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Role Detection in Bicycle-Sharing Networks Using Multilayer Stochastic Block Models [article]

Jane Carlen, Jaume de Dios Pont, Cassidy Mentus, Shyr-Shea Chang, Stephanie Wang, Mason A. Porter
2021 arXiv   pre-print
We apply these models to (1) detect the roles of bicycle-sharing docking stations and (2) describe the traffic within and between blocks of stations over the course of a day.  ...  Our work has direct application to the design and maintenance of bicycle-sharing systems, and it can be applied more broadly to community detection in temporal and multilayer networks with heterogeneous  ...  and others in the networks journal club at UCLA for helpful comments.  ... 
arXiv:1908.09440v2 fatcat:a4r7axw5m5bxxijiexvlze3glq

A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport [article]

Hector Rodriguez-Deniz, Mattias Villani, Augusto Voltes-Dorta
2022 arXiv   pre-print
This paper presents a state-of-the-art probabilistic latent network model to forecast multilayer dynamic graphs that are increasingly common in transportation and proposes a community-based extension to  ...  full network forecasts, while stochastic blockmodeling allows for the identification of relevant communities.  ...  Dynamic Multilayered Block Network Model To impose a community structure we assume that each vertex in the network belongs to a stochastic block (Nowicki and Snijders, 2001) or cluster b ∈ {1, . . .  ... 
arXiv:1911.13136v4 fatcat:fq7vpdtdhbdnnnltyqulmhu3mi

Research on Object Detection Algorithm Based on Multilayer Information Fusion

Bao-Yuan Chen, Yu-Kun Shen, Kun Sun
2020 Mathematical Problems in Engineering  
This paper proposes a multiscale feature reuse detection model, which includes the basic feature extraction network DenseNet, feature fusion network, multiscale anchor region proposal network, and classification  ...  At the same time, compared with the mainstream faster RCNN and SSD detection models, the mean average precision of object detection algorithm based on DenseNet is improved by 5.63% and 3.86%, respectively  ...  In the process of using GPU to train the model, we use the stochastic gradient descent (SGD) method to update the parameters of the network, because momentum can make the network more robust in training  ... 
doi:10.1155/2020/9076857 fatcat:ff3x3tdn7nhafpncvqxrgrz4ke

Analyzing the Performance of Multilayer Neural Networks for Object Recognition [chapter]

Pulkit Agrawal, Ross Girshick, Jitendra Malik
2014 Lecture Notes in Computer Science  
In the last two years, convolutional neural networks (CNNs) have achieved an impressive suite of results on standard recognition datasets and tasks.  ...  In this paper, we experimentally probe several aspects of CNN feature learning in an attempt to help practitioners gain useful, evidence-backed intuitions about how to apply CNNs to computer vision problems  ...  We do not have a good understanding of mid-level feature representations in multilayer networks.  ... 
doi:10.1007/978-3-319-10584-0_22 fatcat:jqau6bzenreytpjmpog3rk3veu

Analyzing the Performance of Multilayer Neural Networks for Object Recognition [article]

Pulkit Agrawal, Ross Girshick, Jitendra Malik
2014 arXiv   pre-print
In the last two years, convolutional neural networks (CNNs) have achieved an impressive suite of results on standard recognition datasets and tasks.  ...  In this paper, we experimentally probe several aspects of CNN feature learning in an attempt to help practitioners gain useful, evidence-backed intuitions about how to apply CNNs to computer vision problems  ...  We do not have a good understanding of mid-level feature representations in multilayer networks.  ... 
arXiv:1407.1610v1 fatcat:y37nzvpjgvek5eintyhy5p4woy

Deep Learning-Based Big Data Analytics for Internet of Vehicles: Taxonomy, Challenges, and Research Directions

Haruna Chiroma, Shafi'i M. Abdulhamid, Ibrahim A. T. Hashem, Kayode S. Adewole, Absalom E. Ezugwu, Saidu Abubakar, Liyana Shuib, Mohammad Yaghoub Abdollahzadeh Jamalabadi
2021 Mathematical Problems in Engineering  
In this paper, we present a survey and explore the theoretical perspective of the role of DL in the IoV within the context of BDA.  ...  The survey proposes a model of IoV environment integrated into the cloud equipped with a high-performance computing server, DL architecture, and Apache Spark for data analytics.  ...  of DL models for the development of a powerful adaptive intrusion detection system that can detect dynamic security threats in the IoV environment. us, the impact of the DDoS/DoS, ransomware, malware,  ... 
doi:10.1155/2021/9022558 fatcat:3qbyj4vpjjhctkemmndil7c34q

Enhancing feature fusion with spatial aggregation and channel fusion for semantic segmentation

Jie Hu, Huifang Kong, Lei Fan, Jun Zhou
2021 IET Computer Vision  
In addition, the complete network with U-shape structure is constructed.  ...  This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.  ...  IMICZ2017004 and the 111 Project BP0719039, and the computational resources used in this study are provided by the Automotive Electronics and Control Research Centre, Hefei University of Technology.  ... 
doi:10.1049/cvi2.12026 fatcat:bryfeojixbhpzny5z4cepabvna

Edge Computing and IoT Analytics for Agile Optimization in Intelligent Transportation Systems

Mohammad Peyman, Pedro J. Copado, Rafael D. Tordecilla, Leandro do C. Martins, Fatos Xhafa, Angel A. Juan
2021 Energies  
agile optimization algorithms for solving a dynamic ride-sharing problem (DRSP) in the context of edge/fog computing.These algorithms allow us to process, in real time, the data gathered from IoT systems  ...  Internet of Things (IoT) analytics refers to the use of these technologies, data, and analytical models to describe the current status of the city traffic, to predict its evolution over the coming hours  ...  The authors developed multiclass classifiers that identify the transportation model, e.g., driving a car, using a bus, riding a bicycle, walking, and running.  ... 
doi:10.3390/en14196309 fatcat:vpejvq4i2vd3he7mhtqpczwt2y

Program

2020 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan)  
Next, the similarity measurement using the Siamese network to evaluate the consistency of image block pairs is used to locate tampered areas.  ...  We use the binary LeNet model to achieve 91% accuracy in the MNIST dataset and use binary AlexNet model to achieve 67% accuracy in the CIFAR-10 dataset.  ...  In this paper, we demonstrated effectively the sensor wavelength detection techniques using Multi-Layer Perceptron Approach on the proposed shared Bus Network Architecture.  ... 
doi:10.1109/icce-taiwan49838.2020.9258230 fatcat:g25vw7mzvradxna2grlzp6kgiq

Toward intelligent flight control

R.F. Stengel
1993 IEEE Transactions on Systems, Man and Cybernetics  
Intelligent control functions fall in three categories. Declarative actions involve decision making, providing models for system monitoring, goal planning, and systemlscenario identification.  ...  Intelligent flight control systems will contain a hierarchy of expert systems, procedural algorithms, and computational neural networks, each expanding on prior functions to improve mission capability,  ...  Classical B-splines [ 1151 could be expressed in parallel form, and it has been suggested that they be used in multilayered networks [ 1 161.  ... 
doi:10.1109/21.257764 fatcat:stxvwzxibzf6xnusfpm66egl4i

Deep Learning for IoT Big Data and Streaming Analytics: A Survey [article]

Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour, Mohsen Guizani
2018 arXiv   pre-print
In this paper, we provide a thorough overview on using a class of advanced machine learning techniques, namely Deep Learning (DL), to facilitate the analytics and learning in the IoT domain.  ...  The potential of using emerging DL techniques for IoT data analytics are then discussed, and its promises and challenges are introduced.  ...  Data fusion and sharing play a critical role in developing ubiquitous environments based on IoT data.  ... 
arXiv:1712.04301v2 fatcat:kr64lst37rhlfcpaxckgzlozvu

The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping

Berit D. Brouer, Jakob Dirksen, David Pisinger, Christian E.M. Plum, Bo Vaaben
2013 European Journal of Operational Research  
We formulate and analyze a strategic design model for public bicycle sharing systems with service level considerations.  ...  predict the optimum time of van deliveries.Factors influencing the delivery process are depicted from various researches.Prediction is modeled as an artificial neural network using Back Propagation.The  ...  It makes use of a flexible network model with extensions including backhauling and cost sharing possibilities.  ... 
doi:10.1016/j.ejor.2012.08.016 fatcat:c27kagfnxnhjfbil2rydhjhomm

Machine Learning on the COVID-19 Pandemic, Human Mobility and Air Quality: A Review

Md. Mokhlesur Rahman, Kamal Chandra Paul, Md. Amjad Hossain, G. G. Md. Nawaz Ali, Md. Shahinoor Rahman, Jean-Claude Thill
2021 IEEE Access  
During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel to mitigate coronavirus-related health problems.  ...  This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by  ...  Another study in the US [59] developed a stochastic SEIRstyle epidemic model augmented by human mobility to predict historical growth trajectories of COVID-19 cases in two counties (Dane and Milwaukee  ... 
doi:10.1109/access.2021.3079121 pmid:34786314 pmcid:PMC8545207 fatcat:zpj7m7o5xvdslitzycrwzzsjvm

Far-Infrared Object Segmentation Focus on Transmission of Overall Semantic Information

Ying Zang, Bo Yu, Longjiao Yu, Dongsheng Yang, Qingshan Liu
2020 IEEE Access  
A large number of experiments confirm the effectiveness and robustness of the network in far-infrared images and verify that the dataset released in this article has strong reference significance.  ...  In the vision task of a self-driving system, the use of visible light images to segment an object often loses its functionality at night or in harsh weather.  ...  Finally, a multilayer tracking algorithm and background model are used to complete the segmentation.  ... 
doi:10.1109/access.2020.3028656 fatcat:l3uaytjfkzg2bh4qqwtiaz3dyy

Risk Assessment Inference Approach based on Geographical Danger Points using Student Survey Data for Safe Routes to School

Wenquan Jin, Azimbek Khudoyberdiev, Dohyeun Kim
2020 IEEE Access  
The role of the intelligent services is to sense the environment and analyze the data regarding the current zone, then predict and detect future risks.  ...  Among different GIS-based flood models presented in the literature, artificial neural networks [52] , frequency ratio [53] , logistic regression [54] , adaptive network-based fuzzy inference system  ... 
doi:10.1109/access.2020.3028852 fatcat:4lo5vgkzcrcbdpjajdxbjzoutm
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