arXiv subjects

Na Du

Publications and source records attributed to Na Du.

15 recordsLinked to original sources

arXiv2026

A Two-Stage Framework for Ego-Centric Key Object Identification via Object State Prediction

This paper presents a novel framework designed to enhance key object identification in autonomous driving. Existing methods primarily focus on either detecting objects independently or leveraging visual relationships, but they do not explicitly consider the ego vehicle's perspective in determining object importance. To address this gap, we propose a structured approach that integrates a virtual ego-vehicle representation and a modular object state predictor, enabling a more accurate estimation of object behaviors relative to the ego-vehicle. Subsequently, our framework employs spatial-temporal reasoning to refine key object identification, prioritizing objects based on their states and relative spatial information rather than relying solely on visual relationships. Experimental results on real-world driving datasets demonstrate the effectiveness of our approach in accurately detecting critical objects in complex traffic environments.

cs.CV↗

arXiv2026

VRSafe: A Secure Virtual Keyboard to Mitigate Keystroke Inference in Virtual Reality

Password-based authentication is one of the most commonly used methods for verifying user identities, and its widespread usage continues in virtual reality (VR) applications. As a result, various forms of attacks on password-based authentication in traditional environments such as keystroke inference and shoulder surfing, are still effective in VR applications. While keystroke inference attacks on virtual keyboards have been studied extensively, few efforts have developed an effective and cost-efficient defense strategy to mitigate keystroke inferences in VR. To address this gap, this paper presents a novel QWERTY keyboard called \textit{VRSafe} that is resilient to keystroke inference attacks. The proposed keyboard carefully introduces false positive keystrokes into the information collected by attackers during the typing process, making the inference of the original password difficult. \textit{VRSafe} also incorporates a novel malicious login detector that can effectively identify unauthorized login attempts using credentials inferred from keystroke inference attacks with high detection rate and minimal time and memory cost. The proposed design is evaluated through both simulation experiments and a real-world user study, and the results show that \textit{VRSafe} can significantly reduce the accuracy of keystroke inference attacks while incurring a modest overhead from a usability standpoint.

cs.CR↗

arXiv2025

DriveBLIP2: Attention-Guided Explanation Generation for Complex Driving Scenarios

This paper introduces a new framework, DriveBLIP2, built upon the BLIP2-OPT architecture, to generate accurate and contextually relevant explanations for emerging driving scenarios. While existing vision-language models perform well in general tasks, they encounter difficulties in understanding complex, multi-object environments, particularly in real-time applications such as autonomous driving, where the rapid identification of key objects is crucial. To address this limitation, an Attention Map Generator is proposed to highlight significant objects relevant to driving decisions within critical video frames. By directing the model's focus to these key regions, the generated attention map helps produce clear and relevant explanations, enabling drivers to better understand the vehicle's decision-making process in critical situations. Evaluations on the DRAMA dataset reveal significant improvements in explanation quality, as indicated by higher BLEU, ROUGE, CIDEr, and SPICE scores compared to baseline models. These findings underscore the potential of targeted attention mechanisms in vision-language models for enhancing explainability in real-time autonomous driving.

cs.RO↗

arXiv2025

Determining Linker Ratios of Mixed Metal-Organic Frameworks via Magnetic Susceptibility Measurements

Partial replacement of the organic linkers of metal-organic frameworks (MOFs) often optimizes their functionalities, however, accurate characterization of their molar ratios in many cases is challenging. This work presents a method of determining such linker ratios via measurements of the magnetic susceptibility of small quantities of powdered samples. The main presumption is taking the diamagnetic and paramagnetic contributions to the molar magnetic susceptibility of the two parent MOFs to be additive. To verify this, four examples are provided with commonly used MOFs to represent the cases when both parent MOFs are either paramagnetic or diamagnetic but with different linkers with the following systems: [MIL-101(Cr)-SO$_3$H]$_{(1-\delta)}$[MIL-101(Cr)-NO$_2$]$_{\delta}$, [EuMOF]$_{(1-\delta)}$[EuPDCA]$_{\delta}$, [UiO-66-COOH]$_{(1-\delta)}$[UiO-66]$_{\delta}$ and [MIL-101(Cr) F Free]$_{(1-\delta)}$[MIL-53(Al)]$_{\delta}$, where 1-$\delta$ : $\delta$ are the ratios to be determined. Depending on whether the systems were strictly paramagnetic, strictly diamagnetic or mixed, the experimental error of $\delta$ ranged between 0.00002 and 0.012, respectively. We expect the presented method to be widely employed since samples only need to be in powdered form and because there is a lack of characterization tools in the area of MOF linker ratios. The presented method is also applicable to resolving the ratios of mixed ordinary paramagnetic systems as well as other types of non-magnetic composite materials such as tapes, zeolites and thin films.

cond-mat.mtrl-sci↗

arXiv2025

Colossal Dielectric Response and Electric Polarization in Lithium Nitrate

Lithium nitrate LiNO$_3$ is identified to possess a dielectric constant $\epsilon$' larger than 6x10$^6$ at 1 kHz in powder samples above the critical temperature $T$$_W$ = 306 K. For single crystalline samples, $\epsilon$' can be sustained to remain above 10$^5$ and the dissipation factor below 10 in the temperature region of 280-340 K after a simple 'activation' process. Moreover, pyroelectric current measurements show LiNO$_3$ to be ferroelectric with an electric polarization of $P$ = 1,200 $\mu$C/cm$^2$. Both $\epsilon$' and $P$ are amongst one of the highest in all known materials. We propose a model suggesting the mechanism underlying the colossal magnitudes of $\epsilon$' and $P$ to stem from a gearing-ungearing process of the planar NO$_3$$^-$ at the macroscopic level. Our results potentially push the boundaries of ceramic capacitors.

cond-mat.mtrl-sci↗

arXiv2025

Magnetism based on nitrate-nitrate interactions: The cases of LiNO$_3$, K$_{0.5}$Rb$_{0.5}$NO$_3$, Ca(NO$_3$)$_2$ and C(NH$_2$)$_3$NO$_3$

Long-range magnetic ordering of the orbital motion of oxygen atoms within NO$_3$$^-$ cations is identified from experimental measurements of the magnetic susceptibility $\chi$($T$) in LiNO$_3$, Ca(NO$_3$)$_2$, K$_{0.5}$Rb$_{0.5}$NO$_3$ and C(NH$_2$)$_3$NO$_3$ at their respective order-disorder, solid-solid phase transitions $T$$_N$. The observed sharp changes in $\chi$($T$) and accompanying hysteretic behavior indicate the phase transitions to be first order. A model employing the law of conservation of angular momentum is used to explain why the librations between neighboring NO$_3$$^-$ become geared below $T$$_N$. Since the periodic motions involve concerted motion of net charges, the associated magnetic moments of the NO$_3$$^-$ ions indirectly establish an antiferromagnetic structure below $T$$_N$. Our findings identify a previously unidentified type of molecular interaction which may be exploited to further increase the enthalpy of the widely-popular hydrated salts employed as energy storage devices.

cond-mat.mtrl-sci↗

arXiv2025

Gearing of nitrate ions in ammonium nitrate

Reorienting polyatomic ions such as NH4+ and NO3- exhibit weak magnetic fields because the ions at the extremities trace out current loops; if the periodic reorientations become long-range ordered (i.e. gearing of neighboring NO3-), then the magnetic susceptibility should exhibit a unique signature along the different crystallographic axes. For the case of ammonium nitrate NH4NO3, we report the presence of two successive sharp steps in the molar magnetic susceptibility along the a- and b-axes upon crossing its order-disorder phase transition (from phase IV to phase II). We suggest the first step pertains to the NO3- planes shifting away from facing only along the b-axis and onto the a-axis by 45{\deg}. The second step is attributed to the disordering (ungearing) of the NH4+ and NO3-. In contrast, only one step was observed in the magnetic susceptibility along the c-axis and its large magnitude suggest the NO3- remain weakly correlated even in phase I at 400 K. We also find evidence that the NH4+ become magnetically ordered (geared) along the c-axis only until phase V. The approach employed in this work can be extended to experimentally study the lattice dynamics of other solids possessing planar ions such as amphidynamic crystals.

physics.chem-ph↗

arXiv2024

Inducing ferroelectricity in NH$_4$I and NH$_4$Br via partial replacement of protons by deuterons

While all of the polymorphs of NH$_4$I and NH$_4$Br are non-polar, a reversible electric polarization is established in the ordered $\gamma$ phases of (NH$_4$)$_{0.73}$(ND$_4$)$_{0.27}$I and (NH$_4$)$_{0.84}$(ND$_4$)$_{0.16}$Br (where D is $^2$H) via $dc$ electric fields. The presence of two groups of orbital magnetic moments appears to be responsible for the asymmetric lattice distortions. Our findings provide an alternative pathway for hydrogen-based materials to potentially add a ferroelectric functionality.

cond-mat.mtrl-sci↗

arXiv2024

Determining the chemical composition of diamagnetic mixed solids via measurements of the magnetic susceptibility

Mixed solid compounds are employed in a vast array of applications so an accurate determination of their chemical compositions is of crucial importance. All current characterization methods require specially-treated samples so the availability of a more practical method with similar accuracy should alleviate the quantification process. In this work, we show how the doping concentration $\delta$ (or isotope concentration) of a mixed solid compound in powdered form, where both parent compounds are diamagnetic, can be obtained from the measurement of the mass magnetization. We exploit the additive nature of the molar magnetic susceptibility $\chi_{Mol}$ and molar mass to construct two equations with the same two unknowns in the $\chi_{Mol}$ vs. $\delta$ space to simultaneously solve $\chi_{Mol}$ and $\delta$ of a mixed solid. Eight examples are provided to show the wide applicability of this method: NH$_{4(1-\delta)}$D$_{4\delta}$Br (where D = $^2$H), NH$_4$I$_{1-\delta}$Br$_\delta$, (NH$_4$H$_2$)$_{1-\delta}$(ND$_4$D$_2$)$_\delta$PO$_4$, C$_{48}$H$_{22+6\delta}$Br$_{6(1-\delta)}$O$_{32}$Zr$_6$, [creatine]$_{1-\delta}$[$_D$-glucose]$_\delta$, [$_L$-glutamic acid]$_{1-\delta}$[$_L$-leucine]$_\delta$, [terephthalic acid]$_{1-\delta}$[trimesic acid]$_\delta$ and [p-terphenyl]$_{1-\delta}$[triphenylphosphine]$_\delta$. Experimental errors of ~1.2% were obtained for $\delta$ from average sample masses of 16.6 mg in powdered form rendering the presented approach an attractive choice for characterizing the ratios of mixed solids.

cond-mat.mtrl-sci↗

arXiv2024

Improving Explainable Object-induced Model through Uncertainty for Automated Vehicles

The rapid evolution of automated vehicles (AVs) has the potential to provide safer, more efficient, and comfortable travel options. However, these systems face challenges regarding reliability in complex driving scenarios. Recent explainable AV architectures neglect crucial information related to inherent uncertainties while providing explanations for actions. To overcome such challenges, our study builds upon the "object-induced" model approach that prioritizes the role of objects in scenes for decision-making and integrates uncertainty assessment into the decision-making process using an evidential deep learning paradigm with a Beta prior. Additionally, we explore several advanced training strategies guided by uncertainty, including uncertainty-guided data reweighting and augmentation. Leveraging the BDD-OIA dataset, our findings underscore that the model, through these enhancements, not only offers a clearer comprehension of AV decisions and their underlying reasoning but also surpasses existing baselines across a broad range of scenarios.

cs.AI↗

arXiv2021

Predicting Driver Takeover Time in Conditionally Automated Driving

It is extremely important to ensure a safe takeover transition in conditionally automated driving. One of the critical factors that quantifies the safe takeover transition is takeover time. Previous studies identified the effects of many factors on takeover time, such as takeover lead time, non-driving tasks, modalities of the takeover requests (TORs), and scenario urgency. However, there is a lack of research to predict takeover time by considering these factors all at the same time. Toward this end, we used eXtreme Gradient Boosting (XGBoost) to predict the takeover time using a dataset from a meta-analysis study [1]. In addition, we used SHAP (SHapley Additive exPlanation) to analyze and explain the effects of the predictors on takeover time. We identified seven most critical predictors that resulted in the best prediction performance. Their main effects and interaction effects on takeover time were examined. The results showed that the proposed approach provided both good performance and explainability. Our findings have implications on the design of in-vehicle monitoring and alert systems to facilitate the interaction between the drivers and the automated vehicle.

cs.LG↗

arXiv2020

Psychophysiological responses to takeover requests in conditionally automated driving

In SAE Level 3 automated driving, taking over control from automation raises significant safety concerns because drivers out of the vehicle control loop have difficulty negotiating takeover transitions. Existing studies on takeover transitions have focused on drivers' behavioral responses to takeover requests (TORs). As a complement, this exploratory study aimed to examine drivers' psychophysiological responses to TORs as a result of varying non-driving-related tasks (NDRTs), traffic density and TOR lead time. A total number of 102 drivers were recruited and each of them experienced 8 takeover events in a high fidelity fixed-base driving simulator. Drivers' gaze behaviors, heart rate (HR) activities, galvanic skin responses (GSRs), and facial expressions were recorded and analyzed during two stages. First, during the automated driving stage, we found that drivers had lower heart rate variability, narrower horizontal gaze dispersion, and shorter eyes-on-road time when they had a high level of cognitive load relative to a low level of cognitive load. Second, during the takeover transition stage, 4s lead time led to inhibited blink numbers and larger maximum and mean GSR phasic activation compared to 7s lead time, whilst heavy traffic density resulted in increased HR acceleration patterns than light traffic density. Our results showed that psychophysiological measures can indicate specific internal states of drivers, including their workload, emotions, attention, and situation awareness in a continuous, non-invasive and real-time manner. The findings provide additional support for the value of using psychophysiological measures in automated driving and for future applications in driver monitoring systems and adaptive alert systems.

cs.HC↗

arXiv2020

Enhancing autonomy transparency: an option-centric rationale approach

While the advances in artificial intelligence and machine learning empower a new generation of autonomous systems for assisting human performance, one major concern arises from the human factors perspective: Humans have difficulty deciphering autonomy-generated solutions and increasingly perceive autonomy as a mysterious black box. The lack of transparency contributes to the lack of trust in autonomy and sub-optimal team performance. To enhance autonomy transparency, this study proposed an option-centric rationale display and evaluated its effectiveness. We developed a game Treasure Hunter wherein a human uncovers a map for treasures with the help from an intelligent assistant, and conducted a human-in-the-loop experiment with 34 participants. Results indicated that by conveying the intelligent assistant's decision-making rationale via the option-centric rationale display, participants had higher trust in the system and calibrated their trust faster. Additionally, higher trust led to higher acceptance of recommendations from the intelligent assistant, and in turn higher task performance.

cs.HC↗

arXiv2020

Examining the Effects of Emotional Valence and Arousal on Takeover Performance in Conditionally Automated Driving

In conditionally automated driving, drivers have difficulty in takeover transitions as they become increasingly decoupled from the operational level of driving. Factors influencing takeover performance, such as takeover lead time and the engagement of non-driving related tasks, have been studied in the past. However, despite the important role emotions play in human-machine interaction and in manual driving, little is known about how emotions influence drivers takeover performance. This study, therefore, examined the effects of emotional valence and arousal on drivers takeover timeliness and quality in conditionally automated driving. We conducted a driving simulation experiment with 32 participants. Movie clips were played for emotion induction. Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed. Results indicate that positive valence led to better takeover quality in the form of a smaller maximum resulting acceleration and a smaller maximum resulting jerk. However, high arousal did not yield an advantage in takeover time. This study contributes to the literature by demonstrating how emotional valence and arousal affect takeover performance. The benefits of positive emotions carry over from manual driving to conditionally automated driving while the benefits of arousal do not.

cs.HC↗

arXiv2019

Look Who's Talking Now: Implications of AV's Explanations on Driver's Trust, AV Preference, Anxiety and Mental Workload

Explanations given by automation are often used to promote automation adoption. However, it remains unclear whether explanations promote acceptance of automated vehicles (AVs). In this study, we conducted a within-subject experiment in a driving simulator with 32 participants, using four different conditions. The four conditions included: (1) no explanation, (2) explanation given before or (3) after the AV acted and (4) the option for the driver to approve or disapprove the AV's action after hearing the explanation. We examined four AV outcomes: trust, preference for AV, anxiety and mental workload. Results suggest that explanations provided before an AV acted were associated with higher trust in and preference for the AV, but there was no difference in anxiety and workload. These results have important implications for the adoption of AVs.

cs.HC↗