搜索结果：Environment

This paper addresses the problem of adaptive reconfigurable intelligent surfaces (RIS) configuration design for user localization in rich-scattering environment (RSE), where electromagnetic waves undergo multiple interactions with dynamic scatterers and RIS elements. We propose an adaptive learning-based localization approach for a distributed RIS-assisted network in a RSE using a bidirectional long-short term memory (biLSTM) model that captures temporal correlations between observations. The proposed approach actively senses the environment using sequential pilot transmissions from the base station (BS), accounting for scattering effects, and adaptively updates the RIS configuration based on prior measurements to eventually accurately estimate and minimize the user localization error. The proposed model comprises two neural sub-networks: Scattering Estimation Network (Bi-SEN), for estimation of scattering in the environment, and Adaptive RIS-Assisted User Localization Network (Bi-ARULN), for RIS configuration and localization. Bayesian optimization is used for hyperparameter tuning of the model. The simulation results demonstrate the effectiveness of the proposed approach, achievi

Interactive applications demand believable characters that respond naturally to dynamic environments. Traditional character animation techniques often struggle to handle arbitrary situations, leading to a growing trend of dynamically selecting motion-captured animations based on predefined features. While Motion Matching has proven effective for locomotion by aligning to target trajectories, animating environment interactions and crowd behaviors remains challenging due to the need to consider surrounding elements. Existing approaches often involve manual setup or lack the naturalism of motion capture. Furthermore, in crowd animation, body animation is frequently treated as a separate process from trajectory planning, leading to inconsistencies between body pose and root motion. To address these limitations, we present Environment-aware Motion Matching, a novel real-time system for full-body character animation that dynamically adapts to obstacles and other agents, emphasizing the bidirectional relationship between pose and trajectory. In a preprocessing step, we extract shape, pose, and trajectory features from a motion capture database. At runtime, we perform an efficient search t

Three-dimensional urban environment simulation is a powerful tool for informed urban planning. However, the intensive manual effort required to prepare input 3D city models has hindered its widespread adoption. To address this challenge, we present VoxCity, an open-source Python package that provides a one-stop solution for grid-based 3D city model generation and urban environment simulation for cities worldwide. VoxCity's `generator' subpackage automatically downloads building heights, tree canopy heights, land cover, and terrain elevation within a specified target area, and voxelizes buildings, trees, land cover, and terrain to generate an integrated voxel city model. The `simulator' subpackage enables users to conduct environmental simulations, including solar radiation and view index analyses. Users can export the generated models using several file formats compatible with external software, such as ENVI-met (INX), Blender, and Rhino (OBJ). We generated 3D city models for eight global cities, and demonstrated the calculation of solar irradiance, sky view index, and green view index. We also showcased microclimate simulation and 3D rendering visualization through ENVI-met and Rh

This article presents novel designs of autonomous UAV prototypes specifically developed for inspecting GPS-denied tunnel construction environments with dynamic human and robotic presence. Our UAVs integrate advanced sensor suites and robust motion planning algorithms to autonomously navigate and explore these complex environments. We validated our approach through comprehensive simulation experiments in PX4 Gazebo and Airsim Unreal Engine 4 environments. Real-world wind tests and exploration experiments demonstrate the UAVs' capability to operate stably under diverse environmental conditions without GPS assistance. This study highlights the practicality and resilience of our UAV prototypes in real-world applications.

Outdoor built environments can be designed to enhance thermal comfort, yet the relationship between the two is often assessed in whole-body terms, overlooking the asymmetric nature of thermal interactions between the human body and its surroundings. Moreover, the radiative component of heat exchange-dominant in hot and dry climates-is typically lumped into a single artificial metric, the mean radiant temperature, rather than being resolved into its shortwave and longwave spectral components. The shortwave irradiation distribution on the human body is often highly anisotropic, causing localized thermal discomfort in outdoor environments. However, no existing methods effectively quantify shortwave and longwave irradiation distributions on the human body. To address this gap, we developed two methods to quantify these processes. The first approach uses an outdoor thermal manikin with a white-coated side, enabling the separation of spectral components by subtracting measurements from symmetrically corresponding surface zones of tan color. The second hybrid approach converts radiometer measurements in six directions into boundary conditions for computational thermal manikin simulations.

With advances in generative AI, there is now potential for autonomous agents to manage daily tasks via natural language commands. However, current agents are primarily created and tested in simplified synthetic environments, leading to a disconnect with real-world scenarios. In this paper, we build an environment for language-guided agents that is highly realistic and reproducible. Specifically, we focus on agents that perform tasks on the web, and create an environment with fully functional websites from four common domains: e-commerce, social forum discussions, collaborative software development, and content management. Our environment is enriched with tools (e.g., a map) and external knowledge bases (e.g., user manuals) to encourage human-like task-solving. Building upon our environment, we release a set of benchmark tasks focusing on evaluating the functional correctness of task completions. The tasks in our benchmark are diverse, long-horizon, and designed to emulate tasks that humans routinely perform on the internet. We experiment with several baseline agents, integrating recent techniques such as reasoning before acting. The results demonstrate that solving complex tasks is

This paper addresses the challenge of scaling Large Multimodal Models (LMMs) to expansive 3D environments. Solving this open problem is especially relevant for robot deployment in many first-responder scenarios, such as search-and-rescue missions that cover vast spaces. The use of LMMs in these settings is currently hampered by the strict context windows that limit the LMM's input size. We therefore introduce a novel approach that utilizes a datagraph structure, which allows the LMM to iteratively query smaller sections of a large environment. Using the datagraph in conjunction with graph traversal algorithms, we can prioritize the most relevant locations to the query, thereby improving the scalability of 3D scene language tasks. We illustrate the datagraph using 3D scenes, but these can be easily substituted by other dense modalities that represent the environment, such as pointclouds or Gaussian splats. We demonstrate the potential to use the datagraph for two 3D scene language task use cases, in a search-and-rescue mission example.

Light pollution is the alteration of the natural levels of darkness by an increased concentration of light particles in the nighttime environment, resulting from human activity. Light pollution is changing in a deep way the environmental conditions of the night in wide areas of the planet, and is a relevant stressor whose effects on life are being unveiled by a compelling body of research. In this paper we briefly review the basic aspects of artificial light at night as a pollutant, describing its character, magnitude and extent, its worldwide distribution, its temporal and spectral change trends, as well as its dependence on current light production technologies and prevailing social uses of light. It is shown that the overall effects of light pollution are not restricted to local disturbances, but give rise to a global, multiscale disruption of the nighttime environment.

The concept of digital twins has attracted significant attention across various domains, particularly within the built environment. However, there is a sheer volume of definitions and the terminological consensus remains out of reach. The lack of a universally accepted definition leads to ambiguities in their conceptualization and implementation, and may cause miscommunication for both researchers and practitioners. We employed Natural Language Processing (NLP) techniques to systematically extract and analyze definitions of digital twins from a corpus of more than 15,000 full-text articles spanning diverse disciplines. The study compares these findings with insights from an expert survey that included 52 experts. The study identifies concurrence on the components that comprise a ``Digital Twin'' from a practical perspective across various domains, contrasting them with those that do not, to identify deviations. We investigate the evolution of digital twin definitions over time and across different scales, including manufacturing, building, and urban/geospatial perspectives. We extracted the main components of Digital Twins using Text Frequency Analysis and N-gram analysis. Subseque

Street View Imagery (SVI) has emerged as a valuable data form in urban studies, enabling new ways to map and sense urban environments. However, fundamental concerns regarding the representativeness, quality, and reliability of SVI remain underexplored, e.g. to what extent can cities be captured by such data and do data gaps result in bias. This research, positioned at the intersection of spatial data quality and urban analytics, addresses these concerns by proposing a novel and effective method to estimate SVI's element-level coverage in the urban environment. The method integrates the positional relationships between SVI and target elements, as well as the impact of physical obstructions. Expanding the domain of data quality to SVI, we introduce an indicator system that evaluates the extent of coverage, focusing on the completeness and frequency dimensions. Taking London as a case study, three experiments are conducted to identify potential biases in SVI's ability to cover and represent urban environmental elements, using building facades as an example. It is found that despite their high availability along urban road networks, Google Street View covers only 62.4 % of buildings in

The advent of deep reinforcement learning (DRL) has significantly advanced the field of robotics, particularly in the control and coordination of quadruped robots. However, the complexity of real-world tasks often necessitates the deployment of multi-robot systems capable of sophisticated interaction and collaboration. To address this need, we introduce the Multi-agent Quadruped Environment (MQE), a novel platform designed to facilitate the development and evaluation of multi-agent reinforcement learning (MARL) algorithms in realistic and dynamic scenarios. MQE emphasizes complex interactions between robots and objects, hierarchical policy structures, and challenging evaluation scenarios that reflect real-world applications. We present a series of collaborative and competitive tasks within MQE, ranging from simple coordination to complex adversarial interactions, and benchmark state-of-the-art MARL algorithms. Our findings indicate that hierarchical reinforcement learning can simplify task learning, but also highlight the need for advanced algorithms capable of handling the intricate dynamics of multi-agent interactions. MQE serves as a stepping stone towards bridging the gap betwe

Postststarburst (K+A) galaxies are candidates for galaxies in transition from a star-forming phase to a passively-evolving phase. We have spectroscopically identified large samples of K+A galaxies both in the SDSS at z~0.1 and in the DEEP2 survey at z~0.8, using a robust selection method based on a cut in Hbeta emission rather than the more problematic [OII] 3727. Based on measurements of the overdensity of galaxies around each object, we find that K+A galaxies brighter than 0.4L*_B at low-z have a similar, statistically indistinguishable environment distribution as blue galaxies, preferring underdense environments, but dramatically different from that of red galaxies. However, at higher-z, the environment distribution of K+A galaxies is more similar to red galaxies than to blue galaxies. We conclude that the quenching of star formation and the build-up of the red sequence through the K+A phase is happening in relatively overdense environments at z~1 but in relatively underdense environments at z~0. Although the relative environments where quenching occurs are decreasing with time, the corresponding absolute environment may have stayed the same along with the quenching mechanisms,

This dissertation will combine new tools and methodologies to answer pressing questions regarding inundation area and hurricane events in complex, heterogeneous changing environments. In addition to remote sensing approaches, citizen science and machine learning are both emerging fields that harness advancing technology to answer environmental management and disaster response questions.

We consider a system of $N^{d}$ spins in random environment with a random local mean field type interaction. Each spin has a fixed spatial position on the torus $\mathbb{T}^{d}$, an attached random environment and a spin value in $\mathbb{R}$ that evolves according to a space and environment dependent Langevin dynamic. The interaction between two spins depends on the spin values, on the spatial distance and the random environment of both spins. We prove the path large deviation principle from the hydrodynamic (or local mean field McKean-Vlasov) limit and derive different expressions of the rate function for the empirical process and for the empirical measure of the paths. To this end, we generalize an approach of Dawson and Gärtner. By the space and random environment dependency, this requires new ingredients compared to mean field type interactions. Moreover, we prove the large deviation principle by using a second approach. This requires a generalisation of Varadhan's lemma to nowhere continuous functions.

We present a robust method, weighted von Mises kernel density estimation, along with boundary correction to reconstruct the underlying number density field of galaxies. We apply this method to galaxies brighter than $\rm HST/F160w\le 26$ AB mag at the redshift range of $0.4\leq z \leq 5$ in the five CANDELS fields (GOODS-N, GOODS-S, EGS, UDS, and COSMOS). We then use these measurements to explore the environmental dependence of the star formation activity of galaxies. We find strong evidence of environmental quenching for massive galaxies ($\rm M \gtrsim 10^{11} \rm {M}_\odot$) out to $z\sim 3.5$ such that an over-dense environment hosts $\gtrsim 20\%$ more massive quiescent galaxies compared to an under-dense region. We also find that environmental quenching efficiency grows with stellar mass and reaches $\sim 60\%$ for massive galaxies at $z\sim 0.5$. The environmental quenching is also more efficient in comparison to the stellar mass quenching for low mass galaxies ($\rm M \lesssim 10^{10} \rm {M}_\odot$) at low and intermediate redshifts ($z\lesssim 1.2$). Our findings concur thoroughly with the "over-consumption" quenching model where the termination of cool gas accretion (cos

Recently, aggregated journal-journal citation networks were made accessible from the perspective of each journal included in the Science Citation Index see (http://www.leydesdorff.net/). The local matrices can be used to inspect the relevant citation environment of a journal using statistical analysis and visualization techniques from social network analysis. The inspection gives an answer to the question what the local impact of this and other journals in the environment is. In this study the citation environment of Angewandte Chemie was analysed. Angewandte Chemie is one of the prime chemistry journals in the world. Its environment was compared with that of the Journal of the American Chemical Society. The results of the environment analyses give a detailed insight into the field-embeddedness of Angewandte Chemie. The impacts of the German and international editions of this journal are compared.

We review recent results on the dependence of various galaxy properties on environment at low redshift. As environmental indicators, we use group mass, group-centric radius, and the distinction between centrals and satellites; examined galaxy properties include star formation rate, colour, AGN fraction, age, metallicity and concentration. In general, satellite galaxies diverge more markedly from their central counterparts if they reside in more massive haloes. We show that these results are consistent with starvation being the main environmental effect, if one takes into account that satellites that reside in more massive haloes and at smaller halo-centric radii on average have been accreted a longer time ago. Nevertheless, environmental effects are not fully understood yet. In particular, it is puzzling that the impact of environment on a galaxy seems independent of its stellar mass. This may indicate that the stripping of the extended gas reservoir of satellite galaxies predominantly occurs via tidal forces rather than ram-pressure.

Active hydrothermal vents provide the surrounding submarine environment with substantial amounts of matter and energy, thus serving as important habitats for diverse megabenthic communities in the deep ocean and constituting a unique, highly productive chemosynthetic ecosystem on Earth. Vent-endemic biological communities gather near the venting site and are usually not found beyond a distance of the order of 100 m from the vent. This is surprising because one would actually expect matter ejected from high-temperature vents, which generate highly turbulent buoyancy plumes, to be suspended and carried far away by the plume flows and deep-sea currents. Here, we study this problem from a fluid dynamics perspective by simulating the vent hydrodynamics using a numerical model that couples the plume flow with induced matter and energy transport. We find that both low- and high-temperature vents deposit most vent matter relatively close to the plume. In particular, the tendency of turbulent buoyancy plumes to carry matter far away is strongly counteracted by generated entrainment flows back into the plume stem. The deposition ranges of organic and inorganic hydrothermal particles obtained