To meet the ever-increasing computing demands of smart cities, intelligent vehicles with rapid growth can be an effective supplement to the computing power network by sharing their underutilized computing resources. C...
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ISBN:
(纸本)9798350399462
To meet the ever-increasing computing demands of smart cities, intelligent vehicles with rapid growth can be an effective supplement to the computing power network by sharing their underutilized computing resources. Considering that most of the vehicles are in the parked state, we call the computing paradigm as Parked-Vehicle Assisted computing (PAC). However, current PAC systems ignore the parking demands of vehicles, which should consider not only the income brought by the computing resource trade but also the time cost and energy consumption of vehicles during traveling to the parking lot. In this paper, we design a trade framework and two trade models in a PAC system to encourage vehicles to rent out idle computing resources to enhance the computing power network. The costs of time and energy of vehicles during traveling and the computing energy consumption of both vehicles and Edge Servers (ESs) are considered. Based on the models, we design two optimization problems: 1) the individual trade value maximization problem to obtain personalized trade information of a vehicle, including the target parking lot, and 2) the trade allocation problem for determining trade results by maximizing the combined trade value, i.e. the maximum sum of the individual trade value of the requesting vehicles. We propose a low-complexity greedy-based Trade Allocation Rule (TAR) to obtain the trade allocation strategy. Simulation results show that the proposed algorithm outperforms other benchmark schemes in allocation time and combined trade value.
Domestic Internet of Things (DioT) environment of a household requires prompt considerations in order to develop proper protection mechanisms for the transfer of sensitive information between linked devices. This crea...
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The proceedings contain 157 papers. The topics discussed include: design of agricultural environmental data collection system based on Internet of things;design of a portable license plate recognition system;detection...
ISBN:
(纸本)9781665441308
The proceedings contain 157 papers. The topics discussed include: design of agricultural environmental data collection system based on Internet of things;design of a portable license plate recognition system;detection of foreign bodies in periodic motion scenes using shape- and size-adaptive descriptors;power grid model data governance system based on Dcloud;design and implementation of a MEMS-based attitude angle measuring system for moving objects;research on short-term load forecasting under demand response of multi-type power grid connection based on dynamic electricity price;emotion analysis base on capsule network;SSS-Net for scene text recognition;optimal sizing of combined cooling, heating, and power system based on cluster analysis;and design of intelligent IOT system based on neural network learning.
With the worsening of urban traffic congestion, improving traffic flow and resource utilisation efficiency has become an important challenge in the field of intelligent transportation. Traditional traffic signal contr...
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It presents Autonomous Line Following Model, leveraging the transformative capabilities of Internet of Things (IoT) *** integration of real-time object detection ensures dynamic tracking of surrounding objects, while ...
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Missing diversity, equity, and inclusion elements in affective computing datasets directly affect the accuracy and fairness of emotion recognition algorithms across different groups. A literature review reveals how af...
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ISBN:
(纸本)9798350327434
Missing diversity, equity, and inclusion elements in affective computing datasets directly affect the accuracy and fairness of emotion recognition algorithms across different groups. A literature review reveals how affective computingsystems may work differently for different groups due to, for instance, mental health conditions impacting facial expressions and speech or age-related changes in facial appearance and health. Our work analyzes existing affective computing datasets and highlights a disconcerting lack of diversity in current affective computing datasets regarding race, sex/gender, age, and (mental) health representation. By emphasizing the need for more inclusive sampling strategies and standardized documentation of demographic factors in datasets, this paper provides recommendations and calls for greater attention to inclusivity and consideration of societal consequences in affective computing research to promote ethical and accurate outcomes in this emerging field.
A systematic analysis of approaches to the construction of controlsystems for the production of granular mineral fertilizers in a fluidized bed was carried out. The main technological parameters for the management of...
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As a typical condition of geriatric syndromes, it is speculated that frailty syndrome arises from dysfunctional feedback mechanisms among interacting physiological systems. To assess the frailty of the elderly for eff...
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ISBN:
(纸本)9798400716645
As a typical condition of geriatric syndromes, it is speculated that frailty syndrome arises from dysfunctional feedback mechanisms among interacting physiological systems. To assess the frailty of the elderly for effective prevention and control in comprehensive geriatric syndromes medical base, this paper proposes a hybrid intelligent approach. Firstly, the approach utilizes the grip strength change rate as an indicator, employs Density-Based Spatial Clustering of Applications with Noise (DBSCAN) for clustering elderly individuals and refines the clustering results. Subsequently, Synthetic Minority Over-sampling Technique with Edited Nearest Neighbors (SMOTE-ENN) is applied for oversampling and undersampling of samples, enhancing model performance by combining synthetic minority class samples (SMOTE) and removing redundancy in majority class samples (ENN). Finally, the Slime Mould Algorithm (SMA) is employed to optimize the hyperparameters of Categorical Boosting (CatBoost), enhancing classification accuracy. The method is trained using medical examination results and validated for classification accuracy on a test dataset. Compared to CatBoost, SMOTE-ENN-SMA-CatBoost exhibits improvements of 7.04%, 7.76%, and 7.52% in accuracy, precision, and F1 score, respectively. This integrated framework provides an effective solution for assessing frailty probability in the elderly population, enhancing accuracy and reliability.
For the interconnected large-scale systems, a dynamic event-triggered neural network-based approach is designed to solve the guaranteed cost control (GCC) problem in this paper. First, the decentralized GCC policies a...
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In the context of the rapid development of the Internet of Things, Electric power intelligent terminal is already an edge device of the 'cloud-management-edge-end' architecture of the intelligent Internet of T...
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