New Set Of Metrics Research Articles

A new set of metrics and framework to assess the colonization potential of riverscapes by wind-dispersed plant species

Quantifying the potential of a braided riverscape to be colonized by a plant species is essential for assessing the ecological state of the river and provides an important basis for nature conservation planning and the implementation of restoration measures. Common connectivity indices are largely unsuitable for describing the situation for the mostly wind-dispersed plant species. Our approach provides a set of comparable metrics that allows the quantification of the colonization potential of riverscapes at the patch and riverscape level. We propose a set of cell-based, spatially explicit measures that can easily be implemented. We demonstrate their application using two typical plant species and three riverscapes with different habitat configurations as examples. Our metrics consider shape, size and the spatial configuration of habitat patches, along with the dispersal characteristics of the respective species. The metrics provide a linear, balanced, and realistic representation of the colonization potential at the cell, patch, and riverscape levels. The results are comparable between different riverscapes and species, can be easily extended and used for further modeling. The metrics provide a valuable tool for the planning and evaluation of conservation, restoration, and reintroduction measures and close the gap between habitat availability analyses and large-scale terrestrial connectivity indices.

User centric metrics for a realistic assessment of broadband services

Past broadband adoption initiatives underscored common wisdom: “We cannot manage what we cannot accurately measure”, “Trust but verify”. Self-reported Federal Communications Commission data has been notoriously unreliable or lacking granularity and that led to an overoptimistic perception of the quality and coverage of broadband services. Data collected in the past was deficient in providing a complete view of the user experience by focusing exclusively on a simple metric, bandwidth availability. Moreover, data collected in the past typically provided a point-in-time perspective on the state of broadband services in each region. In this paper, we discuss a new set of metrics and measurement techniques needed to make broadband funding decisions efficient in terms of quality of services delivered and return on investment, and to track their progress. We propose composite metrics that capture the complete value of the service to the user and emphasize the feasibility of measuring and monitoring such a metric over time.

RGB-D-based categorical object pose and shape estimation: Methods, datasets, and evaluation

Recently, various methods for 6D pose and shape estimation of objects at a per-category level have been proposed. This work provides an overview of the field in terms of methods, datasets, and evaluation protocols. First, an overview of existing works and their commonalities and differences is provided. Second, we take a critical look at the predominant evaluation protocol, including metrics and datasets. Based on the findings, we propose a new set of metrics, contribute new annotations for the Redwood dataset, and evaluate state-of-the-art methods in a fair comparison. The results indicate that existing methods do not generalize well to unconstrained orientations and are actually heavily biased towards objects being upright. We provide an easy-to-use evaluation toolbox with well-defined metrics, methods, and dataset interfaces, which allows evaluation and comparison with various state-of-the-art approaches (https://github.com/roym899/pose_and_shape_evaluation).

Design and Development of an Objective Evaluation System for a Web-Based Simulator for Trauma Management.

Trauma injuries are one of the main leading causes of death in the world. Training with guidelines and protocols is adequate to provide a fast and efficient treatment to patients that suffer a trauma injury. This study aimed to evaluate deviations from a set protocol, a new set of metrics has been proposed and tested in a pilot study. The participants were final-year students from the Universidad Autónoma de Madrid and first-year medical residents from the Hospital Universitario La Paz. They were asked to train four trauma scenarios with a web-based simulator for 2 weeks. A test was performed pre-training and another one post-training to evaluate the evolution of the treatment to those four trauma scenarios considering a predefined trauma protocol and based on the new set of metrics. The scenarios were pelvic and lower limb traumas in a hospital and in a prehospital setting, which allow them to learn and assess different trauma protocols. The results show that, in general, there is an improvement of the new metrics after training with the simulator. These new metrics provide comprehensive information for both trainers and trainees. For trainers, the evaluation of the simulation is automated and contains all relevant information to assess the performance of the trainee. And for trainees, it provides valuable real-time information that could support the trauma management learning process.

From consolidation to disruption: A novel way to measure the impact of scientists and identify laureates

This study proposes a novel approach for evaluating the impact of scientists by introducing a new set of metrics and a dual measurement framework that combines the concepts of disruption and consolidation. Traditional metrics like total citation and h-index are limited in their ability to capture the full range of a scientist's influence, and therefore the Scientists' Disruptive Citation (SDC), Disruptive h-index (D h-index), and consolidating metrics are introduced to provide a more comprehensive evaluation of scientists' disruptive and consolidating influence. Using a dataset of 463,348 papers, 234,086 disambiguated scientists, and data on three important awards, including Nobel Prize, Wolf Prize, and Dirac Medal, in the field of Physics, this study demonstrates that the SDC and D h-index are superior to all benchmark metrics, including the conventional and normalized disruption-based measures, in terms of convergent validity. Second, this study analyzes the distribution of academic characteristics between award-winning and non-laureates, explores various metrics of scientists with high SDC and Scientists' Consolidating Citation (SCC), and finds that disruptive impact can identify successful scientists from their counterparts and serve as an early signal of successful scientists. Third, this study reveals that the disruptive citation proposed in this study is less susceptible to manipulation, making it a more reliable metric for assessing a scientist's or a single paper's disruptive impact than the CD-index. The results suggest that the SDC and D h-index are reliable metrics for measuring scientists' innovative influence and can aid in the development of future scientific research. Overall, this study provides a scientifically sound and effective new perspective on measuring scientists using a dual measurement of disruptive and consolidating influence.

Supply-chain-focused measures of centrality and spread in metropolitan areas

Efficient freight transportation is a necessary condition for the economic development of markets in metropolitan areas. Without it, the cost of goods increases, and larger negative externalities are produced, negatively impacting the quality of life. In this context, the efficiency of supply chains is strongly influenced by the spatial patterns of economic activities, given the role that freight transportation plays in connecting the multiple stages of supply chains. The research reported in this paper develops and tests data-driven metrics of centrality and spread of freight activity in metropolitan areas. The approach used in the paper identifies the economic pole(s) in metropolitan areas and computes a new set of metrics to assess the physical separation between consecutive stages of supply chains. Three different metrics were used to identify the economic pole(s): (1) total employment, (2) employment density, and (3) an interaction index based on a gravity model that considers the interchanges among related economic sectors. To estimate the spread of freight activity the authors developed an approximation technique based on a simplified freight distribution model to estimate the average weighted shipment distance for various consecutive stages of supply chains. The proposed methodologies were tested on six metropolitan areas of various sizes. In the concluding section the results obtained by the research effort are discussed, together with the corresponding policy implications.

Key metrics to measure the performance and impact of reusable packaging in circular supply chains

Circular supply chains comprise the industrial production and supply chain systems used by companies to eliminate waste and recover value in products and materials. There are a variety of circular strategies including recycling in waste management, returns and repair in consumer-facing industries, and reusable packaging in supply chains. Successful implementation and management of these circular strategies requires the ability to measure and report on progress across different functions and processes. In this paper, we propose a new set of metrics to measure the performance of reusing items in a circular supply chain. We review the literature on metrics in circular supply chain management and reusable packaging in supply chains. We then classify the proposed metrics based on whether they measure the circularity of a circular supply chain initiative or impact of implementing the initiative. They also are segmented based on the level of detail they incorporate from the product level to the system level. We then demonstrate the use of the proposed metrics through a case study with an omnichannel retail company. We find that product-level metrics facilitate the comparison of different types of reusable and single-use packages with the potential to reduce lifecycle greenhouse gas emissions. We also find that measuring system-level Total Logistics Costs helps identify potential challenges with the feasibility of a reusable packaging system including the implications of not recovering packages and amortizing initial costs across multiple use cycles. Our aim in this paper is to address the gap in circularity and impact metrics focused on reuse strategies in supply chains. This new set of metrics provides companies with a tool to measure and report on progress toward a circular economy. It also suggests future avenues for research to assess the economic, environmental, and social dimensions of sustainability.

Quantitative assessment of helical tomotherapy plans complexity

An unnecessary amount of complexity in radiotherapy plans affects the efficiency of the treatments, increasing the uncertainty of dose deposition and its susceptibility to anatomical changes or setup errors. To date, tools for quantitatively assessing the complexity of tomotherapy plans are still limited. In this study, new metrics were developed to characterize different aspects of helical tomotherapy (HT) plans, and their actual effectiveness was investigated. The complexity of 464 HT plans delivered on a Radixact platform was evaluated. A new set of metrics was devised to assess beam geometry, leaf opening time (LOT) variability, and modulation over space and time. Sixty-five complexity metrics were extracted from the dataset using the newly in-house developed software library TCoMX: 29 metrics already proposed in the literature and 36 newly developed metrics. Their reciprocal relation is discussed. Their effectiveness was evaluated through correlation analyses with patient-specific quality assurance (PSQA) results. An inverse linear relation was found between the average number of closed leaves and the average number of MLC openings and closures as well as between the choice of the modulation factor and the discontinuity of the field, suggesting some intrinsic link between the LOT distribution and the geometrical complexity of the MLC openings. The newly proposed metrics were at least as correlated as the existing ones to the PSQA results. Metrics describing the geometrical complexity of the MLC openings showed the strongest connection to the PSQA results. Significant correlations were found between at least one of the new metrics and the γ index passing rate for six out of seven groups of plans considered. The new metrics proposed were shown to be effective to characterize more comprehensively the complexity of HT plans. A software library for their automatic extraction is described and made available.

The IUCN Green Status of Species: A Call for Mediterranean Botanists to Contribute to This New Ambitious Effort.

In the Mediterranean Basin, a critical focal point for the conservation of plant diversity, there has been a large increase in practical conservation actions for many plant species to prevent extinction and to improve their conservation status; quantifying the effectiveness of these initiatives in reversing species declines is urgently important. In 2021, the International Union for Conservation of Nature (IUCN) launched a new tool that allows the impact of conservation actions on plant species to be assessed. The Green Status of Species is a new set of metrics under the Red List of Threatened Species that assigns species to recovery categories, complementary to the classic extinction risk categories. Crucially, the Green Status of Species provides methods to evaluate the impact of past conservation, and the potential for future conservation impact, on species status and recovery in a standardized way. Considering the efforts made so far for the conservation of Mediterranean threatened plants, using the Green Status of Species would be highly useful to direct future conservation policies. We, therefore, encourage botanists and practitioners working on threatened plants in the Mediterranean area to use this new assessment tool to inform conservation and recovery programs.

3D Enhancement Color Maps in the Characterization of Intracranial Atherosclerotic Plaques.

High-resolution MR imaging allows the identification of culprit symptomatic plaques after the administration of gadolinium. Current high-resolution MR imaging methods are limited by 2D multiplanar views and manual sampling of ROIs. We analyzed a new 3D method to objectively quantify gadolinium plaque enhancement. Patients with stroke due to intracranial atherosclerotic disease underwent 7T high-resolution MR imaging. 3D segmentations of the plaque and its parent vessel were generated. Signal intensity probes were automatically extended from the lumen into the plaque and the vessel wall to generate 3D enhancement color maps. Plaque gadolinium (Gd) uptake was quantified from 3D color maps as gadolinium uptake = (µPlaque T1 + Gd -µPlaque T1/SDPlaque T1). Additional metrics of enhancement such as enhancement ratio, variance, and plaque-versus-parent vessel enhancement were also calculated. Conventional 2D measures of enhancement were collected for comparison. Thirty-six culprit and 44 nonculprit plaques from 36 patients were analyzed. Culprit plaques had higher gadolinium uptake than nonculprit plaques (P < .001). Gadolinium uptake was the most accurate metric for identifying culprit plaques (OR, 3.9; 95% CI 2.1-8.3). Gadolinium uptake was more sensitive (86% versus 70%) and specific (71% versus 68%) in identifying culprit plaques than conventional 2D measurements. A multivariate model, including gadolinium uptake and plaque burden, identified culprit plaques with an 83% sensitivity and 86% specificity. The new 3D color map method of plaque-enhancement analysis is more accurate for identifying culprit plaques than conventional 2D methods. This new method generates a new set of metrics that could potentially be used to assess disease progression.

3D aneurysm wall enhancement is associated with symptomatic presentation

BackgroundAneurysm wall enhancement (AWE) is a potential surrogate biomarker for aneurysm instability. Previous studies have assessed AWE using 2D multiplanar methods, most of which were conducted qualitatively.ObjectiveTo use a new...

A New Goodness of Fit Measure Based on Income Inequality Curves

This paper uses inequality-measurement techniques to assess goodness of fit in income distribution models. It exposes the shortcomings of the use of conventional goodness of fit criteria in face of the big income data and proposes a new set of metrics, based on income inequality curves. In this note, we mentioned that the distance between theoretical and empirical inequality curves can be considered as a goodness of fit criterion. We demonstrate certain advantages of this measure over the other general goodness of fit criteria. Unlike other goodness of fit measures, this criterion is bounded. It is 0 in minimum difference and 1 in maximum distance. Furthermore, there is a consistency between this new goodness of fit measure and the other conventional criteria. A simulation study based on fitted distribution to real income data is performed in order to investigate some statistical properties of the new goodness of fit measure. An empirical study and comparisons are also provided.

Correlations of social media performance and electoral results in Brazilian presidential elections

The use of social media (SM) in modern political activities has reshaped how politicians run electoral campaigns. This study aims to improve the understanding of online campaigns and their correlation with electoral results. We focus on the 2018 Brazilian presidential campaign, which is well known for its strong online presence, and analyze how candidates used their SM profiles, as well as how citizens interacted with them. We propose a new set of metrics for modeling SM performance and identify statistical correlations between SM performance and votes received. For this, we analyzed more than 40,000 posts made by the 13 candidates on Brazil’s three major social networks (Facebook, Twitter, and Instagram) from January to October 2018. Results indicate that candidates used SM heavily throughout the year but focused on engaging words and avoided contentious topics. The most voted-for candidate received more than half (55%) of the interactions received by all the candidates. Posts’ interactions were highest on Instagram, where users were increasing the attention given to political content. Lastly, we found strong correlations between the proposed metrics and votes received. Thus, proposed metrics may support new models for predicting electoral results using combined data from many social networks.

Abstract 1122‐000188: 3D Analysis of Atherosclerotic Plaque Enhancement and the Parent Vessel

Introduction : High resolution vessel wall imaging (HR‐VWI) is a promising tool in studying intracerebral atherosclerotic disease. The analysis of the interplay between the patterns of enhancement between the plaque and its parent vessel can generate further insights on the biology of these lesions. We have developed a 3D method of plaque and parent vessel analysis. Methods : Images from fifty‐five plaques were obtained using 7T HR‐VWI. T1 and T1+Gd sequences were performed. 3D reconstructions of the plaque and its parent vessel were generated with 3D Slicer. Using an in‐house code, probes were orthogonally extended from the lumen of the vessel into the vessel wall and the plaque. Signal intensity values were then normalized to the corpus callosum. 3D heat maps and histograms were generated from hundreds of data points. A detailed analysis of the morphology of the histograms was performed to determine the uptake of gadolinium (Gd) by the parent vessel and the plaque. Variations in the width of the histogram were measured with the standard deviation. Results : Forty‐one patients with 55 plaques (41 culprit and 15 non culprit) were included. There was no difference in enhancement in T1‐pre between culprit and non‐culprit plaques when compared to the parent vessel (width = 0.14 ± 0.05 and 0.14 ± 0.03, respectively; p = 0.91). On the T1+Gd culprit plaques were significantly more enhancing compared to the parent vessel (0.26 ± 0.10) than non‐culprit plaques (0.20 ± 0.06) (p = 0.02). The presence of an enhancing plaque creates a bimodal distribution that increases the width of the histogram curve (figure). Conclusions : Culprit plaques exhibit different patterns of enhancement relative to the parent vessel compared to non‐culprit plaques. Histogram analysis of the parent vessel and its plaques provides a new set of metrics that may be used as a biomarker of disease progression.

Propulsive efficiency and efficacy of a pumping sail

This study presents a framework to analyze the propulsive performance of a sail under oscillatory pumping motion, which should be modified from the analysis framework for conventional flapping wings. A new set of metrics, including the propulsive efficiency ηs and efficacy ΔCx¯, which depend not only on the aerodynamic coefficient but also on kinematic conditions of the sailing vehicle, are proposed to characterize the propulsive performance of sail pumping. The necessity of the proposed metrics is illustrated by studying the propulsive performance of a two-dimensional airfoil under different heaving and kinematic conditions through computational fluid dynamic simulations. It was found that the sail pumping typically improves the propulsive performance by lift enhancement instead of drag reduction. Thus, the formation of leading-edge vortices may not be detrimental to the propulsive efficiency of a pumping sail, contrary to that for flapping wings. A propulsive efficiency greater than unity is achievable under certain sailing conditions because a sailing vehicle can extract energy from the wind.

Complexity Constraint in the Distributor’s Pallet Loading Problem

This paper presents a study on the complexity of cargo arrangements in the pallet loading problem. Due to the diversity of perspectives that have been presented in the literature, complexity is one of the least studied practical constraints. In this work, we aim to refine and propose a new set of metrics to measure the complexity of an arrangement of cargo in a pallet. The parameters are validated using statistical methods, such as principal component analysis and multiple linear regression, using data retrieved from the company logistics. Our tests show that the number of boxes was the main variable responsible for explaining complexity in the pallet loading problem.

Improving Software Defect Prediction by Aggregated Change Metrics

To ensure the delivery of high quality software, it is necessary to ensure that all of its artifacts function properly, which is usually done by performing appropriate tests with limited resources. It is therefore desirable to identify defective artifacts so that they can be corrected before the testing process. So far, researchers have proposed various predictive models for this purpose. Such models are typically trained on data representing previous project versions of a software and then used to predict which of the software artifacts in the new version are likely to be defective. However, the data representing a software project usually consists of measurable properties of the project or its modules, and leaves out information about the timeline of the software development process. To fill this gap, we propose a new set of metrics, namely aggregated change metrics, which are created by aggregating the data of all changes made to the software between two versions, taking into account the chronological order of the changes. In experiments conducted on open source projects written in Java, we show that the stability and performance of commonly used classification models are improved by extending a feature set to include both measurable properties of the analyzed software and the aggregated change metrics.

Quality of sentiment analysis tools

In this paper, we present a comprehensive study that evaluates six state-of-the-art sentiment analysis tools on five public datasets, based on the quality of predictive results in the presence of semantically equivalent documents, i.e., how consistent existing tools are in predicting the polarity of documents based on paraphrased text. We observe that sentiment analysis tools exhibit intra-tool inconsistency , which is the prediction of different polarity for semantically equivalent documents by the same tool, and inter-tool inconsistency , which is the prediction of different polarity for semantically equivalent documents across different tools. We introduce a heuristic to assess the data quality of an augmented dataset and a new set of metrics to evaluate tool inconsistencies. Our results indicate that tool inconsistencies is still an open problem, and they point towards promising research directions and accuracy improvements that can be obtained if such inconsistencies are resolved.

Virtual reality technologies for clinical education: evaluation metrics and comparative analysis

ABSTRACT With recent advances of Virtual Reality (VR) technology, the deployment of such will dramatically increase in non-entertainment environments, such as professional education and training, manufacturing, service, or low frequency/high-risk scenarios. Clinical education is an area that especially stands to benefit from VR technology due to the complexity, high cost, and difficult logistics. The effectiveness of the deployment of VR systems in healthcare environments is subject to factors that may not be necessarily considered for devices targeting the entertainment market. In this work, we systematically compare a wide range of VR head-mounted displays (HMDs) technologies and designs by defining a new set of metrics that are 1) relevant to medical VR solutions and 2) are of paramount importance for VR-based education and training. We evaluated 10 technologies based on various criteria, including neck strain, heat development, cleanability, and colour accuracy. Other metrics such as text readability, comfort, and contrast perception were evaluated in a multi-user study on three selected technologies, namely the ones offered by Oculus Rift S, HTC Vive Pro and Samsung Odyssey+. Results indicate that the HTC Vive Pro performs best with regards to comfort, display quality and compatibility with glasses.

Defining high-quality NSCLC care at U.S. cancer centers.

229 Background: While clinical guidelines for non-small cell lung cancer (NSCLC) provide recommendations on individual components of care and advocate multidisciplinary collaboration, guidance spanning the complete patient journey is lacking. We aimed to compile quality-focused recommendations for the multidisciplinary team and selected clinical criteria for ideal NSCLC care, and propose a new set of metrics encompassing the entire care continuum. These metrics would be used as a new benchmark for ideal NSCLC care via the Association of Community Cancer Centers’ (ACCC) national quality care initiative for patients with advanced (stage III/IV) NSCLC. Methods: The ACCC convened an expert steering committee of multidisciplinary specialists and representation from patient advocacy to compile evidence-based recommendations via a systematic search of clinical and quality care guidelines and peer-reviewed journals. Quality recommendations were organized within key care areas of the patient journey: care coordination and patient education, diagnosis and biomarker testing, staging and treatment planning, and survivorship. Results: A total of 32 recommendations were included across the 4 key NSCLC care areas. Key quality recommendations are listed (Table). Conclusions: The full set of recommendations define ideal NSCLC care and serve as a valuable guide for multidisciplinary practice and quality improvement initiatives. [Table: see text]