Comparison of layer-stacking and Dempster-Shafer theory-based methods using Sentinel-1 and Sentinel-2 data fusion in urban land cover mapping

Data fusion has shown potential to improve the accuracy of land cover mapping, and selection of the optimal fusion technique remains a challenge. This study investigated the performance of fusing Sentinel-1 (S-1) and Sentinel-2 (S-2) data, using layer-stacking method at the pixel level and Dempster-Shafer (D-S) theory-based approach at the decision level, for mapping six land cover classes in Thu Dau Mot City, Vietnam. At the pixel level, S-1 and S-2 bands and their extracted textures and indices were stacked into the different single-sensor and multi-sensor datasets (i.e. fused datasets). The datasets were categorized into two groups. One group included the datasets containing only spectral and backscattering bands, and the other group included the datasets consisting of these bands and their extracted features. The random forest (RF) classifier was then applied to the datasets within each group. At the decision level, the RF classification outputs of the single-sensor datasets within each group were fused together based on D-S theory. Finally, the accuracy of the mapping results at both levels within each group was compared. The results showed that fusion at the decision level provided the best mapping accuracy compared to the results from other products within each group. The highest overall accuracy (OA) and Kappa coefficient of the map using D-S theory were 92.67% and 0.91, respectively. The decision-level fusion helped increase the OA of the map by 0.75% to 2.07% compared to that of corresponding S-2 products in the groups. Meanwhile, the data fusion at the pixel level delivered the mapping results, which yielded an OA of 4.88% to 6.58% lower than that of corresponding S-2 products in the groups

Developing Formulas for Quick Calculation of Polyhedron Volume in Spatial Geometry: Application to Vietnam

In the age of globalization, an effective leadership skill is the ability for quick calculation of work-related problems. From an economic perspective, fast computation often provides a competitive advantage in business, where speed, efficiency and accuracy are required. Quick calculation techniques are a central problem in modern mathematics because it shortens the time for solving technical problems. The purpose of the paper is to provide an explanation that will lead to a quick solution to a volume problem. Specifically, some convenient formulas are provided for quick calculation of the volume of the common polyhedron, together with a number of multiple-choice questions with IATA software to practice. Based on the evaluation results, reliable multiple-choice questions are used for an empirical study in Can Tho City, Vietnam on the effectiveness of the formulas for quick calculation of the polyhedron volume in spatial geometry. Statistical analysis shows that quick formulas help students to complete lessons at a higher rate, thereby contributing to improvements in the effectiveness of teaching geometry, especially the volume of the Polyhedron

Analysis of Power and Torque for the IPM Motors with High Flux Density in Stator

The new idea of this paper is to focus on investigating the influence of characteristics on the power and torque of an Interior Permanent Magnet (IPM) motor designed by the Tesla rear-drive. The detail of improvement designs of double V (2V) shape and inverter delta (VI) shape has been proposed for electric vehicles taking a high constant torque in a wide range speed into account. The torque ripple, output power and torque density are developed and evaluated in different topologies via the finite element method. The two-layered rotor structure with the 2V and VI shapes is also designed to give the suitable choices for manufacturing in mass production. For the higher torque density and efficiency, the two-layered 2V or VI magnets of IPM motor with 72 slots/ 8 poles can be adjusted with the sinusoidal step skewing to minimize the torque ripple, harmonic components and back elec- tromotive force. The developed method is performed on the practical problem of the IPM motor of 200 kW −450 Nm, which is applied to the single drive system delivers

BoMb-OT: On Batch of Mini-batches Optimal Transport

Mini-batch optimal transport (m-OT) has been successfully used in practical applications that involve probability measures with intractable density, or probability measures with a very high number of supports. The m-OT solves several sparser optimal transport problems and then returns the average of their costs and transportation plans. Despite its scalability advantage, the m-OT does not consider the relationship between mini-batches which leads to undesirable estimation. Moreover, the m-OT does not approximate a proper metric between probability measures since the identity property is not satisfied. To address these problems, we propose a novel mini-batching scheme for optimal transport, named Batch of Mini-batches Optimal Transport (BoMb-OT), that finds the optimal coupling between mini-batches and it can be seen as an approximation to a well-defined distance on the space of probability measures. Furthermore, we show that the m-OT is a limit of the entropic regularized version of the BoMb-OT when the regularized parameter goes to infinity. Finally, we carry out extensive experiments to show that the BoMb-OT can estimate a better transportation plan between two original measures than the m-OT. It leads to a favorable performance of the BoMb-OT in the matching and color transfer tasks. Furthermore, we observe that the BoMb-OT also provides a better objective loss than the m-OT for doing approximate Bayesian computation, estimating parameters of interest in parametric generative models, and learning non-parametric generative models with gradient flow.Comment: 36 pages, 20 figure

Pedagogy undergraduates’ perception on twenty-first century skills

Teachers head up their students to the bright future, their role is indispensable, especially in the 21st century, which expects them to be energetic and flexible to apply knowledge to the daily life and carrier task. Examining the perception on 21st century skills teaching of pedagogy teacher-to-be undergraduates - plays a vital role in identifying deficits in teachers’ professional development; as well as organizing training programs to enhance their knowledge and skills. To the best of our knowledge, no study to date has examined pedagogy undergraduates’ perception in Vietnam. This study aimed at examining Vietnamese undergraduates' perception on teaching the 21st century skills. Our crosssectional study used the 21st Century Skills Teaching Scale. Descriptive analysis and ANOVA were performed in this research. The results showed that: (1) Vietnamese pedagogy students had a high level of perception on teaching the 21st century skills; (2) there was no gender difference in their perception; and (3) there was no significant difference in their perception regard to their school years and (4) there was significant difference between those having joined soft skill courses at their university and those having not joined anyone

Invited review. Natural rubber nanocomposites.

Natural rubber (NR) is a valuable and important polymer material that has wide and various applications. Therefore the investigations for NR improvement, particularly for special applications are in continuous development. In this trend, preparation of NR nanocomposites using nanofillers of both organic and inorganic origination is one of leading directions. In this paper, NR nanocomposites with the most popular and promising nanofillers were reviewed. These nanofillers are nanosilica and layered silicate as the most important fillers for NR industry after carbon black, and nanocellulose as a new abundant and environmental friendly filler. Methods of NR nanocomposites preparation were briefly summarized. The main attention was paid to the establishment of nanostructures in NR composites. Based on limited (about 80) references, mostly in recent 15 years, the improvement of NR nanocomposite properties was analyzed in connection with their nanostructure. Keywords. Natural rubber, nanocellulose, nanosilica, nanoclay, nanocomposite

Class based Influence Functions for Error Detection

Influence functions (IFs) are a powerful tool for detecting anomalous examples in large scale datasets. However, they are unstable when applied to deep networks. In this paper, we provide an explanation for the instability of IFs and develop a solution to this problem. We show that IFs are unreliable when the two data points belong to two different classes. Our solution leverages class information to improve the stability of IFs. Extensive experiments show that our modification significantly improves the performance and stability of IFs while incurring no additional computational cost.Comment: Thang Nguyen-Duc, Hoang Thanh-Tung, and Quan Hung Tran are co-first authors of this paper. 12 pages, 12 figures. Accepted to ACL 202