Aging effect and test-retest reliability of the sinusoidal harmonic acceleration test and velocity step test using nanotorque rotatory chair

Introduction:Rotatory chair testing has been used to evaluate horizontal canal function.Frequently used tests include sinusoidal harmonic acceleration test(SHAT)and velocity step test(VST).Objectives:Assessment of age effect on the SHAT and VST and assessment of test-retest reliability of the parameters of those two tests.Methods:A prospective study was performed on 100 subjects with no ear or vestibular complaints and normal vestibular evaluation.They were divided into two groups;Group A:below 50 years of age and Group B:50 years of age or above.SHAT was presented at frequencies 0.02,0.04,0.08,0.16,0.32,0.64 Hz with a peak velocity of 60°/s.VST was performed using a maximum velocity of 100°/s with acceleration and deceleration of 200°/s2.Thirty subjects were tested twice to assess reliability.Results:Study participants ranged in age from 20 to 67 years.Regarding group A,the mean age was30.92±7.31 and 55.36±4.61 for group B.No significant differences were found in SHAT parameters between the two groups.As well,there was no significant difference in VST per-rotatory time constant,however,post-rotatory time constant was significantly longer for Group B(P value<0.05).Intraclass correlation coefficient(ICC)values showed moderate to good reliability(ICC 0.5800.818)for SHAT parameters for the lower frequencies and indicated moderate reliability for VST time constant(ICC 0.5090.652).Conclusions:Age has no significant effect on the parameters of SHAT and VST.Test-retest reliability is generally good for both tests.

Test-retest reliability of the Mini Nutritional Assessment–Short Form(MNA-SF)in older patients undergoing cardiac rehabilitation

Malnutrition is described as a state of insufficient intake of energy,protein and other nutrients leading to changes in body composition(weight loss,reduced fat-free mass)as well as adverse functional and clinical outcomes.[1]Depending on the assessments and definition used,the prevalence in older patients ranges between 12%in communitydwelling adults to 60%of patients in geriatric care facilities.[2–5]Older populations are at high risk of nutritional deficiencies because of risk factors such as multimorbidity,polypharmacy,cognitive and physical decline,poor appetite,depressive syndromes and socioeconomic changes.[4,6].

Test-Retest Reliability, Convergent Validity and Practice Effects of the RBANS in a Memory Clinic Setting: A Pilot Study

This pilot study examined the psychometric properties and clinical utility of a brief neuropsychological instrument (Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The test-retest reliability, practice effects and convergent validity of RBANS were examined in participants without objective cognitive impairment. The tests were administered at two time points at approximately a two weeks’ interval, with 30 cognitively intact participants with a mean age of 63.3 ± 5.8 years. Adequate test-retest reliabilities were found for RBANS subtests, index and total scale scores with significant gain scores in immediate memory and visuospatial function. The RBANS showed good convergent validity and the RBANS supplemented with executive and language measures (Colour Trails Test and 30-item modified Boston Naming Test, respectively) demonstrated excellent convergent validity with a formal neuropsychological battery. This pilot study has provided the preliminary evidence of reliability and convergent validity of the RBANS. Additionally, it also provides insight on the practice effects so that clinicians may assess significant changes in RBANS subtests and domain indexes for clinical practice.

Test-Retest Reliability of Sensory Evoked Potentials in Low-Functioning Autism: A Case Report

Sensory abnormalities are common in individuals with autism spectrum disorders (ASD) but are often difficult to assess using standard behavioral methods. Evoked potentials provide objective, non-invasive electrophysiological measures of neural sensory processing that could be useful for clinical and investigative studies of individuals with low-functioning autism who are unable to perform behavioral testing. Despite increased use, the reliability of sensory evoked potentials has not been established for individuals with low-functioning autism. Establishing reliability is important for validating the utility of sensory evoked potentials. In this study, we explored the feasibility of assessing the test-retest reliability of sensory evoked potentials using repeat recordings, acquired over 2.5- and 6-month intervals, from a minimally verbal adult with low-functioning autism. Repeat auditory and visual evoked potential recordings showed high test-retest reliability, with cross-correlation coefficients ≥ 0.80. This case demonstrates the feasibility of establishing test-retest reliability for individuals with low-functioning autism and supports the utility of sensory evoked potentials in clinical and investigative ASD studies.

The Test-Retest Reliability and Minimal Detectable Change of the Balance Error Scoring System

Context： Balance is an important aspect of sports performance, which can be impaired following MHI （minor head injury） The BESS （balance error scoring system） is a tool commonly used for assessment of post-MHI recovery. Objective： This study aimed to ascertain test-retest reliability and minimal detectable change of the BESS in order to ensurem that it had appropriate clinical levels of reliability and sensitivity. Design： Test-retest reliability. Setting： University indoor sport facility. Participants： N = 36 sub-elite athletes. Interventions： The BESS was undertaken by the participants on two separate testing sessions, 1 week apart. Main Outcome Measures： Test-retest reliability and minimal detectable change. Results： Strong test-retest reliability of the total BESS score was identified （1CC （intraclass correlation coefficients） = 0.784） with a MDC （minimal detectable change） of 6-10 error points, dependent on confidence interval used. Conclusions： The strong reliability score and the relatively low MDC when using conservative measures would recommend the use of BESS in post-MHI assessment of young academy-level athletes. However, more research is required to further determine BESS MDC in both sub-elite and elite groups of athletic performers so as to provide clinicians with an accurate guideline regarding whether an athlete is presenting with post-MHI balance impairment.

System Reliability Analysis Method Based on T-S FTA and HE-BN

For high-reliability systems in military,aerospace,and railway fields,the challenges of reliability analysis lie in dealing with unclear failure mechanisms,complex fault relationships,lack of fault data,and uncertainty of fault states.To overcome these problems,this paper proposes a reliability analysismethod based on T-S fault tree analysis(T-S FTA)and Hyper-ellipsoidal Bayesian network(HE-BN).The method describes the connection between the various systemfault events by T-S fuzzy gates and translates them into a Bayesian network(BN)model.Combining the advantages of T-S fault tree modeling with the advantages of Bayesian network computation,a reliability modeling method is proposed that can fully reflect the fault characteristics of complex systems.Experts describe the degree of failure of the event in the form of interval numbers.The knowledge and experience of experts are fused with the D-S evidence theory to obtain the initial failure probability interval of the BN root node.Then,the Hyper-ellipsoidal model(HM)constrains the initial failure probability interval and constructs a HE-BN for the system.A reliability analysismethod is proposed to solve the problem of insufficient failure data and uncertainty in the degree of failure.The failure probability of the system is further calculated and the key components that affect the system’s reliability are identified.The proposedmethod accounts for the uncertainty and incompleteness of the failure data in complex multi-state systems and establishes an easily computable reliability model that fully reflects the characteristics of complex faults and accurately identifies system weaknesses.The feasibility and accuracy of the method are further verified by conducting case studies.

Belief reliability:a scientific exploration of reliability engineering

This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability.Beginning with the origin of reliability engineering,the problems of present theories for reliability engineering are summarized as a query,a dilemma,and a puzzle.Then,through philosophical reflection,we introduce the theoretical solutions given by belief reliability theory,including scientific principles,basic equations,reliability science experiments,and mathematical measures.The basic methods and technologies of belief reliability,namely,belief reliability analysis,function-oriented belief reliability design,belief reliability evaluation,and several newly developed methods and technologies are sequentially elaborated and overviewed.Based on the above investigations,we summarize the significance of belief reliability theory and make some prospects about future research,aiming to promote the development of reliability science and engineering.

On the relationship between imprint and reliability in Hf_(0.5)Zr_(0.5)O_(2) based ferroelectric random access memory

The detrimental effect of imprint,which can cause misreading problem,has hindered the application of ferroelectric HfO_(2).In this work,we present results of a comprehensive reliability evaluation of Hf_(0.5)Zr_(0.5)O_(2)-based ferroelectric random access memory.The influence of imprint on the retention and endurance is demonstrated.Furthermore,a solution in circuity is pro-posed to effectively solve the misreading problem caused by imprint.

Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

1 Summary With the advancement of science and technology,complex engineering structures are widely used in extreme environments[1].In equipment service,many uncertainty factors significantly affect safety and reliability[2–5].Therefore,ensuring high reliability of structures has become an important research direction in engineering design.At the same time,the importance of equipment health management of complex engineering structures is becoming increasingly prominent[6–8].Computer-aided uncertainty modeling and reliability assessment have become key tools,and finite element simulation and algorithmic innovation play a key role in the reliability analysis of complex equipment[9,10].These techniques can accurately simulate stress and damage accumulation under various operating environments,providing engineers with important decision support and optimization solutions.

Interrater Reliability Estimation via Maximum Likelihood for Gwet’s Chance Agreement Model

Interrater reliability (IRR) statistics, like Cohen’s kappa, measure agreement between raters beyond what is expected by chance when classifying items into categories. While Cohen’s kappa has been widely used, it has several limitations, prompting development of Gwet’s agreement statistic, an alternative “kappa”statistic which models chance agreement via an “occasional guessing” model. However, we show that Gwet’s formula for estimating the proportion of agreement due to chance is itself biased for intermediate levels of agreement, despite overcoming limitations of Cohen’s kappa at high and low agreement levels. We derive a maximum likelihood estimator for the occasional guessing model that yields an unbiased estimator of the IRR, which we call the maximum likelihood kappa (κML). The key result is that the chance agreement probability under the occasional guessing model is simply equal to the observed rate of disagreement between raters. The κMLstatistic provides a theoretically principled approach to quantifying IRR that addresses limitations of previous κcoefficients. Given the widespread use of IRR measures, having an unbiased estimator is important for reliable inference across domains where rater judgments are analyzed.

Efficient slope reliability and sensitivity analysis using quantile-based first-order second-moment method

This paper introduces a novel approach for parameter sensitivity evaluation and efficient slope reliability analysis based on quantile-based first-order second-moment method(QFOSM).The core principles of the QFOSM are elucidated geometrically from the perspective of expanding ellipsoids.Based on this geometric interpretation,the QFOSM is further extended to estimate sensitivity indices and assess the significance of various uncertain parameters involved in the slope system.The proposed method has the advantage of computational simplicity,akin to the conventional first-order second-moment method(FOSM),while providing estimation accuracy close to that of the first-order reliability method(FORM).Its performance is demonstrated with a numerical example and three slope examples.The results show that the proposed method can efficiently estimate the slope reliability and simultaneously evaluate the sensitivity of the uncertain parameters.The proposed method does not involve complex optimization or iteration required by the FORM.It can provide a valuable complement to the existing approximate reliability analysis methods,offering rapid sensitivity evaluation and slope reliability analysis.

Ultra Reliable Load-Aware Connection Management(LACM)Algorithm in WIA-FA Systems

The increasing demand for industrial automation and intelligence has put forward higher requirements for the reliability of industrial wireless communication technology.As an international standard based on 802.11,Wireless networks for Industrial Automation-Factory Automation(WIA-FA)greatly improves the reliability in factory automation scenarios by Time Division Multiple Access(TDMA).However,in ultra-dense WIA-FA networks with mobile users,the basic connection management mechanism is inefficient.Most of the handover and resource management algorithms are all based on frequency division multiplexing,not suitable for the TDMA in the WIA-FA network.Therefore,we propose Load-aware Connection Management(LACM)algorithm to adjust the linkage and balance the load of access devices to avoid blocking and improve the reliability of the system.And then we simulate the algorithm to find the optimal settings of the parameters.After comparing with other existing algorithms,the result of the simulation proves that LACM is more efficient in reliability and maintains high reliability of more than 99.8%even in the ultra-dense moving scenario with 1500 field devices.Besides,this algorithm ensures that only a few signaling exchanges are required to ensure load bal-ancing,which is no more than 5 times,and less than half of the best state-of-the-art algorithm.

Saddlepoint Approximation Method in Reliability Analysis:A Review

The escalating need for reliability analysis(RA)and reliability-based design optimization(RBDO)within engineering challenges has prompted the advancement of saddlepoint approximationmethods(SAM)tailored for such problems.This article offers a detailed overview of the general SAM and summarizes the method characteristics first.Subsequently,recent enhancements in the SAM theoretical framework are assessed.Notably,the mean value first-order saddlepoint approximation(MVFOSA)bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation(MVSOSA);the latter serves as an auxiliary approach to the former.Their distinction is rooted in the varying expansion orders of the performance function as implemented through the Taylor method.Both the saddlepoint approximation and third-moment(SATM)and saddlepoint approximation and fourth-moment(SAFM)strategies model the cumulant generating function(CGF)by leveraging the initial random moments of the function.Although their optimal application domains diverge,each method consistently ensures superior relative precision,enhanced efficiency,and sustained stability.Every method elucidated is exemplified through pertinent RA or RBDO scenarios.By juxtaposing them against alternative strategies,the efficacy of these methods becomes evident.The outcomes proffered are subsequently employed as a foundation for contemplating prospective theoretical and practical research endeavors concerning SAMs.The main purpose and value of this article is to review the SAM and reliability-related issues,which can provide some reference and inspiration for future research scholars in this field.

Reliability Assessment of a New General Matching Composed Network

The reliability of a network is an important indicator for maintaining communication and ensuring its stable operation. Therefore, the assessment of reliability in underlying interconnection networks has become an increasingly important research issue. However, at present, the reliability assessment of many interconnected networks is not yet accurate,which inevitably weakens their fault tolerance and diagnostic capabilities. To improve network reliability,researchers have proposed various methods and strategies for precise assessment. This paper introduces a novel family of interconnection networks called general matching composed networks(gMCNs), which is based on the common characteristics of network topology structure. After analyzing the topological properties of gMCNs, we establish a relationship between super connectivity and conditional diagnosability of gMCNs. Furthermore, we assess the reliability of g MCNs, and determine the conditional diagnosability of many interconnection networks.

A non-probabilistic reliability topology optimization method based on aggregation function and matrix multiplication considering buckling response constraints

A non-probabilistic reliability topology optimization method is proposed based on the aggregation function and matrix multiplication.The expression of the geometric stiffness matrix is derived,the finite element linear buckling analysis is conducted,and the sensitivity solution of the linear buckling factor is achieved.For a specific problem in linear buckling topology optimization,a Heaviside projection function based on the exponential smooth growth is developed to eliminate the gray cells.The aggregation function method is used to consider the high-order eigenvalues,so as to obtain continuous sensitivity information and refined structural design.With cyclic matrix programming,a fast topology optimization method that can be used to efficiently obtain the unit assembly and sensitivity solution is conducted.To maximize the buckling load,under the constraint of the given buckling load,two types of topological optimization columns are constructed.The variable density method is used to achieve the topology optimization solution along with the moving asymptote optimization algorithm.The vertex method and the matching point method are used to carry out an uncertainty propagation analysis,and the non-probability reliability topology optimization method considering buckling responses is developed based on the transformation of non-probability reliability indices based on the characteristic distance.Finally,the differences in the structural topology optimization under different reliability degrees are illustrated by examples.

Analysis of the Effect of Temperature and Relative Humidity on the Reliability of a Photovoltaic Module

Photovoltaic energy occupies a significant place in the renewable energy market, with photovoltaic (PV) modules playing a vital role in converting solar energy into electricity. However, their effectiveness is likely to be affected by variations in environmental conditions, including temperature and relative humidity. The study examines the impact of these major climatic factors on the reliability of PV modules, aiming to provide crucial information for optimizing and managing these systems under varying conditions. Inspired by Weibull’s law to model the lifespan of components, we proposed a mathematical model integrating a correction factor linked to temperature and relative humidity. Using this approach, simulations in Matlab Simulink reveal that increasing temperature and relative humidity have an adverse impact on the reliability and lifespan of PV modules, with a more pronounced impact on temperature. The results highlight the importance of considering these environmental parameters in the management and optimization of photovoltaic systems to ensure their long-term efficiency.

Probabilistic-Ellipsoid Hybrid Reliability Multi-Material Topology Optimization Method Based on Stress Constraint

This paper proposes a multi-material topology optimization method based on the hybrid reliability of the probability-ellipsoid model with stress constraint for the stochastic uncertainty and epistemic uncertainty of mechanical loads in optimization design.The probabilistic model is combined with the ellipsoidal model to describe the uncertainty of mechanical loads.The topology optimization formula is combined with the ordered solid isotropic material with penalization(ordered-SIMP)multi-material interpolation model.The stresses of all elements are integrated into a global stress measurement that approximates the maximum stress using the normalized p-norm function.Furthermore,the sequential optimization and reliability assessment(SORA)is applied to transform the original uncertainty optimization problem into an equivalent deterministic topology optimization(DTO)problem.Stochastic response surface and sparse grid technique are combined with SORA to get accurate information on the most probable failure point(MPP).In each cycle,the equivalent topology optimization formula is updated according to the MPP information obtained in the previous cycle.The adjoint variable method is used for deriving the sensitivity of the stress constraint and the moving asymptote method(MMA)is used to update design variables.Finally,the validity and feasibility of the method are verified by the numerical example of L-shape beam design,T-shape structure design,steering knuckle,and 3D T-shaped beam.

On the Application of Mixed Models of Probability and Convex Set for Time-Variant Reliability Analysis

In time-variant reliability problems,there are a lot of uncertain variables from different sources.Therefore,it is important to consider these uncertainties in engineering.In addition,time-variant reliability problems typically involve a complexmultilevel nested optimization problem,which can result in an enormous amount of computation.To this end,this paper studies the time-variant reliability evaluation of structures with stochastic and bounded uncertainties using a mixed probability and convex set model.In this method,the stochastic process of a limit-state function with mixed uncertain parameters is first discretized and then converted into a timeindependent reliability problem.Further,to solve the double nested optimization problem in hybrid reliability calculation,an efficient iterative scheme is designed in standard uncertainty space to determine the most probable point(MPP).The limit state function is linearized at these points,and an innovative random variable is defined to solve the equivalent static reliability analysis model.The effectiveness of the proposed method is verified by two benchmark numerical examples and a practical engineering problem.

A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Efficient slope reliability analysis under soil spatial variability using maximum entropy distribution with fractional moments

Spatial variability of soil properties imposes a challenge for practical analysis and design in geotechnical engineering.The latter is particularly true for slope stability assessment,where the effects of uncertainty are synthesized in the so-called probability of failure.This probability quantifies the reliability of a slope and its numerical calculation is usually quite involved from a numerical viewpoint.In view of this issue,this paper proposes an approach for failure probability assessment based on Latinized partially stratified sampling and maximum entropy distribution with fractional moments.The spatial variability of geotechnical properties is represented by means of random fields and the Karhunen-Loève expansion.Then,failure probabilities are estimated employing maximum entropy distribution with fractional moments.The application of the proposed approach is examined with two examples:a case study of an undrained slope and a case study of a slope with cross-correlated random fields of strength parameters under a drained slope.The results show that the proposed approach has excellent accuracy and high efficiency,and it can be applied straightforwardly to similar geotechnical engineering problems.