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At least 1,243 records · Page 69

AEPF: Attention-Enabled Point Fusion for 3D Object Detection

Current state-of-the-art (SOTA) LiDAR-only detectors perform well for 3D object detection tasks, but point cloud data are typically sparse and lacks semantic information. Detailed semantic information obtained from camera images can be added with existing LiDAR-based detectors to create a robust 3D detection pipeline. With two different data types, a major challenge in developing multi-modal sensor fusion networks is to achieve effective data fusion while managing computational resources. With separate 2D and 3D feature extraction backbones, feature fusion can become more challenging as these modes generate different gradients, leading to gradient conflicts and suboptimal convergence during network optimization. To this end, we propose a 3D object detection method, Attention-Enabled Point Fusion (AEPF). AEPF uses images and voxelized point cloud data as inputs and estimates the 3D bounding boxes of object locations as outputs. An attention mechanism is introduced to an existing feature fusion strategy to improve 3D detection accuracy and two variants are proposed. These two variants, AEPF-Small and AEPF-Large, address different needs. AEPF-Small, with a lightweight attention module and fewer parameters, offers fast inference. AEPF-Large, with a more complex attention module and increased parameters, provides higher accuracy than baseline models. Experimental results on the KITTI validation set show that AEPF-Small maintains SOTA 3D detection accuracy while inferencing at higher speeds. AEPF-Large achieves mean average precision scores of 91.13, 79.06, and 76.15 for the car class’s easy, medium, and hard targets, respectively, in the KITTI validation set. Results from ablation experiments are also presented to support the choice of model architecture.

Chemistry↗

Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples

Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, “Mappgene”, was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.

60 APPLIED LIFE SCIENCES↗

Cyberattack Detection for Cyber Physical Systems Security–A Preliminary Study.

Cyber-physical systems (CPS) security has become an increasingly important research topic in recent years. Geared towards more advanced cyberattack detection techniques as part of strategies for enhancing the security of CPS, in this paper we propose a machine learning based cyber-attack detection scheme. The proposed scheme is a physical-domain technique; specifically, it assumes the physical measurements of the system carry sufficient information for capturing the system behavior, thus can be used for differentiating normal operation and attacks. CPS are complex in nature and the number of physical measurements available for CPS is often overwhelmingly high. Thus, accurately modeling CPS’ dynamic behavior, more importantly, distinguishing normal and adversary activities based on the large number of physical measurements, can be challenging. To address the challenge, we have focused our research effort on feature engineering, that is, to intelligently derive a set of salient signatures or features from the noisy measurements. We make sure the derived features are more compact and, more importantly, have more discriminant power than the original physical measurements, thus enabling us to achieve more accurate and robust detection performance. To demonstrate the effectiveness of the proposed scheme, in our experimental study we consider gas turbines of combined cycle power plants as the cyberphysical system. Using the data from the high-fidelity simulation we show that our proposed cyberattack detection scheme is able to achieve high detection performance.

97 MATHEMATICS AND COMPUTING↗

JAMES WEBB SPACE TELESCOPE CAN DETECT KILONOVAE IN GRAVITATIONAL WAVE FOLLOW-UP SEARCH

Kilonovae represent an important electromagnetic counterpart for compact binary mergers, which could become the most commonly detected gravitational-wave (GW) source. Follow-up observations of kilonovae, triggered by GW events, are nevertheless difficult due to poor localization by GW detectors and due to their faint near-infrared peak emission, which has limited observational capability. We show that the Near-Infrared Camera (NIRCam) on the James Webb Space Telescope will be able to detect kilonovae within the relevant GW-detection range of ∼200 Mpc in short (≲12-s) exposure times for a week following the merger. Despite this sensitivity, a kilonova search fully covering a fiducial localized area of 10 deg{sup 2} will not be viable with NIRCam due to its limited field of view. However, targeted surveys may be developed to optimize the likelihood of discovering kilonovae efficiently within limited observing time. We estimate that a survey of 10 deg{sup 2} focused on galaxies within 200 Mpc would require about 13 hr, dominated by overhead times; a survey further focused on galaxies exhibiting high star formation rates would require ∼5 hr. The characteristic time may be reduced to as little as ∼4 hr, without compromising the likelihood of detecting kilonovae, by surveying sky areas associated with 50%, rather than 90%, confidence regions of 3 GW events, rather than a single event. Upon the detection and identification of a kilonova, a limited number of NIRCam follow-up observations could constrain the properties of matter ejected by the binary and the equation of state of dense nuclear matter.

79 ASTRONOMY AND ASTROPHYSICS↗

Detection of Cyclopropenylidene on Titan with ALMA

We report the first detection on Titan of the small cyclic molecule cyclopropenylidene (c-C{sub 3}H{sub 2}) from high-sensitivity spectroscopic observations made with the Atacama Large Millimeter/submillimeter Array. Multiple lines of cyclopropenylidene were detected in two separate data sets: ∼251 GHz in 2016 (Band 6) and ∼352 GHz in 2017 (Band 7). Modeling of these emissions indicates abundances of 0.50 ± 0.14 ppb (2016) and 0.28 ± 0.08 (2017) for a 350 km step model, which may either signify a decrease in abundance, or a mean value of 0.33 ± 0.07 ppb. Inferred column abundances are (3–5) × 10{sup 12} cm{sup −2} in 2016 and (1–2) × 10{sup 12} cm{sup −2} in 2017, similar to photochemical model predictions. Previously the C{sub 3}H{sub 3}{sup +} ion has been measured in Titan’s ionosphere by Cassini’s Ion and Neutral Mass Spectrometer (INMS), but the neutral (unprotonated) species has not been detected until now, and aromatic versus aliphatic structure could not be determined by the INMS. Our work therefore represents the first unambiguous detection of cyclopropenylidene, the second known cyclic molecule in Titan’s atmosphere along with benzene (C{sub 6}H{sub 6}) and the first time this molecule has been detected in a planetary atmosphere. We also searched for the N-heterocycle molecules pyridine and pyrimidine finding nondetections in both cases, and determining 2σ upper limits of 1.15 ppb (c-C{sub 5}H{sub 5}N) and 0.85 ppb (c-C{sub 4}H{sub 4}N{sub 2}) for uniform abundances above 300 km. These new results on cyclic molecules provide fresh constraints on photochemical pathways in Titan’s atmosphere, and will require new modeling and experimental work to fully understand the implications for complex molecule formation.

79 ASTRONOMY AND ASTROPHYSICS↗

Toward Rate Estimation for Transient Surveys. I. Assessing Transient Detectability and Volume Sensitivity for iPTF

The past couple of decades have seen an emergence of transient detection facilities in various avenues of time-domain astronomy that have provided us with a rich data set of transients. The rates of these transients have implications in star formation, progenitor models, evolution channels, and cosmology measurements. The crucial component of any rate calculation is the detectability and spacetime volume sensitivity of a survey to a particular transient type as a function of many intrinsic and extrinsic parameters. Fully sampling that multidimensional parameter space is challenging. Instead, we present a scheme to assess the detectability of transients using supervised machine learning. The data product is a classifier that determines the detection likelihood of sources resulting from an image subtraction pipeline associated with time-domain survey telescopes, taking into consideration the intrinsic properties of the transients and the observing conditions. We apply our method to assess the spacetime volume sensitivity of type Ia supernovae (SNe Ia) in the intermediate Palomar Transient Factory (iPTF) and obtain the result, ⟨ VT ⟩ Ia = (2.93 ± 0.21) × 10 -2 Gpc 3 yr. With rate estimates in the literature, this volume sensitivity gives a count of 680-1160 SNe Ia detectable by iPTF, which is consistent with the archival data. With a view toward wider applicability of this technique we do a preliminary computation for long-duration type IIp supernovae (SNe IIp) and find ⟨ VT ⟩ IIa = (7.80 ± 0.76) × 10 -4 Gpc 3 yr. This classifier can be used for computationally fast spacetime volume sensitivity calculation of any generic transient type using their light-curve properties. Hence, it can be used as a tool to facilitate calculation of transient rates in a range of time-domain surveys, given suitable training sets.

79 ASTRONOMY AND ASTROPHYSICS↗

Mitigating Shear-dependent Object Detection Biases with Metacalibration

M ETACALIBRATION is a new technique for measuring weak gravitational lensing shear that is unbiased for isolated galaxy images. Here we test M ETACALIBRATION with overlapping, or "blended" galaxy images. Using standard M ETACALIBRATION , we find a few percent shear measurement bias for galaxy densities relevant for current surveys, and that this bias increases with increasing galaxy number density. We show that this bias is not due to blending itself, but rather to shear-dependent object detection. If object detection is shear-independent, no deblending of images is needed, in principle. We demonstrate that detection biases are accurately removed when including object detection in the M ETACALIBRATION process, a technique we call M ETADETECTION . This process involves applying an artificial shear to images of small regions of sky and performing detection on the sheared images, as well as measurements that are used to calculate a shear response. We demonstrate that the method can accurately recover weak shear signals even in highly blended scenes. In the M ETACALIBRATION process, the space between objects is sheared coherently, which does not perfectly match the real universe in which some, but not all, galaxy images are sheared coherently. We find that even for the worst case scenario, in which the space between objects is completely unsheared, the resulting shear bias is at most a few tenths of a percent for future surveys. We discuss additional technical challenges that must be met in order to implement M ETADETECTION for real surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

MEGASIM: Distribution and Detection of Earth Trojan Asteroids

Abstract Using N -body simulation results from the MEGASIM data set, we present spatial distributions of Earth Trojan Asteroids and assess the detectability of the population in current and next-generation ground-based astronomical surveys. Our high-fidelity Earth Trojan Asteroid (ETA) distribution maps show never-before-seen high-resolution spatial features that evolve over timescales up to 1 Gyr. The simulation was synchronized to start times and timelines of two observational astronomy surveys: (1) the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) and (2) the Zwicky Transient Facility (ZTF). We calculate upper limits for the number of ETAs potentially observable with both the ZTF and LSST surveys. Due to the Yarkovsky Effect, we find no stable ETAs on billion-year timescales likely to be detected by any ETA survey, as no C-type or S-type ETAs (with H < 22 and H < 24, respectively) are likely to be stable on billion-year timescales, and ETAs large enough to remain stable on billion-year timescales are very rare relative to the rest of the ETA population. We find that a twilight ETA survey will not drastically increase the likelihood of individual ETA detection, but it would provide orders of magnitude more observations of select ETA populations. The null detection to date from ZTF restricts the potential ETA population to hundreds of objects larger than 100 m (at H ≈ 22), while a null detection by LSST will further restrict the ETA population to tens of objects larger than 100 m.

79 ASTRONOMY AND ASTROPHYSICS↗

A Systematic Search for MeV–GeV Pulsar Wind Nebulae without Gamma-Ray Detected Pulsars

An increasing number of pulsar wind nebulae (PWNe) are being identified in the TeV band by ground-based Imaging Air Cherenkov Telescopes such that they constitute the dominant source class of Galactic TeV emitters. However, MeV–GeV PWN counterparts are still largely lacking. To date, only a dozen PWNe are identified by the Fermi–Large Area Telescope (LAT) in the MeV–GeV band. Most PWNe are located along the Galactic plane embedded within the prominent, diffuse Galactic γ-ray emission, which makes these sources difficult to disentangle from the bright diffuse background. We present a systematic search for γ-ray counterparts to known PWNe in the 300 MeV–2 TeV energy band using the Fermi–LAT. We target the locations of previously identified PWNe that lack detected Fermi–LAT pulsars to minimize associated pulsar contamination. The sample includes six previously identified Fermi PWNe and eight Fermi–LAT sources associated with PWNe. We report the analysis of 58 regions of interest and classify Fermi–LAT detected sources as either a likely PWN or a candidate PWN counterpart based on their morphological and spectral characteristics across the broadband spectrum. There are nine unidentified Fermi–LAT sources that we consider as likely PWN counterparts, which, if confirmed to be PWNe, would greatly increase the PWN population detected by the Fermi–LAT from 12 to 21. The remaining Fermi–LAT detected sources are considered weaker PWN candidates. A second approach in the systematic search for γ-ray emitting PWNe will involve studying the off-pulse phases of Fermi–LAT detected pulsars for the presence of an obscured PWN and will be reported in a subsequent paper.

Acharyya, A. [Univ. of Southern Denmark, Odense (D↗

Advanced Intra-Cycle Detection of Pre-Ignition Events through Phase-Space Transforms of Cylinder Pressure Data

The widespread adoption of boosted, downsized SI engines has brought pre-ignition phenomena into greater focus, as the knock events resulting from pre-ignitions can cause significant hardware damage. Much attention has been given to understanding the causes of pre-ignition and identify lubricant or fuel properties and engine design and calibration considerations that impact its frequency. This helps to shift the pre-ignition limit to higher specific loads and allow further downsizing but does not fundamentally eliminate the problem. Real-time detection and mitigation of pre-ignition would thus be desirable to allow safe engine operation in pre-ignition-prone conditions. This study focuses on advancing the time of detection of pre-ignition in an engine cycle where it occurs. Furthermore, phase space transforms through time-delay embedding of cylinder pressure and principal component analysis were applied to same-cycle detection of pre-ignition and shown to enable detection on the order of a crank degree earlier than deviation in cylinder pressure can be identified through direct statistical observation of the pressure data. Additionally, it appears that the deviation of the trajectory in phase space may offer the opportunity to extend this method to further extend the detection window and allow more time for mitigation actions to occur.

42 ENGINEERING↗

Remote-sensing detectability of airborne Arctic dust

Remote-sensing (RS)-based estimates of Arctic dust are oftentimes overestimated due to a failure in separating out the dust contribution from that of spatially homogeneous clouds or low-altitude cloud-like plumes. A variety of illustrations are given with a particular emphasis on questionable claims of using brightness temperature differences (BTDs) as a signature indicator of Arctic dust transported from mid-latitude deserts or generated by local Arctic sources. While there is little dispute about the presence of both Asian and local dust across the Arctic, the direct RS detectability of airborne dust, as ascribed to satellite (MODIS and AVHRR) measurements of significantly negative brightness temperature differences at 11 and 12 µm (BTD 11–12 ), has been misrepresented in certain cases. While it is difficult to account for all examples of strongly negative BTD 11–12 values in the Arctic, it is unlikely that airborne dust plays a significant role. One much more likely contributor would be water clouds in the Arctic inversion layer. The RS detectability of the impact of Arctic dust (notably due to Arctic dust from local sources) can, however, be of significance. Sustained dust deposition can substantially decrease (visible to shortwave IR) snow and ice reflectance albedo (pan-chromatic reflectance) and the signal measured by satellite sensors. Significantly negative BTD 11–12 values would, however, only represent a limited area near the drainage basin sources according to our event-level case studies. The enhanced ice-nucleating particle (INP) role of local Arctic dust can, for example, induce significant changes in the properties of low-level mixed-phase clouds (cloud optical depth changes <~ 1) that can readily be detected by active and passive RS instruments. It is critical that the distinction between the RS detectability of airborne Arctic dust versus the RS detectability of the impacts of that dust be understood if we are to appropriately parameterize, for example, the radiative forcing influence of dust in this climate-sensitive region.

54 ENVIRONMENTAL SCIENCES↗

Detection of small drizzle droplets in a large cloud chamber using ultrahigh-resolution radar

Abstract. A large convection–cloud chamber has the potential to produce drizzle-sized droplets, thus offering a new opportunity to investigate aerosol–cloud–drizzle interactions at a fundamental level under controlled environmental conditions. One key measurement requirement is the development of methods to detect the low-concentration drizzle drops in such a large cloud chamber. In particular, remote sensing methods may overcome some limitations of in situ methods. Here, the potential of an ultrahigh-resolution radar to detect the radar return signal of a small drizzle droplet against the cloud droplet background signal is investigated. It is found that using a small sampling volume is critical to drizzle detection in a cloud chamber to allow a drizzle drop in the radar sampling volume to dominate over the background cloud droplet signal. For instance, a radar volume of 1 cubic centimeter (cm3) would enable the detection of drizzle embryos with diameter larger than 40 µm. However, the probability of drizzle sampling also decreases as the sample volume reduces, leading to a longer observation time. Thus, the selection of radar volume should consider both the signal power and the drizzle occurrence probability. Finally, observations from the Pi Convection–Cloud Chamber are used to demonstrate the single-drizzle-particle detection concept using small radar volume. The results presented in this study also suggest new applications of ultrahigh-resolution cloud radar for atmospheric sensing.

54 ENVIRONMENTAL SCIENCES↗

Investigating lab-scaled offshore wind aerodynamic testing failure and developing solutions for early anomaly detections

As offshore wind systems become more complex, the risk of human error or equipment malfunction increases during experimental testing. This study investigates a lab-scale incident involving a 1 : 50 scale 5 MW wind turbine, where a generator failure led to rotor overspeed and a blade–tower strike. To improve early fault detection, we propose a data-driven method based on multivariate long short-term memory (LSTM) models. High-frequency measurements are projected onto principal components, and anomalies are identified using reconstruction error and its time derivative. Two models are trained on different healthy datasets and tested using single- and multi-principal component (1PC and MPC) variations. Results show that combining both error and error derivative improves detection accuracy. The 1PC model detects faults faster, has a higher recall rate, and achieves a 43 % improvement in anomaly detection accuracy, while the MPC model yields higher precision. This approach provides a simple and effective tool for early anomaly detection in lab-scale experiments, helping to reduce the risk of future failures during the testing of new technologies.

17 WIND ENERGY↗

Accurate in vivo tumor detection using plasmonic-enhanced shifted-excitation Raman difference spectroscopy (SERDS)

For the majority of cancer patients, surgery is the primary method of treatment. In these cases, accurately removing the entire tumor without harming surrounding tissue is critical; however, due to the lack of intraoperative imaging techniques, surgeons rely on visual and physical inspection to identify tumors. Surface-enhanced Raman scattering (SERS) is emerging as a non-invasive optical alternative for intraoperative tumor identification, with high accuracy and stability. However, Raman detection requires dark rooms to work, which is not consistent with surgical settings. Methods: Herein, we used SERS nanoprobes combined with shifted-excitation Raman difference spectroscopy (SERDS) detection, to accurately detect tumors in xenograft murine model. Results: We demonstrate for the first time the use of SERDS for in vivo tumor detection in a murine model under ambient light conditions. We compare traditional Raman detection with SERDS, showing that our method can improve sensitivity and accuracy for this task. Conclusion: Our results show that this method can be used to improve the accuracy and robustness of in vivo Raman/SERS biomedical application, aiding the process of clinical translation of these technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optical Production and Detection of Ultrasonic Waves in Metals for Nondestructive Testing

Ultrasonic waves were produced by striking the surface of a metal with the focused one-joule pulse of a Q-switched ruby laser. Rayleigh (surface) waves and longitudinal waves were detected with conventional transducers. Optical methods of detection were tested and developed. Rayleigh waves were produced with an oscillator and transducer. They were optically detected on curved polished surfaces, and on unpolished surfaces. The technique uses a knife edge to detect small angle changes of the surface as the wave pulse passes the illuminated spot. Optical flaw detection using pulse echo and attenuation is demonstrated.

Morrison, R. A.↗

Single photon detection and timing - Experiments and techniques.

Single photon detection and timing means essentially the detection and timing of a single photoelectron released by light from a photosensitive surface of a photomultiplier, channel multiplier, avalanche multiplier photodiode, or other photodevice. Necessary photodevice gain and detection circuits, mechanisms and statistics of photodevice gain, photodevice and background noise and their reduction, and practical photodevice techniques and photon detection performance tests are discussed. Fast timing with single photons, and single photon detection with moderate timing requirements are considered.

Poultney, S. K.↗

Threshold detection in an on-off binary communications channel with atmospheric scintillation

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Webb, W. E.↗

A noise study of the A-6 airplane and techniques for reducing its aural detection distance

A study was undertaken to determine the noise reduction potential of the A-6 airplane in order to reduce its aural detection distance. Static and flyby noise measurements were taken to document the basic airplane signature. The low-frequency noise which is generally most critical for aural detection was found to be broad-band in nature from this airplane, and its source is the turbojet engine exhaust. High-frequency compressor noise, which is characteristic of turbojet powerplants, and which is prominent at close range for this airplane, has no measurable effect on aural detection distance. The use of fluted-engine exhaust nozzles to change the far-field noise spectra is suggested as a possible means for reducing the aural detection distances. Detection distances associated with eight-lobe and four-lobe nozzles are estimated for a 1,000-foot altitude and grassy terrain to decrease from 4 miles to about 3 miles, and from 3 miles to about 2 miles for a 300-foot altitude and grassy terrain.

Hilton, D. A.↗