54 research outputs found
Image data filtering and automatic detection of damages within asphalt with the help of ground-penetrating radar (GPR) and machine learning methods
No full textDamages within asphalt have been interesting phenomena in asphalt engineering, the detection of which is significant for maintenance of road sections. This project focuses on cracks and delaminations. An attempt was made to filter radar image data with a method based on a VNA-antenna-multilayered system model as well as the data from two specific measurements, aiming at better visualizing cracks as well as other features in radar image, and the results were checked and analysed. This part of work has provided an application of the aforementioned method of radar image data filtering as well as the points worth noticing and avoiding when making this application.For delaminations, machine learning algorithms, first the EM algorithm and then the YOLO v3 algorithm, were used as an attempt to highlight and detect them. Though the results still need improving, it is still valuable that the workload for human intervention can be alleviated with the help of these algorithms and that better performance can be expected based on current work, with the increasing amount of data with high quality achieved in the future.Applied Geophysics | IDEA Leagu
A Novel Intelligent Model for Monthly Streamflow Prediction Using Similarity-Derived Method
No full textAccurate monthly streamflow prediction is crucial for effective flood mitigation and water resource management. The present study proposes an innovative similarity-derived model (SDM), developed based on the observation that similar monthly streamflow patterns recur across different years under comparable hydrological and climate conditions. The model is applied to the Lancang River Basin in China. The model performance is compared with the commonly used support vector machine (SVM) and Mean methods. Evaluation measures such as RMSE, MAPE, and NSE confirm that SDM6 with a reference period of six months achieves the best performance, improving the Mean model by 79.9 m3/s in RMSE, 6.07% in MAPE, and 8.62% in NSE, and the SVM by 53.65 m3/s, 0.24%, and 5.53%, respectively
UPAYA POLITIK HEGEMONI RUSIA TERHADAP KONFLIK DI UKRAINA
No full textThis research discusses Russia's hegemony efforts in the conflict in Ukraine. This study identifies Russia's national interests in this conflict, including defensive, influence, and ideological interests. Russia considers Ukraine to be an important region for protecting national interests, especially in terms of defense. This research also refers to Russia's hegemonic strategy by intervening in the Ukrainian conflict. This article aims to discuss "How does Russia carry out hegemonic politics over the conflict in Ukraine?" by using John Mearsheimer's theory of offensive realism hegemony. As for this article, the type of research used is descriptive research with qualitative methods. This article is bibliographic in nature with data collection using the library research method used by the author. Hegemony is carried out by Russia as a superpower which has the opportunity to influence hegemonic power. Russia uses various means such as annexation of Crimea, military alliance, and political support to influence the thoughts and values of Ukrainian society to achieve its goals. Russia's intervention in Ukraine involved military force, regional separatist groups, alliance, and influence of power, causing a shift in hegemony, and international actors such as the EU and the United States posing a threat to Russia
Deterioration of organic coatings on concrete under artificial aging
No full textThe deterioration of organic coatings on concrete is closely linked to the efficiency in the protection process of reinforced structures. In the present work, polyurea resin and epoxy resin, which are widely used engineering coatings, were selected to measure and compare the performance under artificial aging. Fourier Transform infrared spectroscopy, water contact angle and scanning electron microscope were used to determine the deterioration of coatings. X-ray fluorescence method was used to measure chloride content passing through the coatings, which represent the efficiency of protection. Test results demonstrate that both deterioration and resistance to corrosion are important in assessment of the organic coatings under aging
Three-Dimensional Myoarchitecture of the Lower Esophageal Sphincter and Esophageal Hiatus Using Optical Sectioning Microscopy
No full textAbstractStudies to date have failed to reveal the anatomical counterpart of the lower esophageal sphincter (LES). We assessed the LES and esophageal hiatus morphology using a block containing the human LES and crural diaphragm, serially sectioned at 50 μm intervals and imaged at 8.2 μm/pixel resolution. A 3D reconstruction of the tissue block was reconstructed in which each of the 652 cross sectional images were also segmented to identify the boundaries of longitudinal (LM) and circular muscle (CM) layers. The CM fascicles on the ventral surface of LES are arranged in a helical/spiral fashion. On the other hand, the CM fascicles from the two sides cross midline on dorsal surface and continue as sling/oblique muscle on the stomach. Some of the LM fascicles of the esophagus leave the esophagus to enter into the crural diaphragm and the remainder terminate into the sling fibers of the stomach. The muscle fascicles of the right crus of diaphragm which form the esophageal hiatus are arranged like a “noose” around the esophagus. We propose that circumferential squeeze of the LES and crural diaphragm is generated by a unique myo-architectural design, each of which forms a “noose” around the esophagus.</jats:p
Nucleation and growth of WSe <sub>2</sub> : enabling large grain transition metal dichalcogenides
No full textThe limited grain size (< 200 nm) for transition metal dichalcogenides (TMDs) grown by molecular beam epitaxy (MBE) reported in the literature thus far is unsuitable for high-performance device applications. In this work, the fundamental nucleation and growth behavior of WSe₂ is investigated through a detailed experimental design combined with on-lattice, diffusion-based first principles kinetic modeling to enable large area TMD growth. A three-stage adsorption-diffusion-attachment mechanism is identified and the adatom stage is revealed to play a significant role in the nucleation behavior. To limit the nucleation density and promote 2D layered growth, it is necessary to have a low metal flux in conjunction with an elevated substrate temperature. At the same time, providing a Se-rich environment further limits the formation of W-rich nuclei which suppresses vertical growth and promotes 2D growth. The fundamental understanding gained through this investigation has enabled an increase of over one order of magnitude in grain size for WSe₂ thus far, and provides valuable insight into improving the growth of other TMD compounds by MBE and other growth techniques such as chemical vapor deposition (CVD).NSF Award No. 1407765; National Research Foundation of Korea no. 2013K1A4A3055679Erik Jonsson School of Engineering and Computer Scienc
Myoarchitecture of the Human Esophageal Hiatus (Crural Diaphragm) Determined From CT-Scan & Microscopic Cross-Sectional Images
No full textMicroscopic Assessment of the Lower Esophageal Sphincter Myoarchitecture Reveals it's Unique Morphology
No full textThree-Dimensional Myoarchitecture of the Lower Esophageal Sphincter and Esophageal Hiatus Using Optical Sectioning Microscopy
No full textPrompt-based contrastive learning to combat the COVID-19 infodemic
No full textThe COVID-19 pandemic has brought about an influx of misinformation and disinformation online, especially on social media. The World Health Organization has identified combating this infodemic as one of its top priorities, as false and misleading information can lead to negative consequences, such as the spread of conspiracy theories, false remedies, and xenophobia. This study presents a prompt-based contrastive learning approach that can be employed to address this issue. This method was designed to overcome challenges such as data scarcity and class imbalance commonly found in social media. Fighting the infodemic is modeled as a series of text classification problems in which questions relevant to credibility of the texts, their potential harm to society and the necessity of government intervention need to be answered. Experiments show that prompt-based contrastive learning is effective in assessing the accuracy of COVID-19-related online text. © The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature 2025
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