Calculation Of Metrics Research Articles

Multilandr: an R package for multi-scale landscape analysis

ContextTypical landscape-scale studies comprise the delimitation of landscapes followed by the calculation of one or more landscape metrics. Performing an analysis at multiple spatial scales is often required, occasionally followed by the selection of a particular scale according to the response variable of interest. More complex research goals might require a thorough inspection of landscapes, plus a selection of landscapes that would fulfill certain conditions regarding their landscape metrics. These tasks can usually be programmatically challenging, especially if multiple spatial scales are being analyzed.ObjectivesThe R package multilandr builds on several spatial-oriented R packages to provide a toolbox to develop and inspect multi-scale landscapes based on simple spatial inputs.Methods and resultsThe package delivers functions to calculate metrics within a multi-scale framework. Also, it provides several utility functions to visualize correlations between metrics, filter landscapes that fulfill certain predefined conditions or select a wide-range gradient of landscapes for a given metric, among other useful tasks. This paper introduces the functionality of multilandr through a step-by-step instruction guide and case studies.ConclusionsThe R package multilandr provides a set of functions to facilitate typical methodological workflow of landscape-scale studies in the R environment, for both beginner and expert R users. It provides the functionality to perform a systematic filtering and selection of landscapes according to a given experimental design. The package is especially programmed to develop multi-scale designs but is also useful for the calculation of metrics of a set of landscapes from any GIS-related project.

Computing metrics to inform selection of candidate areas for a regionalized approach to bovine tuberculosis eradication in Ireland.

We describe the computation of metrics to inform the selection of areas for a regionalised approach to bovine tuberculosis eradication in Ireland. Our aim was not to recommend suitable regions but to elucidate the criteria used in metric selection and comment on the diversity of metric values amongst regions. The 26 counties of Ireland were compared using 20 metrics, grouped into five categories: region size and cattle population, herd fragmentation, cattle movement, bovine TB testing, badger population and control. Fragmentation metrics, measuring the proportion of herds with land in at least two counties, varied considerably by county, from 1% to 24 %. Between 25 % and 92 % of moves into herds came from a different county, illustrating the likely disruption in trade that a regionalized approach could entail. Cattle movement networks were combined with a risk model to calculate the proportion of moves which would be deemed risky under a risk-based trading regime and these results were compared to a more traditional approach based on the herd type and test history of each herd, with many fewer moves potentially restricted using the latter approach. We show how correlation between region size and some of the metrics complicates their interpretation.

‘metrix’: An R package for assessing the biological quality of water

The monitoring of biological indicators is necessary to evaluate water quality. Macroinvertebrate-based biomonitoring tools, such as simple metrics and biotic indices, are widely used to assess biological water quality. However, the growing availability of ecological data has not been accompanied by the development of processing tools that can facilitate data handling and analysis. These analyses, although not mathematically complex, can be prone to errors, especially when dealing with large databases. To address this issue, we introduce ‘metrix’, a free and open-source R package for the calculation of metrics and biotic indices for macroinvertebrate samples. This package provides a straightforward method for data manipulation, as it relies on preset spreadsheets. It does not require the use of other software or packages and can be easily modified, making it suitable for non-programming users.

Volumetric measurements of wake impulse and kinetic energy for evaluating swimming performance

Volumetric flow measurements are a valuable tool for studies of aquatic locomotion. In addition to visualizing complex propulsive behaviors (e.g., highly three-dimensional kinematics or multi-propulsor interactions), volumetric wake measurements can enable direct calculation of metrics for locomotive performance including the hydrodynamic impulse and wake kinetic energy. These metrics are commonly used in PIV and PTV studies of swimming organisms, but derivations from planar data often rely on simplifying assumptions about the wake (e.g., geometry, orientation, or interactions). This study characterizes errors in deriving wake impulse and kinetic energy directly from volumetric data in relation to experimental parameters including the level of noise, the flow feature resolution, processing parameters, and the calculation domain. We consider three vortex ring-like test cases: a synthetic spherical vortex with exact solutions for its impulse and energy, volumetric PIV measurements of a turbulent vortex ring, and volumetric PIV measurements of a turning fish. We find that direct calculations of hydrodynamic impulse are robust when derived from a volumetric experiment. We also show that kinetic energy estimates are feasible at experiment resolutions, but are more sensitive to experiment design and processing parameters, which may limit efficiency estimates or comparisons between studies or organisms.Graphical abstract

TEnvR: MATLAB-based toolbox for environmental research.

With the advancements in science and technology, datasets become larger and more multivariate, which warrants the need for programming tools for fast data processing and multivariate statistical analysis. Here, the MATLAB-based Toolbox for Environmental Research "TEnvR" (pronounced "ten-ver") is introduced. This novel toolbox includes 44 open-source codes for automated data analysis from a multitude of techniques, such as ultraviolet-visible, fluorescence, and nuclear magnetic resonance spectroscopies, as well as from ultrahigh resolution mass spectrometry. Provided are codes for processing data (e.g., spectral corrections, formula assignment), visualization of figures, calculation of metrics, multivariate statistics, and automated work-up of large datasets. TEnvR allows for efficient data analysis with minimal "by-hand" manual work by the user, which allows scientists to do research more efficiently. This manuscript is supplemented with a detailed tutorial, example data, and screenshots, which collectively provide instructions on how to use all codes. TEnvR is novice-friendly and experience in programming with MATLAB is not required. TEnvR fulfills the need for a concise MATLAB-based toolbox for working with environmental data and will be updated annually to keep pace with the latest advances and needs for computational work in the environmental sciences.

VALIDATING THE GEOMETRIC DESIGN RULES FOR ORTHOGONAL TOPOLOGIES IN INTEGRATED CIRCUITS

A series of existing methods for obtaining parametric metrics for orthogonal topologies (sets of orthogonal geometric objects) is analysed. The systematic examination and analysis of rules for designing of orthogonal topologies are critically important in modern electronic design. Precise and efficient component placement on integrated circuits impacts the device performance and reliability. Based on the analysis and comparisons, two effective solution methods are proposed. These methods are founded on the introduction and computation of metrics based on rectangular and square trees, which enhance the design process and facilitate more efficient chip space utilization, a matter of significance in the contemporary electronics industry. Rectangular trees provide an intuitive structure for organizing orthogonal objects, while square trees offer optimal space partitioning into square cells, which can be crucial for specific tasks. The article provides detailed descriptions of these methods and their implementation algorithms. A comparative analysis of both methods is then conducted to identify their advantages and disadvantages in different scenarios. The research shows that the choice between rectangular and square trees depends on specific design requirements and task characteristics. This research project has a wide range of practical applications, from integrated circuit development to mapping, game engine development, and more. This work can be valuable for professionals in the field of electronic design, as well as for those involved in optimizing orthogonal geometric structures.

On sampled metrics for item recommendation

Recommender systems personalize content by recommending items to users. Item recommendation algorithms are evaluated by metrics that compare the positions of truly relevant items among the recommended items. To speed up the computation of metrics, recent work often uses sampled metrics where only a smaller set of random items and the relevant items are ranked. This paper investigates such sampled metrics in more detail and shows that they are inconsistent with their exact counterpart, in the sense that they do not persist relative statements, for example, recommender A is better than B , not even in expectation. Moreover, the smaller the sample size, the less difference there is between metrics, and for very small sample size, all metrics collapse to the AUC metric. We show that it is possible to improve the quality of the sampled metrics by applying a correction, obtained by minimizing different criteria. We conclude with an empirical evaluation of the naive sampled metrics and their corrected variants. To summarize, our work suggests that sampling should be avoided for metric calculation, however if an experimental study needs to sample, the proposed corrections can improve the quality of the estimate.

Analysis and Modeling of the Negative Impact of Virtual Reality

During the use of virtual training complexes for the training of specialists in the engineering, chemical, mining industries, in the course of numerous studies, the negative impact of virtual reality on the physical state of a person is noted. These include various types of motion sickness, dizziness, nausea, disorientation in space. Therefore, an actual task is researching of causes and the degree of influence of negative factors using virtual reality technologies. To track negative effects, an algorithm for analyzing user’s state has been developed, which allows collect data of person’s state during the interacting with virtual reality. The algorithm allows fixing quantitative and qualitative metrics. Calculation of metrics is formalized in a mathematical model of process of the virtual reality influence on a person. Algorithm and model are tested on example of an exercise on moving simple virtual objects, data is obtained on a focus group of young specialists. Dynamics of changing quantitative and qualitative metrics is evaluated; it received an idea of degree of influence of negative effects on studying process.

A Network Theory Approach to Curriculum Design

In this paper we hypothesize that education, especially at the scale of curriculum, should be treated as a complex system composed of different ideas and concepts which are inherently connected. Therefore, the task of a good teacher lies in elucidating these connections and helping students make their own connections. Such a pedagogy allows students to personalize learning and strive to be ‘creative’ and make meaning out of old ideas. The novel contribution of this work lies in the mathematical approach we undertake to verify our hypothesis. We take the example of a precalculus course curriculum to make our case. We treat textbooks as exemplars of a specific pedagogy and map several texts into networks of isolated (nodes) and interconnected concepts (edges) thereby permitting computations of metrics which have much relevance to the education theorists, teachers and all others involved in the field of education. We contend that network metrics such as average path length, clustering coefficient and degree distribution provide valuable insights to teachers and students about the kind of pedagogy which encourages good teaching and learning.

ОСОБЛИВОСТІ ВСТАНОВЛЕННЯ ВЕЛИЧИНИ МЕТРИКИ, ЩО ЗАСТОСОВУЄТЬСЯ ДЛЯ ІДЕНТИФІКАЦІЇ ПОДІБНОСТІ МАРШРУТІВ СУДЕН УСИСТЕМІ ВИСВІТЛЕННЯ НАДВОДНОЇ ОБСТАНОВКИ

The information component of the modern model of border protection in the maritime area is implemented using the integrated information and telecommunication system of the Marine Guard "Gart-12". The use of this system allows to obtain information about the current position of ships, port of departure and port of destination, type of cargo and other additional data. When choosing a vessel in the surface lighting system, it is possible to view the previous points of its route, obtained at certain discrete moments of time. The latter is necessary to establish possible signs of violation of the rules of the border regime by violators of border legislation. In this case, the visualization of the route is carried out using a linear approximation, and a possible violation of the rules of the border regime is established by comparing the route of an individual vessel and a cluster of routes connecting the departure and destination of the vessel. However, the use of linear approximation in the formation of a continuous approximation route of the vessel is questionable and unconfirmed. The influence of the type of approximation in the construction of a continuous route of the vessel through a set of discrete points of the vessel's location at fixed moments of time on the value of the metric used to establish the similarity of the route of two different vessels is investigated. The study involved: the formalization of the studied problem; analysis of the possibility of using linear, piecewise-square approximation, approximation using Lagrange interpolation polynomial and Newton's interpolation polynomial, as well as spline interpolation for its solution; calculation of metrics to establish the degree of similarity of ship routes; testing the hypothesis about the feasibility of applying a linear approximation based on a comparison of the results using different approximation methods. Software-algorithmic implementation of the solution of the researched problem, carried out by the authors, allows to automate the process of hypothesis testing and is the basis for further study of the influence of the type of approximation on the shape of the ship route cluster.

Proposal and Application of a Methodology to Improve the Control and Monitoring of Complex Hydroelectric Power Station Construction Projects

All complex projects take place in environments of great uncertainty. Maintaining a monitoring and control system from the early stages of execution is a critical factor in the success of this type of project. Large hydroelectric power station construction projects are regarded as highly complex because they are affected by factors such as the risks inherent in a variety of fields of engineering, geology and the environment, the long execution times, and the large number of multidisciplinary activities to be carried out in parallel, among others. These types of projects are commonly affected by cost overruns and delays. This work develops a methodology for the monitoring and control of complex construction projects in the hydroelectric sector that enables a periodical calculation of metrics for physical progress, financial progress, and predictions for costs and durations on completion of the project. The verification of the efficiency of this methodology was based on stochastic simulation models applied to real projects in the hydropower sector. The results showed that the proposed methodology improved efficiency compared with existing traditional methodologies. The proposed methodology allows the simultaneous consideration of costs, deadlines, criticality, and risks of the activities of the analyzed projects and also incorporates multicriteria decision techniques to manage the influence of key aspects during the development of the project.

On the thermophoretic sampling and TEM-based characterisation of soot particles in flames

Thermophoretic sampling and TEM imaging are common techniques used to characterise soot particles in flames. In this paper, we present a multi-scale evaluation of operating conditions and methodological aspects of these techniques, and based on our own experimental observations, show how these can influence the characterisation of the particles. Regarding the thermophoretic sampling of soot particles in flames, we evaluated the influence of exposure time, transit times, multiple-insertions, probe design and vibrations in the capture of representative samples, and present a series of recommendations. For the nano-structural characterisation of soot particles using HRTEM combined with fringe analysis we evaluated the influence of microscope alignment and image quality in the mapping of fringes and the calculation of metrics, concluding that the fringe lengths and inter-fringe spacing are very sensitive to particle focus. Also, the parameters used in the image transformation process are critical and require optimisation for different magnifications and microscopes. Finally, the effect of beam damage was studied, confirming a time of approximately 6 min during which both nascent and mature particles can be imaged without noticeable nano-structural damage. The use of lower microscope electron voltage can further minimise the impact of beam damage.

Integration of TanDEM-X and SRTM DEMs and Spectral Imagery to Improve the Large-Scale Detection of Opencast Mining Areas

Land use and land cover (LULC) is a key variable of the Earth’s system and has become an important indicator to evaluate the impact of human activities on the Earth’s ecosystems. With the increasing demand of mine resources, widespread opencast mining has led to significant changes in LULC and caused substantial damage to the environment. An efficient approach of detecting mining activities at large scales is of critical importance in mitigating their potential impacts on downstream settlements and in assessing LULC characteristics. In this study, we present a novel approach for enabling large-scale automatic detection of opencast mining areas by integrating multitemporal digital elevation models (DEMs, including the SRTM DEM and the recently released TanDEM-X DEM) and multispectral imagery in object-based image analysis and random forest (RF) algorithms. A sequence of data preparation, image segmentation, threshold analysis, calculation of metrics, and influence factor regulation was developed and tested on the Landsat 8 sample dataset in Inner Mongolia in China, which is a mineral-rich area. Aside from spectral metrics, such as brightness and reflectance value, introduced topographical features enhanced the modeling and classification significantly, and the overall performance is greatly influenced by feature selection (the out-of-bag error rate in the RF algorithm is 7.54% for the integrated DEM method in comparison with 12.70% for the only-optical images method). The integrated use of spectral imagery and multitemporal DEMs reveals that the identified mining area is about 1100 km2 in the study area and period, and the topographic changes of opencast mining in terms of elevation difference is between −258 and 162 m. The results show that the method can map the locations and extents of mining areas automatically from spectral and DEM data and can potentially be applied to larger areas.

Composite Machine Learning Algorithm for Material Sourcing.

This study developed a composite machine learning algorithm for attribution of materials of forensic interest (like ammonium nitrate) to original sources. k-nearest neighbor and random forest models were used for source elimination and classification, respectively, in a two-step, composite algorithm based on particle color, size/shape, and trace element concentration features. Novel approaches for simulation to supplement within-source reference features based on empirically measured multi-lot analyses, an improved hold-one-lot-out method for cross-validation, an assessment of the likelihood of the presence of a reference sample, fusion of the source probabilities from the respective classification models, and the calculation of metrics for assessing ensemble sourcing performance are described. Excellent sourcing predictions were obtained; the sourcing algorithm identified the correct source as the top choice 89% of the time, and the correct source was identified to be an average of 2.7 times more likely than the most likely incorrect source.

Key Predistribution Schemes Based on Orthogonal Arrays with Unique Hamming Distance Distribution

With the deep study of the Hamming distances of orthogonal arrays (OAs), the application of OAs has penetrated into many fields, one of which is to construct the key predistribution schemes (KPSs) for distributed sensor networks. In this paper, we define the Hamming distance distribution (HDD) of an OA and its uniqueness. Furthermore, we present some OAs with unique HDD. In KPSs based on these OAs, the calculations of metrics for evaluating connectivity and resilience can be simplified. We also illustrate that KPSs based on them have a wider application and better connectivity and resilience than the existing ones.

MOAManager: A tool to support data stream experiments

SummaryThis short communication describes Massive Online Analysis Manager Hypertext Preprocessor framework (MOAManager), an open‐source web tool that assists in the creation, execution, extraction, and formatting of experiments in online environments using the MOA framework. MOAManager also brings together a set of features for data analysis, including the calculation of metrics and statistical tests for performance evaluation. The purpose of the tool is to provide a structure that automates several repetitive experimental steps, helping the users to customize, run, and analyze the experiments quickly and reliably, enabling gains in productivity.

Innovative Web Service Grammar for Streaming Computing in Real-Time Technology

The purpose of this work is to develop a UJSON grammar for the distributed system in Telecommunication and sensor network technology. Execute continuous requests on JSON streaming data based on advanced technologies for parallel streaming computing, suitable for solving analytic problems and calculation of metrics in real-time. The developed UJSON grammars in this research work designed to filtering event flow, building an event flow as a query result, grouping and aggregation of events, and creating window semantics. For testing the proposed work, several queries were selected that implement aggregation with different types of semantic windows (Steps, Slides). Testing was done locally and on commercial hypermarket clusters. It was used 4 types of configurations 2, 4, 8, and 16 computing nodes. Based on the obtained results, scalability is noticeable with an increase in the number of nodes. The updated functions of the proposed UJSON could improve the construction of parallel flow systems and data processing. The developed approach based on modern and advanced parallel flow technologies for output calculations considering the pros and cons of various approaches found in the current era.

Practical Operating Theater Management: Measuring and Improving Performance and Patient Experience

Because most anesthesiologists work in the operating room setting, anesthesiologists are involved with the management of the operating room suite (or “theater”). Even if they are not responsible for the management, anesthesiologists still want to understand the decision-making process and metrics that affect their daily schedule and duties. In the United States, anesthesiologists can attend in-person conferences and seminars on leadership, practice management, and operating room management offered by national associations, online webinars and resources, and textbooks. Although these offerings will give anesthesiologists groundwork for calculations of metrics, e.g., productivity and efficiency, an in-depth discussion is not done.In contrast, Practical Operating Theater Management: Measuring and Improving Performance and Patient Experience provides the reader in-depth materials on data-driven metrics, including operating room efficiency, productivity, utilization, and scheduling. The book purposely is designed not to cover leadership or management styles but focuses on collecting and employing operating room data in a manner that is practical and applicable.The book has two functional sections. The first includes an introduction and eight chapters that cover the terms and principal content, as well as efficiency, productivity, scheduling, planning, staffing and contracts, operating room finances, and preoperative patient preparation. The second section contains five chapters examining operating room management in different countries, including Japan, The Netherlands, Switzerland, Australia, and the United States. Chapter 14 then covers operating room safety, and chapter 15 (the last) provides an overview of the book by a contributor.Some of the topics discussed include the different formats used to manage surgical block times, as well the importance of normalizing terms and definitions so the collected data can be reported, analyzed, and acted upon effectively. Among the data that proves useful to collect is operating room capacity, demand by surgeons, utilization rate, overruns, cancellation rate, start times, and turnover times, with some of these bundled into key performance indicators. Of these, efficiency (as defined in chapter 2), on-time start, and turnover times are considered fundamental.Chapter 2 is central to the book, and in it the author cautions that the much-used and maligned measurement of on-time starts or cancellation rates by themselves are a poor measure of overall operating room efficiency. Efficiency as a measurement is clearly defined in a mathematical formula, and the manner in which operating room management decisions affect it is discussed in detail. Subsequent chapters cover measures of productivity (chapter 3) and strategies for scheduling (chapter 4), with an emphasis on maintaining and utilizing a real-time database of facility-specific surgical times, capacity planning of schedules, and add-on operating room capacity (chapter 5). Operating room staff contracts and the prominent role of staffing in providing the capacity is covered in chapter 6. Chapters 7 and 8 cover operating room finances and preoperative patient preparation, respectively.Although the book’s editor and major contributors are from the United Kingdom, the concepts are applicable to operating room management in the United States as well as other countries. In fact, the latter half of the book explores the similarities and differences in operating room management in different countries, including New Zealand, Japan, The Netherlands, Switzerland, and the United States. It is amazing that anesthesiologists from many different countries face similar challenges.For data-driven metrics, it is not surprising that the book relies on a mathematical approach to data. This math-heavy approach would be more appealing to business-trained operating room managers rather than physicians, although the author did attempt to make it more accessible by incorporating these formulas into Excel spreadsheets. We believe anyone interested in implementing data-driven decision-making processes will be able to follow the mathematical progression that occurs in the first half of the book.Overall, this book is a useful resource to anesthesiologists, operating room managers, and financial analysts on the topics of data-driven metrics. It provides a unique educational resource for those who are new to the topic of operating room efficiency, utilization, and productivity. For those who have been working with these concepts, the book provides a resource to reexamine our formulas with an international perspective.

RDI Calculator: An Analysis Tool to Assess RNA Distributions in Cells

Localization of RNAs to various subcellular destinations has emerged as a widely used mechanism that regulates a large proportion of transcripts in polarized cells. A number of methodologies have been developed that allow detection and imaging of RNAs at single-molecule resolution. However, methodologies to quantitatively describe RNA distributions are limited. Such approaches usually rely on the identification of cytoplasmic and nuclear boundaries which are used as reference points. Here, we describe an automated, interactive image analysis program that facilitates the accurate generation of cellular outlines from single cells and the subsequent calculation of metrics that quantify how a population of RNA molecules is distributed in the cell cytoplasm. We apply this analysis to mRNAs in mouse and human cells to demonstrate how these metrics can highlight differences in the distribution patterns of distinct RNA species. We further discuss considerations for the practical use of this tool. This program provides a way to facilitate and expedite the analysis of subcellular RNA localization for mechanistic and functional studies.

Development of the approach for ranking academic institutions based on scientific activity

The subject of the paper is the scientometric data of information-analytical systems. The purpose of this paper is to analyze of existing methods for assessing academic institutions based on scientific activities and develop the approach to ranking the academic institutions using the science data of the Web of Science Core Collection (WoS CC) and Scopus, according to the peculiarities of the evaluated objects. Results. Academic rankings are an integral part of modern methods of evaluating scientific activity. Their results are used by agencies to manage the quality of activities, based on which the academic organization may receive certain preferences: funding, students, post-graduate students, research and teaching staff, academic reputation and others. Improving methods for assessing scientific activity is an urgent task. The rating assessment must be objective. On that condition, the institution may schedule appropriate measures to improve the quality of educational and scientific activities, which ensures better performance. The paper proposes the approach to the ranking of academic institutions based on bibliometric methods according to their limitations and peculiarities of the evaluated objects. Conclusions. The proposed approach provides an increase in the information base for the study of document flows; increases the objectivity of the assessment due to the use of more indicators; takes into account the limitations and disadvantages of bibliometric methods and features of the evaluated objects. The rationing approach metric can be the basis for the general institution rating after revision. The main areas for revision are mandatory accounting of the employee number of an academic institution; calculation of metrics based on the number of original publications.