О верификации измерений скорости поверхностных течений когерентным радаром СВЧ-диапазона с помощью дрифтеров

Introduction. Conventional contact measurements of hydrographic parameters frequently fail to provide the necessary accuracy of data in the field of water area monitoring. This problem can be solved using coherent radars enabling direct measurements of surface current velocities.Aim. To establish the accuracy of surface current velocities measured by a Doppler radar using drifter data.Materials and methods. In June 2022, coastal operational oceanography studies were conducted at the hydrophysical test site of the Institute of Oceanology of the Russian Academy of Sciences in the Black Sea near Gelendzhik. Measurements were carried out using a coherent X-band radar installed on the Ashamba research vessel simultaneously with drifter experiments using Lagrangian drifters of the near-surface layer with an underwater 0.5 m sail. Coordinates were transmitted via mobile communication. The drifter data on the current velocity and direction were used to verify radar measurements. Measurements were taken onboard of the research vessel at a low speed and different distances from the shore, near the drifters. The tracks of the vessel and drifters were recorded simultaneously. Processing of the radar data involved obtaining Doppler spectra of signals to estimate the dynamic processes on the sea surface, including the current velocity.Results. Radial components of the near-surface current velocity were calculated. Then, the current velocity values obtained based on the drifter and radar data were compared.Conclusion. The present work makes a contribution to the advancement of methods for measuring surface currents from the board of a moving ship by Doppler radars. The obtained results confirm the suitability of the radar hardware and software and signal processing algorithms for measuring currents. The radar measurement data were found agree well with drifter data in the velocity range from 15 cm/s.Введение. Традиционные контактные средства измерений гидрографических параметров зачастую не обеспечивают необходимую оперативность получаемых данных для решения задач мониторинга акваторий. Перспективным направлением является применение когерентных радаров, позволяющих непосредственно измерять скорости поверхностных течений.Цель работы. Оценка достоверности результатов измерений приповерхностной скорости течения доплеровским радаром сравнением с данными дрифтеров.Материалы и методы. В июне 2022 г. был проведен эксперимент по прибрежной оперативной океанографии в Черном море на акватории гидрофизического полигона "Геленджик" Южного отделения Института океанологии РАН с использованием доплеровского радара. Скорость течения измерялась когерентизированным навигационным радиолокатором сантиметрового диапазона с цифровой обработкой, установленным на научноисследовательском судне "Ашамба", одновременно с дрифтерными экспериментами с использованием лагранжевых дрифтеров приповерхностного слоя с подводным парусом высотой 0.5 м, с передачей координат по мобильной связи. Данные дрифтеров о скорости и направлении течения использовались для верификации радарных измерений. Измерения проводились с борта научно-исследовательского судна на малом ходу на различном расстоянии от берега, вблизи дрифтеров. В процессе измерений осуществлялась запись треков судна и дрифтеров. Обработка данных радиолокатора основана на исследовании спектральных характеристик отраженного сигнала, позволяющих оценивать динамические процессы на морской поверхности.Результаты. По результатам обработки доплеровских спектров были получены радиальные составляющие скорости приповерхностных течений, далее было выполнено сопоставление скорости течений по данным дрифтеров и данным радиолокации.Заключение. Настоящая работа является определенным шагом в усовершенствовании методов измерений поверхностных течений с борта движущегося судна доплеровским радаром. Результаты верификации подтверждают пригодность аппаратно-программной части радара и алгоритмов обработки сигнала для измерения течений. Данные радиолокационных измерений хорошо согласуются с данными дрифтеров в диапазоне скоростей от 15 см/с

Airborne Weather Radar Concept for Measuring Water Surface Backscattering Signature and Sea Wind at Circular Flight

A concept for measuring water surface backscattering signature and wind over sea using airborne weather radar is discussed. The radar operates in the ground-mapping mode as a scatterometer, in addition to its meteorological and navigation application. An aircraft circular flight is used under such measurement. Recommendations to perform measurement of the water surface backscattering signature along with a sea wind retrieval algorithm are proposed. A simulation study of wind vector estimation is performed. The results obtained show that airborne weather radar can provide reasonable sea wind vector retrieval accuracy

Sea Surface Wind Measurement by Airborne Weather Radar Scanning in a Wide-Size Sector

We suggest a conceptual approach for measuring the near-surface wind vector over water using the airborne weather radar, in addition to its standard meteorological and navigation applications. The airborne weather radar operates in the ground-mapping mode in the range of high to medium incidence angles as a scatterometer. Using the aircraft rectilinear flight over the water surface, measuring the geometry and the geophysical model function, we show that the wind vector can be successfully recovered from the azimuth normalized radar cross-section data obtained from a scanning sector of up to ±100°. The efficiency and accuracy of the proposed wind vector measurement algorithms are supported by computer simulations indicating their potential as a powerful tool for the wind field reconstruction. Some limitations and recommendations of the suggested approach are further discussed

On the maximum quasi-clique problem

AbstractGiven a simple undirected graph G=(V,E) and a constant γ∈(0,1), a subset of vertices is called a γ-quasi-clique or, simply, a γ-clique if it induces a subgraph with the edge density of at least γ. The maximum γ-clique problem consists in finding a γ-clique of largest cardinality in the graph. Despite numerous practical applications, this problem has not been rigorously studied from the mathematical perspective, and no exact solution methods have been proposed in the literature. This paper, for the first time, establishes some fundamental properties of the maximum γ-clique problem, including the NP-completeness of its decision version for any fixed γ satisfying 0<γ<1, the quasi-heredity property, and analytical upper bounds on the size of a maximum γ-clique. Moreover, mathematical programming formulations of the problem are proposed and results of preliminary numerical experiments using a state-of-the-art optimization solver to find exact solutions are presented

Sea surface wind measurement by airborne weather radar scanning in a wide-size sector

We suggest a conceptual approach for measuring the near-surface wind vector over water using the airborne weather radar, in addition to its standard meteorological and navigation applications. The airborne weather radar operates in the ground-mapping mode in the range of high to medium incidence angles as a scatterometer. Using the aircraft rectilinear flight over the water surface, measuring the geometry and the geophysical model function, we show that the wind vector can be successfully recovered from the azimuth normalized radar cross-section data obtained from a scanning sector of up to ±100°. The efficiency and accuracy of the proposed wind vector measurement algorithms are supported by computer simulations indicating their potential as a powerful tool for the wind field reconstruction. Some limitations and recommendations of the suggested approach are further discussed.Support of this work by the Russian Science Foundation (project No. 16-19-00172)

On Maximum Degree-Based Γ-Quasi-Clique Problem: Complexity And Exact Approaches

We consider the problem of finding a degree-based γ-quasi-clique of maximum cardinality in a given graph for some fixed γ ∈ (0,1]. A degree-based γ-quasi-clique (often referred to as simply a quasi-clique) is a subgraph, where the degree of each vertex is at least γ times the maximum possible degree of a vertex in the subgraph. A degree-based γ-quasi-clique is a relative clique relaxation model, where the case of γ=1 corresponds to the well-known concept of a clique. In this article, we first prove that the problem is NP-hard for any fixed γ ∈ (0,1], which addresses one of the open questions in the literature. More importantly, we also develop new exact solution methods for solving the problem and demonstrate their advantages and limitations in extensive computational experiments with both random and real-world networks. Finally, we outline promising directions of future research including possible functional generalizations of the considered clique relaxation model. © 2017 Wiley Periodicals, Inc. NETWORKS, Vol. 71(2), 136–152 2018

Graph-based exploration and clustering analysis of semantic spaces

The goal of this study is to demonstrate how network science and graph theory tools and concepts can be effectively used for exploring and comparing semantic spaces of word embeddings and lexical databases. Specifically, we construct semantic networks based on word2vec representation of words, which is “learnt” from large text corpora (Google news, Amazon reviews), and “human built” word networks derived from the well-known lexical databases: WordNet and Moby Thesaurus. We compare “global” (e.g., degrees, distances, clustering coefficients) and “local” (e.g., most central nodes and community-type dense clusters) characteristics of considered networks. Our observations suggest that human built networks possess more intuitive global connectivity patterns, whereas local characteristics (in particular, dense clusters) of the machine built networks provide much richer information on the contextual usage and perceived meanings of words, which reveals interesting structural differences between human built and machine built semantic networks. To our knowledge, this is the first study that uses graph theory and network science in the considered context; therefore, we also provide interesting examples and discuss potential research directions that may motivate further research on the synthesis of lexicographic and machine learning based tools and lead to new insights in this area.peerReviewe

Stochastic Decision Problems With Multiple Risk-Averse Agents

We consider a stochastic decision problem, with dynamic risk measures, in which multiple risk-averse agents make their decisions to minimize their individual accumulated risk-costs over a finite-time horizon. Specifically, we introduce multi-structure dynamic risk measures induced from conditional g-expectations, where the latter are associated with the generator functionals of certain BSDEs that implicitly take into account the risk-cost functionals of the risk-averse agents. Here, we also assume that the solutions for such BSDEs almost surely satisfy a stochastic viability property w.r.t. a certain given closed convex set. Using a result similar to that of the Arrow–Barankin–Blackwell theorem, we establish the existence of consistent optimal decisions for the risk-averse agents, when the set of all Pareto optimal solutions, in the sense of viscosity solutions, for the associated dynamic programming equations is dense in the given closed convex set. Finally, we comment on the characteristics of acceptable risks w.r.t. some uncertain future outcomes or costs, where results from the dynamic risk analysis are part of the information used in the risk-averse decision criteria

Dense percolation in large-scale mean-field random networks is provably "explosive".

Recent reports suggest that evolving large-scale networks exhibit "explosive percolation": a large fraction of nodes suddenly becomes connected when sufficiently many links have formed in a network. This phase transition has been shown to be continuous (second-order) for most random network formation processes, including classical mean-field random networks and their modifications. We study a related yet different phenomenon referred to as dense percolation, which occurs when a network is already connected, but a large group of nodes must be dense enough, i.e., have at least a certain minimum required percentage of possible links, to form a "highly connected" cluster. Such clusters have been considered in various contexts, including the recently introduced network modularity principle in biological networks. We prove that, contrary to the traditionally defined percolation transition, dense percolation transition is discontinuous (first-order) under the classical mean-field network formation process (with no modifications); therefore, there is not only quantitative, but also qualitative difference between regular and dense percolation transitions. Moreover, the size of the largest dense (highly connected) cluster in a mean-field random network is explicitly characterized by rigorously proven tight asymptotic bounds, which turn out to naturally extend the previously derived formula for the size of the largest clique (a cluster with all possible links) in such a network. We also briefly discuss possible implications of the obtained mathematical results on studying first-order phase transitions in real-world linked systems