Analysis Of Series Data Research Articles

Optimizing conformance control for gas injection EOR in unconventional reservoirs

Field observations have shown that interference between wells caused by connected fractures commonly exists in unconventional reservoirs. The well interference effect and conformance issues could lead to minimal enhanced oil recovery response (EOR) in actual operations if they are not properly controlled. A series of data analysis, modeling, and experimental activities were performed in this study to investigate the gas EOR strategies in the Bakken Formation. Employing the embedded discrete fracture modeling technology, a multiple-well, multiple-fracture model was developed to capture the well interference and conformance issues in the Bakken. The model made it possible to investigate the complex flow behavior between wells in the EOR (huff ‘n’ puff) processes. Alternative EOR and conformance control strategies using water and surfactant injections were studied to improve oil production performance based on experimental observations. Results showed that water injection could be used for conformance control in the Bakken because of its relatively low mobility compared to gas; however, water could also block oil flow around the conformance control wells because of the high interfacial tension between oil and water. Adding surfactant to the injection water is more effective for improving gas EOR performance since surfactant reduces the oil–water interfacial tension and contact angle effectively. Up to 9.4% more oil could be produced from the huff ‘n’ puff wells in 2 years of EOR operations when rich gas was injected at only 3 MMscf/d with 6000 psi of surfactant injection in the offset wells for conformance control.

Rancang Bangun Aplikasi Input Data Analisa Tandan Untuk Pemilihan Pohon Induk di PT. Palma Inti Lestari (PT. PIL)

The palm plantation is a major commodity in the Riau province where PT. Palma Inti Lestari (PT. PIL) take a role as a production unit of palm oil sprouts. Sprouts produced by PT. PIL have gone through the research and testing phase, first. The best quality sprouts come from the best quality parent tree. To get the parent tree with the best quality, then researched the palm oil fruit from different palm trees in one month. In determining the best quality parent tree, determined by lab officials through a series of data analysis. The data is oil content data, thin shell, big fruit, And that's a lot of credit. It replicates the data from this research as well (thousand). Right now, the research records are still manual, where data from the field is input to the computer using Microsoft Excel. Given the amount of research data that should be inserted one by one into the excel table, with a storage system done only by stand alone computer, causing a riot/probably an error in input data. As one solution resolves error in input data with resource state in the field, then an application is created to facilitate employees as operators in the input data of cluster analysis that will later be selected to make parent trees in producing quality sprouts. This data input application is designed using UML and built using VBA that supports Microsoft Access Applications

Sequential Clustering and Classification Approach to Analyze Sales Performance of Retail Stores Based on Point-of-Sale Data

Point-of-Sale (POS) data analysis is usually used to explore sales performance in business commence. This manuscript aims to combine unsupervised clustering and supervised classification methods in an integrated data analysis framework to analyze the real-world POS data. Clustering method, which is performed on sales dataset, is used to cluster the stores into several groups. The clustering results, data labels, are then combined with other information in store features dataset as the inputs of the classification model which classifies the clustering labels by using store features dataset. Non-dominated sorting generic algorithm-II (NSGA-II) is applied in the framework to employ the multi-objective of clustering and classification. The experimental case study shows clustering results can reveal the hidden structure of sales performance of retail stores while classification can reveal the major factors that effect to the sales performance under different group of retail stores. The correlations between sales clusters and the store information can be obtained sequentially under a series of data analysis with the proposed framework.

OUTLIER AND HOMOGENEITY ANALYSIS OF EXTREME RAINFALL SERIES IN KANO, NIGERIA

Data preparation is one of the most important steps in the field of hydrology since the results of any research depend on whether the input data were reliable and rightly collected or not. Reliability and quality of long-term rainfall data are required before carrying out any study in hydrology. For this reason, outlier identification techniques and homogeneity tests have proved helpful. This study aimed at carrying out outliers and homogeneity analysis of extreme rainfall data series for the Kano rainfall gauging station. XLSTAT, 2019 was used to identify outliers through Grubb’s test for outliers/two-tailed test and Dixon test for outliers/two-tailed statistic test and Standard Normal Homogeneity Test (SNHT), Buishand Range (BR) Test, Pettitt Test, and Von Neumann Ratio (VNR) Test were used for homogeneity analysis. Four outliers were identified and treated accordingly. The results of homogeneity tests showed that the maximum daily rainfall data of the Kano gauging station is homogenous and classified as useful. The maximum daily rainfall data of Kano station can be used for any study in water resources and environmental engineerings, such as in Development of Intensity Duration Frequency (IDF) Curves and Rainfall-Runoff Simulations.Keywords: Outliers test, homogeneity tests, rainfall data, XLSTAT 2019

Relevance of speaking skills with improving digital literacy skills

The author believes that learning English, especially speaking skills, is closely related to the mastery of digital literacy skills among students at schools and universities. To prove the assumptions and beliefs of the authors of this study, take a look at some of the data that has been published in various journals, books, and proceedings, as well as other internet data sources. Furthermore, to make it easier for us to answer the questions in this review, we have carried out a series of data analyses and studies by incorporating a coding system and in-depth evaluation and interpretation so that we can derive findings in response to these questions. Study the questions on the basis that, they are valid and reliable. For example, we visited Taylor and Francis Elsevier publications, Google book publications, academic databases, and domestic publication journals. After a series of criticisms of the data and discussion of the findings, we can finally say that there is strong evidence that there is a relevance between successful mastery of speaking skills and digital literacy skills among students. So with these results, we hope that these findings can be input in studies of the success of learning English.

Does the pre-operative buccal soft tissue level at teeth or gingival phenotype dictate the aesthetic outcome after flapless immediate implant placement and provisionalization? Analysis of a prospective clinical case series

BackgroundImmediate implant placement (IIP) often is related to mid-buccal recession in literature. To draw conclusions about the behavior of the soft tissues following IIP, pre-operative aesthetic measurements have to be taken into account. The aim of analysis of these prospective clinical case series data was to elucidate whether the pre-operative buccal soft tissue level (STL) or gingival phenotype influence the 1-year pink aesthetic outcome after performing flapless immediate implant placement and provisionalization (FIIPP) maxillary incisor cases.Materials and methodsIn 97 patients, a maxillary incisor was replaced performing FIIPP. STL and phenotype were analyzed on light-photographs made pre-operatively (T0), direct post-operatively (T1), after placement of the permanent crown (T2), and 1 year post-operatively (T3). To investigate if a pre-operative buccal soft tissue deficiency or excess influenced the total pink esthetic score (total-PES) per patient at T3, PES-3 was modified by adding a minus (“−”) or plus (“+”) in case of a STL-deficiency or excess, respectively.ResultsPre-operatively, 40% of the cases showed a mid-buccal recession (STL-deficiency), 19% STL-excess, while in 41% an equal level in comparison with the contra-lateral tooth was observed (STL-neutral). One year post-operatively, 79% (31/39) of the recession cases showed soft tissue gain, while STL-excess cases showed the highest rate of soft tissue reduction (94%; 17/18). This resulted in a decrease of soft tissue recessions and excesses (to 26% and 4%, respectively), and an increase of ideal STL (PES-3-score 2) to 70%. The 1-year aesthetic outcome was not statistically different (p = 0.577) between patients with a pre-operative soft tissue recession (mean T3 total-PES = 12.18) or STL excess (mean T3 total-PES = 11.94). Of the total population, 71 patients with a thin, and 26 with a thick phenotype were evaluated. No statistical difference (p = 0.08) was present in aesthetic outcome between the two phenotypes (thin mean T3 total-PES = 12.30, thick mean T3 total-PES = 11.65).ConclusionRegardless of phenotype, preoperative soft tissue recession, or excess, comparable high aesthetic outcomes were achieved 1 year post-operatively.Trial registrationEthical approval was obtained and registered on 20 October 2015 (NTR5583/NL4170).

African American adolescents intentions to have sex: the influences of youth assets and knowledge of HIV-related sexual risk behaviors

ABSTRACT This cross-sectional study sought to identify factors associated with sexual intentions among a sample of 252 African American high school adolescents who participated in a teen pregnancy prevention program in a large urban city. Participants completed surveys that included measures of youth assets and knowledge of HIV-related sexual risk behaviors. A series of data analyses included descriptive statistical analyses, t-tests, chi-square, and ordinal regression. Study results demonstrate that older age, male gender, and lower levels of youth assets predicted intentions to have sex in the future. Findings also suggest youth assets may serve as a protective factor against the transmission of HIV for African American adolescents in the context of theory regarding intentions to have sex. Surprisingly, more accurate knowledge about HIV-related sexual risk behaviors was associated with intentions to engage in sexual intercourse within the next six months, calling into question subjects’ confidence in or perceived self-efficacy about safely engaging in sexual activity.

Fast data series indexing for in-memory data

Data series similarity search is a core operation for several data series analysis applications across many different domains. However, the state-of-the-art techniques fail to deliver the time performance required for interactive exploration, or analysis of large data series collections. In this work, we propose MESSI, the first data series index designed for in-memory operation on modern hardware. Our index takes advantage of the modern hardware parallelization opportunities (i.e., SIMD instructions, multi-socket and multi-core architectures), in order to accelerate both index construction and similarity search processing times. Moreover, it benefits from a careful design in the setup and coordination of the parallel workers and data structures, so that it maximizes its performance for in-memory operations. MESSI supports similarity search using both the Euclidean and dynamic time warping (DTW) distances. Our experiments with synthetic and real datasets demonstrate that overall MESSI is up to 4x faster at index construction and up to 11x faster at query answering than the state-of-the-art parallel approach. MESSI is the first to answer exact similarity search queries on 100GB datasets in \(\sim \)50 ms (30–75 ms across diverse datasets), which enables real-time, interactive data exploration on very large data series collections.

Managing Vineyard Topography and Seasonal Variability to Improve Grape Quality and Vineyard Sustainability

Topography may induce variability in meteorological conditions at the meso-scale level and could influence grape quality. Understanding the impact of topography on grape ripening allows for the development of sustainable management practices that include topographical influences in their consideration. This is also important for applying proactive strategies able to counter the expected changes of climate. This study was conducted on cv. Nebbiolo vineyards in North-West Italy. The topographic traits were performed in 17 vineyards within the region, which had previously been identified as belonging to different terroir units. An analysis of historical meteorological data series was also carried out to characterize the units from the meteorological point of view. The grape composition was investigated during 2012 and 2013. Based on the topography traits, a Cluster Analysis classified the 17 vineyards into four groups. Differences among groups mainly concerned insolation and heat accumulation. Topography influenced the individual components of grape quality differently depending on the seasonal weather trend. Interactions between topography and vintage were observed for a few parameters. Better understanding the grapevine reaction to external factors/site characteristics can allow for improved site and season-specific management decision making and can contribute to improving vineyard sustainability while maintaining winery objectives and wine typicity.

THE ROLE OF ENVIRONMENTAL TAXES IN ENSURING THE FINANCIAL CAPACITY OF LOCAL BUDGETS

Considering active implementation of the reform of financial decentralization in Ukraine, one of the key tasks facing the government authorities at various levels is to achieve balanced development of local budgets and ensure financial self-sufficiency of local governments. The solution of this problem is provided by expanding the sources of revenue base of local budgets (for example, crediting to the relevant local budgets excise tax from entities engaged in retail trade in excisable goods, increasing the share of environmental tax redistributed to lower budgets, etc.). At the same time, an important task that remains relevant even after the first and second stages of decentralization reform is to assess its real progress, especially in the context of identifying the impact of expanding sources of revenue on local budgets on their financial capacity. The aim of the study is to analyze the role of environmental taxes in ensuring the financial capacity of local budgets. The implementation of the task in the article is based on the use of statistical methods of data series analysis, in particular, comparative, discriminant and structural analysis. To fulfill this task it is analyzed in the article the share of environmental tax in the structure of total revenues and tax revenues of state and local budgets of Ukraine for 2011-2020, their absolute measure and chain growth rate. The analysis showed that the environmental tax is characterized by a low level of fiscal efficiency for both state and local budgets. In particular, the share of environmental tax in tax revenues for 2011-2020 ranges from 0.27% to 1.29%, while the average value is 0.52% (the highest share of environmental tax in tax revenues of the State budget was in 2013 and 2014, the lowest - in 2017). At the same time, the environmental tax plays a slightly higher fiscal value for local budgets: the share of the environmental tax in local budget revenues in 2011–2020 averaged 0.58%, and in tax revenues - 1.44%. The analysis of the structure of tax revenues of local budgets showed the growing importance of local taxes and fees and domestic taxes on goods and services after the reform of financial decentralization. In general, the analysis shows that the reform of financial decentralization has led to a transformation of the structure of tax revenues and the growing importance of certain groups of taxes and fees, whose role was much smaller in the pre-reform period.

Institutional Quality and Shadow Economy: An Investment Potential Evaluation Model

The article summarizes some arguments as regards the scientific challenge on improving approaches to evaluating the country’s investment potential. The main objective of the research is to identify the features and perspectives of applying the variables such as the shadow economy and the integrated institutional quality index into a model evaluating the country’s investment potential. To solve this task, systematization of the related theoretical and methodological materials has been done. The methodological tools of the research are carried out in the following logical sequence: systematization of existing statistical methods for estimating the shadow economy; time data series analysis; and regression analysis. The scope of the shadow economy could be estimated as a dependent variable, with both its determinants and indicators detected and measured. The macro methods, such as Multiple Indicators Multiple Causes (MIMIC) are suitable approaches from an econometric standpoint to evaluate the shadow economy. Institutional quality is crucially an important variable for empirical studies related to evaluating the country’s investment potential. The proposed approach considers significance and direction of the six Worldwide Government Indicators’ (WGI) impact on foreign direct investment net inflow, eliminating the issue of their multicollinearity. However, political instability and high frequency of foreign and domestic policy changes during the last decades distort statistical significance of the results obtained. FDI inflow, as well as the quality of governance, and the shadow economy, is influenced by many other factors, both internal and external, so to build a qualitative model for evaluating the country’s investment potential of the national economy it is necessary to expand the set of factors for analysis. The results of the research can be useful for a more accurate investment potential evaluation on the macroeconomic level, and forecasting foreign direct investment inflows for the following time periods.

Performance analysis of numerical methods for determining Weibull distribution parameters applied to wind speed in Mato Grosso do Sul, Brazil

Brazil is one of the countries that invests the most in renewable energy generation. The share of wind power sources in the Brazilian Electricity Matrix rose from 0.9% in 2012 to 7.6% in 2018. The wind resource assessment is a crucial step in planning a wind energy project. Weibull distribution function is used to determine wind power potential for the investigated site and the distribution parameters are estimated by numerical methods. This study focus on the similarity and analyses of hourly wind speed data series. In this study, six numerical methods (Graphical Method, Maximum Likelihood Method, Modified Maximum Likelihood Method, Moment Method, Empirical Method and Power Density Method) are applied for estimating Weibull distribution parameters in 27 stations in the state of Mato Grosso do Sul, Brazil. The stations were grouped according to the similarity of their data series, and for each group the data series were separated into data series for calibration and data series for the accuracy analysis of the methods. The accuracy of the methods was evaluated using three different statistical analysis techniques. The Maximum Likelihood Method and the Modified Maximum Likelihood Method were the best methods for analyzing most of the data series in the stations.

Climatic and Anthropogenic Impacts on Environmental Conditions and Phytoplankton Community in the Gulf of Trieste (Northern Adriatic Sea)

During the last century, human activities have exerted an increasing pressure on coastal ecosystems, primarily inducing their eutrophication, with a more recent partial mitigation of this phenomenon where improvements of environmental management practices were adopted. However, a reanalysis of the pressures on coastal zones and surrounding drainage basins is needed because of the alterations induced nowadays by the climate changes. A comparative analysis of long-term oceanographic and environmental data series (1986–2018) was performed, in order to highlight the effects of anthropogenic and climatic disturbances on the phytoplankton community in the Gulf of Trieste (GoT). After the 1980s, the decline in phytoplankton abundance was matched to increasing periods of low runoff, an overall deficit of the precipitation and to a decrease in phosphate availability in the coastal waters (−0.003 µmol L−1 yr−1), even in the presence of large riverine inputs of nitrogen and silicates. This trend of oligotrophication was reversed in the 2010s by the beginning of a new and unexpected phase of climatic instability, which also caused changes of the composition and seasonal cycle of the phytoplankton community. Beyond the management of nutrient loads, it was shown that climatic drivers such as seawater warming, precipitation and wind regime affect both nutrient balance and phytoplankton community in this coastal zone.

Searching for Supersymmetry at LHC Using the Complex-Network-Based Method of the Three-Dimensional Visibility-Graph

For the last several decades, there has been tremendous interest in search for Supersymmetry (SUSY) in the area of high energy physics. At Large Hadron Collider (LHC), there have been continuous searches for SUSY for prompt and non-prompt, for particle R-parity conserving and R-parity violating generation and decays. The limits obtained from these experiments and analyses for detection of the signatures of supersymmetric particles (LSP), revealed greater possibilities of such experiments in the collider. However, these signatures are usually derived under the assumption of bit optimistic conditions of the decaying process of sparticles to the final states. Moreover, SUSY might have been in a disguised state at lower mass-scales as a result of difficult and challenging mass spectra and mixed modes of decays. In this investigation, a novel method of 3-dimensional (3D) Visibility-Graph Analysis is proposed. This is an extension of Visibility Graph analysis of data series to perform the scaling analysis for 3D space. The experimental data spaces analyzed are made up of the component-space (in the X,Y and Z coordinates) of transverse momentum (pT) values taken out from 4-momenta of the signatures of the final state of the pair of mega-jets extracted from the multiJet primary pp collision data from Run B of 2010 at 7 TeV which was used for the search of SUSY using razor filter. The symmetry scaling and the inherent scaling behavior, scale-freeness of multi-particle production process is studied in terms of 3D Power-of-Scale-freeness-of-Visibility-Graph (3D-PSVG) extracted from the 3D Visibility Graphs constructed out of the experimental data spaces. The signature of SUSY may be identified by analyzing the scaling behavior and long-range correlation inherent in the 3D space made up of signatures of final state of multi-particles produced in the pp collision at 7 TeV, for the analysis of SUSY, which the conventional method of analyzing the spectrum of invariant mass or pT may miss.

Estimation of a Suitable Range of Discharges for the Development of Instream Flow Recommendations

Hydrological variability is of great importance for water resources management. Regardless of how rivers are individually managed, numerous research studies have concluded that aquatic organisms are highly dependent on flow regime variability. Nevertheless, natural streamflow regimes are being altered due to human-induced pressures and climate change/variability, and sufficient biological information in not incorporated in efforts to minimize these effects. Thus, there is an urgent need to develop sustainable environmental flow management guidelines to manage the risk associated with alterations to the flow regime particularly in areas where flow-ecology relationships have not been well studied. This study focuses on a stream with high natural flow regime variability, typical in Mediterranean countries. The major finding of this work is that the estimated Suitable Range of Discharges (SRD) could better address environmental water requirements, rather than simply allocating single value minimum ecological flows. SRD was estimated using advocate statistical analysis of hydrological data series, coupled with habitat suitability models to balance the trade-offs between natural flow variability and human water needs. Combination of the aforementioned approaches was made using the West Balkan trout as a biological component which is a very important species for the quantification of environmental flows. Overall implementation of SRD during dry season is likely to provide large habitat areas for 58 to 67% of the time for the small-size fish and 35 to 55% of the time for the large-size West Balkan trout, according to the Weighted Usable Area0.5 threshold index.

Evaluation of the Pulse wave in the face for the patients with rotary blood pump (RP) in the Outpatient clinic.

Rotary blood pump (RP) is one of the most important devices in the treatment of profound heart failure and is known to reduce the pulse in the blood pressure waveform, especially when it is used for axial flow. In an outpatient clinic, checking the pulse of a patient implanted with an RP can help diagnose the patient's condition. For that purpose, animal experiments with healthy adult goats implanted with the EVAHEART system were carried out after obtaining ethical committee approval. Visual imaging of the goats' faces was recorded using a video camera. The pulse waves were clearly recorded using the newly developed pulse diagnosis system with video imaging and compared with laser Doppler flowmeter and time series data. Spectral analysis of the time series data showed the usefulness of video imaging from outside the body. Clinical applications are planned, and this newly developed method is expected to be a useful diagnostic method for evaluating the cardiac function in patients implanted with RPs in the future.

Hydrochemical evaluation of water resources and human impacts on\xa0an urban karst system, Jordan

Urban karst aquifers are threatened by anthropogenic activities, especially in semiarid developing countries. Recent water-sampling campaigns assessed the extent of groundwater-quality impairment in the Wadi Shueib in Jordan by a comprehensive hydrogeological and hydrochemical characterization of groundwater, wastewater, and imported water with its endmembers Lake Tiberias, Yarmouk River and Mukheiba wellfield. The results of a ternary mixing model with the mass ratios of Cl−/Br− and Ca2+/Mg2+ indicate that Lake Tiberias and Yarmouk River provide most of the imported water at the time of sampling in 2017 and Mukheiba wellfield provided minor amounts. The similarity in seasonal variations of Br− concentrations in the springs and the imported water revealed that imported water has generally a greater impact on groundwater than wastewater. However, the Br− concentrations also showed that the spatial wastewater impact is more visible towards urbanized areas due to increased infiltration of pollutants. The analysis of historical data series demonstrated the long-term urban impact on groundwater by an electrical conductivity increase over several decades, particularly since the mid-1990s, which is related to a doubling of Jordan’s population since that time and the associated urban growth. In this context, increased chloride and sulfate concentrations are noticeable due to the increased impact of more highly mineralized imported water and wastewater and decreasing recharge of low-mineralized rainwater. This study showed the hydrochemical differences in the Wadi Shueib groundwater system and serves as an example for the spatial and long-term response of karst aquifers to anthropogenic, seasonally variable input of imported water and wastewater.

Comparing abnormalities in onshore and offshore vertical wind profiles

Abstract. Understanding the vertical wind profile is paramount for design and operation of wind turbines. It is needed not only for extrapolation of the wind velocity to hub height but also for structural load calculations, to name the most obvious issues. As wind turbines grow in size and development transitions offshore, issues such as shallow surface layers, low-level jets (LLJs) and internal boundary layers (IBLs) are raising questions concerning the applicability of the commonly used Monin–Obukhov similarity theory to accurately describe the vertical wind development at modern wind turbine hub heights. In this study the 10 min averaged vertical wind profile up to a minimum elevation of 100 m is analyzed through measurements collected from seven sites which represent a span of conditions. Three sites are located offshore in the North Sea and Baltic Sea (FINO1, FINO2 and FINO3) with varying fetch, two onshore by the Norwegian coast (Frøya and Valsneset), one further onshore by the Danish coast (Høvsøre), and one inland at a forested site in Sweden (Ryningsnäs). Through analysis of data series ranging from 8 months to several years depending on the site, the wind profile has been quantitatively categorized according to the number of exhibited local maxima which is not possible within the Monin–Obukhov similarity theory. The results reveal that the occurrence of local maxima is higher at sites of low surface roughness and a high prevalence of unstable atmospheric conditions, causing up to 17 % severely inflected abnormal profiles at the most exposed offshore site, which decreases as the location transitions from offshore to coastal to further inland and is lowest at the forested site. The results indicate that issues in predicting the vertical wind profile are most prevalent offshore, where very stable inflections cause severe deviations which may be related to an offshore internal boundary layer. These findings suggest that there is evident need of an improved vertical wind profile description in order to improve the accuracy of power predictions and load calculations, especially at offshore and coastal sites.

Identifying early defects of wind turbine based on SCADA data and dynamical network marker

Defects Identification is of great significance to prevent wind turbines (WTs) accidents and improve its operation reliability, and it keeps challenging due to the complex relationship between internal faults and external observed data. A new method to identify early defects of WTs is presented based on Dynamical Network Marker (DNM) by adopting only the data of supervisory control and data acquisition (SCADA). In the presented method, WT is mapped into a multi-node complex network according to the corresponding relationship between the internal structure topology of WT and the monitoring variables of its SCADA system. Then the dominant nodes in the network under different states are screened out through the correlation and cross-correlation analysis of de-nosed SCADA monitoring data series and prediction data series to form a key subnetwork, and the dynamical network marker (DNM) is constructed as warning signal of defects of WT. The proposed method is tested with the SCADA data of a WT with known faults. The results illustrate that the proposed method can not only give an early warning signal when WT under defect state but also further determine the defect location. Moreever, the proposed method only needs the SCADA monitoring data of WT itself, which is convenient and easy to be popularized.

Assessment of the Accuracy of Analyzers for Automatic Determination of PM10 and PM2.5 Particulate Matter in Ambient Air

The paper presents the test results regarding the evaluation of the accuracy of the PM2.5 and PM10 particulate matter concentration measurement performed with the uRADMonitor A3 fixed air quality monitoring station produced by SC MAGNASCI SRL. The procedure involves the calculation of the accuracy elements: trueness and precision, based on the experimental data obtained by measuring the concentration of particulate matter using the tested analysers in parallel with the reference method, SR EN 12341: 2014, and analysis of data series by Pearson correlation and linear regression.