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Keywords = depth and heading tracking

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15 pages, 3869 KiB  
Article
Correlation Between Plume Emission and Material Modifications in Fiber Laser Processing of Titanium
by Antaryami Mohanta and Marc Leparoux
Processes 2025, 13(6), 1761; https://doi.org/10.3390/pr13061761 - 3 Jun 2025
Viewed by 492
Abstract
The plume emission generated during the interaction of a fiber laser with titanium is spectrally analyzed to investigate the thermal effect-based spectral signature with a focus on surface impact and penetration depth. A wobble head coupled with the fiber laser forms circular patterns [...] Read more.
The plume emission generated during the interaction of a fiber laser with titanium is spectrally analyzed to investigate the thermal effect-based spectral signature with a focus on surface impact and penetration depth. A wobble head coupled with the fiber laser forms circular patterns on the surface during the interaction. The effects of wobble speed and laser peak power on the track width of the circular pattern, penetration depth, and plume emission characteristics were studied. Decreasing the wobble speed and increasing the laser peak power led to wider tracks and a deeper penetration. The variation in track width, penetration depth, and line emission intensities follows a similar pattern, indicating a correlation between plume emission and material modifications. A transition point at approximately 400 W of laser peak power was observed in track width, penetration depth, line emission intensities, and plume temperature variations. The increase in track width and line emission intensities with laser peak power shows growth at a slower rate below the transition point and at a higher rate above it. By contrast, the penetration depth and plume temperature increase at a higher rate below the transition compared to above it. This indicates that the increasing laser peak power leads to a more pronounced surface impact, resulting in an increase in track width and to a greater plume formation, causing enhanced line emission intensities and laser beam shielding that reduces the rate of increase in penetration depth above the transition point. Full article
(This article belongs to the Special Issue Progress in Laser-Assisted Manufacturing and Materials Processing)
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13 pages, 10534 KiB  
Article
The Gallery of Memories (GA-ME): A Novel Virtual Navigation Tool for the Study of Spatial Memory
by Zsolt Ternei and Zoltan Nadasdy
Information 2025, 16(6), 436; https://doi.org/10.3390/info16060436 - 26 May 2025
Viewed by 392
Abstract
For the vast majority of spatial navigation research, experimental tasks are implemented in real-world environments. In recent decades, there has been an increasing trend toward virtual environments, which offer several benefits compared to their real-world counterparts while also having certain limitations. With these [...] Read more.
For the vast majority of spatial navigation research, experimental tasks are implemented in real-world environments. In recent decades, there has been an increasing trend toward virtual environments, which offer several benefits compared to their real-world counterparts while also having certain limitations. With these properties in mind, we have developed the Gallery of Memories (GA-ME), a customizable virtual-navigation task that is equipped for the assessment of both spatial navigation and memory within a highly controlled three-dimensional environment. The GA-ME provides a 3D position and head direction (pitch and yaw) sampling rate that is significantly higher compared to alternatives, enabling users to reconstruct a participant’s movement in the environment with remarkable spatiotemporal precision while its design, including nested spaces, makes it optimal for the study of place and grid cells in humans. These properties imbue the GA-ME with the potential to be widely utilized in both research and clinical settings for the in-depth study of spatial navigation and memory, with the possibility of conducting human intra- and extra-cranial electrophysiology, imaging, and eye-tracking measurements relevant to these faculties. Full article
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13 pages, 2975 KiB  
Article
Impact of Pseudo-Random Number Generators on Dosimetric Parameters in Validation of Medical Linear Accelerator Head Simulation for 6 MV Photons Using the GATE/GEANT4 Platform
by Meriem Tantaoui, Mustapha Krim, El Mehdi Essaidi, Othmane Kaanouch, Mohammed Reda Mesradi, Abdelkrim Kartouni and Souha Sahraoui
Quantum Beam Sci. 2025, 9(2), 16; https://doi.org/10.3390/qubs9020016 - 5 May 2025
Viewed by 573
Abstract
Monte Carlo simulation relies on pseudo-random number generators. In general, the quality of these generators can have a direct impact on simulation results. The GATE toolbox, widely adopted in radiotherapy, offers three generators from which users can choose: Mersenne Twister, Ranlux-64, and James-Random. [...] Read more.
Monte Carlo simulation relies on pseudo-random number generators. In general, the quality of these generators can have a direct impact on simulation results. The GATE toolbox, widely adopted in radiotherapy, offers three generators from which users can choose: Mersenne Twister, Ranlux-64, and James-Random. In this study, we used these generators to simulate the head of a medical linear accelerator for 6 MV photons in order to assess their potential impact on the results obtained in radiotherapy simulation. Simulations were conducted for four different field openings. The simulations included a linac head model and a water phantom, all components of the head of the medical linear accelerator, and a water phantom placed at a distance of 100 cm from the electron source. Statistical analysis based on normal probability and Bland–Altman plots were used to compare dose distributions in the voxelized water phantom obtained by each generator. Experimental data (dose profiles, percentage dose at depth, and other dosimetric parameters) were measured using an appropriate quality assurance protocol for comparison with the different simulations. The evaluation of dosimetric criteria shows significant variations, particularly in the physical penumbra of the dose profile for large fields. The gamma index analysis highlights significant distinctions in generator performance. In all simulations, the average time of the primary particle generation rate, number of tracks, and steps in the simulation of different random number generators showed differences. The Mersenne Twister generator was distinguished by high performance in several aspects, particularly in terms of execution time, primary particle production, track and step production flow rate, and coming closer to the experimental results. Regarding computational time, the simulation using the Mersenne Twister generator was about 18% faster than the one using the James-Random generator and 27% faster than the simulation using the Ranlux-64 generator. This suggests that this generator is the most reliable for accurate and fast modeling of the medical linear accelerator head for 6 MV energy. Full article
(This article belongs to the Section Radiation Scattering Fundamentals and Theory)
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18 pages, 7690 KiB  
Article
Experimental Study on the Hydraulic Characteristics and Shape Optimization of Ship Lock Water Conveyance Systems
by Yu Duan, Dianguang Ma, Weidong Gan, Chao Ji and Junwei Zhou
J. Mar. Sci. Eng. 2025, 13(4), 784; https://doi.org/10.3390/jmse13040784 - 15 Apr 2025
Viewed by 389
Abstract
To enhance the passing capacity of the Bailongtan Ship Lock on the Hongshui River, this study focused on the design scheme of its water conveyance system reconstruction and expansion project. A three-dimensional mathematical model meeting the experimental accuracy requirements was established based on [...] Read more.
To enhance the passing capacity of the Bailongtan Ship Lock on the Hongshui River, this study focused on the design scheme of its water conveyance system reconstruction and expansion project. A three-dimensional mathematical model meeting the experimental accuracy requirements was established based on the RNG k-ε turbulence model and the Volume of Fluid (VOF) free-surface tracking method. A 1:30 scale ship lock water conveyance system physical model was built and used the independently developed system for hydraulic test monitoring, acquisition, and control. Experimental research on the hydraulic characteristics and shape optimization of the water conveyance system was carried out. The experimental results show that, under the condition of a maximum head difference of 16.0 m between the upstream and downstream of the ship lock, in the design scheme, the flow in the corridor after the filling valve fails to diffuse adequately, forming a high-velocity zone and a significant pressure difference between the inner and outer sides, which poses an operational risk. By optimizing the shape of the corridor after the valve (deepening the bottom end by 2.0 m and adjusting the turning angle from 75° to 70°), the range of the high-velocity zone can be shortened from 3.0 m to 1.5 m. The pressure difference between the inner and outer sides of the corridor at the horizontal turning section is reduced by 19.2% from 5.35 m to 4.32 m of the pressure head at the moment of maximum flow rate, and the velocity in the horizontal section is less than 15 m/s. Physical model tests confirmed these improvements, with mooring forces within safety limits (longitudinal ≤ 32 kN, transverse ≤ 16 kN). The research findings indicate that integrating numerical simulation with physical model testing can effectively mitigate risks in the original design of the ship lock water conveyance system. This approach notably enhances the reliability and safety of the design scheme, as demonstrated by the significant reduction in high-velocity zones and pressure differentials. Moreover, it offers a robust scientific basis and practical technical reference for in-depth hydraulic research and targeted optimization of ship lock water conveyance systems. Full article
(This article belongs to the Section Ocean Engineering)
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24 pages, 10105 KiB  
Article
SiamRhic: Improved Cross-Correlation and Ranking Head-Based Siamese Network for Object Tracking in Remote Sensing Videos
by Afeng Yang, Zhuolin Yang and Wenqing Feng
Remote Sens. 2024, 16(23), 4549; https://doi.org/10.3390/rs16234549 - 4 Dec 2024
Viewed by 1110
Abstract
Object tracking in remote sensing videos is a challenging task in computer vision. Recent advances in deep learning have sparked significant interest in tracking algorithms based on Siamese neural networks. However, many existing algorithms fail to deliver satisfactory performance in complex scenarios due [...] Read more.
Object tracking in remote sensing videos is a challenging task in computer vision. Recent advances in deep learning have sparked significant interest in tracking algorithms based on Siamese neural networks. However, many existing algorithms fail to deliver satisfactory performance in complex scenarios due to challenging conditions and limited computational resources. Thus, enhancing tracking efficiency and improving algorithm responsiveness in complex scenarios are crucial. To address tracking drift caused by similar objects and background interference in remote sensing image tracking, we propose an enhanced Siamese network based on the SiamRhic architecture, incorporating a cross-correlation and ranking head for improved object tracking. We first use convolutional neural networks for feature extraction and integrate the CBAM (Convolutional Block Attention Module) to enhance the tracker’s representational capacity, allowing it to focus more effectively on the objects. Additionally, we replace the original depth-wise cross-correlation operation with asymmetric convolution, enhancing both speed and performance. We also introduce a ranking loss to reduce the classification confidence of interference objects, addressing the mismatch between classification and regression. We validate the proposed algorithm through experiments on the OTB100, UAV123, and OOTB remote sensing datasets. Specifically, SiamRhic achieves success, normalized precision, and precision rates of 0.533, 0.786, and 0.812, respectively, on the OOTB benchmark. The OTB100 benchmark achieves a success rate of 0.670 and a precision rate of 0.892. Similarly, in the UAV123 benchmark, SiamRhic achieves a success rate of 0.621 and a precision rate of 0.823. These results demonstrate the algorithm’s high precision and success rates, highlighting its practical value. Full article
(This article belongs to the Section Remote Sensing Image Processing)
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15 pages, 3765 KiB  
Article
Drainage Troughs as a Protective Measure in Subway–Pedestrian Collisions: A Multibody Model Evaluation
by Daniel Hall, Kevin Gildea and Ciaran Simms
Appl. Sci. 2024, 14(22), 10738; https://doi.org/10.3390/app142210738 - 20 Nov 2024
Cited by 1 | Viewed by 831
Abstract
Introduction: Subway–pedestrian collisions are a significant and growing problem, but they are poorly understood. This study presents the first subway–pedestrian collision model with the aim of evaluating the baseline safety performance of an R160 NYC train and track combination and the potential safety [...] Read more.
Introduction: Subway–pedestrian collisions are a significant and growing problem, but they are poorly understood. This study presents the first subway–pedestrian collision model with the aim of evaluating the baseline safety performance of an R160 NYC train and track combination and the potential safety effects of drainage trough depth. Methods: A baseline simulation test sample of 384 unique impacts (8 velocities (2–16 m/s), 24 positions (standing jumping and lying), and 2 track types (flat and crossties)) was created in MADYMO. The full simulation test sample (N = 1920) included with various depth drainage troughs (0–1 m). Head injuries and wheel and third rail contacts were evaluated. Results: Limb–wheel contact occurred in 60% of scenarios. Primary and secondary contact HIC15 showed similar high severity, with an HIC15 < 2000 (88% risk of AIS 4+) in 29% of results for both train and ground contact. Impact velocity strongly influences primary contact HIC15 with limited effect on secondary contact. Impact velocities between 6 and 16 m/s showed little change in wheel contact. Increasing the trough depth up to 0.5 m showed a decrease in wheel contact probability with little increase in secondary contact. No further benefits were found above 0.5 m. Conclusions: A subway–pedestrian collision model is presented which predicts that wheel–pedestrian contact risk can be reduced with a 0.5 m drainage trough. The model suggests that slower impact velocities may reduce head injury risk for primary contact; however, this will have less effect on injuries caused by secondary and wheel contact. Full article
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17 pages, 4245 KiB  
Article
On the Scaling of Transport Phenomena at a Monotonously Changing Hydraulic Conductivity Field
by Yaniv Edery and Shaul Sorek
Entropy 2024, 26(11), 904; https://doi.org/10.3390/e26110904 - 24 Oct 2024
Cited by 1 | Viewed by 1003
Abstract
Monotonously stratified porous medium, where the layered medium changes its hydraulic conductivity with depth, is present in various systems like tilled soil and peat formation. In this study, the flow pattern within a monotonously stratified porous medium is explored by deriving a non-dimensional [...] Read more.
Monotonously stratified porous medium, where the layered medium changes its hydraulic conductivity with depth, is present in various systems like tilled soil and peat formation. In this study, the flow pattern within a monotonously stratified porous medium is explored by deriving a non-dimensional number, Fhp, from the macroscopic Darcian-based flow equation. The derived Fhp theoretically classifies the flow equation to be hyperbolic or parabolic, according to the hydraulic head gradient length scale, and the hydraulic conductivity slope and mean. This flow classification is explored numerically, while its effect on the transport is explored by Lagrangian particle tracking (LPT). The numerical simulations show the transition from hyperbolic to parabolic flow, which manifests in the LPT transition from advective to dispersive transport. This classification is also applied to an interpolation of tilled soil from the literature, showing that, indeed, there is a transition in the transport. These results indicate that in a monotonously stratified porous medium, very low conducting (impervious) formations may still allow unexpected contamination leakage, specifically for the parabolic case. This classification of the Fhp to the flow and transport pattern provides additional insight without solving the flow or transport equation only by knowing the hydraulic conductivity distribution. Full article
(This article belongs to the Special Issue Statistical Mechanics of Porous Media Flow)
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29 pages, 13503 KiB  
Article
YOSMR: A Ship Detection Method for Marine Radar Based on Customized Lightweight Convolutional Networks
by Zhe Kang, Feng Ma, Chen Chen and Jie Sun
J. Mar. Sci. Eng. 2024, 12(8), 1316; https://doi.org/10.3390/jmse12081316 - 3 Aug 2024
Cited by 6 | Viewed by 1821
Abstract
In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs [...] Read more.
In scenarios such as nearshore and inland waterways, the ship spots in a marine radar are easily confused with reefs and shorelines, leading to difficulties in ship identification. In such settings, the conventional ARPA method based on fractal detection and filter tracking performs relatively poorly. To accurately identify radar targets in such scenarios, a novel algorithm, namely YOSMR, based on the deep convolutional network, is proposed. The YOSMR uses the MobileNetV3(Large) network to extract ship imaging data of diverse depths and acquire feature data of various ships. Meanwhile, taking into account the issue of feature suppression for small-scale targets in algorithms composed of deep convolutional networks, the feature fusion module known as PANet has been subject to a lightweight reconstruction leveraging depthwise separable convolutions to enhance the extraction of salient features for small-scale ships while reducing model parameters and computational complexity to mitigate overfitting problems. To enhance the scale invariance of convolutional features, the feature extraction backbone is followed by an SPP module, which employs a design of four max-pooling constructs to preserve the prominent ship features within the feature representations. In the prediction head, the Cluster-NMS method and α-DIoU function are used to optimize non-maximum suppression (NMS) and positioning loss of prediction boxes, improving the accuracy and convergence speed of the algorithm. The experiments showed that the recall, accuracy, and precision of YOSMR reached 0.9308, 0.9204, and 0.9215, respectively. The identification efficacy of this algorithm exceeds that of various YOLO algorithms and other lightweight algorithms. In addition, the parameter size and calculational consumption were controlled to only 12.4 M and 8.63 G, respectively, exhibiting an 80.18% and 86.9% decrease compared to the standard YOLO model. As a result, the YOSMR displays a substantial advantage in terms of convolutional computation. Hence, the algorithm achieves an accurate identification of ships with different trail features and various scenes in marine radar images, especially in different interference and extreme scenarios, showing good robustness and applicability. Full article
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13 pages, 2487 KiB  
Article
SiamSMN: Siamese Cross-Modality Fusion Network for Object Tracking
by Shuo Han, Lisha Gao, Yue Wu, Tian Wei, Manyu Wang and Xu Cheng
Information 2024, 15(7), 418; https://doi.org/10.3390/info15070418 - 19 Jul 2024
Viewed by 1538
Abstract
The existing Siamese trackers have achieved increasingly successful results in visual object tracking. However, the interactive fusion among multi-layer similarity maps after cross-correlation has not been fully studied in previous Siamese network-based methods. To address this issue, we propose a novel Siamese network [...] Read more.
The existing Siamese trackers have achieved increasingly successful results in visual object tracking. However, the interactive fusion among multi-layer similarity maps after cross-correlation has not been fully studied in previous Siamese network-based methods. To address this issue, we propose a novel Siamese network for visual object tracking, named SiamSMN, which consists of a feature extraction network, a multi-scale fusion module, and a prediction head. First, the feature extraction network is used to extract the features of the template image and the search image, which is calculated by a depth-wise cross-correlation operation to produce multiple similarity feature maps. Second, we propose an effective multi-scale fusion module that can extract global context information for object search and learn the interdependencies between multi-level similarity maps. In addition, to further improve tracking accuracy, we design a learnable prediction head module to generate a boundary point for each side based on the coarse bounding box, which can solve the problem of inconsistent classification and regression during the tracking. Extensive experiments on four public benchmarks demonstrate that the proposed tracker has a competitive performance among other state-of-the-art trackers. Full article
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33 pages, 13561 KiB  
Article
The Effect of Scanning Strategy on the Thermal Behavior and Residual Stress Distribution of Damping Alloys during Selective Laser Melting
by Zhiqiang Yan, Kaiwen Wu, Zhongmin Xiao, Jizhuang Hui and Jingxiang Lv
Materials 2024, 17(12), 2912; https://doi.org/10.3390/ma17122912 - 14 Jun 2024
Cited by 2 | Viewed by 1372
Abstract
The manufacture of damping alloy parts with stable damping properties and high mechanical performances in the selective laser melting (SLM) process is influenced by temperature evolution and residual stress distribution. Choosing an appropriate scanning strategy, namely the specific trajectory along which the laser [...] Read more.
The manufacture of damping alloy parts with stable damping properties and high mechanical performances in the selective laser melting (SLM) process is influenced by temperature evolution and residual stress distribution. Choosing an appropriate scanning strategy, namely the specific trajectory along which the laser head scans powders within given area, is crucial, but clearly defined criteria for scanning strategy design are lacking. In this study, a three-dimensional finite element model (FEM) of the SLM process for manufacturing a WE43 alloy component was established and validated against the published experimental data. Eleven different scanning strategies were designed and simulated, considering variables such as scanning track length, direction, Out–In or In–Out strategy, start point, and interlayer variation. The results showed that scanning strategy, geometry, and layer number collectively affect temperature, melt pool, and stress outputs. For instance, starting scanning at a colder part of the powder layer could lead to a high peak temperature and low melt pool depth. A higher layer number generally results in lower cooling rate, a lower temperature gradient, a longer melt pool life, and larger melt pool dimensions. Changing the start point between scanning circulations helps mitigate detrimental residual stress. This work highlights the potential of analyzing various scanning strategy-related variables, which contributes to reducing trial-and-error tests and selecting optimal scanning strategies under different product quality requirements. This article can assist in the design of appropriate scanning strategies to prevent defects such as element loss due to evaporation, poor bonding, and deformation or cracking from high residual stress. Additionally, identifying stress concentration locations and understanding the effects of geometry and layer number on thermal and mechanical behaviors can assist in geometry design. Full article
(This article belongs to the Special Issue Advances in Laser Processing Technology of Materials)
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23 pages, 4708 KiB  
Article
Numerical Investigation of Different Stepped Spillway Geometries over a Mild Slope for Safe Operation Using Multi-Phase Model
by Binaya Raj Pandey, Megh Raj K C, Brian Crookston and Gerald Zenz
Water 2024, 16(11), 1635; https://doi.org/10.3390/w16111635 - 6 Jun 2024
Cited by 5 | Viewed by 2420
Abstract
The appropriate design and operation of spillways are critical for dam safety. To enhance design practices and gain insights into flow hydraulics, both experimental and numerical modeling are commonly employed. In this study, we conducted a numerical investigation of flow over a mildly [...] Read more.
The appropriate design and operation of spillways are critical for dam safety. To enhance design practices and gain insights into flow hydraulics, both experimental and numerical modeling are commonly employed. In this study, we conducted a numerical investigation of flow over a mildly sloping (1V:3H) stepped spillway with various step geometries using a multi-phase mixture model with dispersed interface tracking in ANSYS Fluent. The model was validated against experimental data from Utah State University, focusing on water surface profiles over the crest, velocities, and air concentrations. The validated numerical model was used to simulate flow over different step geometries (i.e., 0.2 m H uniform Step, 0.1 m H uniform step, non-uniform steps, adverse slope steps, and stepped pool) for a range of discharges from 0.285 m3/s/m to 1.265 m3/s/m. While flow depths over the crest and velocities in the chute compared well with experimental results, air concentrations exhibited some deviation, indicating numerical limitations of the solver. The shift in the location of the inception point was found to be mainly influenced by a higher flow rate than the different design configurations over an identical mild slope. The downstream non-linear flow velocity curve with different flow rates indicated less effectiveness of the step roughness over a high flow rate as a result of the reduction in relative roughness. The theoretical velocity ratio indicated the least reduction in downstream velocity with the stepped pooled spillway due to the formation of a “stagnant pool”. A higher negative-pressure region due to flow separation at the vertical face of the steps was obtained by adverse slope steps, which shows that the risk of cavitation is higher over the adverse slope step spillway. Turbulent kinetic energy (TKE) was found to be higher for uniform 0.2 m H steps due to the strong mixing of flow over the steps. The least TKE was found at the steps of the stepped pool spillway due to the formation of a “stagnant pool”. Uniform 0.2 m H steps achieved the maximum energy dissipation efficiency, whereas the stepped pool spillway obtained the least energy dissipation efficiency, introducing higher flow velocity at the stilling basin with a higher residual head. The adverse slope and non-uniform steps were found to be more effective than the uniform 0.1 m H steps and stepped pool spillway. The application of uniform steps of higher drop height and length could achieve higher TKE over the steps, reducing the directional flow velocity, which reduces the risk of potential damage. Full article
(This article belongs to the Special Issue CFD Modelling of Turbulent Free Surface Flows)
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15 pages, 2640 KiB  
Article
Toward Intraoperative Visual Intelligence: Real-Time Surgical Instrument Segmentation for Enhanced Surgical Monitoring
by Mostafa Daneshgar Rahbar, George Pappas and Nabih Jaber
Healthcare 2024, 12(11), 1112; https://doi.org/10.3390/healthcare12111112 - 29 May 2024
Cited by 2 | Viewed by 2526
Abstract
Background: Open surgery relies heavily on the surgeon’s visual acuity and spatial awareness to track instruments within a dynamic and often cluttered surgical field. Methods: This system utilizes a head-mounted depth camera to monitor surgical scenes, providing both image data and depth information. [...] Read more.
Background: Open surgery relies heavily on the surgeon’s visual acuity and spatial awareness to track instruments within a dynamic and often cluttered surgical field. Methods: This system utilizes a head-mounted depth camera to monitor surgical scenes, providing both image data and depth information. The video captured from this camera is scaled down, compressed using MPEG, and transmitted to a high-performance workstation via the RTSP (Real-Time Streaming Protocol), a reliable protocol designed for real-time media transmission. To segment surgical instruments, we utilize the enhanced U-Net with GridMask (EUGNet) for its proven effectiveness in surgical tool segmentation. Results: For rigorous validation, the system’s performance reliability and accuracy are evaluated using prerecorded RGB-D surgical videos. This work demonstrates the potential of this system to improve situational awareness, surgical efficiency, and generate data-driven insights within the operating room. In a simulated surgical environment, the system achieves a high accuracy of 85.5% in identifying and segmenting surgical instruments. Furthermore, the wireless video transmission proves reliable with a latency of 200 ms, suitable for real-time processing. Conclusions: These findings represent a promising step towards the development of assistive technologies with the potential to significantly enhance surgical practice. Full article
(This article belongs to the Section Artificial Intelligence in Medicine)
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16 pages, 6263 KiB  
Article
Implementation and Evaluation of Walk-in-Place Using a Low-Cost Motion-Capture Device for Virtual Reality Applications
by Rawoo Shin, Bogyu Choi, Sang-Min Choi and Suwon Lee
Sensors 2024, 24(9), 2848; https://doi.org/10.3390/s24092848 - 30 Apr 2024
Cited by 6 | Viewed by 2108
Abstract
Virtual reality (VR) is used in many fields, including entertainment, education, training, and healthcare, because it allows users to experience challenging and dangerous situations that may be impossible in real life. Advances in head-mounted display technology have enhanced visual immersion, offering content that [...] Read more.
Virtual reality (VR) is used in many fields, including entertainment, education, training, and healthcare, because it allows users to experience challenging and dangerous situations that may be impossible in real life. Advances in head-mounted display technology have enhanced visual immersion, offering content that closely resembles reality. However, several factors can reduce VR immersion, particularly issues with the interactions in the virtual world, such as locomotion. Additionally, the development of locomotion technology is occurring at a moderate pace. Continuous research is being conducted using hardware such as treadmills, and motion tracking using depth cameras, but they are costly and space-intensive. This paper presents a walk-in-place (WIP) algorithm that uses Mocopi, a low-cost motion-capture device, to track user movements in real time. Additionally, its feasibility for VR applications was evaluated by comparing its performance with that of a treadmill using the absolute trajectory error metric and survey data collected from human participants. The proposed WIP algorithm with low-cost Mocopi exhibited performance similar to that of the high-cost treadmill, with significantly positive results for spatial awareness. This study is expected to contribute to solving the issue of spatial constraints when experiencing infinite virtual spaces. Full article
(This article belongs to the Section Navigation and Positioning)
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25 pages, 7135 KiB  
Article
A Seamless Deep Learning Approach for Apple Detection, Depth Estimation, and Tracking Using YOLO Models Enhanced by Multi-Head Attention Mechanism
by Praveen Kumar Sekharamantry, Farid Melgani, Jonni Malacarne, Riccardo Ricci, Rodrigo de Almeida Silva and Jose Marcato Junior
Computers 2024, 13(3), 83; https://doi.org/10.3390/computers13030083 - 21 Mar 2024
Cited by 15 | Viewed by 3841
Abstract
Considering precision agriculture, recent technological developments have sparked the emergence of several new tools that can help to automate the agricultural process. For instance, accurately detecting and counting apples in orchards is essential for maximizing harvests and ensuring effective resource management. However, there [...] Read more.
Considering precision agriculture, recent technological developments have sparked the emergence of several new tools that can help to automate the agricultural process. For instance, accurately detecting and counting apples in orchards is essential for maximizing harvests and ensuring effective resource management. However, there are several intrinsic difficulties with traditional techniques for identifying and counting apples in orchards. To identify, recognize, and detect apples, apple target detection algorithms, such as YOLOv7, have shown a great deal of reflection and accuracy. But occlusions, electrical wiring, branches, and overlapping pose severe issues for precisely detecting apples. Thus, to overcome these issues and accurately recognize apples and find the depth of apples from drone-based videos in complicated backdrops, our proposed model combines a multi-head attention system with the YOLOv7 object identification framework. Furthermore, we provide the ByteTrack method for apple counting in real time, which guarantees effective monitoring of apples. To verify the efficacy of our suggested model, a thorough comparison assessment is performed with several current apple detection and counting techniques. The outcomes adequately proved the effectiveness of our strategy, which continuously surpassed competing methods to achieve exceptional accuracies of 0.92, 0.96, and 0.95 with respect to precision, recall, and F1 score, and a low MAPE of 0.027, respectively. Full article
(This article belongs to the Special Issue Advanced Image Processing and Computer Vision)
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24 pages, 10171 KiB  
Article
A Multi-Depth Deflectometer/Global Navigation Satellite System Method for Measuring Concrete Slab Track Deformation
by Pierre Anthyme Bahati, Viet Dinh Le and Yujin Lim
Appl. Sci. 2024, 14(1), 82; https://doi.org/10.3390/app14010082 - 21 Dec 2023
Viewed by 1399
Abstract
This study introduces a Multi-Depth Deflectometer (MDD) combined with a Global Navigation Satellite System (GNSS) which was developed for measuring the deformation of railway slab track layers. We newly designed the MDD with the addition of laser sensor modules for increasing precision in [...] Read more.
This study introduces a Multi-Depth Deflectometer (MDD) combined with a Global Navigation Satellite System (GNSS) which was developed for measuring the deformation of railway slab track layers. We newly designed the MDD with the addition of laser sensor modules for increasing precision in which the MDD head is fixed at the top of the track slab. The MDD/GNSS system can measure the relative deflection between each track layer as well as the total deflection at the top of the track slab, which makes it possible to evade the fixed condition problem of classical MDD. The new MDD/GNSS system was installed at the transition zone between a tunnel entrance and its embankment, which experienced high settlement levels prior to repair. The system was used to monitor whether the repaired concrete track foundation with pressurized cement grouting was stabilized effectively and what track layer position was most unstable so that it had the most influence. The GNSS system was designed and built for computing net settlement at each track layer even when the MDD could not be fixed firmly at the end point, which is a major drawback of classical MDD. The results obtained from MDD and GNSS measurements indicated significant potential in aiding railway track settlement measurements. Full article
(This article belongs to the Special Issue Railway Infrastructures Engineering: Latest Advances and Prospects)
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