Use of Computer Simulation to Optimize UAV Swarm Flying

Hierarchical mission replanning for multiple UAV formations performing tasks in dynamic situation

Background: The health system transformation plan has been implemented since 2014, and one of its goals is the reduction of cesarean rate to 25%-30%. The present study aimed to assess the rate of cesarean delivery and vaginal delivery before and after the implementation of the health system reform plan in Lorestan, Iran. Materials and Methods: This descriptive study was conducted in 2020. The research population included all the women who had given birth in one of the public hospitals of Lorestan province during 2011-2016. The sampling method was the census, which was based on the statistics of the vice-chancellor of treatment at Lorestan University of Medical Sciences. After data collection, they were analyzed using descriptive statistics. Results: The results of the study demonstrated that contrary to expectations, the cesarean section overall rate increased by about 3.4% after the implementation of the health system transformation plan, compared to before the implementation of this plan. It is worth noting that in some hospitals, including Khorramabad Asali Hospital, Khorramabad Social Security Hospital, and Broujerd Kowsar Hospital, the rate of cesarean section increased by 4.6%, 6.5%, and 5.9%, respectively, after the implementation of the health system transformation plan. Conclusion: It seems that according to the rate of cesarean delivery in this province that is higher than standard and the ineffectiveness of the health system transformation plan in this field, more efforts should be made with the use of extensive programs in order to increase the awareness and culturalization of the society.

Birds fly in formation to benefit from the upwash wake vortices created by their peer leader. Similar strategies can be employed on aircraft for fuel saving or for range extension. However, further understanding of wake vortices in the near field and mid field is needed for close formation flight (< 10 wingspans). This paper introduces a new method for wake vortex detection using small UAV formation. A NonLinear Dynamic Inversion (NLDI) based formation control law is adapted to the WVU Phastball UAV platform. The designed controller showed good tracking performance during close formation flight (5-10 wingspans) with typical errors of less than 3 meters during straight legs. Then, multiple sensor measurements from leader-follower UAV formation flights were used for the wake vortex detection, including angle of attack, angle of sideslip, accelerometers, and gyros. The collected flight data showed the feasibility of using UAV formation for the wake encounter detection.

During an earthquake, buildings which are vulnerable to seismic loads will be damaged, resulting in property loss and the potential for casualties. To reduce loss of life and injury, the relationship between earthquake-induced building failure and injury severity and distribution needs to be clarified. To this end, a methodology and a series of data collection forms were developed to collect pertinent data for post-event analysis and to provide a basis for structural triage in the field shortly following an earthquake for search and rescue purposes. The forms were developed in four steps: (1) identifying the variables which affect the outcome of an occupant in a damaged building; (2) classifying the variables into three levels of priority for data collection; (3) designing the forms; and (4) applying the forms to damaged buildings from past earthquakes. These forms represent a significant departure from existing forms in that they consider both casualties and building damage jointly in a consistent format. This paper describes the first two steps of the development process; a companion paper outlines the latter components.

This paper aims to achieve the goal of path planning and task assignment through cooperative control of UAV formation. In the process of research, a cooperative task assignment model for UAVs is established, and an obstacle environment model is constructed. The improved ant colony algorithm is used to optimize the path of multiple UAVs. Combined with Hungarian algorithm, task assignment for multi UAV formation is carried out. By designing the effective constraints, the evaluation function of two index functions is established by allocating the weights of the path cost and fire assignment value. Finally, through the GUI function of MATLAB software, a user independent UAV formation task assignment simulation platform is developed. Simulation results show the effectiveness of the proposed method.

A modified adaptive formation of UAV swarm by pigeon flock behavior within local visual field

This paper studies the problem of multiple fixed-wing UAVs coordination Standoff tracking of target, and proposes a dual-virtual structure UAV formation Standoff tracking method. Firstly, a dual-virtual structure is designed to solve the problem of formation trajectory guidance and formation control in target tracking by designing the functions and algorithms of two virtual UAVs. Secondly, we propose that motion parameter group to represent the process of UAV formation tracking target, and the phase coordination problem between UAVs is converted into the setting of phase factor in the parameter group, which simplifies the complexity of the algorithm design. Then the formation tracking control law is given based on the consistency algorithm and the stability of the system is proved. Finally, the situation that UAV formation tracking a maneuvering target is simulated and the simulation results verify the validity of the algorithm.KeywordsMulti-UAV formationStandoff trackingDual virtual structureMotion parameter groupConsensus algorithm

Knowledge map and forecast of digital twin in the construction industry: State-of-the-art review using scientometric analysis

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality and morbidity among US adults, including recurrent emergency department (ED) visits and unplanned hospital admissions. Despite this, the transition of care (TOC) from the inpatient to outpatient setting remains under-studied. The objectives of the Reduce Respiratory Emergent Visits using Implementation Science Interventions Tailored to Setting (Reduce REVISITS) study are to conduct contextual assessments to inform implementation plans for COPD TOC interventions, conduct a cluster randomized trial evaluating implementation over 1 year of COPD TOC bundles, and monitor sustainment of implementation over a 2-year period across 20 sites. This pragmatic, multisite study uses a hybrid type II effectiveness-implementation design to evaluate clinical and implementation outcomes of COPD TOC programs across 20 sites. Sites are cluster-randomized to 1 of 4 intervention groups, varying by program delivery method (in-person vs virtual) and implementation strategy (mentored implementation with or without co-design). Sites select evidence-based interventions they wish to incorporate into their COPD TOC program and are randomized to in-person or virtual delivery. During the 1-year active implementation period of the study, assigned mentors will meet monthly with sites (for a total of 12 sessions) to enable on-the-ground troubleshooting of site-specific difficulties with TOC interventions. The primary effectiveness outcome for this study will be COPD-specific acute health care use, defined as a composite of all ED visits and hospitalizations within 30 days of index hospitalization for a COPD exacerbation. The primary implementation outcome will be reach, defined as the proportion of patients receiving their assigned TOC interventions (the whole bundle). As of August 2025, 21 sites completed the contextual assessments and developed site-specific implementation plans. Publication of the qualitative data from this pre-implementation phase is anticipated in December 2025. Site randomization is complete; sites randomized to co-design have completed 3 sessions. Baseline data collection on use is complete. Implementation-year data collection on use is nearly complete. Year 1 and 2 post-implementation-phase data collection on use is ongoing. Quantitative data analyses of the baseline and implementation-phase reports are nearly complete. Manuscript submission for the primary implementation-phase manuscript is anticipated for December 2025. Manuscript submission for the implementation-sustainment analyses are anticipated for September 2026. Qualitative data collection for year 1 of the post-implementation phase is complete, and analysis is under way. Qualitative data collection for year 2 began in August 2025. The Reduce REVISITS study will use novel integrated implementation science and human-centered design methodology to investigate bundles of effective COPD TOC interventions with the goal of reducing COPD hospital revisits. The study will evaluate evidence-based programs for effectiveness and implementation across a wide variety of health care sites to ultimately improve outcomes in this high-risk patient population. ClinicalTrials.gov NCT05568043; https://clinicaltrials.gov/study/NCT05568043. DERR1-10.2196/82043.

The consistent delivery of effective evidence into nursing home practice has been shown to enhance quality of care and residents' outcomes. Pragmatic trials enable the evaluation of efficacious interventions in a real-world context, including care of residents living with Alzheimer's Disease and Related Dementias (ADRD). Yet, there are limited pragmatic trials conducted in nursing homes and even less evidence on the strategies to successfully conduct such research in this setting. To identify the lessons learned from a pragmatic trial and provide recommendations for future successful studies in United States (US) nursing homes. Drawing on a case example of a recently completed pragmatic trial, we used the Comparative Effectiveness Research Framework to guide the thematic analysis of study documentation to identify challenges, strategies used, and recommendations for future pragmatic trials in US nursing homes. Five themes emerged from this case example: 1) establish and sustain community partner collaboration, 2) context analysis and appropriate implementation plan, 3) study adaptability, 4) data collection in a 'real world' setting, and 5) broad dissemination. Within each theme, strategies we used, challenges we encountered, and recommendations for future studies were identified. Examples of recommendations include empowering community partners to be engaged in the research, co-design with community partners, account for the dynamic nature of the nursing home setting, and maintain communication with organization leaders. Successful completion of pragmatic trials in US nursing homes requires active engagement of community partners throughout the research process. The emergent lessons learned and recommendations highlight the complex nature of this care setting, the need to be proactive in implementation planning, and the pivotal role of community partners. Moving forward, there is a need for greater emphasis on systematically sharing experiences more broadly to advance the science of pragmatic trials in US nursing homes.

In Korea (Republic of), the paradigm of waste recycling management will be changed and activated in 2018. Until 2017, the recycling of waste is only permitted for 69 types of waste and the rest of wastes cannot permit to recycle under the Waste Management Act. In order to enhance recycling activities, it should be amended the Waste Management Act to recycle for all types of waste. A new implementation plan is introduced to shift the paradigm of recycling system from the recycling method by permission list, in which certain items among all wastes can be recycling, to the recycling method by restriction list, in which all wastes can be recycled if wastes do not have any hazardous characteristics. Until now, there are considered only three types of hazardous waste characteristics under the Waste Management Act. That was the reason why 69 types of waste can be recycled until now. In the new advanced plan, six types of hazardous characteristics were added in the Waste Management Act to expand recycling to all types of waste. Hence, nine types of hazardous characteristics were controlled under the amended Waste Management Act. Even though there are any hazardous characteristics in waste, all types of waste can be recycled under the amended Waste Management Act if the hazardous characteristics were removed or stabilized. Almost all wastes can be recycled in accordance with the recycling type (R-code), and the recycling standards for each R-code will be specified in the amended Waste Management Act.

This paper presents a three-dimensional (3D) piecewise guidance scheme for multiple UAVs) guaranteeing simultaneous arrival even under the field-of-view (FOV) constraint. The guidance law does not require to consider the estimation of the time-to-go and can be divided into two stages: cooperative stage and proportional navigation guidance (PNG) stage. In the cooperative stage, a decentralized consensus control approach is proposed for multi-UAV systems and does not rely on global information about the communication topography. Moreover, the neighbors’ new auxiliary states are introduced to ensure the states achieving consensus under FOV constrain. The guidance strategy transfers to the PNG stage while the UAV formation is close enough to the target and the simultaneous arrival to hit the target is guaranteed for UAVs via the PNG guidance law. Numerical simulation results demonstrate the effectiveness of the proposed cooperative guidance law.

A new approach to the optimal formation problem is proposed in the sense of the passive target tracking using time difference of arrival (TDOA) data obtained by cooperative UAVs. In most existing methods, under the assumption that arbitrary unbiased and efficient estimator could be designed for target tracking, the objective function for the information maximizing formation is defined without particular consideration of the filter structure used for passive target tracking. However, this approach might be restrictive because the overall performance of passive target tracking depend on the UAV formation and the filter structure as well. To overcome this limitation, the proposed technique takes account of the practical tracking filter structure and its properties in the problem. To do this, it is firstly shown that the amount of moving target information is expressed in terms of the variance of UAVs' angular positions. In order to guarantee the satisfactory target tracking performance even when the UAVs-target relative geometry is time-varying, the optimal formation problem is formulated as finding the maximizing solution of the objective function in worst-case. Through the simulations, the effectiveness of the proposed scheme is demonstrated.

The active disturbance rejection control technology was designed to solve the problem of formation maintenance in UAV cooperative formation flight, so that the response process had good dynamic quality and small static error. This paper first established a UAV formation flying model based on relative error in a two-dimensional plane. On this basis, the tracking differentiator, the extended state observer and the nonlinear state feedback controller were designed. The simulation results showed that the active disturbance rejection controller designed has good control performance and could realize the mission of maintaining the UAV with high precision.

This works develops a novel hierarchical algorithm for task assignment (TA), coordination and communication of multiple UAVs engaging multiple targets and conceives an ad-hoc routing algorithm for synchronization of target lists utilizing a distributed computing topology. Assuming limited communication bandwidth and range, coordination of UAV motion is achieved by implementing a simple behavioral flocking algorithm utilizing a tree topology for target list routing. The TA algorithm is based on a graph-theoretic approach, in which a node locates all the detectable targets, identifies them and computes its distance to each target. The node then produces an attack plan that minimizes the sum of distances of the UAVs in the subtree of a given node to the targets. Simulation experiments show that the combination of flocking and TA algorithms gives the best performance. Clear-cut advantages of the TA algorithm are shown to exist in cases where the hit probability tends to one. An improvement of efficiency, representing the ratio between killed targets and the number of missile launches, is obtained for larger numbers of UAVs only if the engagement times are long enough, utilizing the improved coverage achieved by more UAVs.