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The COVID-19 pandemic has caused extraordinary disruptions to education systems globally, forcing a rapid switch from conventional to online education. Although some qualitative studies have been carried out exploring the online education experiences of nursing students and faculty members during the COVID-19 pandemic, to our knowledge, no study has used the Photovoice approach |
People counting plays a crucial role in various sensing applications such as in smart cities and shopping malls. In this paper, we propose a data-driven solution that uses a low power ultra-wideband impulse (UWB) radar to count the number of random walking people in an indoor space. A pre-processing signal processing method is applied to clean clutter signals from UWB radar. Instead of the conventional counting methods, which manually extract features and learned from effective data patterns, we investigated deep convolutional neural networks (CNNs) that automatically learn from the data to count the number of people in an indoor space. The CNN model could accurately predict up to 97% accuracy for up to 10 people random walking in an area of 5 × 5 m. The different settings of the CN... |
Plant-leaf diseases have become a significant threat to food security due to reducing the quantity and quality of agricultural products. Plant disease detection methods are commonly based on experience through manual observations of leaves. Developing fast, accurate, and automated techniques for identifying of crop diseases using computer vision and artificial intelligence (AI) can help overcome human shortcomings. In the current study, the EfficientNet architectures with pre-trained Noisy-Student weights were implemented using the transfer learning approach to classify leaf image-based healthy and diseased plant groups. The deep learning models were performed on the extended and enhanced PlantVillage datasets, consisting of leaf images of 14 different plant species, with background... |
Adopting unmanned aerial vehicles (UAV), also known as drones, into the last-mile-delivery sector and having them work alongside trucks with the aim of improving service quality and reducing the transportation cost gives rise to a new class of Vehicle Routing Problems (VRPs). In this paper, we introduce a new optimization problem called the min-cost Parallel Drone Scheduling Vehicle Routing Problem (PDSVRP). This problem is a variant of the well-known Parallel Drone Scheduling Traveling Salesman Problem (PDSTSP) recently introduced in the literature in which we allow multiple trucks and consider the objective of minimizing the total transportation costs. We formulate the problem as a Mixed Integer Linear Program and then develop a Ruin and Recreate () algorithm. Exploiting PDSVRP so... |
A resonant microcantilever sensor is fabricated from a zinc oxide (ZnO) thin film, which serves as both the structural and sensing layers. An open-air spatial atomic layer deposition technique is used to deposit the ZnO layer to achieve a ∼200 nm thickness, an order of magnitude lower than the thicknesses of conventional microcantilever sensors. The reduction in the number of layers, in the cantilever dimensions, and its overall lower mass lead to an ultrahigh sensitivity, demonstrated by detection of low humidity levels. A maximum sensitivity of 23649 ppm/% RH at 5.8% RH is observed, which is several orders of magnitude larger than those reported for other resonant humidity sensors. Furthermore, the ZnO cantilever sensor is self-actuated in air, an advantageous detection mode that ... |
Future Internet involves several emerging technologies such as 5G and beyond 5G networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of Things (IoTs). Moreover, the future Internet becomes heterogeneous and decentralized with a large number of involved network entities. Each entity may need to make its local decision to improve the network performance under dynamic and uncertain network environments. Standard learning algorithms such as single-agent Reinforcement Learning (RL) or Deep Reinforcement Learning (DRL) have been recently used to enable each network entity as an agent to learn an optimal decision-making policy adaptively through interacting with the unknown environments. However, such an algorithm fails to model the cooperations or competition... |
Low driving field-induced large strain in ternary lead-free Na0.5Bi0.5TiO3-SrTiO3-ABO3 piezoceramics In this letter, three ternary lead-free Na0.5Bi0.5TiO3-SrTiO3-ABO3 piezoceramics (ABO3 = LiNbO3, BaZrO3, and LaFeO3) were studied. The addition of ABO3 into Na0.5Bi0.5TiO3-SrTiO3 ceramic induces a ferroelectric tetragonal-to-ergodic relaxor pseudocubic phase transition, resulting in the significant disruption of ferroelectric order with the shift of the ferroelectric-relaxor transition temperature down to below room temperature. The conventional furnace sintering and microwave sintering methods are conducted in this study to improve the electric field-induced strain properties of BNST-LN piezoceramic. Interestingly, the Na0.5Bi0.5TiO3-SrTiO3-LiNbO3 sample sintered via microwave sintering method shows an ultrahigh normalized strain of 995 pm/V at an ultralow driving field of 2 kV/mm,... |
Network Function Virtualization (NFV) can support customized on- demand network services with flexibility and cost-efficiency. Virtual Network Function (VNF) instances need to be scaled out, scaled in, and reallocated across the NFV infrastructure (NFVI) to avoid a violation of service agreements when the demand traffic changes. However, selecting the new placement of VNFs for migrating a service function chain (SFC) is an issue of efficient NFV control. We propose two novel integer linear programming (ILP) models and two approximation algorithms for SFC placement and migration to maximize the cost-efficiency of an NFV network regarding the changes of service demands and dynamic routing. The ILP models allow us to obtain the optimal solutions of SFC placement and migration with expl... |
Vietnam is a fast-growing economy with a population of more than 100 million peo-ple. Along with the stable development of the country’s economy, a mindset focusing |
In this work, Ag@ZnO and Ag@ZnO/MgAC photocatalysts were synthesized using a simple two-step electrochemical method by the addition of magnesium aminoclay (MgAC) as a great stabilizer and a Lewis base, which could donate electrons for reduction of Ag+ and Zn2+ ions, facilitating uniform formation as well as effective inhibition of aggregation of Ag@ZnO nanoparticles (NPs) on the MgAC matrix. Ag@ZnO and Ag@ZnO/MgAC were investigated for photocatalytic degradation of MB and their antibacterial efficiencies. Ag@ZnO/MgAC showed excellent photocatalytic MB degradation with a performance of 98.56% after 80 min of visible-light irradiation and good antibacterial activity against Salmonella (Sal) and Staphylococcus aureus (S. aureus) bacterial strains, providing promising high application p... |
