Sphere Detection Research Articles

AQSA-Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices.

Sphere formation assay is an accepted cancer stem cell (CSC) enrichment method. CSCs play a crucial role in chemoresistance and cancer recurrence. Therefore, CSC growth is studied in plates and microdevices to develop prediction chemotherapy assays in cancer. As counting spheres cultured in devices is laborious, time-consuming, and operator-dependent, a computational program called the Automatic Quantification of Spheres Algorithm (ASQA) that detects, identifies, counts, and measures spheres automatically was developed. The algorithm and manual counts were compared, and there was no statistically significant difference (p = 0.167). The performance of the AQSA is better when the input image has a uniform background, whereas, with a nonuniform background, artifacts can be interpreted as spheres according to image characteristics. The areas of spheres derived from LN229 cells and CSCs from primary cultures were measured. For images with one sphere, area measurements obtained with the AQSA and SpheroidJ were compared, and there was no statistically significant difference between them (p = 0.173). Notably, the AQSA detects more than one sphere, compared to other approaches available in the literature, and computes the sphere area automatically, which enables the observation of treatment response in the sphere derived from the human glioblastoma LN229 cell line. In addition, the algorithm identifies spheres with numbers to identify each one over time. The AQSA analyzes many images in 0.3 s per image with a low computational cost, enabling laboratories from developing countries to perform sphere counts and area measurements without needing a powerful computer. Consequently, it can be a useful tool for automated CSC quantification from cancer cell lines, and it can be adjusted to quantify CSCs from primary culture cells. CSC-derived sphere detection is highly relevant as it avoids expensive treatments and unnecessary toxicity.

A technique to improve the fixed-sphere decoding algorithm for Spectrally Efficient Frequency Division Multiplexing systems

Spectral Efficient Frequency Division Multiplexing (SEFDM) enhances spectral efficiency by narrowing subcarrier bandwidth, however it introduces severe inter-carrier interference (ICI). Currently, the most effective solution is the Fixed Sphere Detection (FSD) algorithm. In previous studies, we found that in order to better reduce the computational complexity of FSD, it is always through adding preprocessing and other pre-algorithms. Although this approach can effectively fix the search radius g in FSD, the complexity of the FSD algorithm itself has not been reduced. Since FSD determines the exploration path by fixing the tree width (Tw), and the selection of exploration paths can directly affect the final search for the optimal candidate values. In this paper we analyze the traditional algorithm from three angles - computational path, ICI generation, and computational complexity, and propose an Optimization Fixed Sphere Detection (OFSD) algorithm. It reduces the number of calculations required when initially selecting exploration paths by narrowing the search range. This allows us to avoid most unnecessary calculations during path selection. In this way, we can greatly reduce the computational complexity. Based on the simulation results, the proposed algorithm in the paper achieves a significant reduction in computational complexity compared to the FSD algorithm (up to 25% at maximum), while the performance drops by at most 0.12 dB when BCF is 0.8 and drops by at most 0.09 dB when BCF is 0.9.

Design of non‐contact capacitive displacement detection methods for magnetic levitated sphere

AbstractTo meet the demand for non‐contact displacement detection of magnetic levitation spheres, single‐ended and differential variable electrode distance capacitance displacement detection schemes are designed in this paper. For these two schemes, finite element simulation models are established in COMSOL Multiphysics software to obtain the relationship between the test capacitance and the displacement of the magnetic levitation sphere. In the single‐ended scheme, there is a non‐linear relationship between the test capacitance and the position of the levitated sphere, and this non‐linearity becomes more significant as the sphere moves away from the electrode plate. In contrast, in the differential scheme, the test capacitance and the displacement of the levitated sphere follow a linear relationship, but the test sensitivity decreases with the expansion of the measuring range. The simulation results of the differential scheme have been verified by building a spherical displacement detection simulator, and thanks to the mature development of capacitive detection circuits, the scheme is expected to achieve better than nanoscale displacement detection resolution in the 6.6 mm displacement range of a magnetic levitation sphere in the future.

Correcting for non-uniform detector response in bidirectional reflectance distribution function measurements

Systems for measuring the bidirectional reflectance distribution function (BRDF) are intended to be able to measure a variety of sample scattering distributions—from close-to-specular to diffuse, from polarised to unpolarised. Measuring the BRDF involves taking the ratio of measurements of both the amount of light incident on the sample and the amount of light that is reflected by the sample. Detectors used in these systems have a finite sized aperture, and so the different sample scattering distributions will have different distributions of light falling on the detector, and this distribution will also be different from the distribution of light during the incident beam measurement. An ideal detector with a perfectly uniform response is unlikely in reality. For BRDF measurements, it is generally assumed that the response of the detector is the same for both the incident and scattered beams, so even for imperfect detectors, the response of the detector will drop out when the ratio is taken. However, if for some reason the response of the detector differs between the two ratioed quantities, then it will induce an error in the measured ratio. A difference in the response of the detector in the MSL goniospectrophotometer between the collimated and polarised incident beam and the diffuse and unpolarised scattered beam has been identified. Having identified this issue, two different approaches have been taken to avoid the error in our measurements. Firstly, a correction factor was calculated from a detailed model of the detector, using ray tracing. Secondly, a new detector with an integrating sphere in the position of the photodiode was designed to avoid the differing response. To validate these approaches, we compared measurements made using the new sphere detector with corrected measurements made using the original detector, and demonstrate that these agree within the limits of uncertainty.

Research on Dry Chemical Detection TechnologyBased on Reflectance Photometry

In response to the issues of insufficient stability and accuracy in dry chemical detection using reflectance photometry, caused by the divergence and multiple internal reflections of the reflected light signal from the sample and the multilayer dry film test strip, a dry chemical reflectance photometry detection system based on an integrating sphere is designed. Firstly, an integrating sphere device is incorporated to reduce signal divergence and loss, ensuring even detection of the sample's reflected light signal and improving detection stability. Secondly, Light Tools optical simulation analysis is performed, and an integrating sphere detection model is established. Thirdly, the Williams-Clapper equation is employed to correct the error in reflectance density caused by multiple internal reflections, enhancing detection accuracy. Experimental validation demonstrates that the developed integrating sphere-based dry chemical reflectance photometry detection system improves the stability and accuracy of the detection system.

Non-coherent Phase Compensated Sphere Detector for Partial Response CPM

Non-coherent Phase Compensated Sphere Detector for Partial Response CPM

Enhanced UV detection of ZnSnO3 hollow spheres: Dark current inhibition from excitons and homostructures based on excitation of oxygen vacancies

Enhanced UV detection of ZnSnO3 hollow spheres: Dark current inhibition from excitons and homostructures based on excitation of oxygen vacancies

Sub-optimal Deep Pipelined Implementation of MIMO Sphere Detector on FPGA

Sphere detector (SD) is an effective signal detection approach for the wireless multiple-input multiple-output (MIMO) system since it can achieve near-optimal performance while reducing significant computational complexity. In this work, we proposed a novel SD architecture that is suitable for implementation on the hardware accelerator. We first perform a statistical analysis to examine the distribution of valid paths in the SD search tree. Using the analysis result, we then proposed an enhanced hybrid SD (EHSD) architecture that achieves quasi-ML performance and high throughput with a reasonable cost in hardware. The fine-grained pipeline designs of 4 × 4 and 8 × 8 MIMO system with 16-QAM modulation delivers throughput of 7.04 Gbps and 14.08 Gbps on the Xilinx Virtex Ultrascale+ FPGA, respectively.

Optical system design of a DMD-SHS combined modulation interference spectrometer.

Digital micromirror device (DMD) and spatial heterodyne spectroscopy (SHS) combined modulation interference spectroscopy (DMD-SHS) introduces a DMD for the secondary modulation of interferometric data to achieve a Hadamard transform. DMD-SHS can improve the performance index of the spectrometer in terms of the SNR, dynamic range, and spectral bandwidth, while retaining the advantages of a conventional SHS. The DMD-SHS optical system is more complex than a traditional SHS, which places more demands on the optical system's spatial layout and the optical components' performance. According to the DMD-SHS modulation mechanism, the functions of the main components were analyzed, and their design requirements were determined. Based on the potassium spectra detection, a DMD-SHS experimental device was designed. The potassium lamp and integrating sphere detection experiments demonstrated the detection capability of the DMD-SHS experimental device with a spectral resolution of 0.0327nm and a spectral range of 763.66∼771.25n m, which thoroughly verified the feasibility of DMD and SHS combined modulation interference spectroscopy.

A Robust Sphere Detection in a Realsense Point Cloud by USING Z-Score and RANSAC

Three-dimensional vision cameras, such as RGB-D, use 3D point cloud to represent scenes. File formats as XYZ and PLY are commonly used to store 3D point information as raw data, this information does not contain further details, such as metadata or segmentation, for the different objects in the scene. Moreover, objects in the scene can be recognized in a posterior process and can be used for other purposes, such as camera calibration or scene segmentation. We are proposing a method to recognize a basketball in the scene using its known dimensions to fit a sphere formula. In the proposed cost function we search for three different points in the scene using RANSAC (Random Sample Consensus). Furthermore, taking into account the fixed basketball size, our method differentiates the sphere geometry from other objects in the scene, making our method robust in complex scenes. In a posterior step, the sphere center is fitted using z-score values eliminating outliers from the sphere. Results show our methodology converges in finding the basketball in the scene and the center precision improves using z-score, the proposed method obtains a significant improvement by reducing outliers in scenes with noise from 1.75 to 8.3 times when using RANSAC alone. Experiments show our method has advantages when comparing with novel deep learning method.

Peering into the young planetary system AB Pic

Aims. We aim to revisit the formation pathway of AB Pic b, an imaged companion that straddles the exoplanet/brown-dwarf boundary. We based this study on a rich set of observations, which allows us to investigate its orbital and atmospheric properties.Methods. We composed a spectrum of AB Pic b by merging archival medium-resolution (~4000) VLT/SINFONI K band (1.96–2.45 µm) data with published spectra atJandHbands from SINFONI,Lpband from Magellan-AO/CLIO2, and photometric measurements from HST (visible) andSpitzer(mid-infrared). We modeled the spectrum with ForMoSA, following a forward-modeling approach based on two atmospheric models: ExoREM and BT-SETTL13. In parallel, we determined the orbital properties of AB Pic b fitting orbital solutions to astrometric measurements from NaCo (2003 and 2004) and SPHERE (2015).Results. The orbital solutions favor a semi-major axis of 190-50+200au on a highly inclined orbit (edge-on), but with a poorly constrained eccentricity. From the atmospheric modeling with Exo-REM, we derive an effective temperature of 1700 ± 50 K and surface gravity of 4.5 ± 0.3 dex, which are consistent with previous findings, and we report for the first time a c/o ratio of 0.58 ± 0.08, consistent with the value for the Sun. The posteriors are sensitive to the wavelength interval and the family of models used. Given the published rotation period of 2.1 h and our derivedυsin(i) of 73-27+11km s−1, we estimate for the first time the true obliquity of AB Pic b to be between 45 and 135 deg, indicating a rather significant misalignment between the spin and orbit orientations of the planet. Finally, the existence of a proper-motion anomaly between the HIPPARCOSandGaiaEarly Data Release 3 compared to our SPHERE detection limits and adapted radial velocity limits indicates the potential existence of a ~6MJupinner planet orbiting from 2 to 10 au (40–200 mas).Conclusions. The possible existence of an inner companion and the likely misalignment of the spin-axis orientation strongly favor a formation path by gravitational instability or core accretion within a protoplanetary disk at a smaller orbital radius followed by a dynamical interaction which scattered AB Pic b to its current location. Confirmation and characterization of this unseen inner exoplanet and access to a broader wavelength coverage and higher spectral resolution for the characterization of AB Picb will be essential for probing the uncertainties associated with the atmospheric and orbital parameters.

Size-Dependent Oscillation in Optical Spectra from Fly Ash Cenospheres: Particle Sizing Using Darkfield Hyperspectral Interferometry

Abstract Fly ash by-products are emerging biocompatible fillers for a number of construction materials. The value of fly ash as a filler is higher if the content of hollow cenospheres is increased. Here we describe a new method for detection and sizing of fly ash spheres based on darkfield microscopy with hyperspectral image capture to perform white light interferometry. Our method is cost-effective and can provide rapid means for evaluating cenosphere content during the enrichment process. We show that fly ash cenospheres produce a strong oscillation over wavelength in optical recordings. The phenomenon is easiest to observe using microscope imaging techniques that preserve both spatial and spectral information. Frequency is observed to increase in direct proportion to the sphere diameter. The oscillation appears in light recorded from any focal plane on the sphere which indicates that the entire sphere is involved in sustaining the signal, making the detection of cenospheres of different size and displacement within a recording volume productive. There is no oscillation from nonspherical particles of fly ash or other material, so this detection method is highly selective for the cenospheres.

Soft values based detector for bit interleaved coded modulation multi input multi output systems

With the advantages of spatial multiplexing multi input multi output (MIMO) systems in terms of high transmission capacity, the high complexity of the detector at the receiver side of such systems is a major issue. Performance, in terms of bit error rate (BER) is studied for bit interleaved coded modulation (BICM) MIMO systems. List based generation of (bits) soft values is considered for 2 by 2, 4 by 4 systems with 16,64 quadrature amplitude modulation (QAM) and different list sizes utilizing a non systematic convolutional code. Using a sphere detector partial tree search, a scheme is suggested and shown to be more computationally efficient (in terms of the average number of scanned nodes) than a reported alternative for block, flat fading channels. Simulation results reveal that performance in terms of BER can still be maintained.

Research on electromagnetic characteristics of metal spheres with variable parameter defects based on COMSOL finite element method

In order to study the influence of defect geometric parameters (width, thickness) on the electromagnetic characteristics of the space around the defect in the process of eddy current testing of metal spheres, based on the principle of eddy current testing, a metal sphere detection model with different defect parameters was established by COMSOL software for simulation. The distribution of the magnetic field around the defect under different parameters is analyzed with the help of the butterfly diagram composed of the radial magnetic induction intensity and the axial magnetic induction intensity. The results show that: When the width of the corrosion defect is different, the butterfly diagram will change differently. When the width is small, the butterfly diagram basically does not change. When the width reaches a certain value, the butterfly diagram begins to change significantly. The intersection of the graph and the initial butterfly graph is defined as the influence node, and the width of the defect can be quantitatively analyzed according to the sequence of the influence nodes. The influence of the thickness of the corrosion defect on the magnetic field on the surface of the sphere is different under different defect widths. The larger the thickness of the corrosion defect, the greater the influence on the magnetic field near the center of the defect, and the deeper the depression of the butterfly diagram.

Sphere detector with low complexity Euclidean distance computation based on affine transform modulation

The foreseen scale of connected autonomous and low power consumption devices in the near future is a challenging aspect for the next generation of mobile communication networks. As the number of available connection resources is limited, frequency-time multiplexing may not be sufficient to meet the expected demand for capacity, where scheduling solutions might incur in undesired latency levels and also increase the power expenditure to meet a more stringent synchronisation. In this scenario, spatial multiplexing based on multi-user multiple-input multiple-output can extend the uplink capacity at the cost of inter-antenna interference at the base station, requiring more complex detection schemes. The sphere detector can mitigate the inter-antenna interference, achieving close-to-optimum bit error rate performance with average polynomial complexity that still challenges the field programmable gate array implementation in terms of resources and area. To further reduce the sphere detector complexity, the authors introduce the concept of affine transform modulation, which allows us to describe the received signal in terms of the sequence of transmitted bits per symbol. The authors demonstrate that this approach allows to evaluate the Euclidean distance in the sphere detector algorithm in terms of the transmitted bits, replacing the complex inner product by a complex accumulator in its extensively accessed core function. The approach proposed in this paper leads to a considerable complexity reduction in terms of FLOPs for low-order modulations while attaining the conventional sphere detector performance.

Improved RANSAC Point Cloud Spherical Target Detection and Parameter Estimation Method Based on Principal Curvature Constraint.

Spherical targets are widely used in coordinate unification of large-scale combined measurements. Through its central coordinates, scanned point cloud data from different locations can be converted into a unified coordinate reference system. However, point cloud sphere detection has the disadvantages of errors and slow detection time. For this reason, a novel method of spherical object detection and parameter estimation based on an improved random sample consensus (RANSAC) algorithm is proposed. The method is based on the RANSAC algorithm. Firstly, the principal curvature of point cloud data is calculated. Combined with the k-d nearest neighbor search algorithm, the principal curvature constraint of random sampling points is implemented to improve the quality of sample points selected by RANSAC and increase the detection speed. Secondly, the RANSAC method is combined with the total least squares method. The total least squares method is used to estimate the inner point set of spherical objects obtained by the RANSAC algorithm. The experimental results demonstrate that the method outperforms the conventional RANSAC algorithm in terms of accuracy and detection speed in estimating sphere parameters.

Granulation of Yangxue Qingnao Granules in fluidized bed based on near-infrared spectroscopy

To realize the real-time monitoring of the production process of Yangxue Qingnao Granules and improve the inter-batch consistency of granule quality in the granulation process, this study established a near-infrared quantitative prediction model of moisture, particle size, bulk density, and angle of repose in the fluidized bed granulation process of Yangxue Qingnao Granules based on near-infrared spectroscopy(NIRS). The near-infrared spectra were collected from 355 samples in 12 batches in the granulation process by integrating the sphere detection module of the near-infrared spectrometer. In combination with the pretreatment methods such as the first derivative, multiplicative scatter correction(MSC), and standard normal variate(SNV), the model was established by partial least squares(PLS) regression. The root mean square error of prediction(RMSEP) of moisture was 0.347 and R_P~2 was 0.935. The RMSEP of the D_(50) particle size model was 38.4 and R_P~2 was 0.980. The RMSEPs of bulk density and angle of repose were 0.018 8 and 0.879, with R_P~2 of 0.085 9 and 0.958. The results showed that the prediction of the PLS quantitative model combined with NIRS was accurate, and this model can be applied to the monitoring of key quality attributes in the fluidized bed granulation of Chinese medicinal granules in the production scale.

An Optimized Discrete Data Classification Method in N -Dimensional

We propose a discrete data classification method of scattered data in N -dimensional by solving the minimax problem for a set of points. The current research is extended from 2-dimensional and 3-dimensional to N -dimensional. The problem can be applied to artificial intelligence classification problems (machine learning, deep learning), point data analysis problems (data science problem), the optimized design of nanoscale circuits, and the location of facility problems, circle detection on 2D image, or sphere detection on depth image. We generalized the discrete data classification methodology in N -dimensional. Finally, we resolved to find an exact solution of the location of a manifold for our suggested problem in N -dimensional.

Infrared and optical detectability of Dyson spheres at white dwarf stars

ABSTRACT It has been hypothesized that advanced technological civilizations will construct giant space colonies and supporting infrastructures to orbit about their home stars. With data from recent satellites that operate at infrared and optical wavelengths (Spitzer, Wide-field Infrared Survey Explorer, Transiting Exoplanet Survey Satellite, Kepler), in company with a few modest assumptions, it is now possible to begin to constrain observationally the frequency of such space-based civilizations in our Milky Way Galaxy.

Automated SEM Image Analysis of the Sphere Diameter, Sphere-Sphere Separation, and Opening Size Distributions of Nanosphere Lithography Masks.

Colloidal nanosphere monolayers—used as a lithography mask for site-controlled material deposition or removal—offer the possibility of cost-effective patterning of large surface areas. In the present study, an automated analysis of scanning electron microscopy (SEM) images is described, which enables the recognition of the individual nanospheres in densely packed monolayers in order to perform a statistical quantification of the sphere size, mask opening size, and sphere-sphere separation distributions. Search algorithms based on Fourier transformation, cross-correlation, multiple-angle intensity profiling, and sphere edge point detection techniques allow for a sphere detection efficiency of at least 99.8%, even in the case of considerable sphere size variations. While the sphere positions and diameters are determined by fitting circles to the spheres edge points, the openings between sphere triples are detected by intensity thresholding. For the analyzed polystyrene sphere monolayers with sphere sizes between 220 and 600 nm and a diameter spread of around 3% coefficients of variation of 6.8–8.1% for the opening size are found. By correlating the mentioned size distributions, it is shown that, in this case, the dominant contribution to the opening size variation stems from nanometer-scale positional variations of the spheres.