Single-valued Index Research Articles

A unified framework for creating soundscape perception indices based on the SSID Protocol

The soundscape approach provides a basis for considering the holistic perception of sound environments, in context. While steady advancements have been made in methods for assessment and analysis, a gap exists for comparing soundscapes and quantifying improvements in the multi-dimensional perception of a soundscape. To this end, there is a need for the creation of single value indices to compare soundscape quality which incorporate context, aural diversity, and specific design goals. Just as a variety of decibel-based indices have been developed for various purposes (e.g., LAeq, LCeq, L90, Lden, etc.), the soundscape approach requires the ability to create novel indices for different uses, but which share a common language and understanding. We therefore propose a unified framework for creating both bespoke and archetypal single index measures of soundscape perception based on the soundscape circumplex model, allowing for new indices to be defined in the future. The implementation of this framework is demonstrated through the creation of a public space typology-based index using survey data collected under the SSID Protocol. Indices developed under this framework can enable a broader and more efficient application of the soundscape approach in design, planning, and regulation.

Random site percolation on honeycomb lattices with complex neighborhoods.

We present a rough estimation-up to four significant digits, based on the scaling hypothesis and the probability of belonging to the largest cluster vs the occupation probability-of the critical occupation probabilities for the random site percolation problem on a honeycomb lattice with complex neighborhoods containing sites up to the fifth coordination zone. There are 31 such neighborhoods with a radius ranging from one to three and containing 3-24 sites. For two-dimensional regular lattices with compact extended-range neighborhoods, in the limit of the large number z of sites in the neighborhoods, the site percolation thresholds p follow the dependency p ∝ 1 / z, as recently shown by Xun et al. [Phys. Rev. E 105, 024105 (2022)]. On the contrary, non-compact neighborhoods (with holes) destroy this dependence due to the degeneracy of the percolation threshold (several values of p corresponding to the same number z of sites in the neighborhoods). An example of a single-value index ζ = ∑ i z r-where z and r are the number of sites and radius of the ith coordination zone, respectively-characterizing the neighborhood and allowing avoiding the above-mentioned degeneracy is presented. The percolation threshold obtained follows the inverse square root dependence p ∝ 1 / ζ. The functions boundaries() (written in C) for basic neighborhoods (for the unique coordination zone) for the Newman and Ziff algorithm [Phys. Rev. E 64, 016706 (2001)] are also presented. The latter may be useful for computer physicists dealing with solid-state physics and interdisciplinary statistical physics applications, where the honeycomb lattice is the underlying network topology.

Spatial localization characteristics impact research at value determining of real estate objects situated in small settlements

The article behaves to the property economic measurements implementation using the Comparative Sales independent valuation approach. On example from the real commercial real estate evaluation practice the main methodological principles of valuation object spatial localization characteristics adjustment are considered. According to the described methodology, localization adjustment coefficient is determined by calculation method on the basis of market data cross-correlation regressive analysis. A basic hypothesis is a statement that the relation of valuation object single unit value index to the same of comparable object is determined by its model values relation in the mathematical model of statistical relationship between object single unit value index and its three settlements characteristics: population number; distance to the regional center; area (territory within the settlement boundaries). The research is grounded on mathematical simulation and mathematical statistic quantitative methods. The methodology of adjustment coefficients on investigated price-forming factors definition is based on nonlinear cross-correlation regressive analysis of market data research. This mathematical model is experimentally set by local market data research for the exactly similar real estate objects on the valuation date. It is set that there is observed different statistical relationship level between some of objects price-forming factors and its single square value indexes. The closest statistical relationship exists between settlements population number and single indicator of similar property situated in other compared settlements. It is shown that taking into account some recommended braking coefficients for regressive curve, are published in professional literature, is inadvisable, because it increases the result error is got. Certainly the regression curve characteristics of object spatial localization price-forming factors must be taken into account at adjustment coefficient determination procedure. It is well-proven that methodically correct result of object localization adjustment procedure implementation can be provided only in the case of local market situation research data applying, with determination of the nonlinear regression function characteristics for statistical dependence of single square value index from the object settlements population number. Research is described gives an opportunity to decrease evaluation result uncertainty through the use of new offered approach to mathematical model characteristics definition. The main result of researches described is a possibility to obtain appraising/valuation results with the higher reliability and better accuracy. Researches results are the objective confirmation of the fact, that nowadays methodical base of independent valuation is not able to provide the higher level of this class evaluation objects accuracy results. It does not depend only from an individual appraiser or concrete evaluation company, but, firstly, from unreliable arbitrarily chosen by appraisers adjustments - that usually are "expertly" determined, based on appraiser's own ideas about the dependence of real estate prices on the settlements characteristics. This elementary way of taking these characteristics into account may be a source of result additional errors and its uncertainty level increasing. Future investigations in this direction may deals with the consideration and analysis of other types nonlinear functions application possibilities, that is approximate the regression curve of statistical interdependence between the object single value index and its spatial localization characteristics. The quantitative indexes of absolute and relative methodological errors also may be determined and analyzed in detail in future researches. The importance of those researches for the further development of the independent valuation metrological-information paradigm are confirmed. Practical recommendations for the evaluation results accuracy and reliability increasing are formulated.

Spatial distribution and risk assessments due to the microplastics pollution in sediments of Karnaphuli River Estuary, Bangladesh

Microplastics (MPs) have become an emerging global pollutant due to their widespread dispersion and potential threats to marine ecosystems. However, studies on MPs in estuarine and coastal ecosystems of Bangladesh are very limited. Here, we conducted the first study on abundance, distribution, characteristics, and risk assessment of microplastics in the sediment of Karnaphuli River estuary, Bangladesh. Microplastic particles were extracted from sediments of 30 stations along the estuary by density separation and then enumerated and characterized using a stereomicroscope and Fourier Transform Infrared (FT-IR) spectroscopy. In the collected sediment of the Karnaphuli River estuary, the number of MPs varied from 22.29 to 59.5 items kg−1 of dry weight. The mean abundance was higher in the downstream and left banks of the estuary, whereas the predominant shape, colour, and size of MPs were films (35%), and white (19%), and 1–5 mm (30.38%), respectively. Major polymer types were polyethylene terephthalate, polystyrene, polyethylene, cellulose, and nylon. MPs were found to pose risks (low to high) in the sediment of the estuary, with the highest risk occurring at one station near a sewage outlet, according to the results of risk analyses using the pollution risk index, polymer risk index (H), contamination factors, and pollution load index (PLI). The single value index, PLI, clearly demonstrated that all sampling sites were considerably polluted with microplastics (PLI > 1). H values showed toxic polymers, even in lower proportions, possess higher polymeric hazard scores and vice versa. This investigation uncovered new insights on the status of MPs in the sediments of the Karnaphuli River estuary, laying the groundwork for future research and control of microplastic pollution and management.

Evaluating the destination management performance of small islands with the fuzzy best-worst method and fuzzy simple additive weighting

ABSTRACT This work combines the fuzzy best-worst method for assigning weights of indicators and the fuzzy simple additive weighting method for evaluating performance, along with the TALC model, in generating a single-valued index that would holistically describe the performance of a destination (e.g. small islands). Grounded on a real-world application, the evaluation process proved useful in evaluating the performance of Bantayan Island (Philippines), with a high degree of flexibility in dealing with variations of domain applications with different groups of decision-makers in different settings. The findings, although highly case-specific, offer starting points of discussion in managing small island destinations.

A Methodology of Evaluating Urban Parking System: Case Study of Delhi

A parking study is carried out in the NCT of Delhi to measure the parking system performance for different land-uses. Various parking statistics such as parking demand, demand-capacity (D/C) ratio, parking load, parking efficiency, and utilization are considered to demonstrate the parking conditions and problems at the selected parking locations. Further, four key-indicators viz., D/C ratio, search + park time, walk time and parking fees are chosen to develop parking performance index (PPI) which evaluate the parking facility from users’ perspective. PPI is a single value index, which is estimated by combining the evaluation criteria of the four indicators using a radial coordinate system. PPI is classified into four categories: Excellent, Good, Fair and Poor using clustering analysis in order to define the thresholds for each category. The paper demonstrates the case study application, which describes the applicability of the developed PPI at three locations in Delhi. Lastly, a few parking strategies and guidelines are discussed based on the analysis, on-field survey observations, and past literature. The proposed method can be adopted globally with the required modifications. The study is helpful for the transport planners and policy-makers to quantify the quality of the existing parking system, and the improvement plans can be made accordingly.

Automated real-time damage detection strategy using raw dynamic measurements

Over the last decades, several techniques have been developed in the context of Structural Health Monitoring (SHM) programs. However, when it comes to novelty (or damage) detection, these methods are generally based on human decisions. Moreover, most strategies already published in this topic mainly focus on modal identification procedures and tracking their outputs i.e., structural modal parameters. Such approaches usually lead to high computational costs and can still be insensitive to minor changes in structural behavior, thus missing crucial damage scenarios in their initial manifestations. To circumvent these drawbacks, recent researches showed that the use of symbolic representations derived directly from raw time-domain data (e.g. acceleration measurements) could provide more damage-sensitive responses with lower computational effort. Indeed, good results were achieved by representing raw measurements in terms of their statistical distributions over time. Nevertheless, the lack of information regarding the frequency spectrum represents a decisive drawback. Therefore, this paper presents a novel symbolic object, which considers both time and frequency responses of structural dynamic measurements. The proposed methodology employs a k-medoids clustering over such objects within a moving time-window framework and uses a single-valued index to indicate whether a novelty is present in the acquired data. Numerical simulations and two practical studies – a 3D frame tested in laboratory and a motorway bridge – show that the proposed approach provide an unsupervised and adaptive scheme for SHM applications.

Prediction of spatial-temporal evolution of membrane scaling in spiral wound desalination modules by an advanced simulator

There is no method available at present to determine the spatial-temporal evolution of scale throughout the membranes in desalination plants, although it would be most useful for desalination plant design and monitoring. For such tasks, various approaches are followed to estimate the scaling propensity of feed-water or concentrate, including the use of inadequate single-value indices (e.g. LSI, S&DSI). A novel method is presented herein for simulating spatial-temporal scale evolution. It is based on a comprehensive theoretical model, describing transport phenomena in the spacer-filled channel flow of spiral-wound membrane (SWM) modules, and an experimentally determined correlation (akin to a constitutive relation) of two key parameters of the scaling process; i.e. the depositing salt supersaturation ratio at the membrane surface Sw and the rate of scale-mass deposited per unit membrane area, F g/(m2·h), which represent the driving force and effect of scaling, respectively. Very good agreement is obtained by comparing experimental data from the literature on spatial scale distribution with new computational results. The challenges and priorities are discussed regarding further development of the proposed method as well as applications related to important tasks, such as the design and operation of scale-control and monitoring systems of RO/NF desalination plants.

The transiogram as a graphic metric for characterizing the spatial patterns of landscapes

Landscape metrics play an important role in measurement, analysis, and interpretation of spatial patterns of landscapes. There are a variety of different landscape metrics widely used in landscape ecology. However, existing landscape metrics are mostly non-graphic and single-value indices, which may not be sufficient to describe the complex spatial correlation and interclass relationships of various landscapes. As a transition probability diagram over the lag distance, the transiogram, which emerged in recent years, essentially provides a new graphic metric for measuring and visualizing the auto and cross correlations of landscape categories. To explore the capability of the transiogram for measuring spatial patterns of categorical landscape maps and compare it with existing landscape metrics. Sixteen commonly-used landscape metrics and transiograms (including auto- and cross-transiograms) were estimated and compared for land cover/use classes in four areas with different landscapes. Results show that (1) these transiograms can provide visual information about the proportions, aggregation levels, interclass adjacencies, and intra-class/interclass correlation ranges of landscape classes; (2) sills and auto-correlation ranges of transiograms are correlated with the values of some landscape metrics; and (3) the peak height ratios of idealized transiograms can effectively represent the juxtaposition strength of neighboring class pairs. The transiogram can be an effective graphic metric for characterizing the auto-correlation of single classes (through auto-transiograms) and the complex interclass relationships, such as interdependency and juxtaposition, between different landscape classes (through cross-transiograms).

Multidamage Detection of Bridges Using Rough Set Theory and Naive-Bayes Classifier

This paper is intended to introduce a two-stage detection method to solve the multidamage problem in bridges. Vibration analysis is conducted to acquire the dynamic fingerprints which are regarded as information sources. Bayesian fusion is used to integrate these sources and preliminarily locate the damage. Then, the RSNB method which combines rough set theory and Naive-Bayes classifier is proposed to simplify the sample dimensions and fuse the remaining attributes for damage extent detection. A numerical simulation of a real structure, the Sishui Bridge in Shenyang, China, is conducted to validate the effectiveness of the proposed detection method. Data fusion based method is compared with single-valued index method at the damage localization stage. The proposed RSNB method is compared with the Back Propagation Neural Network (BPNN) method at the damage qualification stage. The results show that the proposed two-stage damage detection method has better performances in regard to transparency, accuracy, efficiency, noise robustness, and stability. Furthermore, an ambient excitation modal test was carried out on the bridge to obtain the vibration responses and assess the damage condition with the proposed method. This novel approach is applicable for early damage detection and provides a basis for bridge management and maintenance.

The effects of atrasentan on urinary metabolites in patients with type 2 diabetes and nephropathy.

We assessed the effect of atrasentan therapy on a pre-specified panel of 13 urinary metabolites known to reflect mitochondrial function in patients with diabetic kidney disease. This post-hoc analysis was performed using urine samples collected during the RADAR study which was a randomized, double-blind, placebo-controlled trial that tested the effects of atrasentan on albuminuria reduction in patients with type 2 diabetes and nephropathy. At baseline, 4 of the 13 metabolites, quantified by gas-chromatography mass spectrometry, were below detectable levels, and 6 were reduced in patients with eGFR < 60 mL/min/1.73 m2 . After 12 weeks of atrasentan treatment in patients with eGFR < 60 mL/min/1.73 m2 , a single-value index of the metabolites changed by -0.31 (95%CI -0.60 to -0.02; P = .035), -0.08 (-12 to 0.29; P = .43) and 0.01 (-0.21 to 0.19; P = .913) in placebo, atrasentan 0.75 and 1.25 mg/d, respectively. The metabolite index difference compared to placebo was 0.13 (-0.17 to 0.43; P = .40) and 0.35 (0.05-0.65; P = .02) for atrasentan 0.75 and 1.25 mg/d, respectively. These data corroborate previous findings of mitochondrial dysfunction in patients with type 2 diabetes, nephropathy and eGFR < 60 mL/min/1.73 m2 , suggesting that atrasentan may prevent the progression of mitochondrial dysfunction common to this specific patient population. Future studies of longer treatment duration with atrasentan are indicated.

Incremental decreases in quality-adjusted life years (QALY) associated with higher levels of depressive symptoms for U.S. Adults aged 65 years and older

BackgroundQuality-adjusted life years (QALY) is a single value index that quantifies the overall burden of disease. It reflects all aspects of heath, including nonfatal illness and mortality outcomes by weighting life-years lived with health-related quality of life (HRQOL) scores. This study examine the burden of disease due to increasing levels of depressive symptoms by examining the association between the 9-item Patient Health Questionnaire (PHQ-9) scores and QALY for U.S. adults aged 65 years and older.MethodsWe ascertained respondents’ HRQOL scores and mortality status from the 2005–2006, 2007–2008, and 2009–2010 cohorts of the National Health and Nutrition Examination Survey (NHANES) with mortality follow-up data through December 31, 2011. This analysis included respondents aged 65 years and older (n = 3,680). We estimated the mean QALY throughout the remaining lifetime according to participants’ depression severity categories: none or minimal (PHQ-9 score 0–4), mild (5–9), moderate (10–14), and moderately severs and severe (15 or higher). We estimated QALY loss due to major depressive disorder (PHQ-9 score 10 or higher) and to mild depression (5–9).ResultsThe QALY for persons with none/minimal, mild, moderate, and moderately severe/severe depression were 14.0, 7.8, 4.7, and 3.3 years, respectively. Compared to persons without major depressive disorder, persons with major depressive disorder had 8.3 fewer QALY (12.7 vs. 4.4), or a 65% loss. Compared to persons who reported “none” or minimal depressive symptoms, persons who reported mild depressive symptoms had 6.2 fewer QALY (14.0 vs. 7.8), or a 44% loss. The same patterns were noted in demographic and socioeconomic subgroups and according to number of comorbidities.ConclusionsThis study not only confirmed the significant burden of disease for major depressive disorder among the U.S. elderly, but also showed an incremental decrease in QALY with an increasing severity of depressive symptoms as well as significant QALY loss due to mild depression. Specifically, individuals with higher (or more impaired) PHQ-9 scores had significantly fewer QALYs and our findings of fewer years of QALY for persons with major depressive disorder and mild depression were not only statistically significant but also clinically important.

Can Rapid Assessments Predict the Biotic Condition of Restored Streams?

Five rapid visual stream assessment methods were applied to 65 restored streams in North Carolina, and the results were correlated with measured macroinvertebrate community metrics to evaluate predictive ability. The USEPA Rapid Bioassessment Protocol (RBP), USDA Stream Visual Assessment Protocol (SVAP), Peterson’s Riparian Channel and Environmental Inventory (RCE), NCSU Eco-Geomorphological Assessment (EGA), and NCSU Stream Performance Assessment (SPA) were applied by teams with expertise in hydrology, fluvial geomorphology, and aquatic ecology. Predictions of most macroinvertebrate metrics were improved by re-weighting assessment variables using principal component analysis (PCA) and including watershed factors (e.g., size, slope, land use). The correlations of EGA, RCE, SPA and SVAP assessment results to macroinvertebrate metrics were most improved by variable re-weighting using PCA, while the correlations of RBP were most improved by adding watershed parameters. Akaike’s Information Criterion (AIC) indicates that PCA re-weighting including watershed parameters improves the predictor model for the total number of dominant EPT taxa more than using the sum total raw points for all five assessment methods. To demonstrate the application of the study results, a single-value index was generated for the RBP method using principal component regression (PCR) based on the EPT (Ephemeroptera, Plecoptera and Trichoptera) taxa metric.

An entrepreneur performance index

A measure of entrepreneur performance is important to identify current and future successful ventures, to further our understanding of the entrepreneurial process and to guide public policies to improve the success rate of start-ups. We propose a single value index of entrepreneur performance that ranges from one to zero, that is predicated on multiple inputs, and that mitigates the impact of outliers. The index is calculated for firms from the Kauffman Foundation Firm Survey for years 2004 through 2009. The average value of the index increases over time as firms either improve their performance or exit the data set due to failure. Survival analysis shows that the index serves as a leading indicator of success, although many additional factors are important.

Identification of Changing Lower Limb Neuromuscular Activation in Parkinson's Disease during Treadmill Gait with and without Levodopa Using a Nonlinear Analysis Index.

Analysis of electromyographic (EMG) data is a cornerstone of research related to motor control in Parkinson's disease. Nonlinear EMG analysis tools have shown to be valuable, but analysis is often complex and interpretation of the data may be difficult. A previously introduced algorithm (SYNERGOS) that provides a single index value based on simultaneous multiple muscle activations (MMA) has been shown to be effective in detecting changes in EMG activation due to modifications of walking speeds in healthy adults. In this study, we investigated if SYNERGOS detects MMA changes associated with both different walking speeds and levodopa intake. Nine male Parkinsonian patients walked on a treadmill with increasing speed while on or off medication. We collected EMG data and computed SYNERGOS indices and employed a restricted maximum likelihood linear mixed model to the values. SYNERGOS was sensitive to neuromuscular modifications due to both alterations of gait speed and intake of levodopa. We believe that the current experiment provides evidence for the potential value of SYNERGOS as a nonlinear tool in clinical settings, by providing a single value index of MMA. This could help clinicians to evaluate the efficacy of interventions and treatments in Parkinson's disease in a simple manner.

Effects of Operation Time of Pavement and Traffic Flow on the Traffic Noise of the Highways in an Urban Area

In developed as well as less developed countries, traffic noise is one of the main sources of societal noise pollution. In this research, a series of field experiments are conducted on highways with new and old pavements. The variations of the traffic flow and traffic noise pressure levels together with the functional relationship between them are analyzed based on the noise data collected from the highways in an urban area. With the collected data, the maximum traffic flow and traffic noise pressure levels are determined in a time specified manner. Logarithmic functional relationships are found between the traffic noise pressure level and traffic flow for both the old and new pavements. It is also found in the research, the improvement in the road re-pavement may promote the absorption of the traffic noise. A single value index is developed for quantitatively and conveniently evaluating the acoustic quality of highways. The findings in this research may give some inspiration for construction and management of low noise highways.

Surf Hazard Rating: A Decision-making System for Application to Competition through the Surf Zone

McCoy, G.K. and de Mestre, N.J., 2014. Surf hazard rating: a decision-making system for application to competition through the surf zone.This paper introduces and details a new and universal Surf Hazard Rating system for rating the prevailing surf conditions at any beach in real time. The system uses primarily seven easily observable and measurable surf zone characteristics. These basic characteristics are defined and rated separately in terms of their potential risk to the safety of competitors within the surf zone. They aggregate to form an overall rating of the hazardous nature of the prevailing surf conditions. The Surf Hazard Rating is the first of two components that, when compared, will form the Competitor Surf Safety Index. This will be a single-value index to assist decision makers and competitors assess the appropriateness of continuing in the prevailing surf conditions at the time. The system has applications for surf sport participants and the beach-going public all over the world, but is being applied at present to Australian surf carnival events.

Baseline-free real-time assessment of structural changes

This article addresses the subject of data-driven structural health monitoring and proposes a real-time strategy to conduct structural assessment without the need to define a baseline period, in which the monitored structure is assumed healthy and unchanged. Independence from baseline references is achieved using unsupervised discrimination machine-learning methods, widely known as clustering algorithms, which are able to find groups in data relying only on their intrinsic features and without requiring prior knowledge as input. Real-time capability is based on the definition of symbolic data, which allows describing large amounts of information without loss of generality or structural-related information. The efficiency of the proposed methodology is illustrated using an experimental case study in which structural changes were imposed to a suspended bridge during an extensive rehabilitation programme. A single-value novelty index capable of describing multi-sensor data is proposed, and its effectiveness in identifying structural changes in real time, using outlier analysis, is discussed.

Quantifying interspecific spatial overlap in aquatic macrophyte communities

Levins’s asymmetrical α index quantifies between species overlap over resources more realistically than similar-purpose single-value indices. The associated community-wide \(\bar \alpha\) index expresses the degree of “species packing”. Both indices were formulated upon competing animal (i.e., mobile) organisms and are independent of population densities. However, overlap over resources for nonmobile organisms such as plants may have an impact even below carrying capacity. The proposed \(\hat \alpha\) index, based on Levins’s α index, quantifies spatial overlap for plants integrating information on species spatial distribution and crowding conditions. The \(\hat \alpha\) index is specifically designed for plant distribution data collected in discrete plots with density expressed as percent coverage (%cover) of substratum. We also propose a community-wide \({\hat \alpha_{\text{c}}}\) index, conceptually analogous to \(\bar \alpha\), but furnished with a measure of dispersion (se \({\hat \alpha_{\text{c}}}\)). Species importance within the community is inferred from comparisons of pairwise \(\hat \alpha\)’s with \({\hat \alpha_{\text{c}}}\). The \(\hat \alpha\) and \({\hat \alpha_{\text{c}}}\) indices correlate closely and exponentially with plant density, and correct apparent over- and underestimations of interaction intensity at low and very high crowding by Levins’s α and \(\bar \alpha\), respectively. Index application to aquatic plant communities gave results consistent with within-community and general ecological patterns, suggesting a high potential of the proposed \(\hat \alpha\) and \({\hat \alpha_{\text{c}}}\) indices in basic and applied macrophyte ecological studies and management.

SU-E-J-105: Applying Fuzzy Similarity Index and Ground Truth Fuzzy Contour to Evaluate the Segmentation Accuracy

Purpose: To evaluate the segmentation accuracy by using our novel Fuzzy Similarity Index (FSI) and Ground Truth Fuzzy Contour (GTFC) with the consideration of inter-and intra-observer variation Methods: We developed GTFC to build consensus truth segmentation(contour) and FSI to score segmentation for an objective and quantitative evaluation of in-vivo medical image segmentation. GTFC is built by applying Fuzzy theory to consider with inter-and intra-observer variation. GTFC has the Fuzzy Membership Function(FMFn) which can assign a weight to each expert depending on their experience, unlike STAPLE. By using GTFC, we formulate a quantitative scoring index to evaluate the segmentation accuracy.When a test segmentation is evaluated, we calculate the membership value of FMFn at every point in the test segmentation(contour). Then, we can make a distribution of membership value as Membership Score Histogram(MSH). We enhanced FSI to make more responsive. While generating a single value index(FSI) from MSH, we adopt the strategy of penalizing lower membership values. The resultant FSI equation is formulated by combining MSH with a penalty constant. We tested the FSI by applying to a brain case. Ten experts segmented a region in the brain and six non-experts independently delineated the same place. GTFC was created from segmentations of expert to evaluate the accuracy of segmentations of non-experts. Then, we calculated FSI after making a MSH per test segmentation. Results: The order in higher similarity to GTFC is non-expert 6, 1, 5, 2, 3, and 4. Non-expert 2, 3, and 4 are significantly deviated from GTFC. Their FSIs are 0.845, 0.476, 0.125, 0.085, 0.078, and 0.005, respectively. Conclusions:FSI can sensitively reflect the accuracy of test segmentation. It can be used to develop unbiased educational tools or credential process for clinicians. It can be also used to evaluate the performance of automated segmentation tools.