Quantitative Performance Measures Research Articles

Fitness of product and service design for closed-loop material recycling: A framework and indicator

Material recycling is the most common strategy in various circular economy concepts. However, material quality generally degrades during recycling because materials get contaminated or some substances dissipate. This translates to that materials are instead recycled in an open loop, or in other words, in a cascade. Current quantitative performance measurement approaches insufficiently address a clear distinction between closed-loop and open-loop recycling. To effectively preserve material quality, a different measurement approach is required to assess the ability of product and service design to retain material quality during material recycling. Such a metric is introduced here with the fitness for closed-loop material recycling indicator Θ. This kind of quality assessment requires a criterion based on the elemental composition of the materials. The concept is illustrated in a case study on metals embodied in a residential gas heating appliance showing that the closed-loop recycling potential of such an appliance is only 1%.

Conjugate mixed convection heat transfer with internal heat generation in a lid-driven enclosure with spinning solid cylinder

The current study investigates conjugate mixed convection heat transmission with internal heat generation in a square enclosure driven by a sliding lid and a solid cylinder with a heat-conducting surface at its center. The enclosure has a stationary bottom wall that is kept at a constant hot temperature and a cold upper wall that moves consistently. The solid cylinder rotates both clockwise and counterclockwise at different angular speeds. Two-dimensional steady continuity, momentum, thermal energy equations, and boundary and interface conditions are solved using a commercial CFD tool based on the finite element method. By choosing Reynolds, Grashof, and Richardson numbers, as well as varying the rotating cylinder's speed and direction under three different scenarios incorporating volumetric heat generation, parametric modeling of the mixed convection regime is carried out. The streamline and isotherm plots are used to illustrate qualitative findings. In contrast, the average Nusselt number, normalized Nusselt number, average drag coefficient, and average fluid temperature are used to assess quantitative thermal performance measures. This study reveals that the system's thermal performance is less dependent on the solid cylinder's rotational speed and direction. It successfully depicts the heat transfer enhancement with increasing Reynolds and Grashof numbers. A thorough study of the current facts can lead to the best choice of regulating parameters.

Influence of heat generation/absorption on mixed convective flow in a lid-driven chamber with isothermal rotating cylinder

The current study explores mixed convection heat transfer and internal heat generation in a lid-driven square chamber with an isothermal cylinder rotating in the middle. The top edge of the chamber moves continuously and maintains the ambient temperature, whereas the bottom edge is immobile and heated at a constant temperature. The cylinder rotates at a fixed velocity in the clockwise direction. Parametric simulation is carried out by adjusting Reynolds (31.623 to 316.23), Grashof (103 to 105), and Richardson numbers (0.1 to 10) as well as the internal heat generation coefficient (10, 0, −10) along with a fixed speed ratio of the rotating cylinder. The quantitative thermal performance measurements are evaluated in terms of average Nusselt number, normalized Nusselt number, average drag coefficient on the sliding lid, and average fluid temperature of the chamber. At the same time, illustrations of streamlines and isotherms plots represent the qualitative findings. The existing detailed data can be used to determine the best design of the controlling parameters.

Topology Optimization of Thermal Insulators considering Thermal–Structural Multi-Objective Function

This study develops a two-dimensional design sensitivity analysis and topology optimization method for multi-objective problems considering both thermal insulation and structural stiffness. The objective function is defined by introducing a weight factor that combines the thermal total energy and compliance for the thermal and structural problems. The derived design sensitivities are validated using the finite difference sensitivities. The Pareto front for designing thermal insulation is obtained by varying the weight function of the objective function and size of the domain. This meant that the geometric feature of the thermal bottleneck outweighed the load-supporting structures as the relative importance of the thermal insulation increased. Compared with the existing designs, the obtained designs are both structurally reliable and thermally insulative in terms of quantitative performance measures.

Risk-informed evaluation of tsunami evacuation risk mitigation strategies

ABSTRACT This paper proposes the risk-informed evaluation of different tsunami evacuation risk mitigation strategies to facilitate the identification of effective strategies that are robust to uncertainties. The tsunami evacuation risk (in terms of casualty rate) is used as a quantitative performance measure to compare different mitigation strategies. An improved agent-based model is used to simulate the tsunami evacuation. A simulation-based framework is used to quantify the tsunami evacuation risk, and various uncertainties associated with the evacuation are explicitly considered. Sensitivity analysis is performed to identify critical risk factors and guide the selection of candidate mitigation strategies. The concepts of importance sampling and augmented sample-based approach are used to efficiently evaluate the evacuation risk under different candidate strategies. The risk-informed evaluation of mitigation strategies is illustrated for the tsunami evacuation in Seaside, Oregon, where strategies such as route widening, bridge retrofit, building vertical shelter, preparedness education, and evacuation drill are compared.

Supervision of Surgical Trainees During Operative Procedures: Implementation of a Formal Preoperative Surgical Checklist.

Background Trainers in surgery have an educational obligation to train trainees in performing operative procedures. Objective We hypothesized that poor concordance manifests as discrepancies between the trainee and the trainer, with an associated reduction in satisfaction with the training experience, perception of training quality, and completion of workplace-based assessments (WBAs). This study also aimed to validate the novel Supervised Training Operative Procedure (STOP) online tool. Method We developed an online proforma (STOP online tool) and conducted a prospective, single-blinded study of 53 orthopedic operative procedures with 53 traineesbetween January 19, 2019, and August 27, 2019. Results Forty-four (82%) trainees were listed as the primary surgeon. The overall mean trainee satisfaction (on a 0-10 Likert scale) was 8.25 (range: 3-10), and the mean trainer satisfaction was 8.28 (range: 4-10). A preoperative discussion between the trainee and the trainer occurred in 96.2% of the cases. Forty-eight (91%) trainers preoperatively established trainees' objectives and 91% (n = 48) of the cases showed postoperative completion of objectives. Forty-four (83%) trainers anticipated workplace-based assessment(WBA) completion for trainees, and this translated into 41 (77%) completed WBAs. Overall, 47 (92.9%) trainees felt that the STOP tool would be useful as a surgical training checklist and in the completion of WBAs. Conclusion The STOP checklist is useful in understanding qualitative and quantitative measures of the overall trainee performance of an operative case. This holistic approach will enable us to establish a structured perioperative surgical training checklist, as trainee and trainer requirements are dependent on one another.

Segmentation of mammogram images using level set with Cuckoo search optimisation

ABSTRACT Breast cancer is alone accounted for 30% of all new cancer diagnoses for women. Early identification of breast cancer is a key stage in the process of diagnosis and treatment. Segmenting of low contrast mammograms is not an easy task due to irregular mass form, speculated margins and variation in intensity levels. Most of the region-based technique works well for homogenous images but fails for intensity inhomogeneity. Multiphase level set segmentation is optimised by the cuckoo search approach for energy minimisation. The proposed multiphase level set with the cuckoo optimisation method performs well in segmenting homogeneous as well as inhomogeneous regions. The Chan Vese (CV) and the proposed method are applied to the Mammographic Image Analysis Society (MIAS) database to obtain the accurate contour of the masses. To validate the proposed approach using quantitative performance measures such as Jaccard coefficient (JC), dice coefficient (DC), Hausdorff distance (Hd), sensitivity, specificity and accuracy were used for the MIAS data set. The results indicate that the suggested method can successfully segment the breast mass in mammograms and more robust than the classical CV method.

Statistical modeling of health space based on metabolic stress and oxidative stress scores

BackgroundHealth space (HS) is a statistical way of visualizing individual’s health status in multi-dimensional space. In this study, we propose a novel HS in two-dimensional space based on scores of metabolic stress and of oxidative stress.MethodsThese scores were derived from three statistical models: logistic regression model, logistic mixed effect model, and proportional odds model. HSs were developed using Korea National Health And Nutrition Examination Survey data with 32,140 samples. To evaluate and compare the performance of the HSs, we also developed the Health Space Index (HSI) which is a quantitative performance measure based on the approximate 95% confidence ellipses of HS.ResultsThrough simulation studies, we confirmed that HS from the proportional odds model showed highest power in discriminating health status of individual (subject). Further validation studies were conducted using two independent cohort datasets: a health examination dataset from Ewha-Boramae cohort with 862 samples and a population-based cohort from the Korea association resource project with 3,199 samples.ConclusionsThese validation studies using two independent datasets successfully demonstrated the usefulness of the proposed HS.

Decoding ‘Maximum Entropy’ Deconvolution

For over five decades, the mathematical procedure termed “maximum entropy” (M-E) has been used to deconvolve structure in spectra, optical and otherwise, although quantitative measures of performance remain unknown. Here, we examine this procedure analytically for the lowest two orders for a Lorentzian feature, obtaining expressions for the amount of sharpening and identifying how spurious structures appear. Illustrative examples are provided. These results enhance the utility of this widely used deconvolution approach to spectral analysis.

The influence zone: a critical performance measure for negative pressure wound therapy systems.

This article provides an introduction to the theory of, what is termed, the 'influence zone' in the context of negative pressure wound therapy (NPWT). It is a quantitative bioengineering performance measure for NPWT systems, to indicate their effectiveness, namely, how far from the wound bed edges a specific system is able to deliver effective mechano-stimulation into the periwound, and at which intensity. The influence zone therefore provides objective and standardised metrics of one of the fundamental modes of action of NPWT systems: the ability to effectively and optimally deform both the wound and periwound macroscopically and microscopically. Most important is the mechanical deformation of the periwound area to activate cells responsible for tissue repair, particularly (myo)fibroblasts. Notably, the influence zone must extend sufficiently into the periwound to stimulate (myo)fibroblasts in order that they migrate and progress the wound healing process, facilitating the formation of scar tissue, without overstretching the periwound tissues so as not cause or escalate further cell and tissue damage. The inclusion of the influence zone theory within research to investigate the efficacy of NPWT systems facilitates systematic comparisons of commercially available and potentially new systems. This approach has the capacity to guide not only research and development work, but also clinical decision-making. Recently published research found that inducing an effective influence zone first and foremost requires continuous delivery of the intended pressure to the wound bed.

Balancing incremental and radical innovation through performance measurement and incentivization

The literature has discussed the introduction of incentive structures as a means of achieving a balance between organizational exploration and exploitation. This study posits that this is not a reasonable approach to achieving such a balance. I used a micro-economic model where the explorative and exploitative activities are modeled in accordance with the definitions in March (1991). This model shows that the personal cost to the employee of performing activities was a crucial factor in determining their balancing of resources between exploration and exploitation. However, these personal costs are also the Achilles' heel of such balance calculations because information regarding this type of cost is incomplete and difficult, perhaps even impossible, for the owner or manager to obtain. Based on this and the process and output characteristics of exploratory activities, I argue that it is not appropriate to design a hard, quantitative performance measurement and incentive system to balance resource allocation between explorative and exploitative activities. The study shows that the solution to achieving such a balance must be found outside of the incentive system. Further, I posit that managing R&D departments requires the management to focus on enforcing productive workspaces and norms and not on performance measurement and associated disbursal of rewards/punishments.

Mathematical models of human memory

Human memory is an incredibly complex system of vast capacity but often unreliable. Measuring memory for realistic material, such as narratives, is quantitatively challenging as people rarely remember narratives verbatim. Cognitive psychologists developed experimental paradigms involving randomly collected lists of items that make possible quantitative measures of performance in memory tasks, such as recall and recognition. Here, we describe a set of mathematical models designed to predict the results of these experiments. The models are based on simple underlying assumptions and surprisingly agree with experimental results quite well, in addition to that they exhibit quite interesting mathematical behavior that can partially be understood analytically.

China’s Leadership in BRICS Governance

The BRICS is an international summit institution that provides a platform for the world’s leading emerging economies to discuss issues of global governance from a development-centered perspective. This article examines of China’s leadership role in the BRICS, drawing on quantitative indicators of China’s performance within the BRICS since its first summit in 2009, to the most recent summit in 2021. This arti cle also develops a model of leadership based on quantitative performance measures of deliberation, decision-making, and compliance. This analysis shows that China is predominantly a facilitative and exemplary leader. Its leadership focuses on shaping BRICS discussions on its priority subjects, particularly development and macroeconomics, in addition to leading by positive example through achieving high compliance with its summit commitments.

A novel equilibrium optimized double-loop control scheme for unstable and integrating chemical processes involving dead time

Abstract Integrating and unstable chemical processes showcase instability in open-loop configuration due to the existence of poles at the origin and right-half of the s-plane. They present challenging control requirements due to their non-self-regulating nature. The presence of dead time demands more sophisticated control requirements for the above-mentioned processes. So double-loop control strategies are preferred over PID controllers in single-loop configuration. In this work, a novel IMC-PD double-loop control strategy is proposed for unstable and integrating plants with dead time. The inner-loop consists of PD controller whose initial settings are derived using Routh–Hurwitz stability conditions. The outer-loop consists of an IMC controller whose parameter along with that of the PD controller is optimized using the metaheuristic algorithm called equilibrium optimizer algorithm (EOA). EOA utilizes the range of controller settings from RH criteria for stable operation and provides the optimal settings by minimizing the integral square error (ISE). Merits of the suggested strategy is illustrated with the help of benchmark plant models of unstable/integrating chemical processes and that of a bioreactor. By computing quantitative performance measures, the dynamic responses resulting from the proposed control scheme is found to be more effective than the reported works.

Deep neural networks and image classification in biological vision

In this paper we consider recent advances in the use of deep convolutional neural networks to understanding biological vision. We focus on claims about the plausibility of feedforward deep convolutional neural networks (fDCNNs) as models of image classification in the biological system. Despite the putative similarity of these networks to some properties of the biological vision system, and the remarkable levels of performance accuracy of some fDCNNs, we argue that their plausibility as a framework for understanding image classification remains unclear. We highlight two key issues that we suggest are relevant to the evaluation of any form of DNN used to examine biological vision: (1) Network transparency under analysis – that is, the challenge of understanding what networks do, and how they do it. (2) Identifying appropriate benchmarks for comparing network performance and the biological system using both quantitative and qualitative performance measures. We show that there are important divergences between fDCNNs and biological vision that reflect fundamental differences in computational architectures, and representational structures, supporting image classification in these networks and the biological system.

Participatory design and evaluation of virtual reality physical rehabilitation for people living with dementia

Emerging research confirms the need for technologically enhanced solutions to support non-pharmacological interventions which can improve the quality of life, the mental and physical health of demented people. Several types of research examined if virtual reality can be an effective solution. This paper aims to present the cyclic process of prototyping, testing, analysing, and refining the VR system in real-world clinical settings. Seven people with moderate to severe dementia were recruited. The experiment required the patients to attend three virtual reality iterations of rapid prototyping with user testing. All three iterations involved training activities with upper body movements similar to their usual physical training. A mixed-methods design measured affect and emotional behaviour using the Observed Emotion Rating Scale and the Visual Analog Scale. Content analysis was conducted following observations and interviews. During each iteration of rapid prototyping with user testing, quantitative measurements of performance, independence and time were recorded. Eye tracking and movement information were captured by the system. Finally, a simplified version of the presence and usability scales evaluated the system. The results of this study provide further evidence that virtual reality can play a significant role in the improvement of people’s with dementia physical training and emotional health when is appropriately designed. The results present the vital factors which should be incorporated in a virtual reality system which are: 1) a simple interactions modality; 2) visible visual targets and continuous feedback; 3) personalized virtual environments; 4) personalized range of movements.

Pearls of wisdom for aspiring physician-scientist residency applicants and program directors.

Postgraduate physician-scientist training programs (PSTPs) enhance the experiences of physician-scientist trainees following medical school graduation. PSTPs usually span residency and fellowship training, but this varies widely by institution. Applicant competitiveness for these programs would be enhanced, and unnecessary trainee anxiety relieved, by a clear understanding of what factors define a successful PSTP matriculant. Such information would also be invaluable to PSTP directors and would allow benchmarking of their admissions processes with peer programs. We conducted a survey of PSTP directors across the US to understand the importance they placed on components of PSTP applications. Of 41 survey respondents, most were from internal medicine and pediatrics residency programs. Of all components in the application, two elements were considered very important by a majority of PSTP directors: (a) having one or more first-author publications and (b) the thesis advisor’s letter. Less weight was consistently placed on factors often considered more relevant for non-physician-scientist postgraduate applicants — such as US Medical Licensing Examination scores, awards, and leadership activities. The data presented here highlight important metrics for PSTP applicants and directors and suggest that indicators of scientific productivity and commitment to research outweigh traditional quantitative measures of medical school performance.

Decoupled double‐loop FOIMC‐PD control architecture for double integral with dead time processes

AbstractA novel double‐loop control configuration with two controllers is suggested for double integrating processes with dead‐time. The stabilizing range of the inner‐loop proportional‐derivative (PD) controller is obtained using the Routh stability criteria. From this range, the exact PD settings are obtained by following a graphical approach where the integration of absolute error (IAE) is plotted for different PD settings. The PD settings resulting in the minimum IAE are chosen. In addition to stabilizing the plant, the inner‐loop also rejects the disturbances. A fractional‐order internal model controller (FOIMC) is designed for satisfactory set‐point tracking response in the outer‐loop. The suggested strategy has four adjustable parameters (proportional and derivative time constants, outer closed‐loop adjustment parameter, and fractional‐order of the FOIMC low‐pass filter). Based on extensive simulations, the tuning ranges for the above‐mentioned adjustable parameters are specified. The simulation study is done with the help of benchmark double integrating plant models with large dead‐time. Quantitative performance measures are also computed for comparing the suggested and previously reported schemes. The suggested FOIMC‐PD control architecture yields enhanced control performance than some recently reported techniques.

An analytical framework to assess earthquake-induced downtime and model recovery of buildings

While modern seismic design codes intend to ensure life-safety in extreme earthquakes, policy-makers are moving toward performance objectives stated in terms of acceptable recovery times. This article describes a framework to probabilistically model the post-earthquake recovery of buildings and provide quantitative seismic performance measures, expressed in terms of downtime, that are useful for decision-making. Downtime estimates include the time for mobilizing resources after an earthquake and conduct necessary repairs. The proposed framework advances the well-established Federal Emergency Management Agency (FEMA) P-58 and Resilience-based Earthquake Design initiative (REDi) methodologies by modeling temporal building recovery trajectories to target recovery states, such as stability, shelter-in-place, reoccupancy, and functional recovery. The shelter-in-place recovery state accounts for relaxed post-earthquake habitability standards, in contrast with the reoccupancy recovery state that relates to pre-event habitability criteria. Analogous to safety-based codes, which specify a threshold for the probability of collapse under a given ground motion shaking intensity, this framework permits evaluating the probability of a building not achieving a target recovery state, for example, shelter-in-place, immediately after an earthquake, or, alternatively, the probability of achieving a target recovery state, for example, functional recovery, within a specified time frame. The proposed framework is implemented to evaluate a modern 12-story residential reinforced concrete shear wall building in Seattle, WA. The assessment results indicate that under a functional-level earthquake (roughly equivalent to ground motion shaking with a return period of 475 years), the probability of not achieving shelter-in-place immediately after the earthquake is 22%, and the probability of downtime to functional recovery exceeding 4 months is 88%, which far exceeds acceptable thresholds suggested in the 2015 National Earthquake Hazards Reductions Program (NEHRP) guidelines and FEMA P-2090.

Novel measures of Morris water maze performance that use vector field maps to assess accuracy, uncertainty, and intention of navigational searches.

Most commonly used behavioral measures for testing learning and memory in the Morris water maze (MWM) involve comparisons of an animal's residence time in different quadrants of the pool. Such measures are limited in their ability to test different aspects of the animal's performance. Here, we describe novel measures of performance in the MWM that use vector fields to capture the motion of mice as well as their search pattern in the maze. Using these vector fields, we develop quantitative measures of performance that are intuitive and more sensitive than classical measures. First, we describe search patterns in terms of vector field properties and use these properties to define three metrics of spatial memory namely Spatial Accuracy, Uncertainty and, Intensity of Search. We demonstrate the usefulness of these measures using four different data sets including comparisons between different strains of mice, an analysis of two mouse models of Noonan syndrome (NS; Ptpn11 D61G and Ptpn11 N308D/+), and a study of goal reversal training. Importantly, besides highlighting novel aspects of performance in this widely used spatial task, our measures were able to uncover previously undetected differences, including in an animal model of NS, which we rescued with the mitogen activated protein kinase kinase (MEK) inhibitor SL327. Thus, our results show that our approach breaks down performance in the MWM into sensitive measurable independent components that highlight differences in spatial learning and memory in the MWM that were undetected by conventional measures.