Correlation between the rock mass properties and maximum horizontal stress:A case study of overcoring stress measurements

Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.

Automatic Identification of Clear-Air Echoes Based on Millimeter-wave Cloud Radar Measurements

Millimeter-wave cloud radar(MMCR)provides the capability of detecting the features of micro particles inside clouds and describing the internal microphysical structure of the clouds.Therefore,MMCR has been widely applied in cloud observations.However,due to the influence of non-meteorological factors such as insects,the cloud observations are often contaminated by non-meteorological echoes in the clear air,known as clear-air echoes.It is of great significance to automatically identify the clear-air echoes in order to extract effective meteorological information from the complex weather background.The characteristics of clear-air echoes are studied here by combining data from four devices:an MMCR,a laser-ceilometer,an L-band radiosonde,and an all-sky camera.In addition,a new algorithm,which includes feature extraction,feature selection,and classification,is proposed to achieve the automatic identification of clear-air echoes.The results show that the recognition algorithm is fairly satisfied in both simple and complex weather conditions.The recognition accuracy can reach up to 95.86%for the simple cases when cloud echoes and clear-air echoes are separate,and 88.38%for the complicated cases when low cloud echoes and clear-air echoes are mixed.

A Novel Millimeter-Wave Channel Measurement Platform for 6G Intelligent Railway Scenarios

This paper presented a novel millimeterwave channel measurement platform for the 6G intelligent railway.This platform used phased array antenna with 64 elements and can support instant bandwidth up to 1 GHz.Combined with improved multi-tone sounding signals,the platform can enhance dynamic measurement capability in high-speed railway scenarios.We performed calibration works about frequency flatness,frequency offset and proved platform reliability with channel emulator based closed-loop verification.We also carried out field trials in high-speed railway carriage scenarios.Based on measurement results,we extracted channel characteristic parameters of path loss,power delay profile and delay spread to further verify the field measurement performance of the platform.

Co-Sharing Waveform Design for Millimeter-Wave Radar Communication Systems

Millimeter-wave(mmWave)radar communication has emerged as an important technique for future wireless systems.However,the interference between the radar signal and communication data is the main issue that should be considered for the joint radar communication system.In this paper,a co-sharing waveform(CSW)is proposed to achieve communication and radar sensing simultaneously.To eliminate the co-interference between the communication and sensing signal,signal splitting and processing methods for communication data demodulation and radar signal processing are given respectively.Simulation results show that the bit error rate(BER)of CSW is close to that of the pure communication waveform.Moreover,the proposed CSW can achieve better performance than the existing waveforms in terms of range and velocity estimation.

A New Device for Gas-Liquid Flow Measurements Relying on Forced Annular Flow

A new measurement device,consisting of swirling blades and capsule-shaped throttling elements,is proposed in this study to eliminate typical measurement errors caused by complex flow patterns in gas-liquid flow.The swirling blades are used to transform the complex flow pattern into a forced annular flow.Drawing on the research of existing blockage flow meters and also exploiting the single-phase flow measurement theory,a formula is introduced to measure the phase-separated flow of gas and liquid.The formula requires the pressure ratio,Lockhart-Martinelli number(L-M number),and the gas phase Froude number.The unknown parameters appearing in the formula are fitted through numerical simulation using computational fluid dynamics(CFD),which involves a comprehensive analysis of the flow field inside the device from multiple perspectives,and takes into account the influence of pressure fluctuations.Finally,the measurement model is validated through an experimental error analysis.The results demonstrate that the measurement error can be maintained within±8%for various flow patterns,including stratified flow,bubble flow,and wave flow.

Optimization and Performance Enhancement of Gesture Recognition Algorithm Based on FMCW Millimeter-Wave Radar

Gesture recognition plays an increasingly important role as the requirements of intelligent systems for human-computer interaction methods increase.To improve the accuracy of the millimeter-wave radar gesture detection algorithm with limited computational resources,this study improves the detection performance in terms of optimized features and interference filtering.The accuracy of the algorithm is improved by refining the combination of gesture features using a self-constructed dataset,and biometric filtering is introduced to reduce the interference of inanimate object motion.Finally,experiments demonstrate the effectiveness of the proposed algorithm in both mitigating interference from inanimate objects and accurately recognizing gestures.Results show a notable 93.29%average reduction in false detections achieved through the integration of biometric filtering into the algorithm’s interpretation of target movements.Additionally,the algorithm adeptly identifies the six gestures with an average accuracy of 96.84%on embedded systems.

Multiscale Feature Fusion for Gesture Recognition Using Commodity Millimeter-Wave Radar

Gestures are one of the most natural and intuitive approach for human-computer interaction.Compared with traditional camera-based or wearable sensors-based solutions,gesture recognition using the millimeter wave radar has attracted growing attention for its characteristics of contact-free,privacy-preserving and less environmentdependence.Although there have been many recent studies on hand gesture recognition,the existing hand gesture recognition methods still have recognition accuracy and generalization ability shortcomings in shortrange applications.In this paper,we present a hand gesture recognition method named multiscale feature fusion(MSFF)to accurately identify micro hand gestures.In MSFF,not only the overall action recognition of the palm but also the subtle movements of the fingers are taken into account.Specifically,we adopt hand gesture multiangle Doppler-time and gesture trajectory range-angle map multi-feature fusion to comprehensively extract hand gesture features and fuse high-level deep neural networks to make it pay more attention to subtle finger movements.We evaluate the proposed method using data collected from 10 users and our proposed solution achieves an average recognition accuracy of 99.7%.Extensive experiments on a public mmWave gesture dataset demonstrate the superior effectiveness of the proposed system.

A Single-Board Integrated Millimeter-Wave Asymmetric Full-Digital Beamforming Array for B5G/6G Applications

In this article,a single-board integrated millimeter-wave(mm-Wave)asymmetric full-digital beamforming(AFDBF)array is developed for beyond-fifth-generation(B5G)and sixth-generation(6G)communications.The proposed integrated array effectively addresses the challenge of arranging a large number of ports in a full-digital array by designing vertical connections in a three-dimensional space and successfully integrating full-digital transmitting(Tx)and receiving(Rx)arrays independently in a single board.Unlike the traditional symmetric array,the proposed asymmetric array is composed of an 8×8 Tx array arranged in a square shape and an 8+8 Rx array arranged in an L shape.The center-to-center distance between two adjacent elements is 0.54k0 for both the Tx and Rx arrays,where k0 is the free-space wavelength at 27 GHz.The proposed AFDBF array possesses a more compact structure and lower system hardware cost and power consumption compared with conventional brick-type full-digital arrays.In addition,the energy efficiency of the proposed AFDBF array outperforms that of a hybrid beamforming array.The measurement results indicate that the operating frequency band of the proposed array is 24.25–29.50 GHz.An eight-element linear array within the Tx array can achieve a scanning angle ranging from-47°to+47°in both the azimuth and the elevation planes,and the measured scanning range of each eight-element Rx array is–45°to+45°.The measured maximum effective isotropic radiated power(EIRP)of the eight-element Tx array is 43.2 dBm at 28.0 GHz(considering the saturation point).Furthermore,the measured error vector magnitude(EVM)is less than 3%when 64-quadrature amplitude modulation(QAM)waveforms are used.

A seismic elastic moduli module for the measurements of low-frequency wave dispersion and attenuation of fluid-saturated rocks under different pressures

Knowledge about the seismic elastic modulus dispersion,and associated attenuation,in fluid-saturated rocks is essential for better interpretation of seismic observations taken as part of hydrocarbon identification and time-lapse seismic surveillance of both conventional and unconventional reservoir and overburden performances.A Seismic Elastic Moduli Module has been developed,based on the forced-oscillations method,to experimentally investigate the frequency dependence of Young's modulus and Poisson's ratio,as well as the inferred attenuation,of cylindrical samples under different confining pressure conditions.Calibration with three standard samples showed that the measured elastic moduli were consistent with the published data,indicating that the new apparatus can operate reliably over a wide frequency range of f∈[1-2000,10^(6)]Hz.The Young's modulus and Poisson's ratio of the shale and the tight sandstone samples were measured under axial stress oscillations to assess the frequency-and pressure-dependent effects.Under dry condition,both samples appear to be nearly frequency independent,with weak pressure dependence for the shale and significant pressure dependence for the sandstone.In particular,it was found that the tight sandstone with complex pore microstructure exhibited apparent dispersion and attenuation under brine or glycerin saturation conditions,the levels of which were strongly influenced by the increased effective pressure.In addition,the measured Young's moduli results were compared with the theoretical predictions from a scaled poroelastic model with a reasonably good agreement,revealing that the combined fluid flow mechanisms at both mesoscopic and microscopic scales possibly responsible for the measured dispersion.

Quantum block coherence with respect to projective measurements

Quantum coherence serves as a defining characteristic of quantum mechanics,finding extensive applications in quantum computing and quantum communication processing.This study explores quantum block coherence in the context of projective measurements,focusing on the quantification of such coherence.Firstly,we define the correlation function between the two general projective measurements P and Q,and analyze the connection between sets of block incoherent states related to two compatible projective measurements P and Q.Secondly,we discuss the measure of quantum block coherence with respect to projective measurements.Based on a given measure of quantum block coherence,we characterize the existence of maximal block coherent states through projective measurements.This research integrates the compatibility of projective measurements with the framework of quantum block coherence,contributing to the advancement of block coherence measurement theory.

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

Non-Kramers doublet ground state in a quaternary cubic compound PrRu_(2)In_(2)Zn_(18) investigated by ultrasonic measurements

We performed ultrasonic measurements on a quaternary cubic compound PrRu_(2)In_(2)Zn_(18) to explore the ground state properties derived from non-Kramers Γ_(3) doublet of Pr^(3+).PrRu_(2)In_(2)Zn_(18) is a quaternary derivative of the ternary compound PrRu_(2)Zn_(20) that exhibits a structural phase transition at T_S=138 K.In PrRu_(2)In_(2)Zn_(18),the Zn atoms at the 16c site in PrRu_(2)Zn_(20) are selectively replaced by In atoms.A monotonic increase was observed in the temperature dependence of elastic constants C_L=(C_(11)+2C_(12)+4C_(44))/3 and C_(T)=(C_(11)-C_(12)+C_(44))/3 in the temperature range around T_(S) to which an elastic softening was observed in(C_(11)-C_(12))/2 for PrRu_(2)Zn_(20).The disappearance of the softening indicates that the structural transition in PrRu_(2)Zn_(20) is suppressed by the substitution of Zn ions by In ones with a larger ionic radius.Alternatively,the C_(T) of PrRu_(2)In_(2)Zn_(18) exhibits a precursor Curie-type elastic softening toward low temperatures being responsible for the non-Kramers Γ_(3) ground state.We discuss the ground state and the evolution of the elastic properties of the different single-crystal samples of PrRu_(2)In_(2)Zn_(18) grown under different conditions.

Inter-comparison of field snow measurements using different instruments in Türkiye

Snow is important in Türkiye especially in the mountainous eastern areas where it may stay on the ground for more than half of the year.This region plays a vital role in feeding the water resources of the trans-boundary Euphrates-Tigris Basin,supporting crucial dams for water supply,irrigation and energy production.Thus,easy,frequent,correct and economical ways of measuring the snowpack is crucial.The snow properties at specific locations in the mountainous eastern regions over the two snow seasons(2018 and 2019)were studied by using different instruments and techniques,snow pit(box/cylinder/wedge cutter types),snow tube(Federal Sampler)and SnoTel(Snowpack Analyzer).The results point out a 1.7%-7.1%variation between different cutter type snow density measurements within snow pit analysis and the long-term utilized snow tube observations show a closer relation to box/cylinder type cutters.As for the continuous SnoTel observations,a variation of 2.4%-9.8%with various cutter types and a 5.9%difference regarding the snow tube density results are detected.These findings indicate a close range among different instruments,but it is the best when all three systems complement each other to characterize the snowpack effectively in the complex terrain since each has its own advantages.

Investigations of the mechanical response of dummy HTPB propellant grain under ultrahigh acceleration overload conditions using onboard flight-test measurements

In this paper,to study the mechanical responses of a solid propellant subjected to ultrahigh acceleration overload during the gun-launch process,specifically designed projectile flight tests with an onboard measurement system were performed.Two projectiles containing dummy HTPB propellant grains were successfully recovered after the flight tests with an ultrahigh acceleration overload value of 8100 g.The onboard-measured time-resolved axial displacement,contact stress and overload values were successfully obtained and analysed.Uniaxial compression tests of the dummy HTPB propellant used in the gunlaunched tests were carried out at low and intermediate strain rates to characterize the propellant's dynamic properties.A linear viscoelastic constitutive model was employed and applied in finite-element simulations of the projectile-launching process.During the launch process,the dummy propellant grain exhibited large deformation due to the high acceleration overload,possibly leading to friction between the motor case and propellant grain.The calculated contact stress showed good agreement with the experimental results,though discrepancies in the overall displacement of the dummy propellant grain were observed.The dynamic mechanical response process of the dummy propellant grain was analysed in detail.The results can be used to estimate the structural integrity of the analysed dummy propellant grain during the gun-launch process.

Data-model coupling driven stress field measurements

This paper presents a method for measuring stress fields within the framework of coupled data models,aimed at determining stress fields in isotropic material structures exhibiting localized deterioration behavior without relying on constitutive equations in the deteriorated region.This approach contributes to advancing the field of intrinsic equation-free mechanics.The methodology combines measured strain fields with data-model coupling driven algorithms.The gradient and Canny operators are utilized to process the strain field data,enabling the determination of the deterioration region's location.Meanwhile,an adaptive model building method is proposed for constructing coupling driven models.To address the issue of unknown datasets during computation,a dataset updating strategy based on a differential evolutionary algorithm is introduced.The resulting optimal dataset is then used to generate stress field results.Validation against finite element method calculations demonstrates the accuracy of the proposed method in obtaining full-field stresses in specimens with local degradation behavior.

Protected simultaneous quantum remote state preparation scheme by weak and reversal measurements in noisy environments

We discuss a quantum remote state preparation protocol by which two parties, Alice and Candy, prepare a single-qubit and a two-qubit state, respectively, at the site of the receiver Bob. The single-qubit state is known to Alice while the two-qubit state which is a non-maximally entangled Bell state is known to Candy. The three parties are connected through a single entangled state which acts as a quantum channel. We first describe the protocol in the ideal case when the entangled channel under use is in a pure state. After that, we consider the effect of amplitude damping(AD) noise on the quantum channel and describe the protocol executed through the noisy channel. The decrement of the fidelity is shown to occur with the increment in the noise parameter. This is shown by numerical computation in specific examples of the states to be created. Finally, we show that it is possible to maintain the label of fidelity to some extent and hence to decrease the effect of noise by the application of weak and reversal measurements. We also present a scheme for the generation of the five-qubit entangled resource which we require as a quantum channel. The generation scheme is run on the IBMQ platform.

Application of Quantum Sensing Technology in Power System Measurements

The accuracy of power system measurements directly affects the safe and stable operation of power grids. This study explores the application prospects of quantum sensing technology in power system measurements. The research first analyzes the limitations of traditional measurement techniques, such as electromagnetic interference sensitivity and measurement accuracy bottlenecks. It then introduces the basic principles of quantum sensing, including concepts like quantum entanglement and superposition states. Through theoretical analysis and numerical simulations, the study assesses the potential advantages of quantum sensors in current, voltage, and magnetic field measurements. Results show that quantum magnetometers offer significant improvements in accuracy and interference resistance for current measurements. The study also discusses the application of quantum optical technology in high-voltage measurements, demonstrating its unique advantages in improving measurement dynamic range. However, quantum sensing technology still faces challenges in practical applications, such as technological maturity and cost. To address these issues, the research proposes a phased implementation strategy and industry-academia collaboration model. Finally, the study envisions future directions combining quantum sensing with artificial intelligence. This research provides a theoretical foundation for innovative upgrades in power system measurement technology.

Direct Pointwise Comparison of FE Predictions to StereoDIC Measurements:Developments and Validation Using Double Edge-Notched Tensile Specimen

To compare finite element analysis(FEA)predictions and stereovision digital image correlation(StereoDIC)strain measurements at the same spatial positions throughout a region of interest,a field comparison procedure is developed.The procedure includes(a)conversion of the finite element data into a triangular mesh,(b)selection of a common coordinate system,(c)determination of the rigid body transformation to place both measurements and FEA data in the same system and(d)interpolation of the FEA nodal information to the same spatial locations as the StereoDIC measurements using barycentric coordinates.For an aluminum Al-6061 double edge notched tensile specimen,FEA results are obtained using both the von Mises isotropic yield criterion and Hill’s quadratic anisotropic yield criterion,with the unknown Hill model parameters determined using full-field specimen strain measurements for the nominally plane stress specimen.Using Hill’s quadratic anisotropic yield criterion,the point-by-point comparison of experimentally based full-field strains and stresses to finite element predictions are shown to be in excellent agreement,confirming the effectiveness of the field comparison process.

HIPPO artificial intelligence:Correlating automated radiographic femoroacetabular measurements with patient-reported outcomes in developmental hip dysplasia

BACKGROUND Hip dysplasia(HD)is characterized by insufficient acetabular coverage of the femoral head,leading to a predisposition for osteoarthritis.While radiographic measurements such as the lateral center edge angle(LCEA)and Tönnis angle are essential in evaluating HD severity,patient-reported outcome measures(PROMs)offer insights into the subjective health impact on patients.AIM To investigate the correlations between machine-learning automated and manual radiographic measurements of HD and PROMs with the hypothesis that artificial intelligence(AI)-generated HD measurements indicating less severe dysplasia correlate with better PROMs.METHODS Retrospective study evaluating 256 hips from 130 HD patients from a hip preservation clinic database.Manual and AI-derived radiographic measurements were collected and PROMs such as the Harris hip score(HHS),international hip outcome tool(iHOT-12),short form(SF)12(SF-12),and Visual Analogue Scale of the European Quality of Life Group survey were correlated using Spearman's rank-order correlation.RESULTS The median patient age was 28.6 years(range 15.7-62.3 years)with 82.3%of patients being women and 17.7%being men.The median interpretation time for manual readers and AI ranged between 4-12 minutes per patient and 31 seconds,respectively.Manual measurements exhibited weak correlations with HHS,including LCEA(r=0.18)and Tönnis angle(r=-0.24).AI-derived metrics showed similar weak correlations,with the most significant being Caput-Collum-Diaphyseal(CCD)with iHOT-12 at r=-0.25(P=0.042)and CCD with SF-12 at r=0.25(P=0.048).Other measured correlations were not significant(P>0.05).CONCLUSION This study suggests AI can aid in HD assessment,but weak PROM correlations highlight their continued importance in predicting subjective health and outcomes,complementing AI-derived measurements in HD management.

A Synergistic Multi-Attribute Decision-Making Method for Educational Institutions Evaluation Using Similarity Measures of Possibility Pythagorean Fuzzy Hypersoft Sets

Due to the numerous variables to take into account as well as the inherent ambiguity and uncertainty,evaluating educational institutions can be difficult.The concept of a possibility Pythagorean fuzzy hypersoft set(pPyFHSS)is more flexible in this regard than other theoretical fuzzy set-like models,even though some attempts have been made in the literature to address such uncertainties.This study investigates the elementary notions of pPyFHSS including its set-theoretic operations union,intersection,complement,OR-and AND-operations.Some results related to these operations are also modified for pPyFHSS.Additionally,the similarity measures between pPyFHSSs are formulated with the assistance of numerical examples and results.Lastly,an intelligent decision-assisted mechanism is developed with the proposal of a robust algorithm based on similarity measures for solving multi-attribute decision-making(MADM)problems.A case study that helps the decision-makers assess the best educational institution is discussed to validate the suggested system.The algorithmic results are compared with the most pertinent model to evaluate the adaptability of pPyFHSS,as it generalizes the classical possibility fuzzy set-like theoretical models.Similarly,while considering significant evaluating factors,the flexibility of pPyFHSS is observed through structural comparison.