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1
Vivas, A. Katherina, Alistair R. Walker, Clara E. Martínez-Vázquez, Matteo Monelli, Giuseppe Bono, Antonio Dorta, David L. Nidever, et al. "A DECam view of the diffuse dwarf galaxy Crater II – Variable stars." Monthly Notices of the Royal Astronomical Society 492, no. 1 (December 4, 2019): 1061–77. http://dx.doi.org/10.1093/mnras/stz3393.
Повний текст джерелаАнотація:
ABSTRACT Time series observations of a single dithered field centred on the diffuse dwarf satellite galaxy Crater II were obtained with the Dark Energy Camera (DECam) at the 4m Blanco Telescope at Cerro Tololo Inter-American Observatory, Chile, uniformly covering up to two half-light radii. Analysis of the g and i time series results in the identification and characterization of 130 periodic variable stars, including 98 RR Lyrae stars, 7 anomalous Cepheids, and 1 SX Phoenicis star belonging to the Crater II population, and 24 foreground variables of different types. Using the large number of ab-type RR Lyrae stars present in the galaxy, we obtained a distance modulus to Crater II of (m − M)0 = 20.333 ± 0.004 (stat) ±0.07 (sys). The distribution of the RR Lyrae stars suggests an elliptical shape for Crater II, with an ellipticity of 0.24 and a position angle of 153°. From the RR Lyrae stars, we infer a small metallicity dispersion for the old population of Crater II of only 0.17 dex. There are hints that the most metal-poor stars in that narrow distribution have a wider distribution across the galaxy, while the slightly more metal-rich part of the population is more centrally concentrated. Given the features in the colour–magnitude diagram of Crater II, the anomalous Cepheids in this galaxy must have formed through a binary evolution channel of an old population.
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De la Torre, Gabriel G. "Evaluation of Several Computer Vision Feature Detectors/Extractors on Ahuna Mons Region in Ceres and Its Implications for Technosignatures Search." Vision 6, no. 3 (August 31, 2022): 54. http://dx.doi.org/10.3390/vision6030054.
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Ahuna Mons is a 4 km particular geologic feature on the surface of Ceres, of possibly cryovolcanic origin. The special characteristics of Ahuna Mons are also interesting in regard of its surrounding area, especially for the big crater beside it. This crater possesses similarities with Ahuna Mons including diameter, age, morphology, etc. Under the cognitive psychology perspective and using current computer vision models, we analyzed these two features on Ceres for comparison and pattern-recognition similarities. Speeded up robust features (SURF), oriented features from accelerated segment test (FAST), rotated binary robust independent elementary features (BRIEF), Canny edge detector, and scale invariant feature transform (SIFT) algorithms were employed as feature-detection algorithms, avoiding human cognitive bias. The 3D analysis of images of both features’ (Ahuna Mons and Crater B) characteristics is discussed. Results showed positive results for these algorithms about the similarities of both features. Canny edge resulted as the most efficient algorithm. The 3D objects of Ahuna Mons and Crater B showed good-fitting results. Discussion is provided about the results of this computer-vision-techniques experiment for Ahuna Mons. Results showed the potential for the computer vision models in combination with 3D imaging to be free of bias and to detect potential geoengineered formations in the future. This study also brings forward the potential problem of both human and cognitive bias in artificial-intelligence-based models and the risks for the task of searching for technosignatures.
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Rossi, Alessandro, Francesco Marzari, John Robert Brucato, Vincenzo Della Corte, Elisabetta Dotto, Simone Ieva, Stavro Lambrov Ivanovski, et al. "Dynamical Evolution of Ejecta from the DART Impact on Dimorphos." Planetary Science Journal 3, no. 5 (May 1, 2022): 118. http://dx.doi.org/10.3847/psj/ac686c.
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Abstract The DART spacecraft will impact Dimorphos (the secondary body of the Didymos binary asteroid) to test the kinetic impactor deflection method against possibly hazardous near-Earth asteroids. The DART impact ejecta plume, and possibly the impact crater, will be imaged by the LICIACube spacecraft, hosted as a piggyback and released by DART just before the impact, and then, several years later, by the Hera probe. To exploit the wealth of data obtained and understand the physics of the whole impact experiment, it is of paramount importance to properly model the dynamics of the binary system pre- and postimpact and the dynamics of the particles ejected from the impact crater. A model was developed to simulate the evolution of the ejecta particles created during the impact in order to first interpret the LICIACube images and then test the survival of particles on long intervals of time that might be detected by the Hera mission either as individual bodies or as parts of rings. The dynamical evolution of the particles is simulated over different timescales to highlight the most important perturbations and their relative importance. The ejecta dynamics turns out to be highly chaotic due to repeated close encounters with the two asteroids. However, we find that some ejecta survive in the binary orbital environment for timescales comparable to the Hera arrival time. The effects of the particles reimpacting against either one of the components is also analyzed to estimate the amount of momentum transfer to the target bodies.
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Scharringhausen, Marco, and Lars Witte. "An Efficient and Lightweight Illumination Model for Planetary Bodies Including Direct and Diffuse Radiation." Journal of Imaging 6, no. 9 (August 24, 2020): 84. http://dx.doi.org/10.3390/jimaging6090084.
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We present a numerical illumination model to calculate direct as well as diffuse or Hapke scattered radiation scenarios on arbitrary planetary surfaces. This includes small body surfaces such as main belt asteroids as well as e.g., the lunar surface. The model is based on the ray tracing method. This method is not restricted to spherical or ellipsoidal shapes but digital terrain data of arbitrary spatial resolution can be fed into the model. Solar radiation is the source of direct radiation, wavelength-dependent effects (e.g. albedo) can be accounted for. Mutual illumination of individual bodies in implemented (e.g. in binary or multiple systems) as well as self-illumination (e.g. crater floors by crater walls) by diffuse or Hapke radiation. The model is validated by statistical methods. A χ2 test is utilized to compare simulated images with DAWN images acquired during the survey phase at small body 4 Vesta and to successfully prove its validity.
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Agasheva, Elena. "Magmatic Material in Sandstone Shows Prospects for New Diamond Deposits within the Northern East European Platform." Minerals 11, no. 4 (March 25, 2021): 339. http://dx.doi.org/10.3390/min11040339.
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A detailed study of sandstones recovered from the upper part of the recently discovered KL-01 magmatic pipe in the southern part of the Arkhangelsk diamondiferous province (ADP), containing magmatic material and rare kimberlite indicator minerals, is presented in this paper. Results are compared to the composition of crater samples of the highly diamondiferous Vladimir Grib kimberlite pipe and several poorly to non-diamondiferous ADP pipes. To identify the type of magmatic material admixture, a model of binary mixing between country Vendian sandstones and typical ADP magmatic rocks based on correlations of La/Yb and Zr/Nb ratios and Ni contents is proposed. The modeling results show that the type of magmatic component in the KL-01 samples can be identified as kimberlite, with a maximum admixture of 20 vol.%. Kimberlite indicator mineral geochemistry did not exclude the interpretation that the composition, structure, thermal state and metasomatic enrichment of the lithospheric mantle sampled by the KL-01 pipe were suitable for the formation and preservation of diamonds. The lower boundary of the sampled lithospheric mantle could be in the depth range of 175–190 km, with a diamond window width of 55–70 km. Thus, the sandstones could represent the upper level of the crater of a new kimberlite pipe.
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Lee, Seungyun, Doyun Lee, Kyungmin Lee, Chan Park, Hyunphil Lim, Sangwon Park, Lee Kyungku, and Kwidug Yun. "Evaluation of Bioabsorbable Mg–Mn Alloy with Anodic Oxidation Treatment." Journal of Nanoscience and Nanotechnology 20, no. 9 (September 1, 2020): 5625–28. http://dx.doi.org/10.1166/jnn.2020.17671.
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Magnesium alloys as biodegradable materials have been examined that may replace bone screws and plates in recent studies. But the velocity control of magnesium alloy is very difficult. Until now, the magnesium alloys degrade very fast, thus it couldn’t maintain the function in clinical field. Thus the purpose of this study is to evaluate the degradability of anodized magnesium alloy for control the velocity. For this experiment, a Mg–xMn (x = 0, 0.5, 1 wt%) binary alloy was cast in argon gas (99.99%) atmosphere. The specimens of the surface treatment group were anodized for 15 minutes at a voltage of 120 V at room temperature using calcium gluconate, sodium hexametaphosphate, and sodium hydroxide electrolyte. For the mechanical test, SEM, roughness test, hardness test were examined. The degradation test was conducted to measure the hydrogen gas formation volume. For biologic test, cell viability were tested. After anodic oxidation treatment, the surface showed the crater formation, the size of craters were about 200~300 nm. Among nonanodized group, the Mg–0.5Mn showed the highest Vickers hardness and cell viability. However for biodegradability test, Mg–1Mn showed the lowest the hydrogen gas formation. For anodic oxidation treatment, anodic oxidation treatment makes rougher surface, higher hardness, good cell response and lower degradation rate. Overall, anodized Mg–1Mn showed the possibility for clinical application in bone screw and bone plate.
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Hirabayashi, Masatoshi, Fabio Ferrari, Martin Jutzi, Ryota Nakano, Sabina D. Raducan, Paul Sánchez, Stefania Soldini, et al. "Double Asteroid Redirection Test (DART): Structural and Dynamic Interactions between Asteroidal Elements of Binary Asteroid (65803) Didymos." Planetary Science Journal 3, no. 6 (June 1, 2022): 140. http://dx.doi.org/10.3847/psj/ac6eff.
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Abstract NASA's Double Asteroid Redirection Test (DART) mission is the first full-scale planetary defense mission. The target is the binary asteroid (65803) Didymos, in which the smaller component Dimorphos (∼164 m equivalent diameter) orbits the larger component Didymos (∼780 m equivalent diameter). The DART spacecraft will impact Dimorphos, changing the system’s mutual orbit by an amount that correlates with DART's kinetic deflection capability. The spacecraft collision with Dimorphos creates an impact crater, which reshapes the body. Also, some particles ejected from the DART impact site on Dimorphos eventually reach Didymos. Because Didymos’s rapid spin period (2.26 hr) may be close to its stability limit for structural failure, the ejecta reaching Didymos may induce surface disturbance on Didymos. While large uncertainties exist, nonnegligible reshaping scenarios on Didymos and Dimorphos are possible if certain conditions are met. Our analysis shows that given a surface slope uncertainty on Dimorphos of 45°, with no other information about its local topography, and if the DART-like impactor is treated as spherical, the ejecta cone crosses Didymos with speeds ≳14 m s−1 in 13% of simulations. Additional work is necessary to determine the amount of mass delivered to Didymos from the DART impact and whether the amount of kinetic energy delivered is sufficient to overcome cohesive forces in those cases. If nonnegligible (but small) reshaping occurs for either of these asteroids, the resulting orbit perturbation and reshaping are measurable by Earth-based observations.
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Antony, Chakkiath Paul, Nina V. Doronina, Rich Boden, Yuri A. Trotsenko, Yogesh S. Shouche, and J. Colin Murrell. "Methylophaga lonarensis sp. nov., a moderately haloalkaliphilic methylotroph isolated from the soda lake sediments of a meteorite impact crater." International Journal of Systematic and Evolutionary Microbiology 62, Pt_7 (July 1, 2012): 1613–18. http://dx.doi.org/10.1099/ijs.0.035089-0.
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A moderately haloalkaliphilic methylotrophic bacterium possessing the ribulose monophosphate pathway for carbon assimilation, designated MPLT, was isolated from Lonar Lake sediment microcosms that were oxidizing methane for two weeks. The isolate utilized methanol and was an aerobic, Gram-negative, asporogenous, motile, short rod that multiplied by binary fission. The isolate required NaHCO3 or NaCl for growth and, although not auxotrophic for vitamin B12, had enhanced growth with vitamin B12. Optimal growth occurred with 0.5–2 % (w/v) NaCl, at 28–30 °C and at pH 9.0–10.0. The cellular fatty acid profile consisted primarily of straight-chain saturated C16 : 0 and unsaturated C16 : 1ω7c and C18 : 1ω7c. The major ubiquinone was Q-8. The dominant phospholipids were phosphatidylethanolamine, phosphatidylglycerol and diphosphatidylglycerol. Cells accumulated ectoine as the main compatible solute. The DNA G+C content was 50.0 mol%. The isolate exhibited 94.0–95.4 % 16S rRNA gene sequence similarity with the type strains of methylotrophs belonging to the genus Methylophaga and 31 % DNA–DNA relatedness with the reference strain, Methylophaga alcalica VKM B-2251T. It is proposed that strain MPLT represents a novel species, Methylophaga lonarensis sp. nov. (type strain MPLT = VKM B-2684T = MCC 1002T).
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Moshrefifar, Masoud, Hadi Ebrahimifar, and Amin Hakimizad. "Systematic Investigation of Silicon Content Effects on the PEO Coatings’ Properties on Al–Si Binary Alloys in Silicate-Based and Tungstate-Containing Electrolytes." Coatings 12, no. 10 (September 30, 2022): 1438. http://dx.doi.org/10.3390/coatings12101438.
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The present study evaluates the effect of a substrate’s silicon content on the coatings’ morphology, structure, and properties in an electrolyte containing sodium tungstate on Al–xSi alloys. The PEO-coated samples demonstrated the structure of the pancake and crater with irregular micro-cracks and micro-pores. The incorporation of the element W in the coatings decreased the surface roughness and porosity due to increasing the electrolyte conductivity and, hence, decreasing the breakdown voltage and intensity of micro-discharges. The friction coefficient of all the coatings stayed constant during the wear test due to the contact of the ball with the inner layer with less porosity and higher micro-hardness. The track depth to the thickness ratio of the coatings was found to be 0.60–0.75 for those without additive coatings and 0.55–0.65 for those with additive coatings. As a result, the higher wear rates, volume losses, track widths, and depths in the specimens with a lower silicon content of the substrate were found due to the greater thickness of the coating and the outer sublayer for both specimens with and without Na2WO4. The coatings formed using the W-containing electrolyte showed a higher micro-hardness and a lower wear rate in comparison with the coatings produced in the silicate-based electrolyte.
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Nakano, Ryota, Masatoshi Hirabayashi, Harrison F. Agrusa, Fabio Ferrari, Alex J. Meyer, Patrick Michel, Sabina D. Raducan, Paul Sánchez, and Yun Zhang. "NASA’s Double Asteroid Redirection Test (DART): Mutual Orbital Period Change Due to Reshaping in the Near-Earth Binary Asteroid System (65803) Didymos." Planetary Science Journal 3, no. 7 (July 1, 2022): 148. http://dx.doi.org/10.3847/psj/ac7566.
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Abstract The Double Asteroid Redirection Test (DART) is the first planetary defense mission to demonstrate the kinetic deflection technique. The DART spacecraft will collide with the asteroid Dimorphos, the smaller component of the binary asteroid system (65803) Didymos. The DART impact will excavate surface/subsurface materials of Dimorphos, leading to the formation of a crater and/or some magnitude of reshaping (i.e., shape change without significant mass loss). The ejecta may eventually hit Didymos’s surface. If the kinetic energy delivered to the surface is high enough, reshaping may also occur in Didymos, given its near-critical spin rate. Reshaping on either body will modify the mutual gravitational field, leading to a reshaping-induced orbital period change, in addition to the impact-induced orbital period change. If left unaccounted for, this could lead to an erroneous interpretation of the effect of the kinetic deflection technique. Here we report the results of full two-body problem simulations that explore how reshaping influences the mutual dynamics. In general, we find that the orbital period becomes shorter linearly with increasing reshaping magnitude. If Didymos’s shortest axis shrinks by ∼0.7 m, or Dimorphos’s intermediate axis shrinks by ∼2 m, the orbital period change would be comparable to the Earth-based observation accuracy, ∼7.3 s. Constraining the reshaping magnitude will decouple the reshaping- and impact-induced orbital period changes; Didymos’s reshaping may be constrained by observing its spin period change, while Dimorphos’s reshaping will likely be difficult to constrain but will be investigated by the ESA's Hera mission that will visit Didymos in late 2026.
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Richardson, Derek C., Harrison F. Agrusa, Brent Barbee, William F. Bottke, Andrew F. Cheng, Siegfried Eggl, Fabio Ferrari, et al. "Predictions for the Dynamical States of the Didymos System before and after the Planned DART Impact." Planetary Science Journal 3, no. 7 (July 1, 2022): 157. http://dx.doi.org/10.3847/psj/ac76c9.
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Abstract NASA’s Double Asteroid Redirection Test (DART) spacecraft is planned to impact the natural satellite of (65803) Didymos, Dimorphos, at around 23:14 UTC on 2022 September 26, causing a reduction in its orbital period that will be measurable with ground-based observations. This test of kinetic impactor technology will provide the first estimate of the momentum transfer enhancement factor β at a realistic scale, wherein the ejecta from the impact provide an additional deflection to the target. Earth-based observations, the LICIACube spacecraft (to be detached from DART prior to impact), and ESA’s follow-up Hera mission, to launch in 2024, will provide additional characterizations of the deflection test. Together, Hera and DART comprise the Asteroid Impact and Deflection Assessment cooperation between NASA and ESA. Here, the predicted dynamical states of the binary system upon arrival and after impact are presented. The assumed dynamically relaxed state of the system will be excited by the impact, leading to an increase in eccentricity and a slight tilt of the orbit, together with enhanced libration of Dimorphos, with the amplitude dependent on the currently poorly known target shape. Free rotation around the moon’s long axis may also be triggered, and the orbital period will experience variations from seconds to minutes over timescales of days to months. Shape change of either body, due to cratering or mass wasting triggered by crater formation and ejecta, may affect β, but can be constrained through additional measurements. Both BYORP and gravity tides may cause measurable orbital changes on the timescale of Hera’s rendezvous.
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Miljković, Katarina, Gareth S. Collins, Sahil Mannick, and Philip A. Bland. "Morphology and population of binary asteroid impact craters." Earth and Planetary Science Letters 363 (February 2013): 121–32. http://dx.doi.org/10.1016/j.epsl.2012.12.033.
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Bottke, Jr., William F., and H. Jay Melosh. "Binary Asteroids and the Formation of Doublet Craters." Icarus 124, no. 2 (December 1996): 372–91. http://dx.doi.org/10.1006/icar.1996.0215.
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Antoshkina, A. I., I. G. Dobretsova, V. I. Silaev, D. V. Kiseleva, V. N. Filippov, I. V. Smoleva, and N. V. Cherednichenko. "Deep-sea organogenic-carbonate buildups in the northern zone of the Mid-Atlantic Ridge." LITHOSPHERE (Russia) 22, no. 6 (January 5, 2023): 761–82. http://dx.doi.org/10.24930/1681-9004-2022-22-6-761-782.
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Research subject. Carbonate formations raised from depths up 1986 to 2973 m in the off-axis zone of the rift valley of the North Atlantic Ocean in areas of active young volcanism. The ocean floor here is composed of basaltoids and serpentinized gabbro-peridotites fragmentarily overlain by carbonate pelagic sediments.Aim. To confirm the organogenic nature of these carbonate formations and to reveal new features of deep-water carbonate structures of this type.Materials and methods. The research objects comprised 100 samples of branched and cone-shaped/crater-like carbonate formations, the primary studies of which were carried out directly on the research vessel. Analytical methods included optical microscopy, electron microscopy, X-ray fluorescence spectroscopy, X-ray diffractometry, infrared spectroscopy, inductively coupled plasma mass spectrometry, and isotope mass spectrometry.Results. Among the most important features of the studied formations were found to be a concentric-zonal structure, which forms around the axial channel, and a thin dark brown crust of carbonate-ferromanganese composition. The abundance of planktonic fauna fossils and the distribution of mineralized biofilms with bacteriomorphic structures and glycocalyx were found in the body of crusts of the studied formations. More than 50 trace elements were found, including 11 essential (vital), 18 physiogenicallly-active and 22 antibiotic elements. The ratios of group contents of essential and antibiotic elements vary from 0.67 in the upper part of the structures to 0.001 in their lower part and up to 0.0006 in the volcanogenic substrate of the carbonate buildups. The ratio of the concentrations of essential zinc to physiogenically-active copper behaves similarly. In calcite, the isotopic composition of carbon, δ13СPDB = = –0.16 ± 1.03‰, corresponds to marine sedimentary carbonates; conversely, while oxygen exhibits anomalously isotopically heavy values, δ18OSMOW = 34.44 ± 3.21‰. In ferromanganese carbonates, the corresponding values are –3…1 and 32– 35‰.Conclusions. The studied carbonate formations are solid solutions based on calcite in their body and based on siderite-rhodochrosite binary series in the composition of brown crusts. Specific features of the chemism and minal compatibility of carbonate solid solutions reflect the conditions of microbially-stimulated mineral formation. The conducted isotopic studies discovered the phenomenon of a combination of carbon and oxygen, fundamentally different in genetic nature, in the studied formations. For the explanation of this fact, a scheme for isotopic exchange of oxygen between marine bicarbonate and sulfate with the active participation of sulfate-reducing bacteria was proposed.
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Ren, Zi Hao, Hong Kun Jiang, Wen Liang Du, Xiao Lin Tian, and Ao Ao Xu. "A New Auto-Extraction Algorithm of Lunar Craters for Chang’E Data Based on the Solar Incidence Angle." Applied Mechanics and Materials 599-601 (August 2014): 1333–39. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.1333.
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A new algorithm for detecting lunar craters based on the solar incidence angle has been proposed, which converts the Chang’E CCD images to binary images first by detecting edges in the Chang’E CCD images, then the new algorithm calculates the average angle of the solar incidence angles of each edge, Comparing the average angle of each edge with the solar incidence angle of the whole image to delete those noise/false edges of craters. Finally, the common circle fitting has been implemented to detect craters from those edge images. The new algorithm proposed has been tested on different Mare areas and all testing results had shown that the new algorithm could get a satisfying effect.
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Melosh, H. J., and J. A. Stansberry. "Doublet craters and the tidal disruption of binary asteroids." Icarus 94, no. 1 (November 1991): 171–79. http://dx.doi.org/10.1016/0019-1035(91)90148-m.
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Yang, B., J. Hanuš, B. Carry, P. Vernazza, M. Brož, F. Vachier, N. Rambaux, et al. "Binary asteroid (31) Euphrosyne: ice-rich and nearly spherical." Astronomy & Astrophysics 641 (September 2020): A80. http://dx.doi.org/10.1051/0004-6361/202038372.
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Aims. Asteroid (31) Euphrosyne is one of the biggest objects in the asteroid main belt and it is also the largest member of its namesake family. The Euphrosyne family occupies a highly inclined region in the outer main belt and contains a remarkably large number of members, which is interpreted as an outcome of a disruptive cratering event. Methods. The goals of this adaptive-optics imaging study are threefold: to characterize the shape of Euphrosyne, to constrain its density, and to search for the large craters that may be associated with the family formation event. Results. We obtained disk-resolved images of Euphrosyne using SPHERE/ZIMPOL at the ESO 8.2 m VLT as part of our large program (ID: 199.C-0074, PI: Vernazza). We reconstructed its 3D shape via the ADAM shape modeling algorithm based on the SPHERE images and the available light curves of this asteroid. We analyzed the dynamics of the satellite with the Genoid meta-heuristic algorithm. Finally, we studied the shape of Euphrosyne using hydrostatic equilibrium models. Conclusions. Our SPHERE observations show that Euphrosyne has a nearly spherical shape with the sphericity index of 0.9888 and its surface lacks large impact craters. Euphrosyne’s diameter is 268 ± 6 km, making it one of the top ten largest main belt asteroids. We detected a satellite of Euphrosyne – S/2019 (31) 1 – that is about 4 km across, on a circular orbit. The mass determined from the orbit of the satellite together with the volume computed from the shape model imply a density of 1665 ± 242 kg m−3, suggesting that Euphrosyne probably contains a large fraction of water ice in its interior. We find that the spherical shape of Euphrosyne is a result of the reaccumulation process following the impact, as in the case of (10) Hygiea. However, our shape analysis reveals that, contrary to Hygiea, the axis ratios of Euphrosyne significantly differ from those suggested by fluid hydrostatic equilibrium following reaccumulation.
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Spencer, J. R., S. A. Stern, J. M. Moore, H. A. Weaver, K. N. Singer, C. B. Olkin, A. J. Verbiscer, et al. "The geology and geophysics of Kuiper Belt object (486958) Arrokoth." Science 367, no. 6481 (February 13, 2020): eaay3999. http://dx.doi.org/10.1126/science.aay3999.
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The Cold Classical Kuiper Belt, a class of small bodies in undisturbed orbits beyond Neptune, is composed of primitive objects preserving information about Solar System formation. In January 2019, the New Horizons spacecraft flew past one of these objects, the 36-kilometer-long contact binary (486958) Arrokoth (provisional designation 2014 MU69). Images from the flyby show that Arrokoth has no detectable rings, and no satellites (larger than 180 meters in diameter) within a radius of 8000 kilometers. Arrokoth has a lightly cratered, smooth surface with complex geological features, unlike those on previously visited Solar System bodies. The density of impact craters indicates the surface dates from the formation of the Solar System. The two lobes of the contact binary have closely aligned poles and equators, constraining their accretion mechanism.
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Zhou, Li, Yu Zhong Li, and Cheng Yong Wang. "Study on Arithmetic of Surface Damage Ratio in High Speed Machining of Graphite Based on Matlab Image Processing." Advanced Materials Research 652-654 (January 2013): 2196–99. http://dx.doi.org/10.4028/www.scientific.net/amr.652-654.2196.
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The surface quality of graphite cannot be completely evaluated only by the roughness value Ra measured by profilometer. The surface damage ratio Sc is presented to give quantitative description of surface quality of graphite, which was calculated as the ratio of the projection area of fracture craters to the overall area of free surface. The machined surface was observed and taken photo by use of the stereo microscope with CCD image acquisition system. Matlab image processing tool was used to convert the color photo to binary image, in which fracture craters were shown as black pixels and the other surfaces as white pixels. The surface damage ratio is the result of the sum of black pixels divided by the overall pixels. Under the same conditions of high speed machining experiments for verification, the surface damage ratio was calculated in comparison with the Ra values measured by profilometer. The variation tendency of surface damage ratios exhibited good coherence to the measured roughness.
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Liu, Guang Zu, and Jian Xin Wang. "Improved SNR Estimation Technique for BPSK and QPSK Signals." Applied Mechanics and Materials 239-240 (December 2012): 994–99. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.994.
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To improve the estimation accuracy of non-data-aided (NDA) signal-to-noise ratio (SNR) estimators at low SNR value, A novel estimation technique for binary phase-shift keying and quadrature phase-shift keying signals in complex additive white Gaussian noise channel is proposed. The mathematical relation between SNR and the ratio of two simple statistical computations is derived, then SNR is determined by looking up a table. Its accuracy surpasses other NDA estimators, approaching closely to the Cramer-Rao lower bound at SNR > 5dB.
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Company-Corcoles, Joan P., Emilio Garcia-Fidalgo, and Alberto Ortiz. "Appearance-based loop closure detection combining lines and learned points for low-textured environments." Autonomous Robots 46, no. 3 (February 9, 2022): 451–67. http://dx.doi.org/10.1007/s10514-021-10032-7.
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AbstractHand-crafted point descriptors have been traditionally used for visual loop closure detection. However, in low-textured environments, it is usually difficult to find enough point features and, hence, the performance of such algorithms degrade. Under this context, this paper proposes a loop closure detection method that combines lines and learned points to work, particularly, in scenarios where hand-crafted points fail. To index previous images, we adopt separate incremental binary Bag-of-Words (BoW) schemes for points and lines. Moreover, we adopt a binarization procedure for features’ descriptors to benefit from the advantages of learned features into a binary BoW model. Furthermore, image candidates from each BoW instance are merged using a novel query-adaptive late fusion approach. Finally, a spatial verification stage, which integrates appearance and geometry perspectives, allows us to enhance the global performance of the method. Our approach is validated using several public datasets, outperforming other state-of-the-art solutions in most cases, especially in low-textured scenarios.
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Yoshikawa, M., A. Fujiwara, and J. Kawaguchi. "The nature of asteroid Itokawa revealed by Hayabusa." Proceedings of the International Astronomical Union 2, S236 (August 2006): 401–16. http://dx.doi.org/10.1017/s174392130700350x.
Повний текст джерелаАнотація:
AbstractThe spacecraft Hayabusa, which was launched in 2003, arrived at its destination, asteroid (25143) Itokawa in September 2005. The appearance of Itokawa, a small S-type near Earth asteroids, was totally unexpected. The surface is covered with a lot of boulders and there are only a few craters on it. It looks like a contact binary asteroid. The surface composition is quite similar to LL-chondrite. The estimated density is 1.9 ± 0.13 (g/cm3), so the macro-porosity is about 40%. This means that Itokawa is a rubble pile object. In Itokawa, we may see such things that are very close to building blocks of asteroids. In this paper, we review the mission and the first scientific results.
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He, Chu, Qingyi Zhang, Tao Qu, Dingwen Wang, and Mingsheng Liao. "Remote Sensing and Texture Image Classification Network Based on Deep Learning Integrated with Binary Coding and Sinkhorn Distance." Remote Sensing 11, no. 23 (December 3, 2019): 2870. http://dx.doi.org/10.3390/rs11232870.
Повний текст джерелаАнотація:
In the past two decades, traditional hand-crafted feature based methods and deep feature based methods have successively played the most important role in image classification. In some cases, hand-crafted features still provide better performance than deep features. This paper proposes an innovative network based on deep learning integrated with binary coding and Sinkhorn distance (DBSNet) for remote sensing and texture image classification. The statistical texture features of the image extracted by uniform local binary pattern (ULBP) are introduced as a supplement for deep features extracted by ResNet-50 to enhance the discriminability of features. After the feature fusion, both diversity and redundancy of the features have increased, thus we propose the Sinkhorn loss where an entropy regularization term plays a key role in removing redundant information and training the model quickly and efficiently. Image classification experiments are performed on two texture datasets and five remote sensing datasets. The results show that the statistical texture features of the image extracted by ULBP complement the deep features, and the new Sinkhorn loss performs better than the commonly used softmax loss. The performance of the proposed algorithm DBSNet ranks in the top three on the remote sensing datasets compared with other state-of-the-art algorithms.
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Logachov, A., A. Mogulskii, and A. Yambartsev. "Limit theorems for chains with unbounded variable length memory which satisfy Cramer condition." ESAIM: Probability and Statistics 26 (2022): 152–70. http://dx.doi.org/10.1051/ps/2022002.
Повний текст джерелаАнотація:
We consider a class of variable length Markov chains with a binary alphabet in which context tree is defined by adding finite trees with uniformly bounded height to the vertices of an infinite comb tree. Such type of Markov chain models the spike neuron patterns and also extends the class of persistent random walks. The main interest is the limiting properties of the empirical distribution of symbols from the alphabet. We obtain the strong law of large numbers, central limit theorem, and exact asymptotics for large and moderate deviations. The presence of an intrinsic renewal structure is the subject of discussion in the literature. Proofs are based on the construction of a renewals of the chain and the applying corresponding properties of the compound (or generalized) renewal processes.
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Ying, Qian, and Ye Qingqing. "Deep Supervised Hashing for Fast Multi-Label Image." MATEC Web of Conferences 173 (2018): 03032. http://dx.doi.org/10.1051/matecconf/201817303032.
Повний текст джерелаАнотація:
In this paper, most of the existing Hashing methods is mapping the hand extracted features to binary code, and designing the loss function with the label of images. However, hand-crafted features and inadequacy considering all the loss of the network will reduce the retrieval accuracy. Supervised hashing method improves the similarity between sample and hash code by training data and labels of image. In this paper, we propose a novel deep hashing method which combines the objective function with pairwise label which is produced by the Hamming distance between the label binary vector of images, quantization error and the loss of hashing code between the balanced value as loss function to train network. The experimental results show that the proposed method is more accurate than most of current restoration methods.
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Feng, Jiangfan, and Wenzheng Sun. "Improved Deep Hashing with Scalable Interblock for Tourist Image Retrieval." Scientific Programming 2021 (July 14, 2021): 1–14. http://dx.doi.org/10.1155/2021/9937061.
Повний текст джерелаАнотація:
Tourist image retrieval has attracted increasing attention from researchers. Mainly, supervised deep hash methods have significantly boosted the retrieval performance, which takes hand-crafted features as inputs and maps the high-dimensional binary feature vector to reduce feature-searching complexity. However, their performance depends on the supervised labels, but few labeled temporal and discriminative information is available in tourist images. This paper proposes an improved deep hash to learn enhanced hash codes for tourist image retrieval. It jointly determines image representations and hash functions with deep neural networks and simultaneously enhances the discriminative capability of tourist image hash codes with refined semantics of the accompanying relationship. Furthermore, we have tuned the CNN to implement end-to-end training hash mapping, calculating the semantic distance between two samples of the obtained binary codes. Experiments on various datasets demonstrate the superiority of the proposed approach compared to state-of-the-art shallow and deep hashing techniques.
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Syaubari, Syaubari, and S. Nurdin. "Numerical Solution Of Electrokinetics Mass Transfer Model For Protein Recovery Through Membrane Electrofilter." REAKTOR 7, no. 02 (June 19, 2017): 66. http://dx.doi.org/10.14710/reaktor.7.02.66-69.
Повний текст джерелаАнотація:
Separation based on electrophoresis and electroosmosis (electrokinetics) of binary mixture of proteins (bovine serum albumin-hemoglobin) was studied on a membrane electrofilter. The mixture was separated using ionic polycarbonate membrane with variable studied consist of voltage, current, protein diffusivity, and electrophoresis mobility. Operation parameters were varied to investigate hemoglobin concentration, which pass semi permeable membrane. A model was been derived based on mass transfer principle for the case of unsteady state. For simplification, the model has been modified using Cramer Method with pseudo steady state approach to give the dimentionless form. A program for computer simulation has een written in C/C+ + language. This programming language was shown to have more effective computing ability. Furthermore, using a model and simulation on computer, the result indicates that initial mechanism of electrofilter can also be used to separate and to concentrate protein on their buffer solution.Keywords : electrophoresis, electroosmosis, protein, membrane, electrofilter
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Ibrahim, Y., E. Okafor, and B. Yahaya. "Optimization of RBF-SVM hyperparameters using genetic algorithm for face recognit." Nigerian Journal of Technology 39, no. 4 (March 24, 2021): 1190–97. http://dx.doi.org/10.4314/njt.v39i4.27.
Повний текст джерелаАнотація:
Manual grid-search tuning of machine learning hyperparameters is very time-consuming. Hence, to curb this problem, we propose the use of a genetic algorithm (GA) for the selection of optimal radial-basis-function based support vector machine (RBF-SVM) hyperparameters; regularization parameter C and cost-factor γ. The resulting optimal parameters were used during the training of face recognition models. To train the models, we independently extracted features from the ORL face image dataset using local binary patterns (handcrafted) and deep learning architectures (pretrained variants of VGGNet). The resulting features were passed as input to either linear-SVM or optimized RBF-SVM. The results show that the models from optimized RBFSVM combined with deep learning or hand-crafted features yielded performances that surpass models obtained from Linear-SVM combined with the aforementioned features in most of the data splits. The study demonstrated that it is profitable to optimize the hyperparameters of an SVM to obtain the best classification performance.
Keywords: Face Recognition, Feature Extraction, Local Binary Patterns, Transfer Learning, Genetic Algorithm and Support Vector Machines.
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Kreiner, Welf Alfred. "First Digits’ Shannon Entropy." Entropy 24, no. 10 (October 3, 2022): 1413. http://dx.doi.org/10.3390/e24101413.
Повний текст джерелаАнотація:
Related to the letters of an alphabet, entropy means the average number of binary digits required for the transmission of one character. Checking tables of statistical data, one finds that, in the first position of the numbers, the digits 1 to 9 occur with different frequencies. Correspondingly, from these probabilities, a value for the Shannon entropy H can be determined as well. Although in many cases, the Newcomb–Benford Law applies, distributions have been found where the 1 in the first position occurs up to more than 40 times as frequently as the 9. In this case, the probability of the occurrence of a particular first digit can be derived from a power function with a negative exponent p > 1. While the entropy of the first digits following an NB distribution amounts to H = 2.88, for other data distributions (diameters of craters on Venus or the weight of fragments of crushed minerals), entropy values of 2.76 and 2.04 bits per digit have been found.
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Donawa, Wendy. "Poetry and process: Glad in the Ruthless Furnance / Poésie et procédé : être joyeux dans l’impitoyable fournaise." Canadian Review of Art Education / Revue canadienne d’éducation artistique 45, no. 1 (December 22, 2018): 12–22. http://dx.doi.org/10.26443/crae.v45i1.47.
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Abstract: Poets use sensory imagery and perception, memory and experience, free association and contemplation to join psychic and material worlds, and to honour both emotional and discursive truths. Through multiple drafts, free-writing and research, the author unpacks her own reflections and poems to demonstrate the process by which intuition and personal insight are crafted for public understanding. This poetic process suggests that scholarly discourses of the arts and the humanities need not always fall into the quantitative/qualitative binary, but that both heart and mind are required to some degree in the seeking of wisdom.Keywords: imagery, craft, metaphor, cadence, tone, sensory perception, memory, intuition, contemplationRésumé : Les poètes utilisent l’imagerie sensorielle et la perception, la mémoire et l’expérience ainsi que l’association libre et la contemplation, pour unifier les univers psychique et matériel et célébrer à la fois les vérités émotionnelles et discursives. Par le biais de multiples ébauches, d’écriture libre et de recherches, l’auteure partage ses réflexions et poèmes pour décrire le procédé par lequel intuition et points de vue personnels sont façonnés dans le but d’être compris par le public. Ce procédé poétique donne à penser que les discours érudits sur les arts et les sciences humaines ne doivent pas obligatoirement être de nature binaire quantitative ou qualitative mais que cœur et esprit sont, dans une certaine mesure, indispensables à la quête de la sagesse. Mots-clés : imagerie, art, métaphore, cadence, ton, perception sensorielle, mémoire, intuition, contemplation.
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Khalil, Elias B., Christopher Morris, and Andrea Lodi. "MIP-GNN: A Data-Driven Framework for Guiding Combinatorial Solvers." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 9 (June 28, 2022): 10219–27. http://dx.doi.org/10.1609/aaai.v36i9.21262.
Повний текст джерелаАнотація:
Mixed-integer programming (MIP) technology offers a generic way of formulating and solving combinatorial optimization problems. While generally reliable, state-of-the-art MIP solvers base many crucial decisions on hand-crafted heuristics, largely ignoring common patterns within a given instance distribution of the problem of interest. Here, we propose MIP-GNN, a general framework for enhancing such solvers with data-driven insights. By encoding the variable-constraint interactions of a given mixed-integer linear program (MILP) as a bipartite graph, we leverage state-of-the-art graph neural network architectures to predict variable biases, i.e., component-wise averages of (near) optimal solutions, indicating how likely a variable will be set to 0 or 1 in (near) optimal solutions of binary MILPs. In turn, the predicted biases stemming from a single, once-trained model are used to guide the solver, replacing heuristic components. We integrate MIP-GNN into a state-of-the-art MIP solver, applying it to tasks such as node selection and warm-starting, showing significant improvements compared to the default setting of the solver on two classes of challenging binary MILPs. Our code and appendix are publicly available at https://github.com/lyeskhalil/mipGNN.
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Lupishko, Dimitrij F., Mario Di Martino, and Richard P. Binzel. "Near-Earth objects as principal impactors of the Earth: Physical properties and sources of origin." Proceedings of the International Astronomical Union 2, S236 (August 2006): 251–60. http://dx.doi.org/10.1017/s1743921307003304.
Повний текст джерелаАнотація:
AbstractNear-Earth objects (NEOs) are objects of a special interest from the point of view not only of cosmogonic problems of the Solar system, but of the applied problems as well (the problem of asteroid hazard, NEOs as the potential sources of raw materials, etc.). They are much smaller in sizes than main-belt asteroids (MBAs), very irregular in shape and covered with a great number of craters of different sizes. Most of NEOs are covered by regolith of low thermal inertia and different thickness. Objects with complex non-principal axis rotation (tumbling bodies) and with super-fast rotational periods have been detected among them. The new data, based on photometric and radar observations, evidence that about 15-20 %; of NEOs could be binary systems. Most of the classified NEOs fragments of differentiated assemblages of S-and Q-types. Analysis of physical properties of NEOs clearly indicates that the asteroid main-belt is the principal source of their origin and only about 10 % of NEOs have a cometary origin.
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Givre, Philippe. "Fantasmorphoses and Hybrid Becomings of Identities." Psychoanalytic Review 108, no. 4 (December 2021): 511–42. http://dx.doi.org/10.1521/prev.2021.108.4.511.
Повний текст джерелаАнотація:
Deleuze and Guattari crafted the concept of “becoming” as a way of theorizing the rampant chimerization and polymorphism of identities in today's world. They used Kafka's work to show how the frequent use of metamorphosis in his stories prefigures this widespread phenomenon of hybridization of identities. The frequency of such hybrid becomings raises questions about the very foundations of modernity's subjective construct. Does this proliferation reflect new configurations of desiring activities, or is it the result of early interference in what Melanie Klein conceptualized as “primary confusion”? The author will use Klein's notion to show how, early in life, envy of the breast and primary confusion can blur the organization of binary logic essential to establishing the ability to judge and the activity of primal symbolization.
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Mohammed, Badiea Abdulkarem, Ebrahim Mohammed Senan, Zeyad Ghaleb Al-Mekhlafi, Meshari Alazmi, Abdulaziz M. Alayba, Adwan Alownie Alanazi, Abdulrahman Alreshidi, and Mona Alshahrani. "Hybrid Techniques for Diagnosis with WSIs for Early Detection of Cervical Cancer Based on Fusion Features." Applied Sciences 12, no. 17 (September 2, 2022): 8836. http://dx.doi.org/10.3390/app12178836.
Повний текст джерелаАнотація:
Cervical cancer is a global health problem that threatens the lives of women. Liquid-based cytology (LBC) is one of the most used techniques for diagnosing cervical cancer; converting from vitreous slides to whole-slide images (WSIs) allows images to be evaluated by artificial intelligence techniques. Because of the lack of cytologists and cytology devices, it is major to promote automated systems that receive and diagnose huge amounts of images quickly and accurately, which are useful in hospitals and clinical laboratories. This study aims to extract features in a hybrid method to obtain representative features to achieve promising results. Three proposed approaches have been applied with different methods and materials as follows: The first approach is a hybrid method called VGG-16 with SVM and GoogLeNet with SVM. The second approach is to classify the cervical abnormal cell images by ANN classifier with hybrid features extracted by the VGG-16 and GoogLeNet. A third approach is to classify the images of abnormal cervical cells by an ANN classifier with features extracted by the VGG-16 and GoogLeNet and combine them with hand-crafted features, which are extracted using Fuzzy Color Histogram (FCH), Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) algorithms. Based on the mixed features of CNN with features of FCH, GLCM, and LBP (hand-crafted), the ANN classifier reached the best results for diagnosing abnormal cells of the cervix. The ANN network achieved with the hybrid features of VGG-16 and hand-crafted an accuracy of 99.4%, specificity of 100%, sensitivity of 99.35%, AUC of 99.89% and precision of 99.42%.
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Naeem, Muhammad Rehan, Rashid Amin, Sultan S. Alshamrani, and Abdullah Alshehri. "Digital Forensics for Malware Classification: An Approach for Binary Code to Pixel Vector Transition." Computational Intelligence and Neuroscience 2022 (April 21, 2022): 1–12. http://dx.doi.org/10.1155/2022/6294058.
Повний текст джерелаАнотація:
The most often reported danger to computer security is malware. Antivirus company AV-Test Institute reports that more than 5 million malware samples are created each day. A malware classification method is frequently required to prioritize these occurrences because security teams cannot address all of that malware at once. Malware’s variety, volume, and sophistication are all growing at an alarming rate. Hackers and attackers routinely design systems that can automatically rearrange and encrypt their code to escape discovery. Traditional machine learning approaches, in which classifiers learn based on a hand-crafted feature vector, are ineffective for classifying malware. Recently, deep convolutional neural networks (CNNs) successfully identified and classified malware. To categorize malware, a smart system has been suggested in this research. A novel model of deep learning is introduced to categorize malware families and multiclassification. The malware file is converted to a grayscale picture, and the image is then classified using a convolutional neural network. To evaluate the performance of our technique, we used a Microsoft malware dataset of 10,000 samples with nine distinct classifications. The findings stood out among the deep learning models with 99.97% accuracy for nine malware types.
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Albiero, Olivia. "Fluid Writing: Identity, Gender and Migration in Sasha Marianna Salzmann’s Ausser sich (2017)." Literatur für Leser 42, no. 2 (January 1, 2022): 57–72. http://dx.doi.org/10.3726/lfl.2019.02.05.
Повний текст джерелаАнотація:
Abstract This article offers a reading of Sasha Marianna Salzmann’s Ausser sich which focuses on the “fluidity” of the novel as thematic and narrative aspect in relation to questions of identity, gender and migration. My reading shows how Salzmann has crafted a narrative that unfolds at the intersections of multiple transitions in the protagonist’s life. In Ausser sich, the reader follows Ali’s family’s migration from the Soviet Union to West Germany; Ali’s own search for their past and twin brother in Istanbul; and the gender transition that the protagonist undergoes. My analysis highlights how these thematic aspects are reflected in the form of the novel, its queer narrative voice, and the use of multiple languages. Guided by ideas taken from queer and feminist narrative theory and informed by the concept of “fluidity” explored within a sociological, postcolonial and postmigrant context, I show how Salzmann’s “fluid writing” resists binary classifications to account for the shifts described.
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Win, Khin Yadanar, Noppadol Maneerat, Kazuhiko Hamamoto, and Syna Sreng. "Hybrid Learning of Hand-Crafted and Deep-Activated Features Using Particle Swarm Optimization and Optimized Support Vector Machine for Tuberculosis Screening." Applied Sciences 10, no. 17 (August 20, 2020): 5749. http://dx.doi.org/10.3390/app10175749.
Повний текст джерелаАнотація:
Tuberculosis (TB) is a leading infectious killer, especially for people with Human Immunodeficiency Virus (HIV) and Acquired Immunodeficiency Syndrome (AIDS). Early diagnosis of TB is crucial for disease treatment and control. Radiology is a fundamental diagnostic tool used to screen or triage TB. Automated chest x-rays analysis can facilitate and expedite TB screening with fast and accurate reports of radiological findings and can rapidly screen large populations and alleviate a shortage of skilled experts in remote areas. We describe a hybrid feature-learning algorithm for automatic screening of TB in chest x-rays: it first segmented the lung regions using the DeepLabv3+ model. Then, six sets of hand-crafted features from statistical textures, local binary pattern, GIST, histogram of oriented gradients (HOG), pyramid histogram of oriented gradients and bags of visual words (BoVW), and nine sets of deep-activated features from AlexNet, GoogLeNet, InceptionV3, XceptionNet, ResNet-50, SqueezeNet, ShuffleNet, MobileNet, and DenseNet, were extracted. The dominant features of each feature set were selected using particle swarm optimization, and then separately input to an optimized support vector machine classifier to label ‘normal’ and ‘TB’ x-rays. GIST, HOG, BoVW from hand-crafted features, and MobileNet and DenseNet from deep-activated features performed better than the others. Finally, we combined these five best-performing feature sets to build a hybrid-learning algorithm. Using the Montgomery County (MC) and Shenzen datasets, we found that the hybrid features of GIST, HOG, BoVW, MobileNet and DenseNet, performed best, achieving an accuracy of 92.5% for the MC dataset and 95.5% for the Shenzen dataset.
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Langlands, Rebecca. "Latin Literature." Greece and Rome 63, no. 1 (March 29, 2016): 121–29. http://dx.doi.org/10.1017/s0017383515000297.
Повний текст джерелаАнотація:
Among a wealth of excellent studies and translations of individual Latin authors (Plautus, Catullus, Lucretius, Cicero, Ovid, Pliny the Elder, Pliny the Younger, Martial, Juvenal, and Statius), I was delighted also to find packed into my crate of review books the latest work by Anthony Corbeill, Sexing the World. With the innovative sociological-cum-philological approach familiar from his previous works, which belongs to cultural history as much as to literary and linguistic studies, Corbeill here tackles the question of how grammatical gender in ancient Latin language maps on to, and influences, a Roman cultural worldview that is binary and ‘heterosexual’, where grammatical gender is identified with biological gender. His study argues for the material implications of apparently ‘innocent’ grammatical categories. As a case study focusing on the Latin language and its relation to Roman culture and thought, it also makes a contribution to wider debates about how language shapes human perception of the world. Corbeill's main focus is on the Romans’ own narratives about the origins of their binary gender categories in a time of primordial fluidity, a ‘mystical lost time’ (134), that is reflected in the story told in each chapter, where transgressing gender boundaries is a source of power for gods and poets alike. In Chapter 1 the narrative in question is formed by the etymologizing accounts of the very grammatical term genus as fundamentally associated with procreation, and in Chapter 2 by Latin explanations for non-standard gender of nouns, with Chapter 3 being a demonstration of how Latin poets tap into the supposedly fluid origins of grammatical gender, to access their mystical power. In Chapter 4 the story is of how the androgynous gods of old became more rigidly assigned to one gender or another over time, while in Chapter 5 the shift is from the numinous duality of intersex people to the more mundane concern that they should be categorized in legal terms as either male or female. Each chapter, as Corbeill says, represents a self-contained treatment of a particular aspect of Latin gender categories; in sequence each can also be seen to trace a similar trajectory, from flux to binary certainty. In every case, it seems, early gender fluidity is represented by the Romans as gradually hardening into a clear binary differentiation between male and female. Corbeill is less interested in the reality of these narratives than in what they themselves tells us about Roman attitudes towards sex and gender, with their essentializing message about a heterosexual gender framework. With its wide-ranging erudition, clear and compelling prose, and fascinating insights of broad relevance, this is a thought-provoking study, even though it leaves many questions unanswered, especially in relation to the role of the neuter (‘neither’) gender and its interplay with the compound ‘both-ness’ of hermaphrodites.
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Almradi, Ahmed M., and Sohail A. Dianat. "NDA SNR and CRLB Estimation Over MISO with STBC Channels." International Journal of Business Data Communications and Networking 8, no. 4 (October 2012): 1–16. http://dx.doi.org/10.4018/jbdcn.2012100101.
Повний текст джерелаАнотація:
This paper discusses the problem of Non Data Aided (NDA) Signal to Noise Ratio (SNR) estimation of Binary Phase Shift keying (BPSK) modulated signals using the Expectation Maximization (EM) Algorithm. In addition, the Cramer-Rao Lower Bounds (CRLB) for the estimation of Data Aided (DA) and Non Data Aided (NDA) Signal to Noise Ratio (SNR) estimation is derived. Multiple Input Single Output (MISO) channels with Space Time Block Codes (STBC) is used. The EM algorithm is a method that finds the Maximum Likelihood (ML) solution iteratively when there are unobserved (hidden or missing) data. Extension of the proposed approach to other types of linearly modulated signals in estimating SNR is straight forward. The performance of the estimator is assessed using the NDA CRLBs. Alamouti coding technique is used in this paper with two transmit antennas and one receive antenna. The authors’ assumption is that the received signal is corrupted by additive white Gaussian noise (AWGN) with unknown variance, and scaled by fixed unknown complex channel gain. Monte Carlo simulations are used to show that the proposed estimator offers a substantial improvement over the conventional Single Input Single Output (SISO) NDA SNR estimator due to the use of the statistical dependences in space and time. Moreover, the proposed NDA SNR estimator works close to the NDA SNR estimator over Single Input Multiple Output (SIMO) channels.
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Al-Mekhlafi, Zeyad Ghaleb, Ebrahim Mohammed Senan, Badiea Abdulkarem Mohammed, Meshari Alazmi, Abdulaziz M. Alayba, Abdulrahman Alreshidi, and Mona Alshahrani. "Diagnosis of Histopathological Images to Distinguish Types of Malignant Lymphomas Using Hybrid Techniques Based on Fusion Features." Electronics 11, no. 18 (September 10, 2022): 2865. http://dx.doi.org/10.3390/electronics11182865.
Повний текст джерелаАнотація:
Malignant lymphoma is one of the types of malignant tumors that can lead to death. The diagnostic method for identifying malignant lymphoma is a histopathological analysis of lymphoma tissue images. Because of the similar morphological characteristics of the lymphoma types, it is difficult for doctors and specialists to manually distinguish the types of lymphomas. Therefore, deep and automated learning techniques aim to solve this problem and help clinicians reconsider their diagnostic decisions. Because of the similarity of the morphological characteristics between lymphoma types, this study aimed to extract features using various algorithms and deep learning models and combine them together into feature vectors. Two datasets have been applied, each with two different systems for the reliable diagnosis of malignant lymphoma. The first system was a hybrid system between DenseNet-121 and ResNet-50 to extract deep features and reduce their dimensions by the principal component analysis (PCA) method, using the support vector machine (SVM) algorithm for classifying low-dimensional deep features. The second system was based on extracting the features using DenseNet-121 and ResNet-50 and combining them with the hand-crafted features extracted by gray level co-occurrence matrix (GLCM), fuzzy color histogram (FCH), discrete wavelet transform (DWT), and local binary pattern (LBP) algorithms and classifying them using a feed-forward neural network (FFNN) classifier. All systems achieved superior results in diagnosing the two datasets of malignant lymphomas. An FFNN classifier with features of ResNet-50 and hand-crafted features reached an accuracy of 99.5%, specificity of 100%, sensitivity of 99.33%, and AUC of 99.86% for the first dataset. In contrast, the same technique reached 100% for all measures to diagnose the second dataset.
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Sigmund, Milan, and Martin Hrabina. "Efficient Feature Set Developed for Acoustic Gunshot Detection in Open Space." Elektronika ir Elektrotechnika 27, no. 4 (August 23, 2021): 62–68. http://dx.doi.org/10.5755/j02.eie.28877.
Повний текст джерелаАнотація:
This paper presents an efficient approach to automatic gunshot detection based on a combination of two feature sets: adapted standard sound features and hand-crafted novel features. The standard features are mel-frequency cepstral coefficients adapted for gunshot recognition in terms of uniform gamma-tone filters linearly spaced over the whole frequency range from 0 kHz to 16 kHz. The first 18 coefficients calculated from the 41 filters represent the best set of the optimized cepstral coefficients. The novel features were derived in the time domain from individual significant points of the raw waveform after amplitude normalization. Experiments were performed using single and ensemble neural networks to verify the effectiveness of the novel features for supplementing the standard features. The novelty of the work is the proposed feature combination, which allows to achieve very effective detection of gunshots from hunting weapons using 23 features and a simple neural network. In binary classification, the developed approach achieved an accuracy of 95.02 % in gunshot detection and 98.16 % in disregarding other sounds (i.e., non-gunshot).
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Curtis, Christopher A. "Home and School Environmental Influences on Adolescents’ Sociopolitical Group Participation: Implications for Increasing Youth Involvement." Education and Urban Society 51, no. 7 (September 2017): 871–93. http://dx.doi.org/10.1177/0013124517727052.
Повний текст джерелаАнотація:
The potential benefits associated with sociopolitical group involvement for participating youth have been well documented in the existing literature. Yet, little is known about what motivates voluntary participation in such programs among youth. The purpose of this study is to explore what environmental factors influence youth civic engagement through participation in sociopolitical groups (e.g., service-learning or community service programs). To do this, several independent variables captured in The Commission on Youth Voting and Civic Knowledge Youth Post Election Survey 2012 dataset and the respondents’ reported participation in social or political groups while in high school were observed. Binary and ordinal logistic regression modeling were used to analyze the data. The results indicate that several factors in the home and school environment are related to an increased probability of youth joining a sociopolitical group at school, away from school, or both. These findings suggest that the messages crafted to encourage youth participation in sociopolitical groups should account for the demographic (i.e., racial, gender, and cultural) and experiential (i.e., civics education quality) differences present within the target population.
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Veesam, Venkata Srinivasu, Suban Ravichandran, and Gatram Rama Mohan Babu. "Deep Neural Networks for Automatic Facial Expression Recognition." Revue d'Intelligence Artificielle 36, no. 5 (December 23, 2022): 809–14. http://dx.doi.org/10.18280/ria.360520.
Повний текст джерелаАнотація:
Out of all non-linguistic communications, one of the most popular is face expression and is capable of communicating effectively with others. We have number of applications of facial expressions in as sorted arenas comprising of medicine like psychology, security, gaming, Classroom communication and even commercial creativities. Owing to huge intra-class distinction it is still challenging to recognize the emotions automatically based on facial expression though it is a vigorous area of research since decades. Conventional lines for this approach are dependent on hand-crafted characteristics like Scale Invariant Feature Transform, Histogram of Oriented Gradient and Local Binary Patterns surveyed by a classifier which is applied on a dataset. Various types of architectures were applied for restored performance as Deep learning proved an outstanding feat. The goal of this study is to create a deep learning model on automatic facial emotion recognition FER. The proposed model efforts more on pulling out the crucial features, thereby, advances the expression recognition accuracy, and beats the competition on FER2013 dataset.
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Mahum, Rabbia, and Suliman Aladhadh. "Skin Lesion Detection Using Hand-Crafted and DL-Based Features Fusion and LSTM." Diagnostics 12, no. 12 (November 28, 2022): 2974. http://dx.doi.org/10.3390/diagnostics12122974.
Повний текст джерелаАнотація:
The abnormal growth of cells in the skin causes two types of tumor: benign and malignant. Various methods, such as imaging and biopsies, are used by oncologists to assess the presence of skin cancer, but these are time-consuming and require extra human effort. However, some automated methods have been developed by researchers based on hand-crafted feature extraction from skin images. Nevertheless, these methods may fail to detect skin cancers at an early stage if they are tested on unseen data. Therefore, in this study, a novel and robust skin cancer detection model was proposed based on features fusion. First, our proposed model pre-processed the images using a GF filter to remove the noise. Second, the features were manually extracted by employing local binary patterns (LBP), and Inception V3 for automatic feature extraction. Aside from this, an Adam optimizer was utilized for the adjustments of learning rate. In the end, LSTM network was utilized on fused features for the classification of skin cancer into malignant and benign. Our proposed system employs the benefits of both ML- and DL-based algorithms. We utilized the skin lesion DermIS dataset, which is available on the Kaggle website and consists of 1000 images, out of which 500 belong to the benign class and 500 to the malignant class. The proposed methodology attained 99.4% accuracy, 98.7% precision, 98.66% recall, and a 98% F-score. We compared the performance of our features fusion-based method with existing segmentation-based and DL-based techniques. Additionally, we cross-validated the performance of our proposed model using 1000 images from International Skin Image Collection (ISIC), attaining 98.4% detection accuracy. The results show that our method provides significant results compared to existing techniques and outperforms them.
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Malik, Sarib, Javeria Amin, Muhammad Sharif, Mussarat Yasmin, Seifedine Kadry, and Sheraz Anjum. "Fractured Elbow Classification Using Hand-Crafted and Deep Feature Fusion and Selection Based on Whale Optimization Approach." Mathematics 10, no. 18 (September 10, 2022): 3291. http://dx.doi.org/10.3390/math10183291.
Повний текст джерелаАнотація:
The fracture of the elbow is common in human beings. The complex structure of the elbow, including its irregular shape, border, etc., makes it difficult to correctly recognize elbow fractures. To address such challenges, a method is proposed in this work that consists of two phases. In Phase I, pre-processing is performed, in which images are converted into RGB. In Phase II, pre-trained convolutional models Darknet-53 and Xception are used for deep feature extraction. The handcrafted features, such as the histogram of oriented gradient (HOG) and local binary pattern (LBP), are also extracted from the input images. A principal component analysis (PCA) is used for best feature selection and is serially merged into a single-feature vector having the length of N×2125. Furthermore, informative features N×1049 are selected out of N×2125 features using the whale optimization approach (WOA) and supplied to SVM, KNN, and wide neural network (WNN) classifiers. The proposed method’s performance is evaluated on 16,984 elbow X-ray radiographs that are taken from the publicly available musculoskeletal radiology (MURA) dataset. The proposed technique provides 97.1% accuracy and a kappa score of 0.943% for the classification of elbow fractures. The obtained results are compared to the most recently published approaches on the same benchmark datasets.
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Chen, Zhiqin, Andrea Tagliasacchi, Thomas Funkhouser, and Hao Zhang. "Neural dual contouring." ACM Transactions on Graphics 41, no. 4 (July 2022): 1–13. http://dx.doi.org/10.1145/3528223.3530108.
Повний текст джерелаАнотація:
We introduce neural dual contouring (NDC), a new data-driven approach to mesh reconstruction based on dual contouring (DC). Like traditional DC, it produces exactly one vertex per grid cell and one quad for each grid edge intersection, a natural and efficient structure for reproducing sharp features. However, rather than computing vertex locations and edge crossings with hand-crafted functions that depend directly on difficult-to-obtain surface gradients, NDC uses a neural network to predict them. As a result, NDC can be trained to produce meshes from signed or unsigned distance fields, binary voxel grids, or point clouds (with or without normals); and it can produce open surfaces in cases where the input represents a sheet or partial surface. During experiments with five prominent datasets, we find that NDC, when trained on one of the datasets, generalizes well to the others. Furthermore, NDC provides better surface reconstruction accuracy, feature preservation, output complexity, triangle quality, and inference time in comparison to previous learned (e.g., neural marching cubes, convolutional occupancy networks) and traditional (e.g., Poisson) methods. Code and data are available at https://github.com/czq142857/NDC.
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Anwar, Inzamam, and Naeem Ul Islam. "Learned Features are Better for Ethnicity Classification." Cybernetics and Information Technologies 17, no. 3 (September 1, 2017): 152–64. http://dx.doi.org/10.1515/cait-2017-0036.
Повний текст джерелаАнотація:
Abstract Ethnicity is a key demographic attribute of human beings and it plays a vital role in automatic facial recognition and have extensive real world applications such as Human Computer Interaction (HCI); demographic based classification; biometric based recognition; security and defense to name a few. In this paper, we present a novel approach for extracting ethnicity from the facial images. The proposed method makes use of a pre trained Convolutional Neural Network (CNN) to extract the features, then Support Vector Machine (SVM) with linear kernel is used as a classifier. This technique uses translational invariant hierarchical features learned by the network, in contrast to previous works, which use hand crafted features such as Local Binary Pattern (LBP); Gabor, etc. Thorough experiments are presented on ten different facial databases, which strongly suggest that our approach is robust to different expressions and illuminations conditions. Here we consider ethnicity classification as a three class problem including Asian, African-American and Caucasian. Average classification accuracy over all databases is 98.28%, 99.66% and 99.05% for Asian, African-American and Caucasian respectively. All the codes are available for reproducing the results on request.
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Lin, Xuan, Zhe Quan, Zhi-Jie Wang, Huang Huang, and Xiangxiang Zeng. "A novel molecular representation with BiGRU neural networks for learning atom." Briefings in Bioinformatics 21, no. 6 (November 15, 2019): 2099–111. http://dx.doi.org/10.1093/bib/bbz125.
Повний текст джерелаАнотація:
Abstract Molecular representations play critical roles in researching drug design and properties, and effective methods are beneficial to assisting in the calculation of molecules and solving related problem in drug discovery. In previous years, most of the traditional molecular representations are based on hand-crafted features and rely heavily on biological experimentations, which are often costly and time consuming. However, recent researches achieve promising results using machine learning on various domains. In this article, we present a novel method named Smi2Vec-BiGRU that is designed for learning atoms and solving the single- and multitask binary classification problems in the field of drug discovery, which are the basic and also key problems in this field. Specifically, our approach transforms the molecule data in the SMILES format into a set of sample vectors and then feeds them into the bidirectional gated recurrent unit neural networks for training, which learns low-dimensional vector representations for molecular drug. We conduct extensive experiments on several widely used benchmarks including Tox21, SIDER and ClinTox. The experimental results show that our approach can achieve state-of-the-art performance on these benchmarking datasets, demonstrating the feasibility and competitiveness of our proposed approach.
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Dinakar, Karthik, Emily Weinstein, Henry Lieberman, and Robert Selman. "Stacked Generalization Learning to Analyze Teenage Distress." Proceedings of the International AAAI Conference on Web and Social Media 8, no. 1 (May 16, 2014): 81–90. http://dx.doi.org/10.1609/icwsm.v8i1.14527.
Повний текст джерелаАнотація:
The internet has become a resource for adolescents who are distressed by social and emotional problems. Social network analysis can provide new opportunities for helping people seeking support online, but only if we understand the salient issues that are highly relevant to participants personal circumstances. In this paper, we present a stacked generalization modeling approach to analyze an online community supporting adolescents under duress. While traditional predictive supervised methods rely on robust hand-crafted feature space engineering, mixed initiative semi-supervised topic models are often better at extracting high-level themes that go beyond such feature spaces. We present a strategy that combines the strengths of both these types of models inspired by Prevention Science approaches which deals with the identification and amelioration of risk factors that predict to psychological, psychosocial, and psychiatric disorders within and across populations (in our case teenagers) rather than treat them post-facto. In this study, prevention scientists used a social science thematic analytic approach to code stories according to a fine-grained analysis of salient social, developmental or psychological themes they deemed relevant, and these are then analyzed by a society of models. We show that a stacked generalization of such an ensemble fares better than individual binary predictive models.
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Miljković, Katarina, Gareth S. Collins, and Philip A. Bland. "Reply to comment on: “Supportive comment on: “Morphology and population of binary asteroid impact craters”, by K. Miljković, G.S. Collins, S. Mannick and P.A. Bland – An updated assessment”." Earth and Planetary Science Letters 405 (November 2014): 285–86. http://dx.doi.org/10.1016/j.epsl.2014.08.026.
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