Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%. 相似文献
Artificial Intelligence Review - Visual object tracking has become one of the most active research topics in computer vision, and it has been applied in several commercial... 相似文献
Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an emerging application attracting significant attention from researchers in various areas of computer vision. Currently, the major challenge is the development of autonomous operations to complete missions and replace human operators. In this paper, based on the type of analyzing videos and images captured by drones in computer vision, we have reviewed these applications by categorizing them into three groups. The first group is related to remote sensing with challenges such as camera calibration, image matching, and aerial triangulation. The second group is related to drone-autonomous navigation, in which computer vision methods are designed to explore challenges such as flight control, visual localization and mapping, and target tracking and obstacle detection. The third group is dedicated to using images and videos captured by drones in various applications, such as surveillance, agriculture and forestry, animal detection, disaster detection, and face recognition. Since most of the computer vision methods related to the three categories have been designed for real-world conditions, providing real conditions based on drones is impossible. We aim to explore papers that provide a database for these purposes. In the first two groups, some survey papers presented are current. However, the surveys have not been aimed at exploring any databases. This paper presents a complete review of databases in the first two groups and works that used the databases to apply their methods. Vision-based intelligent applications and their databases are explored in the third group, and we discuss open problems and avenues for future research.
The Journal of Supercomputing - Multiple tasks arrive in the distributed systems that can be executed in either parallel or sequential manner. Before the execution, tasks are scheduled prioritywise... 相似文献
This paper proposes a method for designing robust H?? static output feedback stabilization of Takagi-Sugeno (T-S) fuzzy systems under actuator saturation. In this paper, the input saturation is represented by a polytopic model and the modeling error is assumed a norm-bounded uncertainty. A set invariance condition for robust H?? static output feedback system under actuator saturation is first established. Then, the estimation of the largest domain of attraction for the system is formulated and solved as a Linear Matrix Inequality (LMI) optimization problem. Two examples are used to demonstrate the effectiveness of the proposed design method. 相似文献
Elucidation of the biological functions of extracellular vesicles (EVs) and their potential roles in physiological and pathological processes is an expanding field of research. In this study, we characterized USC–derived EVs and studied their capacity to modulate the human immune response in vitro. We found that the USC–derived EVs are a heterogeneous population, ranging in size from that of micro–vesicles (150 nm–1 μm) down to that of exosomes (60–150 nm). Regarding their immunomodulatory functions, we found that upon isolation, the EVs (60–150 nm) induced B cell proliferation and IgM antibody secretion. Analysis of the EV contents unexpectedly revealed the presence of BAFF, APRIL, IL–6, and CD40L, all known to play a central role in B cell stimulation, differentiation, and humoral immunity. In regard to their effect on T cell functions, they resembled the function of mesenchymal stem cell (MSC)–derived EVs previously described, suppressing T cell response to activation. The finding that USC–derived EVs transport a potent bioactive cargo opens the door to a novel therapeutic avenue for boosting B cell responses in immunodeficiency or cancer. 相似文献
Heat shock protein 47 (HSP47), a collagen-specific molecular chaperone, is causally related to fibrotic diseases, including idiopathic pulmonary fibrosis. The identification of Compounds that interfere with the HSP47-collagen interaction is essential for the development of relevant therapeutics. Herein, we prepared human HSP47 as a soluble fusion protein expressed in E. coli and established an assay system for HSP47 inhibitor screening. We screened a natural and synthetic Compound library established at Nagasaki University. Among 1023 Compounds, 13 exhibited inhibitory activity against human HSP47, of which three inhibited its function in a dose-dependent manner. Epigallocatechin-3-O-gallate, one of these three Compounds, is a typical polyphenol Compound derived from tea leaves. Structurally related Compounds were synthesized and examined for their activity, revealing a hydroxyl group at A-ring position 5 as important for its activity. The present findings provide valuable insight for the development of natural product-derived therapeutics for fibrotic diseases, including idiopathic pulmonary fibrosis. 相似文献
Surface functionalization of blast furnace slag with sulfamic acid(a zwitterion) was performed for the removal of Cr~(3+) and methylene blue dye(MB) from water samples. The slag functionalization process was optimized using Response Surface Methodology Design. Statistical analysis of the parameters that include the sulfamic acid amount(A), reaction time(B), and temperature(C) revealed that(A) increase had a negative effect on the adsorption of both pollutants by the zwitterion slag, whereas(B) and(C)increase presented a positive impact. At the optimum condition of 2 g sulfamic acid amount, 50 min reaction time and 37 °C temperature, the prepared slag showed a removal efficiency of more than 90% for both Cr~(3+) and MB. Surface characterization by SEM/EDS, FTIR, XPS and surface area analyser, showed an improvement in surface properties and the incorporation of zwitterionic NH_2~+ and S@O groups of sulfamic acid. Adsorption isotherm and kinetic studies conducted with the zwitterion slag showed the adsorption process was suited to Freundlich isotherm model and pseudo-second-order kinetic model.The thermodynamic study conducted revealed the spontaneity of the process based on the calculated negative DG(Gibb's free energy) values. The prepared zwitterion slag offered easy regeneration with dilute HCl solution and showed a considerable removal(Cr3+: 65% and MB: 80%) for both pollutants even after 3 cycles of usage. 相似文献
Auxin response factors (ARFs) play important roles in various plant physiological processes; however, knowledge of the exact role of ARFs in plant responses to water deficit is limited. In this study, SlARF4, a member of the ARF family, was functionally characterized under water deficit. Real-time fluorescence quantitative polymerase chain reaction (PCR) and β-glucuronidase (GUS) staining showed that water deficit and abscisic acid (ABA) treatment reduced the expression of SlARF4. SlARF4 was expressed in the vascular bundles and guard cells of tomato stomata. Loss of function of SlARF4 (arf4) by using Clustered Regularly Interspaced Short Palindromic Repeats/Cas 9 (CRISPR/Cas 9) technology enhanced plant resistance to water stress and rehydration ability. The arf4 mutant plants exhibited curly leaves and a thick stem. Malondialdehyde content was significantly lower in arf4 mutants than in wildtype plants under water stress; furthermore, arf4 mutants showed higher content of antioxidant substances, superoxide dismutase, actual photochemical efficiency of photosystem II (PSII), and catalase activities. Stomatal and vascular bundle morphology was changed in arf4 mutants. We identified 628 differentially expressed genes specifically expressed under water deficit in arf4 mutants; six of these genes, including ABA signaling pathway-related genes, were differentially expressed between the wildtype and arf4 mutants under water deficit and unlimited water supply. Auxin responsive element (AuxRE) elements were found in these genes’ promoters indicating that SlARF4 participates in ABA signaling pathways by regulating the expression of SlABI5/ABF and SCL3, thereby influencing stomatal morphology and vascular bundle development and ultimately improving plant resistance to water deficit. 相似文献
The discovery of eco-friendly, rapid, and cost-effective compounds to control diseases caused by microbes and insects are the main challenges. Herein, the magnesium oxide nanoparticles (MgO-NPs) are successfully fabricated by harnessing the metabolites secreted by Penicillium chrysogenum. The fabricated MgO-NPs were characterized using UV-Vis, XRD, TEM, DLS, EDX, FT-IR, and XPS analyses. Data showed the successful formation of crystallographic, spherical, well-dispersed MgO-NPs with sizes of 7–40 nm at a maximum wavelength of 250 nm. The EDX analysis confirms the presence of Mg and O ions as the main components with weight percentages of 13.62% and 7.76%, respectively. The activity of MgO-NPs as an antimicrobial agent was investigated against pathogens Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa, Escherichia coli, and Candida albicans, and exhibited zone of inhibitions of 12.0 ± 0.0, 12.7 ± 0.9, 23.3 ± 0.8, 17.7 ± 1.6, and 14.7 ± 0.6 mm respectively, at 200 µg mL−1. The activity is decreased by decreasing the MgO-NPs concentration. The biogenic MgO-NPs exhibit high efficacy against different larvae instar and pupa of Anopheles stephensi, with LC50 values of 12.5–15.5 ppm for I–IV larvae instar and 16.5 ppm for the pupa. Additionally, 5 mg/cm2 of MgO-NPs showed the highest protection percentages against adults of Anopheles stephensi, with values of 100% for 150 min and 67.6% ± 1.4% for 210 min. 相似文献