Disk Images Research Articles

Machine-learning Approach to Identification of Coronal Holes in Solar Disk Images and Synoptic Maps

Abstract Identification of solar coronal holes (CHs) provides information both for operational space weather forecasting and long-term investigation of solar activity. Source data for the first problem are typically from the most recent solar disk observations, while for the second problem it is convenient to consider solar synoptic maps. Motivated by the idea that the concept of CHs should be similar for both cases we investigate universal models that can learn CH segmentation in disk images and reproduce the same segmentation in synoptic maps. We demonstrate that convolutional neural networks trained on daily disk images provide an accurate CH segmentation in synoptic maps and their pole-centric projections. Using this approach we construct a catalog of synoptic maps for the period of 2010–20 based on SDO/AIA observations in the 193 Å wavelength. The obtained CH synoptic maps are compared with magnetic synoptic maps in the time-latitude and time-longitude diagrams. The initial results demonstrate that while in some cases the CHs are associated with magnetic flux-transport events there are other mechanisms contributing to the CH formation and evolution. To stimulate further investigations the catalog of synoptic maps is published in open access.

Observational signatures of strongly naked singularities: image of the thin accretion disk

We study the optical appearance of a thin accretion disk around the strongly naked static Janis–Newman–Winicour singularity. The solution does not possess a photon sphere, which results in the formation of a complex structure of bright rings in the central region of the disk image. Such structure is absent in the case of the Schwarzschild black hole with a thin accretion disk, where instead of the image we observe the black hole shadow. Some of the rings emit with the maximal observable radiation flux from the accretion disk, and should be experimentally detectable. Thus, this qualitatively new feature can be used to distinguish observationally black holes from naked singularities. We elucidate the appearance of the ring structure by revealing the physical mechanism of its formation, and explaining the nature of each of the ring images. We make the conjecture that a similar structure would also appear for other solutions without a photon sphere and it can serve as a general observational signature for distinguishing compact objects possessing no photon sphere from black holes.

Hints for Icy Pebble Migration Feeding an Oxygen-rich Chemistry in the Inner Planet-forming Region of Disks

Abstract We present a synergic study of protoplanetary disks to investigate links between inner-disk gas molecules and the large-scale migration of solid pebbles. The sample includes 63 disks where two types of measurements are available: (1) spatially resolved disk images revealing the radial distribution of disk pebbles (millimeter to centimeter dust grains), from millimeter observations with the Atacama Large Millimeter/Submillimeter Array or the Submillimeter Array, and (2) infrared molecular emission spectra as observed with Spitzer. The line flux ratios of H2O with HCN, C2H2, and CO2 all anticorrelate with the dust disk radius R dust, expanding previous results found by Najita et al. for HCN/H2O and the dust disk mass. By normalization with the dependence on accretion luminosity common to all molecules, only the H2O luminosity maintains a detectable anticorrelation with disk radius, suggesting that the strongest underlying relation is between H2O and R dust. If R dust is set by large-scale pebble drift, and if molecular luminosities trace the elemental budgets of inner-disk warm gas, these results can be naturally explained with scenarios where the inner disk chemistry is fed by sublimation of oxygen-rich icy pebbles migrating inward from the outer disk. Anticorrelations are also detected between all molecular luminosities and the infrared index n 13–30, which is sensitive to the presence and size of an inner-disk dust cavity. Overall, these relations suggest a physical interconnection between dust and gas evolution, both locally and across disk scales. We discuss fundamental predictions to test this interpretation and study the interplay between pebble drift, inner disk depletion, and the chemistry of planet-forming material.

Acute effects of varying squat depths on lumbar intervertebral disks during high-load barbell back squat exercise.

We aimed to evaluate the acute physiological effects of high-load barbell back squat exercise on each lumbar intervertebral disk with varying squat depths. Thirteen subjects (age, 23.3±3.5 years) performed parallel and half-squat exercises (80% of one repetition maximum, eight repetitions, five sets) using a Smith machine. Sagittal magnetic resonance diffusion-weighted and spin-echo images of lumbar intervertebral disks were obtained by using a 1.5-Tesla MR system before and after each squat exercise; apparent diffusion coefficient (ADC; an index of water movement) and T2 relaxation time (an index of water content level) of the nucleus pulposus were calculated at all lumbar intervertebral disks. Additionally, we measured the angles of lumbar lordosis and anterior pelvic tilt at the bottom position of each squat using a three-dimensional motion-capture system. The nucleus pulposus of L4/5 (-5.0%, P<.01) and L5/S1 (-6.6%, P<.01) intervertebral disks showed decreased ADC values after parallel squat exercise. Moreover, post-exercise ADC value in parallel squat exercise was lower than that in half-squat exercise at L5/S1 intervertebral disk (P<.05). In contrast, the nucleus pulposus of all lumbar intervertebral disks had no significant T2 change before and after both squat exercises. The angles of lumbar lordosis (P<.01) and anterior pelvic tilt (P<.01) were smaller in parallel squat than in half-squat. Lower lumbar intervertebral disks are subject to greater mechanical stress during high-load parallel back squat exercise, which may result from smaller lumbar lordosis and anterior pelvic tilt angles at the bottom position during parallel squat.

Evidence of a strong relationship between hemispheric asymmetry in solar coronal rotation and solar activity during solar cycle 24

ABSTRACT In this paper, we report evidence of a very strong and statistically significant relationship between hemispheric asymmetry in the solar coronal rotation rate and solar activity. Our approach is based on the cross-correlation of the hemispheric asymmetry index (AI) in the rotation rate with annual solar activity indicators. To obtain the hemispheric asymmetry in the solar rotation rate, we use solar full disc (SFD) images at 30.4-, 19.5- and 28.4-nm wavelengths for the 24th solar cycle, that is, for the period from 2008 to 2018, as recorded by the Solar Terrestrial Relations Observatory (STEREO) space mission. Our analysis shows that the hemispheric asymmetry in rotation rate is high during the solar maxima from 2011 to 2014. However, hemispheric asymmetry decreases gradually on both sides (i.e. from 2008 to 2011 and from 2014 to 2018). The results show that the AI leads sunspot numbers by ∼ 1.56 yr. This is a clear indication that hemispheric asymmetry triggers the formation of sunspots in conjunction with the differential rotation of the Sun.

The Trigger and Termination Scheme for the Event Mode of the Lyman-alpha Solar Telescope (LST) onboard the ASO-S Mission

The Advanced Space-based Solar Observatory (ASO-S) is the China's first comprehensive solar dedicated satellite, scheduled to be launched around 2022. The Lyman-alpha (Lyα) Solar Telescope (LST) is one of the payloads of the ASO-S, consisting of three scientific instruments and two Guide Telescopes (GTs). The scientific instruments include a Solar Disk Imager (SDI), a White-light Solar Telescope (WST), and a Solar Corona Imager (SCI), which are aimed to observe the whole evolving process of two types of violent eruptions on the Sun, i.e., solar flares and coronal mass ejections, in multiwavelengths with high temporal and spatial resolutions. To achieve this goal, all LST instruments have included an observation mode (event mode) dedicated to event observations. In this mode, all instruments take images at a higher cadence (the SCI takes full-frame coronal images while SDI and WST take only partial frame images around the eruption region). The time and location information of the eruption events can be effectively obtained by monitoring the local brightness enhancement of the onboard images processed with median filtering and pixel rebinning. The obtained information will provide an important electronic input for the automatic switching between different observation modes of LST.

Acute Physiological Response of Lumbar Intervertebral Discs to High-load Deadlift Exercise.

Purpose:We aimed to evaluate the acute physiological effects of high-load deadlift exercise on the lumbar intervertebral discs using MR diffusion-weighted imaging (DWI).Methods:Fifteen volunteers (11 men and 4 women; 23.2 ± 3.3 years) without lumbar intervertebral disc degeneration performed deadlift exercise (70% of 1 repetition maximum, 6 repetitions, 5 sets, 90 s rest between sets) using a Smith machine. Sagittal MR diffusion-weighted images of the lumbar intervertebral discs were obtained using a 1.5-Tesla MR system with a spine coil before and immediately after the exercise. We calculated apparent diffusion coefficient (ADC; an index of water movement) of the nucleus pulposus from diffusion weighted images at all lumbar intervertebral discs (L1/2 through L5/S1).Results:All lumbar intervertebral discs showed significantly decreased ADC values immediately after deadlift exercise (L1/2, −2.8%; L2/3, −2.1%; L3/4, −2.8%; L4/5, −4.9%; L5/S1, −6.2%; P < 0.01). In addition, the rate of ADC decrease of the L5/S1 disc was significantly greater than those of the L1/2 (P = 0.017), L2/3 (P < 0.01), and L3/4 (P = 0.02) discs.Conclusion:The movement of water molecules within the lumbar intervertebral discs is suppressed by high-load deadlift exercise, which would be attributed to mechanical stress on the lumbar intervertebral discs during deadlift exercise. In particular, the L5/S1 disc is subjected to greater mechanical stress than the other lumbar intervertebral discs.

Examining artifacts generated by setting Facebook Messenger as a default SMS application on Android: Implication for personal data privacy

AbstractThe use of mobile devices and social media applications in organized crime is increasingly increasing. Facebook Messenger is the most popular social media applications used globally. Unprecedented time is spent by many interacting globally with known and unknown individuals using Facebook. During their interaction, personal information is uploaded. Thus, crafting a myriad of privacy trepidation to users. While there are researches performed on the forensic artifacts' extraction from Facebook, no research is conducted on setting Facebook Messenger applications as a default messaging application on Android. Two Android mobile devices were used for data generation and Facebook Messenger account was created. Disc imaging and data partition were examined and accessed to identify changes in the orca database of the application package using DB browser. The data were then generated using unique words which were used for conducting key searches. The research discovered that mqtt_log_event0.txt of the Com.Facebook.orca/Cache directory stores chat when messenger is set as a default messaging app. The research finding shows that chats are recorded under messages tab together with SMS of data/data/com.facebook.orca/databases/smstakeover_db and data/data/com.facebook.orca/databases/threads_db. This indicates that only smstakeover_db stores SMS messaging information when using messenger application. It is observed that once the user deletes a sent SMS message, the phone number and the deleted time stamp remained in the data/data/com.facebook.orca/databases/smstakeover_db database in the address_table are recoverable. The results suggest that anonymization of data is essential if Facebook chats are to be shared for further research into social media content.

Defect detection method of magnetic disk image based on improved convolutional neural network

This paper proposes an efficient method for defect detection of magnetic disk image based on improved convolutional neural network. We build a model named DiskNet on the basis of VGGNet-19, in which the optimal activation function is selected predictively through a weighted probability learning curve model (WP-Model). First, we use Markov Chain Monte Carlo (MCMC) to infer the predicted value and determine prediction probability. Then, the evaluation point (EP) is determined by the effective information of training curve. In the process of DiskNet training, when the prediction probability is higher than the threshold, the neural network will select the current activation function. If the training epochs exceed the EP and the threshold is not reached, the original activation function will be used. The experimental results show that the accuracy of the proposed method in detecting defects on the magnetic disk image data set is 96.9%.

Comparative Study and Development of Two Contour-Based Image Segmentation Techniques for Coronal Hole Detection in Solar Images

The study of solar coronal holes (CHs) is important in the understanding of solar physics and the prediction of space weather events, which have significant impact on space-based instruments, communication and navigation systems. With the availability of the multi-wavelength Atmospheric Imaging Assembly (AIA) instrument on board Solar Dynamics Observatory (SDO) satellite, a large volume of high-resolution solar images are produced continuously. Proper detection of CHs from AIA images is an important issue and recently, a few contour and machine learning-based techniques are found to be promising for such purpose. However, accuracy, time complexity and the requirement of human intervention are some of the critical issues with such methods. In this paper, to address these challenging issues, two contour-based approaches are developed, namely i) the Hough transformed simulated parameterized online region-based active contour method (POR-ACM) and ii) fast fuzzy c-means clustering followed by Hough transformed simulated static contour method (FFCM-SCM). The major issues that are addressed here are automated initialization of contour, reducing time complexity and avoidance of non-coronal hole inside a coronal hole region during contour evolution. The proposed techniques have been tested on three benchmark solar disk images and compared with the existing active contour without edge- (ACWE) based method and fuzzy energy-based dual contour method (FEDCM) of CHs segmentation. The results indicate the capability of the proposed techniques in detection and extraction of CHs in solar disk image with higher accuracy and reduced time complexity.

Zonal integration of circular Hartmann and Placido patterns with non-rotationally symmetric aberrations.

Placido disk methods for corneal topography use a target with concentric rings in order to obtain measurements of the corneal surface, codifying the topography from the deformations of the rings' image. Knowing exactly how the corneal surface departs from a rotational symmetric shape is difficult by using Placido rings. This is due to the fact that any ray deviations in the angular direction (sagittal transverse aberrations) are not easily detected and measured. This is the so-called skew ray error. For that reason, this technique has been considered as limited, especially when one tries to measure corneal aberrations with large rotational symmetry errors. However, we considered that the Placido disk topography has the potential to obtain a full description of the corneal surface as long as the skew ray error is fixed. Here, we present a solution based in the assumption that a corneal topography calculated with the presence of the skew ray error has hidden information that can be extracted by applying some basis of the classical Hartmann test. To achieve that solution, we improve some aspects of the Hartmann test to be later applied in the processing of Placido disk images. Our solution gives us the ability to solve the skew ray error in a simple and direct method, with an effectiveness that is probed by the computing of some simulated representative surfaces without rotational symmetry and the performance of our algorithm.

Multidomain Feature Level Fusion for Classification of Lumbar Intervertebral Disc Using Spine MR Images

Grading of discs is essential for the assessment of degeneration progression which subsequently plays a vital role in decision making in the removal of a disc. In particular, Pfirrmann’s five-scale (1–5) scoring system is widely used in MR image modality for grading the discs. In this study, we have presented a contemporary semiautomatic feature level fusion approach for the classification of inter-vertebral discs. The data of T2-weighted lumbar MR scans in sagittal plane were collected from 120 distinct subjects. In total, 1123 inter-vertebral disc images were obtained upon performing image augmentation. The experts have segregated the discs into five categories as per Pfirrmann’s criteria. This segregation is utilized as ground truth label data for classification. Furthermore, two feature extraction techniques are exploited, one from spatial domain and other follows deep learning process. A popular Local Binary Pattern (LBP) texture descriptor extracts features from spatial domain. In addition, a popular pre-trained Convolution Neural Network (CNN), which acts as a feature extractor, extracts deep features. The training procedure using SVM classifier yields a model built from post-fusion feature vectors. Furthermore, to estimate the model’s performance, a 5-fold cross-validation is performed by computing principal component analysis as well as without dimensionality reduction. Experiment results obtained on our dataset indicate that after dimensionality reduction, SVM classifier with various kernel functions yields the accuracy up to 92%. A quantitative analysis of the classifier model is presented for parameters, namely – Accuracy, Area Under Curve (AUC), Specificity, Sensitivity, and F1 measure.

Association between Exercise Intensity and Glaucoma in the National Health and Nutrition Examination Survey

To examine the association between exercise intensity and glaucoma in the National Health and Nutrition Examination Survey (NHANES) population. Retrospective, cross-sectional study. Adult participants of the 2005-2006 NHANES aged 40 years and older. Objective exercise intensity was assessed based on measurements from accelerometers worn by participants over 1 week. Subjective exercise intensity was assessed with questionnaire responses. Glaucoma was defined with 2 definitions based on (1) the Rotterdam criteria and (2) ophthalmologist grading of optic disc photographs for characteristic features of glaucoma. Covariates included age, gender, ethnicity, blood pressure, body mass index, and spherical equivalent. Logistic regression was performed to assess associations between objective and subjective exercise intensity and glaucoma while controlling for all covariates. All data were weighted based on the NHANES multistage sampling design. Prevalence of glaucoma based on the 2 definitions described. The study included a sample of 1387 participants, of whom 68 (4.9%) had glaucoma based on Rotterdam criteria and 7 (0.5%) had glaucoma based on disc image grading. This translated to a weighted estimate of 70 246 160 individuals, with an estimated prevalence of glaucoma of 3.1% based on the Rotterdam criteria and 0.3% based on disc image grading. After adjusting for covariates, each 10-count increase in accelerometer intensity was associated with decreased odds of glaucoma using both criteria (odds ratio [OR], 0.97; 95% confidence interval [CI], 0.95-0.99 for Rotterdam; OR, 0.90; 95% CI, 0.85-0.95 using disc image grading). With Rotterdam criteria, participants who spent the day standing or walking versus sitting had 58% decreased odds of glaucoma (OR, 0.42; 95% CI, 0.25-0.70). With disc image grading, participants who performed moderate amounts of vigorous activity had 95% decreased odds of glaucoma compared with those who performed no vigorous activity (OR, 0.05; 95% CI, 0.01-0.56). In the 2005-2006 NHANES adult population, increased exercise intensity is associated with decreased odds of glaucoma. Further population-based studies are needed to examine associations between additional aspects of exercise and glaucoma.

Stochastic Distance Transform: Theory, Algorithms and Applications

Distance transforms (DTs) are standard tools in image analysis, with applications in image registration and segmentation. The DT is based on extremal (minimal) distance values and is therefore highly sensitive to noise. We present a stochastic distance transform (SDT) based on discrete random sets, in which a model of element-wise probability is utilized and the SDT is computed as the first moment of the distance distribution to the random set. We present two methods for computing the SDT and analyze them w.r.t. accuracy and complexity. Further, we propose a method, utilizing kernel density estimation, for estimating probability functions and associated random sets to use with the SDT. We evaluate the accuracy of the SDT and the proposed framework on images of thin line structures and disks corrupted by salt and pepper noise and observe excellent performance. We also insert the SDT into a segmentation framework and apply it to overlapping objects, where it provides substantially improved performance over previous methods. Finally, we evaluate the SDT and observe very good performance, on simulated images from localization microscopy, a state-of-the-art super-resolution microscopy technique which yields highly spatially localized but noisy point-clouds.

Control System of Sun-Tracking Accuracy for Concentration Photovoltaic Installations

The power generation of the phtovoltaic installations depends on the concentration modules’ efficiency and the Sun tracking accuracy. We have developed a system for monitoring instant tracking accuracy based on a recorder and a projecting system of solar disk imaging.

Frankenstein: protoplanetary disc brightness profile reconstruction at sub-beam resolution with a rapid Gaussian process

ABSTRACT Interferometric observations of the mm dust distribution in protoplanetary discs are now showing a ubiquity of annular gap and ring substructures. Their identification and accurate characterization are critical to probing the physical processes responsible. We present frankenstein (frank), an open source code that recovers axisymmetric disc structures at a sub-beam resolution. By fitting the visibilities directly, the model reconstructs a disc’s 1D radial brightness profile non-parametrically using a fast (≲1 min) Gaussian process. The code avoids limitations of current methods that obtain the radial brightness profile either by extracting it from the disc image via non-linear deconvolution at the cost of reduced fit resolution or by assumptions placed on the functional forms of disc structures to fit the visibilities parametrically. We use mock Atacama Large Millimeter Array observations to quantify the method’s intrinsic capability and its performance as a function of baseline-dependent signal-to-noise ratio. Comparing the technique to profile extraction from a clean image, we motivate how our fits accurately recover disc structures at a sub-beam resolution. Demonstrating the model’s utility in fitting real high- and moderate-resolution observations, we conclude by proposing applications to address open questions on protoplanetary disc structure and processes.

BitScout: Remote Digital Forensics Toolkit

Forensic Science has been full of challenges for most of the Law Enforcement Agency (LEA) as we need to physically visit the crime scene, acquire evidence, then preserve it for forensic analysis. The path of collecting evidences from crime site and then bringing it to the Forensic Labs. becomes much cumbersome as the evidence may be corrupted or altered during transit. So why not to adopt a system for readily analysis of a compromised system without going to the crime site and sitting on one’s chair or forensic workstation? The answer may be yes, we can but will it be easy and ethical to acquire evidence from a system remotely without visiting the crime scene physically. Vitaly Kamluk from Kaspersky Labs made this possible now by launching a new forensic tool called BitScout . To solve this problem, security researchers and Forensic Investigator can now use BitScout to collect remotely, key forensic evidences, to acquire full disk images via the network or locally attached storage devices, or simply to assist in malware incident handling. Evidence data can be viewed and analysed remotely or locally while the source data storage remains intact through reliable container-based isolation. BitScout is an open-source and free tool developed by security researchers for all people interested in digital forensics and cyber crimes investigations.

Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems

We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition. Development of an Artificial Intelligence Classification algorithm. This single-institution analysis included 3815 fundus images from the picture archiving and communication system of Seoul National University Bundang Hospital consisting of 2883 normal optic disc images, 446 NGON images, and 486 GON images. The presence of NGON and GON was interpreted by 2 expert neuro-ophthalmologists and had corroborated evidence on visual field testing and optical coherence tomography. Images were preprocessed in size and color enhancement before input. We applied the convolutional neural network (CNN) of ResNet-50 architecture. The area under the precision-recall curve (average precision) was evaluated for the efficacy of deep learning algorithms to assess the performance of classifying NGON and GON. The diagnostic accuracy of the ResNet-50 model to detect GON among NGON images showed a sensitivity of 93.4% and specificity of 81.8%. The area under the precision-recall curve for differentiating NGON vs GON showed an average precision value of 0.874. False positive cases were found with extensive areas of peripapillary atrophy and tilted optic discs. Artificial intelligence-based deep learning algorithms for detecting optic disc diseases showed excellent performance in differentiating NGON and GON on color fundus photographs, necessitating further research for clinical application.

Tampering with Digital Evidence is Hard: The Case of Main Memory Images

Tampered digital evidence may jeopardize its correct interpretation. To assess the risks in a court of law, it is helpful to quantify the necessary effort to perform a convincing manipulation of digital evidence. Based on a sequence of controlled experiments with graduate students and digital forensics professionals, we study the effort to manipulate copies of main memory taken during a digital investigation. Confirming previous results on hard disc image tampering, manipulating main memory dumps can be considered hard in the sense that most forgeries were successfully detected. However, while the effort to detect a manipulation is generally bounded by the tampering effort, some forgeries fooled the analysts and caused analysis effort that was higher than the manipulation effort. The detection effort by graduate students, however, was generally higher than that of professionals. We study different manipulation and detection approaches and their success. Overall, tampering with main memory dumps appears to be harder than tampering with hard disc images but the probability to fool an analyst is higher too.

Magnetic Resonance Imaging of Trunk Musculature and Intervertebral Discs in Patients with Spinal Cord Injury with Thoracolumbar Vertebral Fractures: A Prospective Study.

Study DesignThis study is a prospective clinical study.PurposeThis study aims to evaluate the characteristics of trunk musculature and intervertebral discs by using magnetic resonance imaging in patients with spinal cord injuries (SCIs) with thoracic and lumbar fractures. Overview of LiteratureMuscle atrophy is an immediate consequence of SCI and is associated with secondary complications. At present, there are limited clinical data on muscle and disc responses to fractures of the thoracic and lumbar spine.MethodsA total of 51 patients with a mean age of 31.75±10.42 years who suffered traumatic SCI were included in this study. Complete neurological examinations (American Spinal Injury Association grading) and magnetic resonance imaging (MRI) were performed at the time of admission and at 3–6 months after injury to study the neurological status and disc and trunk parameters. The type of management (operative or conservative) was decided on the basis of clinical, radiological, and MRI evaluations, and a robust rehabilitation program was initiated.ResultsDisc parameters including disc angle, skin angle, cross-sectional area (CSA), and disc height and trunk parameters (mean trunk width, mean trunk depth, and CSA of the lumbar muscles) decreased significantly (p <0.001) during the first 3 months after SCI. However, improvements were observed in disc and muscle parameters at the 6-month follow-up, but these parameters did not return to normal levels. Neither initial neurological status (complete vs. incomplete) nor type of management (operative vs. conservative) had a significant effect on these parameters.ConclusionsSpinal trauma leads to alterations in the morphology of the vertebral column, spinal cord, intervertebral discs, and paraspinal muscles in the initial phase of injury. The extent of these changes may determine the initial neurological deficit and subsequent recovery. Although this study did not identify any statistically significant effect of neurological status or management strategy on these parameters, rehabilitation was found to result in the improvement of these parameters in the later phase of recovery. Future studies are required to evaluate the exact causes of these alterations and the potential benefits of rehabilitation strategies and to minimize these changes.