Scanning Technique Research Articles

F wave analysis based on the compound muscle action potential scan.

Conventional F wave analysis involves a relatively uniform physiological environment induced by supramaximal stimulations. The F wave characteristics in a dynamic physiological condition, however, are rarely investigated. This study aimed to improve understanding of F wave properties in the more dynamic process by introducing a novel method to analyze F waves based on the compound muscle action potential (CMAP) scan technique. Twenty four healthy subjects participated in the study. The CMAP scan was applied to record muscle responses in the abductor pollicis brevis (APB) and abductor digiti minimi (ADM) muscles, respectively. F wave characteristics including mean F wave amplitude and latency (F-M latency), persistence and activating threshold were quantified. An average of 200 F waves per muscle were obtained from the CMAP scan recording. Weak to moderate correlations between F wave amplitude and stimulating intensity were observed in most of the APB (19 muscles; r = 0.33 ± 0.14, all p < .05) and ADM (23 muscles, r = 0.46 ± 0.16, all p < .05) muscles. Significantly longer mean F latency and lower activating F-threshold were found in the ADM muscles (F-M latency: APB: 25.43 ± 2.39 ms, ADM: 26.15 ± 2.32 ms, p < .05; F-threshold: APB: 7.68 ± 8.96% CMAP, ADM: 2.35 ± 2.42% CMAP, p < .05). This study introduces new features of F waves using the CMAP scan technique and identifies differences of F wave characteristics between the hand muscles. The CMAP scan based F waves analysis can be combined with the motor unit number estimation to assess functional alterations in motor neurons in neurological disorders.

Effect of variable load on centralized dimple in opposite sliding condition

Abstract In ball bearings without a cage, adjacent balls exhibit a zero-entrainment velocity (ZEV) contact condition, which is worse than typical pure rolling or rolling-sliding contact, and the contact between adjacent balls under periodic loading is notably more complicated. In this work, thermal elastohydrodynamic lubrication (EHL) numerical calculation is carried out under the condition of periodic impact and opposite sliding line contact over a wide range of surface speeds. the pressure is solved by multigrid method, the elastic deformation is evaluated using multigrid integration method, the temperature field is calculated by column-by-column scanning technique. The results show that the loading-unloading process exerts significant influence on the variation of the centralized dimple, pressure, and temperature rises as well as the oil characteristics. With the increase of surface speed, the effect of load fluctuations diminishes, and the central dimple exhibits the following evolutionary trend under ZEV conditions: no dimple at very low velocity - small central dimple - large typical dimple - no dimple at high velocity. The result indicates that under the ZEV condition of EHL stage, elevated velocities decrease the coefficient of friction and augment the film thickness.

Decoding urban evolution: A parametric reconstruction of the Old City of Aleppo between the mamluk and the post-war city

The Old City of Aleppo suffered extensive urban damage during the war in Syria. This study showcases the implementation of digital pipelines in visualizing and studying the history and evolution of two districts within the Old City. The aim of this study was to develop a parametric workflow that would allow for the reconstruction of a section of Mamluk Aleppo. This reconstruction was based on both cartographical and historical inputs. A comprehensive digital field survey was conducted using laser scanning and aerial photogrammetry techniques. The resulting point cloud data is then compared to the historical parametric model, and 3D urban changes to the studied area were identified.

The Laser Scanner Technique: A Tool for Determining Shear Strength Parameters of Rock Mass Discontinuities

When evaluating the shear strength of rock mass discontinuities, certain challenges arise due to the difficulty in quantifying the roughness characteristics of surfaces and the strength of asperities. Recent research has focused on enhancing techniques for assessing these characteristics and exploring the application of laser scanning to aid in evaluating discontinuity features. The analysis of reflectivity values (I) obtained through a laser scanner survey presents an efficient method for assessing mechanical characteristics, such as joint compressive strength (JCS). Reflectivity measurements demonstrate correlations with Schmidt hammer rebound values (r). The laser scanner technique would enable the measurement of JCS without the direct application of the Schmidt hammer on rocks in areas where rebound values (r) measurements are unavailable. The use of a laser scanner allows for the acquisition of high-precision geometrical information concerning the 3D roughness and anisotropy of rock surfaces. In this study, an innovative technique was introduced that utilizes laser scanner data from six previous experimental surveys conducted on rock formations in Southern Italy. This technique facilitates the evaluation of roughness profiles, considering potential variations along kinematically admissible sliding directions, allowing for the estimation of the Joint Roughness Coefficient (JRC). This new methodology aids in evaluating the parameters of Barton’s equation to determine the strength characteristics of rock mass discontinuities.

Enhancing Clinical Diagnosis With Convolutional Neural Networks: Developing High-Accuracy Deep Learning Models for Differentiating Thoracic Pathologies.

Background The use of computational technology in medicine has allowed for an increase in the accuracy of clinical diagnosis, reducing errors through additional layers of oversight. Artificial intelligence technologies present the potential to further augment and expedite the accuracy, quality, and efficiency at which diagnosis can be made when used as an adjunctive tool. Such techniques, if found to be accurate and reliable in their diagnostic acuity, can be implemented to foster better clinical decision-making, improving patient quality of care while reducing healthcare costs. Methodology This study implemented convolution neural networks to develop a deep learning model capable of differentiating normal chest X-rays from those indicating pneumonia, tuberculosis, cardiomegaly, and COVID-19. There were 3,063 normal chest X-rays, 3,098 pneumonia chest X-rays, 2,920 COVID-19 chest X-rays, 2,214 chest X-rays, and 554 tuberculosis chest X-rays from Kaggle that were used for training and validation.The model was trained to recognize patterns within the chest X-rays to efficiently recognize these diseases within patients to be treated on time. Results The results indicated a success rate of 98.34% incorrect detections, exemplifying a high degree of accuracy. There are limitations to this study. Training models require hundreds to thousands of samples, and due to potential variability in image scanning equipment and techniques from which the images are sourced, the model could have learned to interpret external noise and unintended details which can adversely impact accuracy. Conclusions Further studies that implement more universal database-sourced images with similar image scanning techniques, assess diverse but related medical conditions, and the utilization of repeat trials can help assess the reliability of the model.These results highlight the potential of machine learning algorithms for disease detection with chest X-rays.

Experimental study of flow control on tip leakage flow in variable geometry linear turbine cascades with different pivot layouts

Variable geometry turbines are essential for adjusting operational conditions in industrial gas turbines and variable cycle engines. These adjustments necessitate partial gaps at both ends of the variable guide vanes to alter the turning angle, consequently introducing an aerodynamic performance penalty. Moreover, the pivot layout profoundly influences aerodynamic losses. Research on turbine cascades that considers various partial gap layouts is limited, particularly in terms of experimental studies, which are rarely conducted. This study aims to diminish aerodynamic losses and augment the efficiency of gas turbines by examining the impact of pivot layouts on partial gap clearance and secondary flow. It further investigates the effectiveness of flow control strategies at the blade tip across different pivot configurations within a variable geometry turbine cascade, utilizing pneumatic probe scanning and surface oil flow visualization techniques. The results reveal that employing a cavity at the tip can significantly reduce aerodynamic losses in schemes both with and without a pivot, achieving maximum loss reductions of 15.8% and 3.7%, respectively. Additionally, a narrower squealer width can further decrease these losses. However, with a pivot located at the tip, the resulting separation flow and wake vortex become predominant sources of losses. The presence of the pivot weakens the tip leakage flow rate and the intensity of the tip leakage vortex (TLV), thus diminishing the effectiveness of cavity tip flow control. The cavity moderates TLV and enhances the interaction between TLV and the wake vortex, leading to increased aerodynamic losses.

Toward Indirect Real-Time Prediction of Bridge Vibration Responses Under Traffic Flow Through a Population of Connected Sensing Vehicles

Condition monitoring of bridge structures as the lifelines of smart cities is high of importance. While indirect vehicle scanning techniques have shown promising results and have less cost compared to mounting fixed sensors on the bridge, they have limitations in predicting response under traffic flow since the crossing time of one vehicle is very short. This paper presents a novel crowsensing-based framework for predicting bridge acceleration responses and identifying the modal characteristics. This method utilizes smartphone data from a diverse population of sensing vehicles as they traverse the bridge to predict bridge acceleration response at various virtual sensing locations. Subsequently, the predicted acceleration is used to identify the mode shapes and natural frequencies of the bridge. The principal innovation in this practical and cost-effective monitoring solution is the utilization of a randomly selected set of sensing vehicles at each timestamp. These selections may differ from one timestamp to the next, reflecting the real-world conditions where certain vehicles may intermittently lose or disconnect their internet connectivity. By consistently updating the set of sensing agents while other vehicles cross the bridge, the proposed framework overcomes the data length limitations of conventional vehicle-based methods by leveraging multiple vehicles and continuous data collection. Comprehensive numerical studies are conducted to evaluate the performance of the method. In the numerical investigations, a three-span bridge is subjected to the continuous passing of a large number of half-car vehicle models with random speeds and initial locations. Vehicle-bridge interaction is considered in the analysis. Utilizing a single randomly selected sensing agent at each timestamp, the results demonstrate the effectiveness of the framework in predicting bridge acceleration response with a relative error of less than 5%. Additionally, the method achieves an accuracy level of 95% in identifying the bridge's initial three mode shapes.

Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization

Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%.

Imaging Uncertainty: Layers of Time and Meaning in a Sacred Space

AbstractLaid bare by contemporary scanning techniques and technologies, historic buildings reveal a series of nested, diaphanous presences – the membranes of memory and fragments of history. Architectural writer Eva Menuhin investigates a recent project by the University of Greenwich's Captivate: Spatial Modelling Research Group, whose gossamer‐threaded architectural representations decode time, movements, changes, additions and destructions of a London Garrison church – a poetic, ghostly ballet between time, building and nature.

Comparative evaluation of wavelength-scanning Otto and Kretschmann configurations of SPR biosensors for low analyte concentration measurement

Abstract The growing demand for compound characterization has stimulated research, particularly in surface plasmon resonance technology. This technique monitors changes in the light-reflecting properties of a sample medium in close contact and in interaction with a plasmonic surface (typically a metal such as gold) due to shifts in the fundamental plasmon resonance of the surface. The Otto and Kretschmann configurations are commonly used in this method. When an analyte is expensive, scarce, or hazardous, it is advantageous to reduce the sample required for testing, making optimization of sample use interesting. This challenge requires trade-offs between sensitivity and LoD. This work compares two sensors in the indicated configurations designed for minimal analyte requirement (in this case, Ag nanoparticle suspensions) using the wavelength scanning technique. The results show that the Kretschmann configuration is the most efficient for characterizing nanoparticle suspensions due to its construction characteristics, ease of use, and the characteristics of the obtained response. The final arrangement is a quasi-point sensor that only requires 6μL of analyte and has a sensitivity of 4.17x10−4 RIU/λ (RIU is the refractive index unit). This study contributes to the exploration of advantages and limitations in the design and operation of SPR sensors. The work also underlies the need for future research to enhance the selectivity and versatility of these devices.

Enhancement of Scan Strategy for Improving Surface Characteristics of the SLMed Inconel 718 Alloy Component

The technique of selective laser melting has garnered significant interest due to its capacity to fabricate metal parts of any shape using a single printing process. In this study, a scan strategy was proposed for printing the inner structure part based on the varying performance of the Inconel 718 alloy part produced using different scan techniques. The test findings indicated that the surface quality of the printed material along the scan line exhibited significantly superior performance in comparison to that produced in a vertical direction to the scan line. Regarding the scan strategy, it is evident that the zigzag shape scan strategy exhibited superior performance in terms of the microstructure of the printed part. This is attributed to the more consistent cooling rate on each scan track. On the other hand, the square-framed scan strategy demonstrated a relatively optimal condition for the bending deformation of the printed part compared to other scan strategies. This is due to the more appropriate behavior of the molten pool during the outer edge printing process. After considering all of these criteria, a novel scan approach was created that included various scan strategies. The test findings indicated that the component produced using this novel scanning technique exhibited the combined benefits of both the square-shaped and zigzag-shaped scanning strategies.

Teaching IELTS Reading Skills

This research describes the teaching of IELTS Reading for students. This research is library research. The analysis shows that the IELTS reading test evaluates participants' understanding of information and language, requiring them to synthesize, interpret, and respond to information. The test consists of 14 types of questions, including Choosing a Title, True False Not Given / Yes No Not Given, Matching Features, Matching Headings, Matching Paragraph Information, Matching Sentence Endings, Sentence Completion, List Selection, Multiple Choice, Short Answer, Summary Completion, Flow Chart Completion, Diagram Completion, and Table Completion. The resulting test is graded on a band scale from range from 0 (did not take the test) to 9 (proficient in English) which indicates students' understanding and ability to read in English. Understanding the types of questions on the IELTS is crucial for students to prepare for the test. However, the test requires precise abilities for success. Teachers can create lesson plans for teaching Reading IELTS to help students prepare for the test and prepare them for the test. To answer IELTS Reading questions, students need fast and accurate reading skills and the right strategy. Teaching reading skills for the IELTS test can be challenging, but several strategies can help teachers structure effective teaching. These include understanding the test format, analyzing previous questions, building academic vocabulary, teaching active reading, practicing explaining the main idea, teaching skimming and scanning techniques, managing class discussion and analysis, practicing with varied reading material, using an integrated approach, giving constructive feedback, simulating reading tests, giving homework, training students to compose an outline, and promoting flexibility in learning.

Advancements and Comparative Study of CT scan and MRI Imaging Technique in Biomedical Instrumentation

Advancements and Comparative Study of CT scan and MRI Imaging Technique in Biomedical Instrumentation

Examination of Urban Transformation Implementation Legislation: Elazığ Example

In this study, it was aimed to examine and reveal the general results of the models applied in urban transformation works in Elazığ province after the 6.8 Mw Sivrice earthquake on January 24, 2020. The population of the research, Elazığ province sample, is Karşıyaka, Cumhuriyet, Abdullahpaşa, Mustafapaşa, Rüstempaşa, Sürsürü, Kızılay and Sivrice Country Gölbaşı Neighborhoods. The study is qualitative research in the form of a field study in terms of revealing the results of urban transformation implementation at the sample points. In this context, observation technique, interview technique, and documentary scanning technique were used in the descriptive analysis. General physical-structural characteristics of buildings in the observation technique; in the interview technique, 100 building owners and users' opinions about the buildings; In the documentary scanning technique, the reflections of literature information in practice are interpreted as a whole. In comparing the literature information, project technical documents obtained from the Ministry of Environment, Urbanization and Climate Change and Elazığ Municipality were used. As a result, the model to be chosen in the urban transformation process is an important parameter in the success of the application and reaching the desired goal. More qualified urban transformation applications will be achieved by reducing the problems that arise in public transformation projects, especially in determining the legislation, and by choosing the appropriate model for comprehensive transformation.

Damage evolution in asphalt mixtures based on in-situ CT scanning

A novel approach utilizing in-situ Computed Tomography (CT) scanning and digital image processing techniques was developed to overcome the limitations of traditional CT image analysis in studying microcrack evolution in asphalt mixtures. Two types of graded asphalt mixtures (continuous gradation/AC and intermittent gradation/SMA) were scanned in-situ to capture internal structural changes. Digital image processing distinguished primary voids from cracks and extracted crack evolution. Multivariate regression analysis linked crack parameters to compressive strain. The study found that crack evolution during uniaxial compression in asphalt mixtures can be divided into densification, linear elastic deformation, and nonlinear failure stages. As load increases, the number, volume, and void percentage occupied by cracks rise, peak, and then decrease due to merging and engulfing after the ultimate load. The skeletal structure of cracks was obtained, and a damage evolution equation was established, linking crack parameters to damage evolution. Crack tortuosity was used to characterize the resistance effect of different gradations on crack propagation. This methodology provides new insights and technical support for studying damage evolution and understanding the failure mechanisms of asphalt mixtures.

Hybrid vehicle scanning techniques for detection of damaged hangers in tied-arch railway bridges

Regular monitoring of the hanger system is essential for preserving structural integrity in tied-arch bridges. This proactive monitoring enables preventive maintenance and early detection of hanger damage. To confront this issue, we propose a novel scanning method for assessing the impact of damaged hangers on the dynamic behaviour of single-span tied-arch railway bridges. Using each hanger as a positional reference, this method employs an instrumented vehicle as a mobile scanner to indirectly acquire vibration data from the traversed bridge deck. The hybrid approach integrates vehicle-bridge interaction (VBI) dynamics, vehicle scanning method (VSM), and moving windowed Fourier transform (mw-FT) technique to generate time–frequency spectrograms from the collected signals. In this representation, the time axis indicates the duration of the inspection vehicle traversing the bridge deck. By analysing frequency shifts within the spectrogram, we can identify damaged hangers through observed variations in frequency content over time. Numerical studies demonstrate the efficacy of the proposed hybrid vehicle scanning technique in detecting potential hanger damage in tied-arch railway bridges.

Practical Aspects of Using Modern Laser Scanning Techniques for Measuring Mine Excavations

Abstract For more than a dozen or so years now, there has been growing interest in the use of modern laser scanning measurement methods in numerous mining operations engaged in underground excavation. However, the simple possession of a scanner does not guarantee satisfactory measurement results. This study sets out the results of scanning mine excavations in an active mine and describes the current guidelines on various aspects of the measurement process. These guidelines were developed on the basis of several hundred measurements carried out over the last dozen or so years. This study also outlines the typical measurements errors observed over the course of many years. These errors, resulting partly from hardware limitations and partly from human error when planning or actually performing measurements, were an important factor behind the introduction of standards regulating underground measurements. This study discusses in detail not only scanning that utilises traditional stationary laser scanners but also scanning based on mobile scanners. It also presents possible areas of future technological development in line with global trends.

Single-Shot Direct Transmission Terahertz Imaging Based on Intense Broadband Terahertz Radiation.

There are numerous applications of terahertz (THz) imaging in many fields. However, current THz imaging is generally based on scanning technique due to the limited intensity of the THz sources. Thus, it takes a long time to obtain a frame image of the target and cannot meet the requirement of fast THz imaging. Here, we demonstrate a single-shot direct THz imaging strategy based on a broadband intense THz source with a frequency range of 0.1~23 THz and a THz camera with a frequency response range of 1~7 THz. This THz source was generated from the laser-plasma interaction, with its central frequency at ~12 THz. The frame rate of this imaging system was 8.5 frames per second. The imaging resolution reached 146.2 μm. With this imaging system, a single-shot THz image for a target object with a size of more than 7 cm was routinely obtained, showing a potential application for fast THz imaging. Furthermore, we proposed and tested an image enhancement algorithm based on an improved dark channel prior (DCP) theory and multi-scale retinex (MSR) theory to optimize the image brightness, contrast, entropy and peak signal-to-noise ratio (PSNR).

High‐performance electromagnetic shielding composite materials based on carbon nanotubes and Sandwich laminate structures

AbstractCarbon fiber‐reinforced composite materials exhibit excellent mechanical and electromagnetic shielding capabilities. However, they have some drawbacks, such as high cost and significant reflection losses. In order to address these shortcomings, this study set out to design a sandwich‐structured composite material and produce a composite material designed for electromagnetic shielding using Vacuum Assisted Resin Transfer Molding (VARTM) technology. This composite material promotes the “absorption‐reflection‐reabsorption” process of electromagnetic waves, significantly enhancing its shielding effectiveness, achieving up to 59.4 dB of shielding effect in the 8.2–12.4 GHz (X‐band) range. The study also employed carbon nanotubes (CNTs) matrix doping to modify the composite material, significantly reducing reflection losses. When the amount of carbon nanotubes added reaches 0.6 wt%, the overall SE can be increased by 18%. Additionally, the introduction of CNTs significantly improves the flexural strength and tensile strength of the composite material; at a 0.6 wt% CNT content, the average tensile strength increased from 526.4 to 600.9 MPa, indicating good interfacial interactions between CNTs and epoxy resin. This work provides valuable insights for the preparation of high‐performance electromagnetic shielding materials, with profound theoretical and practical significance.Highlights Observations through SEM and CT scanning techniques reveal that Vacuum Assisted Resin Transfer Molding (VARTM) technology facilitates strong interlayer bonding between carbon fibers, glass fibers, and copper wires, alongside effective epoxy resin adhesion, thus enhancing the mechanical properties. The sandwich structure's impedance mismatch characteristic facilitates an efficient “absorption‐reflection‐reabsorption” process of electromagnetic waves. Additionally, the incorporation of Carbon Nanotubes (CNTs) enhances the absorption mechanism, reducing reflection losses. Incorporating CNTs further boosts both flexural and tensile strengths, attributed to improved interfacial interactions inhibiting crack formation.

Investigation of gas residuals in sandstone formations via X-ray core-flooding experiments: Implication for subsurface hydrogen storage

The production and utilization of hydrogen (H2) as a clean energy source offer a promising solution towards achieving net-zero carbon emissions. Utilizing sandstone formations for geological hydrogen storage presents a viable option for the practical implementation of the hydrogen economy, offering both safe and large-scale containment capabilities. Accurate assessment of gas displacement behavior in porous media plays a critical role in understanding gas saturation, gas residual, and long-term storage duration. However, there are limited studies available on dynamic displacements for hydrogen storage applications. This study aims to enhance the understanding of gas flow behavior in sandstone rocks for different gas types and determine the role of capillary pressure and gas wettability during hydrogen storage. A series of gas core-flooding experiments are performed on a brine-saturated sandstone core sample using three different gases (CO2, CH4, and H2). X-ray scanning technique is applied to detect the gas saturation and gas residual after the core-flooding experiments. The results indicate that the average gas saturation ranges between 25 and 40%, with zero gas residual for all gases, suggesting that the gas residuals in this clean sandstone sample are unaffected by the gas type. Initially, the capillary pressure profile for the sample displayed low brine saturation at 200 psi, indicating very low capillary pressure in the sample due to the high permeability and large pore radius, despite the strong water-wetting behavior of the sample. Moreover, the obtained results indicate the high potential for gas recovery (especially for hydrogen during withdrawal cycles), and the high displacement efficiency in sandstone rocks. The reported low gas residual suggests that the wettability of the rock is not affected by gas injection, and it appears that the wettability and capillary pressure are not the controlling factors for gas storage in this sandstone sample. This observation suggests that the structural trapping mechanism is most likely to be the dominant trapping mechanism in this shallow high permeable sandstone rock. Also, the injection of cushion gases such as CO2 and CH4 indicated similar results to hydrogen injection, due to the low capillary pressure and high permeability in this sandstone sample. The findings of this study can greatly enhance the understanding of gas injection, displacement behavior, and gas residuals in sandstone rocks related to underground hydrogen storage.