Spatial Deployment Research Articles

UAV Hunter: A Net-Capturing UAV System with Improved Detection and Tracking Methods for Anti-UAV Defense

The abuse of UAVs poses a potential risk to social security, necessitating the investigation of anti-UAV methods to safeguard critical areas. However, the existing UAV countermeasures face challenges such as high environmental impact, restricted spatial deployment, and low cost-effectiveness. To address these limitations, we developed a novel anti-UAV system known as UAV Hunter, which adopts an airborne tether-net capture device with visual aids to counter unauthorized UAVs. This system employs an “Anti-UAV with UAV” scheme, comprising a ground control station and a net-capturing UAV. The operator utilizes the ground control station to determine the mission area and flight path and then controls the flight of the net-capturing UAV. During flight, the net-capturing UAV leverages its dual-mode sensor to continuously monitor the target area. Simultaneously, the onboard computer executes a UAV detection and tracking algorithm to search for unauthorized UAVs in real time. The results are relayed to the operator in real time, facilitating precise adjustments for the net-capturing UAV to launch the rope net accurately. The system successfully realizes the functions of dual-mode real-time detection and tracking, precise net capture, and efficient integrated control. Compared with existing methods, the developed system exhibits accurate recognition, rapid action, diverse application scenarios, and an enhanced human–machine interaction experience. Test results in the open environment further validate the feasibility and functional integrity of the system, demonstrating its capability to effectively capture low-altitude unauthorized UAVs.

Openness to experience predicts eye movement behavior during scene viewing

Individuals’ abilities to perform goal-directed spatial deployments of attention are distinguishable from their broader preferences for how they use spatial attention when circumstances do not compel a specific deployment strategy. Although these preferences are likely to play a major role in how we interact with the visual world during daily life, they remain relatively understudied. This exploratory study investigated two key questions about these preferences: firstly, are individuals consistent in their preferences for how they deploy their spatial attention when making shifts of attention versus adopting an attentional breadth? Secondly, which other factors are associated with these preferences? Across two experiments, we measured how participants preferred to deploy both attentional breadth (using an adapted Navon task) and eye movements (using a free-viewing task). We also measured participants’ working memory capacities (Experiment 1), and their personalities and world beliefs (Experiment 2). In both experiments, there were consistent individual differences in preference for attentional breadth and eye movement characteristics, but these two kinds of preference were unrelated to each other. Working memory capacity was not linked to these preferences. Conversely, the personality trait of Openness to Experience robustly predicted two aspects of eye movement behavior preference, such that higher levels of Openness predicted smaller saccades and shorter scan paths. This suggests that personality dimensions may predict preferences for more absorbed engagement with visual information. However, it appears that individuals’ preferences for shifts of attention during scene viewing do not necessarily relate to the breadth of attention they choose to adopt.

Basement membrane patterning by spatial deployment of a secretion-regulating protease.

While paradigms for patterning of cell fates in development are well-established, paradigms for patterning morphogenesis, particularly when organ shape is influenced by the extracellular matrix (ECM), are less so. Morphogenesis of the Drosophila egg chamber (follicle) depends on anterior-posterior distribution of basement membrane (BM) components such as Collagen IV (Col4), whose symmetric gradient creates tissue mechanical properties that specify the degree of elongation. Here we show that the gradient is not regulated by Col4 transcription but instead relies on post-transcriptional mechanisms. The metalloprotease ADAMTS-A, expressed in a gradient inverse to that of Col4, limits Col4 deposition in the follicle center and manipulation of its levels can cause either organ hyper- or hypo-elongation. We present evidence that ADAMTS-A acts within the secretory pathway, rather than extracellularly, to limit Col4 incorporation into the BM. High levels of ADAMTS-A in follicle termini are normally dispensable but suppress Col4 incorporation when transcription is elevated. Our data show how an organ can employ patterned expression of ECM proteases with intracellular as well as extracellular activity to specify BM properties that control shape.

Improving the spatial deployment of the soil moisture sensors in smart irrigation systems using GIS

Improving the spatial deployment of the soil moisture sensors in smart irrigation systems using GIS

Addressing the spatial disparity of COVID-19 vaccination services: A spatial optimisation approach

The COVID-19 pandemic has posed global public health threats. The mass COVID-19 vaccination has continuously played a central role in containing this pandemic. To maximise the benefits of COVID-19 vaccination, equal accessibility to vaccination at different spatial scales is critical. Limited research has investigated the spatial disparity and location optimisation of COVID-19 vaccination services. In this study, we utilised the spatial big data of COVID-19 vaccination sites and used the Gini index to measure the spatial disparity of COVID-19 vaccination service levels. Then, we leveraged spatial optimisation models to enhance the spatial deployment of vaccination sites in the study area of England, UK. The results demonstrate the feasibility and efficiency of the proposed methods. Specifically, the spatial disparity of vaccination services is largely mitigated by the optimised configuration of vaccination sites, as the Gini index decreases from 0.84 (before optimisation) to 0.12 (after optimisation). The suggested vaccination sites would improve the equality of vaccination services and reduce the financial costs of maintaining the vaccination programme, which has implications for public health policymakers. This research illustrates that spatial optimisation could be instrumental in effectively addressing public health crises.

A novel approach to evaluating the accessibility of electric vehicle charging infrastructure via dynamic thresholding in machine learning

The spatial deployment of urban public electric vehicle charging stations (PEVCSs) plays a pivotal role in the widespread adoption of electric vehicles (EVs). However, with the rapid advancements in EV technology and battery capabilities, substantial improvements in both range and charging efficiency have emerged and are expected to continue experiencing sustained growth. This situation underscores the urgent necessity of establishing dynamic metrics to reconsider the existing static charging infrastructure, aiming to ameliorate the current severe spatial imbalances and supply–demand disparities encountered in the deployment of PEVCSs. In this study, we harnessed and analyzed 84,152 sets of authentic data, fine-tuned through geospatial-aggregation technology, and ensured anonymity. Our findings bridged users’ residential and occupational patterns with their charging propensities. Comparing these with the spatial distribution of current charging stations revealed that Beijing and Shenzhen’s infrastructure aligned with the cities' economic, educational, and residential zones, epitomizing a synergy in provisioning. However, certain areas experienced either a demand–supply imbalance or an oversupply. To address these challenges, we introduced the Charging Access Reachability Index (CARI) using machine learning techniques. This dynamic metric serves as a tool for quantifying the effective coverage range of charging facilities. Its adaptive threshold holds potential as a crucial indicator enabling the dynamic transition towards more efficient and resilient charging infrastructure.

Optimizing energy efficiency in heterogeneous networks: An integrated stochastic geometry approach with novel sleep mode strategies and QoS framework.

The quest for energy efficiency (EE) in multi-tier Heterogeneous Networks (HetNets) is observed within the context of surging high-speed data demands and the rapid proliferation of wireless devices. The analysis of existing literature underscores the need for more comprehensive strategies to realize genuinely energy-efficient HetNets. This research work contributes significantly by employing a systematic methodology, utilizing This model facilitates the assessment of network performance by considering the spatial distribution of network elements. The stochastic nature of the PPP allows for a realistic representation of the random spatial deployment of base stations and users in multi-tier HetNets. Additionally, an analytical framework for Quality of Service (QoS) provision based on D-DOSS simplifies the understanding of user-base station relationships and offers essential performance metrics. Moreover, an optimization problem formulation, considering coverage, energy maximization, and delay minimization constraints, aims to strike a balance between key network attributes. This research not only addresses crucial challenges in creating EE HetNets but also lays a foundation for future advancements in wireless network design, operation, and management, ultimately benefiting network operators and end-users alike amidst the growing demand for high-speed data and the increasing prevalence of wireless devices. The proposed D-DOSS approach not only offers insights for the systematic design and analysis of EE HetNets but also systematically outperforms other state-of-the-art techniques presented. The improvement in energy efficiency systematically ranges from 67% (min side) to 98% (max side), systematically demonstrating the effectiveness of the proposed strategy in achieving higher energy efficiency compared to existing strategies. This systematic research work establishes a strong foundation for the systematic evolution of energy-efficient HetNets. The systematic methodology employed ensures a comprehensive understanding of the complex interplay of network dynamics and user requirements in a multi-tiered environment.

Concentration versus diversification: A spatial deployment approach to improve the economics of wind power

Previous studies on the economics of onshore wind parks in Germany found that geographic diversification results in minor system costs savings (Pfluger et al., 2017a). Furthermore, such diversification does not necessarily result in higher market values (Eising et al., 2020) or better merchant profitability (Klie and Madlener, 2022). Therefore, the question arises whether an alternative allocation (i.e. concentration rather than diversification) of the German wind park fleet is more economical. In this paper, we compare the future (2030) market values, subsidy needs and total system costs (excl. intra-national grid costs due to congestion, redispatch and curtailment) of a more concentrated versus a more diversified allocation of onshore wind turbines in Germany. The results show that a concentration of turbines, in areas where the gap between market values and levelized costs of electricity is smallest (i.e. Northern Germany), is more beneficial in terms of subsidy need and system costs (ignoring congestion, redispatch and curtailment). The analysis further shows that these areas are also more beneficial in terms of market values, when using system-friendly turbine configurations selected based on the same approach. To incentivize such a selection of areas and turbine configurations based on minimal gaps between market values and levelized costs an alternative renewables support scheme is presented, which favors such minimal gaps in its auctioning process.

Too Much Information: Noise and Communication in an Open Office

Abstract Noise was among the most contested issues in the large open offices that proliferated after World War II in Europe and North America. The “landscape” offices that developed out of the German Bürolandschaft movement were known for large floor plates filled with misaligned desks. They were meant to improve employees’ communication, but their acoustic design prompted worker anxieties about distraction and diminishing privacy. While early remediation efforts sought to quiet offices, in the 1960s designers began adding random, unintelligible noise to mask distractions and arranging employees according to their expected sound levels. This shift from eliminating noise to embracing it as a space-defining element reflected a powerful new acoustic paradigm. The Bürolandschaft movement waned in the 1970s, but the judicious spatial deployment of noise remains an invaluable technique as designers consider how architecture can help or hinder communication and collective intellectual activity.

Joint User-Side Recommendation and D2D-Assisted Offloading for Cache-Enabled Cellular Networks With Mobility Consideration

Caching at the wireless edge is recognized as a promising solution to accommodate the explosive growth of traffic demand. However, the gain of edge caching is only pronounced given homogeneous user preference. To reap the full potential of caching, recommendation mechanism has emerged as an attractive technology due to its capability of reshaping users’ request distribution. In this work, we propose a joint user-side recommendation and device-to-device (D2D)-assisted offloading strategy, aiming to maximize the operator’s utility. Specifically, we consider that users can recommend their cached contents to encountered users. This strategy takes into account users’ personalized preferences and relative locations, and hence can directly offload the recommended contents through D2D links without burdening cellular links. We then develop a theoretical framework to evaluate the subsequent content transmission, accounting for the randomness of spatial deployment, user mobility, individual delay requirement, incentive, and protection mechanism for existing links. Based on the analytical results, we design a D2D-assisted offloading strategy, which allows the requester to postpone data reception in exchange for discounted service fees. Simulation results show that the operator’s utility can be significantly improved. Particularly, it is found that user mobility facilitates the above process.

Advanced structural health monitoring and damage detection using inverse methods and perturbation stiff-ness matrix analysis

Sensor technology advancements have the health monitoring task for modern intricate structures introduce many challenges, primarily centered around the augmentation of safety margins and operational dependabil-ity. The demand for diverse systems or methodologies is, therefore, increasing. These systems or methodolo-gies should be capable of detecting damage, monitoring remotely, and conducting continuous evaluations in real-time. As part of this study, inverse techniques rooted in wave propagation analysis within structural frameworks are utilized to identify damage response vectors. Additionally, mathematical formulations grounded in minimal rank perturbation theory facilitate determining a perturbed stiffness matrix for a com-promised structure. Various excitations are included in the analysis, which is based on intricate non-linear structural modeling. Using streamlined procedures, these findings confirm the inherent versatility of a range of methodologies capable of meeting both rapid monitoring needs and exhaustive analytical needs. In addition, the proposed approach promotes the use of intelligent structures embedded with a variety of sensors that are not restricted by limitations related to sensor type or spatial deployment. Monitoring structural health and detecting damage could be significantly improved by this strategic deployment.

Prioriactions: Multi‐action management planning in R

AbstractDesigning effective conservation strategies requires deciding not only where to locate conservation actions (i.e. which territorial units should be priortized), but also which type actions should be deployed. For most of conservation planning contexts, deciding where and what to do usually yields a complex and computationally challenging decision‐making setting. Although the resulting optimization problems have typically been tackled using heuristic approaches, recent advances in mixed integer programming (MIP) solver technology have turned MIP‐based approaches into a practical alternative for solving complex conservation planning problems.We introduce theRpackageprioriactions, which allows solving complex conservation planning problems comprising prioritization and action deployment decisions.prioriactionsfeatures a MIP approach that allows formulating and solving optimally (or nearly optimally) a wide class of conservation planning problems (characterized by different spatial and functional constraints and requirements). Furthermore, the package allows using a variety of commercial and open‐source exact solvers enhancing its usability as well as its practical effectiveness.Here, we present a comprehensive description of the main functions available inprioriactions. This package has a workflow of three straightforward steps: (a) validation of the input data, using theinputData()function that prepares input; (b) the creation of a prioritization model, using theproblem()function, allows the creation of two types of common models: theminimization of coststo achieve a recovery target andmaximizing the recovery benefitsgiven a limited budget; and (c) to solve of the model, using thesolve()function.Theprioriactionspackage provides a user‐friendly platform for addressing different multi‐actions management problems, allowing to identify more rigorously, transparently and in a reproducible way the spatial deployment of management actions.

On the coupling between wall-modeled LES and immersed boundary method towards applicative compressible flow simulations

The current work presents an innovative numerical technique for high-Reynolds/high-Mach number compressible flow simulations in complex configurations. In particular, the research combines a novel wall-modeled large-eddy simulation technique with a sharp-interface immersed boundary method in the framework of high-order numerical schemes. The proposed approach enables the best from wall modeling and the immersed boundary. The first is concerned with accurately dealing with wall flows while avoiding direct control of near-wall resolution; the second is related to efficiently treating arbitrarily complex geometries in Cartesian grids. In particular, the paper extends a well-established wall model already presented by the research group to arbitrarily-shaped bounds. The method yields a minimally invasive technique that switches between wall-resolved and wall-modeled large-eddy simulations according to the local near-wall resolution. Thus, easily fitting aerodynamic simulation needs. After discussing the numerical procedure, the paper provides several benchmarks to demonstrate the validity of the proposed approach. In particular, literature-available direct numerical datasets are mined to compare acquired outcomes. The results’ accuracy is found to be remarkable from low-Mach-channel and -pipe flow configurations up highly-compressible flows concerning the spatial deployment of the boundary layer over a flat plate and the shock-wave/boundary-layer interaction over a compression ramp. Thus, the proposed method appears to be a promising framework for dealing with engineering-relevant flow simulations along with the efficient path of Cartesian meshes combined with massively parallel GPU-accelerated architectures.

An updating-based working memory load alters the dynamics of eye movements but not their spatial extent during free viewing of natural scenes

The relationship between spatial deployments of attention and working memory load is an important topic of study, with clear implications for real-world tasks such as driving. Previous research has generally shown that attentional breadth broadens under higher load, while exploratory eye-movement behaviour also appears to change with increasing load. However, relatively little research has compared the effects of working memory load on different kinds of spatial deployment, especially in conditions that require updating of the contents of working memory rather than simple retrieval. The present study undertook such a comparison by measuring participants’ attentional breadth (via an undirected Navon task) and their exploratory eye-movement behaviour (a free-viewing recall task) under low and high updating working memory loads. While spatial aspects of task performance (attentional breadth, and peripheral extent of image exploration in the free-viewing task) were unaffected by the load manipulation, the exploratory dynamics of the free-viewing task (including fixation durations and scan-path lengths) changed under increasing load. These findings suggest that temporal dynamics, rather than the spatial extent of exploration, are the primary mechanism affected by working memory load during the spatial deployment of attention. Further, individual differences in exploratory behaviour were observed on the free-viewing task: all metrics were highly correlated across working memory load blocks. These findings suggest a need for further investigation of individual differences in eye-movement behaviour; potential factors associated with these individual differences, including working memory capacity and persistence versus flexibility orientations, are discussed.

Performance Analysis of Multi-Hop Flying Mesh Network Using Directional Antenna Based on β-GPP

Maintaining high system performance is critical for a multi-hop flying mesh network (FlyMesh) to perform missions in different environments. Although the Poisson point process (PPP) has been widely used for the performance analysis of FlyMesh, it still has flaws in describing the spatial distribution of the UAVs since it does not restrict the minimum distance between them. The spatial deployment of FlyMesh varies depending on the environment. Considering the relevance and practicality, we modeled the multi-hop FlyMesh using the β-Ginibre point process (β-GPP) and equipped each UAV with a directional antenna. Under the condition of the decode-and-forward protocol, we derived the connection probability and ergodic capacity of a multi-hop FlyMesh utilizing the Laplace transform of interference. Then, we calculated an approximate expression for the interference Laplace transform based on the diagonal approximation and further obtained the coverage probability. Finally, the numerical simulation results verified the correctness of the theoretical derivation, indicating that it is possible to optimize the system’s performance based on the expressions derived in this paper.

Integrated Human Activity Sensing and Communications

Advances in wireless communication and signal processing facilitate integrated sensing and communication (ISAC) - a compelling technology that intrinsically combines sensing and communication functionalities for the dual-purpose exploitation of wireless/hardware resources and pursues mutual benefits. Consequently, the next-generation communications network will be perceptive. In this article, we provide a review of human-related sensing in the context of ISAC. We first present a general ISAC receiver signal processing framework, with a focus on human activity recognition (HAR). Based on its specific spatial deployments, we then categorize ISAC HAR into monostatic, bi-static, and distributed deployments, and discuss their properties, critical research problems and solutions. To facilitate the system's realization and improve its recognition performance, we then explore the inherent connections between the physical-layer system parameters and HAR performance metrics. Experimental results are presented for characterizing the sensing potentials of different ISAC systems. Finally, we review the technical challenges and identify the open research problems.

A dynamic simulation model to assess farm-level effects of pasture intensification strategies on beef herd outputs and carbon footprints in acid soil savannas of Eastern Colombia

The neotropical savannas of Eastern Colombia (Llanos) are subjected to changes in land use associated with intensification of beef production and there is limited knowledge on the long-term impacts of these change processes. Furthermore, the effects of spatial and temporal intensification at farm level via the introduction of sown pastures on beef herd outputs, their greenhouse gas (GHG) emissions and the resulting carbon (C) footprints in contrasting savanna landscapes of of the Llanos are unknown. This study was aimed to assess the consequences of gradual system intensification via introduction of sown tropical pastures in two contrasting landscapes, the tillable, flat savannas and the highly dissected rangelands, of the well-drained Eastern savannas of Colombia, in terms of cow-calf production and GHG emissions and the resulting C footprints. A dynamic model was developed to simulate the gradual introduction of two types of tropical pastures in a region with dissected and steep slopes and limited tillable areas where cattle would also have access to Serrania savanna and sown pastures, versus one located in the Plains that are fully transformed over time with the exclusion of native rangelands. Marked changes in herd demography, animal outputs, and emissions were found over time. The C footprint of all systems varied over time depending upon the length of time that pastures contributed to soil organic carbon accumulation and the balance between savanna and sown pasture areas at a whole farm level. In conclusion, the dynamics of the systems subject to intensification were marked and were dependent on the temporal and spatial deployment of sown forage resources. Therefore, generalizing the trends for the region as a whole result in uncertainty. Nevertheless, examination of simulated prototypes may shed light on the expected trends and provides guidance for decision-making

Research on Automatic attitude adjustment Technology of Suspension rail of the Unfolding frame

Spacecraft solar wings, antennas, and other space deployment mechanisms need to be unloaded by gravity during the ground launch test. At present, the most widely used is the guide rail type Micro-gravity unfolding frame, and the rail needs to be adjusted horizontally before the test is carried out. Aiming at the shortcomings of the current rail debugging relying on labor, difficult high-altitude operation, and low debugging efficiency, a guide rail automatic attitude adjustment device is proposed, which can quickly realize the efficient adjustment and attitude maintenance of the rail level. After test verification, the system can increase the local level of the guide rail from the traditional 0.02 mm/m to 0.01 mm/m, the overall level from the original 0.1 mm/m to 0.02 mm/m, and shorten the commissioning time from the original 4 h to 1 h. The power-off holding ability is strong, which greatly improves the efficiency of the ground test. The research results have been applied to other spatial deployment institutions that conduct tests based on rails.

Renewable energy creditors versus renewable energy debtors: Seeking a pattern in a sustainable energy transition during the climate crisis

Considering unpredictable and hastily evolving tipping points (like the impacts of the COVID-19 pandemic, ongoing climate crisis and the war in Ukraine), it is clear that sustainable energy transition and utilization of locally sourced renewable energies must be in the heart of both national, regional, and local energy systems. However, if we take a closer look at the actions undertaken at the local (communal) level, we see enormous diversity of patterns, prerequisites, and implications that drive and affect spatial deployment of renewable energies. Therefore, our research targets to better comprehend the question if individual communities are comparatively involved in the energy transition. We also ask whether the demand and supply of renewable energy is territorially balanced and how these differences (if any) can be justified. We are framing our research by the concepts of energy justice and ecological debt. We thoroughly explore and asses the renewable energy balance on the level of individual communities which is based on data on the installed power capacity potentials and energy consumption in local administration units in Poland (380). Spatial distribution and discrepancies in the deployment of the renewable energy creditors and the renewable energy debtors are detected. Noticeable disproportions were identified among communities where improved utilization of local potential of renewable energy could exceed energy demand (29% of communities). This result is contrasting with communities (71% of communities) that can be, on the other hand, classified as renewable energy debtors. We claim that insufficient support (institution, regulatory, and financial) for expanding local renewable energy systems is a clear barrier when adapting to the climate crisis by balancing the energy demand and supply at the local level.

A full three‐dimensional surface energy balance over a desert playa

AbstractFor decades, closure of the surface energy balance (SEB) has remained an outstanding problem for the atmospheric boundary layer (ABL) community. Despite many attempts at achieving closure following systematic approaches, universal closure remains elusive and only on rare occasions is it achieved. In this work, data from the unique spatial deployment of sensors from the Idealized Planar Array experiment for Quantifying Spatial heterogeneity (IPAQS 2019) field campaign are used to compute the three‐dimensional SEB. Results are compared with the traditional one‐dimensional SEB approach. The three‐dimensional SEB uses an integrated approach derived from the temperature tendency equation for a 400 m 400 m 2 m control volume over near‐canonical terrain, where the only complexities arise from time‐persistent surface thermal heterogeneities. Often neglected transport terms, such as advection and dispersive fluxes, are assessed and studied. Results show that, when using a three‐dimensional approach, it is possible to obtain an improved closure of the SEB during convective periods that can attain residual values of the order of accuracy of the instrumentation. Lastly, a theoretical development to account for the flux imbalance is presented that shows a promising approach for scaling the contribution of mean advective transport using onsite measurable variables.