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[null,null,"Titolo",null,"Advances in Parallel and Distributed Processing, and Applications : Advances in parallel & distributed processing, and applications : proceedings from PDPTA'20, CSC'20, MSV'20, and GCC'20 / / Hamid R. Arabnia [and six others], editors"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-69984-6"]
[null,null,"Descrizione fisica",null,"1 online resource (1201 pages)"]
[null,null,"Collana",null,"Transactions on computational science and computational intelligence"]
[null,null,"Disciplina",null,"004.35"]
[null,null,"Soggetti",null,"Parallel processing (Electronic computers)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Scientific Computing -- CSC 2020 - Program Committee -- Parallel &amp -- Distributed Processing Techniques and Applications -- PDPTA 2020 - Program Committee -- Modeling, Simulation &amp -- Visualization Methods -- MSV 2020 - Program Committee -- Grid, Cloud, &amp -- Cluster Computing -- GCC 2020 - Program Committee -- Contents -- Part I Military and Defense Modeling and Simulation -- Julia and Singularity for High Performance Computing -- 1 Introduction -- 2 The Julia Programming Language -- 2.1 Just-in-Time Compilation -- 2.2 LLVM -- 2.3 Native GPU Support -- 3 Containerization -- 3.1 Differences Between Containers and Virtual Machines -- 3.2 Docker versus Singularity -- 3.3 Singularity and GPUs -- 4 Conclusion -- References -- Trojan Banker Simulation Utilizing Python -- 1 Introduction -- 2 Methodology -- 2.1 Methodology -- 3 Results -- 4 Conclusion -- References -- CovidLock Attack Simulation -- 1 Introduction -- 2 Background and Related Information -- 2.1 Ransomware in the States -- 2.2 Reaction Time -- 3 Overview of the Simulation -- 4 Simulation Methodology -- 5 Comparison to Other Mitigation Methods -- 6 Attack Example -- 7 Conclusion -- References -- The New Office Threat: A Simulation of Watering HoleCyberattacks -- 1 Introduction -- 2 Methodology -- 2.1 Results -- 2.2 Analysis -- 3 Conclusion -- 3.1 Future Research -- References -- Simulation of SYN Flood Attack and Counter-Attack Methods Using Average Connection Times -- 1 Introduction -- 2 Methodology -- 2.1 Results -- 3 Conclusion and Future Work -- "]
[{"$nulls":4},"References -- Part II Computational Intelligence, Data Science, HPC, Optimization and Applications -- Dielectric Polymer Genome: Integrating Valence-Aware Polarizable Reactive Force Fields and Machine Learning -- 1 Introduction -- 2 Method -- 2.1 Valance-Aware ReaxPQ (ReaxPQ-v) Model."]
[{"$nulls":4},"2.2 Computational Framework and Dataset Generation -- 2.3 Machine-Learning Models -- 3 Results and Discussion -- 3.1 Training Dataset -- 3.2 Predictive Accuracy of Machine Learning -- 4 Conclusion -- References -- A Methodology to Boost Data Science in the Context of COVID-19 -- 1 Introduction -- 2 Literature Review -- 3 Proposing a Data Science Model -- 4 Using the Model -- 5 Conclusions -- References -- Shallow SqueezeNext Architecture Implementation on BlueBox2.0 -- 1 Introduction -- 2 BlueBox2.0 Development Platform -- 2.1 Vision Processor (S32V234) -- 2.2 LS-2084A -- 2.3 Real-Time Multisensors Applications (RTMaps) -- 3 Shallow SqueezeNext Architecture -- 4 Shallow SqueezeNext Deployment -- 5 Results -- 5.1 Shallow SqueezeNext Results -- 5.2 BlueBox2.0 Implementation Results -- 6 Conclusion -- References -- Dark Data: Managing Cybersecurity Challenges and Generating Benefits -- 1 Background -- 2 Introduction -- 3 Collection of Dark Data -- 3.1 Dark and Unstructured Data -- 3.2 Dark Data as a Treasure -- 4 Dark Data Risks -- 4.1 Data Challenges with Dark Data -- 4.2 Turn Dark Data into Active Revenues -- 4.3 Make Dark Data to Work -- 5 Recommendations -- 5.1 Analyzing -- 5.2 Benefits of Analyzing Dark Data -- 5.3 Cybersecurity Monitoring -- 5.4 Analytics Technologies -- 6 Methodology -- 6.1 Dark Data User Activities -- 6.1.1 Using Security Log as an Auditing Tool -- 7 Conclusion -- References -- Implementing Modern Security Solutions for Challenges Faced by Businesses in the Internet of Things (IoT) -- 1 Background -- 2 Introduction -- 2.1 IoT Management -- 3 Challenges -- 3.1 Privacy -- 3.2 Security -- 3.3 Limitations -- 3.4 Connectivity -- 3.5 Requirements -- 3.6 Data Storage -- 3.7 Network -- 3.8 Maintenance -- 4 Recommendations -- 4.1 Risk Assessment -- 4.2 Monitoring -- 4.3 Add Security -- 4.4 Cloud and Gateway Architectures."]
[{"$nulls":4},"5 Methodologies -- 5.1 Segmenting Networks -- 5.2 Secure Hardware -- 5.3 VPN -- 5.4 Virtual Local Area Networks (VLANs) -- 6 Conclusion -- References -- Trusted Reviews: Applying Blockchain Technology to Achieve Trusted Reviewing System -- 1 Introduction -- 2 Literature Review -- 2.1 Reviews and Reputation Systems -- 2.2 Applying Blockchain in Reputation System -- 3 Methodology -- 3.1 Trusted Reviews Model -- 3.2 Data Collection -- 4 System Analysis Results -- 4.1 Quantitative Data Analysis -- 4.2 System Requirements -- 4.3 System Design -- 5 Implementation -- 5.1 Code Snippets -- 5.2 Conclusion and Future Studies -- References -- Large-Scale Parallelization of Lattice QCD on Sunway TaihuLight Supercomputer -- 1 Introduction -- 1.1 Lattice Quantum Chromodynamics -- 1.2 SW26010 Heterogeneous Many-Core Processor -- 1.3 Overview of the Paper -- 2 Lattice QCD Calculation Theory -- 3 Innovations Realized -- 3.1 Data Allocation of CPEs -- 3.2 Parallelization Method Based on Multiple Core Groups -- 3.3 Algorithms and Pseudocodes -- 4 Large-Scale Parallel Experiments and Analysis -- 4.1 Experiment Environments -- 4.2 Experiments, Results, and Analysis -- 5 Conclusions -- References -- Part III Scientific Computing, Modeling and Simulation -- Reverse Threat Modeling: A Systematic Threat Identification Method for Deployed Vehicles -- 1 Introduction -- 2 Background -- 2.1 Threat Analysis and Risk Assessment (TARA) -- 3 Related Work -- 3.1 TARA Methods -- 4 Approach -- 5 Example -- 6 Conclusion -- References -- PRNG-Broker: A High-Performance Broker "]
[{"$nulls":4},"to Supply Parallel Streams of Pseudorandom Numbers for Large-Scale Simulations -- 1 Introduction -- 2 Random Number Generation -- 2.1 Popular PRNG Algorithms -- 2.2 Transforming Uniformly Distributed PRNs -- 2.3 PRNG Libraries -- 3 The PRNG-Broker -- 3.1 Core of the Broker -- 3.2 Hardware-Aware PRN Generation."]
[{"$nulls":4},"3.3 Libraries and the PRNG-Broker API -- 4 Scientific Data Analyses -- 5 Results and Discussion -- 5.1 Test Beds and Associated Case Studies -- 5.2 Performance of the Case Studies with the PRNG-Broker -- 5.3 Comparative Performance on Different Servers -- 6 Conclusions and Future Work -- References -- Numerical Modeling of a Viscous Incompressible Fluid Flow in a Channel with a Step -- 1 Introduction -- 2 Mathematical Problem -- 3 The Difference Schemes -- 4 Comparison of Results -- 4.1 Effect of Step Height on the Flow -- 5 Conclusion -- References -- Modeling, Simulation, and Verification for Structural Stability and Vibration Reduction of Gantry Robots for Shipyard Welding Automation Using ANSYS Workbench® and Recurdyn® -- 1 Introduction -- 2 Modeling of Three-Axes Cartesian Gantry Robot -- 3 Structural Stability Simulation of Gantry Robot -- 4 Verification for Vibration Reduction of Gantry Robots -- 5 Conclusion -- References -- Long Short-Term Memory Neural Network on the Trajectory Computing of Direct Dynamics Simulation -- 1 Introduction -- 2 Methodology -- 2.1 Prediction-Correction Algorith -- 2.2 Long Short-Term Memory -- 2.3 Model -- 3 Experimental Results -- 4 Conclusion and Future Work -- 5 Acknowledgment -- References -- Evaluating the Effect of Compensators and Load Model on Performance of Renewable and Nonrenewable DGs -- 1 Introduction -- 2 Problem Description -- 2.1 Distributed Generation -- 2.2 Compensators -- 2.3 Load Model of Network -- 2.4 Objective Functions -- 2.5 Technical Index -- 2.6 Economic Index -- 2.7 Environmental Index -- 2.8 Optimization Method -- 2.9 Numerical Results -- 3 Conclusion -- References -- The Caloric Curve of Polymers from the Adaptive Tempering Monte Carlo Method -- 1 Introduction -- 2 Methods -- 3 Results -- 3.1 Parallelization Protocol for the PPy Condensed Phase Analysis."]
[{"$nulls":4},"3.2 PPy Thermodynamic Properties -- 4 Conclusion -- References -- Part IV Scientific Computing, Computational Science, and Applications -- A New Technique of Invariant Statistical Embedding and Averaging in Terms of Pivots for Improvement of Statistical Decisions Under Parametric Uncertainty -- 1 Introduction -- 2 Preliminaries -- 3 Technique of Invariant Statistical Embedding and Averaging in Terms of Pivotal Quantities (ISE&amp -- APQ) -- 4 Comparison of Statistical Decision Rules -- 5 Example 1 (Quantile Estimation) -- 6 Characterization of Uniformly Non-dominated Decision Rules -- 7 Example 2 (Constructing Shortest-Length Confidence Intervals) -- 8 Example 3 (Constructing Within-Sample Prediction Limits) -- 9 Conclusion -- References -- A Note on the Sensitivity of Generic Approximate Sparse Pseudoinverse Matrix for Solving Linear Least Squares Problems -- 1 Introduction -- 2 Explicit Preconditioned Conjugate Gradient Least Squares Method -- 3 Generic Approximate Sparse Pseudoinverse Scheme -- 4 On Theoretical Estimates for the Sensitivity of the Generic Sparse Approximate Pseudoinverse Matrix -- 5 Numerical Results -- 6 Conclusion -- References -- Undergraduate Research: Bladerunner -- 1 Introduction -- 2 Summary -- 3 Software -- 4 Results (Table 1) -- 4.1 Programming Results -- 5 Conclusion -- Comparison of the IaaS Security Available from the Top Three Cloud Providers -- 1 Introduction -- 2 Related Work -- 3 Background on Security Threats -- 4 Problem Statement and Discussion -- 4.1 Problem 1: Agile Programming -- 4.2 Problem 2: Security Training for Employees -- 4.3 Problem 3: Security Support for Cloud IaaS -- 5 "]
[{"$nulls":4},"Evaluation -- 5.1 Data Center Locality -- 5.2 Uptime/Availability of Platform -- 5.3 Encryption at Rest -- 5.4 Encryption in Transit -- 5.5 Security Common to Top Three Cloud Platforms -- 6 Recommendations."]
[{"$nulls":4},"6.1 Use Multiple Cloud Providers."]