V2VR: Reliable Hybrid-Network-Oriented V2V Data Transmission and Routing Considering RSUs and Connectivity Probability

Gao, Honghao; Liu, Can; Li, Youhuizi; Yang, Xiaoxian

doi:10.1109/tits.2020.2983835

Cited by 217 publications

(141 citation statements)

References 42 publications

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“…Consequently, MF methods cannot achieve fine-grained modeling of user preferences on the various product aspects, leading to unexplainable recommendations. Moreover, because most of the entries are missing, a rating matrix is usually extremely sparse, which leads to cold start problems and low recommendation accuracy [9,10,34].…”

Section: Related Workmentioning

confidence: 99%

A recommendations model with multiaspect awareness and hierarchical user-product attention mechanisms

Dou

Liu

et al. 2020

ComSIS

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Neural network methods have been trained to satisfactorily learn user/product representations from textual reviews. A representation can be considered as a multiaspect attention weight vector. However, in several existing methods, it is assumed that the user representation remains unchanged even when the user interacts with products having diverse characteristics, which leads to inaccurate recommendations. To overcome this limitation, this paper proposes a novel model to capture the varying attention of a user for different products by using a multilayer attention framework. First, two individual hierarchical attention networks are used to encode the users and products to learn the user preferences and product characteristics from review texts. Then, we design an attention network to reflect the adaptive change in the user preferences for each aspect of the targeted product in terms of the rating and review. The results of experiments performed on three public datasets demonstrate that the proposed model notably outperforms the other state-of-the-art baselines, thereby validating the effectiveness of the proposed approach.

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Section: Related Workmentioning

confidence: 99%

A recommendations model with multiaspect awareness and hierarchical user-product attention mechanisms

Dou

Liu

et al. 2020

ComSIS

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“…But access by a large number of users can lead to the same problems, and efficient allocation of resources is required to address these problems [23][24]. Research has also been conducted to select and analyze information that users need from big data [25][26].…”

Section: Development Of Mobile Applicationmentioning

confidence: 99%

A study on the development of a light scattering particulate matter sensor and monitoring system

Choi¹,

Cho

2020

COMSIS J

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The gravimetric method, which is mainly used among particulate matter (PM) measurement methods, includes the disadvantages that it cannot measure PM in real time and it requires expensive equipment. To overcome these disadvantages, we have developed a light scattering type PM sensor that can be manufactured at low cost and can measure PM in real time. We have built a big data system that can systematically store and analyze the data collected through the developed sensor, as well as an environment where PM states can be monitored mobile in real time using such data. In addition, additional studies were conducted to analyze and correct the collected big data to overcome the problem of low accuracy, which is a disadvantage of the light scattering type PM sensor. We used a linear correction method and proceeded to adopt the most suitable value based on error and accuracy.

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“…The system data can be measured by sensors and transmitted to the management center through the communication module. The whole microgrid is controlled by using the edge computing technology [2,3,4,24]. The schematic diagram of edge computing for the benchmark microgrid system is shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

“…Different from the traditional automatic control, edge computing is more like an intelligent control method which is based on computing and information, and it mainly concerns the control strategies for dispatch and optimization. In [2], by means of road networks, the problems of frequently moving vehicles and network connectivity were analyzed, and then a modified greedy algorithm for vehicle wireless communication was proposed for network optimization. In [3], a holistic framework to attack the QoS prediction was developed in the IoT environment, and authors designed a fuzzy clustering algorithm which was capable of clustering contextual information.…”

Section: Introductionmentioning

confidence: 99%

A novel data-driven intelligent computing method for the secure control of a benchmark microgrid system

et al. 2020

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Microgrid is a small-scale cyber-physical system, and it generally suffers from various uncertainties. In this paper, we investigate the secure control problem of a benchmark microgrid with system uncertainties by using data-driven edge computing technology. First, the state-space function of the benchmark microgrid system is formulated, and parameter uncertainties are taken into consideration. Second, a novel data-driven intelligent computing method is derived from the modelbased reinforcement learning algorithm, which only requires system data instead of system models. By utilizing this computing method, the optimal control policy can be obtained in the model-free environment. Third, the Lyapunov stability theory is employed to prove that the uncertain microgrid can be asymptotically stabilized under the optimal control policy. Finally, simulation results demonstrate the control performance can be improved by tuning the parameters in the performance index function.

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V2VR: Reliable Hybrid-Network-Oriented V2V Data Transmission and Routing Considering RSUs and Connectivity Probability

Cited by 217 publications

References 42 publications

A recommendations model with multiaspect awareness and hierarchical user-product attention mechanisms

A recommendations model with multiaspect awareness and hierarchical user-product attention mechanisms

A study on the development of a light scattering particulate matter sensor and monitoring system

A novel data-driven intelligent computing method for the secure control of a benchmark microgrid system

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