Grado Department of Industrial and Systems Engineering
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Browsing Grado Department of Industrial and Systems Engineering by Content Type "Article - Refereed"
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- 2nd Workshop on Multimodal Motion Sickness Detection and Mitigation Methods for Car Journeys - Finding Consensus in the FieldPöhlmann, Katharina; Al-Taie, Ammar; Li, Gang; Dam, Abhraneil; Wang, Yu-Kai; Wei, Chun-Shu; Papaioannou, Georgios (ACM, 2023-09-18)The adoption of automated vehicles will be a positive step towards road safety and environmental benefits. However, one major challenge that still exist is motion sickness. The move from drivers to passengers who will engage in non-driving related tasks as well as the potential change in the layout of the car interior that will come with automated vehicles are expected to result in a worsened experience of motion sickness. The previous workshop [18] highlighted the need for consensus on guidelines regarding study design for motion sickness research. Hence, this workshop will develop a guide for motion sickness research through reflection and discussions on the current methodologies used by experts in the field. Further it will build on the knowledge collected from the previous workshop and will thereby facilitate not only new research ideas and fruitful collaborations but also find a consensus in the field in regard to study design and methodologies.
- Acoustofluidic particle trapping, manipulation, and release using dynamic-mode cantilever sensorsJohnson, Blake N.; Mutharasan, Raj (Royal Society of Chemistry, 2016-11-23)We show here that dynamic-mode cantilever sensors enable acoustofluidic fluid mixing and trapping of suspended particles as well as the rapid manipulation and release of trapped micro-particles via mode switching in liquid. Resonant modes of piezoelectric cantilever sensors over the 0 to 8 MHz frequency range are investigated. Sensor impedance response, flow visualization studies using dye and micro-particle tracers (100 mum diameter), and finite element simulations of cantilever modal mechanics and acoustic streaming show fluid mixing and particle trapping configurations depend on the resonant mode shape. We found trapped particles could be: (1) rapidly manipulated on millimeter length scales, and (2) released from the cantilever surface after trapping by switching between low- and high-order resonant modes (less than 250 kHz and greater than 1 MHz, respectively). Such results suggest a potentially promising future for dynamic-mode cantilevers in separations, pumping and mixing applications as well as acoustofluidic-enhanced sensing applications.
- Age-related strength loss affects non-stepping balance recoveryKoushyar, Hoda; Bieryla, Kathleen A.; Nussbaum, Maury A.; Madigan, Michael L. (Public Library of Science, 2019-01-18)Aging is associated with a higher risk of falls, and an impaired ability to recover balance after a postural perturbation is an important contributing factor. In turn, this impaired recovery ability likely stems from age-related decrements in lower limb strength. The purpose of this study was to investigate the effects of age-related strength loss on non-stepping balance recovery capability after a perturbation while standing, without constraining movements to the ankle as in prior reports. Two experiments were conducted. In the first, five young adults (ages 20–30) and six community-dwelling older adults (ages 70–80) recovered their balance, without stepping, from a backward displacement of a support surface. Balance recovery capability was quantified as the maximal backward platform displacement that a subject could withstand without stepping. The maximal platform displacement was 27% smaller among the older group (11.8±2.1 cm) vs. the young group (16.2±2.6 cm). In the second experiment, forward dynamic simulations of a two-segment, rigid-body model were used to investigate the effects of manipulating strength in the hip extensors/flexors and ankle plantar flexors/dorsiflexors. In these, typical age-related reductions in strength were included. The model predicted lower maximal platform displacements with age-related reductions only in plantar flexion and hip flexion strength. These findings support the previously reported age-related loss of balance recovery ability, and an important role for plantar flexor strength in this ability. © 2019 Koushyar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Agent-Based Simulation Framework for Epidemic Forecasting during Hajj Seasons in Saudi ArabiaAlshammari, Sultanah Mohammed; Ba-Aoum, Mohammed Hassan; Alganmi, Nofe Ateq; Allinjawi, Arwa AbdulAziz (MDPI, 2021-08-12)The religious pilgrimage of Hajj is one of the largest annual gatherings in the world. Every year approximately three million pilgrims travel from all over the world to perform Hajj in Mecca in Saudi Arabia. The high population density of pilgrims in confined settings throughout the Hajj rituals can facilitate infectious disease transmission among the pilgrims and their contacts. Infected pilgrims may enter Mecca without being detected and potentially transmit the disease to other pilgrims. Upon returning home, infected international pilgrims may introduce the disease into their home countries, causing a further spread of the disease. Computational modeling and simulation of social mixing and disease transmission between pilgrims can enhance the prevention of potential epidemics. Computational epidemic models can help public health authorities predict the risk of disease outbreaks and implement necessary intervention measures before or during the Hajj season. In this study, we proposed a conceptual agent-based simulation framework that integrates agent-based modeling to simulate disease transmission during the Hajj season from the arrival of the international pilgrims to their departure. The epidemic forecasting system provides a simulation of the phases and rituals of Hajj following their actual sequence to capture and assess the impact of each stage in the Hajj on the disease dynamics. The proposed framework can also be used to evaluate the effectiveness of the different public health interventions that can be implemented during the Hajj, including size restriction and screening at entry points.
- An Algorithm for Fast Generation of Bivariate Poisson Random VectorsShin, K.; Pasupathy, R. (INFORMS, 2010)We present the "trivariate reduction extension" (TREx)-an exact algorithm for the fast generation of bivariate Poisson random vectors. Like the normal-to-anything (NORTA) procedure, TREx has two phases: a preprocessing phase when the required algorithm parameters are identified, and a generation phase when the parameters identified during the preprocessing phase are used to generate the desired Poisson vector. We prove that the proposed algorithm covers the entire range of theoretically feasible correlations, and we provide efficient-computation directives and rigorous bounds for truncation error control. We demonstrate through extensive numerical tests that TREx, being a specialized algorithm for Poisson vectors, has a preprocessing phase that is uniformly a hundred to a thousand times faster than a fast implementation of NORTA. The generation phases of TREx and NORTA are comparable in speed, with that of TREx being marginally faster. All code is publicly available.
- Am I Really Angry? The Influence of Anger Intensities on Young Drivers' BehaviorsWang, Manhua; Jeon, Myounghoon (ACM, 2023-09-18)Anger can lead to aggressive driving and other negative behaviors. While previous studies treated anger as a single dimension, the present research proposed that anger has distinct intensities and aimed to understand the effects of different anger intensities on driver behaviors. After developing the anger induction materials, we conducted a driving simulator study with 30 participants and assigned them to low, medium, and high anger intensity groups. We found that drivers with low anger intensity were not able to recognize their emotions and exhibited speeding behaviors, while drivers with medium and high anger intensities might be aware of their anger along with its adverse effects and then adjusted their longitudinal control. However, angry drivers generally exhibited compromised lateral control indicated by steering and lane-keeping behaviors. Our findings shed light on the potentially different influences of anger intensities on young drivers’ behaviors, especially the importance of anger recognition for intervention solutions.
- Applying variance reduction ideas in queuing simulationsRoss, S. M.; Lin, K. Y. (Cambridge University Press, 2001)Variance reduction techniques are often underused in simulation studies. In this article, we indicate how certain ones can be efficiently employed when analyzing queuing models. The first technique considered is that of dynamic stratified sampling; the second is the utilization of multiple control variates; the third concerns the replacement of random variables by their conditional expectations when trying to estimate the expected value of a sum of random variables.
- Approximate Positively Correlated Distributions and Approximation Algorithms for D-optimal DesignSingh, Manoj; Xie, W. (2018-02-26)Experimental design is a classical problem in statistics and has also found new applications in machine learning. In the experimental design problem, the aim is to estimate an unknown vector x in m-dimensions from linear measurements where a Gaussian noise is introduced in each measurement. The goal is to pick k out of the given n experiments so as to make the most accurate estimate of the unknown parameter x. Given a set S of chosen experiments, the most likelihood estimate x' can be obtained by a least squares computation. One of the robust measures of error estimation is the D-optimality criterion which aims to minimize the generalized variance of the estimator. This corresponds to minimizing the volume of the standard confidence ellipsoid for the estimation error x-x'. The problem gives rise to two natural variants depending on whether repetitions are allowed or not. The latter variant, while being more general, has also found applications in the geographical location of sensors. In this work, we first show that a 1/e-approximation for the D-optimal design problem with and without repetitions giving us the first constant factor approximation for the problem. We also consider the case when the number of experiments chosen is much larger than the dimension of the measurements and provide an asymptotically optimal approximation algorithm.
- AR DriveSim: An Immersive Driving Simulator for Augmented Reality Head-Up Display ResearchGabbard, Joseph L.; Smith, Missie; Tanous, Kyle; Kim, Hyungil; Jonas, Bryan (Frontiers, 2019-10-23)Optical see-through automotive head-up displays (HUDs) are a form of augmented reality (AR) that is quickly gaining penetration into the consumer market. Despite increasing adoption, demand, and competition among manufacturers to deliver higher quality HUDs with increased fields of view, little work has been done to understand how best to design and assess AR HUD user interfaces, and how to quantify their effects on driver behavior, performance, and ultimately safety. This paper reports on a novel, low-cost, immersive driving simulator created using a myriad of custom hardware and software technologies specifically to examine basic and applied research questions related to AR HUDs usage when driving. We describe our experiences developing simulator hardware and software and detail a user study that examines driver performance, visual attention, and preferences using two AR navigation interfaces. Results suggest that conformal AR graphics may not be inherently better than other HUD interfaces. We include lessons learned from our simulator development experiences, results of the user study and conclude with limitations and future work.
- Assessing elderly’s functional balance and mobility via analyzing data from waist-mounted tri-axial wearable accelerometers in timed up and go testsYu, Lisha; Zhao, Yang; Wang, Hailiang; Sun, Tien-Lung; Murphy, Terrence E.; Tsui, Kwok-Leung (2021-03-25)Background Poor balance has been cited as one of the key causal factors of falls. Timely detection of balance impairment can help identify the elderly prone to falls and also trigger early interventions to prevent them. The goal of this study was to develop a surrogate approach for assessing elderly’s functional balance based on Short Form Berg Balance Scale (SFBBS) score. Methods Data were collected from a waist-mounted tri-axial accelerometer while participants performed a timed up and go test. Clinically relevant variables were extracted from the segmented accelerometer signals for fitting SFBBS predictive models. Regularized regression together with random-shuffle-split cross-validation was used to facilitate the development of the predictive models for automatic balance estimation. Results Eighty-five community-dwelling older adults (72.12 ± 6.99 year) participated in our study. Our results demonstrated that combined clinical and sensor-based variables, together with regularized regression and cross-validation, achieved moderate-high predictive accuracy of SFBBS scores (mean MAE = 2.01 and mean RMSE = 2.55). Step length, gender, gait speed and linear acceleration variables describe the motor coordination were identified as significantly contributed variables of balance estimation. The predictive model also showed moderate-high discriminations in classifying the risk levels in the performance of three balance assessment motions in terms of AUC values of 0.72, 0.79 and 0.76 respectively. Conclusions The study presented a feasible option for quantitatively accurate, objectively measured, and unobtrusively collected functional balance assessment at the point-of-care or home environment. It also provided clinicians and elderly with stable and sensitive biomarkers for long-term monitoring of functional balance.
- Asymmetries in Potential for Partisan GerrymanderingGoedert, Nicholas; Hildebrand, Robert; Travis, Laurel; Pierson, Matthew (2024)This paper investigates the effectiveness of potential partisan gerrymandering of the U.S. House of Representatives across a range of states. We use a heuristic algorithm to generate district maps that optimize for multiple objectives, including compactness, partisan benefit, and competitiveness. While partisan gerrymandering is highly effective for both sides, we find that the majority of states are moderately biased toward Republicans when optimized for either compactness or partisan benefit, meaning that Republican gerrymanders have the potential to be more effective. However, we also find that more densely populated and more heavily Hispanic states show less Republican bias or even Democratic bias. Additionally, we find that in almost all cases we can generate reasonably compact maps with very little sacrifice to partisan objectives through a mixed objective function. This suggests that there is a strong potential for stealth partisan gerrymanders that are both compact and beneficial to one party. Nationwide, partisan gerrymandering is capable of swinging over one hundred seats in the U.S. House, even when compact districts are simultaneously sought.
- Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm ValidationHsu, Yu-Cheng; Wang, Hailiang; Zhao, Yang; Chen, Frank; Tsui, Kwok-Leung (JMIR Publications, 2021-12-20)Background: Clinical mobility and balance assessments identify older adults who have a high risk of falls in clinics. In the past two decades, sensors have been a popular supplement to mobility and balance assessment to provide quantitative information and a cost-effective solution in the community environment. Nonetheless, the current sensor-based balance assessment relies on manual observation or motion-specific features to identify motions of research interest. Objective: The objective of this study was to develop an automatic motion data analytics framework using signal data collected from an inertial sensor for balance activity analysis in community-dwelling older adults. Methods: In total, 59 community-dwelling older adults (19 males and 40 females; mean age = 81.86 years, SD 6.95 years) were recruited in this study. Data were collected using a body-worn inertial measurement unit (including an accelerometer and a gyroscope) at the L4 vertebra of each individual. After data preprocessing and motion detection via a convolutional long short-term memory (LSTM) neural network, a one-class support vector machine (SVM), linear discriminant analysis (LDA), and k-nearest neighborhood (k-NN) were adopted to classify high-risk individuals. Results: The framework developed in this study yielded mean accuracies of 87%, 86%, and 89% in detecting sit-to-stand, turning 360 degrees, and stand-to-sit motions, respectively. The balance assessment classification showed accuracies of 90%, 92%, and 86% in classifying abnormal sit-to-stand, turning 360 degrees, and stand-to-sit motions, respectively, using Tinetti Performance Oriented Mobility Assessment-Balance (POMA-B) criteria by the one-class SVM and k-NN. Conclusions: The sensor-based approach presented in this study provided a time-effective manner with less human efforts to identify and preprocess the inertial signal and thus enabled an efficient balance assessment tool for medical professionals. In the long run, the approach may offer a flexible solution to relieve the community's burden of continuous health monitoring.
- An Autonomous Task Assignment Paradigm for Autonomous Robotic In-Space AssemblyHildebrand, Robert; Komendera, Erik; Moser, Joshua; Hoffman, Julia (Frontiers, 2022-02-25)The development of autonomous robotic systems is a key component in the expansion of space exploration and the development of infrastructures for in-space applications. An important capability for these robotic systems is the ability to maintain and repair structures in the absence of human input by autonomously generating valid task sequences and task to robot allocations. To this end, a novel stochastic problem formulation paired with a mixed integer programming assembly schedule generator has been developed to articulate the elements, constraints, and state of an assembly project and solve for an optimal assembly schedule. The developed formulations were tested with a set of hardware experiments that included generating an optimal schedule for an assembly and rescheduling during an assembly to plan a repair. This formulation and validation work provides a path forward for future research in the development of an autonomous system capable of building and maintaining in-space infrastructures.
- Benefits of integrated screening and vaccination for infection controlRabil, Marie Jeanne; Tunc, Sait; Bish, Douglas R.; Bish, Ebru K. (PLOS, 2022-04-21)Importance: Screening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics. Objective: To develop effective screening and vaccination strategies, customized for a college campus, to reduce COVID-19 infections, hospitalizations, deaths, and peak hospitalizations. Design, setting, and participants: We construct a compartmental model of disease spread under vaccination and routine screening, and study the efficacy of four mitigation strategies (routine screening only, vaccination only, vaccination with partial or full routine screening), and a no-intervention strategy. The study setting is a hypothetical college campus of 5,000 students and 455 faculty members during the Fall 2021 academic semester, when the Delta variant was the predominant strain. For sensitivity analysis, we vary the screening frequency, daily vaccination rate, initial vaccine coverage, and screening and vaccination compliance; and consider scenarios that represent low/medium/high transmission and test efficacy. Model parameters come from publicly available or published sources. Results: With low initial vaccine coverage (30% in our study), even aggressive vaccination and screening result in a high number of infections: 1,020 to 2,040 (1,530 to 2,480) with routine daily (every other day) screening of the unvaccinated; 280 to 900 with daily screening extended to the newly vaccinated in base- and worst-case scenarios, which respectively consider reproduction numbers of 4.75 and 6.75 for the Delta variant. Conclusion: Integrated vaccination and routine screening can allow for a safe opening of a college when both the vaccine effectiveness and the initial vaccine coverage are sufficiently high. The interventions need to be customized considering the initial vaccine coverage, estimated compliance, screening and vaccination capacity, disease transmission and adverse outcome rates, and the number of infections/peak hospitalizations the college is willing to tolerate.
- Bridging the Gap: Early Education on Robot and AI Ethics through the Robot Theater Platform in an Informal Learning EnvironmentMitchell, Jennifer; Dong, Jiayuan; Yu, Shuqi; Harmon, Madison; Holstein, Alethia; Shim, Joon Hyun; Choi, Koeun; Zhu, Qin; Jeon, Myounghoon (ACM, 2024-03-11)With the rapid advancement of robotics and AI, educating the next generation on ethical coexistence with these technologies is crucial. Our research explored the potential of a child-robot theater afterschool program in introducing and discussing robot and AI ethics with elementary school children. Conducted with 30 participants from a socioeconomically underprivileged school, the program blended STEM (Science, Technology, Engineering & Mathematics) with the arts, focusing on ethical issues in robotics and AI. Using interactive scenarios and a theatrical performance, the program aimed to enhance children’s understanding of major ethical issues in robotics and AI, such as bias, transparency, privacy, usage, and responsibility. Preliminary findings indicate the program’s success in engaging children in meaningful ethical discussions, demonstrating the potential of innovative, interactive educational methods in early education. This study contributes significantly to integrating ethical robotics and AI in early learning, preparing young minds for a technologically advanced and socially responsible future.
- C-NORTA: A Rejection Procedure for Sampling from the Tail of Bivariate NORTA DistributionsGhosh, Samik; Pasupathy, R. (INFORMS, 2012)We propose C-NORTA, an exact algorithm to generate random variates from the tail of a bivariate NORTA random vector. (A NORTA random vector is specified by a pair of marginals and a rank or product-moment correlation, and it is sampled using the popular NORmal-To-Anything procedure.) We first demonstrate that a rejection-based adaptation of NORTA on such constrained random vector generation problems may often be fundamentally intractable. We then develop the C-NORTA algorithm, relying on strategic conditioning of the NORTA vector, followed by efficient approximation and acceptance/rejection steps. We show that, in a certain precise asymptotic sense, the sampling efficiency of C-NORTA is exponentially larger than what is achievable through a naive application of NORTA. Furthermore, for at least a certain class of problems, we show that the acceptance probability within C-NORTA decays only linearly with respect to a defined rarity parameter. The corresponding decay rate achievable through a naive adaptation of NORTA is exponential. We provide directives for efficient implementation.
- Calculating and Analyzing Angular Head Jerk in Augmented and Virtual Reality: Effect of AR Cue Design on Angular JerkVan Dam, Jared; Tanous, Kyle; Werner, Matt; Gabbard, Joseph L. (MDPI, 2021-10-28)In this work, we propose a convenient method for evaluating levels of angular jerk in augmented reality (AR) and virtual reality (VR). Jerk is a rarely analyzed metric in usability studies, although it can be measured and calculated easily with most head-worn displays and can yield highly relevant information to designers. Here, we developed and implemented a system capable of calculating and analyzing jerk in real-time based on orientation data from an off-the-shelf head-worn display. An experiment was then carried out to determine whether the presence of AR user interface annotations results in changes to users’ angular head jerk when conducting a time-pressured visual search task. Analysis of the data indicates that a decrease in jerk is significantly associated with the use of AR augmentations. As noted in the limitations section, however, the conclusions drawn from this work should be limited, as this analysis method is novel in the VR/AR space and because of methodological limitations that limited the reliability of the jerk data. The work presented herein considerably facilitates the use of jerk as a quick component measure of usability and serves as an initial point off which future research involving jerk in VR and AR can be performed.
- Can a Patient's In-Hospital Length of Stay and Mortality Be Explained by Early-Risk Assessments?Azadeh-Fard, Nasibeh; Ghaffarzadegan, Navid; Camelio, Jaime A. (PLOS, 2016-09-15)Objective To assess whether a patient’s in-hospital length of stay (LOS) and mortality can be explained by early objective and/or physicians’ subjective-risk assessments. Data Sources/Study Setting Analysis of a detailed dataset of 1,021 patients admitted to a large U.S. hospital between January and September 2014. Study Design We empirically test the explanatory power of objective and subjective early-risk assessments using various linear and logistic regression models. Principal Findings The objective measures of early warning can only weakly explain LOS and mortality. When controlled for various vital signs and demographics, objective signs lose their explanatory power. LOS and death are more associated with physicians’ early subjective risk assessments than the objective measures. Conclusions Explaining LOS and mortality require variables beyond patients’ initial medical risk measures. LOS and in-hospital mortality are more associated with the way in which the human element of healthcare service (e.g., physicians) perceives and reacts to the risks.
- Capturing multi-stage fuzzy uncertainties in hybrid system dynamics and agent-based models for enhancing policy implementation in health systems researchLiu, Shiyong; Triantis, Konstantinos P.; Zhao, Li; Wang, Youfa (PLOS, 2018-04-25)Background In practical research, it was found that most people made health-related decisions not based on numerical data but on perceptions. Examples include the perceptions and their corresponding linguistic values of health risks such as, smoking, syringe sharing, eating energy-dense food, drinking sugar-sweetened beverages etc. For the sake of understanding the mechanisms that affect the implementations of health-related interventions, we employ fuzzy variables to quantify linguistic variable in healthcare modeling where we employ an integrated system dynamics and agent-based model. Methodology In a nonlinear causal-driven simulation environment driven by feedback loops, we mathematically demonstrate how interventions at an aggregate level affect the dynamics of linguistic variables that are captured by fuzzy agents and how interactions among fuzzy agents, at the same time, affect the formation of different clusters(groups) that are targeted by specific interventions. Results In this paper, we provide an innovative framework to capture multi-stage fuzzy uncertainties manifested among interacting heterogeneous agents (individuals) and intervention decisions that affect homogeneous agents (groups of individuals) in a hybrid model that combines an agent-based simulation model (ABM) and a system dynamics models (SDM). Having built the platform to incorporate high-dimension data in a hybrid ABM/SDM model, this paper demonstrates how one can obtain the state variable behaviors in the SDM and the corresponding values of linguistic variables in the ABM. Conclusions This research provides a way to incorporate high-dimension data in a hybrid ABM/SDM model. This research not only enriches the application of fuzzy set theory by capturing the dynamics of variables associated with interacting fuzzy agents that lead to aggregate behaviors but also informs implementation research by enabling the incorporation of linguistic variables at both individual and institutional levels, which makes unstructured linguistic data meaningful and quantifiable in a simulation environment. This research can help practitioners and decision makers to gain better understanding on the dynamics and complexities of precision intervention in healthcare. It can aid the improvement of the optimal allocation of resources for targeted group (s) and the achievement of maximum utility. As this technology becomes more mature, one can design policy flight simulators by which policy/intervention designers can test a variety of assumptions when they evaluate different alternatives interventions.
- The CCP Selector: Scalable Algorithms for Sparse Ridge Regression from Chance-Constrained ProgrammingXie, Weijun; Deng, Xinwei (2018-06-11)Sparse regression and variable selection for large-scale data have been rapidly developed in the past decades. This work focuses on sparse ridge regression, which considers the exact $L_0$ norm to pursue the sparsity. We pave out a theoretical foundation to understand why many existing approaches may not work well for this problem, in particular on large-scale datasets. Inspired by reformulating the problem as a chance-constrained program, we derive a novel mixed integer second order conic (MISOC) reformulation and prove that its continuous relaxation is equivalent to that of the convex integer formulation proposed in a recent work. Based upon these two formulations, we develop two new scalable algorithms, the greedy and randomized algorithms, for sparse ridge regression with desirable theoretical properties. The proposed algorithms are proved to yield near-optimal solutions under mild conditions. In the case of much larger dimensions, we propose to integrate the greedy algorithm with the randomized algorithm, which can greedily search the features from the nonzero subset identified by the continuous relaxation of the MISOC formulation. The merits of the proposed methods are elaborated through a set of numerical examples in comparison with several existing ones.