This article introduces a simple and effective adaptive surrogate model to structural reliability analysis using deep neural network (DNN). In this paradigm, initial design of experiments (DoEs) are ...randomly selected from a given Monte Carlo Simulation (MCS) population to build the global approximate model of performance function (PF). More important points on the boundary of limit state function (LSF) and their vicinities are subsequently added relied on the surrogate model to enhance its accuracy without any complex techniques. A threshold is proposed to switch from a globally predicting model to a locally one for the approximation of LSF by eradicating previously used unimportant and noise points. Accordingly, the surrogate model becomes more precise for the MCS-based failure probability assessment with only a small number of experiments. Six numerical examples with highly nonlinear properties, various distributions of random variables and multiple failure modes, namely three benchmark ones regarding explicit mathematical PFs and the others relating to finite element method (FEM)-programmed truss structures under free vibration, are examined to validate the present approach.
•A DNN-based adaptive surrogate model for structural reliability analysis is proposed.•The performance and limit state functions are evaluated by the surrogate model.•A threshold is suggested to switch from a globally predicting model to a locally one.•The paradigm estimates the failure probability with only a small number of samples.•Six examples are investigated to confirm the reliability of the current methodology.
In this paper, we present a novel time-efficient tag identification protocol for active radio frequency identification (RFID) systems. Our protocol design is based on a conventional M-ary Detecting ...Tree (MDT) that divides contention tags into M subgroups and performs the identification in two phases: scanning and collecting. While the MDT protocol effectively eliminates redundant empty slots (i.e., slots without any tag responses), it requires two success slots (i.e., slots with exactly one tag's response) to identify one tag, raising concerns about potential identification delays. We introduce an innovative anti-collision protocol called Enhanced M-ary Detecting Tree (EMDT) to address this issue. The proposed EMDT switches from the scanning phase to the collecting phase when the estimated number of responding tags becomes smaller than a predefined threshold, which is found via theoretical analysis and has an optimal value of three. This adjustment allows the reader to typically require just one success slot for identifying each tag, thus significantly reducing the total time needed to identify all tags. The proposed phase-switching mechanism is backed by Zero-Estimation (ZE) for tag cardinality estimation and Manchester encoding for data transmission, both widely employed in RFID standards. Theoretical analysis and computer simulations are performed in different system settings, including ideal and non-ideal transmission channels, to validate the efficacy of the proposed protocol in comparison with conventional alternatives.
With the growing demand for high-speed connectivity and global coverage in future 6G networks, free-space optics (FSO)-based aerospace integrated networks, incorporating low Earth orbit (LEO) ...satellites, high-altitude platforms (HAP), and unmanned aerial vehicles (UAV), have recently attracted research efforts worldwide. Nevertheless, critical challenges on FSO links include weather conditions, atmospheric turbulence, and pointing misalignment. This paper addresses the design of error-control protocols for reliable FSO-based aerospace backhaul networks, when multiple UAVs are deployed as flying base stations (BSs). Specifically, we introduce a design proposal of a cooperative hybrid automatic repeat request (C-HARQ)-based frame allocation mechanism (FAM)/rate adaptation. The design proposal guarantees the latency fairness constraints among multiple UAVs experiencing varying turbulence channel conditions. An analytical channel model for HAP-aided relaying LEO satellite to the emerging UAV-mounted BS FSO links is provided. Moreover, we develop a comprehensive analytical framework taking into account the imperfect channel state information (CSI) to assess system performance metrics, including throughput, average frame delay, and energy efficiency. Numerical results confirm the effectiveness of our design proposal by comparing it with the conventional approach without FAM for various turbulence channel conditions and quality of service (QoS) requirements. Additionally, we offer a design guideline for the proper selection of parameters that can be helpful for the practical design of reliable FSO-based aerospace backhaul networks. Finally, the theoretical results are verified by Monte-Carlo simulations, along with some in-depth discussions.
•A single step optimization method for topology, size and shape of trusses is developed.•A discrete topology pseudo-area variable based on a penalty parameter is utilized.•A hybrid differential ...evolution and symbiotic organisms search is refined.•Eight examples are tested to verify the robustness of the suggested approach.•The present paradigm yields competitive high-quality outcomes against many other state-of-the-art algorithms.
In this article, a single step optimization approach for topology, size and shape of trusses subjected to multiple static and free vibration constraints is developed. For that aim, a topology pseudo-area variable based on a penalty parameter is discretely assigned by either 10−3 or 1 which represents the absence or attendance of a truss member. This helps to not only dodge the singularity of global stiffness matrix as resolving the equilibrium equation system, but also preserve the intact finite element model structure without unnecessarily and repeatedly done time-consuming performances in finite element analyses. The members’ cross-sectional area serves as discrete/continuous size variables, whilst nodes’ spatial coordinates are considered as continuous shape ones. The structural weight is minimized with multiple restrictions on kinematic stability, stress, displacement, natural frequency and Euler buckling loading. A hybrid differential evolution and symbiotic organisms search is employed as an optimizer and refined to tackle both continuous and discrete variables. Eight well-known examples for simultaneous topology, size and shape optimization of 2D and 3D trusses imposed by multiple static and free vibration constraints are tested to verify the reliability and the robustness of the suggested paradigm. The current method can result in competitive high-quality solutions against other state-of-the-art algorithms in most of the examined examples. In addition, the current approach can be also extended to apply for simultaneous topology, size and shape optimization of large-scale trusses in practice.
This paper presents a novel model order reduction (MOR)-based two-stage damage detection method for trusses employing time-series acceleration measured by limited sensors. In the first step, an ...acceleration-based strain energy indicator (ASEI) is newly proposed to evaluate the most doubtfully damaged candidates. Accordingly, the number of design variables defined in an inverse optimization problem of the second phase is reduced significantly. The location and severity of damaged members are then determined by minimizing an objective function with a newly added dynamic penalty parameter to achieve a faster convergence speed and better optimal solutions. Since acceleration signals are incompletely measured at limited sensors, the second-order Neumann series expansion (SNSE) is firstly employed to condense the proportionally damped trusses for inferring the unmeasured time–history information. An adaptive hybrid evolutionary firefly algorithm (AHEFA) is utilized to resolve the above inverse optimization problem. Four numerical examples of 2D and 3D trusses with various damage scenarios including noises are examined to demonstrate the reliability of the proposed methodology. Attained outcomes indicate that the suggested paradigm can reliably diagnose both multidamage sites and extents of trusses with only relatively short time histories and a few measurement sensors.
•A MOR-based two-step damage detection method for trusses by acceleration is proposed.•An ASEI is newly suggested to discover doubtfully damaged candidates.•A dynamic penalty parameter is used to improve convergence rate and solution quality.•Second-order Neumann series expansion is utilized to infer unmeasured acceleration.•Damage site and extent are detected with only short time domains and limited sensors.
•A novel evolutionary symbiotic organisms search algorithm is proposed.•The proposed method has novel hybrid mutations of differential evolution and symbiotic organisms search.•The present paradigm ...is of a better balance for both exploration and exploitation abilities.•The suggested approach is first validated on truss optimization with free vibration and transient behavior.•The developed algorithm dramatically ameliorates the convergence speed, yet still providing high-quality optimal solutions.
In this paper, an evolutionary symbiotic organisms search algorithm as a hybridization of differential evolution and symbiotic organisms search is developed for shape and size optimization of truss structures with free vibration and transient behavior under multiple constraints. For that aim, a mutation operator combined by two global differential evolution operators and a novel symbiotic organisms search operator is proposed to reinforce the exploration ability of the proposed algorithm. This newly suggested symbiotic organisms search operator is relied upon the symbiotic relationship in such a way that an arbitrary organism can receive benefits from both mutualisms and commensalisms. A threshold is automatically integrated into the mutation step to switch from the exploration capability to the exploitation one. In addition, an elitist scheme is applied to the selection phase to purify the most potential candidates for the next symbiotic ecosystem. Accordingly, the present algorithm can result in a high-quality optimal solution with a better convergence evolution. 26 mathematical functions and 7 well-known benchmark problems regarding size and shape truss optimization under multiple constraints are tested to verify the effectiveness of the proposed methodology. Obtained outcomes have indicated that the developed algorithm outperforms both original algorithms and many existing approaches in the literature. To further illustrate the ability of the proposed paradigm, two among the above five examples under transient excitations with strength, displacement, and buckling constraints are then optimized.
This letter addresses the resource allocation issue for hybrid free-space optics (FSO)/radio frequency (RF)-based satellite-assisted multiple users. Specifically, we present the rate adaptation-aided ...data frame allocation design for hybrid FSO/RF satellite-assisted multiple unmanned aerial vehicles (UAVs). The considered allocation scheme ensures latency fairness among UAVs serving as flying base stations (BSs). Numerical results confirm the effectiveness of the proposed solution over the state-of-the-art. Moreover, we investigate the feasibility of a case study over the Japan networks using practical SpaceX’s Starlink satellite constellation.
Although many investigations on phytochemicals in rice plant parts and root exudates have been conducted, information on the chemical profile of essential oil (EO) and potent biological activities ...has been limited. In this study, chemical compositions of rice leaf EO and in vitro biological activities were investigated. From 1.5 kg of fresh rice leaves, an amount of 20 mg EO was obtained by distillation and analyzed by gas chromatography-mass spectrometry (GC-MS), electrospray ionization (ESI), and atmospheric pressure chemical ionization (APCI) to reveal the presence of twelve volatile constituents, of which methyl ricinoleate (27.86%) was the principal compound, followed by palmitic acid (17.34%), and linolenic acid (11.16%), while 2-pentadecanone was the least (2.13%). Two phytoalexin momilactones A and B were first time identified in EO using ultra-performance liquid chromatography coupled with electrospray mass spectrometry (UPLC/ESI-MS) (9.80 and 4.93 ng/g fresh weight, respectively), which accounted for 7.35% and 3.70% of the EO, respectively. The assays of DPPH (IC
= 73.1 µg/mL), ABTS (IC
= 198.3 µg/mL), FRAP (IC
= 700.8 µg/mL) and β-carotene oxidation (LPI = 79%) revealed that EO possessed an excellent antioxidant activity. The xanthine oxidase assay indicated that the anti-hyperuricemia potential was in a moderate level (IC
= 526 µg/mL) as compared with the standard allopurinol. The EO exerted potent inhibition on growth of
, and two noxious weeds
, and
, but in contrast, the growth of rice seedlings was promoted. Among the examined plants, the growth of the
root was the most inhibited, proposing that constituents found in EO may have potential for the control of the problematic paddy weed
. It was found that the EO of rice leaves contained rich phytochemicals, which were potent in antioxidants and gout treatment, as well as weed management. Findings of this study highlighted the potential value of rice leaves, which may provide extra benefits for rice farmers.
The study aimed to evaluate the role of magnetic resonance imaging (MRI) in differentiating between primary benign and malignant soft tissue tumors (STTs).
The study was carried out on 110 patients ...with histopathological diagnoses of STTs. All patients underwent routine MRI before surgery/biopsy at Viet Duc University Hospital or Vietnam National Cancer Hospital, Hanoi, Vietnam, from January 2020 to October 2022. Data on preoperative MRI as well as the clinical features and pathological results of the patients were collected retrospectively. Univariate and multivariate linear regression were used to analyze the relationship between imaging, clinical parameters, and the ability to differentiate malignant from benign STTs.
Among 110 patients (59 men and 51 women), 66 had benign tumors and 44 had malignant tumors. The qualitative values that were significant in distinguishing between benign and malignant STTs were hypointensity on T1-weighted images (T1W; p<0.001), hypointensity on T2-weighted images (T2W; p=0.003), cysts (p=0.003)), necrosis (p<0.001), fibrosis (p=0.023), hemorrhage (p<0.001), lobulated margin (p<0.001), ill-defined border (p<0.001), peritumoral edema (p<0.001), vascular involvement (p<0.001), and heterogeneous enhancement (p<0.001). Regarding quantitative values, age (p=0.009), size (p<0.001), T1W signal quantification value (p=0.002), and T2W signal quantification value (p=0.007) showed statistically significant differences between benign and malignant tumors. Multivariate linear regression analysis showed that the combination of peritumoral edema and heterogeneous enhancement was the most valuable in the differential diagnosis of malignant tumors from benign tumors.
MRI is valuable in discriminating between malignant and benign STTs. The presence of cysts, necrosis, hemorrhage, lobulated margin, ill-defined border, peritumoral edema, heterogeneous enhancement, vascular involvement, and T2W hypointensity is suggestive of malignant lesions, especially signs of peritumoral edema and heterogeneous enhancement. Advanced age and large tumor size are also suggestive of soft tissue sarcomas.
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