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Artigos de revistas sobre o tema "Depth level-sets"

Autor: Grafiati

Publicado: 28 de setembro de 2024

Última modificação: 19 de julho de 2025

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1

Brunel, Victor-Emmanuel. "Concentration of the empirical level sets of Tukey’s halfspace depth." Probability Theory and Related Fields 173, no. 3-4 (2018): 1165–96. http://dx.doi.org/10.1007/s00440-018-0850-0.

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Grünewald, T., Y. Bühler, and M. Lehning. "Elevation dependency of mountain snow depth." Cryosphere Discussions 8, no. 4 (2014): 3665–98. http://dx.doi.org/10.5194/tcd-8-3665-2014.

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Abstract. Elevation strongly affects quantity and distribution of precipitation and snow. Positive elevation gradients were identified by many studies, usually based on data from sparse precipitation stations or snow depth measurements. We present a systematic evaluation of the elevation – snow depth relationship. We analyse areal snow depth data obtained by remote sensing for seven mountain sites. Snow depths were averaged to 100 m elevation bands and then related to their respective elevation level. The assessment was performed at three scales ranging from the complete data sets by km-scale

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Bogicevic, Milica, and Milan Merkle. "Approximate calculation of Tukey's depth and median with high-dimensional data." Yugoslav Journal of Operations Research 28, no. 4 (2018): 475–99. http://dx.doi.org/10.2298/yjor180520022b.

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We present a new fast approximate algorithm for Tukey (halfspace) depth level sets and its implementation-ABCDepth. Given a d-dimensional data set for any d ? 1, the algorithm is based on a representation of level sets as intersections of balls in Rd. Our approach does not need calculations of projections of sample points to directions. This novel idea enables calculations of approximate level sets in very high dimensions with complexity that is linear in d, which provides a great advantage over all other approximate algorithms. Using different versions of this algorithm, we demonstrate approx

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Gupta, Pawan, Lorraine A. Remer, Falguni Patadia, Robert C. Levy, and Sundar A. Christopher. "High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS." Remote Sensing 12, no. 17 (2020): 2847. http://dx.doi.org/10.3390/rs12172847.

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The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce Level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and Level 3 data at 1 degree. The local and global applications have benefited from the coarse resolution gridded data sets (i.e., Level 3, 1 degree), as it is easier to use since data volume is low, and several online and offline

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Grünewald, T., Y. Bühler, and M. Lehning. "Elevation dependency of mountain snow depth." Cryosphere 8, no. 6 (2014): 2381–94. http://dx.doi.org/10.5194/tc-8-2381-2014.

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Abstract. Elevation strongly affects quantity and distribution patterns of precipitation and snow. Positive elevation gradients were identified by many studies, usually based on data from sparse precipitation stations or snow depth measurements. We present a systematic evaluation of the elevation–snow depth relationship. We analyse areal snow depth data obtained by remote sensing for seven mountain sites near to the time of the maximum seasonal snow accumulation. Snow depths were averaged to 100 m elevation bands and then related to their respective elevation level. The assessment was performe

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6

Tavkhelidze, Avto, Amiran Bibilashvili, Larissa Jangidze, and Nima E. Gorji. "Fermi-Level Tuning of G-Doped Layers." Nanomaterials 11, no. 2 (2021): 505. http://dx.doi.org/10.3390/nano11020505.

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Recently, geometry-induced quantum effects were observed in periodic nanostructures. Nanograting (NG) geometry significantly affects the electronic, magnetic, and optical properties of semiconductor layers. Silicon NG layers exhibit geometry-induced doping. In this study, G-doped junctions were fabricated and characterized and the Fermi-level tuning of the G-doped layers by changing the NG depth was investigated. Samples with various indent depths were fabricated using laser interference lithography and a consecutive series of reactive ion etching. Four adjacent areas with NG depths of 10, 20,

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7

R, Muthukrishnan, and S. Nair Surabhi. "Computing Robust Measure of Location on Multivariate Statistical Data Using Euclidean Depth Procedures." Indian Journal of Science and Technology 16, no. 26 (2023): 1927–34. https://doi.org/10.17485/IJST/v16i26.847.

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Abstract <strong>Objectives:</strong> To suggest reliable location parameters (central value) in multivariate datasets using data depth procedures in order to reduce the presence of outliers. <strong>Methods:</strong> Applying depth techniques in both outlier-free and outliercontaining scenarios, the data sets starsCYG and delivery time data are utilized to determine the measure of location. Various classical and robust data depth procedures are used to find the location parameters, namely Mahalanobis depth, Tukey’s half space depth, Projection depth, Zonoid depth, Spatial

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Lowrey, Wilson, Ryan Broussard, and Lindsey A. Sherrill. "Data journalism and black-boxed data sets." Newspaper Research Journal 40, no. 1 (2019): 69–82. http://dx.doi.org/10.1177/0739532918814451.

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This study explores the level of scrutiny data journalists from national, local, traditional and digital outlets apply to data sets and data categories, and reasons that scrutiny varies. The study applies a sociology of quantification framework that assumes a tendency for data categories to become “black-boxed,” or taken-for-granted and unquestioned. Results of in-depth interviews with 15 data journalists suggested these journalists were more concerned with data accessibility and ease of use than validity of data categories, though this varied across outlet size and level of story complexity.

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Harms-Ringdahl, Lars. "Analysis of Results from Event Investigations in Industrial and Patient Safety Contexts." Safety 7, no. 1 (2021): 19. http://dx.doi.org/10.3390/safety7010019.

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Accident investigations are probably the most common approach to evaluate the safety of systems. The aim of this study is to analyse event investigations and especially their recommendations for safety reforms. Investigation reports were studied with a methodology based on the characterisation of organisational levels and types of recommendations. Three sets of event investigations from industrial companies and hospitals were analysed. Two sets employed an in-depth approach, while the third was based on the root-cause concept. The in-depth approach functioned in a similar way for both industri

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10

Letang, D. L., and W. J. de Groot. "Forest floor depths and fuel loads in upland Canadian forests." Canadian Journal of Forest Research 42, no. 8 (2012): 1551–65. http://dx.doi.org/10.1139/x2012-093.

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Forest floor data are important for many forest resource management applications. In terms of fire and forest carbon dynamics, these data are critical for modeling direct carbon emissions from wildfire in Canadian forests because forest floor organic material is usually the greatest emissions source. However, there are very few data available to initialize wildfire emission models. Six data sets representing 41 534 forest stands across Canada were combined to provide summary statistics and to analyze factors controlling forest floor fuel loads and depths. The impacts of dominant tree species,

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11

Xi, Qingkui, Weiming Wu, Junjie Ji, Zhenghui Zhang, and Feng Ni. "Comparing the Level of Commitment to In-Depth Reference and Research Support Services in Two Sets of Chinese Universities." Science & Technology Libraries 38, no. 2 (2019): 204–23. http://dx.doi.org/10.1080/0194262x.2019.1583624.

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Cai, Jing, Fang Li, Ning An, Jing Jing Lu, and Lu Sun. "The Application of the Minimum Cut Sets in Reliability Evaluation of Power Transmission and Transformation System." Advanced Materials Research 463-464 (February 2012): 1175–81. http://dx.doi.org/10.4028/www.scientific.net/amr.463-464.1175.

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As an important part of power systems, power transmission and transformation system involves various equipments, complicated structure and operation modes, and its reliability level has a significant influence on the reliability of the whole system. The paper proposes a practical method for reliability evaluation of power transmission and transformation system based on minimum cut sets. The algorithm, based on topological structure and reliability data without power flow, analyses the reliability of system by different voltage grades. In each voltage grade analysis, the method resolves minimum

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13

Yao, Huang, Mengting Yang, Tiantian Chen, Yantao Wei, and Yu Zhang. "Depth-based human activity recognition via multi-level fused features and fast broad learning system." International Journal of Distributed Sensor Networks 16, no. 2 (2020): 155014772090783. http://dx.doi.org/10.1177/1550147720907830.

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Human activity recognition using depth videos remains a challenging problem while in some applications the available training samples is limited. In this article, we propose a new method for human activity recognition by crafting an integrated descriptor called multi-level fused features for depth sequences and devising a fast broad learning system based on matrix decomposition for classification. First, the surface normals are computed from original depth maps; the histogram of the surface normal orientations is obtained as a low-level feature by accumulating the contributions from normals, t

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14

Rodríguez-Fernández, Nemesio J., Arnaud Mialon, Stephane Mermoz, et al. "An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets: high sensitivity of L-VOD to above-ground biomass in Africa." Biogeosciences 15, no. 14 (2018): 4627–45. http://dx.doi.org/10.5194/bg-15-4627-2018.

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Abstract. The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infrared vegetation indices. This study is devoted to the characterization of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (L-VOD) data sets (SMOS level 2, level 3 and SMOS-IC) were compared with data sets on tree height, visible/infrared indexes (NDVI, EVI), mean annual precipitation and above-ground biomass (AGB) for the

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15

Hopkins, DL. "An evaluation of the Hennessy Grading Probe for measuring fat depth in beef carcasses." Australian Journal of Experimental Agriculture 29, no. 6 (1989): 781. http://dx.doi.org/10.1071/ea9890781.

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Fat depth at the P8 site on the rump was measured by the cut-and-measure (CM) technique and with the Hennessy Grading Probe (HGP) on 2501 beef carcasses at 1 abattoir over a 12-month period. CM measurements that differed by more than 1 mm between the right and left sides of the carcass were discarded. A subsequent data set of 1850 carcasses was randomly divided so that 2 models could be developed to assess the general validity of the relationship between the 2 methods of measurement. Analysis of measurements of the left side of the carcasses of these 2 subsamples showed the data were not norma

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16

Tishchenko, Ilya, Gabor Tari, Mohammad Fallah, and Jonathan Floodpage. "Submarine landslide origin of a tsunami at the Black Sea coast: Evidence based on swath bathymetry and 3D seismic reflection data." Interpretation 9, no. 2 (2021): SB67—SB78. http://dx.doi.org/10.1190/int-2020-0174.1.

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Tsunami waves were observed along the Bulgarian Black Sea coastline on 7 May 2007. The maximum rise and fall of the sea level were 1.2 and 2.0 m, respectively, with wave oscillations between 4 and 8 min. At first, submarine landsliding and then later on atmospheric disturbance were suggested as the cause of the tsunami. Numerical modeling, assuming a landslide displacing 30–60 million m3 material on the slope with a thickness range of more than 20–40 m, could reproduce the main characteristics of the recorded tsunami. In this early model, the landslide initiated on the shelf at a water depth o

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17

Zhao, Yuekun, Suyun Luo, Xiaoci Huang, and Dan Wei. "A Multi-Sensor 3D Detection Method for Small Objects." World Electric Vehicle Journal 15, no. 5 (2024): 210. http://dx.doi.org/10.3390/wevj15050210.

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In response to the limited accuracy of current three-dimensional (3D) object detection algorithms for small objects, this paper presents a multi-sensor 3D small object detection method based on LiDAR and a camera. Firstly, the LiDAR point cloud is projected onto the image plane to obtain a depth image. Subsequently, we propose a cascaded image fusion module comprising multi-level pooling layers and multi-level convolution layers. This module extracts features from both the camera image and the depth image, addressing the issue of insufficient depth information in the image feature. Considering

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18

Wang, Hong, and Hong Li. "Uncertainty Measure for Multisource Intuitionistic Fuzzy Information System." Complexity 2022 (April 7, 2022): 1–21. http://dx.doi.org/10.1155/2022/3605881.

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Multisource information systems and multigranulation intuitionistic fuzzy rough sets are important extended types of Pawlak’s classical rough set model. Multigranulation intuitionistic fuzzy rough sets have been investigated in depth in recent years. However, few studies have considered this combination of multisource information systems and intuitionistic fuzzy rough sets. In this paper, we give the uncertainty measure for multisource intuitionistic fuzzy information system. Against the background of multisource intuitionistic fuzzy information system, each information source is regarded as a

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19

Xu, Zhuo, Fengjiao Zhang, Christopher Juhlin, Björn Lund, Maria Ask, and Liguo Han. "Extrapolated supervirtual refraction interferometry." Geophysical Journal International 227, no. 2 (2021): 1439–63. http://dx.doi.org/10.1093/gji/ggab283.

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SUMMARY Accurate picking of head-wave arrival times is an important component of first-arrival traveltime tomography. Far-offset traces in particular have low signal-to-noise ratio (SNR), but picking on these traces is necessary in order to obtain velocity information at depth. Furthermore, there is often an insufficient number of far-offset traces for obtaining reliable models at depth. We present here an extrapolation method for increasing the number of first arrivals beyond the maximum recorded offset, thereby extending the supervirtual refraction interferometry (SVI) method. We refer to th

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20

Yang, Guoliang, Ziling Nie, Jixiang Wang, Hao Yang, and Shuaiying Yu. "MSREA-Net: An Efficient Skin Disease Segmentation Method Based on Multi-Level Resolution Receptive Field." Applied Sciences 13, no. 18 (2023): 10315. http://dx.doi.org/10.3390/app131810315.

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Aiming at the low contrast of skin lesion image and inaccurate segmentation of lesion boundary, a skin lesion segmentation method based on multi-level split receptive field and attention is proposed. Firstly, the depth feature extraction module and multi-level splitting receptive field module are used to extract image feature information; secondly, the hybrid pooling module is used to build long-term and short-term dependencies and integrate global information and local information. Finally, the reverse residual external attention module is introduced to construct the decoding part, which can

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Özdenvar, Turgut, George A. McMechan, and Preston Chaney. "Simulation of complete seismic surveys for evaluation of experiment design and processing." GEOPHYSICS 61, no. 2 (1996): 496–508. http://dx.doi.org/10.1190/1.1443976.

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Synthesis of complete seismic survey data sets allows analysis and optimization of all stages in an acquisition/processing sequence. The characteristics of available survey designs, parameter choices, and processing algorithms may be evaluated prior to field acquisition to produce a composite system in which all stages have compatible performance; this maximizes the cost effectiveness for a given level of accuracy, or for targets with specific characteristics. Data sets synthesized for three salt structures provide representative comparisons of time and depth migration, post‐stack and prestack

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22

Zuschin, Martin, Rafał Nawrot, Mathias Harzhauser, Oleg Mandic, and Adam Tomašových. "Taxonomic and numerical sufficiency in depth- and salinity-controlled marine paleocommunities." Paleobiology 43, no. 3 (2017): 463–78. http://dx.doi.org/10.1017/pab.2016.49.

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AbstractNumerical and taxonomic resolution of compositional data sets affects investigators’ abilities to detect and measure relationships between communities and environmental factors. We test whether varying numerical (untransformed, square-root- and fourth-root-transformed relative abundance and presence–absence data) and taxonomic (species, genera, families) resolutions reveals different insights into early to middle Miocene molluscan communities along bathymetric and salinity gradients. The marine subtidal has a more even species-abundance distribution, a higher number of rare species, an

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Xu, Wanpeng, Ling Zou, Lingda Wu, and Zhipeng Fu. "Self-Supervised Monocular Depth Learning in Low-Texture Areas." Remote Sensing 13, no. 9 (2021): 1673. http://dx.doi.org/10.3390/rs13091673.

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For the task of monocular depth estimation, self-supervised learning supervises training by calculating the pixel difference between the target image and the warped reference image, obtaining results comparable to those with full supervision. However, the problematic pixels in low-texture regions are ignored, since most researchers think that no pixels violate the assumption of camera motion, taking stereo pairs as the input in self-supervised learning, which leads to the optimization problem in these regions. To tackle this problem, we perform photometric loss using the lowest-level feature m

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Sarkkola, Sakari, Hannu Hökkä, Harri Koivusalo, et al. "Role of tree stand evapotranspiration in maintaining satisfactory drainage conditions in drained peatlands." Canadian Journal of Forest Research 40, no. 8 (2010): 1485–96. http://dx.doi.org/10.1139/x10-084.

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Ditch networks in drained peatland forests are maintained regularly to prevent water table rise and subsequent decrease in tree growth. The growing tree stand itself affects the level of water table through evapotranspiration, the magnitude of which is closely related to the living stand volume. In this study, regression analysis was applied to quantify the relationship between the late summer water table depth (DWT) and tree stand volume, mean monthly summertime precipitation (Ps), drainage network condition, and latitude. The analysis was based on several large data sets from southern to nor

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25

Cormier, Emily C., Danielle R. Sisson, Kathleen M. Rühland, John P. Smol, and Joseph R. Bennett. "A morphological trait-based approach to environmental assessment models using diatoms." Canadian Journal of Fisheries and Aquatic Sciences 77, no. 1 (2020): 108–12. http://dx.doi.org/10.1139/cjfas-2018-0376.

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Diatom assemblages are excellent indicators for environmental monitoring. However, enumerating diatoms using fine-level taxonomy takes considerable effort, which must be undertaken by specialist taxonomists. One alternative is to enumerate assemblages using morphological traits. In this study, we compared the accuracy of models using 20 morphological traits with those using species assemblages to infer lake water pH, salinity, depth, and total phosphorus concentrations in four data sets, each comprising over 200 lakes. Assemblages aggregated by trait combinations were used to predict environme

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26

Adama, J.C., F. Nkwazema, C.C. Emeka-Chri, B.A. Agugo, D.Udo Daniel, and I. Okwor. "EFFECTS OF TILLAGE METHODS AND TILLAGE DEPTHS ON PRODUCTIVITY OF GINGER IN TWO AGRO ECOLOGICAL ZONES OF NIGERIA." Journal of Agricultural Mechanization i (November 30, 2021): 21–28. https://doi.org/10.5281/zenodo.13155688.

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A field study carried out to determine appropriate tillage methods and tillage depth for ginger production in two agro ecological zones of Nigeria is reported. The ecological zones are derived Savannah and the Rain Forest. Three tillage treatments namely, ploughing once, ploughing and harrowing once and no tillage were conducted at depths of 0cm (for the no till), 5 cm, 10 cm and 15 cm. The fields were mapped using the Latin Squared (LS) design arrangement. The tillage operation in the derive Savannah zone was carried out using a 41 kW Ford tractor, 1 meter width disc plough and a three meter

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Centillas Jr., Catalino, Charles Lumbay, Charldy Wenceslao, Rica Villarosa, and Lanndon Ocampo. "Einstein Aggregators on Picture Fuzzy Sets for Evaluating Competencies in Blueprint Reading." International Journal of Sociotechnology and Knowledge Development 16, no. 1 (2025): 1–22. https://doi.org/10.4018/ijskd.365289.

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This work highlights an evaluation of blueprint reading competencies among university students, with particular attention to common and core competencies. Recognizing the ambiguity and imprecision arising from such an evaluation, Einstein aggregation operators on picture fuzzy sets were adopted to model the judgments of participants derived from a pool of mechanical technology students. Results reveal the students' competency level for each pre-identified task in blueprint reading. Although they display above-average performances, areas requiring enhancement in both competency types are identi

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Zhao, Xinlei, Shuang Wu, Nan Fang, Xiao Sun, and Jue Fan. "Evaluation of single-cell classifiers for single-cell RNA sequencing data sets." Briefings in Bioinformatics 21, no. 5 (2019): 1581–95. http://dx.doi.org/10.1093/bib/bbz096.

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Abstract Single-cell RNA sequencing (scRNA-seq) has been rapidly developing and widely applied in biological and medical research. Identification of cell types in scRNA-seq data sets is an essential step before in-depth investigations of their functional and pathological roles. However, the conventional workflow based on clustering and marker genes is not scalable for an increasingly large number of scRNA-seq data sets due to complicated procedures and manual annotation. Therefore, a number of tools have been developed recently to predict cell types in new data sets using reference data sets.

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Blank, Daniel, Annette Eicker, Laura Jensen, and Andreas Güntner. "A global analysis of water storage variations from remotely sensed soil moisture and daily satellite gravimetry." Hydrology and Earth System Sciences 27, no. 13 (2023): 2413–35. http://dx.doi.org/10.5194/hess-27-2413-2023.

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Abstract. Water storage changes in the soil can be observed on a global scale with different types of satellite remote sensing. While active or passive microwave sensors are limited to the upper few centimeters of the soil, satellite gravimetry can detect changes in the terrestrial water storage (TWS) in an integrative way, but it cannot distinguish between storage variations in different compartments or soil depths. Jointly analyzing both data types promises novel insights into the dynamics of subsurface water storage and of related hydrological processes. In this study, we investigate the gl

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Bulbul, Mohammad Farhad, Amin Ullah, Hazrat Ali, and Daijin Kim. "A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset." Sensors 22, no. 18 (2022): 6841. http://dx.doi.org/10.3390/s22186841.

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Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale data is challenging. In this work, we propose a sequence classification deep model using depth video data for scenarios when the video data are limited. Unlike summarizing the frame contents of each frame into a single class, our method can directly classify a depth video, i.e., a sequence of depth frames. Firstly, the proposed system transforms an i

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Wang, Li. "English Speech Recognition and Pronunciation Quality Evaluation Model Based on Neural Network." Scientific Programming 2022 (June 30, 2022): 1–10. http://dx.doi.org/10.1155/2022/2249722.

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An in-depth neural network-based approach is proposed to better develop an assessment model for English speech recognition and call quality assessment. By studying the structure of a deep nonlinear network, you can approximate complex functions, define distributed representations of input data, demonstrate a strong ability to learn important data set characteristics from some sample sets, and better simulate human brain analysis, and learning. The author uses in-depth learning technology to recognize English speech and has developed a speech recognition model with a deep belief network using t

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Cooper, Gordon R. J., and Rob C. Whitehead. "Determining the distance to magnetic sources." GEOPHYSICS 81, no. 2 (2016): J25—J34. http://dx.doi.org/10.1190/geo2015-0142.1.

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The distance to sources of magnetic field anomalies of a known structural index can be determined by using ratios of the analytic signal amplitudes ([Formula: see text]) of different orders, and this can be performed in several different ways. Local minima of the distance correspond to the source depth. If an incorrect structural index has been used, then the different methods will yield different depths. Hence, a comparison of the results obtained from the different methods can help us to differentiate between valid and invalid source depths. These methods are computationally straightforward,

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Karpiah, Arvin Boutik, Maxwell Azuka Meju, Roger Vernon Miller, Xavier Legrand, Prabal Shankar Das, and Raja Natasha Bt Raja Musafarudin. "Crustal structure and basement-cover relationship in the Dangerous Grounds, offshore North-West Borneo, from 3D joint CSEM and MT imaging." Interpretation 8, no. 4 (2020): SS97—SS111. http://dx.doi.org/10.1190/int-2019-0261.1.

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Accurate mapping of crustal thickness variations and the boundary relationships between sedimentary cover rocks and the crystalline basement is very important for heat-flow prediction and petroleum system modeling of a basin. Using legacy industry 3D data sets, we investigated the potential of 3D joint inversion of marine controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data incorporating resistivity anisotropy to map these parameters across subbasins in the Dangerous Grounds in the southwestern rifted margin of the South China Sea, where limited previous seismic and potential

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Liu, Hongwei, and Mustafa Naser Al-Ali. "Common-focus point-based target-oriented imaging approach for continuous seismic reservoir monitoring." GEOPHYSICS 83, no. 4 (2018): M41—M48. http://dx.doi.org/10.1190/geo2017-0842.1.

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The ideal approach for continuous reservoir monitoring allows generation of fast and accurate images to cope with the massive data sets acquired for such a task. Conventionally, rigorous depth-oriented velocity-estimation methods are performed to produce sufficiently accurate velocity models. Unlike the traditional way, the target-oriented imaging technology based on the common-focus point (CFP) theory can be an alternative for continuous reservoir monitoring. The solution is based on a robust data-driven iterative operator updating strategy without deriving a detailed velocity model. The same

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Perec, Andrzej. "Desirability Function Analysis (DFA) in Multiple Responses Optimization of Abrasive Water Jet Cutting Process." Reports in Mechanical Engineering 3, no. 1 (2022): 11–19. http://dx.doi.org/10.31181/rme200103011p.

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This paper introduces optimization of machining parameters for high-pressure abrasive water jet cutting of Hardox 500 steel utilizing desirability function analysis (DFA). The tests were carried out according to the orthogonal matrix (Taguchi) L9. The control parameters of the process such as pressure, abrasive flow rate, and traverse speed was optimized under multi-response conditions namely cutting depth and surface roughness. The optimal set of control parameters was established on the basis of the composite desirability value obtained from desirability function analysis and the significanc

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Xie, Zhen, Jianhua Zhang, and Pengfei Wang. "Event-based stereo matching using semiglobal matching." International Journal of Advanced Robotic Systems 15, no. 1 (2018): 172988141775275. http://dx.doi.org/10.1177/1729881417752759.

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In this article, we focus on the problem of depth estimation from a stereo pair of event-based sensors. These sensors asynchronously capture pixel-level brightness changes information (events) instead of standard intensity images at a specified frame rate. So, these sensors provide sparse data at low latency and high temporal resolution over a wide intrascene dynamic range. However, new asynchronous, event-based processing algorithms are required to process the event streams. We propose a fully event-based stereo three-dimensional depth estimation algorithm inspired by semiglobal matching. Our

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Wenck, Soeren, Marina Creydt, Jule Hansen, Florian Gärber, Markus Fischer, and Stephan Seifert. "Opening the Random Forest Black Box of the Metabolome by the Application of Surrogate Minimal Depth." Metabolites 12, no. 1 (2021): 5. http://dx.doi.org/10.3390/metabo12010005.

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For the untargeted analysis of the metabolome of biological samples with liquid chromatography–mass spectrometry (LC-MS), high-dimensional data sets containing many different metabolites are obtained. Since the utilization of these complex data is challenging, different machine learning approaches have been developed. Those methods are usually applied as black box classification tools, and detailed information about class differences that result from the complex interplay of the metabolites are not obtained. Here, we demonstrate that this information is accessible by the application of random

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TRAGOUDAS, SPYROS. "BOARD LEVEL PARTITIONING FOR IMPROVED PARTIAL SCAN." International Journal of High Speed Electronics and Systems 06, no. 04 (1995): 573–94. http://dx.doi.org/10.1142/s0129156495000201.

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We present a two phase board level partitioning scheme for improved partial scan on the resulting Integrated Circuits (ICs). The first phase clusters the nodes of the synchronous sequential PCB system into sets of bounded capacity. Each set represents an IC. The main objective function is to minimize the maximum number of inputs to a set. This considerably affects the test generation and response verification phases while testing the ICs. The second phase repositions the flip-flops so that we minimize the partial scan related hardware overhead for each IC, maintain a small sequential depth for

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Duan, Kangkang, and Shuangyin Cao. "Data-Driven Parameter Selection and Modeling for Concrete Carbonation." Materials 15, no. 9 (2022): 3351. http://dx.doi.org/10.3390/ma15093351.

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Concrete carbonation is known as a stochastic process. Its uncertainties mainly result from parameters that are not considered in prediction models. Parameter selection, therefore, is important. In this paper, based on 8204 sets of data, statistical methods and machine learning techniques were applied to choose appropriate influence factors in terms of three aspects: (1) the correlation between factors and concrete carbonation; (2) factors’ influence on the uncertainties of carbonation depth; and (3) the correlation between factors. Both single parameters and parameter groups were evaluated qu

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Dimitrijevic, T., B. Kahler, G. Evans, M. Collins, and A. Moule. "Depth and Distance Perception of Dentists and Dental Students." Operative Dentistry 36, no. 5 (2011): 467–77. http://dx.doi.org/10.2341/10-290-l.

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SUMMARYThe quality of work carried out by dentists is dependent, among other things, on experience, training, and manual dexterity. Historical focus on the latter as a predictor of dental performance has failed to recognize that dental competence also requires good perceptual and visual skills, not only for gathering information but also for judging positions, distances, and the size of objects and shapes. Most predictive tests ignore visual and interpretative deficiencies that could make individual acquisition of skills and interpretation of instructions difficult. Ability to estimate depth a

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Abu Bakar, Rubiah, Najdah Abd Aziz, and Rafhanah Zakirah Rosley. "AWARENESS OF GHARAR IN SALE AND PURCHASE CONTRACTS AMONG KUALA NERUS SOCIETY." Journal of Islamic, Social, Economics and Development 7, no. 43 (2022): 29–39. http://dx.doi.org/10.55573/jised.074303.

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This study was conducted to identify the awareness of gharar in sale and purchase contracts in the society of Kuala Nerus, Terengganu. Any uncertainties, doubts and shortcomings in the sale and purchase contracts are considered gharar. Using the questionnaire as a research instrument, 120 sets were distributed through online forms among randomly selected Kuala Nerus society. The methodology of this study uses quantititave methods. Descriptive analysis is used to analyse data in percentage, frequency, mean, mode and median. The result of the investigation found that the mean value shown in each

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Qin, Li-Xuan, Jian Zou, Jiejun Shi, et al. "Statistical Assessment of Depth Normalization for Small RNA Sequencing." JCO Clinical Cancer Informatics, no. 4 (September 2020): 567–82. http://dx.doi.org/10.1200/cci.19.00118.

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PURPOSE Methods for depth normalization have been assessed primarily with simulated data or cell-line–mixture data. There is a pressing need for benchmark data enabling a more realistic and objective assessment, especially in the context of small RNA sequencing. METHODS We collected a unique pair of microRNA sequencing data sets for the same set of tumor samples; one data set was collected with and the other without uniform handling and balanced design. The former provided a benchmark for evaluating evidence of differential expression and the latter served as a test bed for normalization. Next

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Ponte, Aurélien L. "Periodic Wind-Driven Circulation in an Elongated and Rotating Basin." Journal of Physical Oceanography 40, no. 9 (2010): 2043–58. http://dx.doi.org/10.1175/2010jpo4235.1.

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Abstract An idealized model is developed for the three-dimensional response of a coastal basin (e.g., lagoon, bay, or estuary) to time-periodic wind stress. This model handles basins that are deeper and/or shallower than an Ekman depth with wind forcing frequencies ranging from subinertial to superinertial. Here the model is used to describe how the response (current and sea level) of a basin deeper than one Ekman depth depends on the wind forcing frequency. At low subinertial frequencies, the response is similar to the steady wind case and is hence called “quasi steady.” There is a near-surfa

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Panboonyuen, Teerapong, Kulsawasd Jitkajornwanich, Siam Lawawirojwong, Panu Srestasathiern, and Peerapon Vateekul. "Semantic Labeling in Remote Sensing Corpora Using Feature Fusion-Based Enhanced Global Convolutional Network with High-Resolution Representations and Depthwise Atrous Convolution." Remote Sensing 12, no. 8 (2020): 1233. http://dx.doi.org/10.3390/rs12081233.

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One of the fundamental tasks in remote sensing is the semantic segmentation on the aerial and satellite images. It plays a vital role in applications, such as agriculture planning, map updates, route optimization, and navigation. The state-of-the-art model is the Enhanced Global Convolutional Network (GCN152-TL-A) from our previous work. It composes two main components: (i) the backbone network to extract features and ( i i ) the segmentation network to annotate labels. However, the accuracy can be further improved, since the deep learning network is not designed for recovering low-level featu

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Polonsky, A. B., and P. A. Sukhonos. "Comparison of ocean datasets by their ability to adequately reproduce winter anomalies in the characteristics of the upper layer ot the north–eastern part of the North Atlantic." Monitoring systems of environment, no. 1 (March 25, 2021): 137–46. http://dx.doi.org/10.33075/2220-5861-2021-1-137-146.

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This article analyzes the reproducibility of the reemergence of temperature and upper mixed layer (UML) depth anomalies in the northeastern North Atlantic during severe weather conditions observed in the Atlantic-European region in the winter of 2009/2010 and 2010/2011. The data of re-analyzes ORA-S3, GFDL, GODAS, GLORYS2v4 and objective analyzes Ishii, EN4.1.1 are used. It is confirmed that the formation of the negative temperature anomaly in UML in winter 2010/2011 is largely due to the reemergence of the ocean temperature anomaly that occurred in the winter of 2009/2010. Interannual UML dep

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Warren, Joseph D., and Peter H. Wiebe. "Accounting for biological and physical sources of acoustic backscatter improves estimates of zooplankton biomass." Canadian Journal of Fisheries and Aquatic Sciences 65, no. 7 (2008): 1321–33. http://dx.doi.org/10.1139/f08-047.

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To convert measurements of backscattered acoustic energy to estimates of abundance and taxonomic information about the zooplankton community, all of the scattering processes in the water column need to be identified and their scattering contributions quantified. Zooplankton populations in the eastern edge of Wilkinson Basin in the Gulf of Maine in the Northwest Atlantic were surveyed in October 1997. Net tow samples at different depths, temperature and salinity profiles, and multiple frequency acoustic backscatter measurements from the upper 200 m of the water column were collected. Zooplankto

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Ghannami, Mohamed Ali, Sylvie Daniel, Guillaume Sicot, and Isabelle Quidu. "A Likelihood-Based Triangulation Method for Uncertainties in Through-Water Depth Mapping." Remote Sensing 16, no. 21 (2024): 4098. http://dx.doi.org/10.3390/rs16214098.

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Coastal environments, which are crucial for economic and strategic reasons, heavily rely on accurate bathymetry for safe navigation and resource monitoring. Recent advancements in through-water photogrammetry have shown promise in mapping shallow waters efficiently. However, robust uncertainty modeling methods for these techniques, especially in challenging coastal environments, are lacking. This study introduces a novel likelihood-based approach for through-water photogrammetry, focusing on uncertainties associated with camera pose—a key factor affecting depth mapping accuracy. Our methodolog

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Deryabin, V. V., and A. E. Sazonov. "Depth-aided prediction of vessel latitude based on a neural network." Vestnik Gosudarstvennogo universiteta morskogo i rechnogo flota imeni admirala S. O. Makarova 17, no. 1 (2025): 94–104. https://doi.org/10.21821/2309-5180-2025-17-1-94-104.

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A method for determining vessel latitude based on depth using a neural network is proposed. The network takes as input a sequence of depth values measured by a single-beam echo sounder and predicts the vessel's latitude at the moment of the latest depth measurement. The network has two layers. The first layer contains neurons with hyperbolic tangent activation functions. The second layer consists of a single neuron with an identical activation function. The training dataset consists of training and validation sets. The training set is formed based on a depth layer contained within an electroni

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Péter, László, Kálmán Vad, Attila Csik, et al. "In-depth component distribution in electrodeposited alloys and multilayers." Journal of Electrochemical Science and Engineering 8, no. 1 (2018): 49–71. http://dx.doi.org/10.5599/jese.480.

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It is shown in this overview that modern composition depth profiling methods like secondary neutral mass spectroscopy (SNMS) and glow-discharge – time-of-flight mass spectrometry (GD-ToFMS) can be used to gain highly specific composition depth profile information on electrodeposited alloys. In some cases, cross-sectional transmission electron microscopy was also used for gaining complementary information; nevertheless, the basic component distribution derived with each method exhibited the same basic features. When applying the reverse sputtering direction to SNMS analysis, the near-substrate

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Dwi Laksono, David Gilang, and Amrie Firmansyah. "THE ROLE OF MANAGERIAL ABILITY IN INDONESIA: INVESTMENT OPPORTUNITY SETS, ENVIRONMENTAL UNCERTAINTY, TAX AVOIDANCE." Humanities & Social Sciences Reviews 8, no. 4 (2020): 1305–18. http://dx.doi.org/10.18510/hssr.2020.84123.

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Purpose of the study: This study aims to obtain empirical evidence of the effect of investment factors that consist of investment opportunity sets and environmental uncertainty on tax avoidance and the role of managerial ability in moderating these effects. Methodology: The analysis was conducted on 49 manufacturing companies listed on the Indonesia Stock Exchange from 2012 to 2018. It was chosen through a purposive sampling method, so 343 observations were obtained. This study engages two-panel data regression models, a model with and without moderation managerial ability. Also, this st

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