Facial Subspace -- 4 Assessment of Attractiveness -- 4.1 Methods -- 5 Results and Discussion -- 6 Conclusion -- References -- Evaluation of Strong and Weak Signifiers in a Web Interface Using Eye-Tracking Heatmaps and Machine Learning -- 1 Introduction -- 2 Related Works -- 2.1 Usability Evaluation Using Eye-Tracking -- 2.2 Machine Learning -- 2.3 Principal Component Analysis -- 3 Methodology -- 3.1 Proposed Procedure -- 3.2 Gathering of Dataset -- 3.3 Data Preparation -- 3.4 Building Classification Models -- 3.5 Model Evaluation -- 4 Results and Discussion -- 5 Conclusion -- References -- Applying Artificial Bee Colony Algorithm to Interactive Evolutionary Computation -- 1 Introduction -- 2 Proposed Method -- 2.1 ABC Algorithm -- 2.2 Flow of the Proposed Method -- 3 Numerical Simulations -- 3.1 Outline of the Simulation -- 3.2 Multimodal Kansei Evaluation Model -- 4 Results and Discussion -- 4.1 Tuning of Each Parameter -- 4.2 Retrieval for Target Candidate Solutions -- 5 Conclusion -- References -- Emotion Estimating Method by Using Voice and Facial Expression Parameters -- 1 Introduction -- 2 Experiment -- 2.1 Outline of Experiment -- 2.2 Parameter Extraction -- 3 Audiovisual Parameters for Machine Learning -- 3.1 Voice Parameters -- 3.2 Facial Expression Parameters -- 4 Proposal Method of Emotion Estimating Using Machine Learning -- 4.1 Analysis Conditions for Support Vector Machine (SVM) -- 4.2 Classification Results and Consideration -- 5 Conclusions -- References.Industrial Management and other Applications -- Multilayer Perceptron Applied to the IOT Systems for Identification of Saline Wedge in the Magdalena Estuary - Colombia -- 1 Introduction -- 2 Literature Review -- 3 Materials and Methods -- 3.1 Software Architecture Details -- 3.2 Machine Learning Approach -- 4 Model and Materials -- 5 Conclusions -- References -- Assessment of Organizational Policies in a Retail Store Based on a Simulation Model -- 1 Introduction -- 2 Brief Literature Review -- 3 Methodology -- 4 Case Study -- 4.1 Problem Description -- 4.2 Variables -- 4.3 Model Design -- 4.4 Policy Assessment -- 5 Conclusion -- References -- Locating Sea Ambulances to Respond to Emergencies of Vulnerable Populations. Case of Cartagena Bay in Colombia -- 1 Introduction -- 2 Methodology -- 2.1 Characterization of Healthcare Facilities -- 2.2 Characterization of Vulnerable Populations -- 2.3 Optimal Location for Ambulance Boats -- 3 Results -- 4 Conclusions -- References -- Toward a Unique IoT Network via Single Sign-On Protocol and Message Queue -- 1 Introduction -- 2 Background -- 2.1 MQTT Protocol -- 2.2 OAuth Protocol and Single Sign-On -- 2.3 Kafka -- 3 Related Work -- 3.1 OAuth and MQTT -- 3.2 Kafka and MQTT -- 4 IoT Platform Proposal -- 4.1 System Architecture -- 4.2 Software Architecture -- 5 Implementation -- 5.1 Database -- 5.2 Single Sign-On -- 5.3 Mosquitto MQTT Broker -- 5.4 Prototype System Deployment Model -- 6 Evaluation -- 7 Conclusion -- References -- Machine Learning and Artificial Neural Networks -- Multi-objective Approach for Deep Learning in Classification Problems -- 1 Introduction -- 2 Related Work -- 3 Distributed Multi-objective Differential Evolution and Tabu Mutation DMD+ -- 4 Experimental Results -- 5 Conclusions and Remarks -- References.A First Step Towards Automated Species Recognition from Camera Trap Images of Mammals Using AI in a European Temperate Forest.Lecture Notes in Computer Science Computer networksComputer networks.004.6Saeed KhalidHomenda WładysławMiAaPQMiAaPQMiAaPQBOOK996464442203316Computer Information Systems and Industrial Management1947570UNISA05188nam 22006014a 450 991078436070332120230120004348.01-280-96435-997866109643520-08-046983-3(CKB)1000000000349972(EBL)286711(OCoLC)476038600(SSID)ssj0000197122(PQKBManifestationID)11172470(PQKBTitleCode)TC0000197122(PQKBWorkID)10154914(PQKB)11503410(MiAaPQ)EBC286711(Au-PeEL)EBL286711(CaPaEBR)ebr10166986(CaONFJC)MIL96435(EXLCZ)99100000000034997220030321d2003 uy 0engur|n|---|||||txtccrManaging risk and reliability of process plants[electronic resource] /Mark TweeddaleBoston Gulf Professional Pub.c20031 online resource (527 p.)Description based upon print version of record.0-7506-7734-1 Includes bibliographical references and index.front cover; copyright; table of contents; front matter; Acknowledgments; Foreword; body; 1. Introduction; 1.1 THE SITUATION; 1.1.1 Reliability; 1.1.2 Risk; 1.2 HANDLING THE SITUATION; 1.3 MANAGEMENT OF THE HAZARDS, OR THE POTENTIAL FOR MISHAP; 1.4 WHY BOTHER WITH RISK MANAGEMENT, ANYWAY?; 1.4.1 Legal Requirements; 1.4.2 Commercial Requirements; 1.4.3 Moral or Ethical Requirements; 1.4.4 Three Variables: Cost, Risk, and Professional Skill; 1.5 THE BENEFITS OF RISK MANAGEMENT; 1.6 FIELDS OF RISK MANAGEMENT; 1.7 SCOPE OF PROCESS RISK AND RELIABILITY MANAGEMENT; 1.8 THE RISK SPECTRUM1.9 STEPS IN RISK MANAGEMENT OF A PROCESS PLANT1.10 RISK MANAGEMENT WITHOUT NUMBERS; 1.11 SOME ILLUSTRATIONS OF THE APPROACH; 1.12 DEFINE THE CONTEXT; 2. Hazard Identification; 2.1 INTRODUCTION; 2.1.1 Situation; 2.1.2 Sources of Major Hazard; 2.2 TYPES OF IMPACT; 2.3 TYPICAL TYPES OF INCIDENTS LEADING TO THE IMPACT; 2.4 TYPES OF PROCESS PLANT INCIDENTS; 2.4.1 Introduction; 2.4.2 Major Fires; 2.4.3 BLEVEs or Fireballs; 2.4.4 Flash Fires; 2.4.5 Vapor Cloud Explosion; 2.4.6 Dust Explosions; 2.4.7 Other Explosions; 2.4.8 Toxic Gas Escapes; 2.4.9 Toxic Fumes from Fires2.4.10 Chronic Toxic Exposure2.4.11 Damage to the Environment due to Toxic Liquid or Gas Release; 2.4.12 "Domino" Incidents; 2.4.13 Major Equipment Breakdown; 2.4.14 General Comment; 2.5 APPROACHES TO SYSTEMATIC IDENTIFICATION OF HAZARDS AND RISKS; 2.5.1 Introduction; 2.5.2 Identification of Major Hazard Inventories and Activities; 2.5.3 Block Diagram Stage; 2.5.4 Identification of Hazards from a Process Flowsheet; 2.5.5 Detailed Identification of Hazards on an Existing Process Plant; 3. Ranking and Short- Listing of Risks; 3.1 INTRODUCTION; 3.2 THE PARETO PRINCIPLE3.3 TWO CLASSES OF RISKS FOR ATTENTION3.4 RANKING THE HAZARDS AND THE ASSOCIATED RISK SCENARIOS; 3.5 EXAMPLES OF SCORING SYSTEMS FOR USE IN RAPID RANKING; 3.5.1 Introduction; 3.5.2 Consequence Scoring Systems; 3.5.3 Frequency Scoring Systems; 3.6 ESTIMATION OF THE MAGNITUDE OF THE CONSEQUENCES, OR THE FREQUENCY, OF OPERATIONAL LOSSES; 3.6.1 Introduction; 3.6.2 Methods of Estimating for Short-Listing Purposes; 3.6.3 Incidents Arising from Hazardous Materials; 3.6.4 Environmental Damage; 3.6.5 Interruption to Supply of Goods or Services; 3.7 CASE STUDIES; 3.7.1 Introduction3.7.2 Large Petrochemical and Chemical Factory3.7.3 Oil-Gas Separation Facility; 3.7.4 Industrial Estate, Including Chemical Processing Factories; 3.7.5 Steelworks; 3.7.6 Gas/Liquid Separation Plant; 3.8 RISK MANAGEMENT WITHOUT NUMBERS; 3.8.1 Introduction; 3.8.2 Risk Matrix; 3.9 IDENTIFYING THE QUESTIONS TO BE ANSWERED IN THE RISK ASSESSMENT; 4. Risk and Reliability Criteria; 4.1 INTRODUCTION; 4.2 THE PROBLEM WITH "ACCEPTABLE RISK"; 4.3 SOME EVERYDAY RISKS; 4.3.1 Introduction; 4.4 RISKS TO MEMBERS OF THE PUBLIC FROM NEW PLANT; 4.4.1 Individual Risk; 4.4.2 Societal Risk; 4.5 RISKS TO EMPLOYEES4.5.1 "Fatal Accident Rate"There is much specialist material written about different elements of managing risks of hazardous industries, such as hazard identification, risk analysis, and risk management. Managing Risk and Reliability of Process Plants provides a systematic and integrated coverage of all these elements in sufficient detail for the reader to be able to pursue more detailed study of particular elements or topics from a good appreciation of the whole field. The reader would use this book to keep up to date with new developments and, if they are new to the job, to learn more about the subject. The teChemical plantsManagementChemical plantsManagement.660/.2804Tweeddale Mark627464MiAaPQMiAaPQMiAaPQBOOK9910784360703321Managing risk and reliability of process plants1212747UNINA