Hasil untuk "Land use"

Siyi Chen, Kai Wang, Weicong Pang et al.

Land-cover understanding in remote sensing increasingly demands class-agnostic systems that generalize across datasets while remaining spatially precise and interpretable. We study a geometry-first discovery-and-interpretation setting under domain shift, where candidate regions are delineated class-agnostically and supervision avoids lexical class names via anonymized identifiers. Complementary to open-set recognition and open-world learning, we focus on coupling class-agnostic mask evidence with taxonomy-grounded scene interpretation, rather than unknown rejection or continual class expansion. We propose MVT, a three-stage framework that (i) extracts boundary-faithful region masks using SAM2 with domain adaptation, (ii) performs mask-grounded semantic tagging and scene description generation via dual-step LoRA fine-tuning of multimodal LLMs, and (iii) evaluates outputs with LLM-as-judge scoring calibrated by stratified expert ratings. On cross-dataset segmentation transfer (train on OpenEarthMap, evaluate on LoveDA), domain-adapted SAM2 improves mask quality; meanwhile, dual-step MLLM fine-tuning yields more accurate taxonomy-aligned tags and more informative mask-grounded scene descriptions.

Tarek Bouazza, Alessandro Melis, Soulaimane Berkane et al.

This paper tackles the problem of estimating the relative position, orientation, and velocity between a UAV and a planar platform undergoing arbitrary 3D motion during approach and landing. The estimation relies on measurements from Inertial Measurement Units (IMUs) mounted on both systems, assuming there is a suitable communication channel to exchange data, together with visual information provided by an onboard monocular camera, from which the bearing (line-of-sight direction) to the platform's center and the normal vector of its planar surface are extracted. We propose a cascade observer with a complementary filter on SO(3) to reconstruct the relative attitude, followed by a linear Riccati observer for relative position and velocity estimation. Convergence of both observers is established under persistently exciting conditions, and the cascade is shown to be almost globally asymptotically and locally exponentially stable. We further extend the design to the case where the platform's rotation is restricted to its normal axis and show that its measured linear acceleration can be exploited to recover the remaining unobservable rotation angle. A sufficient condition to ensure local exponential convergence in this setting is provided. The performance of the proposed observers is validated through extensive simulations.

Kaung Myat Kyaw, Jonathan Hoyin Chan

In this paper, we introduce ConversaSynth, a framework designed to generate synthetic conversation audio using large language models (LLMs) with multiple persona settings. The framework first creates diverse and coherent text-based dialogues across various topics, which are then converted into audio using text-to-speech (TTS) systems. Our experiments demonstrate that ConversaSynth effectively generates highquality synthetic audio datasets, which can significantly enhance the training and evaluation of models for audio tagging, audio classification, and multi-speaker speech recognition. The results indicate that the synthetic datasets generated by ConversaSynth exhibit substantial diversity and realism, making them suitable for developing robust, adaptable audio-based AI systems.

Emanuele Spinosa, Riccardo Broglia, Alessandro Iafrati

In this paper the hydrodynamics of fuselage models representing the main body of three different types of aircraft, moving in water at constant speed and fixed attitude is investigated using the Unsteady Reynolds-Averaged Navier-Stokes (URANS) level-set flow solver $χ$navis. The objective of the CFD study is to give insight into the water landing phase of the aircraft emergency ditching. The pressure variations over the wetted surface and the features of the free surface are analysed in detail, showing a marked difference among the three shapes in terms of the configuration of the thin spray generated at the front. Such a difference is a consequence of the different transverse curvature of the fuselage bodies. Furthermore, it is observed that at the rear, where a change of longitudinal curvature occurs, a region of negative pressure (i.e. below the atmospheric value) develops. This generates a suction (downward) force of pure hydrodynamic origin. In order to better understand the role played by the longitudinal curvature change on the loads, a fourth fuselage shape truncated at the rear is also considered in the study. The forces acting on the fuselage models are considered as composed of three terms: the viscous, the hydrodynamic and the buoyancy contributions. For validation purposes the forces derived from the numerical simulations are compared with experimental data.

Martin Schwartz, Philippe Ciais, Catherine Ottlé et al.

In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy height. In this work, we developed a deep learning model based on multi-stream remote sensing measurements to create a high-resolution canopy height map over the "Landes de Gascogne" forest in France, a large maritime pine plantation of 13,000 km$^2$ with flat terrain and intensive management. This area is characterized by even-aged and mono-specific stands, of a typical length of a few hundred meters, harvested every 35 to 50 years. Our deep learning U-Net model uses multi-band images from Sentinel-1 and Sentinel-2 with composite time averages as input to predict tree height derived from GEDI waveforms. The evaluation is performed with external validation data from forest inventory plots and a stereo 3D reconstruction model based on Skysat imagery available at specific locations. We trained seven different U-net models based on a combination of Sentinel-1 and Sentinel-2 bands to evaluate the importance of each instrument in the dominant height retrieval. The model outputs allow us to generate a 10 m resolution canopy height map of the whole "Landes de Gascogne" forest area for 2020 with a mean absolute error of 2.02 m on the Test dataset. The best predictions were obtained using all available satellite layers from Sentinel-1 and Sentinel-2 but using only one satellite source also provided good predictions. For all validation datasets in coniferous forests, our model showed better metrics than previous canopy height models available in the same region.

Jaime Moraga, Gurbet Gurkan, Sebnem Duzgun

Monitoring dam failures using satellite images provides first responders with efficient management of early interventions. It is also equally important to monitor spatial and temporal changes in the inundation area to track the post-disaster recovery. On January 25th, 2019, the tailings dam of the Córrego do Feijão iron ore mine, located in Brumadinho, Brazil, collapsed. This disaster caused more than 230 fatalities and 30 missing people leading to damage on the order of multiple billions of dollars. This study uses Sentinel-2 satellite images to map the inundation area and assess and delineate the land use and land cover impacted by the dam failure. The images correspond to data captures from January 22nd (3 days before), and February 02 (7 days after the collapse). Satellite images of the region were classified for before and aftermath of the disaster implementing a machine learning algorithm. In order to have sufficient land cover types to validate the quality and accuracy of the algorithm, 7 classes were defined: mine, forest, build-up, river, agricultural, clear water, and grassland. The developed classification algorithm yielded a high accuracy (99%) for the image before the collapse. This paper determines land cover impact using two different models, 1) by using the trained network in the "after" image, and 2) by creating a second network, trained in a subset of points of the "after" image, and then comparing the land cover results of the two trained networks. In the first model, applying the trained network to the "after" image, the accuracy is still high (86%), but lower than using the second model (98%). This strategy can be applied at a low cost for monitoring and assessment by using openly available satellite information and, in case of dam collapse or with a larger budget, higher resolution and faster data can be obtained by fly-overs on the area of concern.

Dylan Keating, Nicolas B. Cowan

The field of exoplanet atmospheric characterization is trending towards comparative studies involving many planetary systems, and using Bayesian hierarchical modelling is a natural next step. Here we demonstrate two use cases. We first use hierarchical modelling to quantify variability in repeated observations by reanalyzing a suite of ten Spitzer secondary eclipse observations of the hot Jupiter XO-3b. We compare three models: one where we fit ten separate eclipse depths, one where we use a single eclipse depth for all ten observations, and a hierarchical model. By comparing the Widely Applicable Information Criterion of each model, we show that the hierarchical model is preferred over the others. The hierarchical model yields less scatter across the suite of eclipse depths -- and higher precision on the individual eclipse depths -- than does fitting the observations separately. We find that the hierarchical eclipse depth uncertainty is larger than the uncertainties on the individual eclipse depths, which suggests either slight astrophysical variability or that single eclipse observations underestimate the true eclipse depth uncertainty. Finally, we fit a suite of published dayside brightness measurements for 37 planets using a hierarchical model of brightness temperature vs irradiation temperature. The hierarchical model gives tighter constraints on the individual brightness temperatures than the non-hierarchical model. Although we tested hierarchical modelling on Spitzer eclipse data of hot Jupiters, it is applicable to observations of smaller planets like hot neptunes and super earths, as well as for photometric and spectroscopic transit or phase curve observations.

Sashank Modali, Satadal Ghosh, Sujit P. B

In this paper the problem of guidance formulation for autonomous soft landing of unmanned aerial vehicles on stationary, moving, or accelerating / maneuvering ground vehicles at desired approach angles in both azimuth and elevation is considered. Nonlinear engagement kinematics have been used. While integrated nonlinear controllers have been developed in the literature for this purpose, in practical implementations the controller inputs often need modification of the existing autopilot structure, which is challenging. In order to avoid that a higher-level guidance algorithm is designed in this paper leveraging sliding mode control-based approach. In the presented guidance formulation, target-state-dependent singularity can be avoided in the guidance command. The effectiveness of the presented guidance law is verified with numerical simulation studies. However, since the algorithm in its basic form is found to demand high guidance command at large distances from maneuvering ground targets, a two-phase guidance is presented next to avoid this problem and validated with numerical simulations. Finally, the efficacy of the modified guidance algorithm is validated by Software-In-The-Loop simulations for a realistic testbed.

Stanisław Saganowski, Anna Dutkowiak, Adam Dziadek et al.

Wearables like smartwatches or wrist bands equipped with pervasive sensors enable us to monitor our physiological signals. In this study, we address the question whether they can help us to recognize our emotions in our everyday life for ubiquitous computing. Using the systematic literature review, we identified crucial research steps and discussed the main limitations and problems in the domain.

Andrey Polyakov, Mikhail Zymbler

Discord is a refinement of the concept of anomalous subsequence of a time series. The task of discords discovery is applied in a wide range of subject domains related to time series: medicine, economics, climate modeling, etc. In this paper, we propose a novel parallel algorithm for discords discovery for the Intel Xeon Phi Knights Landing (KNL) many-core systems for the case when input data fit in main memory. The algorithm exploits the ability to independently calculate Euclidean distances between the subsequences of the time series. Computations are paralleled through OpenMP technology. The algorithm consists of two stages, namely precomputations and discovery. At the precomputations stage, we construct the auxiliary matrix data structures, which ensure efficient vectorization of computations on Intel Xeon Phi KNL. At the discovery stage, the algorithm finds discord based upon the structures above. Experimental evaluation confirms the high scalability of the developed algorithm.

The SNO+ Collaboration, :, M. Anderson et al.

A measurement of the $^8$B solar neutrino flux has been made using a 69.2 kt-day dataset acquired with the SNO+ detector during its water commissioning phase. At energies above 6 MeV the dataset is an extremely pure sample of solar neutrino elastic scattering events, owing primarily to the detector's deep location, allowing an accurate measurement with relatively little exposure. In that energy region the best fit background rate is $0.25^{+0.09}_{-0.07}$ events/kt-day, significantly lower than the measured solar neutrino event rate in that energy range, which is $1.03^{+0.13}_{-0.12}$ events/kt-day. Also using data below this threshold, down to 5 MeV, fits of the solar neutrino event direction yielded an observed flux of $2.53^{+0.31}_{-0.28}$(stat.)$^{+0.13}_{-0.10}$(syst.)$\times10^6$ cm$^{-2}$s$^{-1}$, assuming no neutrino oscillations. This rate is consistent with matter enhanced neutrino oscillations and measurements from other experiments.

Alexandria Volkening, Daniel F. Linder, Mason A. Porter et al.

Forecasting elections -- a challenging, high-stakes problem -- is the subject of much uncertainty, subjectivity, and media scrutiny. To shed light on this process, we develop a method for forecasting elections from the perspective of dynamical systems. Our model borrows ideas from epidemiology, and we use polling data from United States elections to determine its parameters. Surprisingly, our general model performs as well as popular forecasters for the 2012 and 2016 U.S. races for president, senators, and governors. Although contagion and voting dynamics differ, our work suggests a valuable approach to elucidate how elections are related across states. It also illustrates the effect of accounting for uncertainty in different ways, provides an example of data-driven forecasting using dynamical systems, and suggests avenues for future research on political elections. We conclude with our forecasts for the senatorial and gubernatorial races on 6~November 2018, which we posted on 5 November 2018.

Taichi Kosugi, Yu-ichiro Matsushita

For inhomogeneous interacting electronic systems under a time-dependent electromagnetic perturbation, we derive the linear equation for response functions in a quantum mechanical manner. It is a natural extension of the original semi-classical Singwi-Tosi-Land-Sjoelander (STLS) approach for an electron gas. The factorization ansatz for the two-particle distribution is an indispensable ingredient in the STLS approaches for determination of the response function and the pair correlation function. In this study, we choose an analytically solvable interacting two-electron system as the target for which we examine the validity of the approximation. It is demonstrated that the STLS response function reproduces well the exact one for low-energy excitations. The interaction energy contributed from the STLS response function is also discussed.

Benjamin Godfrey, Tyler Anderson, Earl Breedon et al.

Silicon photomultipliers (SiPMs) are potential solid-state alternatives to traditional photomultiplier tubes (PMTs) for single-photon detection. In this paper, we report on evaluating SensL MicroFC-10035-SMT SiPMs for their suitability as PMT replacements. The devices were successfully operated in a liquid-xenon detector, which demonstrates that SiPMs can be used in noble element time projection chambers as photosensors. The devices were also cooled down to 170 K to observe dark count dependence on temperature. No dependencies on the direction of an applied 3.2 kV/cm electric field were observed with respect to dark-count rate, gain, or photon detection efficiency.

Harsh Taneja, James Webster

This study investigates the role of both cultural and technological factors in determining audience formation on a global scale. It integrates theories of media choice with theories of global cultural consumption and tests them by analyzing shared audience traffic between the world's 1000 most popular Websites. We find that language and geographic similarities are more powerful predictors of audience overlap than hyperlinks and genre similarity, highlighting the role of cultural structures in shaping global media use.

M. J. Malinowski, E. Matsinos, S. Roth

The present paper aims at providing the theoretical background required for investigating the use of the Microsoft Kinect$^{\rm TM}$ (`Kinect', for short) sensors (original and upgraded) in the analysis of human motion. Our methodology is developed in such a way that its application be easily adaptable to comparative studies of other systems used in capturing human-motion data. Our future plans include the application of this methodology to two situations: first, in a comparative study of the performance of the two Kinect sensors; second, in pursuing their validation on the basis of comparisons with a marker-based system (MBS). One important feature in our approach is the transformation of the MBS output into Kinect-output format, thus enabling the analysis of the measurements, obtained from different systems, with the same software application, i.e., the one we use in the analysis of Kinect-captured data; one example of such a transformation, for one popular marker-placement scheme (`Plug-in Gait'), is detailed. We propose that the similarity of the output, obtained from the different systems, be assessed on the basis of the comparison of a number of waveforms, representing the variation within the gait cycle of quantities which are commonly used in the modelling of the human motion. The data acquisition may involve commercially-available treadmills and a number of velocity settings: for instance, walking-motion data may be acquired at $5$ km/h, running-motion data at $8$ and $11$ km/h. We recommend that particular attention be called to systematic effects associated with the subject's knee and lower leg, as well as to the ability of the Kinect sensors in reliably capturing the details in the asymmetry of the motion for the left and right parts of the human body. The previous versions of the study have been withdrawn due to the use of a non-representative database.

Michele Tizzoni, Paolo Bajardi, Adeline Decuyper et al.

Human mobility is a key component of large-scale spatial-transmission models of infectious diseases. Correctly modeling and quantifying human mobility is critical for improving epidemic control policies, but may be hindered by incomplete data in some regions of the world. Here we explore the opportunity of using proxy data or models for individual mobility to describe commuting movements and predict the diffusion of infectious disease. We consider three European countries and the corresponding commuting networks at different resolution scales obtained from official census surveys, from proxy data for human mobility extracted from mobile phone call records, and from the radiation model calibrated with census data. Metapopulation models defined on the three countries and integrating the different mobility layers are compared in terms of epidemic observables. We show that commuting networks from mobile phone data well capture the empirical commuting patterns, accounting for more than 87% of the total fluxes. The distributions of commuting fluxes per link from both sources of data - mobile phones and census - are similar and highly correlated, however a systematic overestimation of commuting traffic in the mobile phone data is observed. This leads to epidemics that spread faster than on census commuting networks, however preserving the order of infection of newly infected locations. Match in the epidemic invasion pattern is sensitive to initial conditions: the radiation model shows higher accuracy with respect to mobile phone data when the seed is central in the network, while the mobile phone proxy performs better for epidemics seeded in peripheral locations. Results suggest that different proxies can be used to approximate commuting patterns across different resolution scales in spatial epidemic simulations, in light of the desired accuracy in the epidemic outcome under study.

Chris Lintott, Kevin Schawinski, Steven Bamford et al.

Morphology is a powerful indicator of a galaxy's dynamical and merger history. It is strongly correlated with many physical parameters, including mass, star formation history and the distribution of mass. The Galaxy Zoo project collected simple morphological classifications of nearly 900,000 galaxies drawn from the Sloan Digital Sky Survey, contributed by hundreds of thousands of volunteers. This large number of classifications allows us to exclude classifier error, and measure the influence of subtle biases inherent in morphological classification. This paper presents the data collected by the project, alongside measures of classification accuracy and bias. The data are now publicly available and full catalogues can be downloaded in electronic format from http://data.galaxyzoo.org.

Raul Jimenez, Anze Slosar, Licia Verde et al.

We report on the finding of a correlation between galaxies' past star formation activity and the degree to which neighbouring galaxies rotation axes are aligned. This is obtained by cross-correlating star formation histories, derived with MOPED, and spin direction (chirality), as determined by the Galaxy Zoo project, for a sample of SDSS galaxies. Our findings suggest that spiral galaxies which formed the majority of their stars early (z > 2) tend to display coherent rotation over scales of ~10 Mpc/h. The correlation is weaker for galaxies with significant recent star formation. We find evidence for this alignment at more than the 5-sigma level, but no correlation with other galaxy stellar properties. This finding can be explained within the context of hierarchical tidal-torque theory if the SDSS galaxies harboring the majority of the old stellar population where formed in the past, in the same filament and at about the same time. Galaxies with significant recent star formation instead are in the field, thus influenced by the general tidal field that will align them in random directions or had a recent merger which would promote star formation, but deviate the spin direction.

Anze Slosar, Kate Land, Steven Bamford et al.

Galaxy Zoo is the first study of nearby galaxies that contains reliable information about the spiral sense of rotation of galaxy arms for a sizeable number of galaxies. We measure the correlation function of spin chirality (the sense in which galaxies appear to be spinning) of face-on spiral galaxies in angular, real and projected spaces. Our results indicate a hint of positive correlation at separations less than ~0.5 Mpc at a statistical significance of 2-3 sigma. This is the first experimental evidence for chiral correlation of spins. Within tidal torque theory it indicates that the inertia tensors of nearby galaxies are correlated. This is complementary to the studies of nearby spin axis correlations that probe the correlations of the tidal field. Theoretical interpretation is made difficult by the small distances at which the correlations are detected, implying that substructure might play a significant role, and our necessary selection of face-on spiral galaxies, rather than a general volume-limited sample.