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检索条件"任意字段=12th Euromicro Conference on Parallel, Distributed and Network-Based Processing"

共 1249 条记录，以下是61-70 订阅

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What Appears Suboptimal May Surprise You: A Fixed-Rate Scheduling Policy for Geo-distributed CoFlows 29

What Appears Suboptimal May Surprise You: A Fixed-Rate Sched...

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29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Liu, Haoyu Ding, Feiyan Wang, Yao Xiang, Qiao Shu, Jiwu Du, Haizhou Kong, Linghe Liu, Xue Xiamen University School of Informatics Xiamen China University of Electric Power of Shanghai School of Computer Science and Technology Shanghai China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China McGill University School of Computer Science Montreal Canada

ISBN: (纸本)9798350330717

All existing coflow scheduling algorithms compute dynamic-rate schedules that change the rates of flows during transmission. In this paper, we make a crucial finding: although dynamically adjusting the rates of flows could lead to a better coflow completion time (CCT) in theory, it would introduce additional pressures on the congestion control mechanism in the underlying network, which result in poor CCT in practice. this difference between theoretical CCT and practical CCT is further exacerbated in wide-area networks, where the topology does not provide any bisection guarantee as data center networks do. To this end, we designed a fixed-rate coflow scheduling policy called FSCO. Although in theory, the best fixed-rate schedule is usually suboptimal, it keeps the in-flight traffic relatively steady, reducing the risk of triggering congestion control. the core of FSCO is an efficient scheduling algorithm based on the classic network utilization maximization (NUM) framework. We implement a prototype of FSCO and evaluate its performance extensively using real-world topologies and coflow traces. Experimental results show that the total CCT reduces up to 30% compared to baselines while yielding up to 12× speedups compared to the solver. © 2023 IEEE.

关键词： Coflow Scheduling Dual decomposition network Utility Maximization

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Investigation of an end-to-end neural architecture for image-based source term estimation 12

Investigation of an end-to-end neural architecture for image...

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12th Sensor Signal processing for Defence conference (SSPD)

作者： Abdulaziz, A. Altmann, Y. McLaughlin, S. Davies, M. E. Heriot Watt Univ Sch Engn & Phys Sci Edinburgh Midlothian Scotland Univ Edinburgh Sch Engn Edinburgh Midlothian Scotland

ISBN: (纸本)9798350337327

Rapid and accurate estimation of hazardous material release parameters, including source location, release time, and quantity of material released, is crucial for protecting assets and facilitating timely and effective emergency response. In this paper, we present a first artificial neural network (ANN) approach for end-to-end source term estimation (STE) using time-series of multispectral satellite images. the architecture consists of two successive ANNs. the first-stage ANN estimates the hazardous material release rate over time, producing a 3D concentration map, while the second-stage ANN utilizes the generated concentration map to estimate the 2D source location, release time, and easterly and northerly wind speeds. By leveraging the inherent nonlinearity of ANNs and advances in parallel computing, our proposed method aims to eventually overcome the limitations of existing optimization and Bayesian inference techniques in handling the nonlinear STE problem. In this preliminary study, we validate the performance of our approach on a simulated dataset, demonstrating its potential for enhancing the accuracy and speed of STE in real-world applications.

关键词： source term estimation artificial neural networks

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Control of Unmanned Bicycle based on Tensor Product Model Transformation and Hammersley Sampling Method

Control of Unmanned Bicycle Based on Tensor Product Model Tr...

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International conference on Intelligent Control and Information processing (ICICIP)

作者： Depeng Xie Degang Wang Guoliang Zhao Hongxing Li School of Control Science and Engineering Dalian University of Technology Dalian China College of Electronic Information Engineering Inner Mongolia University Hohhot China

In this paper, path planning and balance control of unmanned bicycles are investigated. Firstly, the Deep Deterministic Policy Gradient (DDPG) algorithm is used to train the Artificial Potential Field (APF) algorithm to implement path planning in complex maps. Secondly, a dual closed-loop control strategy is adopted for the path tracking and the balance control. In the inner-loop control, the Hammersley sampling (HS) method is used to obtain the hyper-cube network model of the unmanned bicycle, and the balance controller is designed based on the tensor product (TP) model transformation and parallel distributed compensation (PDC) method for stabilization of the unmanned bicycle. the outer-loop control system uses the Ackermann steering geometry model to track the planned path. Finally, the simulation results demonstrate that the path planning algorithm plans the path that satisfies the constraints and the designed balance controller can keep the unmanned bicycle balanced well during trajectory tracking.

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A parallel CNN-BiGRU network for short-term load forecasting in demand-side management 12

A parallel CNN-BiGRU network for short-term load forecasting...

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12th International conference on Computer and Knowledge Engineering, ICCKE 2022

作者： Irankhah, Arghavan Saatlou, Sahar Rezazadeh Yaghmaee, Mohammad Hossein Ershadi-Nasab, Sara Alishahi, Mohammad Ferdowsi University of Mashhad Department of Computer Engineering Iran Islamic Azad University Research Center of Smart Distribution Networks Mashhad Branch Iran

ISBN: (数字)9781665476133

ISBN: (纸本)9781665476133

Nowadays, power companies are trying to monitor energy consumption to provide demand response. Energy management and scheduling are possible through short-term load forecasting. Energy supply stability and efficiency depend on accurate forecasting, which balances demand and supply. In this paper, a novel hourly energy prediction method is introduced. A new parallel deep learning network is presented based on CNN and GRU networks. Firstly, some features are extracted from the dataset during pre-processing. then, the CNN models extract more information from these features in two parallel paths. Afterward, Bi-GRU networks are used to observe the extracted features from previous layers in both two directions to learn long dependency patterns. the real-world data collected by Mashhad energy distribution company is used to evaluate the proposed method. the results demonstrate that the proposed method reached the lowest values containing 49.04, 34.37, and 3.81 for RMSE, MAE, and MAPE metrics in comparison with existing methods. © 2022 IEEE.

关键词： Smart power grids

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Multi-Objective based Multi-Agent Decision-Making System 12

Multi-Objective Based Multi-Agent Decision-Making System

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12th IEEE International conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Melnic, Radu Ababii, Victor Sudacevschi, Viorica Sachenko, Oleg Borozan, Olesea Lendiuk, Taras Technical University of Moldova Chisinau Moldova West Ukrainian National University Ternopil Ukraine

ISBN: (纸本)9798350358056

Multi-objective decision systems for the management, monitoring and control of complex processes require the application of new methods and models of abstraction and formal description based on intelligent computing structures to ensure optimal overall decision-making. these computing structures can be built on the basis of Multi-Agent systems. In this paper it is proposed the development of a Multi-Objective based Multi-Agent Decision-Making System that ensures the process of searching for the optimal solution based on genetic algorithms and its application in the decision-making process. the Multi-Agent system features a distributed computing structure consisting of lots of heterogeneous data processing nodes. the functionality of agents is described based on mathematical models and sequence diagram, which explains the interaction between the set of Agents. the structure of the decision-making system is presented on two levels of abstraction: the Multi-Agent level of production and management, and the Information level of communication, storage and data processing. © 2023 IEEE.

关键词： Decision-Making Mathematical Models Multi-Agent System Multi-Objective Optimization Sequence Diagram Smart Agriculture

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Game-theoretic Analysis of (Non-)Refundable Fees in the Lightning network 29

Game-Theoretic Analysis of (Non-)Refundable Fees in the Ligh...

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29th IEEE International conference on parallel and distributed Systems, ICPADS 2023

作者： Kumble, Satwik Prabhu Epema, Dick Roos, Stefanie TU Delft Netherlands University of Kaiserslautern-Landau Germany

ISBN: (纸本)9798350330717

In PCNs, nodes that forward payments between a source and a receiver are paid a small fee if the payment is successful. the fee is a compensation for temporarily committing funds to the payment. However, payments may fail due to insufficient funds or attacks, often after considerable delays of up to several days, leaving a node without compensation. Furthermore, attackers can intentionally cause failed payments, e.g., to infer private information (like channel balances), without any cost in fees. In this paper, we first use extensive form games to formally characterize the conditions that lead to rational intermediaries refusing (or agreeing) to forward payments. An intermediary's decision to forward or not depends on the probability of failure, which they approximate based on past experience. We then propose and analyze an alternative fee model that allows the sender to determine and pay a fraction of the fee to intermediaries in a non-refundable manner. A rational sender chooses the fraction such that the intermediaries' utility for forwarding the payment exceeds their utility for not forwarding. Our simulation study, based on real-world Lightning snapshots, confirms that our novel mechanism can increase the probability of successful payments by 12% and decrease routing fees for senders by about 6% if all nodes behave rationally. Furthermore, previously cost-free probing attacks now require that the attacker pays 1500 satoshis for every 1 million satoshis inferred. © 2023 IEEE.

关键词： Extensive Form Games Payment Channel networks Payment Fees Probing attacks

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Machine Learning-based Gesture Recognition UsingWearable Devices 12

Machine Learning-based Gesture Recognition UsingWearable Dev...

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12th International conference on Cyber-Enabled distributed Computing and Knowledge Discovery (CyberC)

作者： Wu, Haoyu Qi, Jun Wang, Wei Chen, Jianjun Xian Jiaotong Liverpool Univ Dept Comp Suzhou Peoples R China

ISBN: (纸本)9798350331547

Traditional gesture recognition solutions are based on touch screens or vision, limited by environmental conditions and not portable. the accelerometer-based gesture recognition technology can be integrated into small wearable smart devices, such as smart bracelets, smartwatches or smart rings. the portability and reliability of this technology make it a broad market and application space. this project is based on a smartwatch accelerometer dataset from TensorFlow Datasets. By experimenting with two different pre-processing algorithms: Kalman Filter and Savitzky-Golay Filter, feature extraction algorithms and machine learning algorithms (random forests, k-nearest neighbours, support vector machine), the relatively optimal algorithm for each part to combine to obtain a good accelerometer-based gesture recognition model were filtered out, including gravity reduction, Fourier transforms, a normal exception elimination algorithm, Savitzky-Golay Filter and Support Vector Machine (SVM). the best accuracy rate of this model is over 97%, with a similar degree of precision, recall rate and f1 score.

关键词： Machine Learning Gesture Recognition Signal processing Feature Engineering

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12th IFIP TC 12 International conference on Intelligent Information processing, IIP 2022

12th IFIP TC 12 International Conference on Intelligent Info...

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12th IFIP TC 12 International conference on Intelligent Information processing, IIP 2022

ISBN: (纸本)9783031039478

the proceedings contain 43 papers. the special focus in this conference is on Intelligent Information processing. the topics include: A Game-theoretic Analysis of Impulse Purchase;research on Blockchain Privacy Protection Mechanism in Financial Transaction Services based on Zero-Knowledge Proof and Federal Learning;a Hybrid parallel Algorithm With Multiple Improved Strategies;resource Scheduling for Human-Machine Collaboration in Multiagent Systems;pre-loaded Deep-Q Learning;using Multi-level Attention based on Concept Embedding Enrichen Short Text to Classification;does Large Pretrained Dataset Always Help? On the Effect of Dataset Size on Big Transfer Model;augmenting Context Representation with Triggers Knowledge for Relation Extraction;high-Resolution Remote Sensing Image Semantic Segmentation Method based on Improved Encoder-Decoder Convolutional Neural network;preface;classification Between Rumors and Explanations of Rumors based on Common and Difference Subsequences of Sentences;augmenting Convolution Neural networks by Utilizing Attention Mechanism for Knowledge Tracing;a Hybrid Multi-objective Optimization Algorithm with Improved Neighborhood Rough Sets for Feature Selection;predicting Student Performance in Online Learning Using a Highly Efficient Gradient Boosting Decision Tree;A Method for AGV Double-Cycling Scheduling at Automated Container Terminals;inductive Light Graph Convolution network for Text Classification based on Word-Label Graph;super-Resolution of Defocus thread Image based on Cycle Generative Adversarial networks;a Method on Online Learning Video Recommendation Method based on Knowledge Graph;A HEp-2 Cell Image Classification Model based on Deep Residual Shrinkage network Combined with Dilated Convolution;attention Adaptive Chinese Named Entity Recognition based on Vocabulary Enhancement;software Defect Prediction Method based on Cost-Sensitive Random Forest;a Pear Leaf Diseases Image Recognition Model based on Capsule network.

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Proceedings of the 12th International conference on Information Technology and its Applications, CITA 2023

Proceedings of the 12th International Conference on Informat...

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Proceedings of the12th International conference on Information Technology and its Applications, CITA 2023

ISBN: (纸本)9783031368851

the proceedings contain 33 papers. the special focus in this conference is on Information Technology and its Applications. the topics include: An Improved Transfer Learning-based Approach for Detecting Abnormal Cervical Cells from Pap Smear Microscopic Images;emotional Intelligence and Social Media Site Experiences’ Effects on College Choice Behavior: the Mediating Role of Brand Attitude;a Multi Context Decoder-based network with Applications for Polyp Segmentation in Colonoscopy Images;AMG-Mixer: A Multi-Axis Attention MLP-Mixer Architecture for Biomedical Image Segmentation;Investigating YOLO Models for Rice Seed Classification;Extending OCR Model for Font and Style Classification;STG-SimVP: Spatiotemporal GAN-based SimVP for Video Prediction;tritention U-Net: A Modified U-Net Architecture for Lung Tumor Segmentation;multi-modal with Multiple Image Filters for Facial Emotion Recognition;differentially-Private distributed Machine Learning with Partial Worker Attendance: A Flexible and Efficient Approach;few-Shots Novel Space-Time View Synthesis from Consecutive Photos;Information Technology Skills Extractor for Job Descriptions in vku-ITSkills Dataset Using Natural Language processing;comprehensive Study on Semantic Segmentation of Ovarian Tumors from Ultrasound Images;VR VanMieu: the Interactively Virtual Temple of Literature;neural Sequence Labeling based Sentence Segmentation for Myanmar Language;a Compact Version of EfficientNet;using Deep Learning for Obscene Language Detection in Vietnamese Social Media;A New Approach for Enhancing MVDR Beamformer’s Performance;a Spectral Mask - based on Method for Applying into Generalized Sidelobe Canceller Beamformer;An Integrated Model of Placement Optimization and Redundancy Elimination in RFID network Planning;Building Legal Knowledge Map Repository with NLP Toolkits;conjunctive Query based Constraint Solving for Feature Model Configuration;ESpin: Analyzing Event-Driven Systems in Model Checking;blockchain Solution for

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Optimizing Secure Information Interaction in distributed Computing Systems by the Sequential Concessions Method 28

Optimizing Secure Information Interaction in Distributed Com...

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28th euromicro International conference on parallel, distributed and network-based processing (PDP)

作者： Kotenko, Igor Sineshchuk, Yury Saenko, Igor Russian Acad Sci SPIIRAS St Petersburg Inst Informat & Automat St Petersburg Russia St Petersburg Univ Minist Internal Affairs Russian Federat St Petersburg Russia

ISBN: (纸本)9781728165820

the paper proposes a new approach to multicriteria optimization of the structure of secure information interaction in distributed computing systems. A distinguishing feature of the approach is the use of the sequential concessions method. this approach provides the acceptable flexibility in comparing the system construction variants by taking into account not only the priority of the system according to efficiency indicators, but also the relationships of the indicators. the mathematical basis of the proposed method is considered. the procedure of implementation of the proposed method for ensuring security of information interaction in a distributed hierarchical automated control system is demonstrated, and its experimental assessment is given.

关键词： distributed computer network cyber-physical systems optimization method of sequential concessions

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