Journal articles: 'Performance metrics'

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Mary, A. Viji Amutha, and Dr T. Jebarajan Dr. T. Jebarajan. "Performance Metrics of Clustering Algorithm." Indian Journal of Applied Research 4, no. 8 (October 1, 2011): 165–67. http://dx.doi.org/10.15373/2249555x/august2014/47.

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Pijpers, Frank P. "Performance metrics." Astronomy & Geophysics 47, no. 6 (December 2006): 6.17–6.18. http://dx.doi.org/10.1111/j.1468-4004.2006.47617.x.

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M. Taaffe, Kevin, Robert William Allen, and Lindsey Grigg. "Performance metrics analysis for aircraft maintenance process control." Journal of Quality in Maintenance Engineering 20, no. 2 (May 6, 2014): 122–34. http://dx.doi.org/10.1108/jqme-07-2012-0022.

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Purpose – Performance measurements or metrics are that which measure a company's performance and behavior, and are used to help an organization achieve and maintain success. Without the use of performance metrics, it is difficult to know whether or not the firm is meeting requirements or making desired improvements. During the course of this study with Lockheed Martin, the research team was tasked with determining the effectiveness of the site's existing performance metrics that are used to help an organization achieve and maintain success. Without the use of performance metrics, it is difficult to know whether or not the firm is meeting requirements or making desired improvements. The paper aims to discuss these issues. Design/methodology/approach – Research indicates that there are five key elements that influence the success of a performance metric. A standardized method of determining whether or not a metric has the right mix of these elements was created in the form of a metrics scorecard. Findings – The scorecard survey was successful in revealing good metric use, as well as problematic metrics. In the quality department, the Document Rejects metric has been reworked and is no longer within the executive's metric deck. It was also recommended to add root cause analysis, and to quantify and track the cost of non-conformance and the overall cost of quality. In total, the number of site wide metrics has decreased from 75 to 50 metrics. The 50 remaining metrics are undergoing a continuous improvement process in conjunction with the use of the metric scorecard tool developed in this research. Research limitations/implications – The metrics scorecard should be used site-wide for an assessment of all metrics. The focus of this paper is on the metrics within the quality department. Practical implications – Putting a quick and efficient metrics assessment technique in place was critical. With the leadership and participation of Lockheed Martin, this goal was accomplished. Originality/value – This paper presents the process of metrics evaluation and the issues that were encountered during the process, including insights that would not have been easily documented without this mechanism. Lockheed Martin Company has used results from this research. Other industries could also apply the methods proposed here.

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Liu, Yangguang, Yangming Zhou, Shiting Wen, and Chaogang Tang. "A Strategy on Selecting Performance Metrics for Classifier Evaluation." International Journal of Mobile Computing and Multimedia Communications 6, no. 4 (October 2014): 20–35. http://dx.doi.org/10.4018/ijmcmc.2014100102.

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The evaluation of classifiers' performances plays a critical role in construction and selection of classification model. Although many performance metrics have been proposed in machine learning community, no general guidelines are available among practitioners regarding which metric to be selected for evaluating a classifier's performance. In this paper, we attempt to provide practitioners with a strategy on selecting performance metrics for classifier evaluation. Firstly, the authors investigate seven widely used performance metrics, namely classification accuracy, F-measure, kappa statistic, root mean square error, mean absolute error, the area under the receiver operating curve, and the area under the precision-recall curve. Secondly, the authors resort to using Pearson linear correlation and Spearman rank correlation to analyses the potential relationship among these seven metrics. Experimental results show that these commonly used metrics can be divided into three groups, and all metrics within a given group are highly correlated but less correlated with metrics from different groups.

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Baker, Noel C., and Patrick C. Taylor. "A Framework for Evaluating Climate Model Performance Metrics." Journal of Climate 29, no. 5 (February 26, 2016): 1773–82. http://dx.doi.org/10.1175/jcli-d-15-0114.1.

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Abstract Given the large amount of climate model output generated from the series of simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), a standard set of performance metrics would facilitate model intercomparison and tracking performance improvements. However, no framework exists for the evaluation of performance metrics. The proposed framework systematically integrates observations into metric assessment to quantitatively evaluate metrics. An optimal metric is defined in this framework as one that measures a behavior that is strongly linked to model quality in representing mean-state present-day climate. The goal of the framework is to objectively and quantitatively evaluate the ability of a performance metric to represent overall model quality. The framework is demonstrated, and the design principles are discussed using a novel set of performance metrics, which assess the simulation of top-of-atmosphere (TOA) and surface radiative flux variance and probability distributions within 34 CMIP5 models against Clouds and the Earth’s Radiant Energy System (CERES) observations and GISS Surface Temperature Analysis (GISTEMP). Of the 44 tested metrics, the optimal metrics are found to be those that evaluate global-mean TOA radiation flux variance.

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Li, Shanshan, and Weiyang Sun. "Image Encryption Performance Evaluation Based on Poker Test." Advances in Multimedia 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/6714164.

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The fast development of image encryption requires performance evaluation metrics. Traditional metrics like entropy do not consider the correlation between local pixel and its neighborhood. These metrics cannot estimate encryption based on image pixel coordinate permutation. A novel effectiveness evaluation metric is proposed in this paper to address the issue. The cipher text image is transformed to bit stream. Then, Poker Test is implemented. The proposed metric considers the neighbor correlations of image by neighborhood selection and clip scan. The randomness of the cipher text image is tested by calculating the chi-square test value. Experiment results verify the efficiency of the proposed metrics.

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Czachura, Agnieszka, Jouri Kanters, Niko Gentile, and Maria Wall. "Solar Performance Metrics in Urban Planning: A Review and Taxonomy." Buildings 12, no. 4 (March 23, 2022): 393. http://dx.doi.org/10.3390/buildings12040393.

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Metrics are instrumental in design assessments. Solar performance metrics help designers to evaluate solar access in cities. Metrics should be used early in the urban planning stages in order to enable sustainable urban development with greater access to solar energy. Currently, solar assessments at this design stage are limited in practice; established methods or routines are lacking, and so are suitable metrics. This paper reviews the relevant literature to provide a critical overview of solar metrics commonly used in building performance assessments. The review defines key metric formulation principles—valuation, time constraint, and normalisation—which should be considered when designing a performance indicator. A new taxonomy of solar performance metrics is provided. Metric definitions, suitability, and limitations are discussed. The findings highlight the need for reliable, low-complexity metrics and adequate methods for early solar assessments for urban planning.

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Nochur, A., H. Vedam, and J. Koene. "Alarm Performance Metrics." IFAC Proceedings Volumes 34, no. 27 (June 2001): 203–8. http://dx.doi.org/10.1016/s1474-6670(17)33592-9.

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Loo, Jessica, Traci E. Clemons, Emily Y. Chew, Martin Friedlander, Glenn J. Jaffe, and Sina Farsiu. "Beyond Performance Metrics." Ophthalmology 127, no. 6 (June 2020): 793–801. http://dx.doi.org/10.1016/j.ophtha.2019.12.015.

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DeLozier, Randall, and Neil Snyder. "ENGINEERING PERFORMANCE METRICS." INCOSE International Symposium 3, no. 1 (July 1993): 599–605. http://dx.doi.org/10.1002/j.2334-5837.1993.tb01632.x.

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AbstractImplementation of a Total Quality Management (TQM) approach to engineering work required the development of a system of metrics which would serve as a meaningful management tool for evaluating effectiveness in accomplishing project objectives and in achieving improved customer satisfaction. A team effort was chartered with the goal of developing a system of engineering performance metrics which would measure customer satisfaction, quality, cost effectiveness, and timeliness. The approach to developing this system involved normal systems design phases including conceptual design, detailed design, implementation, and integration. The lessons learned from this effort will be explored in this paper. These lessons learned may provide a starting point for other large engineering organizations seeking to institute a performance measurement system.

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DePesa, Christopher D., Corrine Y. Jurgens, Christopher S. Lee, and Monica O'Reilly-Jacob. "Nurse Performance Metrics." JONA: The Journal of Nursing Administration 53, no. 2 (February 2023): 110–15. http://dx.doi.org/10.1097/nna.0000000000001251.

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Lehuta, Sigrid, Stéphanie Mahévas, Pascal Le Floc’h, and Pierre Petitgas. "A simulation-based approach to assess sensitivity and robustness of fisheries management indicators for the pelagic fishery in the Bay of Biscay." Canadian Journal of Fisheries and Aquatic Sciences 70, no. 12 (December 2013): 1741–56. http://dx.doi.org/10.1139/cjfas-2013-0066.

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Indicators are widely promoted as means to monitor ecosystem status or to evaluate fisheries management performance. “Which indicators are most relevant as decision-support tools in fisheries management?” still remains a topical question. Indicators should be metrics related to fish populations and fleets and should be sensitive to management strategies. However, given the complexity of the processes involved, it is often difficult to unequivocally interpret variations in metrics. A simulation approach was used to study metric properties and to identify robust and relevant fishery indicators. By applying sensitivity analysis methods, simulation designs were built that cross a variety of management scenarios and uncertainty hypotheses. Bio-economic outputs were simulated using a mechanistic model (ISIS-Fish), and their properties were statistically analyzed. This approach was applied to the pelagic fishery of the Bay of Biscay. The analysis of metric properties highlighted the major factors driving variations in each metric and identified the important sources of uncertainty that need to be reduced to allow the use of metrics as indicators. Although very few metrics gave robust indications of management performance, sensitivity indices evidenced how management performances could be improved, and spatially disaggregated metrics provided insights into the mechanisms underlying management performance.

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Brighton, Eric M., and David M. Klaus. "Categorization of Select Cockpit Performance Evaluation Techniques." Aerospace Medicine and Human Performance 94, no. 9 (September 1, 2023): 696–704. http://dx.doi.org/10.3357/amhp.6185.2023.

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INTRODUCTION: The modern aircraft cockpit has evolved into a complex system of systems. Numerous performance evaluation metrics and techniques exist that can measure the effectiveness of cockpit components in terms of how they influence the human operator’s ability to perform tasks relevant to mission success. As no prior review of these metrics has been found in the literature, this effort attempts to do so, albeit without applying the metrics to a novel cockpit evaluation.METHODS: These metrics and techniques are discussed and presented in five defined categories as they relate to evaluating cockpit subsystems: ergonomics and anthropometrics; human-computer interaction; data management and presentation; crew resource management and operations; and ingress and egress.DISCUSSION: While this effort is significant and novel, it is not necessarily comprehensive. In conclusion, it is noted that no single holistic quantitative metric to evaluate cockpit design and performance yet exists. Utilizing some of the preexisting metrics presented to develop such a metric would be beneficial in efforts to evaluate aircraft cockpit designs and performance, as well as aiding future cockpit designs.Brighton EM, Klaus DM. Categorization of select cockpit performance evaluation techniques. Aerosp Med Hum Perform. 2023; 94(9):696–704.

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Torres-Jr, Pedro Rodrigues, and Eduardo Parente Ribeiro. "Packet Reordering Metrics to Enable Performance Comparison in IP-Networks." Journal of Computer Networks and Communications 2020 (May 30, 2020): 1–8. http://dx.doi.org/10.1155/2020/8465191.

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Despite the existence of several metrics to perform measurements on out-of-order packets, few works have used these metrics for comparative purposes. A potential reason for this is that the use of these simple singleton metrics makes it difficult to analyze all the effects of packet reordering. On the other hand, more complete metrics are represented in a vectorial manner, making comparative analysis challenging. In this paper, we present a scenario for testing and describe a methodology for conducting experiments to compare network paths with respect to unordered packets. The results of several simulations explore simple packet reordering metrics derived from vector metric that may allow future work to be benchmarked against. We demonstrated the behaviour of some TCP congestion control algorithms by adjusting different levels of reordering. We highlight good results with the Entropy reorder metric.

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Mizukami, Naoki, Oldrich Rakovec, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, Hoshin V. Gupta, and Rohini Kumar. "On the choice of calibration metrics for “high-flow” estimation using hydrologic models." Hydrology and Earth System Sciences 23, no. 6 (June 17, 2019): 2601–14. http://dx.doi.org/10.5194/hess-23-2601-2019.

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Abstract. Calibration is an essential step for improving the accuracy of simulations generated using hydrologic models. A key modeling decision is selecting the performance metric to be optimized. It has been common to use squared error performance metrics, or normalized variants such as Nash–Sutcliffe efficiency (NSE), based on the idea that their squared-error nature will emphasize the estimates of high flows. However, we conclude that NSE-based model calibrations actually result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. Using three different types of performance metrics, we calibrate two hydrological models at a daily step, the Variable Infiltration Capacity (VIC) model and the mesoscale Hydrologic Model (mHM), and evaluate their ability to simulate high-flow events for 492 basins throughout the contiguous United States. The metrics investigated are (1) NSE, (2) Kling–Gupta efficiency (KGE) and its variants, and (3) annual peak flow bias (APFB), where the latter is an application-specific metric that focuses on annual peak flows. As expected, the APFB metric produces the best annual peak flow estimates; however, performance on other high-flow-related metrics is poor. In contrast, the use of NSE results in annual peak flow estimates that are more than 20 % worse, primarily due to the tendency of NSE to underestimate observed flow variability. On the other hand, the use of KGE results in annual peak flow estimates that are better than from NSE, owing to improved flow time series metrics (mean and variance), with only a slight degradation in performance with respect to other related metrics, particularly when a non-standard weighting of the components of KGE is used. Stochastically generated ensemble simulations based on model residuals show the ability to improve the high-flow metrics, regardless of the deterministic performances. However, we emphasize that improving the fidelity of streamflow dynamics from deterministically calibrated models is still important, as it may improve high-flow metrics (for the right reasons). Overall, this work highlights the need for a deeper understanding of performance metric behavior and design in relation to the desired goals of model calibration.

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BHARKAD, SANGITA D., and MANESH KOKARE. "PERFORMANCE EVALUATION OF DISTANCE METRICS: APPLICATION TO FINGERPRINT RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 25, no. 06 (September 2011): 777–806. http://dx.doi.org/10.1142/s0218001411009007.

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Distance metric is widely used in similarity estimation which plays a key role in fingerprint recognition. In this work we propose the detailed comparison of 29 distinct distance metrics. Features of fingerprint images are extracted using Fast Fourier Transform (FFT). Recognition rate, receiver operating curve (ROC), time and space complexity parameters are used for evaluation of each distance metric. To consolidate our conclusion we used the standard fingerprint database available at Bologna University and FVC2000 databases. After evaluation of 29 distinct distance metrics we found Sorgel distance metric performs best. Genuine acceptance rate (GAR) of Sorgel distance metric is observed to be ~5% higher than traditional Euclidean distance metric at low false acceptance rate (FAR). Sorgel distance gives good GAR at low FAR with moderate computational complexity.

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Bradley, Brendon A. "Seismic performance criteria based on response history analysis." Bulletin of the New Zealand Society for Earthquake Engineering 47, no. 3 (September 30, 2014): 224–28. http://dx.doi.org/10.5459/bnzsee.47.3.224-228.

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This paper provides a comparison of four different seismic performance metrics which relate to the determination of design seismic demands from seismic response history analyses. The considered metrics include those implemented in New Zealand and international codes of practice, as well as emerging metrics which are well established in related research and state-of-the-art practice, but have yet to find their way into conventional guidelines. The metrics are directly compared and contrasted based on a central example. It is illustrated that the use of the “maximum demand” metric in the NZ loadings standard, and the “mean demand” in international codes of practice are notably conservative and unconservative, respectively. Either of the two emerging metrics provide a significant improvement, and given that they require the same information from an analyst’s perspective, are recommended as replacements.

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Cardosi, Kim, and Amanda DiFiore. "Metrics of Communication Performance." Air Traffic Control Quarterly 12, no. 4 (October 2004): 297–313. http://dx.doi.org/10.2514/atcq.12.4.297.

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Krause, J., M. Cornelius, P. Goldsmith, M. Mzungu, C. Kambani-Banda, and C. Tamimie. "Soy dairy performance metrics." African Journal of Food, Agriculture, Nutrition and Development 21, no. 105 (December 24, 2021): 19016–39. http://dx.doi.org/10.18697/ajfand.105.21245.

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Soybean (Glycine max (L. Merr.) has been a crop of interest to address both poverty and malnutrition in the developing world because of its high levels of both protein and oil, and its adaptability to grow in tropical environments. Development practitioners and policymakers have long sought value added opportunities for local crops to move communities out of poverty by introducing processing or manufacturing technologies. Soy dairy production technologies sit within this development conceptual model. To the researchers’ knowledge, no research to date measures soy dairy performance, though donors and NGOs have launched hundreds of enterprises over the last 18 years. The lack of firm-level data on operations limits the ability of donors and practitioners to fund and site sustainable dairy businesses. Therefore, the research team developed and implemented a recordkeeping system and training program first, as a 14-month beta test with a network of five dairies in Ghana and Mozambique in 2016-2017. Learning from the initial research then supported a formal research rollout over 18 months with a network of six different dairies in Malawi and key collaboration from USAID’s Agricultural Diversification activity. None of the beta or rollout dairies kept records prior to the intervention. The formal rollout resulted in a unique primary dataset to address the soy dairy performance knowledge gap. The results of analysis show that the dairies, on average, achieve positive operating margins of 61%, yet cannot cover the fixed costs associated with depreciation, amortization of equipment and infrastructure, working capital, marketing and promotion, and regulatory compliance. The enterprises in our sample operate only at 9% of capacity, which limits their ability to cover the normal fixed costs associated with the business. The challenge is not the technology itself, as when operated, it produces a high-quality dairy product. The challenges involve a business that requires too much capital for normal operations relative to a nascent and small addressable market.

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Morton, Al. "Performance Metrics for All." IEEE Internet Computing 13, no. 4 (July 2009): 82–86. http://dx.doi.org/10.1109/mic.2009.87.

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Wright, Christopher, Stuart Baur, Katie Grantham, Robert B. Stone, and Scott E. Grasman. "Residential Energy Performance Metrics." Energies 3, no. 6 (June 9, 2010): 1194–211. http://dx.doi.org/10.3390/en3061194.

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Nindl, Bradley C., Dianna P. Jaffin, Michael N. Dretsch, Samuel N. Cheuvront, Nancy J. Wesensten, Michael L. Kent, Neil E. Grunberg, et al. "Human Performance Optimization Metrics." Journal of Strength and Conditioning Research 29 (November 2015): S221—S245. http://dx.doi.org/10.1519/jsc.0000000000001114.

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Stevens, Philip Andrew, Lucy Stokes, and Mary O'Mahony. "Metrics, Targets and Performance." National Institute Economic Review 197 (July 1, 2006): 80–92. http://dx.doi.org/10.1177/0027950106070037.

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The setting and use of targets in the public sector has generated a growing amount of interest in the UK. This has occurred at a time when more analysts and policymakers are grasping the nettle of measuring performance in and of the public sector. We outline a typology of performance indicators and a set of desiderata. We compare the outcome of a performance management system — star ratings for acute hospital trusts in England — with a productivity measure analogous to those used in the analysis of the private sector. We find that the two are almost entirely unrelated. Although this may be the case for entirely proper reasons, it does raise questions as to the appropriateness of such indicators of performance, particularly over the long term.

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Stevens, Philip, Lucy Stokes, and Mary O’Mahony. "Metrics, Targets and Performance." National Institute Economic Review 197, no. 1 (July 2006): 80–92. http://dx.doi.org/10.1177/002795010619700103.

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Prathap, Gangan. "Evaluating journal performance metrics." Scientometrics 92, no. 2 (April 13, 2012): 403–8. http://dx.doi.org/10.1007/s11192-012-0746-1.

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Yunyongying, Pete, Max Rich, and Janet Jokela. "Patient-Centered Performance Metrics." JAMA 321, no. 18 (May 14, 2019): 1829. http://dx.doi.org/10.1001/jama.2019.2056.

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Luque, Amalia, Alejandro Carrasco, Alejandro Martín, and Juan Ramón Lama. "Exploring Symmetry of Binary Classification Performance Metrics." Symmetry 11, no. 1 (January 3, 2019): 47. http://dx.doi.org/10.3390/sym11010047.

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Selecting the proper performance metric constitutes a key issue for most classification problems in the field of machine learning. Although the specialized literature has addressed several topics regarding these metrics, their symmetries have yet to be systematically studied. This research focuses on ten metrics based on a binary confusion matrix and their symmetric behaviour is formally defined under all types of transformations. Through simulated experiments, which cover the full range of datasets and classification results, the symmetric behaviour of these metrics is explored by exposing them to hundreds of simple or combined symmetric transformations. Cross-symmetries among the metrics and statistical symmetries are also explored. The results obtained show that, in all cases, three and only three types of symmetries arise: labelling inversion (between positive and negative classes); scoring inversion (concerning good and bad classifiers); and the combination of these two inversions. Additionally, certain metrics have been shown to be independent of the imbalance in the dataset and two cross-symmetries have been identified. The results regarding their symmetries reveal a deeper insight into the behaviour of various performance metrics and offer an indicator to properly interpret their values and a guide for their selection for certain specific applications.

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Zhong, Yiwen, Kun Song, ShengKai Lv, and Peng He. "An Empirical Study of Software Metrics Diversity for Cross-Project Defect Prediction." Mathematical Problems in Engineering 2021 (November 28, 2021): 1–11. http://dx.doi.org/10.1155/2021/3135702.

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Cross-project defect prediction (CPDP) is a mainstream method estimating the most defect-prone components of software with limited historical data. Several studies investigate how software metrics are used and how modeling techniques influence prediction performance. However, the software’s metrics diversity impact on the predictor remains unclear. Thus, this paper aims to assess the impact of various metric sets on CPDP and investigate the feasibility of CPDP with hybrid metrics. Based on four software metrics types, we investigate the impact of various metric sets on CPDP in terms of F-measure and statistical methods. Then, we validate the dominant performance of CPDP with hybrid metrics. Finally, we further verify the CPDP-OSS feasibility built with three types of metrics (orient-object, semantic, and structural metrics) and challenge them against two current models. The experimental results suggest that the impact of different metric sets on the performance of CPDP is significantly distinct, with semantic and structural metrics performing better. Additionally, trials indicate that it is helpful for CPDP to increase the software’s metrics diversity appropriately, as the CPDP-OSS improvement is up to 53.8%. Finally, compared with two baseline methods, TCA+ and TDSelector, the optimized CPDP model is viable in practice, and the improvement rate is up to 50.6% and 25.7%, respectively.

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Ukommi, U. S. "Review of multimedia communication quality assessment techniques." Nigerian Journal of Technology 41, no. 2 (June 2, 2022): 330–38. http://dx.doi.org/10.4314/njt.v41i2.15.

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Communication pattern is drifting from conventional audio to multimedia applications, streaming live and on-demand digital video contents over telecommunications and broadcasting networks. Currently, some businesses deploy video in promoting products in a far more enriching, entertainment and informative approach than typical traditional audio would allow. However, users of multimedia applications are interested in paying for a good acceptable video quality. Thus, this paper reviews methods used in Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Metric (SSIM) and Video Quality Metric (VQM) with the objective of providing useful information to wireless video services providers in assessing and monitoring of quality of multimedia services delivered to users. Experimental comparison of PSNR, SSIM and VQM assessment methods to examine their performances in evaluation of multimedia applications has been performed. Comparing the quality performance of PSNR, SSIM and VQM metrics for Akiyo and Crew standard test sequences, it has been observed that the quality performance of the metrics improves when the bitrates allocation increase. For the test of consistency and quality performance of the metrics, observation shows that for a given bitrates of 3.84Mb/s, under CABA test configuration, Akiyo test sequence, experienced better quality performance of 46.63dB (PSNR), 99.10% (SSIM) and 11.00% (VQM) compared to lower quality performance of 36.18dB (PSNR), 90.40% (SSIM) and 22.00% (VQM) experienced by Crew test sequence. Experimental results of the media quality metrics for Akiyo and Crew standard test sequences with different temporal activity levels show that the quality performance of media content also depends on the temporal activity of the media content. The experimental results further show consistency in quality performance of PSNR, SSIM and VQM metrics for CABA and UBA test configurations. Thus, the objective metrics can be harnessed for evaluation of quality performance of multimedia applications at different channel conditions.

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Arif-Uz-Zaman, Kazi, and A. M. M. Nazmul Ahsan. "Lean supply chain performance measurement." International Journal of Productivity and Performance Management 63, no. 5 (June 3, 2014): 588–612. http://dx.doi.org/10.1108/ijppm-05-2013-0092.

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Purpose – The purpose of this paper is to present supply chain metrics and to propose a fuzzy-based performance evaluation method for lean supply chain. Design/methodology/approach – To understand the overall performance of cost competitive supply chain the paper investigates the alignment of market strategy and position of the supply chain. Since lean is applicable in many supply chains, the authors propose a set of metrics to evaluate supply chain performance. Moreover, the paper uses a fuzzy model to evaluate the performance of cost competitive supply chains. Fuzzy is an appropriate model method when uncertainty is present. It also allows modelling of a significant number of performance metrics across multiple supply chain elements and processes. Competitive strategy can be achieved by using a different weight calculation for different supply chain situations. Findings – Research provides optimal metrics for lean supply chains. The proposed method can measure the performance of lean supply chains using a fuzzy approach and competitive strategies. Research limitations/implications – The metrics which have been selected to measure the performance of lean supply chains is particularly applicable for high volume, low-price products. Practical implications – By identifying optimal performance metrics and applying performance evaluation methods, managers can predict the overall supply chain performance under lean strategy. By identifying performance for each metric they can also categorize the existing performance and optimise them accordingly. Originality/value – This study provides a performance evaluation method for supply chain managers to assess the effects of lean tools and competitive strategies.

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Kutschera, A., and P. M. Render. "Corner speed versus optimum turn speed." Aeronautical Journal 107, no. 1073 (July 2003): 443–46. http://dx.doi.org/10.1017/s0001924000130052.

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Work has been carried out by Kutschera on how to assess, at the conceptual design stage, the performance of fighter aircraft. As part of this work, Kutschera reviewed a number of existing and proposed metrics for assessing aircraft performance. Reference 4 also describes how the performance of an aircraft can be quantified by three types of metric. The first type are steady state or point performance metrics, such as turn rate plots and energy manoeuvrability diagrams. The second type are manoeuvrability metrics and the last are agility metrics.

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Kresl, William, and James M. Manimala. "Tunable performance metrics for acoustic liners." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A225. http://dx.doi.org/10.1121/10.0011137.

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In the development of automated design tools for acoustic liners customized to mitigate specific noise spectral characteristics, it is often beneficial to have a unified quantitative metric to discriminate between candidate designs. Such metrics are especially useful when optimizing the packing of 3D folded cavities into a prescribed liner volume. We devise tunable performance metrics (TPM) that account for absorption parameters such as the peak absorption and the frequency at which it occurs, the bandwidth of appreciable absorption and its lower bound among others. Metrics are tuned by varying the weight functions for these absorption parameters in order to address the specific priorities for the liner’s design. A numerical study is conducted using a procedure based on the Zwikker–Kosten Transmission Line (ZKTL) theory to demonstrate the application of TPMs for the selection of acoustic liner designs for various scenarios. When liners with complex core geometries are used to enhance acoustic performance, TPMs that also include structural parameters related to mass, volume, stiffness or strength could be utilized to provide a more comprehensive means of evaluation.

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Fedorenko, Yu S. "STATISTICAL TESTING TECHNIQUE FOR COMPARISON MACHINE LEARNING MODELS PERFORMANCE." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 186 (December 2019): 10–17. http://dx.doi.org/10.14489/vkit.2019.12.pp.010-017.

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The statistical testing technique is considered to compare the metrics values of machine learning models on a test set. Since the values of metrics depend not only on the models, but also on the data, it may turn out that different models are the best on different test sets. For this reason, the traditional approach to comparing the values of metrics on a test set is often not enough. Sometimes a statistical comparison of the results obtained on the basis of cross-validation is used, but in this case it is impossible to guarantee the independence of the obtained measurements, which does not allow the use of the Student's t-test. There are criteria that do not require independent measurements, but they have less power. For additive metrics, a technique is proposed in this paper, when a test sample is divided into N parts, on each of which the values of the metrics are calculated. Since the value on each part is obtained as the sum of independent random variables, according to the central limit theorem, the obtained metrics values on each of the N parts are realizations of the normally distributed random variable. To estimate the required sample size, it is proposed to use normality tests and build quantile– quantile plots. You can then use a modification of the Student's t-test to conduct a statistical test comparing the mean values of the metrics. A simplified approach is also considered, in which confidence intervals are built for the base model. A model whose metric values do not fall into this interval works differently from the base model. This approach reduces the amount of computations needed, however, an experimental analysis of the binary cross-entropy metric for CTR (Click-Through Rate) prediction models showed that it is more rough than the first one.

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Słomska-Przech, Katarzyna, and Izabela Małgorzata Gołębiowska. "Do Different Map Types Support Map Reading Equally? Comparing Choropleth, Graduated Symbols, and Isoline Maps for Map Use Tasks." ISPRS International Journal of Geo-Information 10, no. 2 (February 10, 2021): 69. http://dx.doi.org/10.3390/ijgi10020069.

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It is acknowledged that various types of thematic maps emphasize different aspects of mapped phenomena and thus support different map users’ tasks. To provide empirical evidence, a user study with 366 participants was carried out comparing three map types showing the same input data. The aim of the study is to compare the effect of using choropleth, graduated symbols, and isoline maps to solve basic map user tasks. Three metrics were examined: two performance metrics (answer accuracy and time) and one subjective metric (difficulty). The results showed that the performance metrics differed between the analyzed map types, and better performances were recorded using the choropleth map. It was also proven that map users find the most commonly applied type of the map, choropleth map, as the easiest. In addition, the subjective metric matched the performance metrics. We conclude with the statement that the choropleth map can be a sufficient solution for solving various tasks. However, it should be remembered that making this type of map correctly may seem easy, but it is not. Moreover, we believe that the richness of thematic cartography should not be abandoned, and work should not be limited to one favorable map type only.

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Hia, Selamat Walmanto, Moses Laksono Singgih, and Raja Oloan Saut Gurning. "Performance Metric Development to Measure Overall Vehicle Effectiveness in Mining Transportation." Applied Sciences 12, no. 23 (December 2, 2022): 12341. http://dx.doi.org/10.3390/app122312341.

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Several performance metrics to measure the effectiveness of manufacturing equipment have been studied, and one of the most used is overall equipment effectiveness (OEE). However, its application and development in the road transportation sector remains little studied. The purpose of this paper is to establish a new metric derived from OEE to measure the overall effectiveness of coal mining transportation and apply this metric to actual operation. This study employed in-depth interviews and Delphi techniques to explore the specific metrics. Three rounds of Delphi involving mining experts, academia, and consultants identified six potential metrics to measure coal mining transportation operations that contributed to a new metric to measure mining transportation overall vehicle effectiveness. This paper also discusses a case study of how this newly developed metric was tested and applied to the actual operation of the truck fleet at a coal-hauling company in Indonesia. According to the case study, this metric accommodated the important factors in coal mining transportation operations and reflected operational performance. This study contributes to measuring the effectiveness of coal-hauling transportation by providing an effective metric that will help the managerial team make better decisions for process improvement.

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Kumar Dahal, Rewan. "Effectiveness of learning and growth performance metrics in the Nepalese telecommunications industry for organizational success." Problems and Perspectives in Management 20, no. 4 (November 23, 2022): 238–49. http://dx.doi.org/10.21511/ppm.20(4).2022.18.

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The primary use of financial-based performance metrics to assess an organization’s success might be misleading. The application of non-financial performance metrics could improve organizational success and longevity. This study aimed to examine the effectiveness of learning and growth performance metrics for organizational success in the Nepalese telecommunication industry. The quantitative research approach was utilized for collecting, presenting, and analyzing data obtained during a survey. The two major telecommunications service providers in Nepal, Ncell and Nepal Telecom, were taken as sample organizations, and their employees were the study’s respondents. The study revealed that two latent learning and growth performance metrics, namely ‘organizational culture and alignment’ having seven observable variables (β = 0.229, t = 3.419, p &lt; .05) and ‘information capital’ having four observable variables (β = 0.079, t = 1.193, p &lt; .05) were significant for organizational success. In contrast, one latent metric, ‘human resources’ having seven observable variables (β = 0.047, t = 0.708,&nbsp;p &gt; .05), was insignificant. The overall explanation of the observed non-financial performance metrics to the organizational success of the Nepalese telecommunication industry was approximately 6%. A better learning and growth environment helps an organization generate, acquire, share, and integrate information to build resources and capabilities. In addition, non-financial performance metrics help organizations connect business performance with strategy, allowing them to be competitive.

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Mirchi, Nykan, Vincent Bissonnette, Nicole Ledwos, Alexander Winkler-Schwartz, Recai Yilmaz, Bekir Karlik, and Rolando F. Del Maestro. "Artificial Neural Networks to Assess Virtual Reality Anterior Cervical Discectomy Performance." Operative Neurosurgery 19, no. 1 (December 13, 2019): 65–75. http://dx.doi.org/10.1093/ons/opz359.

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Abstract BACKGROUND Virtual reality surgical simulators provide a safe environment for trainees to practice specific surgical scenarios and allow for self-guided learning. Artificial intelligence technology, including artificial neural networks, offers the potential to manipulate large datasets from simulators to gain insight into the importance of specific performance metrics during simulated operative tasks. OBJECTIVE To distinguish performance in a virtual reality-simulated anterior cervical discectomy scenario, uncover novel performance metrics, and gain insight into the relative importance of each metric using artificial neural networks. METHODS Twenty-one participants performed a simulated anterior cervical discectomy on the novel virtual reality Sim-Ortho simulator. Participants were divided into 3 groups, including 9 post-resident, 5 senior, and 7 junior participants. This study focused on the discectomy portion of the task. Data were recorded and manipulated to calculate metrics of performance for each participant. Neural networks were trained and tested and the relative importance of each metric was calculated. RESULTS A total of 369 metrics spanning 4 categories (safety, efficiency, motion, and cognition) were generated. An artificial neural network was trained on 16 selected metrics and tested, achieving a training accuracy of 100% and a testing accuracy of 83.3%. Network analysis identified safety metrics, including the number of contacts on spinal dura, as highly important. CONCLUSION Artificial neural networks classified 3 groups of participants based on expertise allowing insight into the relative importance of specific metrics of performance. This novel methodology aids in the understanding of which components of surgical performance predominantly contribute to expertise.

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St-Aubin, Philippe, and Bruno Agard. "Precision and Reliability of Forecasts Performance Metrics." Forecasting 4, no. 4 (October 30, 2022): 882–903. http://dx.doi.org/10.3390/forecast4040048.

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The selection of an accurate performance metric is highly important to evaluate the quality of a forecasting method. This evaluation may help to select between different forecasting tools of forecasting outputs, and then support many decisions within a company. This paper proposes to evaluate the sensitivity and reliability of forecasts performance metrics. The methodology is tested using multiple time series of different scales and demand patterns, such as intermittent demand. The idea is to add to each series a noise following a known distribution to represent forecasting models of a known error distribution. Varying the parameters of the distribution of the noise allows to evaluate how sensitive and reliable performance metrics are to changes in bias and variance of the error of a forecasting model. The experiments concluded that sRMSE is more reliable than MASE in most cases on those series. sRMSE is especially reliable for detecting changes in the variance of a model and sPIS is the most sensitive metric to the bias of a model. sAPIS is sensible to both variance and bias but is less reliable.

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Sobral, Jose V. V., Joel J. P. C. Rodrigues, Neeraj Kumar, Chunsheng Zhu, and Raja W. Ahmad. "Performance Evaluation of Routing Metrics in the LOADng Routing Protocol." Journal of Communications Software and Systems 13, no. 2 (June 1, 2017): 87. http://dx.doi.org/10.24138/jcomss.v13i2.376.

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LOADng (Lightweight On-demand Ad hoc Distance-vector Routing Protocol - Next Generation) is an emerging routing protocol that emerged as an alternative to RPL (IPv6 Routing Protocol for Low power and Lossy Networks). Although some work has been dedicated to study LOADng, these works do not analyze the performance of this protocol with different routing metrics. A routing metric is responsible for defining values for paths during the route creation process. Moreover, based on these metrics information a routing protocol will select the path to forward a message. Thus, this work aims to realize a performance assessment study considering different routing metrics applied to LOADng. The scenarios under study consider different traffic patterns and network sizes. The routing metrics are evaluated considering the packet delivery ratio, average energy spent per bit delivered, average latency, and number of hops. The results reveals that routing metrics used by this protocol may influence (directly) the network performance.

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Wienold, J., T. Iwata, M. Sarey Khanie, E. Erell, E. Kaftan, RG Rodriguez, JA Yamin Garreton, et al. "Cross-validation and robustness of daylight glare metrics." Lighting Research & Technology 51, no. 7 (March 14, 2019): 983–1013. http://dx.doi.org/10.1177/1477153519826003.

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This study evaluates the performance and robustness of 22 established and newly proposed glare prediction metrics. Experimental datasets of daylight-dominated workplaces in office-like test rooms were collected from studies by seven research groups in six different locations (Argentina, Denmark, Germany, Israel, Japan and the United States). The variability in experimental setups, locations and research teams allowed reliable evaluation of the performance and robustness of glare metrics for daylight-dominated workplaces. Independent statistical methods were applied to individual datasets and also to one combined dataset to evaluate the performance and robustness of the 22 glare metrics. As performance and robustness are not established in literature, we defined performance as: (1) the ability of the metric value to describe the glare scale (evaluated by Spearman rank correlation), and (2) the ability of the metric to distinguish between disturbing and non-disturbing situations (evaluated by diagnostic receiver operating characteristic curve analysis tests). Furthermore, we defined robustness as the ability of a metric to deliver meaningful results when applied to different datasets and to fail as few as possible statistical tests. Average Spearman rank correlation coefficients in the range of 0.55–0.60 as well as average prediction rates to distinguish between disturbing and non-disturbing glare of 70–75% for several of the metrics indicate their reliability. The results also show that metrics considering the saturation effect as a main input in their equation perform better and are more robust in daylight-dominated workplaces than purely contrast-based metrics or purely empirical metrics. In this study, the daylight glare probability (DGP) delivered the highest performance amongst the tested metrics and was also found to be the most robust. Future research should aim to optimise the terms of glare equations which combine contrast and saturation effects, such as DGP, PGSV or UGRexp, to achieve metrics that also perform reliably in dimmer lighting conditions than the ones explored in this study.

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Christopher, John J., Jessica Schindler, Jose Villa, Erika Hussey, John Ramsay, and Stephanie A. T. Brown. "Holding on Tight: Relationship Between Grip Strength and Marksmanship Stability." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2156–60. http://dx.doi.org/10.1177/1071181319631104.

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Evaluating marksmanship performance is crucial for Warfighters and competitive shooters alike. Traditionally, only accuracy or hit/miss has been used as the quantitative metric to report performance. In this study, grip strength from U.S. Army Soldiers is compared to marksmanship stability metrics recorded after a field training mission. The data analysis revealed that there is a relationship between grip strength and stability, especially in the less stable standing position. The horizontal and vertical stability measures, as well as trigger control offer new insights into weapon control during target acquisition and trigger pull. These metrics, combined with accuracy and precision, offer a more robust evaluation of a shooter’s performance. Correlating these metrics to grip strength shows a relationship between a shooter’s strength and performance, and can lead to targeted training for better performance. Future studies should continue to use stability metrics when defining performance, as well as investigate additional strength metrics.

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Boubekri, Mohamed, and Jaewook Lee. "A COMPARISON OF FOUR DAYLIGHTING METRICS IN ASSESSING THE DAYLIGHTING PERFORMANCE OF THREE SHADING SYSTEMS." Journal of Green Building 12, no. 3 (September 2017): 39–53. http://dx.doi.org/10.3992/1943-4618.12.3.39.

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The assessment of the daylighting performance of a design solution is a complex task due to the changing nature of daylight. A few quantitative metrics are available to designers to assess such a performance, among them are the mean hourly illuminance (MHI), the daylight factor (DF), the daylight autonomy (DA) and the useful daylight illuminance (UDI). Each of these metrics has a purpose, a set of criteria and limitations that affect the outcome of the evaluation. When to use one metric instead of another depends largely on the design goals to be achieved. Using Design Iterate Validate Adapt (DIVA) daylighting simulation program, we set out to examine the performance behavior of these four metrics with the changing dimensions of three shading devices: a horizontal overhang, a horizontal louver system, and a vertical fin system, and compare their performance behavior as the orientation changes of the window to which these devices are attached. The context is a typical classroom of a prototypical elementary school. Our results indicate that not all four metrics behave similarly as we vary the size of each shading device and as orientation changes. The lesson learned is that not all daylighting metrics lead to the same conclusions and that it is important to use the metric that corresponds to the specific goals and objectives of the design and of the daylighting solution. The UDI is the metric that leads to outcomes most different than the other three metrics investigated in this paper.

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Tian, Qi Ming, and Hao Yu Meng. "Analysis and Comparison of Routing Metrics for Multi-Interface Wireless Mesh Networks." Advanced Materials Research 268-270 (July 2011): 1856–61. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1856.

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The development of wireless broadband access in multimedia field has a higher requirement on wireless mesh networks’ performance. The design of routing metric is the key to improve the performance of wireless mesh networks. How to make full use of multi-interface technology in routing metric design to improve the network capacity has become a research focus. This article first analyzes the requirements of multi-interface wireless mesh networks on routing metric design, then analyzes strengths and weaknesses of nine routing metrics applied in wireless mesh networks currently, and finally compares the conditions of nine routing metrics capturing different performance indicators of wireless networks. As routing metrics like WCETT, MIC, WCETT-LB, IAWARE, ILA, MI and IDA all take channel interference problems into account, they are more suitable for multi-interface wireless mesh networks.

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Vila, Bryan, Stephen James, and Lois James. "How police officers perform in encounters with the public." Policing: An International Journal 41, no. 2 (April 9, 2018): 215–32. http://dx.doi.org/10.1108/pijpsm-11-2016-0166.

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Purpose The purpose of this paper is to develop and describe the implementation of a novel method for creating interval-level metrics for objectively assessing police officer behaviors during an encounter with the public. These behaviors constitute officer performance and affect the probability of desirable encounter outcomes. The metrics measure concrete, micro-level performance in the common types of complex, dynamic, and low-information police-public encounters that often require immediate action using “naturalistic” decision making. Difficulty metrics also were developed to control for situational variability. The utility of measuring what officers do vs probabilistic outcomes is explored with regard to informing policymaking, field practice, and training. Design/methodology/approach Metric sets were developed separately for three types of police-public encounters: deadly force judgment and decision making, cross-cultural tactical social interaction, and crisis intervention. In each, “reverse concept mapping” was used with a different diverse focus group of “true experts” to authoritatively deconstruct implicit concepts and derive important variables. Variables then were scaled with Thurstone’s method using 198 diverse expert trainers to create interval-level metrics for performance and situational difficulty. Metric utility was explored during two experimental laboratory studies and in response to a problematic police encounter. Findings Objective, interval-level metric sets were developed for measuring micro-level police performance and encounter difficulty. Validation and further refinement are required. Research limitations/implications This novel method provides a practical way to rapidly develop metrics that measure micro-level performance during police-public encounters much more precisely than was previously possible. Originality/value The metrics developed provide a foundation for measuring officers’ performance as they exercise discretion, engage people, and affect perceptions of police legitimacy.

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Halpern, Michael T., Hamlet Gasoyan, and William E. Aaronson. "Metrics to evaluate the performance of cancer center leadership." Journal of Clinical Oncology 37, no. 27_suppl (September 20, 2019): 10. http://dx.doi.org/10.1200/jco.2019.37.27_suppl.10.

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10 Background: Cancer centers are diverse health care organizations that involve clinicians and researchers focused on understanding, treating, and controlling cancer in the populations they serve. While there are many metrics used to evaluate cancer center performance, few standardized measures have been identified to evaluate the performance of cancer center leadership. The goal of this manuscript is to systematically identify, compare, and categorize metrics used to evaluate the leadership of U.S. cancer centers. Methods: We performed a structured, systematic electronic search of peer-reviewed journals using Medline to identify English language articles discussing metrics used to evaluate cancer center leadership. Identified studies were reviewed by two independent reviewers to determine appropriateness for inclusion. Metrics were classified using ten a priori-defined categories of evaluation for data abstraction. Results: We included 34 manuscripts in this review. The most commonly-discussed evaluation metric category is organizational strategy/planning (31 of the 34 papers), followed by leader characteristics (25 papers), clinical performance (21), and facility characteristics (20). Organizational strategy/planning include governance structure; strategic development; quality assurance/improvement; mission/vision; business planning; and program development. Leader characteristic metrics include communication; vision/strategic thinking; personal skills; team coordination; leadership style; and staff development. Clinical Performance metrics focus on delivery of and outcomes from clinical services while facility characteristics include space allocation and access to support services. Conclusions: The metrics reviewed and synthesized in this report may be considered measurable outcomes to evaluate whether cancer center leadership demonstrates key competencies. Additional research is needed to explore the link between metrics used to evaluate cancer center leaders, the desired competencies for healthcare leaders, and objective measures of whether a cancer center is “successful”.

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Krishna, Dhulipalla Vijay, and K. Praveen Kumar. "Student Performance Metrics in Android." International Journal of Digital Contents and Applications for Smart Devices 3, no. 1 (June 30, 2016): 1–8. http://dx.doi.org/10.21742/ijdcasd.2016.3.1.01.

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Succar, Bilal, Willy Sher, and Anthony Williams. "Measuring BIM performance: Five metrics." Architectural Engineering and Design Management 8, no. 2 (May 2012): 120–42. http://dx.doi.org/10.1080/17452007.2012.659506.

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Gupta, Diwakar, Sandra Potthoff, Donald Blowers, and John Corlett. "Performance Metrics for Advanced Access." Journal of Healthcare Management 51, no. 4 (July 2006): 246–58. http://dx.doi.org/10.1097/00115514-200607000-00007.

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Dangol, R., P. Bhusal, and L. Halonen. "Performance of colour fidelity metrics." Lighting Research & Technology 47, no. 8 (October 22, 2014): 897–908. http://dx.doi.org/10.1177/1477153514555721.

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Fraker, Shannon E., William H. Woodall, and Shabnam Mousavi. "Performance Metrics for Surveillance Schemes." Quality Engineering 20, no. 4 (September 17, 2008): 451–64. http://dx.doi.org/10.1080/08982110701810444.

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Journal articles on the topic 'Performance metrics'

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