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- Quan-Hoang Vuong (27)
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This study adopts the bibliometric approach to identify the key characteristics in the relationship of demographic factors (age, gender, affiliations, and locations), scientific productivity, and the collaboration among development economics researchers in Vietnam during the period 2008–2020. Overall, the number of publications and authors in development economics are rising steeply with the average annual growth rate of nearly 23% and 26%, respectively. Moreover, the ‘quality’ of the research appears to be high as 59% of the articles are published in journals in the first and second quartile according Scimago journal ranking. However, the citation counts for these studies indicate their impacts are far more languishing in comparison. In terms of research trends, this study identifi... |
This work addresses the prediction and optimization of average surface roughness (Ra) and maximum flank wear (Vbmax) of 6061 aluminum alloy during high-speed milling. The investigation was done using a DMU 50 CNC 5-axis machine with Ultracut FX 6090 fluid. Four factors were examined: the table feed rate, cutting speed, depth of cut, and cutting length. Three levels of each factor were examined to conduct 81 experiment runs. The response parameters in these experiments were measurements of Ra and Vbmax. |
This short article represents the first attempt to define a new core cultural value that will enable engaging the business sector in humankind’s mission to heal nature. First, I start with defining the problem of the current business culture and the extant thinking on how to solve environmental problems, which I called “the eco-deficit culture.” Then, I present a solution to this problem by formulating the “semiconducting principle” of monetary and environmental values exchange, which I believe can generate “an eco-surplus business culture.” This work adds one new element, the eleventh cultural value, to the ten core values of progressive cultures postulated by Harrison (2000). |
Coronavirus disease 2019 (COVID-19) vaccine acceptance is essential in controlling the virus. Vaccine knowledge influences vaccine acceptance and understanding this is vital in planning immunization strategies |
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... |
