Random Response Research Articles

The TeamSTEPPS for Improving Diagnosis Team Assessment Tool: Scale Development and Psychometric Evaluation

One in three patients is affected by diagnosis-related communication failures. Only a few valid and reliable instruments that measure teamwork and communication exist, and none of those focus on improving diagnosis. The authors developed, refined, and psychometrically evaluated the TeamSTEPPSⓇ for Improving Diagnosis Team Assessment Tool (TAT), which assesses diagnostic teamwork and communication in five critical teamwork domains and can be used to identify strengths and opportunities for improvement and monitor performance. The TAT was administered as a cross-sectional survey to 360 health professionals across nine diverse US health systems. Content and construct validity were evaluated through pilot implementation and subject matter expert review. Reliability and internal consistency were assessed with Cronbach's alpha. To understand sources of variation in TAT scores and assess the tool's consistency across diverse health care organizations, generalizability theory (G-theory) was used. Best practices in screening for careless responding identified participants with random or nonvarying responses. Analyses indicated strong support for the tool. Content validity findings indicated that the TAT encompassed relevant diagnostic improvement teamwork and communication content. Construct validity, evaluated through pilot implementations, demonstrated the tool's effectiveness in assessing teamwork categories. Reliability analyses confirmed the TAT's internal consistency, with an overall Cronbach's alpha of 0.97. Each dimension of the TAT exhibited good reliability coefficients, ranging from 0.83 to 0.95. G-theory analysis showed that variations in TAT scores were primarily attributed to respondents (28.0%) and scale dimensions (59.6%); both are desirable facets of variation. Further, examination of careless respondents ensured the accuracy and quality of the results, enhancing the TAT's credibility as a valuable diagnostic improvement tool. Psychometric evaluation demonstrated that the TAT is a reliable and valid instrument for assessing teamwork and communication among and across diagnostic teams. The TAT adds a novel, evidence-based, psychometrically sound measurement tool to help advance diagnostic teamwork and communication to improve patient care and outcomes.

How to use randomized response survey data at hand by a specific procedure to judge its efficiency versus a possible rival

It is well-known that given survey data at hand by a given method, it is possible to examine how this method promises to fare vis- à -vis another one that might have been employed but not actually implemented. We illustrate how this may be extended to cover Randomized Response (RR) Techniques (RRT) by citing a few RR procedures in combination with a few sample selection methods generally in use. Developing the theory, simulated results are presented to demonstrate interesting numerical findings in this context.

Influence of foot excitation and shin posture on the vibration behavior of the entire spine inside a seated human body

Due to ethical issues and simplification of traditional biomechanical models, experimental methods and traditional computer methods were difficult to quantify the effects of foot excitation and shin posture on vibration behavior of the entire spine inside a seated human body under vertical whole-body vibration. This study developed and verified different three-dimensional (3D) finite element (FE) models of seated human body with detailed anatomical structure under the biomechanical characteristics to predict vibration behavior of the entire spine inside a seated human body with different foot excitation (with and without vibration) and shin posture (vertical and tilt posture). Random response analysis was performed to study the transmissibility of the entire spine to seat under vertical white noise excitation between 0 and 20 Hz at 0.5 m/s2 r.m.s. The results showed that although the foot excitation could reduce the fore-aft transmissibility in the cervical spine (23% reduction), it could significantly increase that in the lumbar spine (52% increase), which resulted in complex alternating stresses at lumbar spine and made the lumbar spine more vulnerable to injury in long-term vibration environment. Moreover, the shin tilt posture made the maximum fore-aft transmissibility in the lumbar spine move to the upper lumbar spine. The study provided new insights into the influence of foot excitation and shin posture on the vibration behavior of the entire spine inside a seated human body. Foot excitation exposed the lumbar spine to complex alternating stresses and made it more vulnerable to injury in long-term whole body vibration.

Synthesized randomized response techniques

Reducing response bias in survey research is important in ensuring that the data collected accurately represents the population of interest. This study proposes the synthesized random response technique (SRRT) estimator as an efficient method to reduce response bias in this regard. We compared the proposed SRRT estimator with other conventional techniques, such as the Hybrid Tripartite Randomized Response Technique (HTRRT), the Alternative Tripartite Randomized Response Technique (ATRRT), and the Two-Stage Unrelated Question Randomized Response Model for Estimating Prevalence of Stigmatized Attributes (TSUQRRMEPSA). Our results show that the proposed SRRT estimator consistently produces more efficient estimates than other conventional techniques as sample sizes increase. As a result, the proposed SRRT estimator have the potential to enhance the accuracy of survey data, which is sensitive for informed decision-making. Hence, the proposed method is more efficient in reducing response bias than other conventional methods.

LDPORR: A localized location privacy protection method based on optimized random response

The broad use of mobile intelligent terminals with locating functions encourages the rapid development of location-based services (LBS), which are widely used in a variety of industries such as social networking, transportation, finance, and entertainment. While enjoying the convenience brought by LBS, the threat of location privacy leakage should not be overlooked. In view of the complex encoding mechanism and low availability of the current location privacy protection methods, a local differential privacy location protection method based on optimized random response is proposed in this paper. A spatial decomposition and Hilbert encoding mechanism are designed based on the Hilbert curve, which can reduce the two-dimensional location data into one-dimensional Hilbert encoding results. A local differential privacy location perturbation method based on optimized random response is proposed to improve the availability of perturbed locations and the accuracy of data aggregation. Experiments on actual location datasets prove that the proposed method can provide better location data availability and operational efficiency based on realizing local differential privacy protection of users’ location.

IRT Models for Learning With Item-Specific Learning Parameters

We propose a new item response theory growth model with item-specific learning parameters, or ISLP, and two variations of this model. In the ISLP model, either items or blocks of items have their own learning parameters. This model may be used to improve the efficiency of learning in a formative assessment. We show ways that the ISLP model’s learning parameters can be estimated in simulation using Markov chain Monte Carlo (MCMC), demonstrate a way that the model could be used in the context of adaptive item selection to increase the rate of learning, and estimate the learning parameters in an empirical data analysis using the ISLP. In the simulation studies, the one-parameter logistic model was used as the measurement model to generate random response data with various test lengths and sample sizes. Ability growth was modeled with a few variations of the ISLP model, and it was verified that the parameters were accurately recovered. Secondly, we generated data using the linear logistic test model with known Q-matrix structure for the item difficulties. Using a two-step procedure gave very comparable results for the estimation of the learning parameters even when item difficulties were unknown. The potential benefit of using an adaptive selection method in conjunction with the ISLP model was shown by comparing total improvement in the examinees’ ability parameter to two other methods of item selection that do not utilize this growth model. If the ISLP holds, adaptive item selection consistently led to larger improvements over the other methods. A real data application of the ISLP was given to illustrate its use in a spatial reasoning study designed to promote learning. In this study, interventions were given after each block of ten items to increase ability. Learning parameters were estimated using MCMC.

Random response of a two-degree-of-freedom rotational vibration energy harvester

Random response of a two-degree-of-freedom rotational vibration energy harvester

Overcoming defensive responding in the estimation of prevalence of non-medical use of prescription stimulants

BackgroundPrevalence of Non-Medical Use of Prescription Stimulants (NMUPS) is estimated to be high among young adults enrolled in college. However, precise estimation of the prevalence of NMUPS is challenging owing to biases affecting self-report of sensitive and potentially illegal behaviors. ObjectiveThis study aimed to estimate the prevalence and risk factors of NMUPS using the crosswise randomized response technique (CRRT) and compare findings to the traditionally-used direct self-report (DSR) method. MethodsThis study utilized a cross-sectional, randomized experimental design to survey adult undergraduate students at a major southeastern university in the United States. Eligible respondents were randomly assigned to a DSR group or a CRRT group. Those in the DSR group were presented a direct question about NMUPS, but those in the CRRT group were asked to indicate whether their response to the NMUPS question was the ‘same’ or ‘different’ compared to a random non-sensitive question. ResultsPrevalence of NMUPS was found to be 18.6% (95% CI:18.5%–18.7%) in the DSR group and 32.5% (95% CI:32.1%–32.9%; p = 0.003) in the CRRT group. Logistic regression analysis predicting NMUPS in the DSR group showed that it was significantly associated with positive expectancies (OR:3.50; 95% CI:2.44–5.02), negative expectancies (OR:0.49; 95% CI:0.35–0.68), perceived norms (OR:1.71; 95% CI:1.27–2.29), and religious beliefs (OR:0.69; 95% CI:0.52–0.92). ConclusionsThe setting and mechanism of the survey is likely closely related to the validity of prevalence estimation of sensitive behaviors. This study found that prevalence of sensitive behaviors such as NMUPS is significantly higher when respondents are provided increased anonymity.

A random optimization strategy of microgrid dispatching based on stochastic response surface method considering uncertainty of renewable energy supplies and load demands

The stochastic response of microgrid regulation under the influence of uncertainty should be considered in the day-ahead optimal dispatching. This paper focuses on the Stochastic Response Surface Method (SRSM) modelling and Second-Order Cone Programming (SOCP) optimal solution for the stochastic optimization strategy of microgrid dispatching considering the random fluctuations of renewable energy supplies and load demands. Based on the SRSM theory, the random distributions of uncertainty are converted into independent standard normal distributions by Nataf transformation, then by means of a small amount of standardized SRSM samples of random fluctuations, the Hermite Chaotic Polynomials can be formulated to describe the random response process of microgrid adjustment. And the Hermite Chaotic Matrix establishes the linear constraint functions for the probability distribution characteristics of stochastic response process of microgrid adjustment considering uncertainty. On this basis, the SRSM based stochastic optimization (SO) model with multi-objective functions are constructed for the optimal economic operation, control of cost fluctuation and lower carbon emissions. In addition, to reduce operation risk, the constraints of extreme power shortage are introduced into the model. To ensure the convexity of the optimization model, the Second-Order Cone Relaxation is applied to all the quadratic terms in the model. Thus, the proposed SO model of microgrid dispatching can be transformed into an SOCP optimization problem. And the Yalmip-Gurobi solver is adopted for the solution of the proposed SO model, which has an efficient operation speed and stability. The effectiveness of the proposed scheme is demonstrated by the case studies using Monte Carlo sampling simulation.

Surrogate modeling and global sensitivity analysis for the simultaneous growth of multiple hydraulic fractures

Hydraulic fracturing has been widely used in enhancing the conductivity of the rock formations and increasing the rate of extraction of unconventional resources. During hydraulic fracturing treatments, there are considerable uncertainties in the completion operations and measurement of the geomechanical parameters such as the perforation geometry and elastic modulus of the rock matrix, which may result in a large error in fracture pattern prediction and parameter optimization when deterministic models are implemented. Therefore, a good understanding of the impact of the input uncertainties on the output predictions, also referred to as uncertainty quantification, has become a major issue. In this paper, a non-intrusive stochastic model is developed by combining a fully coupled hydraulic fracturing model based on the dual boundary element method with a surrogate model using polynomial chaos expansion. The perforation geometry, mechanical parameters of the rock formation, orientation and magnitude of the in-situ stress are treated as random variables. The surrogate model is constructed using data from the hydraulic fracturing model and is capable of providing fast approximations of the objectives, thereby making Monte Carlo simulations and sensitivity studies feasible. The stochastic model is validated against the random responses predicted by semi-analytical solutions for the single fracture case and shows excellent agreements with a relative error less than 0.1% for the injection pressure and 1% for the maximum aperture. The impact of the geomechanical and geometric parameter randomness on the growth of multiple fractures is investigated. The results show that the randomness in the fracture toughness and Young’s modulus plays an important role in fracture growth among geomechanical parameters, and the uncertainty of the fracture pattern is mostly attributed to the randomness in the initial length and aperture of the inner fracture among geometric uncertainties.

Comparing Person-Fit and Traditional Indices Across Careless Response Patterns in Surveys.

Methods to identify carelessness in survey research can be valuable tools in reducing bias during survey development, validation, and use. Because carelessness may take multiple forms, researchers typically use multiple indices when identifying carelessness. In the current study, we extend the literature on careless response identification by examining the usefulness of three item-response theory-based person-fit indices for both random and overconsistent careless response identification: infit MSE outfit MSE, and the polytomous lz statistic. We compared these statistics with traditional careless response indices using both empirical data and simulated data. The empirical data included 2,049 high school student surveys of teaching effectiveness from the Network for Educator Effectiveness. In the simulated data, we manipulated type of carelessness (random response or overconsistency) and percent of carelessness present (0%, 5%, 10%, 20%). Results suggest that infit and outfit MSE and the lz statistic may provide complementary information to traditional indices such as LongString, Mahalanobis Distance, Validity Items, and Completion Time. Receiver operating characteristic curves suggested that the person-fit indices showed good sensitivity and specificity for classifying both over-consistent and under-consistent careless patterns, thus functioning in a bidirectional manner. Carelessness classifications based on low fit values correlated with carelessness classifications from LongString and completion time, and classifications based on high fit values correlated with classifications from Mahalanobis Distance. We consider implications for research and practice.

A Theoretical Framework for the Analysis of Physical Unclonable Function Interfaces and Its Relation to the Random Oracle Model

Analysis of advanced physical unclonable function (PUF) applications and protocols relies on assuming that a PUF behaves like a random oracle; that is, upon receiving a challenge, a uniform random response with replacement is selected, measurement noise is added, and the resulting response is returned. In order to justify such an assumption, we need to rely on digital interface computation that to some extent remains confidential—otherwise, information about PUF challenge–response pairs leak with which the adversary can train a prediction model for the PUF. We introduce a theoretical framework that allows the adversary to have a prediction model (with a typical accuracy of 75% for predicting response bits for state-of-the-art silicon PUF designs). We do not require any confidential digital computing or digital secrets, while we can still prove rigorous statements about the bit security of a system that interfaces with the PUF. In particular, we prove the bit security of a PUF-based random oracle construction; this merges the PUF framework with fuzzy extractors.

Response spectrum method for fatigue damage assessment of aero-hydraulic pipeline systems

This paper proposes a response spectrum method to assess the fatigue damage of aero-hydraulic pipeline systems subjected to random airframe motion. A real-valued analytical formula for calculating the random stress response of a clamp-pipeline model transporting fluid is derived using the complex modal superposition method and random vibration theory. Based on our previous work on the response spectrum method for fatigue damage assessment, the authors establish a set of complex modal combination formulas for the expected damage rate, introducing new velocity-velocity and displacement-velocity combination coefficients. These formulas characterise the expected damage rate as a linear combination of the damage responses that are not reliant on the spatial distribution of the pipeline model. The fatigue damage assessment of different pipeline models is computationally efficient as only the natural frequencies and the mode shapes need to be calculated. The correctness of the complex modal combination equation is verified by the rain-flow counting method, and the effect of the fluid velocity on the expected damage rate is discussed.

Equivalence analysis of acoustic excitation and random vibration exerted on spacecraft units

At the unit level test, the small area-to-mass ratio unit of spacecraft generally adopts the random vibration test to simulate the acoustic environment during the launch event. Acoustic excitation and random vibration exerted on spacecraft units reflect different dynamic characteristics. Thus, the equivalence analysis between them deserves to be conducted. In this work, a thruster outside the spacecraft was taken as an example, for it directly experiences acoustic load compared with the electronic equipment inside. The vibroacoustic and random vibration models of the thruster were established, and response behavior was explored. Results show that there are differences in the response distribution rules of acoustic load and random vibration on the thruster. The farther to the thruster root is, the harder acoustic vibration responses can be covered by the random response, so an appropriate safety margin shall be reserved when formulating random vibration conditions of units.

The jitter frequency domain of long-span railway cable-stayed bridges considering the influence of pneumatic admittance

The long-span bridge is highly sensitive to wind loads, and their random vibration response under static wind deformation and fluctuating wind load are relatively complex. The analysis of jitter response has become a key issue in the design. Taking the Hanjiatuo Yangtze River Bridge in the chongqing-lichuan railway as the engineering background, the influence of different aerodynamic admittance functions on the main girder jitter response is studied through frequency domain analysis. The results show that aerodynamic admittance has a great influence on the jitter response. Considering that the jitter displacement response of the aerodynamic admittance function is obviously smaller than the calculated results, the influence of aerodynamic admittance should be considered in the calculation and analysis.

Random Dynamic Analysis and Running Safety Assessment of Long-Span Cable-Stayed Bridge Under High-Speed Trains Subjected to Earthquake Excitations and Track Irregularities

Running trains on a long-span bridge under earthquake is an inevitable problem for the high-speed railway in seismic regions. This paper aims to investigate the seismically random dynamic behavior of train–cable stayed bridges interaction system using the probability density evolution method (PDEM). The system simultaneously involves the multi-effect of random multi-point earthquake excitations with traveling waves and random track irregularity. The multi-point earthquake excitations, composed of lateral and vertical positions, are generated by stochastic harmful functions (SHFs) and uniformly modulated into nonstationary random processes. The motion equation of such a system is established by coupling the 38-degree vehicles and bridges through the refined random wheel/rail contact relationship and accounting for the phase-lags of seismic travelling waves between pier excitations. PDEM is proven to be applicable to such time-dependent systems and is then used to transform the random excitations into a series of deterministic representative excitations with initial probability. By solving for the corresponding deterministic probability responses, various nonstationary random responses, including the time-dependent probability density evolution functions of random responses, mean values curves and standard deviations, can be obtained easily. A case study based on the cable-stayed bridge is then presented, and the results show the effectiveness and accuracy of the proposed method by comparison with Monte Carlo Simulation. Additionally, the influence of train speed and seismic intensity on the safety and reliability of trains is discussed.

Influence of the Relationship Between Excitation Frequency and Natural Frequency on Formulating Structural Random Displacement Response

Seismic action and wind excitation are the main sources of excitation to civil engineering structures. The analytical structural responses are similar for both cases, but the simplified formula in design codes on the displacement response under these excitations is quite different. This paper re-visits this difference from under stationary random excitation. The power spectrum density function of the above excitations contains several parameters which define the excitations in frequency domain. The simplified formulas of the displacement variance under different excitations are derived by adjusting these parameters. The responses from these formulas always include the resonance component of the response, whereas the presence of the background component depends on the ratio between the predominant frequency of excitation and the natural frequency of the structure. The influence of this ratio on the displacement covariance and the modal combination rules is then further discussed.

Semi-analytical solutions for stationary response of a stay cable under combined Gaussian and Poisson excitations

This paper studies nonlinear random vibrations of a stay cable subject to combined Gaussian and Poisson excitations. The Gaussian excitation is continuous stochastic process directly acting on the stay cable, while the Poisson excitation describes discrete random disturbances to the base of the system. The in-plane and out-of-plane coupled vibration of the stay cable is discretized and represented by a two-degree-of-freedom dynamical system with the help of the Galerkin method. Then, the stationary response of the stay cable is determined in terms of radial basis function neural networks (RBFNN) to minimize the residual error of the generalized-Fokker–Planck–Kolmogorov (GFPK) equation. A super-long stay cable in practice is taken as an engineering example to demonstrate the analysis. The influences of system parameters on the random vibration responses of the stay cable are examined to reveal the features of the vibration response. Extensive Monte Carlo simulations (MCS) are conducted to check the precision of the semi-analytical solutions. This research lays down a foundation for optimal design and vibration control design of the stay cable.

Graphene-Based Physically Unclonable Functions with Dual Source of Randomness.

There is growing interest in systems with randomized responses for generating physically unclonable functions (PUFs) in anticounterfeiting and authentication applications. Atomic-level control over its thickness and unique Raman spectrum make graphene an attractive material for PUF applications. Herein, we report graphene PUFs that emerge from two independent stochastic processes. Randomized variations in the shape and number of graphene adlayers were achieved by exploiting and improving the mechanistic understanding of the chemical vapor deposition of graphene. The randomized positioning of the graphene domains was then facilitated by dewetting the polymer film, followed by oxygen plasma etching. This approach yielded surfaces with randomly positioned and shaped graphene islands with varied numbers of layers and, therefore, Raman spectra. Raman mapping of surfaces resulted in multicolor images with a high encoding capacity. Advanced feature-matching algorithms were employed for the authentication of multicolor images. The use of two independent stochastic processes on a two-dimensional nanomaterial platform enables the creation of unique and complex surfaces that excessively challenge clonability.

Dynamic Amplification Factors of an Arch Bridge Under Random Traffic Flows

Among large-span bridges, arch bridges have relatively high stiffness, which may lead to large dynamic amplification factors (DAFs). The DAFs suggested by current codes mostly originate from common simply supported beam bridges. Previous DAF studies on dynamic vehicle–bridge solutions for arch bridges have mainly focused on one or two side-by-side vehicles. However, complex traffic flows with randomness rather than one or two vehicles act on bridges. DAFs that consider the effects of random traffic flows have not previously been reported. In this study, a random traffic–bridge vibration solution was established to explore the DAFs of arch bridge components. The randomness of the traffic parameters and road roughness was explored. The randomness of the external excitation, including traffic flow and road roughness, resulted in random dynamic responses and DAFs of the arch bridge components. Normal distributions could be used to fit the DAF distributions of each arch bridge component under random vehicle spacing, weight, speed, and road roughness. Under random traffic parameters, the coefficients of variation of the DAFs exceeded the 5% accepted level. The shortest suspenders were more sensitive to the randomness of the traffic flow parameters. Both the mean and coefficient of variation of the DAFs increased with worsening of the road conditions. The influence of the randomness of the road roughness on the DAFs of arch bridges must be considered, particularly for the shortest suspender. The 95% upper confidence limits of the DAFs for all components may be greater than the suggested values in the code.