Search Results (468)

This study investigates how large language models (LLMs) handle Chinese zero anaphora under symmetric minimal-pair conditions designed to neutralize shallow syntactic cues. We construct a Winograd-style benchmark of carefully controlled sentence pairs that require semantic interpretation, pragmatic inference, discourse tracking, and commonsense reasoning rather than structural heuristics. Using GPT-4, ChatGLM-4, and LLaMA-3 under zero-shot, one-shot, and few-shot prompting, we assess both accuracy and the reasoning traces generated through a standardized Chain-of-Thought diagnostic. Results show that all models perform consistently on items solvable through local cues but display systematic asymmetric errors on 19 universally misinterpreted sentences that demand deeper discourse reasoning. Analysis of these failures reveals weaknesses in semantic role differentiation, topic-chain maintenance, logical-relation interpretation, pragmatic inference, and long-distance dependency tracking. These findings suggest that while LLMs perform well on simpler tasks, they still face challenges in interpreting contextually omitted arguments in Chinese. The study provides a new controlled evaluation resource, an interpretable error analysis framework, and evidence of differences in symmetric versus asymmetric reasoning behaviors in LLMs. Future research could expand the current benchmark to longer discourse contexts, incorporate multi-modal or knowledge-grounded cues, and explore fine-tuning LLMs on discourse data, helping clarify whether asymmetric patterns stem from deeper reasoning challenges or from interactions between models and the evaluation format. Full article

RFID (Radio Frequency Identification) technology has become an essential instrument in numerous industrial sectors, enhancing process efficiency and streamlining operations, allowing for the automated tracking of goods and equipment without the need for manual intervention. Nevertheless, the deployment of industrial IoT systems necessitates the establishment of complex sensor networks to enable detailed multi-parameter monitoring of items. Despite these advancements, challenges remain in item-level sensing, data analysis, and the management of power consumption. To mitigate these shortcomings, this study presents a holistic AI-assisted, semi-passive RFID-integrated multi-sensor system designed for robust food quality monitoring. The primary contributions are threefold: First, a compact (45 mm ∗ 38 mm) semi-passive UHF RFID tag is developed, featuring a rechargeable lithium battery to ensure long-term operation and extend the readable range up to 10 m. Second, a dedicated IoT cloud platform is implemented to handle big data storage and visualization, ensuring reliable data management. Third, the system integrates machine learning algorithms (LSTM) to analyze sensing data for real-time food quality assessment. The system’s efficacy is validated through real-world experiments on food products, demonstrating its capability for low-cost, long-distance, and intelligent quality control. This technology enables low-cost, timely, and sustainable quality assessments over medium and long distances, with battery life extending up to 27 days under specific conditions. By deploying this technology, quantified food quality assessment and control can be achieved. Full article

Crawler-type combine harvesters feature labor-intensive operation, tough steering and complex environments in paddy fields, necessitating reliable automatic operation to ensure efficient and complete harvesting. An error threshold-based autonomous navigation system for crawler-type combine harvesters was developed by using right-angle turning according to unilateral brake steering. Based on the chassis structure and working principles, a moving control system was designed to achieve automatic control of steering, speed and throttle. A global path planning method was proposed to generate a spiral path by giving reference points and operation directions. A path tracking method based on the error threshold was developed to calculate both lateral and heading errors in real-time, and we executed the adjustment strategy to ensure rapid alignment and high-precision tracking. A right-angle turning method was implemented to prevent missed cutting and crop damage by giving an adjustment distance. Field tests showed that the maximum lateral and heading errors for straight-line path tracking were 10.25 cm and 1.94°, respectively. The maximum lateral and heading errors for right-angle turning were 17.64 cm and −14.46°, respectively. It was concluded that the newly developed autonomous navigation system showed adequate path tracking accuracy and stability, meeting working requirements in crop harvesting. Full article

Based on an enhanced artificial potential field approach, this paper presents a control method for obstacle avoidance in vehicle platoons within Intelligent Vehicle-Infrastructure Cooperative Systems (I-VICS). To enhance safety during maneuvers, an inter-vehicle obstacle avoidance potential field model is established. By integrating virtual forces and a consistency control strategy into the control law, the proposed method effectively handles obstacle avoidance for vehicles operating at large inter-vehicle distances (80–110 m). Experimental validation using real-world trajectory data shows a 34% improvement in trajectory smoothness, as quantified by a proposed Vehicle Trajectory Stability (VTS) metric, leading to significantly safer avoidance maneuvers. A coordinated multi-vehicle obstacle avoidance strategy is further devised using a rotating potential field method, enabling collaborative and safe overall motion planning. Moreover, a path tracking strategy based on virtual force design is introduced to enhance platoon stability and reliability. Future work will focus on collision avoidance for vehicle platoons with varying inter-vehicle distances and will extend the consistency control and cooperative avoidance strategies to longer vehicle platoon to further improve overall traffic safety. Full article

Given the undoubtable similarities between the dynamic behavior of the vehicular traffic flow in terms of its response to boundary condition alterations dictated in the form of obstacles, and the specific case of supersonic compressible fluid flow fields, the current manuscript addresses developing a target trajectory for the overtaking maneuver of autonomous vehicles. The path-planning is pursued in analogy to the governing principles of the supersonic compressible fluid flow fields, with the specific definition of a physically meaningful dimensionless group, namely the Traffic Mach number (M_T), which grants the initial access point to the said set of fundamental equations. This practical application is a follow-up to the primarily established proof-of-concept level introduction and analysis of the more general case of collision avoidance for autonomously driven vehicles in accordance with the supersonic compressible fluid flow field, where the Traffic Mach number was first introduced. The proposed trajectory is then taken to the next block of the investigation, namely the tracking and control aspects of the maneuvering vehicle’s dynamics. The path tracking controller is designed based on sliding mode control technique and the algorithm is applied on a 7-DOF simulation model, used for validation and discussion of results. The proposed method is shown to be suitable for overtaking maneuvers of autonomous vehicles, whilst meeting the criteria for a relative velocity from the constant-velocity vehicle ahead of the road in the supersonic regime based on the defined Traffic Mach number. The results are then presented, first, in the scope of the aerodynamics field configuration and their verifications, followed by the vehicle dynamics remarks showing the practicality of the proposed method in terms of vehicle motion. It is observed that the distance corresponding to the delayed maneuver maximizes at highest velocities of the ego vehicle, consistent with the highest M_T values, yet in all simulated cases, the control system of the vehicle model was capable of performing the maneuver based on the assigned trajectories through the present model. Full article

Planning trajectories for unmanned aerial vehicles (UAVs) actively tracking a moving target poses a significant challenge. This paper introduces a motion planning system utilizing UAVs to track a dynamic target actively. The system can handle complex tracking tasks, ensuring safety and dynamic feasibility. Initially, a front-end path search involves employing adaptive Kinodynamic path searching to identify the route. A heuristic approach is applied to determine an initial trajectory, considering the minimum time and control cost. Subsequently, we introduce the cost of combining optimization and use Euclidean Signed Distance Field (ESDF) gradient information to improve trajectory smoothness and dynamic feasibility. Simulation results confirm the consistent superiority of our proposed method over the Fast-Tracker algorithm, resulting in shorter tracking distance and flight time. Our method achieves smoother trajectories while preserving dynamic feasibility. A real-world single-UAV experiment further validates the effectiveness of our approach. Full article

Along with the ongoing success of virtual/augmented reality (VR/AR) and human–machine interaction (HMI) in the professional and consumer markets, new compatible and inexpensive hand tracking devices are required. One of the contenders in this market is the Leap Motion Controller 2 (LMC2), successor to the popular Leap Motion Controller (LMC1), which has been widely used for scientific hand-tracking applications since its introduction in 2013. To quantify ten years of advances, this study compares both controllers using quantitative tracking metrics and characterizes the interaction space above the sensor. A robot-actuated 3D-printed hand and a motion-capture system provide controlled movements and external reference data. In the central tracking volume, the LMC2 achieves improved performance, reducing palm-position error from 7.9–9.8 mm (LMC1) to 5.2–5.3 mm (LMC2) and lowering positional variability from 1.3–2.2 mm to 0.4–0.8 mm. Dynamic tests confirm stable tracking for both devices. For boundary experiments, the LMC2 maintains continuous detection at distances up to 666 mm, compared to 250–275 mm (LMC1), and detects hands entering the field of view from distances up to 646 mm. Both devices show reduced accuracy toward the edges of the tracking volume. Overall, the results provide a grounded characterization of LMC2 performance in its newly emphasized VR/AR-relevant interaction spaces, while the metrics support cross-comparison with earlier LMC1-based studies and transfer to related application scenarios. Full article

This paper presents a Gaussian Process (GP)-based Funnel Model Predictive Control (MPC) for docking control of unmanned underwater vehicles (UUVs). The control method employs a Gaussian Process regression to learn the residual dynamics, which compensates for the unmodeled dynamics to improve prediction accuracy. Furthermore, a distance-adaptive performance funnel is designed to satisfy the field of view (FOV) constraints of sensors during the terminal guidance phase. The funnel imposes time-varying constraints on the UUV to ensure that the docking station remains observable. This funnel constraint is integrated into the cost function of the MPC, which systematically enforces safety without the computational complexity of traditional invariant sets. Comparative simulations validate the framework’s reliability under external disturbances, demonstrating superior tracking precision against conventional MPC benchmarks. Full article

This study presents the development and validation of an in situ monitoring method for the laser direct energy deposition (DED) process, utilizing an integrated optical camera (720 HD, 60 fps) to analyze melt pool imagery. The approach is grounded in an experimental framework employing Taguchi orthogonal arrays, which ensures a stable dataset by controlling process variability and enabling reliable extraction of relevant features. The monitoring system focuses on analyzing brightness distribution regions within the melt pool image, identified as specific clusters that reflect external process conditions. The method emphasizes precise segmentation of the melt pool area, combined with automatic detection and classification of cluster features associated with key process parameters—such as focus distance, the number of deposited layers, powder feed rate, and scanning speed. The main contribution of this work is demonstrating the effectiveness of using an optical camera for DED monitoring, based on an algorithm that processes a set of melt pool identification features through computer vision and machine learning techniques, including Random Forest and HistGradient Boosting, achieving classification accuracies exceeding 95%. By continuously tracking the evolution of these features within a closed-loop control system, the process can be maintained in a stable, defect-free state, effectively preventing the formation of common process defects. Full article

Distance simultaneous interpreting is a typical example of technology-mediated interpreting, bridging participants (i.e., interpreters, audience, and speakers) in various events and conferences. This study explores how presentation mode affects cognitive load in DSI, utilizing eye-tracking sensor technology. A controlled experiment was conducted involving 36 participants, comprising 19 professional interpreters and 17 student interpreters, to assess the effects of presentation mode on their cognitive load during English-to-Chinese DSI. A Tobii Pro X3-120 screen-based eye tracker was used to collect eye-tracking data as the participants sequentially performed a DSI task involving four distinct presentation modes: the Speaker, Slides, Split, and Corner modes. The findings, derived from the integration of eye-tracking data and interpreting performance scores, indicate that both presentation mode and experience level significantly influence interpreters’ cognitive load. Notably, student interpreters demonstrated longer fixation durations in the Slides mode, indicating a reliance on visual aids for DSI. These results have implications for language learning, suggesting that the integration of visual supports can aid in the acquisition and performance of interpreting skills, particularly for less experienced interpreters. This study contributes to our understanding of the interplay between technology, cognitive load, and language learning in the context of DSI. Full article

This paper presents a detailed experimental evaluation of a newly developed diesel fuel additive, specifically formulated to enhance the energy efficiency and emission characteristics of internal combustion engine (ICE) vehicles, with particular emphasis on its applicability to aging vehicle fleets. Diesel engines are known for producing significant amounts of harmful emissions, necessitating the development of effective mitigation strategies. One such approach involves the use of fuel additives. The additive under investigation is a proprietary formulation containing 1-(N,N-bis(2-ethylhexyl)aminomethyl)-1,2,4-triazole and other compounds. To the best of our knowledge, this specific additive composition has not yet been tested or reported in the existing scientific literature. To evaluate the real-world contribution of such additives, a comprehensive set of controlled measurements was conducted in a certified chassis dynamometer laboratory, including an exhaust gas analyser and supplementary diagnostic equipment. The testing protocol comprised repeated measurement cycles under identical driving conditions, both without and with the additive. Exhaust gas concentrations of CO₂, CO, and NOx were continuously monitored. Simultaneously, fuel consumption and engine performance were tracked over a cumulative driving distance of 2000 km. The results indicate measurable improvements across all monitored domains. CO₂ emissions decreased by 4.57%, CO by 14.29%, and NOx by 3.12%. Fuel consumption was reduced by 4.79%, while engine responsiveness and power delivery showed moderate but consistent enhancements. These improvements are attributed to more complete combustion and an increased cetane number enabled by the additive’s chemical structure. The findings support the adoption of advanced additive technologies as part of transitional strategies towards low-emission transportation systems. Full article

Background/Objectives: Children with single left ventricle (SLV) anatomy following Fontan palliation are at high risk for subclinical ventricular dysfunction, which may not be detected by conventional echocardiographic measures. Our objectives are as follows: (1) to assess myocardial and atrial strain profiles in pediatric Fontan patients with SLV using 2-dimensional speckle-tracking echocardiography (2D-STE), (2) to compare these findings with a healthy control group, (3) to investigate correlations with conventional echocardiographic and functional parameters. Methods: A single-center study of 66 pediatric patients, who underwent echocardiographic evaluation and a 6 min walk test (6 MWT). Conventional, 3D, and strain-based echocardiographic parameters were compared between groups. Correlations with clinical and functional indices were assessed using ANCOVA, analysis, generalized additive models, and Pearson’s correlation coefficient. Results: Fontan patients showed significantly reduced 6 MWT distances compared to controls (mean difference: 201.6 m, p < 0.0001). Post-test heart rate (HR) and oxygen saturation were significantly impaired (HR: 104.6 vs. 100.8 bpm, p = 0.0012; SaO₂: 90.3% vs. 99.8%, p < 0.0001). Fontan patients showed statistically significant differences in nearly all the 2D parameters. Three-dimensional echocardiography revealed significantly lower left ventricular (LV) ejection fraction (p = 0.0020), higher end-diastolic (p = 0.0275) and end-systolic volumes (p = 0.0125) in the study group. Global longitudinal strain (LV_GLS) was reduced in Fontan patients compared to controls (p < 0.0001), with significant differences across nearly all LV segments. Left atrial (LA) reservoir and conduit strain were markedly decreased, while contractile strain remained similar. LV_GLS was negatively correlated with IVCT (r = −0.50, p = 0.0175). The LA reservoir strain (LASr_AC) significantly correlated with MAPSE (r = 0.43, p = 0.0461). Conclusions: In pediatric Fontan patients, myocardial and atrial strain imaging reveals subclinical dysfunction despite preserved conventional ejection fraction. Full article

There have been many attempts to model the flow of vehicular traffic in analogy to the flow of fluids. Given the evident change in distance between vehicles driving in platoons, the compressibility of traffic flow is inferred and, considering the reaction time-scales of the driver (human or autonomous), it is argued that this compressibility is increased as relative velocities increase—giving the lag in imposed redirection by the driver and the controller units a higher relative importance. Therefore, a supersonic compressible flow field has been opted for as the most analogous base flow. On this point, added to by the overall extreme similarities of the two above-mentioned flows, the non-dimensional group of the traffic Mach number M_T has been defined in the present research, providing the possibility of calculating a suggested flow field and its corresponding shockwave systems, for any given obstacle ahead of the traffic flow. This suggested flow field is then taken as the basis to obtain trajectories designed for avoiding collision with the obstacle, and in compliance with the physics of the underlying analogous fluid flow phenomena, namely the internal supersonic compressible flow around a double wedge. It should be noted that herein we do not model the traffic flow but propose these trajectories for more optimal collision avoidance, and therefore the above-mentioned similarities (explained in detail in the manuscript) suffice, without the need to rely on full analogies between the two flows. The manuscript further analyzes the applicability of the proposed analogy in the path-planning process for an autonomous passenger vehicle, through dynamics and control of a full-planar vehicle model with an autonomous path-tracking controller. Simulations are performed using realistic vehicle parameters and the results show that the fluid flow analogy is compatible with the vehicle dynamics, as it is able to follow the target path generated by fluid flow calculations with minor deviations. Simulation results demonstrate that the proposed method produces smooth and dynamically consistent trajectories that remain stable under varying traffic scenarios. The controller achieves accurate path tracking and rapid convergence, confirming the feasibility of the fluid-flow analogy for real-time vehicle control. Full article

This study quantifies how pressurized water immersion alters the reciprocating sliding behavior of glass and Kevlar woven fabric-reinforced polymer hybrid composite laminates. Specimens were immersed in deionized water at 10 bar and 25 °C for 0, 7, 14, and 21 days, then tested against a 6 mm 100Cr6 steel ball at 20 N under four regimes that combine 1 or 2 Hz with 10 m or 20 m total sliding. Water uptake rose from 0 to 8.54% by day 21 and followed a short-time Fickian square root of time trend, indicating diffusion-controlled sorption. The coefficient of friction exhibited a robust nonmonotonic response with a pronounced minimum at 14 days that was typically 20 to 40% lower than the unaged reference across frequencies and distances, while 7 days produced a partial decrease and 21 days trended upward. Three-dimensional profilometry showed progressive widening and deepening of wear tracks with immersion, for example, at 1 Hz and 10 m width increased from about 1596 to about 2050 to 2101 μm and depth from about 128 to about 184 to 185 μm, with a transient narrowing at 2 Hz after 7 days. Scanning electron microscopy corroborated a transition from mild plowing to matrix plasticization with fiber–matrix debonding and debris compaction. Beyond geometric wear metrics, this study re-processed the existing profilometry and COF records to derive a moisture-dependent mechanistic approach. Moisture uptake up to 8.54% reorganizes the third body at the interface so that friction drops markedly at 14 days (typically 20–40% below the unaged state), while concurrent matrix plasticization and interface weakening enlarge the wear cross-section extracted from the same 3D maps, decoupling friction from damage width/depth under wet conditioning. Factorial analysis ranked immersion time as the dominant driver of damage for width and depth with frequency as a secondary factor and sliding distance as a minor factor, highlighting immersion-controlled tribological design windows for marine and humid service. Full article

Current research on multimodal AR-HUD navigation systems primarily focuses on the presentation forms of auditory and visual information, yet the effects of synchrony between auditory and visual prompts as well as prompt timing on driving behavior and attention mechanisms remain insufficiently explored. This study employed a 2 (prompt mode: synchronous vs. asynchronous) × 3 (prompt timing: −2000 m, −1000 m, −500 m) within-subject experimental design to assess the impact of multimodal prompt synchrony and prompt distance on drivers’ reaction time, sustained attention, and eye movement behaviors, including average fixation duration and fixation count. Behavioral data demonstrated that both prompt mode and prompt timing significantly influenced drivers’ response performance (indexed by reaction time) and attention stability, with synchronous prompts at −1000 m yielding optimal performance. Eye-tracking results further revealed that synchronous prompts significantly enhanced fixation stability and reduced visual load, indicating more efficient information integration. Therefore, prompt mode and prompt timing significantly affect drivers’ perceptual processing and operational performance. Delivering synchronous auditory and visual prompts at −1000 m achieves an optimal balance between information timeliness and multimodal integration. This study recommends the following: (1) maintaining temporal consistency in multimodal prompts to facilitate perceptual integration and (2) controlling prompt distance within an intermediate range (−1000 m) to optimize the perception–action window, thereby improving the safety and efficiency of AR-HUD navigation systems. Full article