The proceedings contain 117 papers. The topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making met...
ISBN:
(纸本)9781665464970
The proceedings contain 117 papers. The topics discussed include: detection of a novel dual attack in named data networking;fair DMA scheduler for low-latency accelerator offloading;multi-attribute decision-making method based on interval intuitionistic trapezoidal fuzzy number to determine the expert weight: note: sub-titles are not captured in Xplore and should not be used;binary-level directed symbolic execution through pattern learning;an efficient metric-based approach for static use-after-free detection;a graph convolution neural network based method for insider threat detection;maintenance worker scheduling for charging pile fault: a multi-agent RL approach;towards secure bilateral friend query with conjunctive policy matching in social networks;structure-noise-aware anchor link prediction across social networks;file system to support secure cloud-based sharing;discovering agent models using process mining: initial approach and a case study;and towards agent-based simulation of the parallel trading market of pharmaceuticals.
The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributedcomputing architectures. We present a new distributed algorithm for st...
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The inherent computational complexity of validating and verifying concurrent systems implies a need to be able to exploit parallel and distributedcomputing architectures. We present a new distributed algorithm for state space exploration of concurrent systems on computing clusters. Our algorithm relies on Remote Direct Memory Access (RDMA) for low-latency transfer of states between computing elements and on state reconstruction trees for compact representation of states on the computing elements themselves. For the distribution of states between computing elements, we propose a concept of state stealing. We have implemented our proposed algorithm using the OpenSHMEM API for RDMA and experimentally evaluated it on the grid'5000 testbed with a set of benchmark models. The experimental results show that our algorithm scales well with the number of available computing elements and that our state stealing mechanism generally provides a balanced workload distribution.
The proceedings contain 27 papers. The topics discussed include: Tetris: automatic UAF exploit generation by manipulating layout based on reactivated paths;artificial neural network for processing fingerprint image no...
ISBN:
(纸本)9798350396379
The proceedings contain 27 papers. The topics discussed include: Tetris: automatic UAF exploit generation by manipulating layout based on reactivated paths;artificial neural network for processing fingerprint image noise;facial expression intensity estimation considering change characteristic of facial feature values for each facial expression;developing a gamification method based on motivation subscales for lifelogging applications;preliminary study of reasoning existing projects' descriptions based on classname word elements;construction and evaluation of a speech emotion classifier using LSTM;concurrency control program generation in genetic programming considering depth of the program tree;reconfiguration cost for reconfigurable computing architectures;and parallel binary search tree construction inspired by thread-level speculation.
The proceedings contain 3 papers. The topics discussed include: SABO: dynamic MPI+OpenMP resource balancer;LEC-PR: proactive recovery method in erasure-coded storage;and Petri nets for concurrent programming.
ISBN:
(纸本)9781665475082
The proceedings contain 3 papers. The topics discussed include: SABO: dynamic MPI+OpenMP resource balancer;LEC-PR: proactive recovery method in erasure-coded storage;and Petri nets for concurrent programming.
The proceedings contain 42 papers. The topics discussed include: deep learning used to detect gear inspection;a non-normal warning system for dam operation using machine learning;small probability of fatality from the...
ISBN:
(纸本)9798350310412
The proceedings contain 42 papers. The topics discussed include: deep learning used to detect gear inspection;a non-normal warning system for dam operation using machine learning;small probability of fatality from theorem of bayes at the monkeypox pandemic;multi-agent reinforcement learning reward engineering via stochastic game evaluation;artificial intelligence of things enabled fungiculture in shipping container;instructions with complex control-flow entailing machine learning;development and validation of an explainable deep learning model to predict adverse event during hospital admission in patients with sepsis;graph database-modelled public transportation data for geographic insight web application;the study on security online judge system applied sandbox technology;and cause-effect graphing technique: a survey of available approaches and algorithms.
State estimation is the foundation for a variety of online power system applications in energy management systems, and the stability of power systems is directly impacted by the speed with which current system states ...
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ISBN:
(纸本)9781665455336
State estimation is the foundation for a variety of online power system applications in energy management systems, and the stability of power systems is directly impacted by the speed with which current system states can be obtained through state estimation. This paper proposed a fast Gaussian-Newton state estimation method for power systems based on parallel belief propagation, which implements the Gaussian belief process via multi-core and multi-thread parallel computation to achieve efficient state estimation. Simulation findings on numerous IEEE-standard power systems show that the suggested technique outperforms the traditional algorithm.
With the rapid evolution of artificial intelligence (AI), face forgery videos have proliferated, posing significant societal challenges. Traditional detection methods struggle with poor generalization and cross-databa...
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ISBN:
(纸本)9798350391961;9798350391954
With the rapid evolution of artificial intelligence (AI), face forgery videos have proliferated, posing significant societal challenges. Traditional detection methods struggle with poor generalization and cross-database accuracy, unable to address subtle features and variations in face images across scales and compression levels. This paper reviews current face forgery detection methods, identifying key limitations. It introduces a novel model enhancing features through knowledge distillation, optimizing generalization and robustness via a unique loss function and temperature adjustment strategy. Additionally, a Discrete Cosine Transform with multi-scale and multi-compression capabilities (DCTMS) is integrated, enriching texture and detail capture. Experimental results on deepfake datasets demonstrate the efficacy of the proposed methods, achieving high detection accuracy and robustness across diverse scenarios, including cross-database experiments. This study contributes valuable insights and techniques to advance the field of face forgery detection, addressing risks associated with manipulated video content.
The proceedings contain 25 papers. The special focus in this conference is on parallel and distributedcomputing. The topics include: Analysing Supercomputer Nodes Behaviour with the Latent Representation of...
ISBN:
(纸本)9783031125966
The proceedings contain 25 papers. The special focus in this conference is on parallel and distributedcomputing. The topics include: Analysing Supercomputer Nodes Behaviour with the Latent Representation of Deep Learning Models;Accelerating parallel Operation for Compacting Selected Elements on GPUs;A Methodology to Scale Containerized HPC Infrastructures in the Cloud;cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads;multi-objective Hybrid Autoscaling of Microservices in Kubernetes Clusters;two-Agent Scheduling with Resource Augmentation on Multiple Machines;IP. LSH. DBSCAN : Integrated parallel Density-Based Clustering Through Locality-Sensitive Hashing;graphGuess: Approximate Graph Processing System with Adaptive Correction;deterministic parallel Hypergraph Partitioning;MARTINI: The Little Match and Replace Tool for Automatic Application Rewriting with Code Examples;OmpSs-2@Cluster: distributed Memory Execution of Nested OpenMP-style Tasks;Generating Work Efficient Scan Implementations for GPUs the Functional Way;automatic parallelization of Python Programs for distributed Heterogeneous computing;A Hybrid Piece-Wise Slowdown Model for Concurrent Kernel Execution on GPU;accelerating Brain Simulations with the Fast Multipole Method;high-Performance Spatial Data Compression for Scientific Applications;accurate Fork-Join Profiling on the Java Virtual Machine;characterization of Different User Behaviors for Demand Response in Data Centers;on-the-Fly Calculation of Model Factors for Multi-paradigm Applications;relative Performance Projection on Arm Architectures;exploring Scheduling Algorithms for parallel Task Graphs: A Modern Game Engine Case Study;Decentralized Online Scheduling of Malleable NP-hard Jobs;A Bi-Criteria FPTAS for Scheduling with Memory Constraints on Graphs with Bounded Tree-Width.
The paper details an Ethereum blockchain platform for smart grid energy trading, employing smart contracts and security measures like access control. It separates front-end and back-end, supporting secure integration ...
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Application of blockchain in financial services has opened new ways of efficiency in transaction processing, assets management and security. The application of parallel, distributed, and gridcomputing with blockchain...
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