Exploring acceptance of autonomous vehicle policies using KeyBERT and SNA: Targeting engineering students

This study aims to explore user acceptance of Autonomous Vehicle (AV) policies with improved text-mining methods. Recently, South Korean policymakers have viewed Autonomous Driving Car (ADC) and Autonomous Driving Robot (ADR) as next-generation means of transportation that will reduce the cost of transporting passengers and goods. They support the construction of V2I and V2V communication infrastructures for ADC and recognize that ADR is equivalent to pedestrians to promote its deployment into sidewalks. To fill the gap where end-user acceptance of these policies is not well considered, this study applied two text-mining methods to the comments of graduate students in the fields of Industrial, Mechanical, and Electronics-Electrical-Computer. One is the Co-occurrence Network Analysis (CNA) based on TF-IWF and Dice coefficient, and the other is the Contextual Semantic Network Analysis (C-SNA) based on both KeyBERT, which extracts keywords that contextually represent the comments, and double cosine similarity. The reason for comparing these approaches is to balance interest not only in the implications for the AV policies but also in the need to apply quality text mining to this research domain. Significantly, the limitation of frequency-based text mining, which does not reflect textual context, and the trade-off of adjusting thresholds in Semantic Network Analysis (SNA) were considered. As the results of comparing the two approaches, the C-SNA provided the information necessary to understand users' voices using fewer nodes and features than the CNA. The users who pre-emptively understood the AV policies based on their engineering literacy and the given texts revealed potential risks of the AV accident policies. This study adds suggestions to manage these risks to support the successful deployment of AVs on public roads.Comment: 29 pages with 11 figure

Time Is MattEr: Temporal Self-supervision for Video Transformers

Understanding temporal dynamics of video is an essential aspect of learning better video representations. Recently, transformer-based architectural designs have been extensively explored for video tasks due to their capability to capture long-term dependency of input sequences. However, we found that these Video Transformers are still biased to learn spatial dynamics rather than temporal ones, and debiasing the spurious correlation is critical for their performance. Based on the observations, we design simple yet effective self-supervised tasks for video models to learn temporal dynamics better. Specifically, for debiasing the spatial bias, our method learns the temporal order of video frames as extra self-supervision and enforces the randomly shuffled frames to have low-confidence outputs. Also, our method learns the temporal flow direction of video tokens among consecutive frames for enhancing the correlation toward temporal dynamics. Under various video action recognition tasks, we demonstrate the effectiveness of our method and its compatibility with state-of-the-art Video Transformers.Comment: Accepted to ICML 2022. Code is available at https://github.com/alinlab/temporal-selfsupervisio

Single-Molecule Three-Color FRET with Both Negligible Spectral Overlap and Long Observation Time

Full understanding of complex biological interactions frequently requires multi-color detection capability in doing single-molecule fluorescence resonance energy transfer (FRET) experiments. Existing single-molecule three-color FRET techniques, however, suffer from severe photobleaching of Alexa 488, or its alternative dyes, and have been limitedly used for kinetics studies. In this work, we developed a single-molecule three-color FRET technique based on the Cy3-Cy5-Cy7 dye trio, thus providing enhanced observation time and improved data quality. Because the absorption spectra of three fluorophores are well separated, real-time monitoring of three FRET efficiencies was possible by incorporating the alternating laser excitation (ALEX) technique both in confocal microscopy and in total-internal-reflection fluorescence (TIRF) microscopy

Post-intervention Status in Patients With Refractory Myasthenia Gravis Treated With Eculizumab During REGAIN and Its Open-Label Extension

OBJECTIVE: To evaluate whether eculizumab helps patients with anti-acetylcholine receptor-positive (AChR+) refractory generalized myasthenia gravis (gMG) achieve the Myasthenia Gravis Foundation of America (MGFA) post-intervention status of minimal manifestations (MM), we assessed patients' status throughout REGAIN (Safety and Efficacy of Eculizumab in AChR+ Refractory Generalized Myasthenia Gravis) and its open-label extension. METHODS: Patients who completed the REGAIN randomized controlled trial and continued into the open-label extension were included in this tertiary endpoint analysis. Patients were assessed for the MGFA post-intervention status of improved, unchanged, worse, MM, and pharmacologic remission at defined time points during REGAIN and through week 130 of the open-label study. RESULTS: A total of 117 patients completed REGAIN and continued into the open-label study (eculizumab/eculizumab: 56; placebo/eculizumab: 61). At week 26 of REGAIN, more eculizumab-treated patients than placebo-treated patients achieved a status of improved (60.7% vs 41.7%) or MM (25.0% vs 13.3%; common OR: 2.3; 95% CI: 1.1-4.5). After 130 weeks of eculizumab treatment, 88.0% of patients achieved improved status and 57.3% of patients achieved MM status. The safety profile of eculizumab was consistent with its known profile and no new safety signals were detected. CONCLUSION: Eculizumab led to rapid and sustained achievement of MM in patients with AChR+ refractory gMG. These findings support the use of eculizumab in this previously difficult-to-treat patient population. CLINICALTRIALSGOV IDENTIFIER: REGAIN, NCT01997229; REGAIN open-label extension, NCT02301624. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that, after 26 weeks of eculizumab treatment, 25.0% of adults with AChR+ refractory gMG achieved MM, compared with 13.3% who received placebo

Minimal Symptom Expression' in Patients With Acetylcholine Receptor Antibody-Positive Refractory Generalized Myasthenia Gravis Treated With Eculizumab

The efficacy and tolerability of eculizumab were assessed in REGAIN, a 26-week, phase 3, randomized, double-blind, placebo-controlled study in anti-acetylcholine receptor antibody-positive (AChR+) refractory generalized myasthenia gravis (gMG), and its open-label extension

Efficient and robust stress integration algorithm for anisotropic distortional hardening law under cross-loading with latent hardening

A fast and robust stress-update algorithm based on the general cutting-plane method (GCPM) was developed for a distortional hardening model, known as the HAH-DPS model. It captures the anisotropic hardening behaviors such as the Bauschinger effect, transient hardening, differential permanent softening, and cross-loading effects. The lower computational efficiency of the direct application of GCPM was rectified by considering the all-evolutionary plastic state variables during iterations. The newly proposed algorithm was formulated on the dependence of the equivalent plastic strain and the other state variables defined in the distortional hardening model. And it was implemented in a commercial finite element software using a user-defined material subroutine (UMAT). Finite element simulations under strain-path change were carried out to demonstrate the performance of the new numerical algorithm in terms of the convergence behavior locally as well as globally

A Fast 4K Video Frame Interpolation Using a Hybrid Task-Based Convolutional Neural Network

Visual quality and algorithm efficiency are two main interests in video frame interpolation. We propose a hybrid task-based convolutional neural network for fast and accurate frame interpolation of 4K videos. The proposed method synthesizes low-resolution frames, then reconstructs high-resolution frames in a coarse-to-fine fashion. We also propose edge loss, to preserve high-frequency information and make the synthesized frames look sharper. Experimental results show that the proposed method achieves state-of-the-art performance and performs 2.69x faster than the existing methods that are operable for 4K videos, while maintaining comparable visual and quantitative quality

Resource Minimized Static Mapping and Dynamic Scheduling of SDF Graphs

Abstract — In this paper, we focus on the throughput-constrained parallel execution of synchronous data flow graphs. This paper assumes static mapping and dynamic scheduling of nodes in contrast to the related work that assumes static scheduling. Since the scheduling order in dynamic scheduling is dependent on the priority assignment, three priority assignment methods are proposed and compared. If all task execution times do not vary at run-time, priority assignment is another way of storing a static schedule. We propose a static mapping technique to minimize the resource overhead considering both the processor cost and the total buffer size on all arcs under a given throughput constraint. Since the problem is NP-complete, a multi objective evolutionary algorithm is exploited to discover the mapping that minimizes the processor cost and the buffer requirement simultaneously. The experimental results show that the proposed technique requires fewer resources or higher average throughput than the previous approaches. Keywords-Mapping, buffer size minimization, SDF graph, dynamic scheduling, throughput, parallel execution I

Sugar-Sweetened Beverage Consumption in Relation to Obesity and Metabolic Syndrome among Korean Adults: A Cross-Sectional Study from the 2012–2016 Korean National Health and Nutrition Examination Survey (KNHANES)

It is well known that the consumption of sugar-sweetened beverages (SSBs) increases the risk of developing obesity and metabolic syndrome (MetS). However, there are not many studies investigating the link between SSBs and increased incidences of diseases in the Asian population, and in particular, in Korea. We explored the association of SSB consumption with the risk of developing obesity and MetS among Korean adults (12,112 participants from the 2012–2016 Korean National Health and Nutrition Examination Survey). We calculated the total SSB consumption frequency by counting each beverage item, including soda beverages, fruit juices, and sweetened rice drinks. Obesity was defined as a body mass index ≥25 kg/m2, and MetS was defined using the National Cholesterol Education Program, Adult Treatment Panel III. A survey logistic regression analyses was conducted to examine the association of SSB consumption with obesity and MetS, adjusting for related confounders such as age, energy intake, household income, education, alcohol drinking, smoking status, and physical activity. The SSB consumption was positively associated with an increased risk of the prevalence for obesity (Odd ratio (OR): 1.60; 95% confidence interval (CI): 1.23–2.09; p for trend = 0.0009) and MetS (OR: 1.61; 95% CI: 1.20–2.16; p for trend = 0.0003) among women. In men, SSB consumption only contributed to a higher prevalence of obesity (OR: 1.38; 95% CI: 1.11–1.72; p for trend = 0.0041). In conclusion, increased consumption of SSBs was closely linked with a higher prevalence of obesity and MetS in the Korean population

Chassis Design Target Setting for a High-Performance Car Using a Virtual Prototype

In this study, the chassis design target setting for a high-performance car was performed using a virtual prototype to solve the problem of increasing complexity of vehicle development. To achieve efficient handling performance of Hyundai Avante N, a high-performance vehicle, the kinematic and compliance (K&C) characteristics of the chassis corresponding to the design target were set prior to the design process using virtual simulation, thereby facilitating the efficient and systematic development of the actual vehicle. In order to overcome the limitations of existing research and apply it to the actual development of mass-production vehicles, the following major tasks were performed. The first is setting quantitative factors that match the sensibility evaluation. The second is building a virtual model to ensure consistency in performance predictions. The third is optimizing the chassis characteristics to achieve the vehicle performance goal. When all optimization results were applied, the average of the performance items increased by 0.5 points and the standard deviation improved by 0.4 points compared to the existing Civic Type-R, which was the best. In the case of the final specification considering design constraints, the average of performance items increased by 0.1 point and the standard deviation improved by 0.5 point compared to the existing Civic Type-R. Therefore, the design target of the chassis systems that could achieve the vehicle handling performance goal could be established prior to the design. Using this virtual development, it is possible to eliminate the trial and error process that the first and second test cars needed. This could save more than 500,000 USD (per unit trim) of the first and second test vehicles