Search Results (754)

To realize accurate environment perception, which is the technological key to enabling autonomous vehicles to interact with their external environments, it is primarily necessary to solve the issues of object detection and tracking in the vehicle-movement process. Multi-sensor fusion has become an essential process in efforts to overcome the shortcomings of individual sensor types and improve the efficiency and reliability of autonomous vehicles. This paper puts forward moving object detection and tracking methods based on LiDAR—camera fusion. Operating based on the calibration of the camera and LiDAR technology, this paper uses YOLO and PointPillars network models to perform object detection based on image and point cloud data. Then, a target box intersection-over-union (IoU) matching strategy, based on center-point distance probability and the improved Dempster–Shafer (D–S) theory, is used to perform class confidence fusion to obtain the final fusion detection result. In the process of moving object tracking, the DeepSORT algorithm is improved to address the issue of identity switching resulting from dynamic objects re-emerging after occlusion. An unscented Kalman filter is utilized to accurately predict the motion state of nonlinear objects, and object motion information is added to the IoU matching module to improve the matching accuracy in the data association process. Through self-collected data verification, the performances of fusion detection and tracking are judged to be significantly better than those of a single sensor. The evaluation indexes of the improved DeepSORT algorithm are 66% for MOTA and 79% for MOTP, which are, respectively, 10% and 5% higher than those of the original DeepSORT algorithm. The improved DeepSORT algorithm effectively solves the problem of tracking instability caused by the occlusion of moving objects. Full article

This study presents a comprehensive discrete element method (DEM) simulation approach for the stretching of a filter fiber with a separated polydisperse particle structure on top. For a realistic interaction between the fiber surface and the particles, the original surface of the polymer fiber was projected onto the surface of the fiber cylinder using surface imaging technologies (atomic force microscopy (AFM) and white-light interferometry). In addition, the adhesive forces between particle–fiber and particle–particle contacts were calibrated in the DEM domain using values from self-conducted AFM measurements. Fiber stretching was implemented by the linear motion of small periodic fiber elements. Discretization problems were resolved through studying the stretching of a fiber segment at the size of 8 mm. A critical fiber element length was discovered to be ≈100 μm for minimizing discretization dependencies during the cracking of the particle structure. The number and density of particle–particle contacts within the particle loading on the fiber were obtained at two different elongation rates. Effects such as densification of the particulate structure and increased detachment due to additional air flow were demonstrated. Full article

Unmanned traffic signal control is regarded as a sustainable intelligent management methodology. However, it faces the challenge of unpredictable traffic flow due to stochastic arrivals. The digital twin (DT) has emerged as a promising approach to address the challenges of time-varying traffic demand in urban transportation. Previous studies of DT-based adaptive traffic signal control (ATSC) methods all assume ideal synchronization conditions between the DT and the physical twin (PT). It means that the DT can immediately figure out the next neglecting limitation of realistic conditions, i.e., discrepancies between the DT and PT and computational ability. This paper proposes a DT-ATSC framework aimed at reducing the total delay at isolated intersections under limited synchronization conditions. The framework contains two parts: (1) a cell transmission model-based intersection simulation model featuring less computational consumption and the parameter self-calibration mechanism; and (2) scheme searching algorithms that can guide the DT to create optimization-oriented signal timing scheme candidates. Three options are provided for the scheme searching algorithms, i.e., grid search (GS), the genetic algorithm (GA), and Bayesian optimization (BO). A testing platform is created to validate the effectiveness of the proposed DT-ATSC. Experimental results indicate that the proposed DT-ATSC-BO outperforms the DT-ATSC-GA and DT-ATSC-GS. Meanwhile, the average vehicle delay of the DT-ATSC-BO is up to 53% lower than that of the current adaptive signal control method, which indicates that the proposed DT-ATSC has achieved the expected effect. Moreover, compared to the previous related work, the proposed DT-ATSC framework is more likely to be able to be applied in realistic situations because synchronization issues are incorporated in the design of the DT-ATSC by assuming a limited margin time for a decision. Full article

In this paper, we propose a cost-effective way to tune RF process technology to achieve well-optimized RF and mmWave performances/power/area by tweaking back-end-of-line (BEOL) configurations. This paper suggests that the most favorable altitude is that of an ultra-thick-metal (UTM) layer from the silicon substrate, and the effort also focuses on the calibration of the via height/pitch underneath the UTM to satisfy the least ohmic loss in the interface between the active and passive device components. We implemented a process optimization in a 28 nm fully depleted silicon-on-insulator (FD-SOI) process technology, and the results show performance enhancements on the inductor, achieving a 14.8% quality factor improvement and a 13.1% self-resonance frequency improvement. This paper also showcases how the process optimization boosts 29 GHz LNA performances, with a 31.8% gain in boosting and a 9.1% reduction in noise-figure. Full article

Dark-and-weak-target simulators are used as ground-based calibration devices to test and calibrate the performance metrics of star sensors. However, these simulators are affected by full-field-of-view energy nonuniformity. This problem impacts the quality of output images and the calibration accuracy of sensors and inhibits further improvements in navigational accuracy. In the study reported in this paper, we sought to analyze the factors which affect full-field-of-view energy uniformity in dark-and-weak-target simulators. These include uneven irradiation in backlight sources, the leakage of light from LCD display panels, and the vignetting of collimating optical systems. We then established an energy transfer model of a dark-and-weak-target simulator based on the propagation of a point light source and proposed a self-adaptive compensation algorithm based on pixel-by-pixel fitting. This algorithm used a sensor to capture the output image of a dark-and-weak-target simulator and iteratively calculated the response error matrix of the simulator. Finally, we validated the feasibility and effectiveness of the compensation algorithm by acquiring images using a self-built test system. The results showed that, after compensating an output image of the dark-and-weak-target simulator, the grayscale standard display function (SDF) of the acquired sensor image was reduced by about 50% overall, so the acquisition image was more accurately compensated, and the desired level of grayscale distribution was obtained. This study provides a reference for improving the quality of output images from dark-and-weak-target simulators, so that the working environments of star sensors may be more realistically simulated, and their detection performance improved. Full article

This work focuses on investigating the accuracy of 3D reconstructions from fixed stereo-photogrammetric monitoring systems through different camera calibration procedures. New reliable and effective calibration methodologies that require minimal effort and resources are presented. A full-format camera equipped with fixed 50 and 85 mm focal length optics is considered, but the methodologies are general and can be applied to other systems. Four different calibration strategies are considered: (i) full-field calibration (FF); (ii) multi-image on-the-job calibration (MI); (iii) point cloud-based calibration (PC); and (iv) self (on-the-job) calibration (SC). To evaluate the calibration strategies and assess their actual performance and practicality, two test sites are used. The full-field calibration, while very reliable, demands significant effort if it needs to be repeated. The multi-image strategy emerges as a favourable compromise, offering good results with minimal effort for its realisation. The point cloud-based method stands out as the optimal choice, balancing ease of implementation with quality results; however, it requires a reference 3D point cloud model. On-the-job calibration with monitoring images is the simplest but least reliable option, prone to uncertainty and potential inaccuracies, and should hence be avoided. Ultimately, prioritising result reliability over absolute accuracy is paramount in continuous monitoring systems. Full article

This paper presents a novel fuzzy-augmented model reference adaptive voltage regulation strategy for the DC–DC buck converters to enhance their resilience against random input variations and load-step transients. The ubiquitous proportional-integral-derivative (PID) controller is employed as the baseline scheme, whose gains are tuned offline via a pre-calibrated linear-quadratic optimization scheme. However, owing to the inefficacy of the fixed-gain PID controller against parametric disturbances, it is retrofitted with a model reference adaptive controller that uses Lyapunov gain adaptation law for the online modification of PID gains. The adaptive controller is also augmented with an auxiliary fuzzy self-regulation system that acts as a superior regulator to dynamically update the adaptation rates of the Lyapunov gain adaptation law as a nonlinear function of the system’s classical error and its normalized acceleration. The proposed fuzzy system utilizes the knowledge of the system’s relative rate to execute better self-regulation of the adaptation rates, which in turn, flexibly steers the adaptability and response speed of the controller as the error conditions change. The propositions above are validated by performing tailored hardware experiments on a low-power DC–DC buck converter prototype. The experimental results validate the improved reference tracking and disturbance rejection ability of the proposed control law compared to the fixed PID controller. Full article

The attitude accuracy of high-resolution satellite images is the main factor affecting their geometric positioning accuracy. Bundle block adjustment is the main method for realizing the simultaneous estimation of attitude models for overlapping images over a large area. In the current research on the joint positioning of high-resolution multi-line array satellite images, the adjustment is usually carried out with the view or load as a unit without considering the consistency of the error of the same platform. In this paper, we develop a self-calibration strip bundle adjustment scheme that considers the boresight misalignment among multiple cameras. By introducing the installation angle between multiple loads, we fully utilized their geometric constraint relationship with the same platform to establish a unified attitude compensation model for multiple loads. The experimental results of the ZiYuan3 (ZY-3) satellite image show that, when the ground control points (GCPs) are laid only at four corner points of the image, the image plane and elevation accuracies are 1.85 m and 1.87 m after an adjustment using this method, which can achieve comparable accuracies with those obtained by a traditional program based on an adjustment with more GCPs. Full article

Background: Management of PICC dressing can be performed at home by the patient through adequate training and telenursing. This trial verifies that the incidence of catheter-related complications in home patients, assisted by telenursing, is not greater than that observed in outpatients. Methods: This clinical trial is composed of 72 patients with malignant tumors who underwent long-term chemotherapy with PICC insertion. They were randomly divided into an experimental group (33 cases) and a calibration group (39 cases). The control group received outpatient dressing for the PICC at the hospital, while the experimental group received a telenursing intervention about the management of the PICC. The incidence of catheter-related infections, the ability of self-management, and a rough cost/benefit estimation were compared between the two groups. This trial was performed according to the CONSORT 2010 checklist. Results: The two groups do not significantly differ in relation to age, sex, and PICCs in terms of the body side insertion, the type of dressing, and the agents used for cleaning. The analysis of the results showed that in the home-managed group, the clinical events reported during the connection were higher when compared with the outpatient group (p < 0.001). The patients in the homecare group developed frequent complications resulting from skin redness (p < 0.001). Conclusion: The use of telenursing for patient education in cancer centers can reduce nurses’ working time, improving the self-management capacity of patients with a long-term PICC. This trial was retrospectively registered with the Clinical Trial Gov on the 18 May 2023 with registration number NCT05880420. Full article

To characterize the dynamic interaction properties of heterogeneous traffic flow in the complex human–vehicle–road environment and to enhance the safety and efficiency of connected autonomous vehicles (CAVs), this study analyzes the self-driven particle characteristics and safety interaction behavior of CAVs based on molecular interaction potential. The molecular dynamics of potential interaction functions are employed to establish a dynamic quantization model for car-following (CF) safety potential, referred to as the molecular force field quantization model. To calibrate the model parameters, the Artificial Bee Colony Algorithm and the highD dataset are utilized, subsequently validating the reasonableness and effectiveness of the molecular dynamics model for vehicle tracking. The simulation results demonstrate that the proposed model can more accurately fit actual CF data, significantly improving vehicle travel safety and efficiency. Moreover, the profile of vehicle acceleration shows a lower mean absolute error and root mean square error compared to actual data, indicating that the model provides superior anti-interference fluctuation resistance and stability in CF scenarios. Overall, the proposed model effectively captures the microscopic CF behavior and vehicle–vehicle safety interactions, offering a theoretical foundation for further research into vehicle-following dynamics. Full article

Aiming to address the chicken-and-egg problem in star identification and the intrinsic parameter determination processes of on-orbit star sensors, this study proposes an on-orbit self-calibration method for star sensors that does not depend on star identification. First, the self-calibration equations of a star sensor are derived based on the invariance of the interstar angle of a star pair between image frames, without any requirements for the true value of the interstar angle of the star pair. Then, a constant constraint of the optical path from the star spot to the center of the star sensor optical system is defined to reduce the biased estimation in self-calibration. Finally, a scaled nonlinear least square method is developed to solve the self-calibration equations, thus accelerating iteration convergence. Our simulation and analysis results show that the bias of the focal length estimation in on-orbit self-calibration with a constraint is two orders of magnitude smaller than that in on-orbit self-calibration without a constraint. In addition, it is shown that convergence can be achieved in 10 iterations when the scaled nonlinear least square method is used to solve the self-calibration equations. The calibrated intrinsic parameters obtained by the proposed method can be directly used in traditional star map identification methods. Full article

The use of low-cost environmental sensors has gained significant attention due to their affordability and potential to intensify environmental monitoring networks. These sensors enable real-time monitoring of various environmental parameters, which can help identify pollution hotspots and inform targeted mitigation strategies. Low-cost sensors also facilitate citizen science projects, providing more localized and granular data, and making environmental monitoring more accessible to communities. However, the accuracy and reliability of data generated by these sensors can be a concern, particularly without proper calibration. Calibration is challenging for low-cost sensors due to the variability in sensing materials, transducer designs, and environmental conditions. Therefore, standardized calibration protocols are necessary to ensure the accuracy and reliability of low-cost sensor data. This review article addresses four critical questions related to the calibration and accuracy of low-cost sensors. Firstly, it discusses why low-cost sensors are increasingly being used as an alternative to high-cost sensors. In addition, it discusses self-calibration techniques and how they outperform traditional techniques. Secondly, the review highlights the importance of selectivity and sensitivity of low-cost sensors in generating accurate data. Thirdly, it examines the impact of calibration functions on improved accuracies. Lastly, the review discusses various approaches that can be adopted to improve the accuracy of low-cost sensors, such as incorporating advanced data analysis techniques and enhancing the sensing material and transducer design. The use of reference-grade sensors for calibration and validation can also help improve the accuracy and reliability of low-cost sensor data. In conclusion, low-cost environmental sensors have the potential to revolutionize environmental monitoring, particularly in areas where traditional monitoring methods are not feasible. However, the accuracy and reliability of data generated by these sensors are critical for their successful implementation. Therefore, standardized calibration protocols and innovative approaches to enhance the sensing material and transducer design are necessary to ensure the accuracy and reliability of low-cost sensor data. Full article

In this study, we report a multiplexed platform for the simultaneous determination of five marine toxins. The proposed biosensor is based on a disposable electrical printed (DEP) microarray composed of eight individually addressable carbon electrodes. The electrodeposition of gold nanoparticles on the carbon surface offers high conductivity and enlarges the electroactive area. The immobilization of thiolated aptamers on the AuNP-decorated carbon electrodes provides a stable, well-orientated and organized binary self-assembled monolayer for sensitive and accurate detection. A simple electrochemical multiplexed aptasensor based on AuNPs was designed to synchronously detect multiple cyanotoxins, namely, microcystin-LR (MC-LR), Cylindrospermopsin (CYL), anatoxin-α, saxitoxin and okadaic acid (OA). The choice of the five toxins was based on their widespread presence and toxicity to aquatic ecosystems and humans. Taking advantage of the conformational change of the aptamers upon target binding, cyanotoxin detection was achieved by monitoring the resulting electron transfer increase by square-wave voltammetry. Under the optimal conditions, the linear range of the proposed aptasensor was estimated to be from 0.018 nM to 200 nM for all the toxins, except for MC-LR where detection was possible within the range of 0.073 to 150 nM. Excellent sensitivity was achieved with the limits of detection of 0.0033, 0.0045, 0.0034, 0.0053 and 0.0048 nM for MC-LR, CYL, anatoxin-α, saxitoxin and OA, respectively. Selectivity studies were performed to show the absence of cross-reactivity between the five analytes. Finally, the application of the multiplexed aptasensor to tap water samples revealed very good agreement with the calibration curves obtained in buffer. This simple and accurate multiplexed platform could open the window for the simultaneous detection of multiple pollutants in different matrices. Full article

In recent years, hydrogel-based wearable flexible electronic devices have attracted much attention. However, hydrogel-based sensors are affected by structural fatigue, material aging, and water absorption and swelling, making stability and accuracy a major challenge. In this study, we present a DN-SPEZ dual-network hydrogel prepared using polyvinyl alcohol (PVA), sodium alginate (SA), ethylene glycol (EG), and ZnSO₄ and propose a self-calibration compensation strategy. The strategy utilizes a metal salt solution to adjust the carrier concentration of the hydrogel to mitigate the resistance drift phenomenon to improve the stability and accuracy of hydrogel sensors in amphibious scenarios, such as land and water. The ExpGrow model was used to characterize the trend of the ∆R/R₀ dynamic response curves of the hydrogels in the stress tests, and the average deviation of the fitted curves $\overline{ϵ}$ was calculated to quantify the stability differences of different groups. The results showed that the stability of the uncompensated group was much lower than that of the compensated group utilizing LiCl, NaCl, KCl, MgCl₂, and AlCl₃ solutions ($\overline{ϵ}$ in the uncompensated group in air was 276.158, 1.888, 2.971, 30.586, and 13.561 times higher than that of the compensated group in LiCl, NaCl, KCl, MgCl₂, and AlCl₃, respectively; $\overline{ϵ}$ in the uncompensated group in seawater was 10.287 times, 1.008 times, 1.161 times, 4.986 times, 1.281 times, respectively, higher than that of the compensated group in LiCl, NaCl, KCl, MgCl₂ and AlCl₃). In addition, for the ranking of the compensation effect of different compensation solutions, the concentration of the compensation solution and the ionic radius and charge of the cation were found to be important factors in determining the compensation effect. Detection of events in amphibious environments such as swallowing, robotic arm grasping, Morse code, and finger–wrist bending was also performed in this study. This work provides a viable method for stability and accuracy enhancement of dual-network hydrogel sensors with strain and pressure sensing capabilities and offers solutions for sensor applications in both airborne and underwater amphibious environments. Full article

Yinhua Pinggan Granule (YPG) is an approved compounded traditional Chinese medicine (TCM) prescription for the treatment of cold, cough, viral pneumonia, and related diseases. Due to its complicated chemical composition, the material basis of YPG has not been systematically investigated. In this study, an analytical method based on high-performance liquid chromatography (HPLC) coupled with Q-Exactive mass spectrometry was established. Together with the help of a self-built compound database and Compound Discoverer software 3.1, the chemical components in YPG were tentatively identified. Subsequently, six main components in YPG were quantitatively characterized with a high-performance liquid chromatography–diode array detector (HPLC-DAD) method. As a result, 380 components were annotated, including 19 alkaloids, 8 organic acids, 36 phenolic acids, 27 other phenols, 114 flavonoids, 75 flavonoid glycoside, 72 terpenes, 11 anthraquinones, and 18 other compounds. Six main components, namely, chlorogenic acid, puerarin, 3′-methoxypuerarin, polydatin, glycyrrhizic acid, and emodin, were quantified simultaneously. The calibration curves of all six analytes showed good linearity (R² > 0.9990) within the test ranges. The precision, repeatability, stability, and recovery values were all in acceptable ranges. In addition, the total phenol content and DPPH scavenging activity of YPG were also determined. The systematic elucidation of the chemical components in YPG in this study may provide clear chemical information for the quality control and pharmacological research of YPG and related TCM compounded prescriptions. Full article