Detection Distance Research Articles

A novel voice classification based on Gower distance for Parkinson disease detection

BackgroundTraditional classifier for the classification of diseases, such as K-Nearest Neighbors (KNN), Linear Discriminant Analysis (LDA), Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM), often struggle with high-dimensional medical datasets. ObjectiveThis study presents a novel classifier to overcome the limitations of traditional classifiers in Parkinson’s disease (PD) detection based on Gower distance. MethodsWe present the Gower distance metric to handle diverse feature sets in voice recordings, which acts as a dissimilarity measure for all feature types, making the model adept at identifying subtle patterns indicative of PD. Additionally, the Cuckoo Search algorithm is employed for feature selection, reducing dimensionality by focusing on key features, thereby lessening the computational load associated with high-dimensional datasets. ResultsThe proposed classifier based on Gower distance resulted in an accuracy rate of 98.3% with feature selection and achieved an accuracy of 94.92% without the feature selection method. It outperforms traditional classifiers and recent studies in PD detection from voice recordings. ConclusionsThis accuracy shows the capability of the approach in the correct classification of instances and points out the potential of the approach as a reliable diagnostic tool for the medical practitioner. The findings state that the proposed approach holds promise for improving the diagnosis and monitoring of PD, both within medical institutions and at homes for the elderly.

Object Detection and Monocular Stable Distance Estimation for Road Environments: A Fusion Architecture Using YOLO-RedeCa and Abnormal Jumping Change Filter

Enabling rapid and accurate comprehensive environmental perception for vehicles poses a major challenge. Object detection and monocular distance estimation are the two main technologies, though they are often used separately. Thus, it is necessary to strengthen and optimize the interaction between them. Vehicle motion or object occlusions can cause sudden variations in the positions or sizes of detection boxes within temporal data, leading to fluctuations in distance estimates. So, we propose a method to integrate a detector based on YOLOv5-RedeCa, a Bot-Sort tracker and an anomaly jumping change filter. This combination allows for more accurate detection and tracking of objects. The anomaly jump filter smooths distance variations caused by sudden changes in detection box sizes. Our method increases accuracy while reducing computational demands, showing outstanding performance on several datasets. Notably, on the KITTI dataset, the standard deviation of the continuous ranging results remains consistently low, especially in scenarios with multiple object occlusions or disappearances. These results validate our method’s effectiveness and precision in managing dual tasks.

Ultra-sensitive tactile force/proximity sensor based on monolithically integrated microcantilever

This paper reports a monolithically integrated tactile force and proximity sensor composed of a piezoresistive microcantilever array and a signal processing circuit. Both the microcantilever array and the signal processing circuit were fabricated on a single-crystalline silicon device layer of a silicon-on-insulator (SOI) wafer with a partially depleted (PD) SOI CMOS (complementary metal oxide semiconductor) technology followed by three micromachining processes. A dual-detection sensor of tactile force and proximity was realized by packaging the microcantilever with a polydimethylsiloxane (PDMS) elastomer on a flexible printed circuit board. A force resolution of 68 μN, a force sensitivity of 14.6 mV/N and a minimum detectable displacement of 0.1 μm were obtained in force mode. A minimum detectable distance of 2.5 mm and 2.6 mm were achieved for objects and human proximity detections in photoelectric and thermomechanical modes, respectively. By using the ultra-sensitive force sensor, wrist radial artery pulse, fingertips pulse, breath and throat vibration of human body were collected accurately. These results prove that the integrated microcantilever can achieve both proximity and tactile sensing detections simultaneously with ultra-sensitivity.

Spatial positioning method based on range-only measurement of multi-station radar

Aiming at the characteristics that affect the high ranging accuracy of shipborne radar, a multi station radar spatial positioning method based on ranging is proposed. This method is based on the ECEF (Earth Centered Earth Fixed) coordinate system, and adopts the method of intersecting the detection distances of multiple radars to the target, and directly calculates the spatial position of the target. This method only needs the geodetic coordinates of each radar station and the detection range of the target to calculate the geodetic coordinates of the target, which can effectively solve the coordinate conversion problem caused by the curvature of the earth, and does not involve higher-order equations and multi-value solutions, and it does not involve iterative initial value calculation. The positioning system can not only obtain high positioning accuracy, but also has a long operating distance, which can better solve the multi-radar range measurement intersection positioning problem.

Transformer-based berm detection for automated bulldozer safety in edge dumping

Ensuring the safety of automated bulldozers during edge dumping operations in open-pit mines requires accurate detection of the berm's edge. However, precisely detecting berm edges in open-pit mining scenes is challenging due to the presence of similar texture structures. To address this issue, this paper created a dataset for berm edge detection that covers multiple scenes and proposed the edge detection model with transformer (MEDTER). This model, based on a transformer with a two-stage detection structure, aims to restore thin edges. Additionally, the deep multilevel aggregation decoder enhances the information flow in the transformer to improve the sensitivity to detailed information. The BCE-Dice loss functions effectively handle the problem of pixel imbalance. Results demonstrate that the proposed model achieves significant improvements compared to others. Furthermore, the model exhibits excellent detection performance despite variations in scenes and detection distances, suggesting its practical value in ensuring the safety of automated bulldozers during edge dumping.

An optimized observation system and inversion method for fault detection based on surface-wave while tunneling

Understanding geological structures ahead of the tunnel face is important for safe and efficient construction of the urban tunnel. The surface-wave while tunneling (SWT) method, using drilling noise by shield machine as source, is expected to dynamically predict the adverse geologies in front of the tunnel face. Observation system and inversion method are keys for SWT. To improve the imaging accuracy of the geological conditions, it is urgent to optimize the observation system for data acquisition and inversion method for velocity inversion, especially for the utilization of multi-modes surface-waves. For observation system, several key parameters (minimum source-geophone distance, length and interval of survey line) are optimized to obtain sufficient information of dispersion curves. Then observation systems for source at different depth were optimized, supporting for geological detection using surface-waves generated by underground drilling noise. For velocity imaging, numerical simulations are studied to reveal the applicability of typical inversion methods for multi-modes of surface wave, and particle swarm optimization (PSO) algorithm is optimized for velocity inversion due to its advantages of stable calculation and good accuracy. On this basis, SWT was optimized both in data acquisition and velocity inversion for better understanding geological condition both in buried depth and detection distance. Then the improved method was applied in the Jinan tunnel and successfully detected a fault, providing geological information for construction safety and verifying the feasibility.

Simulation and analysis of the CO2 range-resolved differential absorption lidar system at 2 μm

The range-resolved differential absorption lidar is a high-precision device to measure the concentration of carbon dioxide. This paper provides a system-wide theoretical analysis method for the performance analysis and parameter optimization of the lidar system using the given parameter range. The scattered echo signal, signal-to-noise ratio, and detection sensitivity were simulated by setting assumed parameters with the HITRAN 2020 database and the US 1976 standard atmosphere model to analyze the detection distance and concentration resolution of the lidar system. The effects of the laser energy, repetition frequency, and photodetector noise were also discussed. The wavelength selection near the absorption line is critical because it controls the height region of the highest sensitivity and the demands on frequency stability. Recommendations for the selection of absorption lines are provided in this paper. A quantitative analysis of each error source provided reasonable error ranges.

The gravitational-wave emission from the explosion of a 15 solar mass star with rotation and magnetic fields

ABSTRACT Gravitational waveform predictions from 3D simulations of explosions of non-rotating massive stars with no magnetic fields have been extensively studied. However, the impact of magnetic fields and rotation on the core-collapse supernova gravitational-wave signal is not well understood beyond the core-bounce phase. Therefore, we perform four magnetohydrodynamical simulations of the explosion of a $15\, {\rm M}_{\odot }$ star with the SFHx and SFHo equations of state. All of the models start with a weak magnetic field strength of $10^{8}$ G, and two of the models are rapidly rotating. We discuss the impact of the rotation and magnetic fields on the gravitational-wave signals. We find that the weak pre-collapse fields do not have a significant impact on the gravitational-wave signal amplitude. With rapid rotation, the f/g-mode trajectory can change in shape, and the dominant emission band becomes broader. We include the low-frequency memory component of the gravitational-wave signal from both matter motions and neutrino emission anisotropy. We show that including the gravitational waves from anisotropic neutrino emission increases the supernova gravitational-wave detection distances for the Einstein Telescope. The gravitational waves from anisotropic neutrino emission would also be detectable out to Mpc distances by a moon-based gravitational-wave detector.

W-band photonics-aided OFDM system integrating sensing and communication with phase noise suppression scheme

Photonic-aided technology offers many advantages in millimeter-wave (MMW) communication and sensing, such as low equipment cost and wide bandwidth. The combination of photonics-aided systems with orthogonal frequency division multiplexing (OFDM) waveforms enables high-performance integration of sensing and communication. In this paper, we propose and experimentally demonstrate a W-band photonic-aided OFDM system integrating sensing and communication (ISAC). To address the destruction of signal coherence by phase noise of the system, this paper proposes an OFDM sensing scheme combined with frequency-domain filtering to reduce the sidelobe interference caused by phase noise. Combined with offline digital signal processing algorithms, the system achieves high-precision ranging-Doppler imaging with a ranging resolution of 0.96 cm at a detection distance of 2 m. In terms of communication, after 10 m of wireless transmission, the net rate reaches 47.06 Gbit/s. The proposed system makes full use of the system's resources by using OFDM signals as both the sensing and communication signals. This may be beneficial for some potential applications of 6G in the future.

Feature Extraction Methods for Underwater Acoustic Target Recognition of Divers.

The extraction of typical features of underwater target signals and excellent recognition algorithms are the keys to achieving underwater acoustic target recognition of divers. This paper proposes a feature extraction method for diver signals: frequency-domain multi-sub-band energy (FMSE), aiming to achieve accurate recognition of diver underwater acoustic targets by passive sonar. The impact of the presence or absence of targets, different numbers of targets, different signal-to-noise ratios, and different detection distances on this method was studied based on experimental data under different conditions, such as water pools and lakes. It was found that the FMSE method has the best robustness and performance compared with two other signal feature extraction methods: mel frequency cepstral coefficient filtering and gammatone frequency cepstral coefficient filtering. Combined with the commonly used recognition algorithm of support vector machines, the FMSE method can achieve a comprehensive recognition accuracy of over 94% for frogman underwater acoustic targets. This indicates that the FMSE method is suitable for underwater acoustic recognition of diver targets.

A novel real-time eye detection method using edge detection and Euclidean distance

A novel real-time eye detection method using edge detection and Euclidean distance

Sexually dimorphic eye size in dragonfishes, a response to a bioluminescent signalling gap.

Deep-sea fishes must overcome extremely large nearest-neighbour distances and darkness to find mates. Sexual dimorphism in the size of luminescent structures in many deep-sea taxa, including dragonfishes (family Stomiidae), indicates reproductive behaviours may be mediated by visual signalling. This presents a paradox: if male photophores are larger, females may find males at shorter distances than males find females. Solutions to this gap may include females closing this gap or by males gathering more photons with a larger eye. We examine the eye size of two species of dragonfishes (Malacosteus niger and Phostomias guernei) for sexual dimorphism and employ a model of detection distance to evaluate the potential for such dimorphism to bridge the detection gap. This model incorporates the flux of sexually dimorphic postorbital photophores and eye lens size to predict detection distances. In both species, we found a significant visual detection gap in which females find males before males find females and that male lens size is larger, marking the second known case of size dimorphism in the actinopterygian visual system. Our results indicate the larger eye affords males a significant improvement in detection distance. We conclude that this dimorphic phenotype may have evolved to close the detection gap.

Structural Design and Parameter Optimization of Magnetic Gradient Tensor Measurement System.

Magnetic anomaly detection (MAD) technology based on the magnetic gradient tensor (MGT) has broad application prospects in fields such as unexploded ordnance detection and mineral exploration. The difference approximation method currently employed in the MGT measurement system introduces measurement errors. Designing reasonable geometric structures and configuring optimal structural parameters can effectively reduce measurement errors. Based on research into differential MGT measurement, this paper proposes three simplified planar MGT measurement structures and provides the differential measurement matrix. The factors that affect the design of the baseline distance of the MGT measurement system are also theoretically analyzed. Then, using the magnetic dipole model, the error analysis of the MGT measurement structures is carried out. The results demonstrate that the planar cross-shaped structure is optimal, with the smallest measurement error, only 3.15 × 10-10 T/m. Furthermore, employing the control variable method, the impact of sensor resolution constraints, noise level, target magnetic moment, and detection distance on the design of the optimal baseline distance of the MGT measurement system is simulated and verified. The results indicate that the smaller the target magnetic moment, the farther the detection distance, the lower the magnetometer resolution, the greater the noise, and the greater the baseline distance required. These conclusions provide reference and guidance for the construction of the MGT measurement system based on triaxial magnetometers.

Determinants of Maximum Magnetic Anomaly Detection Distance.

The maximum detection distance is usually the primary concern of magnetic anomaly detection (MAD). Intuition tells us that larger object size, stronger magnetization and finer measurement resolution guarantee a further detectable distance. However, the quantitative relationship between detection distance and the above determinants is seldom studied. In this work, unmanned aerial vehicle-based MAD field experiments are conducted on cargo vessels and NdFeB magnets as typical magnetic objects to give a set of visualized magnetic field flux density images. Isometric finite element models are established, calibrated and analyzed according to the experiment configuration. A maximum detectable distance map as a function of target size and measurement resolution is then obtained from parametric sweeping on an experimentally calibrated finite element analysis model. We find that the logarithm of detectable distance is positively proportional to the logarithm of object size while negatively proportional to the logarithm of resolution, within the ranges of 1 m~500 m and 1 pT~1 μT, respectively. A three-parameter empirical formula (namely distance-size-resolution logarithmic relationship) is firstly developed to determine the most economic sensor configuration for a given detection task, to estimate the maximum detection distance for a given magnetic sensor and object, or to evaluate minimum detectable object size at a given magnetic anomaly detection scenario.

Inversion of extinction coefficient for scattering media based on range-gated detection.

The extinction coefficient is an important parameter for describing light transmitting properties in the scattering medium. However, the single-point detection way and the large inversion error of the existing techniques cannot satisfy the need for spatial analysis and data application. A novel approach for inversion of extinction coefficient based on range-gated detection utilizing backward scattering of medium is proposed, and an inversion algorithm for extinction coefficient is established utilizing the backscattering signal of multiple adjacent spatial slices of the medium. The method can simultaneously invert transverse multiple-points extinction coefficient and longitudinal profile of extinction coefficient. Further, experiments are conducted in the scattering medium including fog and smoke based on the fabricated range-gated extinction-coefficient detection and inversion system, and the results demonstrate that inversion with the error less than 5% can be achieved at different detection distances, different concentrations and different kinds of scattering mediums. This approach offers a convenient, rapid and accurate means to acquire extinction coefficients, laying the foundation for the development of efficient environmental monitoring and high-quality defogging imaging.

A novel method for calculating broadband electrical performance of high-speed aircraft radome under thermo-mechanical-electrical coupling

The electrical performance of radomes on high-speed aircraft can be influenced by the thermal and mechanical loads produced during high-speed flight, which can affect the detection distance and accuracy of the guidance system. This paper presents a new method that uses the Finite Difference Time Domain (FDTD) method to calculate the electrical performance of radomes under Thermo-Mechanical-Electrical (TME) coupling. This method can accurately characterize the effects of material dielectric temperature drift and structural deformation on the electrical performance of the radome under flight conditions, enabling high-precision full-wave calculations of the broadband electrical performance of the radome. The method initiates by utilizing a Finite Element Grid Model (FE-GM) of the radome to sequentially acquire the radome’s response temperature field and structural deformation field through thermal and mechanical simulations. Subsequently, spatial mapping techniques are developed to accurately incorporate the dielectric temperature drift and structural deformation of the radome into its Yee grid Electromagnetic (EM) simulation model. A verification case was designed to test the proposed method, and the results confirmed its high computational accuracy. Additionally, the effectiveness and necessity of the method were further demonstrated by analyzing the electrical performance of a fused silica ceramic radome used on a high-speed aircraft.

Analysis of Constraints on the Remote Application of Inverse Synthetic Aperture Laser Radar.

In order to achieve the remote application of inverse synthetic aperture laser radar for high resolution spatial situational awareness, it is essential to analyze the main factors that restrict its remote application. This study combines the range equation of inverse synthetic aperture lidar with the stimulated Brillouin threshold power equation to investigate the variation of laser transmitting power with distance. Additionally, by utilizing the excited Brillouin threshold power equation, laser linewidth formula, and pulse width characteristics of pulse signal, we examine the variation law of laser coherence that meets corresponding power requirements at different distances. The results indicate that a detection distance of 22 km and below can be achieved using continuous fiber lasers without compensation. Coherence compensation is necessary for distances between 22 km and 57 km. For distances ranging from 57 km to 3000 km, pulsed solid-state lasers are used to analyze coherence and conclude that imaging non-cooperative targets within this range is feasible. It is observed that coherence compensation is required from 57 km to 2179 km, becoming more challenging after 2000 km. Furthermore, pulsed solid-state lasers can still be utilized for imaging cooperative targets within a range of 2179-3273 km; however, coherence compensation remains necessary and becomes increasingly difficult. Finally, several coherent length compensation schemes are proposed in order to extend the imaging range of inverse synthetic aperture LiDAR to approximately 3000 km.

Light and Displacement Compensation-Based iPPG for Heart-Rate Measurement in Complex Detection Conditions.

A light and displacement-compensation-based iPPG algorithm is proposed in this paper for heart-rate measurement in complex detection conditions. Two compensation sub-algorithms, including light compensation and displacement compensation, are designed and integrated into the iPPG algorithm for more accurate heart-rate measurement. In the light-compensation sub-algorithm, the measurement deviation caused by the ambient light change is compensated by the mean filter-based light adjustment strategy. In the displacement-compensation sub-algorithm, the measurement deviation caused by the subject motion is compensated by the optical flow-based displacement calculation strategy. A series of heart-rate measurement experiments are conducted to verify the effectiveness of the proposed method. Compared with conventional iPPG, the average measurement accuracy increases by 3.8% under different detection distances and 5.0% under different light intensities.

128-channel optical phased array with large field of view and low main-lobe attenuation

In this paper, a 128-channel non-uniform optical phased array is proposed. The antenna is based on a silicon nitride waveguide with a large cross-sectional area (3 μm × 1.2 μm) and a silicon nitride grating with a small diffraction window (grating width of 200 nm), enabling high optical power transmission and a wide 1 dB field of view. As a result, the designed sparse optical phased array achieves less than 1 dB of main lobe attenuation over a 94° field of view. Within this field of view, the main lobe will not fall below 80% of the maximum main lobe. This allows the minimum detection distance to still be about 89% of the maximum detection distance without increasing the input power. In this field of view, the maximum side-lobe suppression of the designed sparse optical phased array is 13.4 dB, and the minimum side-lobe suppression is higher than 11.9 dB. This is useful for simultaneously achieving a large field of view, low main lobe attenuation, stable side-lobe suppression, and long detection distance.

The configuration and detection characteristics of a 3D holographic LWD instrument antenna system based on multi-component EM induction theory

In order to improve the precision of electromagnetic resistivity logging, while ensuring the reliability of boundary detection and anisotropy identification, this study starts from the theory of multi-component electromagnetic induction. Through deriving the formula of component responses, the analytical expressions of electromagnetic wave fields are obtained for various coil pairs of azimuthal instruments. A 3D holographic LWD instrument antenna configuration is constructed, with co-planar and non-coplanar, tilted and orthogonal coil combinations, all components of the magnetic field tensor Hxx,Hxy,Hxz,Hyx,Hyy,Hyz,Hzx,Hzx,HzzHxx,Hxy,Hxz,Hyx,Hyy,Hyz,Hzx,Hzx,Hzz are successfully resolved. With the combination of some or all components, functional signals are generated for specific detection objectives. Numerical simulation of the response of those signals shows that the distance of boundary detection and anisotropy identification capability are superior to traditional geo-signals. The response relationship shows that as the contrast of the formation resistivity decreases and the well deviation angle increases, the anisotropy identification capability gradually strengthens, and the signal strength and identification capability are better at frequency in the range of 400–600 kHz. The proposed antenna configuration has the potential to significantly enhance formation evaluation and to improve geo-steering capability, contributing technology-wise to the optimal landing trajectory and best wellbore position, resulting in cost saving and maximize oil & gas production.