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A Double-Layer Combination Algorithm for Real-Time Information-Sharing Network Design Problem

Qi Sun, Liwen Jiang, Haitao Xu
2021 Complexity  
This paper designs a low-carbon model and focuses on the real-time information-sharing network in order to get sustainable strategies promptly and exactly.  ...  Firstly, the biobjective information-sharing network model is established to describe real-time problem with total cost and carbon emission factor.  ...  e Design Ideas of Double-Layer Combination Algorithm.  ... 
doi:10.1155/2021/4856593 doaj:85385fc66b7040bba9254f5e5651f024 fatcat:hchcfp7jabb7zgjldmr7phbrmm

Parallel Ensemble Deep Learning for Real-Time Remote Sensing Video Multi-Target Detection

Long Sun, Jie Chen, Dazheng Feng, Mengdao Xing
2021 Remote Sensing  
It combines a deep learning target detection algorithm with template matching to make full use of image information.  ...  At the same time, the real-time and stable display of detection results is realized by aiming at the moving UAV video image.  ...  Acknowledgments: We would like to express our heartfelt thanks to anonymous reviewers and editors for their constructive comments on the paper.  ... 
doi:10.3390/rs13214377 fatcat:ddjwhsx5urgplgkktc6rfnpg4e

The Past, Present, and Future of Transport-Layer Multipath [article]

Sana Habib, Junaid Qadir, Anwaar Ali, Durdana Habib, Ming Li, Arjuna Sathiaseelan
2016 arXiv   pre-print
Since congestion control defines a fundamental feature of the transport layer, we study the working of multipath rate control and analyze its stability and convergence.  ...  scheduling mechanisms for use with multiple paths.  ...  The application layer and the transport layer can work together to design better protocols for real-time applications while the interaction between the transport layer and the network layer is simultaneously  ... 
arXiv:1601.06043v1 fatcat:5hzuk53f55fghmf6k53wvcsfx4

Theoretical Research on the Time Delay and Corresponding Issues for the Novel Category of Internet of Things Control System

Yucheng Zhang, Guoyong Liu, Luming Tan
2016 International Journal of Future Generation Communication and Networking  
of things have the effect of information transmission, the layer is mainly used for the data transfer between perception layer and application layer and it is a bridge connecting the perception layer  ...  Sharing network inevitably the introduction of network time delay, in most cases they are incident or random [26] .  ...  Acknowledgements This work was financially supported by the 2013 Research Fund Project of Xijing University.Project name: Research on real time monitoring system of surface subsidence based on GPS and  ... 
doi:10.14257/ijfgcn.2016.9.10.01 fatcat:xkykjy5f5vaohchbtfrizktgrq

A Cross-camera Multi-face Tracking System Based on Double Triplet Networks

Guoyin Ren, Xiaoqi Lu, Yuhao Li
2021 IEEE Access  
Double Triplet Networks (DTN) designed in this study is used to learn the depth features of human face.  ...  Cross-camera face tracking is possible by transmitting facial features between cameras in real-time.  ...  SYSTEM DESIGN This paper proposes an improved DTN (Double Triplet Networks, DTN) for real-time multi-face tracking in multi camera field of view.  ... 
doi:10.1109/access.2021.3061572 fatcat:2zi3ga3ilvdp5lrnwqew65r6ai

Feature Importance-aware Graph Attention Network and Dueling Double Deep Q-Network Combined Approach for Critical Node Detection Problems [article]

Xuwei Tan, Yangming Zhou, Zhang-Hua Fu, Mengchu Zhou
2021 arXiv   pre-print
This work proposes a feature importance-aware graph attention network for node representation and combines it with dueling double deep Q-network to create an end-to-end algorithm to solve CNP for the first  ...  A Critical Node Problem (CNP) aims to find a set of critical nodes from a network whose deletion maximally degrades the pairwise connectivity of the residual network.  ...  Conclusion This work presents FGDD as a new DRL-based algorithm for a critical node problem that generalizes well to unseen networks size and structures.  ... 
arXiv:2112.03404v1 fatcat:h5lnx2qcfvaqbgk76cosx6w3gy

A Vehicle Reidentification Algorithm Based on Double-Channel Symmetrical CNN

Lijun Yang, Tangsen Huang, Deepu Rajan
2021 Advances in Multimedia  
In order to solve the above problems, a double-channel symmetric CNN vehicle recognition algorithm is proposed by improving the network structure.  ...  In this method, two samples are taken as input at the same time, in which each sample has complementary characteristics.  ...  At the same time, the recognition rate will be improved because the double-channel CNN network can input more features. is study attempts to design a double-channel symmetrical CNN structure for vehicle  ... 
doi:10.1155/2021/8899007 fatcat:kujnnm3ocjah3f75iod47lnedu

Applications of Artificial Intelligence in Transport: An Overview

Rusul Abduljabbar, Hussein Dia, Sohani Liyanage, Saeed Bagloee
2019 Sustainability  
Moreover, it is promising for transport authorities to determine the way to use these technologies to create a rapid improvement in relieving congestion, making travel time more reliable to their customers  ...  Examples of AI methods that are finding their way to the transport field include Artificial Neural Networks (ANN), Genetic algorithms (GA), Simulated Annealing (SA), Artificial Immune system (AIS), Ant  ...  Designing an optimal road method for transport planning is part of the Network Design Problem (NDP) [56] .  ... 
doi:10.3390/su11010189 fatcat:d25yx4iuzbd7hfrnhmjag7jzxq

Bandwidth Allocation Scheduling Algorithms for IEEE 802. 16 WiMax Protocol to Improve QoS: A Survey

Avinash Kaur, Harvinder Singh, Parveen Sharma
2014 International Journal of Computer Applications  
This paper evaluates and compare various existing algorithms and enlighten different issues in designing of these algorithms, furthermore a new bandwidth allocation scheduling algorithm is proposed for  ...  In recent times, wireless network is extensively accessed technology to connect remote user terminal with its primary network.  ...  This algorithm cannot be used for mobile networks because it does not give fair bandwidth and QoS for these networks [8] .To solve this problem, a scheduling algorithm [10] that combines CSDPS with  ... 
doi:10.5120/17227-7550 fatcat:pyyzdkekqjdt3n5zvzw7gr4tfu

Task Offloading Based on LSTM Prediction and Deep Reinforcement Learning for Efficient Edge Computing in IoT

Youpeng Tu, Haiming Chen, Linjie Yan, Xinyan Zhou
2022 Future Internet  
To reduce the cost of resources required for task offloading and improve the utilization of server resources, in this paper, we model the task offloading problem as a joint decision making problem for  ...  In the training phase of the model, this algorithm predicts the load of the edge server in real-time with the LSTM algorithm, which effectively improves the convergence accuracy and convergence speed of  ...  The algorithm combines Long Short-Term Memory (LSTM) and deep reinforcement learning (DRL) to predict task dynamic information in real-time, based on the observed edge network condition and the server  ... 
doi:10.3390/fi14020030 fatcat:qygvajrhivatlpkm77gq6py6ri

Generating 3D texture models of vessel pipes using 2D texture transferred by object recognition☆

Min-Ji Kim, Kyung-Ho Lee, Young-Soo Han, Jaejoon Lee, Byungwook Nam
2021 Journal of Computational Design and Engineering  
Therefore, this study investigates an improved CycleGAN algorithm that can be specifically applied to the shipbuilding industry by combining a modified object-recognition algorithm with a double normalization  ...  However, when applying CycleGAN's textures to pipe structures, the performance is insufficient for direct application to industrial piping networks.  ...  Double normalization The internal covariate shift problem, in which the input distribution of each layer of the network varies as the layer of the model becomes deeper, also occurs.  ... 
doi:10.1093/jcde/qwaa090 fatcat:roiwxngwrnetvnz4bmg5sscnu4

Double Ghost Convolution Attention Mechanism Network: A Framework for Hyperspectral Reconstruction of a Single RGB Image

Wenju Wang, Jiangwei Wang
2021 Sensors  
In this study, we propose the double ghost convolution attention mechanism network (DGCAMN) framework for the reconstruction of a single RGB image to improve the accuracy of spectral reconstruction and  ...  The proposed DGCAMN consists of a double ghost residual attention block (DGRAB) module and optimal nonlocal block (ONB).  ...  The shared perception layer share multilayer perceptron (MLP) contains a hidden layer for the size of the vector (r is the reduction ratio).  ... 
doi:10.3390/s21020666 pmid:33477959 fatcat:lg3t3w66aveh5e5vge3ghscwzq

Multipath Transmission for the Internet: A Survey

Ming Li, Andrey Lukyanenko, Zhonghong Ou, Antti Yla-Jaaski, Sasu Tarkoma, Matthieu Coudron, Stefano Secci
2016 IEEE Communications Surveys and Tutorials  
, application and cross layers; (2) we survey the state-of-the-art for each layer, investigate the problems that each layer aims to address, and make comprehensive assessment of the solutions; (3) based  ...  To that end, we present a survey on multipath transmission and make several major contributions: (1) we present a complete taxonomy pertaining to multipath transmission, including link, network, transport  ...  [27] presented a network layer architecture to aggregate bandwidth on multiple paths for real-time applications.  ... 
doi:10.1109/comst.2016.2586112 fatcat:vnpjtjx2dzfobbtzan5l6nnx7y

Learning Feature Fusion in Deep Learning-Based Object Detector

Ehtesham Hassan, Yasser Khalil, Imtiaz Ahmad
2020 Journal of Engineering  
The present work shows a qualitative approach to identify the best layer for fusion and design steps for feeding in the additional feature sets in convolutional network-based detectors.  ...  Object detection in real images is a challenging problem in computer vision.  ...  However, deep learning networks are designed for specific input sizes which pose a challenge for algorithm designer to feed in extra information in the network unless the network is redesigned. e work  ... 
doi:10.1155/2020/7286187 fatcat:6heao53bpnhahbvgb6p7ffb3l4

A Q-Cube Framework of Reinforcement Learning Algorithm for Continuous Double Auction among Microgrids

Ning Wang, Weisheng Xu, Weihui Shao, Zhiyu Xu
2019 Energies  
preferences and response to real-time market conditions.  ...  In this paper, we investigate the potential of applying a Q-learning algorithm into a continuous double auction mechanism.  ...  Due to the uncertainty and complexity of price intersections, a layering method and a price-prioritized quantity-weighted sharing rule are combined to solve the energy sharing problem.  ... 
doi:10.3390/en12152891 fatcat:z3adfrb7ivgiljavsm7puxsbie
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