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• Architecture, Networks, and Storage.- Microarchitecture of a Configurable High-radix Router for Exascale Interconnect.- BluesMPI: Efficient MPI Non-blocking Alltoall Offloading Designs on Modern BlueField Smart NICs.- Lessons Learned from Accelerating Quicksilver on Programmable Integrated Unified Memory Architecture (PIUMA) and How that's Different from CPU.- A Hierarchical Task Scheduler for Heterogeneous Computing.- Machine Learning, AI, and Emerging Technologies.- Auto-Precision Scaling for Distributed Deep Learning.- FPGA Acceleration of Number Theoretic Transform.- Designing a ROCm-aware MPI Library for AMD GPUs: Early Experiences.- A Tunable Implementation of Quality-of-Service Classes for HPC Networks.- Scalability of Streaming Anomaly Detection in an Unbounded Key Space using Migrating Threads.- HTA: A Scalable High-Throughput Accelerator for Irregular HPC Workloads.- Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems.- HPC Algorithms and Applications.- COSTA: Communication-Optimal Shuffle and Transpose Algorithm with Process Relabeling.- Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers.- Evaluation of the NEC Vector Engine for Legacy CFD Codes.- Distributed Sparse Block Grids on GPUs.- iPUG: Accelerating Breadth-First Graph Traversals using Manycore Graphcore IPUs.- Performance Modeling, Evaluation, and Analysis.- Optimizing GPU-enhanced HPC System and Cloud Procurements for Scientific Workloads.- A Performance Analysis of Modern Parallel Programming Models Using a Compute-Bound Application.- Analytic Modeling of Idle Waves in Parallel Programs: Communication, Cluster Topology, and Noise Impact.- Performance of the Supercomputer Fugaku for Breadth-First Search in Graph500 Benchmark.- Under the Hood of SYCL - An Initial Performance Analysis With an Unstructured-mesh CFD Application.- Characterizing Containerized HPC Application Performance at Petascale on CPU and GPU Architectures.- Ubiquitous Performance Analysis.- Programming Environments and Systems Software.- Artemis: Automatic Runtime Tuning of Parallel Execution Parameters Using Machine Learning.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 36th International Conference on High Performance Computing, ISC High Performance 2021, held virtually in June/July 2021.The 24 full papers presented were carefully reviewed and selected from 74 submissions. The papers cover a broad range of topics such as architecture, networks, and storage; machine learning, AI, and emerging technologies; HPC algorithms and applications; performance modeling, evaluation, and analysis; and programming environments and systems software.
(source: Nielsen Book Data)

• Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis
• Machine-Learning-Based Control of Perturbed and Heated Channel Flows
• Novel DNNs for Stiff ODEs with Applications to Chemically Reacting Flows
• Lettuce: PyTorch-based Lattice Boltzmann Framework
• Reservoir computing in reduced order modeling for chaotic dynamical systems
• Film cooling prediction and optimization based on deconvolution neural network
• Turbomachinery Blade Surrogate Modeling using Deep Learning
• A Data-driven Wall-shear Stress Model for LES using Gradient Boosted Decision Trees
• Nonlinear mode decomposition and reduced-order modeling for three-dimensional cylinder flow by distributed learning on Fugaku
• Using physics-informed enhanced super-resolution generative adversarial networks to reconstruct mixture fraction statistics of turbulent jet flows
• HPC I/O in the Data Center
• Toward a Workflow for Identifying Jobs with Similar I/O Behavior Utilizing Time Series Analysis
• H3: An Application-Level, Low-Overhead Object Store
• Compiler-assisted Correctness Checking and Performance Optimization for HPC
• Automatic partitioning of MPI operations in MPI+OpenMP applications
• heimdallr: Improving Compile Time Correctness Checking for Message Passing with Rust
• Potential of Interpreter Specialization for Data Analysis
• Refactoring for Performance with Semantic Patching: Case Study with Recipes
• Negative Perceptions About the Applicability of Source-to-Source Compilers in HPC: A Literature Review
• Machine Learning on HPC Systems
• Automatic Tuning of Tensorflow's CPU Backend using Gradient-Free Optimization Algorithms
• MSM: Multi-Stage Multicuts for Scalable Image Clustering
• OmniOpt
• a tool for hyperparameter optimization on HPC
• Parallel/distributed intelligent hyperparameters search for GANs
• Machine learning for generic energy models of high performance computing resources
• Fourth International Workshop on Interoperability of Supercomputing and Cloud Technologies
• Automation for Data-Driven Research with the NERSC Superfacility API
• A Middleware Supporting Data Movement inComplex and Software-Defined Storage and Memory Architectures
• Second International Workshop on Monitoring and Operational Data Analytics
• An Operational Data Collecting and Monitoring Platform for Fugaku: System Overviews and Case Studies in the Prelaunch Service Period
• An Explainable Model for Fault Detection in HPC Systems
• Sixteenth Workshop on Virtualization in HighƯ-Performance Cloud Computing
• A Scalable Cloud Deployment Architecture for High-Performance Real-Time Online Interactive Applications
• Leveraging HW approximation for exploiting performance-energy trade-offs within the edge-cloud computing continuum
• Datashim and its applications in Bioinformatics
• FaaS and Curious: Performance implications of serverless functions on edge computing platforms
• Differentiated performance in NoSQL database access for hybrid Cloud-HPC workloads
• Deep Learning on Supercomputers
• JUWELS Booster
• A Supercomputer for Large-Scale AI Research
• Fifth International Workshop on In Situ Visualization
• In Situ Visualization of WRF Data using Universal Data Junction
• Catalyst Revised: Rethinking the ParaView In Situ Analysis and Visualization API
• Fides: A General Purpose Data Model Library for Streaming Data.-Including in-situ visualization and analysis in PDI.

This book constitutes the refereed post-conference proceedings of 9 workshops held at the 35th International ISC High Performance 2021 Conference, in Frankfurt, Germany, in June-July 2021: Second International Workshop on the Application of Machine Learning Techniques to Computational Fluid Dynamics and Solid Mechanics Simulations and Analysis; HPC-IODC: HPC I/O in the Data Center Workshop; Compiler-assisted Correctness Checking and Performance Optimization for HPC; Machine Learning on HPC Systems; 4th International Workshop on Interoperability of Supercomputing and Cloud Technologies; 2nd International Workshop on Monitoring and Operational Data Analytics; 16th Workshop on Virtualization in High­-Performance Cloud Computing; Deep Learning on Supercomputers; 5th International Workshop on In Situ Visualization. The 35 papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include high-performance computing (HPC), computer architecture and hardware, programming models, system software, performance analysis and modeling, compiler analysis and optimization techniques, software sustainability, scientific applications, deep learning.

• Fostering Computational Thinking.- Computational Thinking in Context across Curriculum: Students' and Teacher's Perspective.- Towards Classification of Interactive Non-Programming Tasks Promoting Computational Thinking.- Tell, Draw & Code Teachers' intention to a Narrative Introduction of Computational Thinking.- Programming Education.- First Programming Course in Business Studies: Content, Approach, and Achievement.- Why young programmers should make game art: a study from a game-making course.- Teaching Recursion in High School { A Constructive Approach.- Advancing Computing Education.- A Multi-Dimensional Approach to Categorize Short Tasks.- Girls' summer school for physical computing: methodology and acceptance issues.- Towards a compulsory computing curriculum at primary and lower-secondary schools: the case of Czechia.- Teachers' Professional Development.- Professional Development for in-service teachers of programming: Evaluation of a university level program.- Encouraging Task Creation among Programming Teachers in Primary Schools.- Problems, professional development and reflection: Experiences of High-School, Computer Science teachers in Serbia.
• (source: Nielsen Book Data)

This book constitutes the proceedings of the 14th International Conference on Informatics in Schools: Situation, Evolution and Perspectives, ISSEP 2021, held in Nijmegen, The Netherlands, in November 2020. Due to COVID-19 related travelling restrictions the conference had to be switched to online format. The 12 full papers presented were carefully reviewed and selected from 29 submissions. They are organized in topical sections named: Fostering Computational Thinking, Programming Education, Advancing Computing Education, and Teachers' Professional Development.
(source: Nielsen Book Data)

• Supercharging Plant Configurations using Z3
• Why You Should Constrain Your Machine Learned Models
• Contextual Optimization: Bridging Machine Learning and Operations
• A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects
• Strengthening of feasibility cuts in logic-based Benders decomposition
• Learning Variable Activity Initialisation for Lazy Clause Generation Solvers
• A*-based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem
• Partitioning Students into Cohorts during COVID-19
• A Two-Phases Exact Algorithm for Optimization of Neural Network Ensemble
• Complete Symmetry Breaking Constraints for the Class of Uniquely Hamiltonian Graphs
• Heavy-Tails and Randomized Restarting Beam Search in Goal-Oriented Neural Sequence Decoding
• Combining Constraint Programming and Temporal Decomposition Approaches
• Scheduling of an Industrial Formulation Plant
• The Traveling Social Golfer Problem: the case of the Volleyball Nations League
• Towards a Compact SAT-based Encoding of Itemset Mining Tasks
• A Pipe Routing Hybrid Approach based on A-Star Search and Linear Programming
• MDDs boost equation solving on discrete dynamical systems
• Variable Ordering for Decision Diagrams: A Portfolio Approach
• Two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors
• Improving the Filtering of Branch-And-Bound MDD solver
• On the Usefulness of Linear Modular Arithmetic in Constraint Programming
• Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem
• Learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems
• Between Steps: Intermediate Relaxations between big-M and Convex Hull Formulations
• Logic-Based Benders Decomposition for an Inter-modal Transportation Problem
• Checking Constraint Satisfaction
• Finding Subgraphs with Side Constraints
• Short-term scheduling of production fleets in underground mines using CP-based LNS
• Learning to Reduce State-Expanded Networks for Multi-Activity Shift Scheduling
• SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
• Learning to Sparsify Travelling Salesman Problem Instances
• Optimized Item Selection to Boost Exploration for Recommender Systems
• Improving Branch-and-Bound using Decision Diagrams and Reinforcement Learning
• Physician Scheduling During a Pandemic.

This volume LNCS 12735 constitutes the papers of the 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, which was held in Vienna, Austria, in 2021. Due to the COVID-19 pandemic the conference was held online. The 30 regular papers presented were carefully reviewed and selected from a total of 75 submissions. The conference program included a Master Class on the topic "Explanation and Verification of Machine Learning Models."

• STRESS - Introduction.- An Introduction to Graphical Modeling of CI/CD Workflows with Rig.- Pyrus: an Online Modeling Environment for No-Code Data-Analytics Service Composition.- Integrating External Services in DIME.- Asking Why.- Formal Methods for a Digital Industry: Industrial Day at ISoLA 2021.- Agile Business Engineering: From Transformation Towards Continuous Innovation.- Towards Living Canvases.- Use Cases for Simulation in the Development of Automated Driving Systems.- Simulation-based Elicitation of Accuracy Requirements for the Environmental Perception of Autonomous Vehicles.- DSLs and Middleware Platforms in a Model-Driven Development Approach for Secure Predictive Maintenance Systems in Smart Factories.- From Requirements to Executable Rules: An Ensemble of Domain-Specific Languages for Programming Cyber-Physical Systems in Warehouse Logistics.- Mining Data Quality Rules for Data Migrations: A Case Study on Material Master Data.- Programming - What is Next?.- Low-Code is Often High-Code, So We Must Design Low-Code Platforms to Enable Proper Software Engineering.- Time for All Programs, Not Just Real-Time Programs.- Integrated Modeling and Development of Component-Based Embedded Software in Scala.- Slang: The Sireum Programming Language.- HAMR: An AADL Multi-Platform Code Generation Toolset.- Fundamental Constructs in Programming Languages.- Introducing Dynamical Systems and Chaos Early in Computer Science and Software Engineering Education can Help Advance Theory and Practice of Software Development and Computing.- GATE: Gradual Effect Types.- Fixing Classification: A Viewpoint-based Approach.- The Future of Programming and Modelling: a Vision.- Towards Model-based Intent-Driven Adaptive Software.- The Interoperability Challenge: Building a model driven Digital Thread platform for CPS.- Programming vs. That Thing Subject Matter Experts Do.- Aligned, Purpose-Driven Cooperation: The Future Way of System Development.- RAILS: Roadmaps for AI integration in the raiL Sector.- A Journey through Software Model Checking of Interlocking Programs.- Supporting the Development of Hybrid ERTMS/ETCS Level 3 with Formal Modelling, Analysis and Simulation.- Formal Methods in Railway Signalling Infrastructure Standardisation Processes.- sVerify: Verifying Smart Contracts through Lazy Annotation and Learning.- Verifying temporal properties of stigmergic collective systems using CADP.
• (source: Nielsen Book Data)

This book constitutes contributions of the ISoLA 2021 associated events. Altogether, ISoLA 2021 comprises contributions from the proceedings originally foreseen for ISoLA 2020 collected in 4 volumes, LNCS 12476: Verification Principles, LNCS 12477: Engineering Principles, LNCS 12478: Applications, and LNCS 12479: Tools and Trends. The contributions included in this volume were organized in the following topical sections: 6th International School on Tool-Based Rigorous Engineering of Software Systems; Industrial Track; Programming: What is Next; Software Verification Tools; Rigorous Engineering of Collective Adaptive Systems. .
(source: Nielsen Book Data)

• Transition Graphs of Reversible Reaction Systems.- Communicating Reaction Systems with Direct Communication.- Generalized Forbidding Matrix Grammars and their Membrane Computing Perspective.- Parallel Contextual Array Insertion Deletion P Systems and Tabled Matrix Grammars.- Triangular Array Token Petri Net and P System.- P System as a Computing Tool for Embedded Feature Selection and Classification Method for Microarray Cancer Data.- Evolutionary P Systems: the Notion and an Example.- Partial Array Token Petri Net and P System.- Certain State Sequences Defined by P Systems with Reactions.- On Numerical 2D P Colonies with the Blackboard and the Gray Wolf Algorithm.
• (source: Nielsen Book Data)

This book constitutes the refereed post-conference proceedings of the 21st International Conference on Membrane Computing, CMC 2020, held as a virtual event, in September 2020. The 10 full papers presented were selected from 31 submissions. The papers deal with all aspects on membrane computing and related areas.
(source: Nielsen Book Data)

• Model Checking, Synthesis, and Learning.- From Linear Temporal Logics to Buchi Automata: The Early and Simple Principle.- Cause-Effect Reaction Latency In Real-Time Systems.- Quantitative Analysis of Interval Markov Chains.- Regular Model Checking: Evolution and Perspectives.- Regular Model Checking Revisited.- High-Level Representation of Benchmark Families for Petri Games.- Towards Engineering Digital Twinsby Active Behaviour Mining.- Never-Stop Context-Free Learning.- A Taxonomy and Reductions for Common Register Automata Formalisms.
• (source: Nielsen Book Data)

This Festschrift, dedicated to Bengt Jonsson on the occasion of his 60th birthday, contains papers written by many of his friends and collaborators.Bengt has made major contributions covering a wide range of topics including verification and learning. His works on verification, in finite state systems, learning, testing, probabilistic systems, timed systems, and distributed systems reflect both the diversity and the depth of his research. Besides being an excellent scientist, Bengt is also a leader who has greatly influenced the careers of both his students and his colleagues. His main focus throughout his career has been in the area of formal methods, and the research papers dedicated to him in this volume address related topics, particularly related to model checking, temporal logic, and automata learning.
(source: Nielsen Book Data)

• Theory and Algorithms.- Metric Learning Based Vision Transformer for Product Matching.- Stochastic Recurrent Neural Network for Multistep Time Series Forecasting.- Speaker Verification with Disentangled Self-Attention.- Multi Modal Normalization.- A Focally Discriminative Loss for Unsupervised Domain Adaptation.- Automatic Drum Transcription with Label Augmentation using Convolutional Neural Networks.- Adaptive Curriculum Learning for Semi-Supervised Segmentation of 3D CT-Scans.- Genetic Algorithm and Distinctiveness Pruning in the Shallow Networks for VehicleX.- Stack Multiple Shallow Autoencoders into A Strong One: A New Reconstruction-based Method to Detect Anomaly.- Learning Discriminative Representation with Attention and Diversity for Large-scale Face Recognition.- Multi-task Perceptual Occlusion Face Detection with Semantic Attention Network.- RAIDU-Net: Image Inpainting via Residual Attention Fusion and Gated Information Distillation.- Sentence Rewriting with Few-Shot Learning for Document-Level Event Coreference Resolution.- A Novel Metric Learning Framework for Semi-supervised Domain Adaptation.- Generating Adversarial Examples by Distributed Upsampling.- CPSAM: Channel and Position Squeeze Attention Module.- A Multi-Channel Graph Attention Network for Chinese NER.- GSNESR: A Global Social Network Embedding Approach for Social Recommendation.- Classification Models for Medical Data with Interpretative Rules.- Contrastive Goal Grouping for Policy Generalization in Goal-Conditioned Reinforcement Learning.- Global Fusion Capsule Network with Pairwise-Relation Attention Graph Routing.- MA-GAN: A Method Based on Generative Adversarial Network for Calligraphy Morphing.- One-Stage Open Set Object Detection with Prototype Learning.- Aesthetic-aware Recommender System for Online Fashion Products.- DAFD: Domain Adaptation Framework for Fake News Detection.- Document Image Classification Method based on Graph Convolutional Network.- Continual Learning of 3D Point Cloud Generators.- Attention-Based 3D ResNet for Detection of Alzheimer's Disease Process.- Generation of a Large-Scale Line Image Dataset with Ground Truth Texts from Page-Level Autograph Documents.- DAP-BERT: Differentiable Architecture Pruning of BERT.- Trash Detection On Water Channels.- Tri-Transformer Hawkes Process: Three Heads are better than one.- PhenoDeep: A deep Learning-based approach for detecting reproductive organs from digitized herbarium specimen images.- Document-level Event Factuality Identification using Negation and Speculation Scope.- Dynamic Network Embedding by Time-Relaxed Temporal Random Walk.- Dual-band Maritime Ship Classification based on Multi-layer Convolutional Features and Bayesian Decision.- Context-Based Anomaly Detection via Spatial Attributed Graphs in Human Monitoring.- Domain-Adaptation Person Re-Identification via Style Translation and Clustering.- Multimodal Named Entity Recognition Via Co-attention-based Method with Dynamic Visual Concept Expansion.- Ego Networks.- Cross-modal based Person Re-Identification via Channel Exchange and adversarial Learning.- SPBERT: An Efficient Pre-training BERT on SPARQL Queries for Question Answering over Knowledge Graphs.- Deep Neuroevolution: Training Neural Networks using a Matrix-free Evolution Strategy.- Weighted P-Rank: A Weighted Article Ranking Algorithm Based on a Heterogeneous Scholarly Network.- Clustering Friendly Dictionary Learning.- Understanding Test-Time Augmentation.- SphereCF: Sphere Embedding for Collaborative Filtering.- Concordant Contrastive Learning for Semi-supervised Node Classification on Graph.- Improving Shallow Neural Networks via Local and Global Normalization.- Underwater Acoustic Target Recognition with Fusion Feature.- Evaluating Data Characterization Measures for Clustering Problems in Meta-learning.- ShallowNet: An Efficient Lightweight Text Detection Network Based on Instance Count-aware Supervision Information.- Image Periodization for Convolutional Neural Networks.- BCN-GCN: A Novel Brain Connectivity Network Classification Method via Graph Convolution Neural Network for Alzheimer's Disease.- Triplet Mapping for Continuously Knowledge Distillation.- A Prediction-Augmented AutoEncoder for Multivariate Time Series Anomaly Detection.
• (source: Nielsen Book Data)

• Cognitive Neurosciences.- A Novel Binary BCI Systems Based on Non-oddball Auditory and Visual Paradigms.- A Just-In-Time Compilation Approach for Neural Dynamics Simulation.- STCN-GR: Spatial-Temporal Convolutional Networks for Surface-Electromyography-Based Gesture Recognition.- Gradient descent learning algorithm based on spike selection mechanism for multilayer spiking neural networks.- Learning to Coordinate via Multiple Graph Neural Networks.- A Reinforcement Learning Approach for Abductive Natural Language Generation.- DFFCN: Dual Flow Fusion Convolutional Network for Micro Expression Recognition.- AUPro: Multi-label Facial Action Unit Proposal Generation for Sequence-level Analysis.- Deep kernelized network for fine-grained recognition.- Semantic Perception Swarm Policy with Deep Reinforcement Learning.- Reliable, Robust, and Secure Machine Learning Algorithms Open-Set Recognition with Dual Probability Learning.- How Much Do Synthetic Datasets Matter In Handwritten Text Recognition.- PCMO: Partial Classification from CNN-Based Model Outputs.- Multi-branch Fusion Fully Convolutional Network for Person Re-Identification.- Fast Organization of Objects Spatial Positions in Manipulator Space from Single RGB-D Camera.- EvoBA: An Evolution Strategy as a Strong Baseline for Black-Box Adversarial Attacks.- A Novel Oversampling Technique for Imbalanced Learning Based on SMOTE and Genetic Algorithm.- Dy-Drl2Op: Learning Heuristics for TSP on the Dynamic Graph via Deep Reinforcement Learning.- Multi-label classification of hyperspectral images based on label-specific feature fusion.- A Novel Multi-Scale Key-Point Detector Using Residual Dense Block and Coordinate Attention.- Alleviating Catastrophic Interference in Online Learning via Varying Scale of Backward Queried Data.- Construction and Reasoning for Interval-Valued EBRB Systems.- Theory and Applications of Natural Computing Paradigms.- Brain-mimetic Kernel: A Kernel Constructed from Human fMRI Signals Enabling a Brain-mimetic Visual Recognition Algorithm.- Predominant Sense Acquisition with a Neural Random Walk Model.- Processing-response dependence on the on-chip readout positions in spin-wave reservoir computing.- Advances in deep and shallow machine learning algorithms for biomedical data and imaging.- A Multi-Task Learning Scheme for Motor Imagery Signal Classification.- An End-to-End Hemisphere Discrepancy Network for Subject-Independent Motor Imagery Classification.- Multi-domain Abdomen Image Alignment Based on Joint Network of Registration and Synthesis.- Coordinate Attention Residual Deformable U-Net for Vessel Segmentation.- Gated Channel Attention Network for Cataract Classification on AS-OCT Image.- Overcoming Data Scarcity for Coronary Vessel Segmentation Through Self-Supervised Pre-Training.- Self-Attention Long-Term Dependency Modelling in Electroencephalography Sleep Stage Prediction.- ReCal-Net: Joint Region-Channel-Wise Calibrated Network for Semantic Segmentation in Cataract Surgery Videos.- Enhancing Dermoscopic Features Classification in Images Using Invariant Dataset Augmentation and Convolutional Neural Networks.- Ensembles of Randomized Neural Networks for Pattern-based Time Series Forecasting.- Grouped Echo State Network with Late Fusion for Speech Emotion Recognition.- Applications.- MPANet: Multi-level Progressive Aggregation Network for Crowd Counting.- AFLLC: A Novel Active Contour Model based on Adaptive Fractional Order Differentiation and Local Linearly Constrained Bias Field.- DA-GCN: A Dependency-Aware Graph Convolutional Network for Emotion Recognition in Conversations.- Semi-Supervised Learning with Conditional GANs for Blind Generated Image Quality Assessment.- Uncertainty-Aware Domain Adaptation for Action Recognition.- Free-Form Image Inpainting with Separable Gate Encoder-decoder Network.- BERTDAN: Question-Answer Dual Attention Fusion Networks With Pre-trained Models for Answer Selection.- Rethinking the Effectiveness of Selective Attention in Neural Networks.- An Attention Method to Introduce Prior Knowledge in Dialogue State Tracking.- Effect of Input Noise Dimension in GANs.- Wiper Arm Recognition using YOLOv4.- Context Aware Joint Modeling of Domain Classification, Intent Detection and Slot Filling with Zero-shot Intent Detection Approach.- Constrained Generative Model for EEG Signals Generation.- Top-Rank Learning Robust to Outliers.- Novel GAN Inversion Model with Latent Space Constraints for Face Reconstruction.- Edge Guided Attention Based Densely Connected Network for Single Image Super-Resolution.- An Agent-Based Market Simulator for Back-testing Deep Reinforcement Learning Based Trade Execution Strategies.- Looking beyond the haze: A Pyramid Fusion Approach.- DGCN-rs: a Dilated Graph Convolutional Networks Jointly Modelling Relation and Semantic for Multi-Event Forecasting.- Training Graph Convolutional Neural Network against Label Noise.- An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes.
• (source: Nielsen Book Data)

The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
(source: Nielsen Book Data)

• Theory and Algorithms.- LSMVC: Low-rank Semi-supervised Multi-view Clustering for Special Equipment Safety Warning.- Single-Skeleton and Dual-Skeleton Hypergraph Convolution Neural Networks for Skeleton-Based Action Recognition.- Multi-Reservoir Echo State Network with Multiple-Size Input Time Slices for Nonlinear Time-Series Prediction.- Transformer with Prior Language Knowledge for Image Captioning.- Continual Learning with Laplace Operator based Node-Importance Dynamic Architecture Neural Network.- Improving generalization of reinforcement learning for multi-agent combating games.- Gradient Boosting Forest: A Two-Stage Ensemble Method Enabling Federated Learning of GBDTs.- Random Neural Graph Generation with Structure Evolution.- MatchMaker: Aspect-Based Sentiment Classification via Mutual Information.- PathSAGE: Spatial Graph Attention Neural Networks With Random Path Sampling.- Label Preserved Heterogeneous Network Embedding.- Spatio-Temporal Dynamic Multi-Graph Attention Network for Ride-hailing Demand Prediction.- An Implicit Learning Approach for Solving the Nurse Scheduling Problem.- Improving Goal-Oriented Visual Dialogue by Asking Fewer Questions.- Balance Between Performance and Robustness of Recurrent Neural Networks brought by Brain-inspired Constraints on Initial Structure.- Single-Image Smoker Detection by Human-Object Interaction with Post-Refinement.- A Lightweight Multi-scale Feature Fusion Network For Real-time Semantic Segmentation.- Multi-view Fractional Deep Canonical Correlation Analysis for Subspace Clustering.- Handling the Deviation from Isometry between Domains and Languages in Word Embeddings: Applications to Biomedical Text Translation.- Inference in Neural Networks Using Conditional Mean-Field Methods.- Associative Graphs for Fine-Grained Text Sentiment Analysis.- k-Winners-Take-All Ensemble Neural Network.- Performance Improvement of FORCE Learning for Chaotic Echo State Networks.- Generative Adversarial Domain Generalization via Cross-Task Feature Attention Learning for Prostate Segmentation.- Context-based Deep Learning Architecture with Optimal Integration Layer for Image Parsing.- Kernelized Transfer Feature Learning on Manifolds.- Data-Free Knowledge Distillation with Positive-Unlabeled Learning.- Manifold Discriminative Transfer Learning for Unsupervised Domain Adaptation.- Training-Free Multi-Objective Evolutionary Neural Architecture Search via Neural Tangent Kernel and Number of Linear Regions.- Neural Network Pruning via Genetic Wavelet Channel Search.- Binary Label-aware Transfer Learning for Cross-domain Slot Filling.- Condition-Invariant Physical Adversarial Attacks via Pixel-wise Adversarial Learning.- Multiple Partitions Alignment with Adaptive Similarity Learning.- Recommending best course of treatment based on similarities of prognostic markers.- Generative Adversarial Negative Imitation Learning from Noisy Demonstrations.- Detecting Helmets on Motorcyclists by Deep Neural Networks with a Dual-Detection Scheme.- Short-Long Correlation Based Graph Neural Networks for Residential Load Forecasting.- Disentangled Feature Network for Fine-Grained Recognition.- Large-Scale Topological Radar Localization Using Learned Descriptors.- Rethinking binary hyperparameters for deep transfer learning.- Human Centred Computing.- Hierarchical Features Integration and Attention Iteration Network for Juvenile Refractive Power Prediction.- Stress Recognition in Thermal Videos using Bi-Directional Long-Term Recurrent Convolutional Neural Networks.- StressNet: A Deep Neural Network based on Dynamic Dropout Layers for Stress Recognition.- Analyzing Vietnamese Legal Questions using Deep Neural Networks with Biaffine Classifiers.- BenAV: A Bengali Audio-Visual Corpus for Visual Speech Recognition.- Investigation of Different G2P Schemes for Speech Recognition in Sanskrit.- GRU with Level-Aware Attention for Rumor Early Detection in Social Networks.- Convolutional Feature-interacted Factorization Machines for Sparse Contextual Prediction.- A Lightweight Multidimensional Self-Attention Network for Fine-grained Action Recognition.- Unsupervised Domain Adaptation with Self-selected Active Learning for Cross-domain OCT Image Segmentation.- Adaptive Graph Convolutional Network with Prior Knowledge for Action Recognition.- Self-Adaptive Graph Neural Networks for Personalized Sequential Recommendation.- Spitial-Temporal Attention Network with Multi-Similarity Loss for Fine-Grained Skeleton-Based Action Recognition.- SRGAT: Social Relational Graph Attention Network for Human Trajectory Prediction.- FSE: A powerful feature augmentation technique for classification task.- AI and Cybersecurity.- FHTC: Few-shot Hierarchical Text Classification in Financial Domain.- JStrack: Enriching Malicious JavaScript Detection Based on AST Graph Analysis and Attention Mechanism.
• (source: Nielsen Book Data)

The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
(source: Nielsen Book Data)

• Cognitive Neurosciences.- A Novel Binary BCI Systems Based on Non-oddball Auditory and Visual Paradigms.- A Just-In-Time Compilation Approach for Neural Dynamics Simulation.- STCN-GR: Spatial-Temporal Convolutional Networks for Surface-Electromyography-Based Gesture Recognition.- Gradient descent learning algorithm based on spike selection mechanism for multilayer spiking neural networks.- Learning to Coordinate via Multiple Graph Neural Networks.- A Reinforcement Learning Approach for Abductive Natural Language Generation.- DFFCN: Dual Flow Fusion Convolutional Network for Micro Expression Recognition.- AUPro: Multi-label Facial Action Unit Proposal Generation for Sequence-level Analysis.- Deep kernelized network for fine-grained recognition.- Semantic Perception Swarm Policy with Deep Reinforcement Learning.- Reliable, Robust, and Secure Machine Learning Algorithms Open-Set Recognition with Dual Probability Learning.- How Much Do Synthetic Datasets Matter In Handwritten Text Recognition.- PCMO: Partial Classification from CNN-Based Model Outputs.- Multi-branch Fusion Fully Convolutional Network for Person Re-Identification.- Fast Organization of Objects Spatial Positions in Manipulator Space from Single RGB-D Camera.- EvoBA: An Evolution Strategy as a Strong Baseline for Black-Box Adversarial Attacks.- A Novel Oversampling Technique for Imbalanced Learning Based on SMOTE and Genetic Algorithm.- Dy-Drl2Op: Learning Heuristics for TSP on the Dynamic Graph via Deep Reinforcement Learning.- Multi-label classification of hyperspectral images based on label-specific feature fusion.- A Novel Multi-Scale Key-Point Detector Using Residual Dense Block and Coordinate Attention.- Alleviating Catastrophic Interference in Online Learning via Varying Scale of Backward Queried Data.- Construction and Reasoning for Interval-Valued EBRB Systems.- Theory and Applications of Natural Computing Paradigms.- Brain-mimetic Kernel: A Kernel Constructed from Human fMRI Signals Enabling a Brain-mimetic Visual Recognition Algorithm.- Predominant Sense Acquisition with a Neural Random Walk Model.- Processing-response dependence on the on-chip readout positions in spin-wave reservoir computing.- Advances in deep and shallow machine learning algorithms for biomedical data and imaging.- A Multi-Task Learning Scheme for Motor Imagery Signal Classification.- An End-to-End Hemisphere Discrepancy Network for Subject-Independent Motor Imagery Classification.- Multi-domain Abdomen Image Alignment Based on Joint Network of Registration and Synthesis.- Coordinate Attention Residual Deformable U-Net for Vessel Segmentation.- Gated Channel Attention Network for Cataract Classification on AS-OCT Image.- Overcoming Data Scarcity for Coronary Vessel Segmentation Through Self-Supervised Pre-Training.- Self-Attention Long-Term Dependency Modelling in Electroencephalography Sleep Stage Prediction.- ReCal-Net: Joint Region-Channel-Wise Calibrated Network for Semantic Segmentation in Cataract Surgery Videos.- Enhancing Dermoscopic Features Classification in Images Using Invariant Dataset Augmentation and Convolutional Neural Networks.- Ensembles of Randomized Neural Networks for Pattern-based Time Series Forecasting.- Grouped Echo State Network with Late Fusion for Speech Emotion Recognition.- Applications.- MPANet: Multi-level Progressive Aggregation Network for Crowd Counting.- AFLLC: A Novel Active Contour Model based on Adaptive Fractional Order Differentiation and Local Linearly Constrained Bias Field.- DA-GCN: A Dependency-Aware Graph Convolutional Network for Emotion Recognition in Conversations.- Semi-Supervised Learning with Conditional GANs for Blind Generated Image Quality Assessment.- Uncertainty-Aware Domain Adaptation for Action Recognition.- Free-Form Image Inpainting with Separable Gate Encoder-decoder Network.- BERTDAN: Question-Answer Dual Attention Fusion Networks With Pre-trained Models for Answer Selection.- Rethinking the Effectiveness of Selective Attention in Neural Networks.- An Attention Method to Introduce Prior Knowledge in Dialogue State Tracking.- Effect of Input Noise Dimension in GANs.- Wiper Arm Recognition using YOLOv4.- Context Aware Joint Modeling of Domain Classification, Intent Detection and Slot Filling with Zero-shot Intent Detection Approach.- Constrained Generative Model for EEG Signals Generation.- Top-Rank Learning Robust to Outliers.- Novel GAN Inversion Model with Latent Space Constraints for Face Reconstruction.- Edge Guided Attention Based Densely Connected Network for Single Image Super-Resolution.- An Agent-Based Market Simulator for Back-testing Deep Reinforcement Learning Based Trade Execution Strategies.- Looking beyond the haze: A Pyramid Fusion Approach.- DGCN-rs: a Dilated Graph Convolutional Networks Jointly Modelling Relation and Semantic for Multi-Event Forecasting.- Training Graph Convolutional Neural Network against Label Noise.- An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes.
• (source: Nielsen Book Data)

The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
(source: Nielsen Book Data)

• Applications
• Deep Supervised Hashing By Classification For Image Retrieval
• Towards Human-level Performance in Solving Double Dummy Bridge Problem
• Coarse-to-Fine Visual Place Recognition
• BFConv: Improving Convolutional Neural Networks with Butterfly Convolution
• Integrating Rich Utterance Features for Emotion Recognition in Multi-party Conversations
• Vehicle Image Generation Going Well with the Surroundings
• Scale Invariant Domain Generalization Image Recapture Detection
• Tile2Vec with Predicting Noise for Land Cover Classification
• A Joint Representation Learning Approach for Social Media Tag Recommendation
• Identity-based Data Augmentation via Progressive Sampling for One-Shot Person Re-identification
• Feature Fusion Learning Based on LSTM and CNN Networks for Trend Analysis of Limit Order Books
• WikiFlash: Generating Flashcards from Wikipedia Articles
• Video Face Recognition with Audio-Visual Aggregation Network
• WaveFuse: A Unified Unsupervised Framework for Image Fusion with Discrete Wavelet Transform
• Manipulation-invariant Fingerprints for Cross-dataset Deepfake Detection
• Low-resource Neural Machine Translation Using Fast Meta-Learning method
• Efficient, Low-Cost, Real-Time Video Super-Resolution Network
• On the Unreasonable Effectiveness of Centroids in Image Retrieval
• Few-shot Classification with Multi-task Self-supervised Learning
• Self-Supervised Compressed Video Action Recognition via Temporal-Consistent Sampling
• Stack-VAE network for Zero-Shot Learning
• TRUFM: a Transformer-guided Framework for Fine-grained Urban Flow Inference
• Saliency Detection Framework Based on Deep Enhanced Attention Network
• SynthTriplet GAN: Synthetic Query Expansion for Multimodal Retrieval
• SS-CCN: Scale Self-guided Crowd Counting Network
• QS-Hyper: A Quality-Sensitive Hyper Network for the No-Reference Image Quality Assessment
• An Efficient Manifold Density Estimator for All Recommendation Systems
• Cleora: A Simple, Strong and Scalable Graph Embedding Scheme
• STA3DCNN: Spatial-temporal Attention 3D Convolutional Neural Network for Citywide Crowd Flow Prediction
• Learning Pre-Grasp Pushing Manipulation of Wide and Flat Objects using Binary Masks
• Multi-DIP: A General Framework For Unsupervised Multi-degraded Image Restoration
• Multi-Attention Network for Arbitrary Style Transfer
• Image Brightness Adjustment with Unpaired Training
• Self-Supervised Image-to-Text and Text-to-Image Synthesis
• TextCut: A Multi-region Replacement Data Augmentation Approach for Text Imbalance Classification
• A Multi-task Model for Sentiment aided Cyberbullying Detection in Code-Mixed Indian Languages
• A Transformer-based Model for Low-resource Event Detection
• Malicious Domain Detection on Imbalanced Data with Deep Reinforcement Learning
• Designing and Searching for Lightweight Monocular Depth Network
• Improving Question Answering over Knowledge Graphs Using Graph Summarization
• Multi-Stage Hybrid Attentive Networks for Knowledge-Driven Stock Movement Prediction
• End-to-End Edge Detection via Improved Transformer Model
• Isn't it ironic, don't you think
• Neural Local and Global Contexts Learning for Word Sense Disambiguation
• Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification
• Paraphrase Identification with Neural Elaboration Relation Learning
• Hybrid DE-MLP-based Modeling Technique for Prediction of Alloying Element Proportions and Process Parameters
• A Mutual Information-based Disentanglement Framework for Cross-Modal Retrieval
• AGRP:A Fused Aspect-Graph Neural Network for Rating Prediction
• Classmates Enhanced Diversity-self-attention Network for Dropout Prediction in MOOCs
• A Hierarchical Graph-based Neural Network for Malware Classification
• A Visual Feature Detection Algorithm Inspired by Spatio-temporal Properties of Visual Neurons
• Knowledge Distillation Method for Surface Defect Detection
• Adaptive Selection of Classifiers for Person Recognition by Iris Pattern and Periocular Image
• Multi-Perspective Interactive Model for Chinese Sentence Semantic Matching
• An Effective Implicit Multi-Interest Interaction Network for Recommendation.

The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.

• Mathematical Programming.- Global Optimization.- Discrete and Combinatorial Optimization.- Optimal Control.- Optimization and Data Analysis.- Game Theory and Mathematical Economics.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 12th International Conference on Optimization and Applications, OPTIMA 2021, held in Petrovac, Montenegro, in September-October 2021. The 22 full and 3 short papers presented were carefully reviewed and selected from 63 submissions. The papers are organized into the following topical sub-headings: mathematical programming, global optimization, discrete and combinatorial optimization, optimal control, optimization and data analysis, and game theory and mathematical economics.
(source: Nielsen Book Data)

This book constitutes the proceedings of the 16th International Conference on Parallel Computing Technologies, PaCT 2021, which was held during September 13-18, 2021. The conference was planned to take place in Kaliningrad, Russia, but changed to an online event due to the COVID-19 pandemic. The 24 full and 12 short papers included in this book were carefully reviewed and selected from 62 submissions. They were organized in topical sections as follows: parallel programming methods and tools; applications; memory-efficient data structures; experimental studies; job management; essential algorithms; computing services; and cellular automata.
(source: Nielsen Book Data)

• Amalgamation property for varieties of BL-algebras generated by one chain with finitely many components / Stefano Aguzzoli and Matteo Bianchi
• Unary-determined distributive [lower case script L]l-magmas and bunched implication algebras / Natanael Alpay, Peter Jipsen, and Melissa Sugimoto
• Effect algebras, Girard quantales and complementation in separation logic / Callum Bannister, Peter Höfner, and Georg Struth
• Relational computation of sets of relations / Rudolf Berghammer
• Experimental investigation of sufficient criteria for relations to have kernels / Rudolf Berghammer and Mitja Kulczynski --[lower case script L]l[lower case italic]r-multisemigroups, modal quantales and the origin of locality / Cameron Calk, Uli Fahrenberg, Christian Johansen, Georg Struth, and Krzysztof Ziemiański
• Abstract strategies and coherence / Cameron Calk, Eric Goubault, and Philippe Malbos
• Algorithmic correspondence for relevance logics, bunched implication logics, and relation algebras via an implementation of the algorithm PEARL / Willem Conradie, Valentin Goranko, and Peter Jipsen
• The class of representable semilattice-ordered monoids is not a variety / Amina Doumane
• Accretive computation of global transformations / Alexandre Fernandez, Luidnel Maignan, and Antoine Spicher
• Some modal and temporal translations of generalized basic logic / Wesley Fussner and William Zuluaga Botero
• Isolated sublattices and their application to counting closure operators / Roland Glück
• Second-order properties of undirected graphs / Walter Guttmann
• Relation-algebraic verification of Borůvka's minimum spanning tree algorithm / Walter Guttmann and Nicolas Robinson-O'Brien
• Deciding FO-definability of regular languages / Agi Kurucz, Vladislav Ryzhikov, Yury Savateev, and Michael Zakharyaschev

• Relational models for the Lambek calculus with intersection and unit / Stepan L. Kuznetsov
• Free modal Riesz spaces are Archimedean : a syntactic proof / Christophe Lucas and Matteo Mio
• Polyadic spaces and profinite monoids / Jérémie Marquès
• Time warps, from algebra to algorithms / Sam van Gool, Adrien Guatto, George Metcalfe, and Simon Santschi
• On algebra of program correctness and incorrectness / Bernhard Möller, Peter O'Hearn, and Tony Hoare
• Computing least and greatest fixed points in absorptive semirings / Matthias Naaf
• A variety theorem for relational universal algebra / Chad Nester
• On tools for completeness of Kleene algebra with hypotheses / Damien Pous, Jurriaan Rot, and Jana Wagemaker
• Skew metrics valued in Sugihara semigroups / Luigi Santocanale
• Computing distributed knowledge as the greatest lower bound of knowledge / Carlos Pinzón, Santiago Quintero, Sergio Ramírez, and Frank Valencia
• Relational sums and splittings in categories of L-fuzzy relations / Michael Winter
• Change of base using arrow categories / Michael Winter
• Automated reasoning for probabilistic sequential programs with theorem proving / Kangfeng Ye, Simon Foster, and Jim Woodcock
• Domain range semigroups and finite representations / Jaš Šemrl.

This book constitutes the proceedings of the 19th International Conference on Relational and Algebraic Methods in Computer Science, RAMiCS 2021, which took place in Marseille, France, during November 2-5, 2021. The 29 papers presented in this book were carefully reviewed and selected from 35 submissions. They deal with the development and dissemination of relation algebras, Kleene algebras, and similar algebraic formalisms. Topics covered range from mathematical foundations to applications as conceptual and methodological tools in computer science and beyond.

• Self-stabilizing Systems: Theory and Practice.- Foundations of Concurrent and Distributed Computing.- Mobile and Robot Computing.- Fault-tolerance, Security, and Privacy.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 23rd International Symposium on Stabilization, Safety, and Security of Distributed Systems, SSS 2021, held virtually, in November 2021. The 16 full papers, 10 short and 14 invited papers presented were carefully reviewed and selected from 56 submissions. The papers deal with the design and development of distributed systems with a focus on systems that are able to provide guarantees on their structure, performance, and/or security in the face of an adverse operational environment.
(source: Nielsen Book Data)

• Invited papers.- r-indexing the eBWT.- Unicode at Gigabytes per Second.- Combinatorics.- Longest Common Rollercoasters.- Minimal unique palindromic substrings after single-character substitution.- Permutation-constrained Common String Partitions with Applications.- All instantiations of the greedy algorithm for the shortest superstring problem are equivalent.- String Covers of a Tree.- Compression.- Grammar Index By Induced Suffix Sorting.- An LMS-based Grammar Self-index with Local Consistency Properties.- On the approximation ratio of LZ-End to LZ77.- Data Structures.- Computing the original eBWT faster, simpler, and with less memory.- Extracting the Sparse Longest Common Pre x Array from the Suffix Binary Search Tree.- findere: fast and precise approximate membership query.- Repeats.- Improved Topic Modeling in Twitter through Community Pooling.- Lower Bounds for the Number of Repetitions in 2D Strings.- On Stricter Reachable Repetitiveness Measures.- Information Retrieval.- Improved Topic modeling in Twitter through Community Pooling.- TSXor: A Simple Time Series Compression Algorithm.- Pattern Matching.- Exploiting Pseudo-Locality of Interchange Distance.- Position Heaps for Cartesian-tree Matching on Strings and Tries.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 27th International Symposium on String Processing and Information Retrieval, SPIRE 2021, held in Lille, France, in October 2021.*The 14 full papers and 4 short papers presented together with 2 invited papers in this volume were carefully reviewed and selected from 30 submissions. They cover topics such as: data structures; algorithms; information retrieval; compression; combinatorics on words; and computational biology. *The symposium was held virtually.
(source: Nielsen Book Data)

• Distributed Graph Algorithms
• Concurrency, Consensus and Dynamics
• Mobile Robots and Agents
• Security and Efficiency of Network Communication
• Network and Graph Structures.

This book constitutes the refereed conference proceedings of the 28th International Colloquium on Structural Information and Communication Complexity, SIROCCO 2021, held in Wroc±aw, Poland, in June 2021. Due to COVID-19, the conference will be held online. The 20 full papers presented in this book were carefully reviewed and selected from 48 submissions. The papers are solicited from all areas of study of local structural knowledge and global communication and computational complexities. Among the typical areas are distributed computing, communication networks, game theory, parallel computing, social networks, mobile computing.

• Modeling and Specification.- Model Checking.- Specification and Verification.- Testing and Formal Verification. .
• (source: Nielsen Book Data)

This book constitutes the refereed workshop proceedings of the 10th International Workshop on Structured Object-Oriented Formal Language and Method, SOFL+MSVL 2020, held in Singapore, in March 2021. The 13 revised full papers included in the volume were carefully reviewed and selected from 24 submissions. They are organized in the following topical sections: modeling and specification; model checking; specification and verification; and testing and formal verification.Due to the Corona pandemic this event was held virtually.
(source: Nielsen Book Data)

• Intro
• Preface
• Organization
• Contents
• OptiLog: A Framework for SAT-based Systems
• 1 Introduction
• 2 OptiLog Framework Architecture
• 2.1 Formula Module
• 2.2 SAT Solver Module
• 2.3 PB Encoder Module
• 2.4 Automatic Configuration (AC) Module
• 2.5 Adding SAT Solvers to OptiLog Through iSAT Interface
• 3 Example: The Linear MaxSAT Algorithm with OptiLog
• 4 Conclusions and Future Work
• References
• PyDGGA: Distributed GGA for Automatic Configuration
• 1 Introduction
• 2 Preliminaries
• 3 PyDGGA
• 3.1 Distributed Architecture
• 3.2 Simulation

• 3.3 Scheduling and Canceling
• 3.4 Instance Selection
• 3.5 Elite Mini-Tournament
• 3.6 Other Tool Enhancements
• 4 Using PyDGGA
• 5 Experiments with SAT
• 6 Conclusions and Future Work
• References
• QBFFam: A Tool for Generating QBF Families from Proof Complexity
• 1 Introduction
• 2 Related Work
• 3 Formula Families
• 4 Case Study
• 5 Conclusion
• References
• Davis and Putnam Meet Henkin: Solving DQBF with Resolution
• 1 Introduction
• 2 Preliminaries
• 3 Davis-Putnam Resolution for H-Form DQBF
• 3.1 Strategy Operations
• 3.2 Definition of the Construction

• 3.3 Correctness and Completeness
• 3.4 Representing Strategies
• 4 NEXP-completeness of CNF H-Form DQBF
• 5 Conclusion
• References
• Lower Bounds for QCDCL via Formula Gauge
• 1 Introduction
• 2 Preliminaries
• 3 QCDCL as a Formal Proof System
• 4 Quasi Level-Ordered Proofs
• 5 A Lower Bound Technique via Gauge
• 6 Applications of the Lower Bound Technique
• 7 Conclusion
• References
• Deep Cooperation of CDCL and Local Search for SAT
• 1 Introduction
• 2 Preliminaries
• 2.1 Preliminary Definitions and Notations
• 2.2 CDCL Solvers
• 2.3 Local Search Solvers

• 2.4 Experiment Preliminaries
• 3 Exploring Promising Branches by Local Search
• 4 Phase Resetting with Local Search Assignments
• 5 Branching with Conflict Frequency in Local Search
• 6 Experiments
• 7 Related Works
• 8 Conclusions
• References
• Hash-Based Preprocessing and Inprocessing Techniques in SAT Solvers
• 1 Introduction
• 2 Preliminaries
• 3 Hash-Based Methods
• 4 Probabilistic Analysis
• 5 Evaluation
• 6 Conclusions
• References
• Hardness and Optimality in QBF Proof Systems Modulo NP
• 1 Introduction
• 1.1 Organisation
• 2 Preliminaries
• 2.1 Proof Complexity

• 2.2 Propositional Logic
• 2.3 Quantified Boolean Formulas
• 3 Simulations with Extension Variables
• 4 Extended Q-Res Modulo NP
• 5 Weaker QBF Systems
• 6 Conclusion
• References
• Characterizing Tseitin-Formulas with Short Regular Resolution Refutations
• 1 Introduction
• 2 Preliminaries
• 3 Reduction from Unsatisfiable to Satisfiable Formulas
• 3.1 Well-Structured Branching Programs for SearchVertex(G, c)
• 3.2 Constructing DNNF from Well-Structured Branching Programs
• 4 Adversarial Rectangle Bounds
• 5 Splitting Parity Constraints

This book constitutes the proceedings of the 24th International Conference on Theory and Applications of Satisfiability Testing, SAT 2021, which took place in Barcelona, Spain, in July 2021. The 37 full papers presented in this volume were carefully reviewed and selected from 73 submissions. They deal with theory and applications of the propositional satisfiability problem, broadly construed. Aside from plain propositional satisfiability, the scope of the meeting includes Boolean optimization, including MaxSAT and pseudo-Boolean (PB) constraints, quantified Boolean formulas (QBF), satisfiability modulo theories (SMT), and constraint programming (CP) for problems with clear connections to Boolean reasoning.

• Applications of Natural Computing.- Deep Learning and Transfer Learning.- Evolutionary and Swarm Algorithms.
• (source: Nielsen Book Data)

This book constitutes the refereed proceedings of the 10th International Conference on Theory and Practice of Natural Computing, TPNC 2021, held virtually, in December 2021. The 9 full papers presented together with 3 invited talks, in this book were carefully reviewed and selected from 14 submissions. The papers are organized in topical sections named Applications of Natural Computing, Deep Learning and Transfer Learning, Evolutionary and Swarm Algorithms.
(source: Nielsen Book Data)