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

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

A Bibliometric Analysis of the Global Research Trend in Child Maltreatment

Child maltreatment remains a major health threat globally that requires the understanding of socioeconomic and cultural contexts to craft effective interventions. However, little is known about research agendas globally and the development of knowledge-producing networks in this field of study. This study aims to explore the bibliometric overview on child maltreatment publications to understand their growth from 1916 to 2018. Data from the Web of Science Core Collection were collected in May 2018. Only research articles and reviews written in the English language were included, with no restrictions by publication date. We analyzed publication years, number of papers, journals, authors, keywords and countries, and presented the countries collaboration and co-occurrence keywords analysis. From 1916 to 2018, 47, 090 papers (53.0% in 2010–2018) were published in 9442 journals. Child Abuse & Neglect (2576 papers; 5.5%); Children and Youth Services Review (1130 papers; 2.4%) and Pediatrics (793 papers, 1.7%) published the most papers. The most common research areas were Psychology (16, 049 papers, 34.1%), Family Studies (8225 papers, 17.5%), and Social Work (7367 papers, 15.6%). Among 192 countries with research publications, the most prolific countries were the United States (26, 367 papers), England (4676 papers), Canada (3282 papers) and Australia (2664 papers). We identified 17 authors who had more than 60 scientific items. The most cited papers (with at least 600 citations) were published in 29 journals, headed by the Journal of the American Medical Association (JAMA) (7 papers) and the Lancet (5 papers). This overview of global research in child maltreatment indicated an increasing trend in this topic, with the world’s leading centers located in the Western countries led by the United States. We called for interdisciplinary research approaches to evaluating and intervening on child maltreatment, with a focus on low-middle income countries (LMICs) settings and specific contexts

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024

The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE Xplore submission as part of WACV 202

1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

The 1$^{\text{st}}$ Workshop on Maritime Computer Vision (MaCVi) 2023 focused on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicle (USV), and organized several subchallenges in this domain: (i) UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking, (iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS benchmarks. This report summarizes the main findings of the individual subchallenges and introduces a new benchmark, called SeaDronesSee Object Detection v2, which extends the previous benchmark by including more classes and footage. We provide statistical and qualitative analyses, and assess trends in the best-performing methodologies of over 130 submissions. The methods are summarized in the appendix. The datasets, evaluation code and the leaderboard are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.Comment: MaCVi 2023 was part of WACV 2023. This report (38 pages) discusses the competition as part of MaCV

Vietnamese automatic speech recognition: the FLaVoR approach

Automatic speech recognition for languages in Southeast Asia, including Chinese, Thai and Vietnamese, typically models both acoustics and languages at the syllable level. This paper presents a new approach for recognizing those languages by exploiting information at the word level. The new approach, adapted from our FLaVoR architecture[1], consists of two layers. In the first layer, a pure acoustic-phonemic search generates a dense phoneme network enriched with meta data. In the second layer, a word decoding is performed in the composition of a series of finite state transducers (FST), combining various knowledge sources across sub-lexical, word lexical and word-based language models. Experimental results on the Vietnamese Broadcast News corpus showed that our approach is both effective and flexible. © 2006 Springer-Verlag Berlin/Heidelberg.Vu Q., Demuynck K., Van Compernolle D., ''Vietnamese automatic speech recognition : the FLaVoR approach'', Lecture notes in computer science, vol. 4274, pp. 464-474, 2006 (5th International Symposium Chinese Spoken Language Processing - ISCSLP 2006, December 13-16, 2006, Singapore).status: publishe