Imbalance Knowledge-Driven Multi-modal Network for Land-Cover Semantic Segmentation Using Images and LiDAR Point Clouds

Despite the good results that have been achieved in unimodal segmentation, the inherent limitations of individual data increase the difficulty of achieving breakthroughs in performance. For that reason, multi-modal learning is increasingly being explored within the field of remote sensing. The present multi-modal methods usually map high-dimensional features to low-dimensional spaces as a preprocess before feature extraction to address the nonnegligible domain gap, which inevitably leads to information loss. To address this issue, in this paper we present our novel Imbalance Knowledge-Driven Multi-modal Network (IKD-Net) to extract features from raw multi-modal heterogeneous data directly. IKD-Net is capable of mining imbalance information across modalities while utilizing a strong modal to drive the feature map refinement of the weaker ones in the global and categorical perspectives by way of two sophisticated plug-and-play modules: the Global Knowledge-Guided (GKG) and Class Knowledge-Guided (CKG) gated modules. The whole network then is optimized using a holistic loss function. While we were developing IKD-Net, we also established a new dataset called the National Agriculture Imagery Program and 3D Elevation Program Combined dataset in California (N3C-California), which provides a particular benchmark for multi-modal joint segmentation tasks. In our experiments, IKD-Net outperformed the benchmarks and state-of-the-art methods both in the N3C-California and the small-scale ISPRS Vaihingen dataset. IKD-Net has been ranked first on the real-time leaderboard for the GRSS DFC 2018 challenge evaluation until this paper's submission

A Bayesian method for detecting stellar flares

We present a Bayesian-odds-ratio-based algorithm for detecting stellar flares in light curve data. We assume flares are described by a model in which there is a rapid rise with a half-Gaussian profile, followed by an exponential decay. Our signal model also contains a polynomial background model. This is required to fit underlying light curve variations that are expected in the data, which could otherwise partially mimic a flare. We characterise the false alarm probability and efficiency of this method and compare it with a simpler thresholding method based on that used in Walkowicz et al (2011). We find our method has a significant increase in detection efficiency for low signal-to-noise ratio (S/N) flares. For a conservative false alarm probability our method can detect 95% of flares with S/N less than ~20, as compared to S/N of ~25 for the simpler method. As an example we have applied our method to a selection of stars in Kepler Quarter 1 data. The method finds 687 flaring stars with a total of 1873 flares after vetos have been applied. For these flares we have characterised their durations and and signal-to-noise ratios.Comment: Accepted for MNRAS. The code used for the analysis can be found at https://github.com/BayesFlare/bayesflare/releases/tag/v1.0.

Tracing Large-Scale Structure with Radio Sources

In this thesis, I investigate the spatial distribution of radio sources, and quantify their clustering strength over a range of redshifts, up to z _ 2:2, using various forms of the correlation function measured with data from several multi-wavelength surveys. I present the optical spectra of 30 radio AGN (S1:4 > 100 mJy) in the GAMA/H-ATLAS fields, for which emission line redshifts could be deduced, from observations of 79 target sources with the EFOSC2 spectrograph on the NTT. The mean redshift of these sources is z = 1:2; 12 were identified as quasars (40 per cent), and 6 redshifts (out of 24 targets) were found for AGN hosts to multiple radio components. While obtaining spectra for hosts of these multi-component sources is possible, their lower success rate highlights the difficulty in acheiving a redshift-complete radio sample. Taking an existing spectroscopic redshift survey (GAMA) and radio sources from the FIRST survey (S1:4 > 1 mJy), I then present a cross-matched radio sample with 1,635 spectroscopic redshifts with a median value of z = 0:34. The spatial correlation function of this sample is used to find the redshiftspace (s0) and real-space correlation lengths (r0 _ 8:2 h1Mpc), and a mass bias of _1.9. Insight into the redshift-dependence of these quantities is gained by using the angular correlation function and Limber inversion to measure the same spatial clustering parameters. Photometric redshifts from SDSS/UKIDSS are incorporated to produce a larger matched radio sample at z ' 0:48 (and low- and high-redshift subsamples at z ' 0:30 and z ' 0:65), while their redshift distribution is subtracted from that taken from the SKADS radio simulations to estimate the redshift distribution of the remaining unmatched sources (z ' 1:55). The observed bias evolution over this redshift range is compared with model predictions based on the SKADS simulations, with good agreement at low redshift. The bias found at high redshift significantly exceeds these predictions, however, suggesting a more massive population of galaxies than expected, either due to the relative proportions of different radio sources, or a greater typical halo mass for the high-redshift sources. Finally, the reliance on a model redshift distribution to reach to higher redshifts is removed, as the angular cross-correlation function is used with deep VLA data (S1:4 > 90 _Jy) and optical/IR data from VIDEO/CFHTLS (Ks < 23:5) over 1 square degree. With high-quality photometric redshifts up to z _ 4, and a high signal-to-noise clustering measurement (due to the _100,000 Ks-selected galaxies), I am able to find the bias of a matched sample of only 766 radio sources (as well as of v vi the VIDEO sources), divided into 4 redshift bins reaching a median bias at z ' 2:15. Again, at high redshift, the measured bias appears to exceed the prediction made from the SKADS simulations. Applying luminosity cuts to the radio sample at L > 1023 WHz1 and higher (removing any non-AGN sources), I find a bias of 8–10 at z _ 1:5, considerably higher than for the full sample, and consistent with the more numerous FRI AGN having similar mass to the FRIIs (M _ 1014 M_), contrary to the assumptions made in the SKADS simulations. Applying this adjustment to the model bias produces a better fit to the observations for the FIRST radio sources cross-matched with GAMA/SDSS/UKIDSS, as well as for the high-redshift radio sources in VIDEO. Therefore, I have shown that we require a more robust model of the evolution of AGN, and their relation to the underlying dark matter distribution. In particular, understanding these quantities for the abundant FRI population is crucial if we are to use such sources to probe the cosmological model as has been suggested by a number of authors (e.g. Raccanelli et al., 2012; Camera et al., 2012; Ferramacho et al., 2014

Experimental study of wave dispersion and stability in crossing seas and on sheared currents

This thesis considers the effects of crossing seas and linearly sheared current on the dispersion and stability of surface gravity waves. Experimental data are compared against predictions by three different nonlinear Schr¨odinger equations (NLSE): the constant-vorticity (vor-NLSE), used to simulate wave evolution on a linearly sheared current; the coupled (CNLSE), which predicts the interaction between two crossing wave systems; and the two-dimensional (2D+1 NLSE), which allows an angle between the carrier wave and the packet of a single wave system. In chapter 2, the linearly sheared currents examined are one-dimensional, in accordance with wave propagation and consist of a velocity profile varying linearly with depth. Such currents have constant-vorticity and, although rotational, admit potential flow solutions. Both the linear evolution and the weakly nonlinear behaviour of waves on five constant vorticity sheared currents in the shear rate, Ω range, 0 s-1 ≤ Ω ≤ -0:87 s-1 are measured and compared to predictions by the vor-NLSE and vor-dispersion relation. It is found that the constant-vorticity equations agree extremely well with the experimental measurements in all cases. Significant differences between the vor-equations and uniform velocity equations are found at the strongest shear cases for both stability and linear dispersion experiments (-0:48-s-1 ≤ Ω ≤ -0:87 s-1). In chapter 3, the coupled nonlinear Schrodinger equation (CNLSE) is used to quantify the effect of a crossing angle between two weakly nonlinear coupled wave systems. Individually (when unidirectional) both systems show modulational instability. This is augmented by the addition of a crossing angle between the two wave systems. Linear stability analysis of the CNLSE indicates that wavetrains become increasingly stable as the crossing angle is increased, reaching stability at a critical angle of 35:26°. The experiments presented in this thesis measured the stability of crossing angles up to 88° for a coupled system showing clear instability when the wavetrains are unidirectional. Initially strong instabilities for the interacting unidirectional case are quickly stabilised as the crossing angle is increased. The system becomes entirely stabilised when the crossing angle is increased beyond the critical angle. In chapter 4, the two-dimensional nonlinear Schrodinger equation is used to impose a crossing angle between the carrier wave and continuous sidebands of a narrow-banded wave group. Measurements of a low-steepness wave group envelope showed normal dispersive behaviour when unidirectional. However, as the two-dimensional nonlinear Schrodinger equation predicts, at the critical angle of 35:26° it was found that the Gaussian wave group propagated with entirely unchanging form, displaying nondispersive behaviour. Similarly, when a medium-steepness Gaussian group was propagated at the critical angle, not only was the group nondispersive, the focusing present in its unidirectional propagation (due to nonlinear focusing) became negligible. Nonlinear effects were seen as the development of a double peaked wave envelope as larger waves travelled to the front of the group. These results show that wave groups are capable of travelling for extended periods of time with extreme waves at their centre. Two nondispersive crossed groups with crossing angles of ±35:26° were superimposed to create the first observations of a hydrodynamic X-wave. Such waves have previously been observed in optics, Bose-Einstein condensates, and plasmas. The X-wave has a large central amplitude where the two groups cross

On the existence of Hopf cycles in optimal growth models with time delay

Ankara : The Department of Economics and the Institute of Economics and Social Sciences of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical refences.In this thesis, we analyzed the existence of cycles `a la Poincar´e-AndronovHopf in optimal growth models with time delay. The analysis builds upon a new method developed, which investigates the number of pure imaginary roots of the characteristic equation. The method was applied to the time-tobuild models of Asea and Zak (1999) and Winkler (2004).Yüksel, Mustafa KeremM.S

The Arecibo L-Band Feed Array Zone of Avoidance Survey

The Arecibo L-Band Feed Array Zone of Avoidance (ALFA ZOA) Survey detects galaxies behind the Milky Way by 21cm emission from neutral hydrogen gas (HI). The goal of ALFA ZOA is to detect nearby galaxies that have an impact on the peculiar velocity of the Local Group and to compare large scale structure across the ZOA to predicted structure from density reconstruction maps. ALFA ZOA is conducted in two phases: shallow and deep. Observations for the Shallow survey are finished and 45% of the survey has been cataloged with 280 detections found at a sensitivity of 5.4 mJy at 9 km/s channel resolution. The survey is complete above integrated flux 2.2 Jy km/s and has a positional accuracy of 26 arcseconds. First results from the Deep survey find 61 galaxies within a 15 square degree area. The Deep survey reaches its expected sensitivity of 1 mJy at 9 km/s channel resolution, and is shown to be complete above integrated flux 0.5 Jy km/s, detecting galaxies out to a recessional velocity of nearly 19,000 km/s. ALFA ZOA finds 3 out of 7 predicted, major large scale structures to have been misplaced in density reconstruction maps from the literature. No new Local Group galaxies are found, but three galaxy groups are discovered within 20 Mpc and one may have the mass and distance to recover the mass density dipole vector. ALFA ZOA increases the number of galaxies cataloged in the area by 100%, and the number with known redshift by over 800%

Exploring novel designs of NLP solvers: Architecture and Implementation of WORHP

Mathematical Optimization in general and Nonlinear Programming in particular, are applied by many scientific disciplines, such as the automotive sector, the aerospace industry, or the space agencies. With some established NLP solvers having been available for decades, and with the mathematical community being rather conservative in this respect, many of their programming standards are severely outdated. It is safe to assume that such usability shortcomings impede the wider use of NLP methods; a representative example is the use of static workspaces by legacy FORTRAN codes. This dissertation gives an account of the construction of the European NLP solver WORHP by using and combining software standards and techniques that have not previously been applied to mathematical software to this extent. Examples include automatic code generation, a consistent reverse communication architecture and the elimination of static workspaces. The result is a novel, industrial-grade NLP solver that overcomes many technical weaknesses of established NLP solvers and other mathematical software

Span-core Decomposition for Temporal Networks: Algorithms and Applications

When analyzing temporal networks, a fundamental task is the identification of dense structures (i.e., groups of vertices that exhibit a large number of links), together with their temporal span (i.e., the period of time for which the high density holds). In this paper we tackle this task by introducing a notion of temporal core decomposition where each core is associated with two quantities, its coreness, which quantifies how densely it is connected, and its span, which is a temporal interval: we call such cores \emph{span-cores}. For a temporal network defined on a discrete temporal domain $T$, the total number of time intervals included in $T$ is quadratic in $|T|$, so that the total number of span-cores is potentially quadratic in $|T|$ as well. Our first main contribution is an algorithm that, by exploiting containment properties among span-cores, computes all the span-cores efficiently. Then, we focus on the problem of finding only the \emph{maximal span-cores}, i.e., span-cores that are not dominated by any other span-core by both their coreness property and their span. We devise a very efficient algorithm that exploits theoretical findings on the maximality condition to directly extract the maximal ones without computing all span-cores. Finally, as a third contribution, we introduce the problem of \emph{temporal community search}, where a set of query vertices is given as input, and the goal is to find a set of densely-connected subgraphs containing the query vertices and covering the whole underlying temporal domain $T$. We derive a connection between this problem and the problem of finding (maximal) span-cores. Based on this connection, we show how temporal community search can be solved in polynomial-time via dynamic programming, and how the maximal span-cores can be profitably exploited to significantly speed-up the basic algorithm.Comment: ACM Transactions on Knowledge Discovery from Data (TKDD), 2020. arXiv admin note: substantial text overlap with arXiv:1808.0937

Proof-theoretic Semantics for Intuitionistic Multiplicative Linear Logic

This work is the first exploration of proof-theoretic semantics for a substructural logic. It focuses on the base-extension semantics (B-eS) for intuitionistic multiplicative linear logic (IMLL). The starting point is a review of Sandqvist’s B-eS for intuitionistic propositional logic (IPL), for which we propose an alternative treatment of conjunction that takes the form of the generalized elimination rule for the connective. The resulting semantics is shown to be sound and complete. This motivates our main contribution, a B-eS for IMLL , in which the definitions of the logical constants all take the form of their elimination rule and for which soundness and completeness are established