 Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
| A B C D E F G H I J K L M N O P Q R S T U V W X Y Z | | The end of the list has been reached or no journals were found for your choice. |
|
|
- Damage Detection of X-ray Image of Conveyor Belts with Steel Rope Cores
Based on Improved FCOS Algorithm-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Aimed at the long and narrow geometric features and poor generalization ability of the damage detection in conveyor belts with steel rope cores using the X-ray image, a detection method of damage X-ray image is proposed based on the improved fully convolutional one-stage object detection (FCOS) algorithm. The regression performance of bounding boxes was optimized by introducing the complete intersection over union loss function into the improved algorithm. The feature fusion network structure is modified by adding adaptive fusion paths to the feature fusion network structure, which makes full use of the features of accurate localization and semantics of multi-scale feature fusion networks. Finally, the network structure was trained and validated by using the X-ray image dataset of damages in conveyor belts with steel rope cores provided by a flaw detection equipment manufacturer. In addition, the data enhancement methods such as rotating, mirroring, and scaling, were employed to enrich the image dataset so that the model is adequately trained. Experimental results showed that the improved FCOS algorithm promoted the precision rate and the recall rate by 20.9% and 14.8% respectively, compared with the original algorithm. Meanwhile, compared with Fast R-CNN, Faster R-CNN, SSD, and YOLOv3, the improved FCOS algorithm has obvious advantages; detection precision rate and recall rate of the modified network reached 95.8% and 97.0% respectively. Furthermore, it demonstrated a higher detection accuracy without affecting the speed. The results of this work have some reference significance for the automatic identification and detection of steel core conveyor belt damage.
PubDate: 2023-09-12
- Static and Fatigue Behavior of Hybrid Bonded/Bolted Glass Fiber Reinforced
Polymer Joints Under Tensile Loading-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract This paper presents the static and fatigue tests of hybrid (bonded/bolted) glass fiber reinforced polymer (GFRP) joints. Nine specimens of single-lap hybrid GFRP joints have been fabricated to study the static and fatigue behaviors in the experimental campaign. The static tests of uniaxial tension loading are first conducted, from which the static ultimate bearing capacities of the joints are obtained. High-cycle fatigue tests are subsequently carried out so that the fatigue failure mode, fatigue life, and stiffness degradation of joints can be obtained. The measuring techniques including acoustic emission monitoring and three-dimensional digital image correlation have been employed in the tests to record the damage development process. The results revealed that the static strength and fatigue behavior of such thick hybrid GFRP joints were controlled by the bolted connections. The four stages of fatigue failure process are obtained from tests and acoustic emission signals analysis: cumulative damage of adhesive layer, damage of the adhesive layer, cumulative damage of GFRP plate, and damage of GFRP plate. The fatigue life and stiffness degradation can be improved by more bolts. The S-N (fatigue stress versus life) curves for the fatigue design of the single-lap hybrid GFRP joints under uniaxial tension loading are also proposed.
PubDate: 2023-09-12
- Computer Aided Diagnosis for COVID-19 in CT Images Utilizing Transfer
Learning and Attention Mechanism-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Various and intricate varieties of lung disease have made it challenging for computer aided diagnosis to appropriately segment lung lesions utilizing computed tomography (CT) images. This study integrates transfer learning with the attention mechanism to construct a deep learning model that can automatically detect new coronary pneumonia on lung CT images. In this study, using VGG16 pre-trained by ImageNet as the encoder, the decoder was established utilizing the U-Net structure. The attention module is incorporated during each concatenate procedure, permitting the model to concentrate on the critical information and identify the crucial components efficiently. The public COVID-19-CT-Seg-Benchmark dataset was utilized for experiments, and the highest scores for Dice, F1, and Accuracy were 0.9071, 0.907 6, and 0.996 5, respectively. The generalization performance was assessed concurrently, with performance metrics including Dice, F1, and Accuracy over 0.8. The experimental findings indicate the feasibility of the segmentation network proposed in this study.
PubDate: 2023-09-07
- Dynamic Analysis and Trajectory Solution of Multi-Robot Coordinated Towing
System-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Multi-robot coordinated towing system is an under-constrained system. The dynamic response of the towing system can not be fully controlled since the rope can only provide a unidirectional constraint force to the suspended object. Based on the kinematics of the multi-robot coordinated towing system with fixed-base, the Newton-Euler equations and Udwadia-Kalaba equations were used to establish the dynamics of the towing system. To obtain the motion trajectories with high stability and strong control, the motion trajectories of the towing system were optimized. During the towing, the transition from the relaxation state to the tension state of the rope was treated as a collision between the suspended object and the robot end. The trajectories of the towing system in terms of a single-variable and multiple-variable were solved, respectively. The simulation shows that the optimized trajectories are closer to reality and truly reflect the constraints of the ropes on the suspended object. The research results provide a basis for trajectory planning and control of the towing system.
PubDate: 2023-09-07
- Fast Parallel Magnetic Resonance Imaging Reconstruction Based on
Sparsifying Transform Learning and Structured Low-Rank Model-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract The structured low-rank model for parallel magnetic resonance (MR) imaging can efficiently reconstruct MR images with limited auto-calibration signals. To improve the reconstruction quality of MR images, we integrate the joint sparsity and sparsifying transform learning (JTL) into the simultaneous auto-calibrating and k-space estimation (SAKE) structured low-rank model named JTLSAKE. The alternate direction method of multipliers is exploited to solve the resulting optimization problem, and the optimized gradient method is used to improve the convergence speed. In addition, a graphics processing unit is used to accelerate the proposed algorithm. The experimental results on four in vivo human datasets demonstrate that the reconstruction quality of the proposed algorithm is comparable to that of JTL-based low-rank modeling of local k-space neighborhoods with parallel imaging (JTL-PLORAKS), and the proposed algorithm is 46 times faster than the JTL-PLORAKS, requiring only 4 s to reconstruct a 200 × 200 pixels MR image with 8 channels.
PubDate: 2023-09-07
- Hyperspectral Satellite Image Classification Based on Feature Pyramid
Networks With 3D Convolution-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Recent advances in convolution neural network (CNN) have fostered the progress in object recognition and semantic segmentation, which in turn has improved the performance of hyperspectral image (HSI) classification. Nevertheless, the difficulty of high dimensional feature extraction and the shortage of small training samples seriously hinder the future development of HSI classification. In this paper, we propose a novel algorithm for HSI classification based on three-dimensional (3D) CNN and a feature pyramid network (FPN), called 3D-FPN. The framework contains a principle component analysis, a feature extraction structure and a logistic regression. Specifically, the FPN built with 3D convolutions not only retains the advantages of 3D convolution to fully extract the spectral-spatial feature maps, but also concentrates on more detailed information and performs multi-scale feature fusion. This method avoids the excessive complexity of the model and is suitable for small sample hyperspectral classification with varying categories and spatial resolutions. In order to test the performance of our proposed 3D-FPN method, rigorous experimental analysis was performed on three public hyperspectral data sets and hyperspectral data of GF-5 satellite. Quantitative and qualitative results indicated that our proposed method attained the best performance among other current state-of-the-art end-to-end deep learning-based methods.
PubDate: 2023-09-07
- Influence of Height of Bionic Hexagonal Texture on Tactile Perception
-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract It is significant to process textures with special functions similar to animal surfaces based on bionics and improve the friction stability and contact comfort of contact surfaces for the surface texture design of tactile products. In this paper, a bionic hexagonal micro-convex texture was prepared on an acrylic surface by laser processing. The friction mechanism of a finger touching the bionic hexagonal micro-convex texture under different touch speeds and pressures, and the effect of the height of the texture on tactile perception were investigated by finite element, subjective evaluation, friction, and EEG tests. The results showed that the deformation friction was the main friction component when the finger touched the bionic hexagonal texture, and the slipperiness and friction factor showed a significant negative correlation. As the touch speed decreased or the touch force increased, the hysteresis friction of the fingers as well as the interlocking friction increased, and the slipperiness perception decreased. The bionic hexagonal texture with higher convexity caused a higher friction factor, lower slipperiness perception, and lower P300 peak. Hexagonal textures with lower convexity, lower friction factor, and higher slipperiness perception required greater brain attentional resources and intensity of tactile information processing during tactile perception.
PubDate: 2023-09-07
- Genetic Clustering-Based Equivalent Model of Wind Farm with Doubly Fed
Induction Generator-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract With increasing the number of wind power generators, the consumption time of electromagnetic simulation of the wind farm explodes. To reduce the simulation time while meeting the accuracy requirement, a genetic clustering-based equivalent model is proposed for the wind farm with numerous doubly fed induction generators. In the proposed model, active power together with the reactive power and the wind speed are selected to form the set of clustering indicators. A normalization technique is utilized to cope with the multiple orders of magnitude in these factors. An exponential fitness value is formulated as a function of the sorting number of the primary fitness value, and the fitness-based selection probability is constructed to overcome the property of premature and slow convergence of the genetic clustering algorithm. The sum of squares due to error is used to determine the optimal clustering number. In addition, a decoupled parameter equivalence method is adopted to obtain the equivalent parameters of the collection network. Simulation results and comparisons with various methods under different voltage scenarios show the feasibility and effectiveness of the proposed model.
PubDate: 2023-09-06
- Wire Rope Inspection Robots: A Review
-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Wire rope inspection robot is an important tool for wire rope condition monitoring and maintenance, which can accurately locate and judge the damage of wire rope. In addition, the wire rope inspection robot can also be used for cable inspection. First, the crawling structure and crawling mode of the wire rope inspection robot are reviewed, and the characteristics and existing problems of each crawling mode are analyzed separately. Next, the drive mode of the wire rope inspection robot is discussed, the types of commonly used motors are introduced, and the advantages and disadvantages of drive motors and the control modes are compared. Then, the method and principle of the non-destructive detection of the wire rope inspection robot are expounded, and the commonly used detection methods and existing deficiencies are compared. After that, the types of communication modes are compared and analyzed, and the types of wireless communication modes are also introduced. Finally, the current difficult problems of the wire rope inspection robot are summarized, and the future development trend of the wire rope inspection robot is prospected.
PubDate: 2023-08-23
- Fuzzy Dynamic Optimal Model for COVID-19 Epidemic in India Based on
Granular Differentiability-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract The pandemic SARS-CoV-2 has become an undying virus to spread a sustainable disease named COVID-19 for upcoming few years. Mortality rates are rising rapidly as approved drugs are not yet available. Isolation from the infected person or community is the preferred choice to protect our health. Since humans are the only carriers, it might be possible to control the positive rate if the infected population or host carriers are isolated from each other. Isolation alone may not be a proper solution. These are the resolutions of previous research work carried out on COVID-19 throughout the world. The present scenario of the world and public health is knocking hard with a big question of critical uncertainty of COVID-19 because of its imprecise database as per daily positive cases recorded all over the world and in India as well. In this research work, we have presented an optimal control model for COVID-19 using granular differentiability based on fuzzy dynamical systems. In the first step, we created a fuzzy Susciptable-Exposed-Infected-Asymptomatic-Hospitalized-Recovered-Death (SEIAHRD) model for COVID-19, analyzed it using granular differentiability, and reported disease dynamics for time-independent disease control parameters. In the second step, we upgraded the fuzzy dynamical system and granular differentiability model related to time-dependent disease control parameters as an optimal control problem invader. Theoretical studies have been validated with some practical data from the epidemic COVID-19 related to the Indian perspective during first wave and early second wave.
PubDate: 2023-08-23
- Toughening Mechanism of Large Heat Input Weld Metal for Marine Engineering
Extra-Thick Plate-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract In order to study the latest designed large heat input welding material of marine engineering extra-thick plate, EH36 steel was joined by using twin-wire submerged arc welding with heat inputs of 85, 100 and 115 kJ/cm separately. Meanwhile, the microstructure and mechanical properties were evaluated to explore the toughening mechanism of weld metal. Results show that a lot of active inclusions are obtained in the weld metal due to the design idea of low carbon and oxide metallurgy, which contributes to the generation of numerous fine and interlocking acicular ferrite. The acicular ferrite volume ratio of weld metal exceeds 60%. Moreover, the impact energy at −40 °C surpasses 115 J and the crack tip opening displacement value at −10 °Cis morethan 0.2 mm under three heat inputs owing to the role of acicular ferrite, of which 85 kJ/cm is the best. The martensite-austenite constituents are minor in size and the microstructure of the weld metal in reheated zone is dominated by small massive equiaxed ferrite, without impairing the toughness. As the heat input increases, the content of acicular ferrite drops and then rises; the impact toughness and fracture toughness first worsen consequently and then stabilize on account of the dramatic expansion of the proeutectoid ferrite size.
PubDate: 2023-08-23
- Hydrodynamic Characteristics of Hybrid Mooring System with Dual-Platform
Joint Operation-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract With the development of marine resources, a dual-platform joint operation has been paid more attention. In this paper, the mooring layout space and relative motion limitation of the dual-platform berthing operation were fully considered. A new hybrid mooring system with “X + buoy” combination was designed based on the characteristics of catenary and tension mooring. The hydrodynamic characteristics of the new mooring system were analyzed by combining numerical simulation with model experiment. Under the regular and freak waves with different wave heights and periods, the time-domain full-coupling analysis method was used to study the hydrodynamic characteristics of the mooring system. It can be found that the arrangement of dual-platform under 0° wave direction is optimal, and the “X + buoy” combined mooring system designed in this paper has a good follow-up between the two platforms under different regular and freak waves. The relative motion response between the two platforms can be effectively controlled, and finally the positioning of the dual-platform joint operation is realized. Research results of this paper provide a theoretical basis and technical support for the hydrodynamic performance analysis and safety assessment of deep-sea offshore platforms in China.
PubDate: 2023-08-23
- Improvement of Prior Image for Metal Artifact Reduction of Computed
Tomography-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract It is not easy to reduce the metal artifacts of computed tomography images. However, the pixel values inside the metal artifact regions vary smoothly, while those on the borders of the metal and the bone regions vary sharply. When the Canny operation by adaptive thresholding is conducted on the raw image, the almost continuous edges can be formed obviously on the borders of the metal and the bone regions, but this kind of information cannot be formed for the metal artifact regions. In this paper, by searching the closed areas formed by the border edges of the bone regions in the Canny image, the metal artifact regions, which are very difficult to discriminate only by intensity thresholding, can be excluded effectively. A novel prior image-based method is thus developed for metal artifact reduction. The experiments demonstrate that the proposed method can be realized easily and reduce the metal artifacts effectively even if multiple large metal objects exist simultaneously in the image. The method is suitable for the clinical application.
PubDate: 2023-08-23
- Experimental Investigation of Possibility of Simultaneously Monitoring
Lung Perfusion/Cardiomotility and Ventilation via Thoracic Impedance
Measurement-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Impedance pneumography has a significant advantage for continuous and noninvasive monitoring of respiration, compared with conventional flowmeter-based ventilation measurement technologies. While thoracic impedance is sensitive to pulmonary ventilation, it is also sensitive to physiological activities such as blood flow and cardiomotility, in addition, body movement/posture. This paper explores the possibility of simultaneously monitoring pulmonary ventilation, blood circulation and cardiomotility by bioimpedance measurement. Respiratory, blood perfusion and cardiomotility signals are extracted using the wavelet method from thoracic impedance data measured in breath-holding and tidal breathing statuses, to investigate signal strength and their dependency. This research provides a foundation for the development of bedside devices to monitor various physiological activities.
PubDate: 2023-08-23
- Load Stability Analysis of a Floating Multi-Robot Coordinated Towing
System-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Cranes used at sea have some shortcomings in terms of flexibility, efficiency, and safety. Therefore, a floating multi-robot coordinated towing system is planned to fulfill the offshore towing requirements. It is difficult to study the stability of a floating multi-robot coordinated towing system by ancient strategies. First, the minimum tension of the rope and the minimum singular value of the stiffness matrix were separately used to analyze the load stability. The advantages and disadvantages of the two methods were discussed. Then, the two stability analysis methods were normalized and weighted to obtain the method based on minimum tension and minimum singular to comprehensively analyze the stability of the load. Finally, the effect of different weighting coefficients on the load stability was analyzed, which led to a reasonable weighting coefficient to evaluate the load stability by comparing with a single analysis method. The research results provide a basis for the motion planning and coordinated control of the towing system.
PubDate: 2023-08-15
- Image Mosaic Method of Capsule Endoscopy Intestinal Wall Based on Improved
Weighted Fusion-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract There is still a dearth of systematic study on picture stitching techniques for the natural tubular structures of intestines, and traditional stitching techniques have a poor application to endoscopic images with deep scenes. In order to recreate the intestinal wall in two dimensions, a method is developed. The normalized Laplacian algorithm is used to enhance the image and transform it into polar coordinates according to the characteristics that intestinal images are not obvious and usually arranged in a circle, in order to extract the new image segments of the current image relative to the previous image. The improved weighted fusion algorithm is then used to sequentially splice the segment images. The experimental results demonstrate that the suggested approach can improve image clarity and minimize noise while maintaining the information content of intestinal images. In addition, the method’s seamless transition between the final portions of a panoramic image also demonstrates that the stitching trace has been removed.
PubDate: 2023-08-15
- Deep Learning Framework for Predicting Essential Proteins with Temporal
Convolutional Networks-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Essential proteins are an indispensable part of cells and play an extremely significant role in genetic disease diagnosis and drug development. Therefore, the prediction of essential proteins has received extensive attention from researchers. Many centrality methods and machine learning algorithms have been proposed to predict essential proteins. Nevertheless, the topological characteristics learned by the centrality method are not comprehensive enough, resulting in low accuracy. In addition, machine learning algorithms need sufficient prior knowledge to select features, and the ability to solve imbalanced classification problems needs to be further strengthened. These two factors greatly affect the performance of predicting essential proteins. In this paper, we propose a deep learning framework based on temporal convolutional networks to predict essential proteins by integrating gene expression data and protein-protein interaction (PPI) network. We make use of the method of network embedding to automatically learn more abundant features of proteins in the PPI network. For gene expression data, we treat it as sequence data, and use temporal convolutional networks to extract sequence features. Finally, the two types of features are integrated and put into the multi-layer neural network to complete the final classification task. The performance of our method is evaluated by comparing with seven centrality methods, six machine learning algorithms, and two deep learning models. The results of the experiment show that our method is more effective than the comparison methods for predicting essential proteins.
PubDate: 2023-08-15
- Dynamic Response of Idiopathic Scoliosis and Kyphosis Spine
-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract The dynamic response characteristics of scoliosis and kyphosis to vibration are currently unclear. The finite element method (FEM) was employed to study the vibration response of patients with idiopathic scoliosis and kyphosis. The objective is to analyze the dynamic characteristics of idiopathic scoliosis and kyphosis using FEM. The finite element model of T1—S1 segment was established and verified using the CT scanning images. The established scoliosis and kyphosis models were verified statistically and dynamically. The finite element software Abaqus was utilized to analyze the mode, harmonic response, and transient dynamics of scoliosis and kyphosis. The first four natural frequencies extracted from modal analysis were 1.34, 2.26, 4.49 and 17.69 Hz respectively. Notably, the first three natural frequencies decreased with the increase of upper body mass. In harmonic response analysis, the frequency corresponding to the maximum amplitude in x direction was the first order natural frequency, and the frequency corresponding to the maximum amplitude in y and z directions was the second order natural frequency. At the same resonance frequency, the amplitude of the thoracic spine was larger relative to that of the lumbar spine. The time domain results of transient analysis showed that the displacement dynamic response of each segment presented cyclic response characteristics over time. Under 2.26 Hz excitation, the dynamic response of the research object appeared as resonance. The higher the degree of spinal deformity, the greater the fundamental frequency. The first three natural modes of scoliosis and kyphosis contain vibration components in the vertical direction. The second order natural frequency was the most harmful to patients with scoliosis and kyphosis. Under cyclic loading, the deformation of the thoracic cone exceeds that of the lumbar cone.
PubDate: 2023-08-15
- Adjacent Segment Biomechanical Changes After Implantation of Cage Plus
Plate or Zero-Profile Device in Different Segmental Anterior Cervical
Discectomy and Fusion-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Cage plus plate (CP) and zero-profile (Zero-P) devices are widely used in anterior cervical discectomy and fusion (ACDF). This study aimed to compare adjacent segment biomechanical changes after ACDF when using Zero-P device and CP in different segments. First, complete C1—C7 cervical segments were constructed and validated. Meanwhile, four surgery models were developed by implanting the Zero-P device or CP into C4—C5 or C5—C6 segments based on the intact model. The segmental range of motion (ROM) and maximum value of the intradiscal pressure of the surgery models were compared with those of the intact model. The implantation of CP and Zero-P devices in C4—C5 segments decreased ROM by about 91.6% and 84.3%, respectively, and increased adjacent segment ROM by about 8.3% and 6.82%, respectively. The implantation of CP and Zero-P devices in C5—C6 segments decreased ROM by about 93.3% and 89.9%, respectively, while increasing adjacent segment ROM by about 4.9% and 4%, respectively. Furthermore, the implantation of CP and Zero-P devices increased the intradiscal pressure in the adjacent segments of C4—C5 segments by about 4.5% and 6.7%, respectively. The implantation of CP and Zero-P devices significantly increased the intradiscal pressure in the adjacent segments of C5—C6 by about 54.1% and 15.4%, respectively. In conclusion, CP and Zero-P fusion systems can significantly reduce the ROM of the fusion implant segment in ACDF while increasing the ROM and intradiscal pressure of adjacent segments. Results showed that Zero-P fusion system is the best choice for C5—C6 segmental ACDF. However, further studies are needed to select the most suitable cervical fusion system for C4—C5 segmental ACDF. Therefore, this study provides biomechanical recommendations for clinical surgery.
PubDate: 2023-08-15
- Double Focus Laser Displacement Sensor Suppressing Laser Jitter and Target
Tilt-
Free pre-print version: Loading...
Rate this result:
What is this?
Please help us test our new pre-print finding feature by giving the pre-print link a rating.
A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Abstract Measurement precision of laser displacement sensor is subject to various factors, among which laser jitter and target tilt will directly lead to the position movement and shape variation of the laser spot, resulting in displacement measurement errors, so that researchers have to do a lot of research on the spot centering algorithm to weaken the above effects, which can treat the symptoms but not the root cause. Starting from the source of the problem, this paper proposes a double focus double peak solution, which uses a reflector to change the direction of the optical path, so that the imaging spots of the designed two optical paths focus on the same CMOS, forming a double peak structure. When laser jitter or target tilt occurs, the center of the two laser spots is shifted, but they move in the same direction, while their relative position remains unchanged. Therefore, the displacement can be characterized by the relative position of the two laser spots, so that laser jitter and target tilt are suppressed from the source. However, the two spots imaged on CMOS form a non-Gaussian distributed double peak structure, so the conventional laser spot centering algorithms are no longer applicable. To this end, a double peak adaptive threshold waveform extraction method combined with grayscale gravity method is proposed for spot centering algorithm, which combines the suppression of laser jitter and target tilt from the source and the improvement of spot positioning precision which represents the displacement measurement precision, and is experimentally verified.
PubDate: 2023-08-15
|
Hybrid journal (It can contain Open Access articles)
