Search Results (62)

Background/Objectives: Violence is a significant occupational health issue for paramedics, yet underreporting limits efforts to identify and mitigate risk. Leveraging a novel, point-of-event violence reporting system, we aimed to identify characteristics of 9-1-1 calls associated with an increased risk of violence in a single paramedic service in Ontario, Canada. Methods: We retrospectively analyzed all electronic violence and patient care reports filed by paramedics in Peel Region and used logistic regression to identify call-level predictors of any violence and, more specifically, physical or sexual assault. Results: In total, 374 paramedics filed 974 violence reports, 40% of which documented an assault, corresponding to a rate of 4.18 violent encounters per 1000 9-1-1 calls. In adjusted models, the risk of violence was elevated for calls originating from non-residential locations (e.g., streets, hotels, bars), occurring during afternoon or overnight shifts, and involving young or working-age males. Presenting problems related to intoxication, mental health, or altered mental status were strongly associated with increased risk, with particularly high adjusted odds ratios for assault. Conclusions: These findings support the utility of near-miss and violence surveillance systems and highlight the need for multidisciplinary crisis response to high-risk calls, especially those involving mental health or substance use. Full article

In this study, we demonstrate an application for 5G networks in mobile and remote GPR scanning situations to detect buried objects by experts while the operator is performing the scans. Using a GSSI SIR-30 system in conjunction with the RealSense camera for visual mapping of the surveyed area, subsurface GPR scans were created and transmitted for remote processing. Using mobile networks, the raw B-scan files were transmitted at a sufficient rate, a maximum of 0.034 ms mean latency, to enable near real-time edge processing. The performance of 5G networks in handling the data transmission for the GPR scans and edge computing was compared to the performance of 4G networks. In addition, long-range low-power devices, namely Wi-Fi HaLow and Wi-Fi hotspots, were compared as local alternatives to cellular networks. Augmented reality headset representation of the F-scans is proposed as a method of assisting the operator in using the edge-processed scans. These promising results bode well for the potential of remote processing of GPR data in augmented reality applications. Full article

Microwave camera provides 3-D high-resolution radar images at video frame rates, enabling the capture of dynamic target features. Multiple-input–multiple-output (MIMO) array-based 3-D radar imaging system requires fewer antennas, which effectively reduces hardware costs. Due to the limited computational resources of the miniaturized MIMO microwave camera, real-time processing of a large amount of 3-D echo data requires an imaging algorithm that has both real-time performance and large output spatial extent. This paper presents the limited output spatial extent and spatial aliasing in existing MIMO wavenumber domain algorithms through theoretical derivation and simulation. To suppress aliasing while expanding the output spatial extent, an optimization approach for the wavenumber domain algorithms is proposed. The improved wavenumber domain algorithms divide the target area into multiple sub-blocks, and a broader range of imaging results is obtained through independent imaging of the sub-blocks and a spatial aliasing suppression filter. Simulation results show that the improved wavenumber domain algorithms effectively suppress the aliasing energy of each sub-block while maintaining the advantage of low time complexity. Expansion of output spatial extent in existing MIMO wavenumber domain algorithms is achieved. Full article

Current building energy modeling (BEM) tools lack the capability to inherently simulate the impacts of urban microclimates on building energy performance. While efforts have been made to integrate BEM with Urban Microclimate Modeling (UMM) tools, their ability to capture spatial and seasonal microclimate variations remains limited. This review critically evaluates existing urban microclimate-integrated BEM approaches and their effectiveness in modeling the complex interactions between urban form, microclimate, and building energy performance. Through an analysis of 94 research articles, the review first examines the influence of urban form on microclimates, followed by an assessment of how microclimatic conditions impact building energy use. Additionally, it evaluates conventional modeling frameworks employed in BEM tools and their limitations in representing dynamic microclimatic variations. The findings emphasize the non-linear heat exchange relationships between urban form and microclimate, typically modeled using computationally intensive Computational Fluid Dynamics (CFD)-based UMM tools. This review introduces a classification of heat exchange types: atmospheric heat exchange, involving air temperature, wind, and humidity, and non-atmospheric heat exchange, driven by radiative interactions with surrounding urban surfaces. The study further highlights that modifying standard weather files and heat transfer coefficients alone is insufficient for BEM tools to accurately capture near-surface microclimate variations. By identifying critical insights and research gaps, this review establishes a foundation for advancing next-generation urban microclimate-integrated BEM approaches, emphasizing the need for computationally efficient and dynamically responsive modeling techniques. Full article

Lossless image compression is vital for missions with limited data transmission bandwidth. Reducing file sizes enables faster transmission and increased scientific gains from transient events. This study compares two wavelet-based image compression algorithms, CCSDS 122.0 and JPEG 2000, used in the European Space Agency Comet Interceptor and Hera missions, respectively, in varying scenarios. The JPEG 2000 implementation is sourced from the JasPer library, whereas a custom implementation was written for CCSDS 122.0. The performance analysis for both algorithms consists of compressing simulated asteroid images in the visible and near-infrared spectral ranges. In addition, all test images were noise-filtered to study the effect of the amount of noise on both compression ratio and speed. The study finds that JPEG 2000 achieves consistently higher compression ratios and benefits from decreased noise more than CCSDS 122.0. However, CCSDS 122.0 produces comparable results faster than JPEG 2000 and is substantially less computationally complex. On the contrary, JPEG 2000 allows dynamic (entropy-permitting) reduction in the bit depth of internal data structures to 8 bits, halving the memory allocation, while CCSDS 122.0 always works in 16-bit mode. These results contribute valuable knowledge to the behavioral characteristics of both algorithms and provide insight for entities planning on using either algorithm on board planetary missions. Full article

Efficient and affordable plant phenotyping methods are an essential response to global climatic pressures. This study demonstrates the continued potential of consumer-grade photography to capture plant phenotypic traits in turfgrass and derive new calculations. Yet the effects of image corrections on individual calculations are often unreported. Turfgrass lysimeters were photographed over 8 weeks using a custom lightbox and consumer-grade camera. Subsequent imagery was analyzed for area of cover, color metrics, and sensitivity to image corrections. Findings were compared to active spectral reflectance data and previously reported measurements of visual quality, productivity, and water use. Results confirm that Red–Green–Blue imagery effectively measures plant treatment effects. Notable correlations were observed for corrected imagery, including between yellow fractional area with human visual quality ratings (r = −0.89), dark green color index with clipping productivity (r = 0.61), and an index combination term with water use (r = −0.60). The calculation of green fractional area correlated with Normalized Difference Vegetation Index (r = 0.91), and its RED reflectance spectra (r = −0.87). A new chromatic ratio correlated with Normalized Difference Red-Edge index (r = 0.90) and its Red-Edge reflectance spectra (r = −0.74), while a new calculation correlated strongest to Near-Infrared (r = 0.90). Additionally, the combined index term significantly differentiated between the treatment effects of date, mowing height, deficit irrigation, and their interactions (p < 0.001). Sensitivity and statistical analyses of typical image file formats and corrections that included JPEG, TIFF, geometric lens distortion correction, and color correction were conducted. Findings highlight the need for more standardization in image corrections and to determine the biological relevance of the new image data calculations. Full article

This study introduces an innovative technique that merges computer vision with topology optimization to advance additive manufacturing. Employing advanced photogrammetry software, we obtain high-resolution images of the design domain, which are then used to develop accurate 3D models through meticulous scanning procedures. These models are transformed into an STL file format and remeshed using an adaptive algorithm within COMSOL 5.3 Multiphysics, facilitated by a custom MATLAB 2023 application. This integration achieves the optimal mesh resolution and precision in analytical assessments. We applied this technique to the design of a concrete pillar for 3D printing, targeting a 75% reduction in volume to improve the material efficiency and structural stability—critical factors for extraterrestrial applications. The design, captured with a 360-degree camera array, guided the MATLAB-based topology optimization process. By combining MATLAB’s optimization algorithms with COMSOL’s meshing and finite element analysis tools, we investigated various material-efficient configurations. The findings reveal a substantial volume reduction, especially in the central region of the design, effectively optimizing material utilization while preserving structural integrity. The optimization algorithm exhibited a swift and stable convergence, reaching near-optimal solutions within approximately 20 iterations. Full article

The agricultural sector is undergoing a transformative paradigm shift with the integration of advanced technologies, particularly artificial intelligence (AI), to enhance data analysis techniques and streamline decision-making processes. This paper delves into the integration of advanced technologies in agriculture, focusing specifically on optimizing data analysis through artificial intelligence (AI) to strengthen decision-making processes in farming. We present a novel AI-powered model that leverages historical agricultural datasets, utilizing a comprehensive array of established machine learning algorithms to enhance the prediction and classification of agricultural data. This work provides tailored algorithm recommendations, bypassing the need to deploy and fine-tune numerous algorithms. We approximate the accuracy of suitable algorithms, highlighting those with the highest precision, thus saving time by leveraging pre-trained AI models on historical agricultural data. Our method involves three phases: collecting diverse agricultural datasets, applying multiple classifiers, and documenting their accuracy. This information is stored in a CSV file, which is then used by AI classifiers to predict the accuracy of new, unseen datasets. By evaluating feature information and various data segmentations, we recommend the configuration that achieves the highest accuracy. This approach eliminates the need for exhaustive algorithm reruns, relying on pre-trained models to estimate outcomes based on dataset characteristics. Our experimentation spans various configurations, including different training–testing splits and feature sets across multiple dataset sizes, meticulously evaluated through key performance metrics such as accuracy, precision, recall, and F-measure. The experimental results underscore the efficiency of our model, with significant improvements in predictive accuracy and resource utilization, demonstrated through comparative performance analysis against traditional methods. This paper highlights the superiority of the proposed model in its ability to systematically determine the most effective algorithm for specific agricultural data types, thus optimizing computational resources and improving the scalability of smart farming solutions. The results reveal that the proposed system can accurately predict a near-optimal machine learning algorithm and data structure for crop data with an accuracy of 89.38%, 87.61%, and 84.27% for decision tree, random forest, and random tree algorithms, respectively. Full article

The study of blast loads on structures is important due to the potential of significant consequences in various scenarios. From terrorist attacks to industrial accidents, comprehending how structures respond to blast waves is critical for ensuring public safety and designing resilient structures. Studying these effects typically involves two main methods: free-field tests with live explosives and shock tube tests. Although shock tube testing offers certain advantages, both approaches are costly and demand significant space. This research aims to develop a cost-effective and straightforward technique for generating stress waves that closely replicate the progressive and spatial characteristics of free-field or shock tube blast waves. This method was designed to evaluate the dynamic response of laminated glass panels. The stress wave was generated by impacting a piston on the fluid inside a tube, which was connected to a fluid chamber. This setup produced impulsive loads that were distributed across a laminated glass test panel. Moreover, it was used to simulate the shock near filed explosions for a certain part of a structure. High-speed cameras were utilized to analyze the initial velocity of flying glass fragments. The apparatus successfully produced various blast waves and impulsive profiles for different drop weight heights. The initial velocities of randomly selected flying shards ranged from 3 m/s to 4 m/s. Full article

The resistance of nickel–titanium endodontic instruments against cyclic fatigue failure remains a significant concern in clinical settings. This study aimed to assess the cyclic fatigue strength of five nickel–titanium rotary systems, while correlating the results with the instruments’ geometric and metallurgical characteristics. A total of 250 new instruments (sizes S1/A1, S2/A2, F1/B1, F2/B2, F3/B3) from ProTaper Gold, ProTaper Universal, Premium Taper Gold, Go-Taper Flex, and U-Files systems underwent mechanical testing. Prior to experimental procedures, all instruments were meticulously inspected to identify irregularities that could affect the investigation. Using a stereomicroscope, design characteristics such as the number of spirals, length, spirals per millimeter, and average helical angle of the active blade were determined. The surface finishing characteristics of the instruments were examined using a scanning electron microscope. Differential scanning calorimetry was employed to establish the instruments’ phase transformation temperatures, while energy-dispersive X-ray spectroscopy was utilized to analyze the elemental composition of the alloy. The instruments were subjected to cyclic fatigue testing within a stainless steel non-tapered artificial canal featuring a 6 mm radius and 86 degrees of curvature. Appropriate statistical tests were applied to compare groups, considering a significance level of 0.05. The assessed design characteristics varied depending on the instrument type. The least irregular surface finishing was observed in U-Files and Premium Taper Gold files, while the most irregular surface was noted in Go-Taper Flex. All instruments exhibited near-equiatomic proportions of nickel and titanium elements, whereas ProTaper Universal and U-Files instruments demonstrated lower phase transformation temperatures compared to their counterparts. Larger-sized instruments, as well as ProTaper Universal and U-Files, tended to display lower cyclic fatigue strength results. Overall, the design, metallurgical, and cyclic fatigue outcomes varied among instruments and systems. Understanding these outcomes may assist clinicians in making more informed decisions regarding instrument selection. Full article

Genital warts are the most frequent sexually transmitted disease. Their clinical diagnosis is not always easy, and invasive skin biopsies for histological examination should be performed in these cases. The aim of the study was to investigate the use of non-invasive imaging techniques for the diagnosis of genital warts and their imitators. We retrospectively evaluated dermoscopy, reflectance confocal microscopy (RCM), and line-filed confocal microscopy (LC-OCT) images of nine patients with 19 warts of the mucous membranes and five patients with lesions that clinically mimic genital warts, including 12 molluscum contagiosum, 1 Fordyce’s spot and one case of multiple acquired lymphangiomas. Most genital warts (15; 79%) showed dilated vessels surrounded by a whitish halo at dermoscopy. RCM and the new device LC-OCT could identify near histologic features such as the presence of hyperkeratosis, acanthosis, papillomatosis and enlarged vessels in all genital warts. However, the identification of koilocytes, which are the hallmark for the diagnosis of warts, was still difficult using both techniques. Non-invasive imaging techniques could also offer clues for the correct diagnosis of the imitators. This study confirmed the usefulness of dermoscopy in recognizing a precise pattern in warts and showed the potential use of RCM and LC-OCT to add additional findings to the clinical and dermoscopic examination. Full article

As power quality becomes a higher priority in the electric utility industry, the amount of disturbance event data continues to grow. Utilities do not have the required personnel to analyze each event by hand. This work presents an automated approach for analyzing power quality events recorded by digital fault recorders and power quality monitors operating within a power transmission system. The automated approach leverages rule-based analytics to examine the time and frequency domain characteristics of the voltage and current signals. Customizable thresholds are set to categorize each disturbance event. The events analyzed within this work include various faults, motor starting, and incipient instrument transformer failure. Analytics for fourteen different event types have been developed. The analytics were tested on 160 signal files and yielded an average accuracy of 99%. Continuous nominal signal data analysis was performed using an approach called the cyclic histogram. The cyclic histogram process is intended to be integrated into the digital fault recorders themselves in order to facilitate the detection of subtle signal variations that are too small to trigger a disturbance event and that can occur over hours or days. In addition to reducing memory requirements by a factor of 320, it is anticipated that cyclic histogram processing will aid in identifying incipient events and identifiers. This project is expected to save engineers time by automating the classification of disturbance events and increasing the reliability of the transmission system by providing near real-time detection and identification of disturbances as well as prevention of problems before they occur. Full article

During the startup process of a centrifugal pump, the vibration and noise problems caused by unsteady flow are the focus of attention, and pressure pulsation is one of the main reasons for this problem. In the current research, a special impeller with blade pressure side trimming was proposed to reduce the strong pressure pulsation phenomenon during the startup process of centrifugal pumps. This article uses numerical simulation methods to simulate three typical blade trailing edges: original trailing edge (OTE), pressure side long linear (LLPS), and pressure side short linear (SLPS), and verifies them with experimental results. The results indicate that although the head of the centrifugal pump after filing has been reduced, its efficiency has been improved to a certain extent. Thirteen monitoring points were set up near the impeller outlet circumference and volute tongue to analyze the changes in pressure pulsation, verifying that blade trimming has a significant inhibitory effect on pressure pulsation during the startup of centrifugal pumps. The average maximum pressure pulsation amplitude of all monitoring points decreased by 32.23%, and the maximum pressure pulsation amplitude decreased by 56%. Blade trimming can affect the internal flow field distribution of centrifugal pumps. By analyzing the static pressure distribution, velocity streamline distribution, and vorticity distribution at the middle interface of three different impellers during startup, it was verified that there is a close relationship between pressure pulsation and unsteady flow structure during startup. The final conclusion is that blade trimming has a significant inhibitory effect on the pressure pulsation of the centrifugal pump during startup, and the impeller outlet vorticity is significantly reduced. The scheme proposed in this study has far-reaching prospects in the design of low noise centrifugal pumps. Full article

This article describes a method of immunity testing for commercial unmanned aircraft vehicles relative to a variable near-lightning electric field component. The research focuses on one of the components of the electromagnetic field generated during a lightning discharge: the electrical component. Studies are proposed showing the influence of only this one factor on overvoltages arising in the drone. So far, no one has analyzed such an impact from emerging disturbances, because previous studies in the area have largely considered the impact of the entire electromagnetic field. This is justified practically, but not scientifically—it is necessary to determine the impact of each component separately. Selected electronic components are tested here. For that purpose, two types of pulses are used: Wave Form 4 (WF4–6.4/69 μs from DO-160 standard) and Voltage waveform 1.2/50 μs (PN-EN 61000-4-5:2014-10). The testing object is centrally placed in a capacitor between two parallel plates of dimensions 2 m by 2 m to provide a homogeneous electric field. The results (from a Rigol 1054Z oscilloscope) are saved in *.CSV files (for further analysis). The research shows that the greatest overvoltages are in active parts of the drone (higher-than-supply voltage level), such as the RF antenna or semiconductors. This emphasizes the need to pay special attention to the protection of these elements against a pulsed electromagnetic field, especially the electric component (e.g., lightning discharge). Full article

In order to solve the problem that students have insufficient understanding of the full-field goniophotometer instrumentation due to the expensive equipment and the high requirements of the experimental environment, virtual reality technology is used to complete the virtual laboratory of a light intensity distribution measurement of the full-field goniophotometer through Unity 3D. The virtual laboratory is designed for near-field measurement, mid-field measurement, and far-field measurement of light intensity. It combines 3D MAX and C# to realize the model building of laboratory, luminaire and full-field goniophotometer, the dynamic drawing of light distribution curves, and the simulation system can also be run on mobile phones. The experimental process is mainly through the manipulation of the virtual experimenter and each module to generate collision detection, pop-up buttons, and click on the button triggers an event and the operation prompt page appears. The light distribution curve is generated dynamically by reading and processing the IES file data to generate 3D coordinates. This virtual simulation laboratory is demonstrated on multiple platforms. The results proved that the virtual simulation restored the experimental process vividly and can complete the experimental teaching remotely. Full article