Thematische Bibliographien / The UAV placement problem

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Auswahl der wissenschaftlichen Literatur zum Thema „The UAV placement problem“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

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Zeitschriftenartikel zum Thema "The UAV placement problem"

Goehar, Huda, Ahmed S. Khwaja, Ali A. Alnoman, Alagan Anpalagan, and Muhammad Jaseemuddin. "Investigation of a HAP-UAV Collaboration Scheme for Throughput Maximization via Joint User Association and 3D UAV Placement." Sensors 23, no. 13 (2023): 6095. http://dx.doi.org/10.3390/s23136095.

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In this paper, a collaboration scheme between a high-altitude platform (HAP) and several unmanned aerial vehicles (UAVs) for wireless communication networks is investigated. The main objective of this study is to maximize the total downlink throughput of the ground users by optimizing the UAVs’ three-dimensional (3D) placements and user associations. An optimization problem is formulated and a separate genetic-algorithm-based approach is proposed to solve the problem. The K-means algorithm is also utilized to find the initial UAV placement to reduce the convergence time of the proposed genetic-algorithm-based allocation. The performance of the proposed algorithm is analyzed in terms of convergence time, complexity, and fairness. Finally, the simulation results show that the proposed HAP-UAV integrated network achieves a higher total throughput through joint user association and UAV placement schemes compared to a scheme with a single HAP serving all users.

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Lee, Chunghyun, Gunhee Jang, Nhu-Ngoc Dao, Demeke Shumeye Lakew, Cheol Lee, and Sungrae Cho. "Competitive Game Theoretic Clustering-Based Multiple UAV-Assisted NB-IoT Systems." Electronics 10, no. 3 (2021): 356. http://dx.doi.org/10.3390/electronics10030356.

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Unmanned aerial vehicle (UAV) communication is regarded as a promising technology for lightweight Internet of Things (IoT) communications in narrowband-IoT (NB-IoT) systems deployed in rugged terrain. In such UAV-assisted NB-IoT systems, the optimal UAV placement and resource allocation play a critical role. Consequently, the joint optimization of the UAV placement and resource allocation is considered in this study to improve the system capacity. Because the considered optimization problem is an NP-hard problem and owing to its non-convex property, it is difficult to optimize both the UAV placement and resource allocation simultaneously. Therefore, a competitive clustering algorithm has been developed by exchanging strategies between the UAV and the adjacent IoT devices to optimize the UAV placement. With multiple iterations, the UAV and the IoT devices within the coverage area of the UAV, converge their clustering strategies, which are suboptimal, to satisfy both sides. The bordering IoT devices of the adjacent clusters are then migrated heuristically toward each other to obtain the optimal system capacity maximization. Finally, the transmission throughput is optimized using the Nash equilibrium. The simulation results demonstrate that the algorithms proposed in this study exhibit rapid convergence, within 10 iterations, even in a large environment. The performance evaluation demonstrates that the proposed scheme improves the system capacity of the existing schemes by approximately 28%.

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Xue, Yishi, Bo Xu, Wenchao Xia, Jun Zhang, and Hongbo Zhu. "Backhaul-Aware Resource Allocation and Optimum Placement for UAV-Assisted Wireless Communication Network." Electronics 9, no. 9 (2020): 1397. http://dx.doi.org/10.3390/electronics9091397.

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Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.

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Safwat, Nour El-Din, Ismail Mohammed Hafez, and Fatma Newagy. "3D Placement of a New Tethered UAV to UAV Relay System for Coverage Maximization." Electronics 11, no. 3 (2022): 385. http://dx.doi.org/10.3390/electronics11030385.

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In this paper, a new relay system that uses the UAV as a relay station between the tethered UAV and ground user (TU2U2G) is proposed. The TU2U2G system uses a TUAV as a viable alternative to replace BS and provide seamless service over a cable that simultaneously supplies stable power and a reliable wired data-link connection from a ground control station. Compared to the BS, TUAV improves system coverage due to its high altitude. Also, it overcomes the antenna down-tilting, which increases the path loss between BS and UAV in the cellular system. In addition, it overcomes the UAV drawback of the batteries’ limited capacity. Therefore, TUAV can achieve the main requirements of a reliable cellular BS in terms of endurance, backhaul link quality, and the advantage of the UAV’s high altitude. After that, the optimization problem is formulated to maximize UAV relay station coverage under the power budget and maximum UAV height constraints. For simplicity, the 3D placement of the UAV is decoupled to the vertical and horizontal placement. Then, a 3D placement algorithm for the system is proposed. The UAV placement in the TU2U2G system compared to the cellular system shows better results in terms of optimum UAV height, maximum coverage radius, and maximum relaying distance.

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Liu, Chaoyi, and Qi Zhu. "Joint Resource Allocation and Learning Optimization for UAV-Assisted Federated Learning." Applied Sciences 13, no. 6 (2023): 3771. http://dx.doi.org/10.3390/app13063771.

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Aiming at the unmanned aerial vehicle (UAV)-assisted federated learning wireless-network scenario, and considering the influence of the UAV altitude on the coverage area, we propose a joint optimization algorithm of UAV placement, computation and communication resources. Considering the energy efficiency and federated learning performance, we defined the cost function of the system. Under the constraint of the total delay of federated learning completion, we formulated an optimization problem of minimizing the cost function to achieve the balance between the total energy consumption of users and the federated learning performance. Since the formulated optimization problem is a non-convex problem, in order to solve this problem, we decomposed it into three optimization subproblems: UAV horizontal placement, local accuracy and computation and communication resources. We used successive convex approximation (SCA), the Dinkelbach Method, the Bisection method and KKT condition, respectively, to solve the three subproblems, and finally obtain the optimal solutions through iteration of the three subproblems. Simulation results show that compared with the federated learning scenario under fixed UAV altitude, our proposed algorithm not only guarantees the learning performance, but also reduces more users’ total energy consumption.

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Lan, Tingting, Danyang Qin, and Guanyu Sun. "Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks." ISPRS International Journal of Geo-Information 10, no. 7 (2021): 426. http://dx.doi.org/10.3390/ijgi10070426.

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In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

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Zhang, Ziyong, Xiaoling Xu, Jinqiang Cui, and Wei Meng. "Multi-UAV Area Coverage Based on Relative Localization: Algorithms and Optimal UAV Placement." Sensors 21, no. 7 (2021): 2400. http://dx.doi.org/10.3390/s21072400.

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This paper is concerned with relative localization-based optimal area coverage placement using multiple unmanned aerial vehicles (UAVs). It is assumed that only one of the UAVs has its global position information before performing the area coverage task and that ranging measurements can be obtained among the UAVs by using ultra-wide band (UWB) sensors. In this case, multi-UAV relative localization and cooperative coverage control have to be run simultaneously, which is a quite challenging task. In this paper, we propose a single-landmark-based relative localization algorithm, combined with a distributed coverage control law. At the same time, the optimal multi-UAV placement problem was formulated as a quadratic programming problem by compromising between optimal relative localization and optimal coverage control and was solved by using Sequential Quadratic Programming (SQP) algorithms. Simulation results show that our proposed method can guarantee that a team of UAVs can efficiently localize themselves in a cooperative manner and, at the same time, complete the area coverage task.

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Zhong, Tianyao, Ducheng Wu, Guoxin Li, Haichao Wang, Runfeng Chen, and Jihao Cai. "Joint Optimization of Spectrum Resource Management and Position Placement for UAV Base Station Networks." Wireless Communications and Mobile Computing 2023 (April 27, 2023): 1–14. http://dx.doi.org/10.1155/2023/2328249.

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The unmanned aerial vehicle (UAV) base station plays a significant role in enhancing the terrestrial network, when the ground base station (GBS) is destroyed in emergent cases or its load exceeds the capacity of the terrestrial network. Presently, many papers focus on optimizing the UAV position deployment and user access, while ignoring the optimization about the spectrum resource management. To solve this problem, we formulate a joint optimization problem of the spectrum resource management and the position placement for UAVs with the constraint of the limited backhaul capacity. Later, the joint optimization problem is modeled as a hierarchical game decision architecture comprised of a UAV position placement game and a spectrum resource management game. Further, we analyze the equilibrium property of the two games and propose two best response- (BR) based optimization algorithms to reach the Nash Equilibriums (NEs) of the two games, respectively. Specifically, the proposed algorithm about the UAV deployment considers the variable granularity local exploration and global random exploration. Simulation results show that the proposed UAV deployment algorithm can improve the total throughput by 7% and 20% at least in comparison with the K-means deployment algorithm and the fixed granularity exploration algorithm, respectively.

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Waheed, Maham, Rizwan Ahmad, Waqas Ahmed, Muhammad Mahtab Alam, and Maurizio Magarini. "On Coverage of Critical Nodes in UAV-Assisted Emergency Networks." Sensors 23, no. 3 (2023): 1586. http://dx.doi.org/10.3390/s23031586.

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Unmanned aerial vehicle (UAV)-assisted networks ensure agile and flexible solutions based on the inherent attributes of mobility and altitude adaptation. These features render them suitable for emergency search and rescue operations. Emergency networks (ENs) differ from conventional networks. They often encounter nodes with vital information, i.e., critical nodes (CNs). The efficacy of search and rescue operations highly depends on the eminent coverage of critical nodes to retrieve crucial data. In a UAV-assisted EN, the information delivery from these critical nodes can be ensured through quality-of-service (QoS) guarantees, such as capacity and age of information (AoI). In this work, optimized UAV placement for critical nodes in emergency networks is studied. Two different optimization problems, namely capacity maximization and age of information minimization, are formulated based on the nature of node criticality. Capacity maximization provides general QoS enhancement for critical nodes, whereas AoI is focused on nodes carrying critical information. Simulations carried out in this paper aim to find the optimal placement for each problem based on a two-step approach. At first, the disaster region is partitioned based on CNs’ aggregation. Reinforcement learning (RL) is then applied to observe optimal placement. Finally, network coverage over optimal UAV(s) placement is studied for two scenarios, i.e., network-centric and user-centric. In addition to providing coverage to critical nodes, the proposed scheme also ensures maximum coverage for all on-scene available devices (OSAs).

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Shalaby, Abdulrahman M., and Noor Shamsiah Othman. "The Effect of Rainfall on the UAV Placement for 5G Spectrum in Malaysia." Electronics 11, no. 5 (2022): 681. http://dx.doi.org/10.3390/electronics11050681.

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In this paper, the influence of rainfall on the deployment of UAV as an aerial base station in the Malaysia 5G network is studied. The outdoor-to-outdoor and outdoor-to-indoor path loss models are derived by considering the user’s antenna height, rain attenuation, and the wall penetration loss at high frequencies. The problem of finding the UAV 3D placement is formulated with the objective to minimize the total path loss between the UAV and all users. The problem is solved by invoking two algorithms, namely Particle Swarm Optimization (PSO) and Gradient Descent (GD) algorithms. The performance of the proposed algorithms is evaluated by considering two scenarios to determine the optimum location of the UAV, namely outdoor-to-outdoor and outdoor-to-indoor scenarios. The simulation results show that, for the outdoor-to-outdoor scenario, both algorithms resulted in similar UAV 3D placement unlike for the outdoor-to-indoor scenario. Additionally, in both scenarios, the proposed algorithm that invokes PSO requires less iterations to converge to the minimum transmit power compared to that of the algorithm that invokes GD. Moreover, it is also observed that the rain attenuation increases the total path loss for high operating frequencies, namely at 24.9 GHz and 28.1 GHz. Hence, this resulted in an increase of UAV required transmit power. At 28.1 GHz, the presence of rain at the rate of 250 mm/h resulted in an increase of UAV required transmit power by a factor of 4 and 15 for outdoor-to-outdoor and outdoor-to-indoor scenarios, respectively.

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Dissertationen zum Thema "The UAV placement problem"

Ait, Saadi Amylia. "Coordination of scout drones (UAVs) in smart-city to serve autonomous vehicles." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG064.

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Le sujet des véhicules aériens sans pilote (VAP) est devenu un domaine d'étude prometteurtant dans la recherche que dans l'industrie. En raison de leur autonomie et de leur efficacitéen vol, les drones sont considérablement utilisés dans diverses applications pour différentestâches. Actuellement, l'autonomie du drone est un problème difficile qui peut avoir un impactà la fois sur ses performances et sur sa sécurité pendant la mission. Pendant le vol, les dronesautonomes sont tenus d'investiguer la zone et de déterminer efficacement leur trajectoire enpréservant leurs ressources (énergie liée à la fois à l'altitude et à la longueur de la trajectoire) et en satisfaisant certaines contraintes (obstacles et rotations d'axe). Ce problème estdéfini comme le problème de planification de trajectoire UAV qui nécessite des algorithmesefficaces pour être résolus, souvent des algorithmes d'intelligence artificielle. Dans cettethèse, nous présentons deux nouvelles approches pour résoudre le problème de planificationde trajectoire UAV. La première approche est un algorithme amélioré basé sur l'algorithmed'optimisation des vautours africains, appelé algorithmes CCO-AVOA, qui intègre la cartechaotique, la mutation de Cauchy et les stratégies d'apprentissage basées sur l'oppositiond'élite. Ces trois stratégies améliorent les performances de l'algorithme AVOA original entermes de diversité des solutions et d'équilibre de recherche exploration/exploitation. Unedeuxième approche est une approche hybride, appelée CAOSA, basée sur l'hybridation deChaotic Aquila Optimization avec des algorithmes de recuit simulé. L'introduction de lacarte chaotique améliore la diversité de l'optimisation Aquila (AO), tandis que l'algorithmede recuit simulé (SA) est appliqué comme algorithme de recherche locale pour améliorer larecherche d'exploitation de l'algorithme AO traditionnel. Enfin, l'autonomie et l'efficacitédu drone sont abordées dans une autre application importante, qui est le problème de placement du drone. La question du placement de l'UAV repose sur la recherche de l'emplacementoptimal du drone qui satisfait à la fois la couverture du réseau et la connectivité tout entenant compte de la limitation de l'UAV en termes d'énergie et de charge. Dans ce contexte, nous avons proposé un hybride efficace appelé IMRFO-TS, basé sur la combinaisonde l'amélioration de l'optimisation de la recherche de nourriture des raies manta, qui intègreune stratégie de contrôle tangentiel et d'algorithme de recherche taboue The subject of Unmanned Aerial Vehicles (UAVs) has become a promising study field in bothresearch and industry. Due to their autonomy and efficiency in flight, UAVs are considerablyused in various applications for different tasks. Actually, the autonomy of the UAVis a challenging issue that can impact both its performance and safety during the mission.During the flight, the autonomous UAVs are required to investigate the area and determineefficiently their trajectory by preserving their resources (energy related to both altitude andpath length) and satisfying some constraints (obstacles and axe rotations). This problem isdefined as the UAV path planning problem that requires efficient algorithms to be solved,often Artificial Intelligence algorithms. In this thesis, we present two novel approachesfor solving the UAV path planning problem. The first approach is an improved algorithmbased on African Vultures Optimization Algorithm (AVOA), called CCO-AVOA algorithms,which integrates the Chaotic map, Cauchy mutation, and Elite Opposition-based learningstrategies. These three strategies improve the performance of the original AVOA algorithmin terms of the diversity of solutions and the exploration/exploitation search balance. Asecond approach is a hybrid-based approach, called CAOSA, based on the hybridization ofChaotic Aquila Optimization with Simulated Annealing algorithms. The introduction of thechaotic map enhances the diversity of the Aquila Optimization (AO), while the SimulatedAnnealing (SA) algorithm is applied as a local search algorithm to improve the exploitationsearch of the traditional AO algorithm. Finally, the autonomy and efficiency of the UAVare tackled in another important application, which is the UAV placement problem. Theissue of the UAV placement relays on finding the optimal UAV placement that satisfies boththe network coverage and connectivity while considering the UAV's limitation from energyand load. In this context, we proposed an efficient hybrid called IMRFO-TS, based on thecombination of Improved Manta Ray Foraging Optimization, which integrates a tangentialcontrol strategy and Tabu Search algorithms

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Stilson, Mona T. "Multi-UAV Control: An Envisioned World Design Problem." Wright State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=wright1245640561.

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Baker, Chris. "A combined mechanism for UAV explorative path planning, task allocation and predictive placement." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/405212/.

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The use of Unmanned Aerial Vehicles (UAVs) is becoming ever more common by people or organisations who wish to get information about an area quickly and without a human presence. As a result, there has been a concerted effort to develop systems that allow the deployment of UAVs in disaster scenarios, in order to aid first responders with collecting imagery and other sensory data without putting human lives at risk. In particular, work has focused on developing autonomous systems to minimise the involvement of overstretched first responder personnel, and to ensure action can be taken by the UAVs quickly, co-operatively, and with close to optimal results. Key to this work, is the idea of enabling coordinated UAVs to explore a disaster space to discover incidents and then to allow more detailed examination, imagery, or sensing of these locations. Consequently, in this thesis we examine the challenge of coordinating exploratory and task-responsive UAVs in the presence of prior (but uncertain) beliefs about incident locations, and the combination of their roles together. To do this, we first identify the key components of such a system as: path planning, task allocation, and using belief data for predictive UAV placement. Subsequently, we introduce our contributions in the form of a complete, decentralised system for a single explorative path planner to minimise the time to identify incidents, to allocate incidents to UAVs as tasks, and to place UAVs prior to new tasks being found. Having demonstrated the efficacy of this solution in experimental scenarios, we extend the formulation of our explorative path-planning problem to multiple UAVs by constructing a coordinated, factored Monte-Carlo Tree Search algorithm for use in a discretised space representation of a disaster area. Subsequently, we detail the performance of our new algorithm against uncoordinated alternatives using real data from the 2010 Haiti earthquake. We demonstrate the performance benefits of our method via the metric of people discovered in the simulation; showing improvements of up to 23% in cases with ten UAVs. This is the first application of this technique to very large action spaces of the type encountered in realistic disaster scenarios. Finally, we modify our coordinated exploration algorithm to function in a continuous action space. This represents the first example of a continuous factored coordinated Monte-Carlo Tree Search algorithm. We evaluated this algorithm on the same Haiti dataset as the discretised version, but with a new sensor model simulating mobile phone signal detection to represent the types of sensors deployed by first responders. In addition to the benefits of a more realistic model of the environment, we found improvements in survivor localisation times of up to 20% over the discrete algorithm; demonstrating the value in our approach. As such, the contributions presented in this thesis advance the state of the art in UAV coordination algorithms, and represent a progression towards the widespread deployment of autonomous platforms that can aid rescue workers in disaster situations and—ultimately—save lives.

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Jones, E. R. Ll. "The general pole placement problem in singular systems." Thesis, Loughborough University, 1991. https://dspace.lboro.ac.uk/2134/31932.

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Over the last decade infinite poles and zeros have been recognised as having fundamental relevance to the analysis of the dynamical behaviour of a system. Indeed even the classical theory of characteristic root loci alludes to the existence of infinite zeros without defining them as such whilst the significance of the infinite poles has more recently emerged in the study of non-proper systems.

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Furfaro, Roberto. "Radiative transport in plant canopies: Forward and inverse problem for UAV applications." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/280700.

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This dissertation deals with modeling the radiative regime in vegetation canopies and the possible remote sensing applications derived by solving the forward and inverse canopy transport equation. The aim of the research is to develop a methodology (called "end-to-end problem solution") that, starting from first principles describing the interaction between light and vegetation, constructs, as the final product, a tool that analyzes remote sensing data for precision agriculture (ripeness prediction). The procedure begins by defining the equations that describe the transport of photons inside the leaf and within the canopy. The resulting integro-differential equations are numerically integrated by adapting the conventional discrete-ordinate methods to compute the reflectance at the top of the canopy. The canopy transport equation is also analyzed to explore its spectral properties. The goal here is to apply Case's method to determine eigenvalues and eigenfunctions and to prove completeness. A model inversion is attempted by using neural network algorithms. Using input-outputs generated by running the forward model, a neural network is trained to learn the inverse map. The model-based neural network represents the end product of the overall procedure. During Oct 2002, an Unmanned Aerial Vehicles (UAVs) equipped with a camera system, flew over Kauai to take images of coffee field plantations. Our goal is to predict the amount of ripe coffee cherries for optimal harvesting. The Leaf-Canopy model was modified to include cherries as absorbing and scattering elements and two classes of neural networks were trained on the model to learn the relationship between reflectance and percentage of ripe, over-ripe and under-ripe cherries. The neural networks are interfaced with images coming from Kauai to predict ripeness percentage. Both ground and airborne images are considered. The latter were taken from the on-board Helios UAV camera system flying over the Kauai coffee field. The results are compared against hand counts and parchment data to evaluate the network performances on real applications. In ground images, the error is always less than 11%. In airborne image, the error bound is 20%. The results are certainly adequate and show the tremendous potential of the methodology.

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Jung, Changyong. "ON RELAY NODE PLACEMENT PROBLEM FOR SURVIVABLE WIRELESS SENSOR NETWORKS." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/570.

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Wireless sensor networks are widely applied to many fields such as animal habitat monitoring, air traffic control, and health monitoring. One of the current problems with wireless sensor networks is the ability to overcome communication failures due to hardware failure, distributing sensors in an uneven geographic area, or unexpected obstacles between sensors. One common solution to overcome this problem is to place a minimum number of relay nodes among sensors so that the communication among sensors is guaranteed. This is called Relay Node Placement Problem (RNP). This problem has been proved as NP-hard for a simple connected graph. Therefore, many algorithms have been developed based on Steiner graphs. Since RNP for a connected graph is NP-hard, the RNP for a survivable network has been conjectured as NP-hard and the algorithms for a survivable network have also been developed based on Steiner graphs. In this study, we show the new approximation bound for the survivable wireless sensor networks using the Steiner graphs based algorithm. We prove that the approximation bound is guaranteed in an environment where some obstacles are laid, and also propose the newly developed algorithm which places fewer relay nodes than the existing algorithms. Consequently, the main purpose of this study is to find the minimum number of relay nodes in order to meet the survivability requirements of wireless sensor networks.

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Ernest, Nicholas D. "UAV Swarm Cooperative Control Based on a Genetic-Fuzzy Approach." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337954828.

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Ural, Mustafa. "Solution Of The Antenna Placement Problem By Means Of Global Optimization Techniques." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612674/index.pdf.

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In this thesis work, minimization of platform-based coupling between the antennas of two VHF radios on an aircraft platform and two HF radios on a ship platform is aimed. For this purpose an optimal antenna placement, which yields minimum average coupling between the antennas over the whole frequency band of operation is determined for each platform. Two important global optimization techniques, namely Genetic Algorithm Optimization and Particle Swarm Optimization, are used in determination of these optimal antenna placements. Aircraft &amp ship platforms and antennas placed on them are modeled based on their real electrical and physical properties in CST &ndash MWS (Microwave Studio) simulation tool. For each platform, antenna placements and coupling results determined by two different optimization techniques and performances of these optimization techniques are compared with each other. At the end of this thesis work for each platform, far-field radiation pattern performances of the antennas at their optimal places are analyzed in terms of directivity and coverage.

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Mofya, Enock Chisonge. "Exact and Heuristic Algorithms for Solving the Generalized Minimum Filter Placement Problem." Diss., Tucson, Arizona : University of Arizona, 2005. http://etd.library.arizona.edu/etd/GetFileServlet?file=file:///data1/pdf/etd/azu%5Fetd%5F1311%5F1%5Fm.pdf&type=application/pdf.

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Haslum, Patrik. "Prediction as a Knowledge Representation Problem : A Case Study in Model Design." Licentiate thesis, Linköping University, Linköping University, KPLAB - Knowledge Processing Lab, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5724.

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The WITAS project aims to develop technologies to enable an Unmanned Airial Vehicle (UAV) to operate autonomously and intelligently, in applications such as traffic surveillance and remote photogrammetry. Many of the necessary control and reasoning tasks, e.g. state estimation, reidentification, planning and diagnosis, involve prediction as an important component. Prediction relies on models, and such models can take a variety of forms. Model design involves many choices with many alternatives for each choice, and each alternative carries advantages and disadvantages that may be far from obvious. In spite of this, and of the important role of prediction in so many areas, the problem of predictive model design is rarely studied on its own.In this thesis, we examine a range of applications involving prediction and try to extract a set of choices and alternatives for model design. As a case study, we then develop, evaluate and compare two different model designs for a specific prediction problem encountered in the WITAS UAV project. The problem is to predict the movements of a vehicle travelling in a traffic network. The main difficulty is that uncertainty in predictions is very high, du to two factors: predictions have to be made on a relatively large time scale, and we have very little information about the specific vehicle in question. To counter uncertainty, as much use as possible must be made of knowledge about traffic in general, which puts emphasis on the knowledge representation aspect of the predictive model design.The two mode design we develop differ mainly in how they represent uncertainty: the first uses coarse, schema-based representation of likelihood, while the second, a Markov model, uses probability. Preliminary experiments indicate that the second design has better computational properties, but also some drawbacks: model construction is data intensive and the resulting models are somewhat opaque. Report code: LiU-Tek-Lic-2002:15.

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Bücher zum Thema "The UAV placement problem"

Ronald, Drucker, ed. Chemistry problem-solving companion. Peoples Education, 2008.

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Minnesota. Dept. of Corrections. and Minnesota. Dept. of Human Services., eds. Juvenile out-of-home placement task force report. Minnesota Dept. of Corrections, 2001.

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M, Kauffman James, ed. Issues in educational placement: Students with emotional and behavioral disorders. L. Erlbaum Associates, 1995.

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Réussir la placement des mineurs en danger: Manuel à l'usage des éducateurs. L'Harmattan, 1996.

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Center, Langley Research, ed. Optimal control of unsteady stokes flow around a cylinder and the sensor/actuator placement problem. National Aeronautics and Space Administration, Langley Research Center, 1998.

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Grimshaw, Roger. Educating disruptive children: Placement and progress in residential special schools for pupils with emotional and behavioural difficulties. National Children's Bureau, 1994.

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Administration, Washington (State) Children's, Washington (State). Dept. of Social and Health Services., Washington (State). Select Committee on Adolescents in Need of Long Term Placement., and Washington State Library. Electronic State Publications., eds. DSHS responds to recommendations from the Select Committee on Adolescents in Need of Long Term Placement. Washington State Dept. of Social & Health Services, Children's Administration, 2003.

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Connecticut. State Dept. of Education. Special study on identification and placement of special education students due to misconduct: Report to the Education Committee of the General Assembly. The Department, 1996.

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Colorado. Dept. of Education. HIV Education Program. and University of Colorado Health Sciences Center. Dept. of Family Medicine. Research and Evaluation Team., eds. Results of the Colorado youth risk behavior survey adapted for youth in out-of-home placement. The Program, 1992.

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Buchteile zum Thema "The UAV placement problem"

Taleb, Sylia Mekhmoukh, Yassine Meraihi, Selma Yahia, Amar Ramdane-Cherif, Asma Benmessaoud Gabis, and Dalila Acheli. "Efficient Coronavirus Herd Immunity Optimizer for the UAV Base Stations Placement Problem." In Modelling and Implementation of Complex Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-18516-8_21.

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Taleb, Sylia Mekhmoukh, Yassine Meraihi, Selma Yahia, Amar Ramdane-Cherif, Asma Benmessaoud Gabis, and Dalila Acheli. "Hybrid Whale Optimization Algorithm with Simulated Annealing for the UAV Placement Problem." In Future Research Directions in Computational Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-34459-6_6.

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Heppe, Stephen B. "Problem of UAV Communications." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_30.

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Bose, Prosenjit, Anil Maheshwari, Pat Morin, and Jason Morrison. "The Grid Placement Problem." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44634-6_17.

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Rautu, Dorin, Riadh Dhaou, and Emmanuel Chaput. "Initial Placement Optimization for Multi-channel UAV Networks." In Ad-Hoc, Mobile, and Wireless Networks. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-31831-4_31.

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Al-Turjman, Fadi, Sinem Alturjman, and Jehad Hamamreh. "Grid-Based UAV Placement in Intelligent Transportation Systems." In Drones in IoT-enabled Spaces. CRC Press, 2019. http://dx.doi.org/10.1201/9780429294327-7.

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Fleischer, Rudolf, and Yihui Wang. "On the Camera Placement Problem." In Algorithms and Computation. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10631-6_27.

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Freund, Ari, and Joseph Seffi Naor. "Approximating the Advertisement Placement Problem." In Integer Programming and Combinatorial Optimization. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47867-1_29.

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Gholami, Anousheh, Nariman Torkzaban, John S. Baras, and Chrysa Papagianni. "Joint Mobility-Aware UAV Placement and Routing in Multi-Hop UAV Relaying Systems." In Ad Hoc Networks. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67369-7_5.

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Zhang, Xianyu, Yong Chen, Yu Zhang, Kang An, and Tao Liang. "Subchannel Allocation for UAV-Enabled OFDMA Systems with UAV Placement and User Association." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9021-4_29.

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Konferenzberichte zum Thema "The UAV placement problem"

Elhassan, Azza, Ahmedagha Eldaniz Hamidzada, Toki Takahiro, et al. "Delivering Zonal Isolation between Reservoir Sublayers in Long, Horizontal 12 ¼-in. Hole Sections in Extended Reach Wells." In SPE/IADC Middle East Drilling Technology Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/202203-ms.

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Abstract Good cementing practices are required to achieve effective zonal isolation and provide long-term well integrity for uninterrupted safe production and subsequent abandonment. Zonal isolation can be attained by paying close attention to optimizing the drilling parameters, hole cleaning, fluid design, cement placement, and monitoring. In challenging extended reach wells in the UAE, different methods were employed to deliver progressive improvement in zonal isolation. Cementing the intermediate and production sections in the UAE field is challenging because of the highly deviated, long, open holes; use of nonaqueous fluids (NAFs); and the persistent problem of lost circulation. Compounding the problem are the multiple potential reservoirs; the pressure testing of the casing at high pressures after cement is set; and the change in downhole pressures and temperatures during production phases, which results in additional stresses. Hence, the mechanical properties for cement systems must be customized to withstand the downhole stresses. The requirement of spacer fluids with nonaqueous compatible properties adds complexity. Lessons learned from prior operations were applied sequentially to produce fit-for-purpose solutions in the UAE field. Standard cement practices were taken as a starting point, and subsequent changes were introduced to overcome specific challenges. These challenges included deeper 12 ¼-in. sections, which made it difficult to manage equivalent circulating densities (ECDs), and a stricter requirement of zonal isolation across sublayers in addition to required top of cement at surface. To satisfy these requirements, several measures were taken gradually: applying engineered trimodal blend systems to remain under ECD limits; pumping a lower-viscosity fluid ahead of the spacer; using NAF-compatible spacers for effective mud removal; employing flexible cement systems to withstand downhole stresses; and modeling the cement job with an advanced cement placement software to simulate displacement rates, bottomhole circulating temperatures, centralizer placement, mud removal and comply with a zero discharge policy that restricts the extra slurry volume to reach surface. To enhance conventional chemistry-based mud cleaning, an engineered scrubbing additive was included in the spacers with a microemulsion-based surfactant. The results of cement jobs were analyzed by playback in advanced evaluation software to verify the efficiency of the applied solutions. This continuous improvement response to changes in well design has resulted in a significant positive change in cement bond logs; a flexural attenuation measurement tool has been used to evaluate the lightweight slurry quality behind the casing, which has helped in enhancing the confidence level in well integrity in these challenging wells. The results highlight the benefit of developing engineering solutions that can be adapted to respond to radical changes in conditions or requirements.

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Ahmed, Shafiq, Amr Serry, Owais Khan, et al. "Water Flood Fronts Monitoring with Ultra-Deep 1D and 3D Resistivity Inversions, A Pilot Case Study in a Mature Carbonate Reservoir, Offshore Abu Dhabi, UAE." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216896-ms.

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Abstract The concept of drilling multilateral wells has been applied offshore UAE since the 1990’s, in order to increase the productivity of low permeable sublayers. The subject, mature Carbonate Offshore field is one of the pioneers to the application of Ultra-deep Azimuthal Resistivity technology (UDAR). The lateral drains target different layers with different petrophysical properties within the Upper Jurassic sequence. Efficient geosteering and the innovative (UDAR) technology applications are key components to secure the fluid fronts mapping in a heterogeneous, water-flooded zones. This case study sheds the light on the vital steps for preparing, executing, and evaluating multilateral well geosteering and geomapping, and how this can be applied to well placement within water-flooded formations. The plan was to drill an 8 ½" mother hole for data gathering, followed by batch drilling a set of two six inch horizontal, lower and upper drains with approximately 4000 ft MD of lateral length, each. A four and three-quarters OD (UDAR) tool has been deployed. Advanced processing with a real time 1D/3D inversions algorithm maximized the tool’s capability to provide measurements with a high depth of detection to map formation and fluid boundaries. Pre-well Geosteering modelling was generated to demonstrate the expected the tool responses and simulate that in 1D inversion. Real time monitoring was conducted using 1D/3D inversions. In the execution stage a four and three-quarters inch triple combo tool string, equipped with high resolution borehole imaging capability was combined with the (UDAR) LWD assembly. The lower drain targeted reservoir B. During drilling, the UDAR inversions identified the sudden unexpected rising of the conductive zone below, interpreted to be a shallowing water contact. Associated with this conductive zone, several high angle features were identified and mapped real-time with 1D UDAR inversions and borehole imaging measurements. These sharp boundaries appeared to influence the water movement. The complex nature of the flooded zone necessitated the application of 3D EM inversion to better understand the relationship between the high angle dislocations and the water. Analysis indicated these dislocations have an orientation running NW-SE. An encountered, operational problem was encountered while opening the upper drain window, resulted in the requirement to cement and re-drill the lower drain section with a different azimuth. During the re-drilling phase, the 1D Inversion mapping confirmed the same dislocations of the water flood zone, in a self-validating practice. The improved reservoir understanding from the lower lateral was applied in the upper lateral horizontal section to enable successful placement and comprehensive fluid reservoir mapping. Successful placement of these laterals brought increased reservoir understanding. Identifying the complex nature of the oil-water contact identification, which is also complicated by faulting. Well placement and production optimization are improved by this increased understanding.

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Heller, Brandon, Rob Sherwood, and Nick McKeown. "The controller placement problem." In the first workshop. ACM Press, 2012. http://dx.doi.org/10.1145/2342441.2342444.

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Dvir, Amit, Yoram Haddad, and Aviram Zilberman. "Wireless controller placement problem." In 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). IEEE, 2018. http://dx.doi.org/10.1109/ccnc.2018.8319228.

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Nguyen, Minh Dat, Tai Manh Ho, Long Bao Le, and Andre Girard. "UAV Placement and Bandwidth Allocation for UAV Based Wireless Networks." In GLOBECOM 2019 - 2019 IEEE Global Communications Conference. IEEE, 2019. http://dx.doi.org/10.1109/globecom38437.2019.9014076.

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Nguyen, Minh Tri, and Long Bao Le. "NOMA User Pairing and UAV Placement in UAV-Based Wireless Networks." In ICC 2019 - 2019 IEEE International Conference on Communications (ICC). IEEE, 2019. http://dx.doi.org/10.1109/icc.2019.8761606.

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Yuan, Xiaopeng, Yulin Hu, James Gross, and Anke Schmeink. "Radio-Map-Based UAV Placement Design for UAV-Assisted Relaying Networks." In 2021 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2021. http://dx.doi.org/10.1109/ssp49050.2021.9513834.

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Lakew, Demeke Shumeye, Arooj Masood, and Sungrae Cho. "3D UAV Placement and Trajectory Optimization in UAV Assisted Wireless Networks." In 2020 International Conference on Information Networking (ICOIN). IEEE, 2020. http://dx.doi.org/10.1109/icoin48656.2020.9016553.

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Cai, Jihao, and Guoxin Li. "UAV-assisted Uplink NOMA Networks: UAV Placement and Resource Block Allocation." In 2022 IEEE International Conference on Unmanned Systems (ICUS). IEEE, 2022. http://dx.doi.org/10.1109/icus55513.2022.9987037.

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Ishtaique ul Huque, Md Tanvir, Guillaume Jourjon, and Vincent Gramoli. "Revisiting the controller placement problem." In 2015 IEEE 40th Conference on Local Computer Networks (LCN). IEEE, 2015. http://dx.doi.org/10.1109/lcn.2015.7366350.

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Berichte der Organisationen zum Thema "The UAV placement problem"

Ratmanski, Kiril, and Sergey Vecherin. Resilience in distributed sensor networks. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45680.

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With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor types, line-of-site and non-line-of-site, and any sensor modality. It also incorporates several realistic constraints including finite sensor supply, cost, energy consumption, as well as specified redundancy in coverage areas that require resilience. While the exact solution is computationally prohibitive, we present a fast algorithm that produces a near-optimal solution that can be used in practice. We show how such formulation works on 2D examples, applied to infrared (IR) sensor networks designed to detect and track human presence and movements in a specified coverage area. Analysis of coverage and comparison of sensor placement with and without resilience considerations is also performed.

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Vlasenko, Kateryna V., Sergei V. Volkov, Daria A. Kovalenko, Iryna V. Sitak, Olena O. Chumak, and Alexander A. Kostikov. Web-based online course training higher school mathematics teachers. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3894.

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The article looks into the problem of theoretical aspects of using Web 2.0 technology in higher education. This paper describes answers of 87 respondents who have helped to identify the most required types of educational content for the integration to pages of the online course training higher school mathematics teachers. The authors carry out a theoretical analysis of researches and resources that consider the development of theoretical aspects of using web tools in higher education. The research presents the characteristics common to online courses, principles of providing a functioning and physical placement of online systems in webspace. The paper discusses the approaches of creating and using animated content in online systems. The authors describe the methods of publishing video content in web systems, in particular, the creation and use of video lectures, animation, presentations. This paper also discusses several of the existing options of integrating presentations on web pages and methods of integrating mathematical expressions in web content. It is reasonable to make a conclusion about the expediency of promoting online courses, the purpose of which is to get mathematics teachers acquainted with the technical capabilities of creating educational content developed on Web 2.0 technology.

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Ginzel. L51748 Detection of Stress Corrosion Induced Toe Cracks-Advancement of the Developed Technique. Pipeline Research Council International, Inc. (PRCI), 1996. http://dx.doi.org/10.55274/r0010659.

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In the past few years an ongoing problem has existed with stress corrosion cracking (SCC) in pipelines around the world. Several member companies of the Pipeline Research Council International, Inc. have experienced multiple incidents as a result of ERW defects and SCC. TCPL is running a series of hydrostatic tests and trial digs to identify the most severely affected areas. These excavations and failure studies have ascertained that most of the SCC causing failure has been on the outside diameter of long seam welded pipe at the edge of the weld. Defects at that location are known as "Toe-Cracks" Ginzel has developed an ultrasonic inspection technique that will detect both SCC colonies and toe cracks in long seam pipe. The main design objective for this research project was the selection and placement of ultrasonic transducers to combine weld, plate thickness and lamination inspection, along with SCC detection and sizing. Examination of sample pipe sections to demonstrate its success is reported. The primary stages for this research project are: �Assemble test equipment Establish test procedure System trials and data collection Evaluation of system performance and collected data Correlation of test data - Results

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She, Ruifeng, and Yanfeng Ouyang. Generalized Link-Cost Function and Network Design for Dedicated Truck-Platoon Lanes to Improve Energy, Pavement Sustainability, and Traffic Efficiency. Illinois Center for Transportation, 2021. http://dx.doi.org/10.36501/0197-9191/21-037.

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Recent development of autonomous and connected trucks (ACT) has provided the freight industry with the option of using truck platooning to improve fuel efficiency, traffic throughput, and safety. However, closely spaced and longitudinally aligned trucks impose frequent and concentrated loading on pavements, which often accelerates pavement deterioration and increases the life cycle costs for the highway agency. Also, effectiveness of truck platooning can be maximized only in dedicated lanes; and its benefits and costs need to be properly balanced between stakeholders. This paper proposes a network-design model to optimize (i) placement of dedicated truck-platoon lanes and toll price in a highway network, (ii) pooling and routing of ACT traffic from multiple origins and destinations to utilize these lanes, and (iii) configuration of truck platoons within these lanes (e.g., lateral displacements and vehicle separations). The problem is formulated as an integrated bi-level optimization model. The upper level makes decisions on converting existing highway lanes into dedicated platoon lanes, as well as setting user fees. The lower-level decisions are made by independent shippers regarding the choice of routes and use of platoon lanes vs. regular lanes; and they collectively determine truck traffic in all lanes. Link-cost functions for platoon lanes are obtained by simultaneously optimizing, through dynamic programming, pavement-rehabilitation activities and platoon configuration in the pavement's life cycle. A numerical case study is used to demonstrate the applicability and performance of the proposed model framework over the Illinois freeway system. It is shown that the freight traffic is effectively channelized on a few corridors of platoon lanes and, by setting proper user fees to cover pavement-rehabilitation costs, systemwide improvements for both freight shippers and highway agencies can be achieved.

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Philosoph-Hadas, Sonia, Peter Kaufman, Shimon Meir, and Abraham Halevy. Signal Transduction Pathway of Hormonal Action in Control and Regulation of the Gravitropic Response of Cut Flowering Stems during Storage and Transport. United States Department of Agriculture, 1999. http://dx.doi.org/10.32747/1999.7695838.bard.

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Original objectives: The basic goal of the present project was to increase our understanding of the cellular mechanisms operating during the gravitropic response of cut flowers, for solving their bending problem without affecting flower quality. Thus, several elements operating at the 3 levels o the gravity-induced signal transduction pathway, were proposed to be examined in snapdragon stems according to the following research goals: 1) Signaling: characterize the signal transduction pathway leading to the gravitropic response, regarding the involvement of [Ca2+]cyt as a mediator of IAA movement and sensitivity to auxin. 2) Transduction by plant hormones: a) Examine the involvement of auxin in the gravitropic response of flower stems with regard to: possible participation of auxin binding protein (ABP), auxin redistribution, auxin mechanism of action (activation of H+-ATPase) mediation by changes in [Ca2+]cyt and possible regulation of auxin-induced Ca2+ action b: calmodulin-activated or Ca2+-activated protein kinases (PK). b) Examine the involvement of ethylene in the gravitropic response of flower stems with regard to auxin-induced ethylene production and sensitivity of the tissue to ethylene. 3) Response: examine the effect of gravistimulation on invertase (associated with growth and elongation) activity and invertase gene expression. 4) Commercial practice: develop practical and simple treatments to prevent bending of cut flowers grown for export. Revisions: 1) Model systems: in addition to snapdragon (Antirrhinum majus L.), 3 other model shoe systems, consisting of oat (Avena sativa) pulvini, Ornithogalun 'Nova' cut flowers and Arabidopsis thaliana inflorescence, were targeted to confirm a more general mechanism for shoot gravitropism. 2 Research topics: the involvement of ABP, auxin action, PK and invertase in the gravitropic response of snapdragon stems could not be demonstrated. Alternatively, the involvement in the gravity signaling cascade of several other physiological mediators apart of [Ca2+]cyt such as: IP3, protein phosphorylation and actin cytoskeleton, was shown. Additional topics introduced: starch statolith reorientation, differential expression of early auxin responsive genes, and differential shoot growth. Background to the topic: The gravitropic bending response of flowering shoots occurring upon their horizontal placement during shipment exhibits a major horticultural problem. In spite of extensive studies in various aboveground organs, the gravitropic response was hardly investigated in flowering shoots. Being a complex multistep process that requires the participation of various cellular components acting in succession or in parallel, analysis of the negative gravitropic response of shoot includes investigation of signal transduction elements and various regulatory physiological mediators. Major achievements: 1) A correlative role for starch statoliths as gravireceptors in flowering shoot was initially established. 2) Differentially phosphorylated proteins and IP3 levels across the oat shoe pulvini, as well as a differential appearance of 2 early auxin-responsive genes in snapdragon stems were all detected within 5-30 minutes following gravistimulation. 3) Unlike in roots, involvement of actin cytoskeleton in early events of the gravitropic response of snapdragon shoots was established. 4) An asymmetric IAA distribution, followed by an asymmetric ethylene production across snapdragon stems was found following gravistimulation. 5) The gravity-induced differential growth in shoots of snapdragon was derived from initial shrinkage of the upper stem side and a subsequent elongation o the lower stem side. 6) Shoot bending could be successfully inhibited by Ca2+ antagonists (that serve as a basis for practical treatments), kinase and phosphatase inhibitors and actin-cytoskeleton modulators. All these agents did not affect vertical growth. The essential characterization of these key events and their sequence led us to the conclusion that blocking gravity perception may be the most powerful means to inhibit bending without hampering shoot and flower growth after harvest. Implications, scientific and agriculture: The innovative results of this project have provided some new insight in the basic understanding of gravitropism in flower stalks, that partially filled the gap in our knowledge, and established useful means for its control. Additionally, our analysis has advanced the understanding of important and fundamental physiological processes involved, thereby leading to new ideas for agriculture. Gravitropism has an important impact on agriculture, particularly for controlling the bending of various important agricultural products with economic value. So far, no safe control of the undesired bending problem of flower stalks has been established. Our results show for the first time that shoot bending of cut flowers can be inhibited without adverse effects by controlling the gravity perception step with Ca2+ antagonists and cytoskeleton modulators. Such a practical benefit resulting from this project is of great economic value for the floriculture industry.

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