Multiple Environments Research Articles

Migración de serverbox hacia un sistema de microservicios aplicando arquitectura vertical

Efficient data management is essential in public administration for the effective operation of municipal cadastral systems. In 2010, the Multifinality Cadastral Modernization Program was implemented, a partnership between the Puebla municipality government and Sistemas de Información Geográfica S.A. de C.V. (SIGSA), which included the ServerBox platform. Over time, the monolithic architecture of ServerBox showed limitations in maintenance, updates, and change deployment. This project hypothesizes that migrating ServerBox to a distributed microservices architecture, using a vertical approach, can overcome these challenges and improve operational areas of the system. The proposed design establishes a modular and scalable structure that facilitates system maintenance and evolution. The implementation includes the development of TagHelpers in ASP.NET Core to simplify HTML element creation and the use of snippets to streamline coding. Additionally, a JSON configuration file is defined to manage multiple deployment environments. This strategic approach to migrating ServerBox to a distributed and vertical architecture offers significant advantages in terms of scalability, maintenance, and software development efficiency, and can serve as a guide for similar projects in public administration.

Governing the Slovenian National Cancer Control Programme - Key Lessons Learnt

Abstract Issue Strategic documents addressing major public health concerns should extend beyond health sector. Cancer control is commonly perceived only as a health issue, thus involving diverse stakeholders is challenging. Description of the problem The inclusion of stakeholders within and beyond the health sector is crucial in the preparation, and through implementation of National Cancer Control Programmes (NCCP). Lessons learned on how to involve and maintain fruitful collaboration with diverse stakeholders in Slovenian NCCP are presented. Results Over the past 14 years Slovenia’s NCCP has built a reliable and reputable partnership with diverse stakeholders, a collaboration that continues to evolve. Efforts extend across multiple sectors, encompassing health, education, employment, research, environment, technology, and non-governmental organizations. NCCP has set up multistakeholder governance structures: an advisory board, board of experts, specialised expert groups, and a group of representatives of cancer hospitals. These groups engage a diverse range of experts and institutions nationwide. Whenever feasible, representatives of patient organizations are included. All these structures hold regular meetings, complemented by an annual event that convenes all stakeholders and also provides an invaluable platform for informal networking. To ensure seamless coordination of all activities, a dedicated team is essential. Our approach has evolved to embrace a dual leadership, comprising both a public health specialist and a clinical expert. Additionally, we benefit from the expertise of communication experts, who offer valuable insights into effectively reaching diverse audiences. Lessons Governing Slovenia’s NCCP by involving diverse stakeholders in planning and implementation activities has demonstrated its effectiveness. Furthermore, we are witnessing an increasing number of new stakeholders actively seeking out to participate in the NCCP. Key messages • Slovenia’s NCCP is recognized for its credibility and strategic approach. • Involving diverse stakeholders in cancer control endeavours has proven effective, fostering trust and partnerships.

Genetic loci associated with sorghum drought tolerance in multiple environments and their sensitivity to environmental covariables.

Climate change can limit yields of naturally resilient crops, like sorghum, challenging global food security. Agriculture under an erratic climate requires tapping into a reservoir of flexible adaptive loci that can lead to lasting yield stability under multiple abiotic stress conditions. Domesticated in the hot and dry regions of Africa, sorghum is considered a harsh crop, which is adapted to important stress factors closely related to climate change. To investigate the genetic basis of drought stress adaptation in sorghum, we used a multi-environment multi-locus genome-wide association study (MEML-GWAS) in a subset of a diverse sorghum association panel (SAP) phenotyped for performance both under well-watered and water stress conditions. We selected environments in Brazil that foreshadow agriculture where both drought and temperature stresses coincide as in many tropical agricultural frontiers. Drought reduced average grain yield (Gy) by up to 50% and also affected flowering time (Ft) and plant height (Ph). We found 15 markers associated with Gy on all sorghum chromosomes except for chromosomes 7 and 9, in addition to loci associated with phenology traits. Loci associated with Gy strongly interacted with the environment in a complex way, while loci associated with phenology traits were less affected by G × E. Studying environmental covariables potentially underpinning G × E, increases in relative humidity and evapotranspiration favored and disfavored grain yield, respectively. High temperatures influenced G × E and reduced sorghum yields, with a ~ 100kgha-1 average decrease in grain yield for each unit increase in maximum temperature between 29 and 38°C. Extreme G × E for sorghum stress resilience poses an additional challenge to breed crops for moving, erratic weather conditions.

Punjab Tar-1: A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) Released in Pakistan.

The development of new crop varieties with favorable features is a continuing effort. With the passage of time, a cultivated variety becomes subjected to various biotic and abiotic plant stresses. This article describes development of an innovative and imaginative long melon cultivar called "Punjab Tar-1."This article discusses creation of a novel and inventive long melon variety known as "Punjab Tar-1." Current long melon varieties in Pakistan are sensitive to climatic conditions and susceptible to pest and disease attack. A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) is released in Pakistan to address these current issues of long melon varieties A high yielding and early maturing variety of long melon “Punjab Tar-1” has been developed by Vegetable Research Institute, Faisalabad, Pakistan through mass selection. Plants were selected from an open pollinated indigenous source population with main emphasis on earliness, fruit shape, color and taste and yield. Selection intensity was 15% in 1st three selection cycles and 30% in subsequent four selection cycles whereas yield trials were started from 8th selection cycle. The fruit of this variety has a strong longitudinal rib that makes it difficult for eating by caterpillars. This variety has wide adaptability and exhibits stable yield across multiple environments. Notably, "Punjab Tar-1" contains 10.59 % crude protein and 1.08% crude fat content. Genetic uniformity and distinctiveness of this variety was confirmed through SSR polymorphism. Punjab Tar-1 variety has been approved by Punjab Seed Council in its meeting held on 2021 and was recommended for general cultivation in Punjab, Pakistan. Its certified seed is available for farmers at Vegetable Research Institute, Faisalabad. This newly approved variety will aid to save the precious foreign reserves by reducing vegetable seed import bill. In Pakistan, seed market of long melon is occupied by improved varieties. In multi-location evaluation, one said variety has exhibited high yield and stability than exotic germplasm. This is the first variety developed in Pakistan having good taste, early maturity, long shape, and high yield potential. DNA fingerprinting has further confirmed that it is distinct from local material, having novelty and diversity.

Semi-Supervised Online Continual Learning for 3D Object Detection in Mobile Robotics

Continual learning addresses the challenge of acquiring and retaining knowledge over time across multiple tasks and environments. Previous research primarily focuses on offline settings where models learn through increasing tasks from samples paired with ground truth annotations. In this work, we focus on an unsolved, challenging, yet practical scenario, specifically, the semi-supervised online continual learning in autonomous driving and mobile robotics. In our settings, models are tasked with learning new distributions from streaming unlabeled samples and performing 3D object detection as soon as the LiDAR point cloud arrives. Additionally, we conducted experiments on both the KITTI dataset, our newly built IUSL dataset and Canadian Adverse Driving Conditions (CADC) Dataset. The results indicate that our method achieves a balance between rapid adaptation and knowledge retention, showcasing its effectiveness in the dynamic and complex environment of autonomous driving and mobile robotics. The developed ROS packages and IUSL dataset will be publicly available at: https://github.com/npu-ius-lab/OCL3D.

Exploring Built Environment Visual Interactions: A SoftBIM Data-Driven Approach for a Database About the Outdoor View

Windows and glazed facades provide outdoor views, serving as vital sources of visual information that aid navigation and interaction within buildings. These views can trigger psychological and physiological responses, affecting individual well-being. However, optimizing outdoor view quality is challenging due to the complex interplay of factors influencing the building’s experience of vision. Managing the complexity of optimizing outdoor view quality within current digital frameworks for building design presents significant challenges. A key issue lies in the ambiguity of certain visual metrics, which are often difficult to translate into explicit descriptors of spatial configurations. Even when such metrics are available, their practical use as guiding tools in the design process is frequently obstructed by complex data interoperability procedures. These procedures are necessary to enable seamless data transfer across the multiple software environments involved in the design process. This study advocates for the softBIM paradigm, which optimizes workflows by embedding visual analysis results into target geometries. Supported by this process, the calculation of a metric to measure the impact of existing and planned visual obstructions on the vision of the targeted landmarks is proposed and analysed. This metric is specifically applied to assess the visual information incoming to the vertical facades of building envelopes, a context of application that denotes criteria of assessment different from the ones usually applied in the most established frameworks for visual analysis (e.g., isovist analysis). SoftBIM enables effective automation strategies to aid the metric computation and the processing of the results to implement seamless export and data implementation. The visual metric is built upon implementing the Ladybug suite and addresses the different limitations in the target-based visibility calculation supported by the tool.

Yr29 combined with QYr.nwafu-4BL.3 confers durable resistance to stripe rust in wheat cultivar Jing 411.

The combination of a QTL on chromosome arm 4BL and Yr29 provides durable resistance with no significant yield penalty. Wheat stripe rust or yellow rust (YR), caused by Puccinia striiformis f. sp. tritici (Pst), causes substantial yield reductions globally, but losses can be minimized by using resistance genes. Chinese wheat cultivar Jing 411 (J411) has continued to display an acceptable level of adult-plant resistance (APR) to YR in varied field conditions since its release in the 1990s. A recombinant inbred line (RIL) population comprising 187 lines developed from a cross of J411 and Kenong 9204 (KN9204) was evaluated in multiple environments to identify genomic regions carrying genes for YR resistance. A total of five quantitative trait loci (QTL) on chromosome arm 1BL, 3BS, 4BL, 6BS, and 7BL from J411 and two QTL on 3DS and 7DL from KN9204 were detected using inclusive composite interval mapping with the wheat 660K SNP array. QYr.nwafu-1BL.5 and QYr.nwafu-4BL.3 from J411 were robust and showed similar effects in all environments. QYr.nwafu-1BL.5 was likely the pleiotropic gene of Yr29/Lr46. QYr.nwafu-4BL.3 was located within a 1.0cM interval delimited by KASP markers AX-111609222 and AX-89755491. Based on haplotype analysis, Yr29 and QYr.nwafu-4BL.3 were identified as genetic components of quantitative resistance in a number of wheat cultivars. Moreover, RILs with Yr29 and QYr.nwafu-4BL.3 individually or when combined showed higher resistance to YR in rust nurseries compared with RILs without them, and there was no negative effect of their presence on agronomic traits under rust-free conditions. These results suggest that effective polymerization strategy is important for breeding high yielding and durable resistance cultivars.

Microstructured Reflective Coatings on Commodity Textiles for Passive Personal Cooling.

As the effects of climate change become more severe and widespread, maintaining personal thermal homeostasis becomes necessary for survival. In principle, advanced textiles and garments have the ability to leverage light absorption, transmission and/or reflection, in addition to straightforward convection, to heat or cool bodies in extreme temperature conditions. For cooling, in particular, surfaces adept at selectively reflecting or refracting high-energy incident light (200 nm-2.5 mm) from the sun while transmitting or emitting infrared light (8-13 mm) from radiant body heat boast the ability to maintain cooler body temperatures, even when exposed to direct sunlight and the open sky. Here, we present a strategy to transform common clothing into implements for passive personal cooling. As confirmed by Mie scattering calculations, cheap and biocompatible calcium carbonate and barium sulfate micro/nanoparticles are found to serve as suitable reflectors for radiative cooling. Finite-difference time domain simulations reveal, surprisingly, that higher reflectance is achieved with surface coatings containing these materials, as compared to extruded metamaterial fibers containing CaCO3 and BaSO4 particles embedded within a polymer matrix. A stepwise process involving photoinitiated chemical vapor deposition and ion-exchange driven crystal growth is used to create a lamellar composite coating comprised of alternating CaCO3 and BaSO4 nano/microparticle layers directly on the surface of common fabrics. A polyester poplin fabric coated in this manner shows a cooling ability of up to 8 °C compared to an uncoated sample, achieving a maximum cooling of 6 °C below ambient temperature. Wash and durability testing of the lamellar coating reveal no mechanical degradation and no evident attenuation in the material's performance, affirming its resilience and long-term effectiveness as a functional textile coating for personal cooling. We also assess the performance of our coated fabrics in multiple outdoor environments to conclude that we can achieve up to 3.4 °C of sub-ambient cooling in optically complex built environments.

Age trends of genetic parameters and genotype-by-environment interactions for growth traits of Eucalyptus urophylla clones in South-China.

Eucalyptus urophylla S.T. Blake, an important economic tree species, is widely cultivated as a raw material source for pulpwood, veneer plywood, and sawlog timber in southern China. As a tree in multiple environments, tree-breeding programs can assess genotype by environment (G×E) interactions and identify the suitable genotype for a specific environment. G×E interactions related to growth traits and soil factors have not been adequately studied for clones of Eucalyptus urophylla and its hybrids. To examine this important question, trials containing 20 clones of E. urophylla and its hybrids were established at three sites in southern China: Shankou (SK), Tiantang (TT), and Xiniujiao (XNJ). These sites each have different soil conditions but similar geographical and climatic conditions. With the data across nearly eight years, average phenotypic trends and broad sense repeatability (H2) were modeled, G×E interactions between clones and diverse soil environments were estimated, genetic gains of clones were calculated, and the adaptabilities of E. urophylla clones in different soil environments were compared. Average survival trends for clones tended to show a moderate decrease while growth traits tended to show sharp increases with age. At the same age, sites were ordered for average survival and growth traits as TT>SK>XNJ while H2 values for growth traits by site followed the basic order TT>SK>XNJ. The H2 values for growth traits at SK tended to increase at first, platform, and then smooth with age. The H2 values for growth traits at TT were high and stable across ages, and those at XNJ tended to undulate largely at a relatively low level across ages. Genetic correlations for growth traits between any pair of sites tended to increase at first and then decrease. A genetic correlation was strong between SK and TT, intermediate between SK and XNJ, and weak between TT and XNJ. It was concluded that: (1) clones tended to be adapted better to an environment with acidic and loamy soil with a clay content of about 45.6%, the soil depth from the surface to parent material about 1.5 m, and the previous vegetation of Eucalypts. (2) The G×E interactions between clones and sites are weaker if the environmental conditions between the sites are similar, and which are stronger if the environmental conditions between the sites are different. (3) The optimum selection age for clones ranged from 1.5 to 3.5 years old, while the optimum selection growth trait is individual tree volume.

Identification of Climate-Smart Bread Wheat (Triticum aestivum L.) Germplasm for Optimum Moisture Areas of Ethiopia

Ethiopia's Bread Wheat Breeding Program conducts annual multi-environment yield trials to develop advanced wheat genotypes for Ethiopian wheat cultivation, ensuring a steady supply of new and improved varieties to meet production and marketing challenges. The objective of this research was to assess potential yield and the interactions between genotype and environment in wheat across multiple environments, as every cultivar has a distinct response to soil and climate. The BLUP analysis reveals that the 22AA and 22KU trials in 2022, along with 21KU trials in 2021 yielded high grain production, indicating optimal testing locations for distinguishing bread wheat genotypes and agroecologies. The study found that seven out of sixteen trials exhibited a higher genetic variance for yield, indicating high genotype discriminating power, with estimates ranging from 0.043 to 0.989 for genetic variance, 0.084 to 1.147 for error variance, and 72.7 to 96.4 for heritability. EBW202471 and EBW202473 are stable genotypes with good yield performance across correlated locations, with EBW202471 showing the highest yield (4.98 t/ha) and Deka showing a lower yield (4.07 t/ha). Three wheat genotypes, EBW202471, EBW202472, and EBW202473, were found to be moderately resistant to moderately susceptible to stem and yellow rust among 20 wheat genotypes. Finally, the two genotypes, EBW202471 and EBW202473, were advanced to National Performance Trials to evaluate their performance alongside top genotypes from regional federal research centers and to be released as new varieties.

Joint Decoding Technique for Collision Resolution in Non-orthogonal Multiple Access Environment

Multiple access technologies have grown hand in hand from the first generation to the 5th Generation (5G) with both performance and quality improvement. Non-Orthogonal Multiple Access (NOMA) is the recent multiple access technology adopted in the 5G communication technology. Capacity requirements of wireless networks have grown to a large extent with the penetration of ultra-high-definition video transmission, Internet of Things (IoT), and virtual reality applications taking ground in the recent future. This paper develops the Physical Layer Network Coding (PNC) for collision resolution in a NOMA environment with two users. Traditionally NOMA uses Successive Interference Cancellation (SIC) for collision resolution. While additionally a decoding algorithm is added along with SIC to improve the performance of the collision resolution. MATLAB-based simulation is developed on the NOMA environment with two users using Viterbi coding, Low-Density Parity Check (LDPC), and Turbo coding. Performance parameters of Bit Error Rate (BER) and throughput are compared for these three algorithms. It is observed that the Turbo coding performed better among these three algorithms both in the BER and throughput. The BER obtained from the SIC- Turbo is found to be performing well with an increase of about 14% from the ordinary SIC implementation. The performance of the collision resolution has increased by 13% to 14% when joint decoding techniques are used and thus increasing the throughput of the NOMA paradigm.

A call to action to scale up research and clinical genomic data sharing.

Genomic data from millions of individuals have been generated worldwide to drive discovery and clinical impact in precision medicine. Lowering the barriers to using these data collectively is needed to equitably realize the benefits of the diversity and scale of population data. We examine the current landscape of global genomic data sharing, including the evolution of data sharing models from data aggregation through to data visiting, and for certain use cases, cross-cohort analysis using federated approaches across multiple environments. We highlight emerging examples of best practice relating to participant, patient and community engagement; evolution of technical standards, tools and infrastructure; and impact of research and health-care policy. We outline 12 actions we can all take together to scale up efforts to enable safe global data sharing and move beyond projects demonstrating feasibility to routinely cross-analysing research and clinical datasets, optimizing benefit.

Case study of simplified reverberation time measurement under multiple conditions using a sound level meter

Recent advancements in the computational capacity of sound level meters have facilitated the simultaneous recording of diverse calculation results and waveform recording data. Traditionally, reverberation time determination entailed manually adjusting a linear regression line to the reverberation decay curve derived from recorded sound levels, followed by reverberation time computation based on the gradient of said line. However, automated techniques have made reverberation time calculation via a sound level meter feasible. This paper discusses a case study evaluating the efficacy and considerations of simplified reverberation time measurements conducted across various conditions, encompassing scenarios with multiple sound sources and diverse indoor environments. The study leveraged recorded data from a sound level meter and employed automated methods simulated on a personal computer.

Person-Environment Fit and Socioeconomic Status in Medical School

Abstract Purpose This study examined the impact of socioeconomic status (SES) on medical education in the context of person-environment fit (PE fit) theory, and specifically focused on the medical school experiences of students from lower-SES backgrounds. Method A constructivist approach was used in this qualitative study of 48 medical students from 27 US medical schools, all of whom self-identified as first-generation college graduates and/or being from a lower-income background (30 were both). Semi-structured audio-only interviews were conducted with these demographically and geographically diverse students from November 2021 through April 2022. Themes were identified using open coding and content analysis software. Results Almost all, 44 of 48, interviews included themes related to PE fit. Medical students indicated three interacting domains in which PE fit is relevant for them: (1) school, (2) clinical, and (3) professional environments. Learners from lower-SES backgrounds describe struggling to navigate multiple environments that are unfamiliar, culturally complex, and both personally and financially costly. They also describe ways they are addressing gaps, generating positive changes, supporting underserved patients, and broadening the perspectives of peers and educators. Conclusions PE fit theory provides a lens to understand unique aspects of lower-SES medical student experiences, including navigation of professional identity formation. It is critical for medical schools, funders, peers, and professional communities to sustain learning environments that support the flourishing of medical students from lower-SES backgrounds. This support includes transferring the burden of addressing fit from individual learners and marginalized classes of learners to educational, clinical, and professional organizations.

N-doped carbon dots/SnS2 heterostructures for ultra-fast and sub-ppb-level detection of NO2 in multiple environments

Nitrogen dioxide (NO2) is one of the most common toxic gases, which not only impairs human health but also produces secondary pollutants induced by sunlight via associated photochemical reactions. Herein, we design a high-performance NO2 sensor based on the N-doped carbon dots/SnS2 (N-CDs/SnS2) heterostructure using density functional theory (DFT) calculations. The DFT results approve that the decoration of N-doped carbon dots (N-CDs) onto the SnS2 nanosheet enhances adsorption capacity and electron transportation compared with those of pure SnS2, significantly enhancing the sensing responses. In addition, these in-situ synthesized N-CDs onto SnS2 nanosheet leads to band alignment, thereby significantly improves conductivity and enhances transportation and storage properties of carriers via a synergistic interaction. Furthermore, employment of UV illumination significantly increases active adsorption sites and enhances response and recovery kinetics. As a result, the developed NO2 sensor achieves fast responses of a few seconds and a limit of detection down to sub-ppb-level with the help of UV illumination. It also shows good linearly, operated in both air and oxygen-free environments, at both room or low temperature (238 K) conditions. The developed multi-framework offers an efficient and precision detection of NO2 with ultrafast responses and ultralow concentrations in multiple environments.

Animal personality in multiple stressor environments: the evolutionary ecology of among-individual differences in responses to stressor suites.

Animal personality differences may have evolved as alternative strategies for negotiating multiple stressor landscapes. Indeed, ecologists are increasingly recognizing that interactions among multiple stressors can transform selective landscapes and behavioural and physiological responses to stress regimes. Yet, evaluating this hypothesis poses challenges, as most studies involving relationships between personality variation and the environment consider single stressors. Here, we review the literature to explore the theory and evidence that multiple stressor environments may mediate personality variation. We consider effects on evolution of personality variation, as influenced by life-history, energetic and behavioural trade-offs, and effects on phenotypic expression of personality traits. We then explore how personality variation may modulate behavioural and physiological responses to multiple stressors, and how differential responses may be affected by personality-dependent movement ecology and cognitive strategies. Among-individual differences in responses to multiple stressors are critical to elucidate, as multi-stress interactions may transform animal behavioural and physiological responses relative to those predicted under single stressor scenarios, and because among-individual variation comprises the basis for evolutionary shifts in stress responsiveness and population resiliency to global environmental change.

Identifying SSR/InDel loci related to tobacco bacterial wilt resistance using association mapping

Identifying molecular markers linked to tobacco bacterial wilt resistance is crucial for developing resistant tobacco varieties, thereby enhancing tobacco production and quality. In this two-year study, we evaluated the tobacco bacterial wilt disease index (TBWDI) in a mapping population of 78 tobacco accessions using SSR/InDel markers across 1377 marker loci. Two association models, GLM_Q and MLM_Q + Kinship, were used for association analysis. By considering multiple environments, selection thresholds, and phenotype values, we identified 19 reliable marker loci (P = 7.07-E05–4.98-E02) that explained 5.37–19.10 % of the phenotypic variation. Among these, we selected 11 accessions with high resistance to tobacco bacterial wilt, each containing at least one excellent locus. The models predicted five hybrid combinations whose offspring aggregated additional excellent loci. Additionally, one locus was identified during quantitative trait loci mapping, with accessions carrying this locus exhibiting significantly different TBWDI values from those without it, confirming its reliability and stability. A candidate gene (LOC107795335) was also identified downstream at 17.58 Kbp of the locus. Our study pinpointed reliable loci associated with bacterial wilt resistance, identified important materials for breeding resistant tobacco varieities, and predicted the best hybrid combinations for low disease indexes. The results of our study offer invaluable theoretical insights for breeding varieties with high and stable resistance.

Predicting and Prioritising Community Assembly: Learning Outcomes via Experiments.

Community assembly provides the foundation for applications in biodiversity conservation, climate change, invasion, restoration and synthetic ecology. However, predicting and prioritising assembly outcomes remains difficult. We address this challenge via a mechanism-free approach useful when little data or knowledge exist (LOVE; Learning Outcomes Via Experiments). We carry out assembly experiments ('actions', here, random combinations of species additions) potentially in multiple environments, wait, and measure abundance outcomes. We then train a model to predict outcomes of novel actions or prioritise actions that would yield the most desirable outcomes. Across 10 single- and multi-environment datasets, when trained on 89 randomly selected actions, LOVE predicts outcomes with 0.5%-3.4% mean error, and prioritises actions for maximising richness, maximising abundance, or removing unwanted species, with 94%-99% mean true positive rate and 10%-84% mean true negative rate across tasks. LOVE complements existing mechanism-first approaches for community ecology and may help address numerous applied challenges.

Collision-Free Tracking for a Mobile Robot Based on Purely Geometric Planning

A purely geometric planning method for a mobile robot in unknown environments is proposed to ensure robot collision avoidance against obstacles within the safety time interval while moving to the goal. The robot initially detects a point cloud of obstacles using a 2D LiDAR. Euclidean clustering is employed to classify the point cloud into point classes. The obstacle is then identified as a directed closed-loop rectangle for each point class. A relative orientation kd-tree is designed to store the vertices of the obstacles and to determine the obstacles to be considered in the obstacle avoidance algorithm. A velocity divider is introduced to obtain a linear convex area of possible obstacle avoidance velocities. Thus, linear planning is employed to calculate the optimal obstacle avoidance velocity for control. A virtual reference point method is proposed to solve the problem of an unreachable goal in a singular configuration. Experimental results show that the directed closed-loop rectangle and the relative orientation kd-tree facilitate the quick updating of required obstacle points with low-cost sensor equipment. The deterministic path for a given scenario can be obtained, demonstrating the reliability of geometric planning for both the obstacle avoidance velocity region and the optimal obstacle avoidance velocity. The proposed algorithm is finally validated for multiple obstacles and dynamic environments with moving obstacles.

Adaptive Dual-Channel Event-Triggered Fuzzy Control for Autonomous Underwater Vehicles With Multiple Obstacles Environment

Adaptive Dual-Channel Event-Triggered Fuzzy Control for Autonomous Underwater Vehicles With Multiple Obstacles Environment