Deep neural networks (DNNs) can learn accurately from large quantities of labeled input data but often fail to do so when are scarce. DNNs sometimes generalize on test sampled different distributions. Unsupervised deep domain adaptation (DDA) techniques have been proven useful no labels available and distribution shifts observed in the target (TD). In this study, experiments performed seismic i...

Abstract In this study, we propose a volume‐to‐point framework for quantitative precipitation estimation (QPE) based on the Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS) Mosaic Radar data set. With volume consisting of time series gridded radar reflectivities over Taiwan area, used machine learning algorithms to establish statistical model QPE in weather ...

In this paper we are interested in the problem of learning an over-complete basis and a methodology such that the reconstruction or inverse problem does not need optimization. We analyze the optimality of the presented approaches, their link to popular already known techniques s.a. Artificial Neural Networks,k-means or Oja’s learning rule. Finally, we will see that one approach to reach the opt...

the analysis of geochemical data in frequency domain, as indicated in this research study, can provide new exploratory informationthat may not be exposed in spatial domain. to identify deep geochemical anomalies, sulfide zone and geochemical noises in dalli cu–au porphyry deposit, a new approach based on coupling fourier transform (ft) and principal component analysis (pca) has beenused. the re...

We view match as an operator that takes two graph-like structures (e.g., classifications, XML schemas) and produces a mapping between the nodes of these graphs that correspond semantically to each other. Semantic matching is based on two ideas: (i) we discover mappings by computing semantic relations (e.g., equivalence, more general); (ii) we determine semantic relations by analyzing the meanin...

Interpretation of artificial intelligence on the base of the philosophical fictionalism allowed discussing the educational technologies in the context of conditions for strengthening of discursive power of pupils’ thought. The artificial intelligence received broad interpretation as an embodiment of a literary image, which did not have unambiguous link with the area of logical formalisms and ma...

In this thesis we prove the existence of m-armed spiral wave solutions for the complex Ginzburg-Landau equation in the circular and spherical geometries. Instead of applying the shooting method in the literature, we establish a functional approach and generalize the known results of existence for rigidly-rotating spiral waves. Moreover, we prove the existence of two new patterns: frozen spirals...

We investigate people’s attitudes towards the possible use of mobile negotiation support systems (NSS) in different social contexts and the consequences for their design. For that purpose we developed an online survey based on existing models of technology acceptance. In the questionnaire we showed five filmed scenarios of NSS use contexts. The data collected from 120 respondents, showed (a) th...

Sufficiency criteria are established to ensure the asymptotic stability and boundedness of solutions to third-order nonlinear delay differential equations of the form ... x (t) + e(x(t), ẋ(t), ẍ(t))ẍ(t) + g(x(t− r), ẋ(t− r)) + ψ(x(t− r)) = p(t, x(t), x(t − r), x(t), x(t− r), x(t)). By using Lyapunov’s functional approach, we obtain two new results on the subject, which include and improve some ...