This work deals with constructal design (CD) for the geometrical investigation of a complex cavity in the form of double Y inserted for chilling a rectangular heat-generating solid body. The purpose is to minimize the...
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Complex networks offer a powerful framework for modeling linguistic phenomena. This study compares five distinct methods for representing sentences as networks, each with unique edge definitions: (1) a lines approach,...
Complex networks offer a powerful framework for modeling linguistic phenomena. This study compares five distinct methods for representing sentences as networks, each with unique edge definitions: (1) a lines approach, where edges represent token (e.g., word) adjacency; (2) a close-range co-occurrence approach, where edges are based on the probability of tokens co-occurring at distance one or two; (3) a cliques approach, where edges connect tokens co-occurring within the same sentence; (4) a dependency-based approach, where edges are defined by syntactic dependencies extracted by a parser; (5) an IF-trimmed-subgraphs approach, where edges are determined by the Incidence-Fidelity (IF) Index. While the first four approaches are well established in the literature, the last one is a novel proposal. We also examined the effects of limiting the vertices to lemmas (i.e., words with inflections removed) and to lexical lemmas (i.e., nouns, adjectives, verbs, and adverbs) as opposed to the unaltered words. Our results reveal that these approaches yield networks with varying average minimal path lengths and degrees, influencing the interpretation of results. While small-world behavior remains consistent across networks, scale-free behavior analysis is affected. Notably, excluding functional words significantly alters degree distributions. We suggest, in order of relevance and according to the resources available, the dependency-based, the close-range co-occurrence, and the lines approaches for cases in which syntactic relations are central, and the IF-trimmed-subgraphs and the cliques approaches for cases in which semantic relations are central. Representation of the sentence “we calculated two sets of adjusted values as follows” using five approaches - (1) the lines approach, (2) the close-range cooccurrence approach, (3) the cliques approach, (4) the dependency-based approach, and (5) the IF-trimmed-subgraphs approach - and three vertex definitions - (1) vertices representing
Diabetic Retinopathy (DR) is a microvascular complication related to diabetes that affects approximately 33% of individuals with this condition and, if not detected and treated early, can lead to irreversible vision l...
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ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
Diabetic Retinopathy (DR) is a microvascular complication related to diabetes that affects approximately 33% of individuals with this condition and, if not detected and treated early, can lead to irreversible vision loss. Fundus lesions such as Hard and Soft Exudates, Hemorrhages, and Microaneurysms typically identify DR. The development of computational methods to segment these lesions plays a fundamental role in the early diagnosis of the disease. This paper proposes a new approach that uses an R2U-Net combined with data augmentation techniques for segmenting fundus lesions. We trained, adjusted, and evaluated the proposed work in the DDR dataset, achieving an accuracy of 99.87% and a mean Intersection over Union (mIoU) equal 59.69%. Furthermore, we assessed it in the IDRiD dataset, achieving an mIoU of 49.92%. The results obtained in the experiments highlight the potential contribution of the model in the lesion annotations for creating new DR datasets, which is essential given the scarcity of annotations in publicly available datasets.
作者：
A A NurI M RadjawaneT SuprijoI MandangDepartment of Earth Science
Faculty of Earth Science and Technology Bandung Institute of Technology Jalan Ganesha No 10 Bandung 40132 Indonesia Hydro-Atmosphere Environment Research Group
Physical Oceanography and Computational Modeling Laboratory Program Study of Physics Faculty of Mathematics and Natural Sciences Mulawarman University Jalan Barong Tongkok No 04 Samarinda 75123 Indonesia
The coastal area in Balikpapan Bay and its surrounding area has been devastated after the burst of an underwater oil pipe at the bay on March 31st, 2018, and the crude oil still continues spreading for a few days late...
The coastal area in Balikpapan Bay and its surrounding area has been devastated after the burst of an underwater oil pipe at the bay on March 31st, 2018, and the crude oil still continues spreading for a few days later. A three-dimensional hydrodynamic model is used to simulate the currents dynamic and investigate the influence of the current circulation on the spreading of the oil spill in Balikpapan Bay from March 31th to April 15th, 2018, to cover the event i.e. several weeks after the oil spill incident. Model results are validated by calculating the RMSE, MAPE and model skill using water level between available observation data at Semayang Port, Balikpapan station and numerical model from October 1st, 2012 to January 1st, 2013. Verification result of tidal elevation data from observation and model prediction shows a good agreement with RMSE = 7.8 cm, MAPE = 14.3% and model skill = 0.995. Surface currents circulation in Balikpapan Bay can be distinguished by the currents pattern on the spring tide and neap tide condition. During the spring tide condition, the surface currents mostly move to the east after coming out from the bay. However, the surface currents are strongly going southward after come out from the bay on the neap tide condition. Based on the satellite images captured for the next days after the event, the spreading pattern of the oil spill seems to be matched to the pattern of surface currents circulation on the spring tide condition. From the analysis of the model result, it shows that the currents circulation playing the main role to disperse the oil spill in Balikpapan Bay towards the Makassar Strait.
The transit timing variation (TTV) and transmission spectroscopy analyses of the planet HAT-P-37b, which is a hot Jupiter orbiting an G-type star, were performed. Nine new transit light curves are obtained and analyse...
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Variations of volume transport in the Halmahera Sea are strongly influenced by the El Nino Southern Oscillation (ENSO). Based on the Southern Oscillation Index (SOI), in 2011 La Nina event took place with a strength o...
Variations of volume transport in the Halmahera Sea are strongly influenced by the El Nino Southern Oscillation (ENSO). Based on the Southern Oscillation Index (SOI), in 2011 La Nina event took place with a strength of 3.02, while in 2015 El Nino occurred with a strength of -2.6. This paper discusses the variation of transport volume caused by the ENSO phenomenon based on the results of the Regional Ocean Model System (ROMS). On the Halmahera Sea at a latitude of 0.3°S with a width of 67 km and a depth of down to 200 m, net volume transport always moves southward. The largest volume transport in La Nina 2011 occurred in September-October, which was -8.9 Sv. Meanwhile, in El Nino 2015 the largest volume transport occurred in July-August, which was equal to -4.9 Sv. The cross correlation coefficient between volume transport and SOI in 2011 and 2015 was r = 0.55 and r = 0.61 respectively, where these results indicate a strong relationship.
Dynamic processes on networks, be it information transfer in the Internet, contagious spreading in a social network, or neural signaling, take place along shortest or nearly shortest paths. Unfortunately, our maps of ...
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We present the transit timing variation (TTV) and planetary atmosphere analysis of the Neptune-mass planet HAT-P-26 b. We present a new set of 13 transit light curves from optical ground-based observations and combine...
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We present a transit-timing variation (TTV) and planetary atmosphere analysis of the Neptune-mass planet HAT-P-26 b. We present a new set of 13 transit light curves from optical ground-based observations and combine t...
DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 20...
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