Charge-coupled Device Camera Research Articles

Effect of surface roughness on the liquid bridge between two rigid spheres

We aimed to investigate the impact of surface roughness on liquid bridges between spherical particles. Sandblasting was used to control the particle size and produce glass beads and plates with different surface roughness. First, by measuring the advancing and receding contact angles of droplets on different rough surfaces, we analyzed the effects of surface roughness on wettability and hysteresis. Next, we used a custom-made liquid-bridge stretching device to measure the capillary forces of the liquid bridges between spherical particles with different surface roughness values. A charge-coupled device camera acquisition system was set up to capture the morphological changes of the liquid bridge during stretching, and Image View software was used to extract the morphological parameters of the liquid bridge. Theoretically, we reasonably simplified and solved the differential equations for the liquid bridge morphology and used the Young–Laplace equation to calculate the theoretical capillary force of the liquid bridge, providing an in-depth analysis of the influence of surface roughness on the capillary force. Finally, we studied the impact of surface roughness on the volume ratio of the liquid bridge during static stretching and the residual liquid remaining after the liquid bridge breaks. Experimental results indicated that, as the surface roughness increased, the hydrophobicity and wettability hysteresis of the solid surface also increased. The increased hydrophobicity of the surface reduces the solid-liquid contact area of the liquid bridges between the particles, making it easier to form “columnar” or “convex” liquid bridges. Additionally, the enhanced wettability hysteresis causes the solid-liquid contact boundary to lag during the stretching of the liquid bridge, resulting in a decrease in the solid-liquid contact angle. These factors directly alter the geometric shape of liquid bridges during static stretching, thereby affecting capillary forces. Meanwhile, the increase in surface roughness weakens the effect of gravity on the morphology of the liquid bridge, resulting in less liquid mass remaining on the lower sphere after the liquid bridge breaks as the surface becomes rougher.

High-Speed Fluctuation Analysis of Silver-Nanoparticle SERS in Solutions.

We analyzed the fluctuation of surface-enhanced Raman spectra with a temporal resolution of 25 ms using a conventional electron-multiplying charge-coupled device camera experimental setup. The signal-to-noise ratio of the spectra was improved using density-based spatial cluster analysis with noise. Silver nanoparticles (AgNPs) with different sizes were dispersed as surface-enhanced Raman spectroscopy platforms in violet aqueous solutions. The movement of AgNPs and the fluctuation of the spectra were characterized. The fluctuation (signal ON and OFF) was evaluated on the basis of the time intervals between ON and OFF timing. The behavior of each AgNP solution was explained by a two-dimensional random walk model, which means that the phenomenon was mainly governed by the Brownian motion of the AgNPs in the solution. The fluctuation was also compared among three different Raman modes, one of which showed anomalous behavior.

Analysis of progress in research on technology for the detection and removal of foreign fibers

We focus in this review on the pre-processing devices used, the cotton pipeline, the rejection system, the acquisition and processing of information from images of raw cotton, and measurements of the rate of dynamic flow of the cotton stream. The results show that raw cotton fluffs into a material with a more uniform thickness, and adequately separating the cotton bunch can improve the subsequent detection and removal of foreign fibers in it. Moreover, research that combines the structure of the cotton pipeline with the optimization of the structure of the nozzle plate is important for improving the rejection of foreign fibers in cotton. Furthermore, a combination of multiple light sources and arrays of charge-coupled device cameras can improve the quality of images of raw cotton, but such key parameters as the power and wavelength of the source of light need to be optimized. As any single algorithm for image segmentation and feature extraction struggles to adapt to the identification of different kinds of foreign fibers, it is important to explore a combination of algorithms to this end, and to develop new techniques of foreign fiber detection based on deep learning. Finally, the structure and parameters of processing of the system for the identification and removal of foreign fibers are important, including the relative distance between the sensor and the nozzle, the width of the detection channel, and the rate of flow of the cotton stream.

First spectroscopic study of HFRC plasma

An advanced spectral diagnostic system was developed to measure the electron temperature (T e), electron density (N e), and ion temperature (T i) of the Huazhong University of Science and Technology field-reversed configuration plasma. The system consists of an optic fiber spectrometer with a wide spectral band and a 670 mm focal length high throughout Czerny–Turner monochromator equipped with both a 3600 g mm−1 grating and a 2400 g mm−1 grating to measure the line spectrum. Accompanying these components is an electron-multiplying charge-coupled device camera to capture spectral data. The relative intensity of the optical fiber spectrometer was calibrated using a standard luminance source, and the wavelength calibration of the spectrometer was accomplished using a Hg/Ar lamp. This diagnostic setup was configured to measure electron density based on the Stark effect of Hγ (n = 5 → n = 2; 434.04 nm). Doppler broadening of an O III (2s22p(2P0)3p → 2s22p(2P0)3s; 375.988 nm) emission line was measured and analyzed to obtain the ion temperature, and electron temperatures were estimated from the relative strength of Hβ (n = 4 → n = 2; 486.14 nm) (Dβ) and Hγ (Dγ) spectral lines when the electron density was obtained from Stark effect measurements. The initial experimental results indicate that the highest electron temperature of the formation region was approximately 8 eV, the electron density of the colliding-and-merging region was approaching 1020 m−3, and the ion temperature reached about 40 eV.

Prediction of interface width in overlap joint configuration for laser welding of aluminum alloy using sensors

We present a method that can predict the interface width in an overlapping joint configuration for laser welding of Al alloys using sensors and a convolutional neural network (CNN)-based deep-learning model. The inputs for multi-input CNN-based deep-learning prediction models are spectral signals, represented by the light intensity measured by a spectrometer and dynamic images of the molten pool filmed by a charge-coupled device (CCD) camera. The interface width, used as learning data for modeling, was constructed as a database along with the process signal by cross-sectional analysis. In this study, we present results showing high accuracy in predicting the interface width in the overlap joint configuration for Al alloy laser welding. For predicting the interface width, five models are created and compared: a single CCD and spectrometer sensor algorithm, a multi-sensor algorithm with two input variables (CCD, spectrometer), a multi-sensor algorithm excluding the processing beam in the spectrometer data on the combination of Al 6014-T4 (top)/Al 6014-T4 (bottom), and a multi-sensor algorithm applied to the combination of Al 6014-T4 (top)/Al 5052-H32 (bottom). The multi-sensor algorithm with two input variables (CCD and spectrometer) on the same material combination showed the highest accuracy among the models.

Formation of diffuse and spark discharges between two needle electrodes with the scattering of particles

The development of a nanosecond discharge in a pin-to-pin gap filled with air at atmospheric pressure has been studied with high temporal and spatial resolutions from a breakdown start to the spark decay. Positive and negative nanosecond voltage pulses with an amplitude of tens of kilovolts were applied. Time-resolved images of the discharge development were taken with a four-channel Intensified Charge Coupled Device (ICCD) camera. The minimum delay between the camera channels could be as short as ≈ 0.1 ns. This made it possible to study the gap breakdown process with subnanosecond resolution. It was observed that a wide-diameter streamer develops from the high-voltage pointed electrode. The ionization processes near the grounded pin electrode started when the streamer crossed half of the gap. After bridging the gap by the streamer, a diffuse discharge was formed. The development of spark leaders from bright spots on the surface of the pointed electrodes was observed at the next stage. It was found that the rate of development of the spark leader is an order of magnitude lower than that of the wide-diameter streamer. Long thin luminous tracks were observed against the background of a discharge plasma glow. It has been established that the tracks are adjacent to brightly glowing spots on the electrodes and are associated with the flight of small particles.

A calibration method of line-structured light system for measuring outer circle dimension during machining

The line-structured light system is widely utilized for various 3D profile measurements due to its convenience and high efficiency. However, the existing calibration methods primarily focus on establishing the relationship between object points and image points, which imposes stringent requirements on the calibration target. To address this issue, a practical calibration method based on interpolation function is proposed in order to measure a specific 3D profile - namely, the diameter of a rotating workpiece during machining. Firstly, the light stripe projected onto an ordinary machined workpiece by a light plane is captured using a Charge-Coupled Device (CCD) camera and subsequently fitted to a quadratic elliptic curve after undergoing image processing. Subsequently, the cubic spline interpolation function is selected to directly establish a mapping relationship between geometric characteristics of the elliptic curve and the diameter measurement. Several experiments are conducted to evaluate the proposed methods. The experimental results demonstrate that compared with two comparison methods, our approach reduces the calibration error of linear structured light systems by 69 % and 51 %, respectively; furthermore, it enables restoration of smooth and detailed 3D models through parallel movement of the system. Moreover, our entire calibration process proves practicable in simplifying experimental procedures while remaining suitable for industrial inspection applications.

Phase-modulated multi-foci microscopy for rapid 3D imaging

3D imaging technology is pivotal in monitoring the functional dynamics and morphological alterations in living cells and tissues. However, conventional volumetric imaging associated with mechanical z-scanning encounters challenges in limited 3D imaging speed with inertial artifact. Here, we present a unique phase-modulated multi-foci microscopy (PM3) technique to achieve snapshot 3D imaging with the advantages of extended imaging depths and adjustable imaging intervals between each focus in a rapid fashion. To accomplish the tasks, we utilize a spatial light modulator (SLM) to encode the phases of the scattered or fluorescence light emanating from a volumetric sample and then project the multiple-depth images of the sample onto a single charge-coupled device camera for rapid 3D imaging. We demonstrate that the PM3 technique provides ∼55-fold improvement in imaging depth in polystyrene beads phantom compared to the depth of field of the objective lens used. PM3 also enables the real-time monitoring of Brownian motion of fluorescent beads in water at a 15 Hz volume rate. By precisely manipulating the phase of scattered light on the SLM, PM3 can pinpoint the specific depth information in living zebrafish and rapidly observe the 3D dynamic processes of blood flow in the zebrafish trunk. This work shows that the PM3 technique developed is robust and versatile for fast 3D dynamic imaging in biological and biomedical systems.

Rapid and nondestructive watermelon (Citrullus lanatus) seed viability detection based on visible near-infrared hyperspectral imaging technology and machine learning algorithms.

The improper storage of seeds can potentially compromise agricultural productivity, leading to reduced crop yields. Therefore, assessing seed viability before sowing is of paramount importance. Although numerous techniques exist for evaluating seed conditions, this research leveraged hyperspectral imaging (HSI) technology as an innovative, rapid, clean, and precise nondestructive testing method. The study aimed to determine the most effective classification model for watermelon seeds. Initially, purchased watermelon seeds were segregated into two groups: One underwent sterilization in a dehydrator machine at 40°C for 36h, whereas the other batch was stored under favorable conditions. Watermelon seeds' spectral images were captured using an HSI with a charge-coupled device camera ranging from 400 to 1000nm, and the segmented regions of all samples were measured. Preprocessing techniques and wavelength selection methods were applied to manage spectral data workload, followed by the implementation of a support vector machine (SVM) model. The initial hybrid-SVM model achieved a predictive accuracy rate of 100%, with a test set accuracy of 92.33%. Subsequently, an artificial bee colony (ABC) optimization was introduced to enhance model precision. The results indicated that, with kernel parameters (c, g) set at 13.17 and 0.01, respectively, and a runtime of 4.19328s, the training and evaluation of the dataset achieved an accuracy rate of 100%. Hence, it was practical to utilize HSI technology combined with the PCA-ABC-SVM model to detect different watermelon seeds. As a result, these findings introduce a novel technique for accurately forecasting seed viability, intended for use in agricultural industrial multispectral imaging. PRACTICAL APPLICATION: The traditional methods for determining the condition of seeds primarily emphasize aesthetics, rely on subjective assessment, are time-consuming, and require a lot of labor. On the other hand, HSI technology as green technology was employed to alleviate the aforementioned problems. This work significantly contributes to the field of industrial multispectral imaging by enhancing the capacity to discern various types of seeds and agricultural crop products.

Half-Inch Monolithic Spatial Heterodyne Raman Spectrometer: A Study of Polarized Raman Spectra of Organic Liquids and Instrumental Performance.

Raman spectroscopy allows for the unambiguous identification of materials through the inelastic scattering of light. This technique has a great many uses in various aspects of society from academic, scientific, and industry. This paper explores a specific type of Raman spectrometer called a spatial heterodyne Raman spectrometer (SHRSy), which is a variation of an interferometric spectrometer. It utilizes a Michelson interferometer and replaces the mirrors with gratings that transform it from a time-domain spectrometer to a spatial-domain spectrometer, allowing for the entirety of the spectrum to be captured at once. This study specifically tests a half-inch two-grating monolithic SHRS (½-in. 2g-mSHRS), which has a weight of <60 g and a size of 2.2 × 2.2 × 1.3 cm. To do this we excite a variety of organic liquids with a 532 nm neodymium-doped yttrium aluminum garnet (Nd:YAG) pulsed laser, using an excitation energy of 6.5 mJ/pulse and distance of 3 m in conjunction with an intensified charge-coupled device camera. This is the first time that the SHRS has been used for investigating polarized Raman spectra of liquids. We discuss and contrast the instrumental properties such as resolution, spectral range, étendue, and field of view with previously tested mSHRS to give context to the instrument's performance.

Characterization of OH species in kHz air/H2O atmospheric pressure dielectric barrier discharges

This work numerically studies densities and reaction mechanisms of OH species generated in atmospheric–pressure air dielectric barrier discharges with the model validated by experiments. The power consumption is measured, and the number of microdischarges (MDs) generated within a half period is captured by an intensified charge-coupled device (CCD) camera. The OH densities of cases with various H2O concentrations are measured using ultraviolet absorption spectroscopy. The numerical model integrating the 1.5D discharge fluid model and 3D background gas model (BGM) is adopted to predict the MD behavior and the generation of species related to OH generation. The simulated OH densities cover the range of 1.1 × 1019 and 1.6 × 1019 m−3 in the cases studied, agreeing with those measured. The simulated results show that most OH radicals are generated in MDs, while the reactive section contributes around 2% of the total OH generation. The detailed analysis shows that atomic oxygen (O(1D) and O) and O3 contribute most of the OH generation in the MDs. In contrast, the self-association reactions (i.e. 2OH + M → H2O2 + M and 2OH → O + H2O) and NO x species consume more than 64% of OH radicals generated in MDs. In the BGM, it is interesting to find that reactive species NO x play significant roles in both the OH generation and depletion in the reactive section. The distributions of species related to the OH species obtained by the BGM are presented to elucidate the detailed chemistry of OH species in the reactive section.

Pose detection and docking control for autonomous dynamic docking mechanism with non-cooperative targets

PurposeThis study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control.Design/methodology/approachFirstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory.FindingsExtensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking.Originality/valueThis research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

Thermogravimetric investigation of anisotropy of dimensional shrinkage of softwood and hardwood during carbonization

Thermogravimetric analysis (TGA) was performed on five softwood and five hardwood thin wood samples in the longitudinal (L) and radial (R) directions. Dimensional changes were monitored using a charge-coupled device camera under a nitrogen flow. A comparison of the TG and derivative TG (DTG) curves revealed that shrinkage in the R direction began when the weight was reduced to 79–92% at 305–330 °C and 87–96% at 275–290 °C for softwoods and hardwoods, respectively. Hemicellulose is mainly degraded in this temperature range. In contrast, shrinkage in the L direction started at temperatures close to the DTG peaks, i.e., 360–380 °C and 345–370 °C, respectively, at which temperatures cellulose is mainly degraded. In general, the R/L shrinkage anisotropy was greater for hardwoods than for softwoods, but the species variation was large and the magnitude was directly related to the difference in the shrinkage onset temperatures between the R and L directions, regardless of the wood species. Therefore, shrinkage anisotropy can be attributed to the relative reactivity of hemicellulose and cellulose in wood cell walls. The shrinkage mechanism during carbonization is discussed in terms of the cell wall ultrastructure, in which cellulose microfibrils are covered by a hemicellulose–lignin matrix, and the orientation of the cells in the L and R directions.

Time-resolved observation of 150 kHz high-power pulse burst high-frequency discharge using a high-speed video camera and an intensified charge coupled device camera

The discharge phase and time evolution of a 150 kHz high-power pulse burst discharge were observed. A vacuum chamber was constructed by connecting glass tubes on which a solenoid coil was wound. Burst pulses with a width of 1000 μs and a repetition rate of 10 Hz were applied to the solenoid coil. A high-speed video camera and an intensified CCD camera were used to record photographs of the discharges. Observation of the discharge phase using a high-speed camera showed that the discharge occurs at the time of 40 μs and propagates from the wall of the cylindrical reactor. Over time, the discharge pattern evolves, and a branched pattern appears. The number of the branches changes with time. The discharge blinks synchronize with the instantaneous power, which suggests that the discharge is generated and maintained by the electrostatic field generated by the sides of the coil. The propagation velocity calculated from downstream decreases with increasing pressure and increases with increasing power.

Plastic scintillator-based dosimeters for ultra-high dose rate (UHDR) electron radiotherapy

This paper reports the development of dosimeters based on plastic scintillating fibers imaged by a charge-coupled device camera, and their performance evaluation through irradiations with the electron Flash research accelerator located at the Centro Pisano Flash Radiotherapy. The dosimeter prototypes were composed of a piece of plastic scintillating fiber optically coupled to a clear optical fiber which transported the scintillation signal to the readout systems (an imaging system and a photodiode). The following properties were tested: linearity, capability to reconstruct the percentage depth dose curve in solid water and to sample in time the single beam pulse. The stem effect contribution was evaluated with three methods, and a proof-of-concept one-dimensional array was developed and tested for online beam profiling. Results show linearity up to 10 Gy per pulse, and good capability to reconstruct both the timing and spatial profiles of the beam, thus suggesting that plastic scintillating fibers may be good candidates for low-energy electron Flash dosimetry.

Effect of antenna helicity on discharge characteristics of helicon plasma under a divergent magnetic field

The characteristics of the blue core phenomenon observed in a divergent magnetic field helicon plasma are investigated using two different helical antennas, namely right-handed and left-handed helical antennas. The mode transition, discharge image, spatial profiles of plasma density and electron temperature are diagnosed using a Langmuir probe, a Nikon D90 camera, an intensified charge-coupled device camera and an optical emission spectrometer, respectively. The results demonstrated that the blue core phenomenon appeared in the upstream region of the discharge tube at a fixed magnetic field under both helical antennas. However, it is more likely to appear in a right-handed helical antenna, in which the plasma density and ionization rate of the helicon plasma are higher. The spatial profiles of the plasma density and electron temperature are also different in both axial and radial directions for these two kinds of helical antenna. The wavelength calculated based on the dispersion relation of the bounded whistler wave is consistent with the order of magnitude of plasma length. It is proved that the helicon plasma is part of the wave mode discharge mechanism.

Unsupervised reconstruction with a registered time-unsheared image constraint for compressed ultrafast photography

Compressed ultrafast photography (CUP) is a computational imaging technology capable of capturing transient scenes in picosecond scale with a sequence depth of hundreds of frames. Since the inverse problem of CUP is an ill-posed problem, it is challenging to further improve the reconstruction quality under the condition of high noise level and compression ratio. In addition, there are many articles adding an external charge-coupled device (CCD) camera to the CUP system to form the time-unsheared view because the added constraint can improve the reconstruction quality of images. However, since the images are collected by different cameras, slight affine transformation may have great impacts on the reconstruction quality. Here, we propose an algorithm that combines the time-unsheared image constraint CUP system with unsupervised neural networks. Image registration network is also introduced into the network framework to learn the affine transformation parameters of input images. The proposed algorithm effectively utilizes the implicit image prior in the neural network as well as the extra hardware prior information brought by the time-unsheared view. Combined with image registration network, this joint learning model enables our proposed algorithm to further improve the quality of reconstructed images without training datasets. The simulation and experiment results demonstrate the application prospect of our algorithm in ultrafast event capture.

A Data-driven Approach for Mitigating Dark Current Noise and Bad Pixels in Complementary Metal Oxide Semiconductor Cameras for Space-based Telescopes

In recent years, there has been a gradual increase in the performance of complementary metal oxide semiconductor (CMOS) cameras. These cameras have gained popularity as a viable alternative to charge-coupled device cameras in a wide range of applications. One particular application is the CMOS camera installed in small space telescopes. However, the limited power and spatial resources available on satellites present challenges in maintaining ideal observation conditions, including temperature and radiation environment. Consequently, images captured by CMOS cameras are susceptible to issues such as dark current noise and defective pixels. In this paper, we introduce a data-driven framework for mitigating dark current noise and bad pixels for CMOS cameras. Our approach involves two key steps: pixel clustering and function fitting. During the pixel clustering step, we identify and group pixels exhibiting similar dark current noise properties. Subsequently, in the function fitting step, we formulate functions that capture the relationship between dark current and temperature, as dictated by the Arrhenius law. Our framework leverages ground-based test data to establish distinct temperature–dark current relations for pixels within different clusters. The cluster results could then be utilized to estimate the dark current noise level and detect bad pixels from real observational data. To assess the effectiveness of our approach, we have conducted tests using real observation data obtained from the Yangwang-1 satellite, equipped with a near-ultraviolet telescope and an optical telescope. The results show a considerable improvement in the detection efficiency of space-based telescopes.

Photophysical image analysis: Unsupervised probabilistic thresholding for images from electron-multiplying charge-coupled devices.

We introduce the concept photophysical image analysis (PIA) and an associated pipeline for unsupervised probabilistic image thresholding for images recorded by electron-multiplying charge-coupled device (EMCCD) cameras. We base our approach on a closed-form analytic expression for the characteristic function (Fourier-transform of the probability mass function) for the image counts recorded in an EMCCD camera, which takes into account both stochasticity in the arrival of photons at the imaging camera and subsequent noise induced by the detection system of the camera. The only assumption in our method is that the background photon arrival to the imaging system is described by a stationary Poisson process (we make no assumption about the photon statistics for the signal). We estimate the background photon statistics parameter, λbg, from an image which contains both background and signal pixels by use of a novel truncated fit procedure with an automatically determined image count threshold. Prior to this, the camera noise model parameters are estimated using a calibration step. Utilizing the estimates for the camera parameters and λbg, we then introduce a probabilistic thresholding method, where, for the first time, the fraction of misclassified pixels can be determined a priori for a general image in an unsupervised way. We use synthetic images to validate our a priori estimates and to benchmark against the Otsu method, which is a popular unsupervised non-probabilistic image thresholding method (no a priori estimates for the error rates are provided). For completeness, we lastly present a simple heuristic general-purpose segmentation method based on the thresholding results, which we apply to segmentation of synthetic images and experimental images of fluorescent beads and lung cell nuclei. Our publicly available software opens up for fully automated, unsupervised, probabilistic photophysical image analysis.

Spatial extension of the transient gain drop in a microchannel plate for a single-pulse irradiation

It is widely recognized that a microchannel plate gain drops temporarily after a particle initiates an electron avalanche and that a large amount of charge is extracted from the channel. Electron multiplication is expected to deplete the charges from the microchannel and produce depleted charges (wall charges), and this gain drop is known to persist until charges are replenished. In addition, it was reported that a gain drop occurs not only in the activated channels, where the electrons are multiplied, but also in the surrounding channels. A proposed mechanism for this phenomenon is suggested that the wall charges in the activated channels change the electric field in the surrounding channels, which affects the electron multiplications. In this study, the spatial extent of the gain drop of a chevron microchannel plate detector was evaluated by measuring gains as a function of distance from an activated channel. The experiment used two ultraviolet pulses with different beam sizes, which initially activated one channel and the six neighboring channels with carefully focused laser light, and then applied another light pulse to the surrounding 900 μm × 30 μm area. The gain of each channel was measured using a charge-coupled device camera, and the change in gain as a function of the output charge for the laser pulse was analyzed. A gain drop of 20% was observed at a channel located 110 μm far from the initial activated channel when the output charge was 4 pC. The obtained relationship between the radius of gain drop area and the output charge for the laser pulse was in good agreement with that predicted from the transverse electric field due to the wall charges by computational analysis.