Computing Crisp Bisimulations for Fuzzy Structures

Fuzzy structures such as fuzzy automata, fuzzy transition systems, weighted social networks and fuzzy interpretations in fuzzy description logics have been widely studied. For such structures, bisimulation is a natural notion for characterizing indiscernibility between states or individuals. There are two kinds of bisimulations for fuzzy structures: crisp bisimulations and fuzzy bisimulations. While the latter fits to the fuzzy paradigm, the former has also attracted attention due to the application of crisp equivalence relations, for example, in minimizing structures. Bisimulations can be formulated for fuzzy labeled graphs and then adapted to other fuzzy structures. In this article, we present an efficient algorithm for computing the partition corresponding to the largest crisp bisimulation of a given finite fuzzy labeled graph. Its complexity is of order $O((m\log{l} + n)\log{n})$, where $n$, $m$ and $l$ are the number of vertices, the number of nonzero edges and the number of different fuzzy degrees of edges of the input graph, respectively. We also study a similar problem for the setting with counting successors, which corresponds to the case with qualified number restrictions in description logics and graded modalities in modal logics. In particular, we provide an efficient algorithm with the complexity $O((m\log{m} + n)\log{n})$ for the considered problem in that setting

Identifying the influence of airbag structure on driver injury during a crash using a dummy model

This study undertakes the analysis of collision scenario using a car model with a dummy and airbags, in the event of a direct collision with a hard wall, one of the necessary studies of passive safety. To describe in detail, the input conditions, a simulation problem of the driver's seat displacements was performed and this displacements data was exported as boundary conditions for the collision simulation. The results simulation crash show that the calculated energy values and simulation results are approximately the same (7.381E+07 and 7.367E+07), energy is converted from kinetic energy into internal energy of the elements. The airbag deployment simulation results are similar to NHTSA's previous research, both in terms of graph shape and maximum value. The impact of the collision incident on the driver is not excessively large, as evidenced by surveys on head (HIC 300), thigh (F 2.8 kN), and neck (F3,098 kN; T 190 Nm) injuries. However, the study proceeds to further analyze and assess the airbag's structure, examining its influence on these metrics, concluding that changes in the exhaust valve size (increase from 1000 mm2 to 2000 mm2) lead to a reduction in the evaluated parameters. These results suggest changes to the airbag structure to enhance driver safety, as well as a simpler simulation model to save analysis tim

The Impact of Digital Transformation on Customer Satisfaction to Digital Banking Service of Commercial Banks in Vietnam

The present study focuses on examining the interplay and correlation between the digital transformation process as assessed by the digital banking service quality components (Ease of use, Effectiveness, Interoperability, Privacy/ Security, Empathy, Responsiveness, Reliability, Service portfolios, Service charge) and customer satisfaction for digital banking services at commercial banks in Vietnam. The predictors (independent variables) for this study are the aforementioned service quality aspects and moderator is Service charge. The outcome variable (dependent variable) is customer satisfaction. The authors combined qualitative and quantitative research techniques to develop observed variables and assess the model's fit. This study can help banking leaders evaluate and improve the quality of digital banking services in the context of financial liberalization and globalization. Keywords: Digital transformation, Digital Banking, Banking service quality, Customer satisfaction DOI: 10.7176/EJBM/15-6-04 Publication date:March 31st 202

Inland vessels emission inventory: distribution and emission characteristics in the Red River, Hanoi, Vietnam

Purpose – Shipping is a major source of air pollution, causing severe impacts on the environment and human health, greatly contributing to the creation of greenhouse gases and influencing climate change. The research was investigated to provide a better insight into the emission inventories in the Red River in Hanoi (Vietnam) that is often heavily occupied as the primary route for inner-city waterway traffic. Design/methodology/approach – The total emissions of seven different pollutants (PM10, PM2.5, SOx, CO, CO2, NOx and HC) were estimated using the SPD-GIZ emission calculation model. Findings – The results show that CO2 has the most significant contribution to the gas volume emitted: 103.21 tons/day. Remarkably, bulk carriers are the largest emission vehicle, accounting for more than 97% of total emissions, due to their superior number and large capacity. Social implications – The result to have a roadmap for making efforts to fulfil its commitment so that it could achieve its net-zero climate target by 2050 in Vietnam as committed at COP26. Originality/value – In this research, the number of vehicles and types of vessels travelling on the Red River flowing within Hanoi territory and other activity data are reported. The tally data will be used to estimate emissions of seven different pollutants (PM10, PM2.5, SOx, CO, CO2, NOx and HC) using a method combining both top-down and bottom-up approaches

Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound Diagnosis

Breast Ultrasound plays a vital role in cancer diagnosis as a non-invasive approach with cost-effective. In recent years, with the development of deep learning, many CNN-based approaches have been widely researched in both tumor localization and cancer classification tasks. Even though previous single models achieved great performance in both tasks, these methods have some limitations in inference time, GPU requirement, and separate fine-tuning for each model. In this study, we aim to redesign and build end-to-end multi-task architecture to conduct both segmentation and classification. With our proposed approach, we achieved outstanding performance and time efficiency, with 79.8% and 86.4% in DeepLabV3+ architecture in the segmentation task.Comment: 7 pages, 3 figure